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A discrete memoryless generalized multiple access channel (GMAC) with confidential messages is studied, where two users attempt to transmit common information to a destination and each user also has private (confidential) information intended for the destination. The two users are allowed to receive channel outputs, and hence may obtain the confidential information sent by each other from channel outputs they receive. However, each user views the other user as a wire-tapper, and wishes to keep its confidential information as secret as possible from the other user. The level of secrecy of the confidential information is measured by the equivocation rate, i.e., the entropy rate of the confidential information conditioned on channel outputs at the wire-tapper. The performance measure of interest for the GMAC with confidential messages is the rate-equivocation tuple that includes the common rate, two private rates and two equivocation rates as components. The set that includes all these achievable rate-equivocation tuples is referred to as the capacity-equivocation region. The GMAC with one confidential message set is first studied, where only one user (user 1) has private (confidential) information for the destination. Inner and outer bounds on the capacity-equivocation region are derived, and the capacity-equivocation are established for some classes of channels including the Gaussian GMAC. Furthermore, the secrecy capacity region is established, which is the set of all achievable rates with user 2 being perfectly ignorant of confidential messages of user 1. For the GMAC with two confidential message sets, where both users have confidential messages for the destination, an inner bound on the capacity-equivocation region is obtained. | Generalized Multiple Access Channels with Confidential Messages | 7,200 |
The capacity regions are investigated for two relay broadcast channels (RBCs), where relay links are incorporated into standard two-user broadcast channels to support user cooperation. In the first channel, the Partially Cooperative Relay Broadcast Channel, only one user in the system can act as a relay and transmit to the other user through a relay link. An achievable rate region is derived based on the relay using the decode-and-forward scheme. An outer bound on the capacity region is derived and is shown to be tighter than the cut-set bound. For the special case where the Partially Cooperative RBC is degraded, the achievable rate region is shown to be tight and provides the capacity region. Gaussian Partially Cooperative RBCs and Partially Cooperative RBCs with feedback are further studied. In the second channel model being studied in the paper, the Fully Cooperative Relay Broadcast Channel, both users can act as relay nodes and transmit to each other through relay links. This is a more general model than the Partially Cooperative RBC. All the results for Partially Cooperative RBCs are correspondingly generalized to the Fully Cooperative RBCs. It is further shown that the AWGN Fully Cooperative RBC has a larger achievable rate region than the AWGN Partially Cooperative RBC. The results illustrate that relaying and user cooperation are powerful techniques in improving the capacity of broadcast channels. | Cooperative Relay Broadcast Channels | 7,201 |
We consider the multiple-access communication problem in a distributed setting for both the additive white Gaussian noise channel and the discrete memoryless channel. We propose a scheme called Distributed Rate Splitting to achieve the optimal rates allowed by information theory in a distributed manner. In this scheme, each real user creates a number of virtual users via a power/rate splitting mechanism in the M-user Gaussian channel or via a random switching mechanism in the M-user discrete memoryless channel. At the receiver, all virtual users are successively decoded. Compared with other multiple-access techniques, Distributed Rate Splitting can be implemented with lower complexity and less coordination. Furthermore, in a symmetric setting, we show that the rate tuple achieved by this scheme converges to the maximum equal rate point allowed by the information-theoretic bound as the number of virtual users per real user tends to infinity. When the capacity regions are asymmetric, we show that a point on the dominant face can be achieved asymptotically. Finally, when there is an unequal number of virtual users per real user, we show that differential user rate requirements can be accommodated in a distributed fashion. | Asymptotically Optimal Multiple-access Communication via Distributed
Rate Splitting | 7,202 |
The problem of finding the shortest linear shift-register capable of generating t finite length sequences over some field F is considered. A similar problem was already addressed by Feng and Tzeng. They presented an iterative algorithm for solving this multi-sequence shift-register synthesis problem, which can be considered as generalization of the well known Berlekamp-Massey algorithm. The Feng-Tzeng algorithm works indeed, if all t sequences have the same length. This paper focuses on multi-sequence shift-register synthesis for generating sequences of varying length. It is exposed, that the Feng-Tzeng algorithm does not always give the correct solution in this case. A modified algorithm is proposed and formally proved, which overcomes this problem. | Linear Shift-Register Synthesis for Multiple Sequences of Varying Length | 7,203 |
Tight bounds on the block entropy of patterns of sequences generated by independent and identically distributed (i.i.d.) sources are derived. A pattern of a sequence is a sequence of integer indices with each index representing the order of first occurrence of the respective symbol in the original sequence. Since a pattern is the result of data processing on the original sequence, its entropy cannot be larger. Bounds derived here describe the pattern entropy as function of the original i.i.d. source entropy, the alphabet size, the symbol probabilities, and their arrangement in the probability space. Matching upper and lower bounds derived provide a useful tool for very accurate approximations of pattern block entropies for various distributions, and for assessing the decrease of the pattern entropy from that of the original i.i.d. sequence. | Patterns of i.i.d. Sequences and Their Entropy - Part I: General Bounds | 7,204 |
This paper outlines a three-step procedure for determining the low bit error rate performance curve of a wide class of LDPC codes of moderate length. The traditional method to estimate code performance in the higher SNR region is to use a sum of the contributions of the most dominant error events to the probability of error. These dominant error events will be both code and decoder dependent, consisting of low-weight codewords as well as non-codeword events if ML decoding is not used. For even moderate length codes, it is not feasible to find all of these dominant error events with a brute force search. The proposed method provides a convenient way to evaluate very low bit error rate performance of an LDPC code without requiring knowledge of the complete error event weight spectrum or resorting to a Monte Carlo simulation. This new method can be applied to various types of decoding such as the full belief propagation version of the message passing algorithm or the commonly used min-sum approximation to belief propagation. The proposed method allows one to efficiently see error performance at bit error rates that were previously out of reach of Monte Carlo methods. This result will provide a solid foundation for the analysis and design of LDPC codes and decoders that are required to provide a guaranteed very low bit error rate performance at certain SNRs. | A General Method for Finding Low Error Rates of LDPC Codes | 7,205 |
A sequential updating scheme (SUS) for belief propagation (BP) decoding of LDPC codes over Galois fields, $GF(q)$, and correlated Markov sources is proposed, and compared with the standard parallel updating scheme (PUS). A thorough experimental study of various transmission settings indicates that the convergence rate, in iterations, of the BP algorithm (and subsequently its complexity) for the SUS is about one half of that for the PUS, independent of the finite field size $q$. Moreover, this 1/2 factor appears regardless of the correlations of the source and the channel's noise model, while the error correction performance remains unchanged. These results may imply on the 'universality' of the one half convergence speed-up of SUS decoding. | Parallel vs. Sequential Belief Propagation Decoding of LDPC Codes over
GF(q) and Markov Sources | 7,206 |
This paper is motivated by a sensor network on a correlated field where nearby sensors share information, and can thus assist rather than interfere with one another. A special class of two-user Gaussian interference channels (IFCs) is considered where one of the two transmitters knows both the messages to be conveyed to the two receivers (called the IFC with degraded message sets). Both achievability and converse arguments are provided for this scenario for a class of discrete memoryless channels with weak interference. For the case of the Gaussian weak interference channel with degraded message sets, optimality of Gaussian inputs is also shown, resulting in the capacity region of this channel. | On the Capacity of Interference Channels with Degraded Message sets | 7,207 |
This paper is motivated by a sensor network on a correlated field where nearby sensors share information, and can thus assist rather than interfere with one another. We consider a special class of two-user Gaussian interference channels (IFCs) where one of the two transmitters knows both the messages to be conveyed to the two receivers. Both achievability and converse arguments are provided for a channel with Gaussian inputs and Gaussian noise when the interference is weaker than the direct link (a so called weak IFC). In general, this region serves as an outer bound on the capacity of weak IFCs with no shared knowledge between transmitters. | On the Capacity of Gaussian Weak Interference Channels with Degraded
Message sets | 7,208 |
The memoryless noncoherent single-input single-output (SISO) Rayleigh-fading channel is considered. Closed-form expressions for the mutual information between the output and the input of this channel when the input magnitude distribution is discrete and restricted to having two mass points are derived, and it is subsequently shown how these expressions can be used to obtain closed-form expressions for the capacity of this channel for signal to noise ratio (SNR) values of up to approximately 0 dB, and a tight capacity lower bound for SNR values between 0 dB and 10 dB. The expressions for the channel capacity and its lower bound are given as functions of a parameter which can be obtained via numerical root-finding algorithms. | On the Capacity and Mutual Information of Memoryless Noncoherent
Rayleigh-Fading Channels | 7,209 |
The problem of discrete universal filtering, in which the components of a discrete signal emitted by an unknown source and corrupted by a known DMC are to be causally estimated, is considered. A family of filters are derived, and are shown to be universally asymptotically optimal in the sense of achieving the optimum filtering performance when the clean signal is stationary, ergodic, and satisfies an additional mild positivity condition. Our schemes are comprised of approximating the noisy signal using a hidden Markov process (HMP) via maximum-likelihood (ML) estimation, followed by the use of the forward recursions for HMP state estimation. It is shown that as the data length increases, and as the number of states in the HMP approximation increases, our family of filters attain the performance of the optimal distribution-dependent filter. | Universal Filtering via Hidden Markov Modeling | 7,210 |
A fading broadcast channel is considered where the transmitter employs two antennas and each of the two receivers employs a single receive antenna. It is demonstrated that even if the realization of the fading is precisely known to the receivers, the high signal-to-noise (SNR) throughput is greatly reduced if, rather than knowing the fading realization \emph{precisely}, the trasmitter only knows the fading realization \emph{approximately}. The results are general and are not limited to memoryless Gaussian fading. | On the Capacity of Fading MIMO Broadcast Channels with Imperfect
Transmitter Side-Information | 7,211 |
A discrete memoryless generalized multiple access channel (GMAC) with confidential messages is studied, where two users attempt to transmit common information to a destination and each user also has private (confidential) information intended for the destination. This channel generalizes the multiple access channel (MAC) in that the two users also receive channel outputs. It is assumed that each user views the other user as a wire-tapper, and wishes to keep its confidential information as secret as possible from the other user. The level of secrecy of the confidential information is measured by the equivocation rate. The performance measure of interest is the rate-equivocation tuple that includes the common rate, two private rates and two equivocation rates as components. The set that includes all achievable rate-equivocation tuples is referred to as the capacity-equivocation region. For the GMAC with one confidential message set, where only one user (user 1) has private (confidential) information for the destination, inner and outer bounds on the capacity-equivocation region are derived. The secrecy capacity region is established, which is the set of all achievable rates with user 2 being perfectly ignorant of confidential messages of user 1. Furthermore, the capacity-equivocation region and the secrecy capacity region are established for the degraded GMAC with one confidential message set. For the GMAC with two confidential message sets, where both users have confidential messages for the destination, inner bounds on the capacity-equivocation region and the secrecy capacity region are obtained. | The Generalized Multiple Access Channel with Confidential Messages | 7,212 |
Assuming iterative decoding for binary erasure channels (BECs), a novel tree-based technique for upper bounding the bit error rates (BERs) of arbitrary, finite low-density parity-check (LDPC) codes is provided and the resulting bound can be evaluated for all operating erasure probabilities, including both the waterfall and the error floor regions. This upper bound can also be viewed as a narrowing search of stopping sets, which is an approach different from the stopping set enumeration used for lower bounding the error floor. When combined with optimal leaf-finding modules, this upper bound is guaranteed to be tight in terms of the asymptotic order. The Boolean framework proposed herein further admits a composite search for even tighter results. For comparison, a refinement of the algorithm is capable of exhausting all stopping sets of size <14 for irregular LDPC codes of length n=500, which requires approximately 1.67*10^25 trials if a brute force approach is taken. These experiments indicate that this upper bound can be used both as an analytical tool and as a deterministic worst-performance (error floor) guarantee, the latter of which is crucial to optimizing LDPC codes for extremely low BER applications, e.g., optical/satellite communications. | Upper Bounding the Performance of Arbitrary Finite LDPC Codes on Binary
Erasure Channels | 7,213 |
In this paper, random coding error exponents and cutoff rate are studied for noncoherent Rician fading channels, where neither the receiver nor the transmitter has channel side information. First, it is assumed that the input is subject only to an average power constraint. In this case, a lower bound to the random coding error exponent is considered and the optimal input achieving this lower bound is shown to have a discrete amplitude and uniform phase. If the input is subject to both average and peak power constraints, it is proven that the optimal input achieving the random coding error exponent has again a discrete nature. Finally, the cutoff rate is analyzed, and the optimality of the single-mass input amplitude distribution in the low-power regime is discussed. | Error Exponents and Cutoff Rate for Noncoherent Rician Fading Channels | 7,214 |
We describe and analyze sparse graphical code constructions for the problems of source coding with decoder side information (the Wyner-Ziv problem), and channel coding with encoder side information (the Gelfand-Pinsker problem). Our approach relies on a combination of low-density parity check (LDPC) codes and low-density generator matrix (LDGM) codes, and produces sparse constructions that are simultaneously good as both source and channel codes. In particular, we prove that under maximum likelihood encoding/decoding, there exist low-density codes (i.e., with finite degrees) from our constructions that can saturate both the Wyner-Ziv and Gelfand-Pinsker bounds. | Low-density constructions can achieve the Wyner-Ziv and Gelfand-Pinsker
bounds | 7,215 |
In this paper, we investigate communication strategies for the multiple access channel with feedback and correlated sources (MACFCS). The MACFCS models a wireless sensor network scenario in which sensors distributed throughout an arbitrary random field collect correlated measurements and transmit them to a common sink. We derive achievable rate regions for the three-node MACFCS. First, we study the strategy when source coding and channel coding are combined, which we term full decoding at sources. Second, we look at several strategies when source coding and channel coding are separated, which we term full decoding at destination. From numerical computations on Gaussian channels, we see that different strategies perform better under certain source correlations and channel setups. | The Multiple Access Channel with Feedback and Correlated Sources | 7,216 |
In this paper, we derive the capacity of a special class of mesh networks. A mesh network is defined as a heterogeneous wireless network in which the transmission among power limited nodes is assisted by powerful relays, which use the same wireless medium. We find the capacity of the mesh network when there is one source, one destination, and multiple relays. We call this channel the single source multiple relay single destination (SSMRSD) mesh network. Our approach is as follows. We first look at an upper bound on the information theoretic capacity of these networks in the Gaussian setting. We then show that the bound is achievable asymptotically using the compress-forward strategy for the multiple relay channel. Theoretically, the results indicate the value of cooperation and the utility of carefully deployed relays in wireless ad-hoc and sensor networks. The capacity characterization quantifies how the relays can be used to either conserve node energy or to increase transmission rate. | The Capacity of the Single Source Multiple Relay Single Destination Mesh
Network | 7,217 |
We present a novel differential space-time modulation (DSTM) scheme that is single-symbol decodable and can provide full transmit diversity. It is the first known singlesymbol- decodable DSTM scheme not based on Orthogonal STBC (O-STBC), and it is constructed based on the recently proposed Minimum-Decoding-Complexity Quasi-Orthogonal Space-Time Block Code (MDC-QOSTBC). We derive the code design criteria and present systematic methodology to find the solution sets. The proposed DSTM scheme can provide higher code rate than DSTM schemes based on O-STBC. Its decoding complexity is also considerably lower than DSTM schemes based on Sp(2) and double-symbol-decodable QOSTBC, with negligible or slight trade-off in decoding error probability performance. | Single-Symbol-Decodable Differential Space-Time Modulation Based on
QO-STBC | 7,218 |
A game-theoretic analysis is used to study the effects of receiver choice on the energy efficiency of multi-hop networks in which the nodes communicate using Direct-Sequence Code Division Multiple Access (DS-CDMA). A Nash equilibrium of the game in which the network nodes can choose their receivers as well as their transmit powers to maximize the total number of bits they transmit per unit of energy is derived. The energy efficiencies resulting from the use of different linear multiuser receivers in this context are compared, looking at both the non-cooperative game and the Pareto optimal solution. For analytical ease, particular attention is paid to asymptotically large networks. Significant gains in energy efficiency are observed when multiuser receivers, particularly the linear minimum mean-square error (MMSE) receiver, are used instead of conventional matched filter receivers. | Energy Efficiency in Multi-hop CDMA Networks: A Game Theoretic Analysis | 7,219 |
The recovery of network structure from experimental data is a basic and fundamental problem. Unfortunately, experimental data often do not directly reveal structure due to inherent limitations such as imprecision in timing or other observation mechanisms. We consider the problem of inferring network structure in the form of a directed graph from co-occurrence observations. Each observation arises from a transmission made over the network and indicates which vertices carry the transmission without explicitly conveying their order in the path. Without order information, there are an exponential number of feasible graphs which agree with the observed data equally well. Yet, the basic physical principles underlying most networks strongly suggest that all feasible graphs are not equally likely. In particular, vertices that co-occur in many observations are probably closely connected. Previous approaches to this problem are based on ad hoc heuristics. We model the experimental observations as independent realizations of a random walk on the underlying graph, subjected to a random permutation which accounts for the lack of order information. Treating the permutations as missing data, we derive an exact expectation-maximization (EM) algorithm for estimating the random walk parameters. For long transmission paths the exact E-step may be computationally intractable, so we also describe an efficient Monte Carlo EM (MCEM) algorithm and derive conditions which ensure convergence of the MCEM algorithm with high probability. Simulations and experiments with Internet measurements demonstrate the promise of this approach. | Network Inference from Co-Occurrences | 7,220 |
An outer bound to the capacity region of the two-receiver discrete memoryless broadcast channel is given. The outer bound is tight for all cases where the capacity region is known. When specialized to the case of no common information, this outer bound is contained in the Korner-Marton outer bound. This containment is shown to be strict for the binary skew-symmetric broadcast channel. Thus, this outer bound is in general tighter than all other known outer bounds on the discrete memoryless broadcast channel. | An outer bound to the capacity region of the broadcast channel | 7,221 |
We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements from an underlying random process, code and transmit those measurement samples to a collector node in a cooperative multiple access channel with imperfect feedback, and reconstruct the entire random process at the collector node. We provide lower and upper bounds for the minimum achievable expected distortion when the underlying random process is Gaussian. In the case where the random process satisfies some general conditions, we evaluate the lower and upper bounds explicitly and show that they are of the same order for a wide range of sum power constraints. Thus, for these random processes, under these sum power constraints, we determine the achievability scheme that is order-optimal, and express the minimum achievable expected distortion as a function of the sum power constraint. | Optimal Distortion-Power Tradeoffs in Gaussian Sensor Networks | 7,222 |
Precoding with block diagonalization is an attractive scheme for approaching sum capacity in multiuser multiple input multiple output (MIMO) broadcast channels. This method requires either global channel state information at every receiver or an additional training phase, which demands additional system planning. In this paper we propose a lattice based multi-user precoder that uses block diagonalization combined with pre-equalization and perturbation for the multiuser MIMO broadcast channel. An achievable sum rate of the proposed scheme is derived and used to show that the proposed technique approaches the achievable sum rate of block diagonalization with water-filling but does not require the additional information at the receiver. Monte Carlo simulations with equal power allocation show that the proposed method provides better bit error rate and diversity performance than block diagonalization with a zero-forcing receiver. Additionally, the proposed method shows similar performance to the maximum likelihood receiver but with much lower receiver complexity. | A Lattice-Based MIMO Broadcast Precoder for Multi-Stream Transmission | 7,223 |
Pseudocodewords of q-ary LDPC codes are examined and the weight of a pseudocodeword on the q-ary symmetric channel is defined. The weight definition of a pseudocodeword on the AWGN channel is also extended to two-dimensional q-ary modulation such as q-PAM and q-PSK. The tree-based lower bounds on the minimum pseudocodeword weight are shown to also hold for q-ary LDPC codes on these channels. | Pseudocodeword weights for non-binary LDPC codes | 7,224 |
The multi-terminal rate-distortion problem has been studied extensively. Notably, among these, Tung and Housewright have provided the best known inner and outer bounds for the rate region under certain distortion constraints. In this paper, we first propose an outer bound for the rate region, and show that it is tighter than the outer bound of Tung and Housewright. Our outer bound involves some $n$-letter Markov chain constraints, which cause computational difficulties. We utilize a necessary condition for the Markov chain constraints to obtain another outer bound, which is represented in terms of some single-letter mutual information expressions evaluated over probability distributions that satisfy some single-letter conditions. | An Outer Bound for the Multi-Terminal Rate-Distortion Region | 7,225 |
In this work we focus on the general relay channel. We investigate the application of estimate-and-forward (EAF) to different scenarios. Specifically, we consider assignments of the auxiliary random variables that always satisfy the feasibility constraints. We first consider the multiple relay channel and obtain an achievable rate without decoding at the relays. We demonstrate the benefits of this result via an explicit discrete memoryless multiple relay scenario where multi-relay EAF is superior to multi-relay decode-and-forward (DAF). We then consider the Gaussian relay channel with coded modulation, where we show that a three-level quantization outperforms the Gaussian quantization commonly used to evaluate the achievable rates in this scenario. Finally we consider the cooperative general broadcast scenario with a multi-step conference. We apply estimate-and-forward to obtain a general multi-step achievable rate region. We then give an explicit assignment of the auxiliary random variables, and use this result to obtain an explicit expression for the single common message broadcast scenario with a two-step conference. | On the Role of Estimate-and-Forward with Time-Sharing in Cooperative
Communications | 7,226 |
We consider a peak-power-limited single-antenna block-stationary Gaussian fading channel where neither the transmitter nor the receiver knows the channel state information, but both know the channel statistics. This model subsumes most previously studied Gaussian fading models. We first compute the asymptotic channel capacity in the high SNR regime and show that the behavior of channel capacity depends critically on the channel model. For the special case where the fading process is symbol-by-symbol stationary, we also reveal a fundamental interplay between the codeword length, communication rate, and decoding error probability. Specifically, we show that the codeword length must scale with SNR in order to guarantee that the communication rate can grow logarithmically with SNR with bounded decoding error probability, and we find a necessary condition for the growth rate of the codeword length. We also derive an expression for the capacity per unit energy. Furthermore, we show that the capacity per unit energy is achievable using temporal ON-OFF signaling with optimally allocated ON symbols, where the optimal ON-symbol allocation scheme may depend on the peak power constraint. | Capacity Results for Block-Stationary Gaussian Fading Channels with a
Peak Power Constraint | 7,227 |
In this paper, the multiple access channel (MAC) with channel state is analyzed in a scenario where a) the channel state is known non-causally to the transmitters and b) there is perfect causal feedback from the receiver to the transmitters. An achievable region and an outer bound are found for a discrete memoryless MAC that extend existing results, bringing together ideas from the two separate domains of MAC with state and MAC with feedback. Although this achievable region does not match the outer bound in general, special cases where they meet are identified. In the case of a Gaussian MAC, a specialized achievable region is found by using a combination of dirty paper coding and a generalization of the Schalkwijk-Kailath, Ozarow and Merhav-Weissman schemes, and this region is found to be capacity achieving. Specifically, it is shown that additive Gaussian interference that is known non-causally to the transmitter causes no loss in capacity for the Gaussian MAC with feedback. | On the Capacity of Multiple Access Channels with State Information and
Feedback | 7,228 |
The sum capacity on a symbol-synchronous CDMA system having processing gain $N$ and supporting $K$ power constrained users is achieved by employing at most $2N-1$ sequences. Analogously, the minimum received power (energy-per-chip) on the symbol-synchronous CDMA system supporting $K$ users that demand specified data rates is attained by employing at most $2N-1$ sequences. If there are $L$ oversized users in the system, at most $2N-L-1$ sequences are needed. $2N-1$ is the minimum number of sequences needed to guarantee optimal allocation for single dimensional signaling. $N$ orthogonal sequences are sufficient if a few users (at most $N-1$) are allowed to signal in multiple dimensions. If there are no oversized users, these split users need to signal only in two dimensions each. The above results are shown by proving a converse to a well-known result of Weyl on the interlacing eigenvalues of the sum of two Hermitian matrices, one of which is of rank 1. The converse is analogous to Mirsky's converse to the interlacing eigenvalues theorem for bordering matrices. | The Size of Optimal Sequence Sets for Synchronous CDMA Systems | 7,229 |
This paper examines the performance of decision feedback based iterative channel estimation and multiuser detection in channel coded aperiodic DS-CDMA systems operating over multipath fading channels. First, explicit expressions describing the performance of channel estimation and parallel interference cancellation based multiuser detection are developed. These results are then combined to characterize the evolution of the performance of a system that iterates among channel estimation, multiuser detection and channel decoding. Sufficient conditions for convergence of this system to a unique fixed point are developed. | Performance Analysis of Iterative Channel Estimation and Multiuser
Detection in Multipath DS-CDMA Channels | 7,230 |
Feedback of quantized channel state information (CSI), called limited feedback, enables transmit beamforming in multiple-input-multiple-output (MIMO) wireless systems with a small amount of overhead. Due to its efficiency, beamforming with limited feedback has been adopted in several wireless communication standards. Prior work on limited feedback commonly adopts the block fading channel model where temporal correlation in wireless channels is neglected. This paper considers temporally-correlated channels and designs single-user transmit beamforming with limited feedback. Analytical results concerning CSI feedback are derived by modeling quantized CSI as a first-order finite-state Markov chain. These results include the source bit rate generated by time-varying quantized CSI, the required bit rate for a CSI feedback channel, and the effect of feedback delay. In particular, based on the theory of Markov chain convergence rate, feedback delay is proved to reduce the throughput gain due to CSI feedback at least exponentially. Furthermore, an algorithm is proposed for CSI feedback compression in time. Combining the results in this work leads to a new method for designing limited feedback beamforming as demonstrated by a design example. | Limited Feedback Beamforming Over Temporally-Correlated Channels | 7,231 |
A generic $(r,m)$-erasure correcting set is a collection of vectors in $\bF_2^r$ which can be used to generate, for each binary linear code of codimension $r$, a collection of parity check equations that enables iterative decoding of all correctable erasure patterns of size at most $m$. That is to say, the only stopping sets of size at most $m$ for the generated parity check equations are the erasure patterns for which there is more than one manner to fill in theerasures to obtain a codeword. We give an explicit construction of generic $(r,m)$-erasure correcting sets of cardinality $\sum_{i=0}^{m-1} {r-1\choose i}$. Using a random-coding-like argument, we show that for fixed $m$, the minimum size of a generic $(r,m)$-erasure correcting set is linear in $r$. Keywords: iterative decoding, binary erasure channel, stopping set | Generating parity check equations for bounded-distance iterative erasure
decoding | 7,232 |
In this correspondence, we study the minimum pseudo-weight and minimum pseudo-codewords of low-density parity-check (LDPC) codes under linear programming (LP) decoding. First, we show that the lower bound of Kelly, Sridhara, Xu and Rosenthal on the pseudo-weight of a pseudo-codeword of an LDPC code with girth greater than 4 is tight if and only if this pseudo-codeword is a real multiple of a codeword. Then, we show that the lower bound of Kashyap and Vardy on the stopping distance of an LDPC code is also a lower bound on the pseudo-weight of a pseudo-codeword of this LDPC code with girth 4, and this lower bound is tight if and only if this pseudo-codeword is a real multiple of a codeword. Using these results we further show that for some LDPC codes, there are no other minimum pseudo-codewords except the real multiples of minimum codewords. This means that the LP decoding for these LDPC codes is asymptotically optimal in the sense that the ratio of the probabilities of decoding errors of LP decoding and maximum-likelihood decoding approaches to 1 as the signal-to-noise ratio leads to infinity. Finally, some LDPC codes are listed to illustrate these results. | Minimum Pseudo-Weight and Minimum Pseudo-Codewords of LDPC Codes | 7,233 |
Let $N$ local decision makers in a sensor network communicate with their neighbors to reach a decision \emph{consensus}. Communication is local, among neighboring sensors only, through noiseless or noisy links. We study the design of the network topology that optimizes the rate of convergence of the iterative decision consensus algorithm. We reformulate the topology design problem as a spectral graph design problem, namely, maximizing the eigenratio~$\gamma$ of two eigenvalues of the graph Laplacian~$L$, a matrix that is naturally associated with the interconnectivity pattern of the network. This reformulation avoids costly Monte Carlo simulations and leads to the class of non-bipartite Ramanujan graphs for which we find a lower bound on~$\gamma$. For Ramanujan topologies and noiseless links, the local probability of error converges much faster to the overall global probability of error than for structured graphs, random graphs, or graphs exhibiting small-world characteristics. With noisy links, we determine the optimal number of iterations before calling a decision. Finally, we introduce a new class of random graphs that are easy to construct, can be designed with arbitrary number of sensors, and whose spectral and convergence properties make them practically equivalent to Ramanujan topologies. | Topology for Distributed Inference on Graphs | 7,234 |
In this paper, a downlink scenario in which a single-antenna base station communicates with K single antenna users, over a time-correlated fading channel, is considered. It is assumed that channel state information is perfectly known at each receiver, while the statistical characteristics of the fading process and the fading gain at the beginning of each frame are known to the transmitter. By evaluating the random coding error exponent of the time-correlated fading channel, it is shown that there is an optimal codeword length which maximizes the throughput. The throughput of the conventional scheduling that transmits to the user with the maximum signal to noise ratio is examined using both fixed length codewords and variable length codewords. Although optimizing the codeword length improves the performance, it is shown that using the conventional scheduling, the gap between the achievable throughput and the maximum possible throughput of the system tends to infinity as K goes to infinity. A simple scheduling that considers both the signal to noise ratio and the channel time variation is proposed. It is shown that by using this scheduling, the gap between the achievable throughput and the maximum throughput of the system approaches zero. | Scheduling and Codeword Length Optimization in Time Varying Wireless
Networks | 7,235 |
A partially cooperative relay broadcast channel (RBC) is a three-node network with one source node and two destination nodes (destinations 1 and 2) where destination 1 can act as a relay to assist destination 2. Inner and outer bounds on the capacity region of the discrete memoryless partially cooperative RBC are obtained. When the relay function is disabled, the inner and outer bounds reduce to new bounds on the capacity region of broadcast channels. Four classes of RBCs are studied in detail. For the partially cooperative RBC with degraded message sets, inner and outer bounds are obtained. For the semideterministic partially cooperative RBC and the orthogonal partially cooperative RBC, the capacity regions are established. For the parallel partially cooperative RBC with unmatched degraded subchannels, the capacity region is established for the case of degraded message sets. The capacity is also established when the source node has only a private message for destination 2, i.e., the channel reduces to a parallel relay channel with unmatched degraded subchannels. | Rate Regions for Relay Broadcast Channels | 7,236 |
We consider the detection of binary (antipodal) signals transmitted in a spatially multiplexed fashion over a fading multiple-input multiple-output (MIMO) channel and where the detection is done by means of semidefinite relaxation (SDR). The SDR detector is an attractive alternative to maximum likelihood (ML) detection since the complexity is polynomial rather than exponential. Assuming that the channel matrix is drawn with i.i.d. real valued Gaussian entries, we study the receiver diversity and prove that the SDR detector achieves the maximum possible diversity. Thus, the error probability of the receiver tends to zero at the same rate as the optimal maximum likelihood (ML) receiver in the high signal to noise ratio (SNR) limit. This significantly strengthens previous performance guarantees available for the semidefinite relaxation detector. Additionally, it proves that full diversity detection is in certain scenarios also possible when using a non-combinatorial receiver structure. | The Diversity Order of the Semidefinite Relaxation Detector | 7,237 |
Several recent standards such as IEEE 802.11a/g, IEEE 802.16, and ECMA Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM) for high data-rate Ultra-Wideband (UWB), employ bit-interleaved convolutionally-coded multicarrier modulation over quasi-static fading channels. Motivated by the lack of appropriate error rate analysis techniques for this popular type of system and channel model, we present two novel analytical methods for bit error rate (BER) estimation of coded multicarrier systems operating over frequency-selective quasi-static channels with non-ideal interleaving. In the first method, the approximate performance of the system is calculated for each realization of the channel, which is suitable for obtaining the outage BER performance (a common performance measure for e.g. MB-OFDM systems). The second method assumes Rayleigh distributed frequency-domain subcarrier channel gains and knowledge of their correlation matrix, and can be used to directly obtain the average BER performance. Both methods are applicable to convolutionally-coded interleaved multicarrier systems employing Quadrature Amplitude Modulation (QAM), and are also able to account for narrowband interference (modeled as a sum of tone interferers). To illustrate the application of the proposed analysis, both methods are used to study the performance of a tone-interference-impaired MB-OFDM system. | Error Rate Analysis for Coded Multicarrier Systems over Quasi-Static
Fading Channels | 7,238 |
For a wide class of multi-user systems, a subset of capacity region which includes the corner points and the sum-capacity facet has a special structure known as polymatroid. Multiaccess channels with fixed input distributions and multiple-antenna broadcast channels are examples of such systems. Any interior point of the sum-capacity facet can be achieved by time-sharing among corner points or by an alternative method known as rate-splitting. The main purpose of this paper is to find a point on the sum-capacity facet which satisfies a notion of fairness among active users. This problem is addressed in two cases: (i) where the complexity of achieving interior points is not feasible, and (ii) where the complexity of achieving interior points is feasible. For the first case, the corner point for which the minimum rate of the active users is maximized (max-min corner point) is desired for signaling. A simple greedy algorithm is introduced to find the optimum max-min corner point. For the second case, the polymatroid properties are exploited to locate a rate-vector on the sum-capacity facet which is optimally fair in the sense that the minimum rate among all users is maximized (max-min rate). In the case that the rate of some users can not increase further (attain the max-min value), the algorithm recursively maximizes the minimum rate among the rest of the users. It is shown that the problems of deriving the time-sharing coefficients or rate-spitting scheme can be solved by decomposing the problem to some lower-dimensional subproblems. In addition, a fast algorithm to compute the time-sharing coefficients to attain a general point on the sum-capacity facet is proposed. | Fairness in Multiuser Systems with Polymatroid Capacity Region | 7,239 |
In this paper we show a some new look at large deviation theorems from the viewpoint of the information-spectrum (IS) methods, which has been first exploited in information theory, and also demonstrate a new basic formula for the large deviation rate function in general, which is a pair of the lower and upper IS rate functions. In particular, we are interested in establishing the general large deviation rate functions that can be derivable as the Fenchel-Legendre transform of the cumulant generating function. The final goal is to show a necessary and sufficient condition for the rate function to be of Cram\'er-G\"artner-Ellis type. | An information-spectrum approach to large deviation theorems | 7,240 |
A code over GF$(q^m)$ can be imaged or expanded into a code over GF$(q)$ using a basis for the extension field over the base field. The properties of such an image depend on the original code and the basis chosen for imaging. Problems relating the properties of a code and its image with respect to a basis have been of great interest in the field of coding theory. In this work, a generalized version of the problem of self-orthogonality of the $q$-ary image of a $q^m$-ary code has been considered. Given an inner product (more generally, a biadditive form), necessary and sufficient conditions have been derived for a code over a field extension and an expansion basis so that an image of that code is self-orthogonal. The conditions require that the original code be self-orthogonal with respect to several related biadditive forms whenever certain power sums of the dual basis elements do not vanish. Numerous interesting corollaries have been derived by specializing the general conditions. An interesting result for the canonical or regular inner product in fields of characteristic two is that only self-orthogonal codes result in self-orthogonal images. Another result is that image of a code is self-orthogonal for all bases if and only if trace of the code is self-orthogonal, except for the case of binary images of 4-ary codes. The conditions are particularly simple to state and apply for cyclic codes. To illustrate a possible application, new quantum error-correcting codes have been constructed with larger minimum distance than previously known. | Self-orthogonality of $q$-ary Images of $q^m$-ary Codes and Quantum Code
Construction | 7,241 |
We consider a pair of correlated processes {Z_n} and {S_n} (two sided), where the former is observable and the later is hidden. The uncertainty in the estimation of Z_n upon its finite past history is H(Z_n|Z_0^{n-1}), and for estimation of S_n upon this observation is H(S_n|Z_0^{n-1}), which are both sequences of n. The limits of these sequences (and their existence) are of practical and theoretical interest. The first limit, if exists, is the entropy rate. We call the second limit the estimation entropy. An example of a process jointly correlated to another one is the hidden Markov process. It is the memoryless observation of the Markov state process where state transitions are independent of past observations. We consider a new representation of hidden Markov process using iterated function system. In this representation the state transitions are deterministically related to the process. This representation provides a unified framework for the analysis of the two limiting entropies for this process, resulting in integral expressions for the limits. This analysis shows that under mild conditions the limits exist and provides a simple method for calculating the elements of the corresponding sequences. | Hidden Markov Process: A New Representation, Entropy Rate and Estimation
Entropy | 7,242 |
In this paper multi-user detection techniques, such as Parallel and Serial Interference Cancellations (PIC & SIC), General Minimum Mean Square Error (GMMSE) and polynomial MMSE, for the downlink of a broadband Multi-Carrier Code Division Multiple Access (MCCDMA) system are investigated. The Bit Error Rate (BER) and Frame Error Rate (FER) results are evaluated, and compared with single-user detection (MMSEC, EGC) approaches, as well. The performance evaluation takes into account the system load, channel coding and modulation schemes. | Performance comparison of multi-user detectors for the downlink of a
broadband MC-CDMA system | 7,243 |
On the multi-antenna broadcast channel, the spatial degrees of freedom support simultaneous transmission to multiple users. The optimal multiuser transmission, known as dirty paper coding, is not directly realizable. Moreover, close-to-optimal solutions such as Tomlinson-Harashima precoding are sensitive to CSI inaccuracy. This paper considers a more practical design called per user unitary and rate control (PU2RC), which has been proposed for emerging cellular standards. PU2RC supports multiuser simultaneous transmission, enables limited feedback, and is capable of exploiting multiuser diversity. Its key feature is an orthogonal beamforming (or precoding) constraint, where each user selects a beamformer (or precoder) from a codebook of multiple orthonormal bases. In this paper, the asymptotic throughput scaling laws for PU2RC with a large user pool are derived for different regimes of the signal-to-noise ratio (SNR). In the multiuser-interference-limited regime, the throughput of PU2RC is shown to scale logarithmically with the number of users. In the normal SNR and noise-limited regimes, the throughput is found to scale double logarithmically with the number of users and also linearly with the number of antennas at the base station. In addition, numerical results show that PU2RC achieves higher throughput and is more robust against CSI quantization errors than the popular alternative of zero-forcing beamforming if the number of users is sufficiently large. | Performance of Orthogonal Beamforming for SDMA with Limited Feedback | 7,244 |
This paper is focused on the performance analysis of binary linear block codes (or ensembles) whose transmission takes place over independent and memoryless parallel channels. New upper bounds on the maximum-likelihood (ML) decoding error probability are derived. These bounds are applied to various ensembles of turbo-like codes, focusing especially on repeat-accumulate codes and their recent variations which possess low encoding and decoding complexity and exhibit remarkable performance under iterative decoding. The framework of the second version of the Duman and Salehi (DS2) bounds is generalized to the case of parallel channels, along with the derivation of their optimized tilting measures. The connection between the generalized DS2 and the 1961 Gallager bounds, addressed by Divsalar and by Sason and Shamai for a single channel, is explored in the case of an arbitrary number of independent parallel channels. The generalization of the DS2 bound for parallel channels enables to re-derive specific bounds which were originally derived by Liu et al. as special cases of the Gallager bound. In the asymptotic case where we let the block length tend to infinity, the new bounds are used to obtain improved inner bounds on the attainable channel regions under ML decoding. The tightness of the new bounds for independent parallel channels is exemplified for structured ensembles of turbo-like codes. The improved bounds with their optimized tilting measures show, irrespectively of the block length of the codes, an improvement over the union bound and other previously reported bounds for independent parallel channels; this improvement is especially pronounced for moderate to large block lengths. | Coding for Parallel Channels: Gallager Bounds for Binary Linear Codes
with Applications to Repeat-Accumulate Codes and Variations | 7,245 |
The performance of maximum-likelihood (ML) decoded binary linear block codes is addressed via the derivation of tightened upper bounds on their decoding error probability. The upper bounds on the block and bit error probabilities are valid for any memoryless, binary-input and output-symmetric communication channel, and their effectiveness is exemplified for various ensembles of turbo-like codes over the AWGN channel. An expurgation of the distance spectrum of binary linear block codes further tightens the resulting upper bounds. | Tightened Upper Bounds on the ML Decoding Error Probability of Binary
Linear Block Codes | 7,246 |
The performance of maximum-likelihood (ML) decoded binary linear block codes over the AWGN channel is addressed via the tangential-sphere bound (TSB) and two of its recent improved versions. The paper is focused on the derivation of the error exponents of these bounds. Although it was exemplified that some recent improvements of the TSB tighten this bound for finite-length codes, it is demonstrated in this paper that their error exponents coincide. For an arbitrary ensemble of binary linear block codes, the common value of these error exponents is explicitly expressed in terms of the asymptotic growth rate of the average distance spectrum. | On the Error Exponents of Some Improved Tangential-Sphere Bounds | 7,247 |
Broadly speaking Information theory (IT) assumes no structure of the underlying states. But what about contexts where states do have a clear structure - how should IT cope with such situations? And if such coping is at all possible then - how should structure be expressed so that it can be coped with? A possible answer to these questions is presented here. Noting that IT can cope well with a structure expressed as an accurate clustering (by shifting to the implied reduced alphabet), a generalization is suggested in which structure is expressed as a measure on reduced alphabets. Given such structure an extension of IT is presented where the reduced alphabets are treated simultaneously. This structure-sensitive IT, called ITs, extends traditional IT in the sense that: a)there are structure-sensitive analogs to the notions of traditional IT and b)translating a theorem in IT by replacing its notions with their structure-sensitive counterparts, yields a (provable) theorem of ITs. Seemingly paradoxically, ITs extends IT but it's completely within the framework of IT. The richness of the suggested structures is demonstrated by two disparate families studied in more detail: the family of hierarchical structures and the family of linear structures. The formal findings extend the scope of cases to which a rigorous application of IT can be applied (with implications on quantization, for example). The implications on the foundations of IT are that the assumption regarding no underlying structure of states is not mandatory and that there is a framework for expressing such underlying structure. | ITs, a structure sensitive information theory | 7,248 |
We consider the problem of estimating the total probability of all symbols that appear with a given frequency in a string of i.i.d. random variables with unknown distribution. We focus on the regime in which the block length is large yet no symbol appears frequently in the string. This is accomplished by allowing the distribution to change with the block length. Under a natural convergence assumption on the sequence of underlying distributions, we show that the total probabilities converge to a deterministic limit, which we characterize. We then show that the Good-Turing total probability estimator is strongly consistent. | Strong Consistency of the Good-Turing Estimator | 7,249 |
The paper deals with orthogonal space-time block coded MC-CDMA systems in outdoor realistic downlink scenarios with up to two transmit and receive antennas. Assuming no channel state information at the transmitter, we compare several linear single-user detection and spreading schemes, with or without channel coding, achieving a spectral efficiency of 1-2 bits/s/Hz. The different results obtained demonstrate that spatial diversity significantly improves the performance of MC-CDMA systems, and allows different chip-mapping without notably decreasing performance. Moreover, the global system exhibits a good trade-off between complexity at mobile stations and performance. Then, Alamouti's STBC MC-CDMA schemes derive full benefit from the frequency and spatial diversities and can be considered as a very realistic and promising candidate for the air interface downlink of the 4/sup th/ generation mobile radio systems. | Performance of STBC MC-CDMA systems over outdoor realistic MIMO channels | 7,250 |
The asymptotic iterative decoding performances of low-density parity-check (LDPC) codes using min-sum (MS) and sum-product (SP) decoding algorithms on memoryless binary-input output-symmetric (MBIOS) channels are analyzed in this paper. For MS decoding, the analysis is done by upper bounding the bit error probability of the root bit of a tree code by the sequence error probability of a subcode of the tree code assuming the transmission of the all-zero codeword. The result is a recursive upper bound on the bit error probability after each iteration. For SP decoding, we derive a recursively determined lower bound on the bit error probability after each iteration. This recursive lower bound recovers the density evolution equation of LDPC codes on the binary erasure channel (BEC) with inequalities satisfied with equalities. A significant implication of this result is that the performance of LDPC codes under SP decoding on the BEC is an upper bound of the performance on all MBIOS channels with the same uncoded bit error probability. All results hold for the more general multi-edge type LDPC codes. | Iterative Decoding Performance Bounds for LDPC Codes on Noisy Channels | 7,251 |
We consider Slepian-Wolf code design based on LDPC (low-density parity-check) coset codes for memoryless source-side information pairs. A density evolution formula, equipped with a concentration theorem, is derived for Slepian- Wolf coding based on LDPC coset codes. As a consequence, an intimate connection between Slepian-Wolf coding and channel coding is established. Specifically we show that, under density evolution, design of binary LDPC coset codes for Slepian-Wolf coding of an arbitrary memoryless source-side information pair reduces to design of binary LDPC codes for binary-input output-symmetric channels without loss of optimality. With this connection, many classic results in channel coding can be easily translated into the Slepian-Wolf setting. | Slepian-Wolf Code Design via Source-Channel Correspondence | 7,252 |
The performance of iterative decoding techniques for linear block codes correcting erasures depends very much on the sizes of the stopping sets associated with the underlying Tanner graph, or, equivalently, the parity-check matrix representing the code. In this paper, we introduce the notion of dead-end sets to explicitly demonstrate this dependency. The choice of the parity-check matrix entails a trade-off between performance and complexity. We give bounds on the complexity of iterative decoders achieving optimal performance in terms of the sizes of the underlying parity-check matrices. Further, we fully characterize codes for which the optimal stopping set enumerator equals the weight enumerator. | Results on Parity-Check Matrices with Optimal Stopping and/or Dead-End
Set Enumerators | 7,253 |
Elaborating on prior work by Minka, we formulate a general computation rule for lossy messages. An important special case (with many applications in communications) is the conversion of "soft-bit" messages to Gaussian messages. By this method, the performance of a Kalman equalizer is improved, both for uncoded and coded transmission. | A general computation rule for lossy summaries/messages with examples
from equalization | 7,254 |
We model the development of the linear complexity of multisequences by a stochastic infinite state machine, the Battery-Discharge-Model, BDM. The states s in S of the BDM have asymptotic probabilities or mass Pr(s)=1/(P(q,M) q^K(s)), where K(s) in N_0 is the class of the state s, and P(q,M)=\sum_(K in\N0) P_M(K)q^(-K)=\prod_(i=1..M) q^i/(q^i-1) is the generating function of the number of partitions into at most M parts. We have (for each timestep modulo M+1) just P_M(K) states of class K \. We obtain a closed formula for the asymptotic probability for the linear complexity deviation d(n) := L(n)-\lceil n\cdot M/(M+1)\rceil with Pr(d)=O(q^(-|d|(M+1))), for M in N, for d in Z. The precise formula is given in the text. It has been verified numerically for M=1..8, and is conjectured to hold for all M in N. From the asymptotic growth (proven for all M in N), we infer the Law of the Logarithm for the linear complexity deviation, -liminf_{n\to\infty} d_a(n) / log n = 1 /((M+1)log q) = limsup_{n\to\infty} d_a(n) / log n, which immediately yields L_a(n)/n \to M/(M+1) with measure one, for all M in N, a result recently shown already by Niederreiter and Wang. Keywords: Linear complexity, linear complexity deviation, multisequence, Battery Discharge Model, isometry. | Towards a General Theory of Simultaneous Diophantine Approximation of
Formal Power Series: Multidimensional Linear Complexity | 7,255 |
We explain how to optimize finite-length LDPC codes for transmission over the binary erasure channel. Our approach relies on an analytic approximation of the erasure probability. This is in turn based on a finite-length scaling result to model large scale erasures and a union bound involving minimal stopping sets to take into account small error events. We show that the performances of optimized ensembles as observed in simulations are well described by our approximation. Although we only address the case of transmission over the binary erasure channel, our method should be applicable to a more general setting. | How to Find Good Finite-Length Codes: From Art Towards Science | 7,256 |
Two product array codes are used to construct the (24, 12, 8) binary Golay code through the direct sum operation. This construction provides a systematic way to find proper (8, 4, 4) linear block component codes for generating the Golay code, and it generates and extends previously existing methods that use a similar construction framework. The code constructed is simple to decode. | On Construction of the (24,12,8) Golay Codes | 7,257 |
Let $X$ be a discrete random variable with support $S$ and $f : S \to S^\prime$ be a bijection. Then it is well-known that the entropy of $X$ is the same as the entropy of $f(X)$. This entropy preservation property has been well-utilized to establish non-trivial properties of discrete stochastic processes, e.g. queuing process \cite{prg03}. Entropy as well as entropy preservation is well-defined only in the context of purely discrete or continuous random variables. However for a mixture of discrete and continuous random variables, which arise in many interesting situations, the notions of entropy and entropy preservation have not been well understood. In this paper, we extend the notion of entropy in a natural manner for a mixed-pair random variable, a pair of random variables with one discrete and the other continuous. Our extensions are consistent with the existing definitions of entropy in the sense that there exist natural injections from discrete or continuous random variables into mixed-pair random variables such that their entropy remains the same. This extension of entropy allows us to obtain sufficient conditions for entropy preservation in mixtures of discrete and continuous random variables under bijections. The extended definition of entropy leads to an entropy rate for continuous time Markov chains. As an application, we recover a known probabilistic result related to Poisson process. We strongly believe that the frame-work developed in this paper can be useful in establishing probabilistic properties of complex processes, such as load balancing systems, queuing network, caching algorithms. | On entropy for mixtures of discrete and continuous variables | 7,258 |
The problem of cooperative fusion in the presence of Byzantine sensors is considered. An information theoretic formulation is used to characterize the Shannon capacity of sensor fusion. It is shown that when less than half of the sensors are Byzantine, the effect of Byzantine attack can be entirely mitigated, and the fusion capacity is identical to that when all sensors are honest. But when at least half of the sensors are Byzantine, they can completely defeat the sensor fusion so that no information can be transmitted reliably. A capacity achieving transmit-then-verify strategy is proposed for the case that less than half of the sensors are Byzantine, and its error probability and coding rate is analyzed by using a Markov decision process modeling of the transmission protocol. | Capacity of Cooperative Fusion in the Presence of Byzantine Sensors | 7,259 |
In this paper, we derive Gallager's random coding error exponent for multiple-input multiple-output (MIMO) channels, assuming no channel-state information (CSI) at the transmitter and perfect CSI at the receiver. This measure gives insight into a fundamental tradeoff between the communication reliability and information rate of MIMO channels, enabling to determine the required codeword length to achieve a prescribed error probability at a given rate below the channel capacity. We quantify the effects of the number of antennas, channel coherence time, and spatial fading correlation on the MIMO exponent. In addition, general formulae for the ergodic capacity and the cutoff rate in the presence of spatial correlation are deduced from the exponent expressions. These formulae are applicable to arbitrary structures of transmit and receive correlation, encompassing all the previously known results as special cases of our expressions. | Gallager's Exponent for MIMO Channels: A Reliability-Rate Tradeoff | 7,260 |
We provide achievability as well as converse results for the degrees of freedom region of a MIMO $X$ channel, i.e., a system with two transmitters, two receivers, each equipped with multiple antennas, where independent messages need to be conveyed over fixed channels from each transmitter to each receiver. With M=1 antennas at each node, we find that the total (sum rate) degrees of freedom are bounded above and below as $1 \leq\eta_X^\star \leq {4/3}$. If $M>1$ and channel matrices are non-degenerate then the precise degrees of freedom $\eta_X^\star = {4/3}M$. Simple zero forcing without dirty paper encoding or successive decoding, suffices to achieve the ${4/3}M$ degrees of freedom. With equal number of antennas at all nodes, we explore the increase in degrees of freedom when some of the messages are made available to a transmitter or receiver in the manner of cognitive radio. With a cognitive transmitter we show that the number of degrees of freedom $\eta = {3/2}M$ (for $M>1$) on the MIMO $X$ channel. The same degrees of freedom are obtained on the MIMO $X$ channel with a cognitive receiver as well. In contrast to the $X$ channel result, we show that for the MIMO \emph{interference} channel, the degrees of freedom are not increased even if both the transmitter and the receiver of one user know the other user's message. However, the interference channel can achieve the full $2M$ degrees of freedom if \emph{each} user has either a cognitive transmitter or a cognitive receiver. Lastly, if the channels vary with time/frequency then the $X$ channel with single antennas $(M=1)$ at all nodes has exactly 4/3 degrees of freedom with no shared messages and exactly 3/2 degrees of freedom with a cognitive transmitter or a cognitive receiver. | Degrees of Freedom Region for the MIMO X Channel | 7,261 |
We consider a state-dependent multiaccess channel (MAC) with state non-causally known to some encoders. We derive an inner bound for the capacity region in the general discrete memoryless case and specialize to a binary noiseless case. In the case of maximum entropy channel state, we obtain the capacity region for binary noiseless MAC with one informed encoder by deriving a non-trivial outer bound for this case. For a Gaussian state-dependent MAC with one encoder being informed of the channel state, we present an inner bound by applying a slightly generalized dirty paper coding (GDPC) at the informed encoder that allows for partial state cancellation, and a trivial outer bound by providing channel state to the decoder also. The uninformed encoders benefit from the state cancellation in terms of achievable rates, however, appears that GDPC cannot completely eliminate the effect of the channel state on the achievable rate region, in contrast to the case of all encoders being informed. In the case of infinite state variance, we analyze how the uninformed encoder benefits from the informed encoder's actions using the inner bound and also provide a non-trivial outer bound for this case which is better than the trivial outer bound. | Multiaccess Channels with State Known to Some Encoders and Independent
Messages | 7,262 |
In this paper, we present a method of estimating the volatility of a signal that displays stochastic noise (such as a risky asset traded on an open market) utilizing Linear Predictive Coding. The main purpose is to associate volatility with a series of statistical properties that can lead us, through further investigation, toward a better understanding of structural volatility as well as to improve the quality of our current estimates. | Linear Predictive Coding as an Estimator of Volatility | 7,263 |
The decoding of Low-Density Parity-Check codes by the Belief Propagation (BP) algorithm is revisited. We check the iterative algorithm for its convergence to a codeword (termination), we run Monte Carlo simulations to find the probability distribution function of the termination time, n_it. Tested on an example [155, 64, 20] code, this termination curve shows a maximum and an extended algebraic tail at the highest values of n_it. Aiming to reduce the tail of the termination curve we consider a family of iterative algorithms modifying the standard BP by means of a simple relaxation. The relaxation parameter controls the convergence of the modified BP algorithm to a minimum of the Bethe free energy. The improvement is experimentally demonstrated for Additive-White-Gaussian-Noise channel in some range of the signal-to-noise ratios. We also discuss the trade-off between the relaxation parameter of the improved iterative scheme and the number of iterations. | Improving convergence of Belief Propagation decoding | 7,264 |
We consider codes over the alphabet Q={0,1,..,q-1}intended for the control of unidirectional errors of level l. That is, the transmission channel is such that the received word cannot contain both a component larger than the transmitted one and a component smaller than the transmitted one. Moreover, the absolute value of the difference between a transmitted component and its received version is at most l. We introduce and study q-ary codes capable of correcting all unidirectional errors of level l. Lower and upper bounds for the maximal size of those codes are presented. We also study codes for this aim that are defined by a single equation on the codeword coordinates(similar to the Varshamov-Tenengolts codes for correcting binary asymmetric errors). We finally consider the problem of detecting all unidirectional errors of level l. | On q-ary codes correcting all unidirectional errors of a limited
magnitude | 7,265 |
In this paper we consider the communication problem that involves transmission of correlated sources over broadcast channels. We consider a graph-based framework for this information transmission problem. The system involves a source coding module and a channel coding module. In the source coding module, the sources are efficiently mapped into a nearly semi-regular bipartite graph, and in the channel coding module, the edges of this graph are reliably transmitted over a broadcast channel. We consider nearly semi-regular bipartite graphs as discrete interface between source coding and channel coding in this multiterminal setting. We provide an information-theoretic characterization of (1) the rate of exponential growth (as a function of the number of channel uses) of the size of the bipartite graphs whose edges can be reliably transmitted over a broadcast channel and (2) the rate of exponential growth (as a function of the number of source samples) of the size of the bipartite graphs which can reliably represent a pair of correlated sources to be transmitted over a broadcast channel. | A Graph-based Framework for Transmission of Correlated Sources over
Broadcast Channels | 7,266 |
Given a probability distribution P, what is the minimum amount of bits needed to store a value x sampled according to P, such that x can later be recovered (except with some small probability)? Or, what is the maximum amount of uniform randomness that can be extracted from x? Answering these and similar information-theoretic questions typically boils down to computing so-called smooth entropies. In this paper, we derive explicit and almost tight bounds on the smooth entropies of n-fold product distributions. | On the randomness of independent experiments | 7,267 |
New approach for analysis and decoding MIMO signaling is developed for usual model of nongaussion noise consists of background and impulsive noise named epsilon - noise. It is shown that non-gaussion noise performance significantly worse than gaussion ones. Stimulation results strengthen out theory. Robust in statistical sense detection rule is suggested for such kind of noise features much best robust detector performance than detector designed for Gaussian noise in impulsive environment and modest margin in background noise. Proposed algorithms performance are comparable with developed potential bound. Proposed tool, is crucial issue for MIMO communication system design, since real noise environment has impulsive character that contradict with wide used Gaussian approach, so real MIMO performance much different for Gaussian a non-Gaussian noise model. | MIMO scheme performance and detection in epsilon noise | 7,268 |
In this paper, a unifying framework for orthogonal frequency division multiplexing (OFDM) multiuser resource allocation is presented. The isolated seeming problems of maximizing a weighted sum of rates for a given power budget $\bar{P}$ and minimizing sum power for given rate requirements $\mathbf{\bar{R}}$ can be interpreted jointly in this framework. To this end we embed the problems in a higher dimensional space. Based on these results, we subsequently consider the combined problem of maximizing a weighted sum of rates under given rate requirements $\mathbf{\bar{R}}$ and a fixed power budget $\bar{P}$. This new problem is challenging, since the additional constraints do not allow to use the hitherto existing approaches. Interestingly, the optimal decoding orders turn out to be the ordering of the Lagrangian factors in all problems. | Optimal resource allocation for OFDM multiuser channels | 7,269 |
A new approach for decoding binary linear codes by solving a linear program (LP) over a relaxed codeword polytope was recently proposed by Feldman et al. In this paper we investigate the structure of the polytope used in the LP relaxation decoding. We begin by showing that for expander codes, every fractional pseudocodeword always has at least a constant fraction of non-integral bits. We then prove that for expander codes, the active set of any fractional pseudocodeword is smaller by a constant fraction than the active set of any codeword. We exploit this fact to devise a decoding algorithm that provably outperforms the LP decoder for finite blocklengths. It proceeds by guessing facets of the polytope, and resolving the linear program on these facets. While the LP decoder succeeds only if the ML codeword has the highest likelihood over all pseudocodewords, we prove that for expander codes the proposed algorithm succeeds even with a constant number of pseudocodewords of higher likelihood. Moreover, the complexity of the proposed algorithm is only a constant factor larger than that of the LP decoder. | Guessing Facets: Polytope Structure and Improved LP Decoder | 7,270 |
This paper derives an improved sphere-packing (ISP) bound for finite-length codes whose transmission takes place over symmetric memoryless channels. We first review classical results, i.e., the 1959 sphere-packing (SP59) bound of Shannon for the Gaussian channel, and the 1967 sphere-packing (SP67) bound of Shannon et al. for discrete memoryless channels. A recent improvement on the SP67 bound, as suggested by Valembois and Fossorier, is also discussed. These concepts are used for the derivation of a new lower bound on the decoding error probability (referred to as the ISP bound) which is uniformly tighter than the SP67 bound and its recent improved version. The ISP bound is applicable to symmetric memoryless channels, and some of its applications are exemplified. Its tightness is studied by comparing it with bounds on the ML decoding error probability, and computer simulations of iteratively decoded turbo-like codes. The paper also presents a technique which performs the entire calculation of the SP59 bound in the logarithmic domain, thus facilitating the exact calculation of this bound for moderate to large block lengths without the need for the asymptotic approximations provided by Shannon. | An Improved Sphere-Packing Bound for Finite-Length Codes on Symmetric
Memoryless Channels | 7,271 |
We consider multi-hop multiple access (MAC) and broadcast channels (BC) where communication takes place with the assistance of relays that amplify and forward (AF) their received signals. For a two hop parallel AF relay MAC, assuming a sum power constraint across all relays we characterize optimal relay amplification factors and the resulting capacity regions. We find that the parallel AF relay MAC with total transmit power of the two users $P_1+P_2=P$ and total relay power $P_R$ is the dual of the parallel AF relay BC where the MAC source nodes become the BC destination nodes, the MAC destination node becomes the BC source node, the dual BC source transmit power is $P_R$ and the total transmit power of the AF relays is $P$. The duality means that the capacity region of the AF relay MAC with a sum power constraint $P$ on the transmitters is the same as that of the dual BC. The duality relationship is found to be useful in characterizing the capacity region of the AF relay BC as the union of MAC capacity regions. The duality extends to distributed relays with multiple antennas and more than 2 hops as well. | Duality and Capacity Region of AF Relay MAC and BC | 7,272 |
We consider capacity of discrete-time channels with feedback for the general case where the feedback is a time-invariant deterministic function of the output samples. Under the assumption that the channel states take values in a finite alphabet, we find an achievable rate and an upper bound on the capacity. We further show that when the channel is indecomposable, and has no intersymbol interference (ISI), its capacity is given by the limit of the maximum of the (normalized) directed information between the input $X^N$ and the output $Y^N$, i.e. $C = \lim_{N \to \infty} \frac{1}{N} \max I(X^N \to Y^N)$, where the maximization is taken over the causal conditioning probability $Q(x^N||z^{N-1})$ defined in this paper. The capacity result is used to show that the source-channel separation theorem holds for time-invariant determinist feedback. We also show that if the state of the channel is known both at the encoder and the decoder then feedback does not increase capacity. | Finite State Channels with Time-Invariant Deterministic Feedback | 7,273 |
This work considers the problem of communication from a single transmitter, over a network with colocated users, through an independent block Rayleigh fading channel. The colocation nature of the users allows cooperation, which increases the overall achievable rate, from the transmitter to the destined user. The transmitter is ignorant of the fading coefficients, while receivers have access to perfect channel state information (CSI). This gives rise to the multi-layer broadcast approach used by the transmitter. The broadcast approach allows, in our network setting, to improve the cooperation between the colocated users. That is due to the nature of broadcasting, where the better the channel quality, the more layers that can be decoded. The cooperation between the users is performed over an additive white Gaussian channels (AWGN), with a relaying power constraint, and unlimited bandwidth. Three commonly used cooperation techniques are studied: amplify-forward (AF), compress-forward (CF), and decode-forward (DF). These methods are extended using the broadcast approach, for the case of relaxed decoding delay constraint. For this case a separated processing of the layers, which includes multi-session cooperation is shown to be beneficial. Further, closed form expressions for infinitely many AF sessions and recursive expressions for the more complex CF are given. Numerical results for the various cooperation strategies demonstrate the efficiency of multi-session cooperation. | Broadcast Cooperation Strategies for Two Colocated Users | 7,274 |
This paper considers the Linear Minimum Variance recursive state estimation for the linear discrete time dynamic system with random state transition and measurement matrices, i.e., random parameter matrices Kalman filtering. It is shown that such system can be converted to a linear dynamic system with deterministic parameter matrices but state-dependent process and measurement noises. It is proved that under mild conditions, the recursive state estimation of this system is still of the form of a modified Kalman filtering. More importantly, this result can be applied to Kalman filtering with intermittent and partial observations as well as randomly variant dynamic systems. | Applications of Random Parameter Matrices Kalman Filtering in Uncertain
Observation and Multi-Model Systems | 7,275 |
This paper deals with throughput scaling laws for random ad-hoc wireless networks in a rich scattering environment. We develop schemes to optimize the ratio, $\rho(n)$ of achievable network sum capacity to the sum of the point-to-point capacities of source-destinations pairs operating in isolation. For fixed SNR networks, i.e., where the worst case SNR over the source-destination pairs is fixed independent of $n$, we show that collaborative strategies yield a scaling law of $\rho(n) = {\cal O}(\frac{1}{n^{1/3}})$ in contrast to multi-hop strategies which yield a scaling law of $\rho(n) = {\cal O}(\frac{1}{\sqrt{n}})$. While, networks where worst case SNR goes to zero, do not preclude the possibility of collaboration, multi-hop strategies achieve optimal throughput. The plausible reason is that the gains due to collaboration cannot offset the effect of vanishing receive SNR. This suggests that for fixed SNR networks, a network designer should look for network protocols that exploit collaboration. The fact that most current networks operate in a fixed SNR interference limited environment provides further motivation for considering this regime. | Wireless ad-hoc networks: Strategies and Scaling laws for the fixed SNR
regime | 7,276 |
Code annealing, a new method of designing good codes of short block length, is proposed, which is then concatenated with cyclic lifting to create finite codes of low frame error rate (FER) error floors without performance outliers. The stopping set analysis is performed on the cyclically lifted code ensemble assuming uniformly random lifting sequences, and the suppressing effect/weight of the cyclic lifting is identified for the first time, based on which the ensemble FER error floor can be analytically determined and a scaling law is derived. Both the first-order and high-order suppressing effects are discussed and quantified by different methods including the explicit expression, an algorithmic upper bound, and an algebraic lower bound. The mismatch between the suppressing weight and the stopping distances explains the dramatic performance discrepancy among different cyclically lifted codes when the underlying base codes have degree 2 variable nodes or not. For the former case, a degree augmentation method is further introduced to mitigate this metric mismatch, and a systematic method of constructing irregular codes of low FER error floors is presented. Both regular and irregular codes of very low FER error floors are reported, for which the improvement factor ranges from 10^6-10^4 when compared to the classic graph-based code ensembles. | Code Annealing and the Suppressing Effect of the Cyclically Lifted LDPC
Code Ensemble | 7,277 |
We apply two variations of the principle of Minimum Cross Entropy (the Kullback information measure) to fit parameterized probability density models to observed data densities. For an array beamforming problem with P incident narrowband point sources, N > P sensors, and colored noise, both approaches yield eigenvector fitting methods similar to that of the MUSIC algorithm[1]. Furthermore, the corresponding cross-entropies are related to the MDL model order selection criterion[2]. | Cross Entropy Approximation of Structured Covariance Matrices | 7,278 |
As a generalization of cyclic codes, quasi-cyclic (QC) codes contain many good linear codes. But quasi-cyclic codes studied so far are mainly limited to one generator (1-generator) QC codes. In this correspondence, 2-generator and 3-generator QC codes are studied, and many good, new QC codes are constructed from simplex codes. Some new binary QC codes or related codes, that improve the bounds on maximum minimum distance for binary linear codes are constructed. They are 5-generator QC [93, 17, 34] and [254, 23, 102] codes, and related [96, 17, 36], [256, 23, 104] codes. | New Quasi-Cyclic Codes from Simplex Codes | 7,279 |
This paper describes an efficient implementation of binning for the relay channel using low-density parity-check (LDPC) codes. We devise bilayer LDPC codes to approach the theoretically promised rate of the decode-and-forward relaying strategy by incorporating relay-generated information bits in specially designed bilayer graphical code structures. While conventional LDPC codes are sensitively tuned to operate efficiently at a certain channel parameter, the proposed bilayer LDPC codes are capable of working at two different channel parameters and two different rates: that at the relay and at the destination. To analyze the performance of bilayer LDPC codes, bilayer density evolution is devised as an extension of the standard density evolution algorithm. Based on bilayer density evolution, a design methodology is developed for the bilayer codes in which the degree distribution is iteratively improved using linear programming. Further, in order to approach the theoretical decode-and-forward rate for a wide range of channel parameters, this paper proposes two different forms bilayer codes, the bilayer-expurgated and bilayer-lengthened codes. It is demonstrated that a properly designed bilayer LDPC code can achieve an asymptotic infinite-length threshold within 0.24 dB gap to the Shannon limits of two different channels simultaneously for a wide range of channel parameters. By practical code construction, finite-length bilayer codes are shown to be able to approach within a 0.6 dB gap to the theoretical decode-and-forward rate of the relay channel at a block length of $10^5$ and a bit-error probability (BER) of $10^{-4}$. Finally, it is demonstrated that a generalized version of the proposed bilayer code construction is applicable to relay networks with multiple relays. | Bilayer Low-Density Parity-Check Codes for Decode-and-Forward in Relay
Channels | 7,280 |
Expressions for (EPI Shannon type) Divergence-Power Inequalities (DPI) in two cases (time-discrete and band-limited time-continuous) of stationary random processes are given. The new expressions connect the divergence rate of the sum of independent processes, the individual divergence rate of each process, and their power spectral densities. All divergences are between a process and a Gaussian process with same second order statistics, and are assumed to be finite. A new proof of the Shannon entropy-power inequality EPI, based on the relationship between divergence and causal minimum mean-square error (CMMSE) in Gaussian channels with large signal-to-noise ratio, is also shown. | On Divergence-Power Inequalities | 7,281 |
In this paper we address the problem of closed-form spectral evaluation of CPM. We show that the multi-h CPM signal can be conveniently generated by a PTI SM. The output is governed by a Markov chain with the unusual peculiarity of being cyclostationary and reducible; this holds also in the single-h context. Judicious reinterpretation of the result leads to a formalization through a stationary and irreducible Markov chain, whose spectral evaluation is known in closed-form from the literature. Two are the major outcomes of this paper. First, unlike the literature, we obtain a PSD in true closed-form. Second, we give novel insights into the CPM format. | Exact Spectral Analysis of Single-h and Multi-h CPM Signals through PAM
decomposition and Matrix Series Evaluation | 7,282 |
High data-rate Distributed Orthogonal Space-Time Block Codes (DOSTBCs) which achieve the single-symbol decodability and full diversity order are proposed in this paper. An upper bound of the data-rate of the DOSTBC is derived and it is approximately twice larger than that of the conventional repetition-based cooperative strategy. In order to facilitate the systematic constructions of the DOSTBCs achieving the upper bound of the data-rate, some special DOSTBCs, which have diagonal noise covariance matrices at the destination terminal, are investigated. These codes are referred to as the row-monomial DOSTBCs. An upper bound of the data-rate of the row-monomial DOSTBC is derived and it is equal to or slightly smaller than that of the DOSTBC. Lastly, the systematic construction methods of the row-monomial DOSTBCs achieving the upper bound of the data-rate are presented. | High Data-Rate Single-Symbol ML Decodable Distributed STBCs for
Cooperative Networks | 7,283 |
We present simple coding strategies, which are variants of the Schalkwijk-Kailath scheme, for communicating reliably over additive white noise channels in the presence of corrupted feedback. More specifically, we consider a framework comprising an additive white forward channel and a backward link which is used for feedback. We consider two types of corruption mechanisms in the backward link. The first is quantization noise, i.e., the encoder receives the quantized values of the past outputs of the forward channel. The quantization is uniform, memoryless and time invariant (that is, symbol-by-symbol scalar quantization), with bounded quantization error. The second corruption mechanism is an arbitrarily distributed additive bounded noise in the backward link. Here we allow symbol-by-symbol encoding at the input to the backward channel. We propose simple explicit schemes that guarantee positive information rate, in bits per channel use, with positive error exponent. If the forward channel is additive white Gaussian then our schemes achieve capacity, in the limit of diminishing amplitude of the noise components at the backward link, while guaranteeing that the probability of error converges to zero as a doubly exponential function of the block length. Furthermore, if the forward channel is additive white Gaussian and the backward link consists of an additive bounded noise channel, with signal-to-noise ratio (SNR) constrained symbol-by-symbol encoding, then our schemes are also capacity-achieving in the limit of high SNR. | Coding for Additive White Noise Channels with Feedback Corrupted by
Uniform Quantization or Bounded Noise | 7,284 |
Asymptotic spectral distribution (ASD) of the crosscorrelation matrix is investigated for a random spreading short/long-code asynchronous direct sequence-code division multiple access (DS-CDMA) system. The discrete-time decision statistics are obtained as the output samples of a bank of symbol matched filters of all users. The crosscorrelation matrix is studied when the number of symbols transmitted by each user tends to infinity. Two levels of asynchronism are considered. One is symbol-asynchronous but chip-synchronous, and the other is chip-asynchronous. The existence of a nonrandom ASD is proved by moment convergence theorem, where the focus is on the derivation of asymptotic eigenvalue moments (AEM) of the crosscorrelation matrix. A combinatorics approach based on noncrossing partition of set partition theory is adopted for AEM computation. The spectral efficiency and the minimum mean-square-error (MMSE) achievable by a linear receiver of asynchronous CDMA are plotted by AEM using a numerical method. | Asymptotic Spectral Distribution of Crosscorrelation Matrix in
Asynchronous CDMA | 7,285 |
The normalized min-sum algorithm can achieve near-optimal performance at decoding LDPC codes. However, it is a critical question to understand the mathematical principle underlying the algorithm. Traditionally, people thought that the normalized min-sum algorithm is a good approximation to the sum-product algorithm, the best known algorithm for decoding LDPC codes and Turbo codes. This paper offers an alternative approach to understand the normalized min-sum algorithm. The algorithm is derived directly from cooperative optimization, a newly discovered general method for global/combinatorial optimization. This approach provides us another theoretical basis for the algorithm and offers new insights on its power and limitation. It also gives us a general framework for designing new decoding algorithms. | Deriving the Normalized Min-Sum Algorithm from Cooperative Optimization | 7,286 |
In this paper, we present a fast min-sum algorithm for decoding LDPC codes over GF(q). Our algorithm is different from the one presented by David Declercq and Marc Fossorier in ISIT 05 only at the way of speeding up the horizontal scan in the min-sum algorithm. The Declercq and Fossorier's algorithm speeds up the computation by reducing the number of configurations, while our algorithm uses the dynamic programming instead. Compared with the configuration reduction algorithm, the dynamic programming one is simpler at the design stage because it has less parameters to tune. Furthermore, it does not have the performance degradation problem caused by the configuration reduction because it searches the whole configuration space efficiently through dynamic programming. Both algorithms have the same level of complexity and use simple operations which are suitable for hardware implementations. | Fast Min-Sum Algorithms for Decoding of LDPC over GF(q) | 7,287 |
Many implementations for decoding LDPC codes are based on the (normalized/offset) min-sum algorithm due to its satisfactory performance and simplicity in operations. Usually, each iteration of the min-sum algorithm contains two scans, the horizontal scan and the vertical scan. This paper presents a single-scan version of the min-sum algorithm to speed up the decoding process. It can also reduce memory usage or wiring because it only needs the addressing from check nodes to variable nodes while the original min-sum algorithm requires that addressing plus the addressing from variable nodes to check nodes. To cut down memory usage or wiring further, another version of the single-scan min-sum algorithm is presented where the messages of the algorithm are represented by single bit values instead of using fixed point ones. The software implementation has shown that the single-scan min-sum algorithm is more than twice as fast as the original min-sum algorithm. | Single-Scan Min-Sum Algorithms for Fast Decoding of LDPC Codes | 7,288 |
This paper derives an improved sphere-packing (ISP) bound targeting codes of short to moderate block lengths. We first review the 1967 sphere-packing (SP67) bound for discrete memoryless channels, and a recent improvement by Valembois and Fossorier. These concepts are used for the derivation of a new lower bound on the decoding error probability (referred to as the ISP bound) which is uniformly tighter than the SP67 bound and its recent improved version. Under a mild condition, the ISP bound is applicable to general memoryless channels, and some of its applications are exemplified. Its tightness is studied by comparing it with bounds on the ML decoding error probability. It is exemplified that the ISP bound suggests an interesting alternative to the 1959 sphere-packing (SP59) bound of Shannon for the Gaussian channel, especially for digital modulations of high spectral efficiency. | An Improved Sphere-Packing Bound Targeting Codes of Short to Moderate
Block Lengths and Applications | 7,289 |
This paper is focused on the performance analysis of binary linear block codes (or ensembles) whose transmission takes place over independent and memoryless parallel channels. New upper bounds on the maximum-likelihood (ML) decoding error probability are derived. The framework of the second version of the Duman and Salehi (DS2) bounds is generalized to the case of parallel channels, along with the derivation of optimized tilting measures. The connection between the generalized DS2 and the 1961 Gallager bounds, known previously for a single channel, is revisited for the case of parallel channels. The new bounds are used to obtain improved inner bounds on the attainable channel regions under ML decoding. These improved bounds are applied to ensembles of turbo-like codes, focusing on repeat-accumulate codes and their recent variations. | Coding for Parallel Channels: Gallager Bounds and Applications to
Repeat-Accumulate Codes | 7,290 |
We propose a new low-density parity-check code construction scheme based on 2-lifts. The proposed codes have an advantage of admitting efficient hardware implementations. With the motivation of designing codes with low error floors, we present an analysis of the low-weight stopping set distributions of the proposed codes. Based on this analysis, we propose design criteria for designing codes with low error floors. Numerical results show that the resulting codes have low error probabilities over binary erasure channels. | Constructing LDPC Codes by 2-Lifts | 7,291 |
Classical rate-distortion theory requires knowledge of an elusive source distribution. Instead, we analyze rate-distortion properties of individual objects using the recently developed algorithmic rate-distortion theory. The latter is based on the noncomputable notion of Kolmogorov complexity. To apply the theory we approximate the Kolmogorov complexity by standard data compression techniques, and perform a number of experiments with lossy compression and denoising of objects from different domains. We also introduce a natural generalization to lossy compression with side information. To maintain full generality we need to address a difficult searching problem. While our solutions are therefore not time efficient, we do observe good denoising and compression performance. | Approximating Rate-Distortion Graphs of Individual Data: Experiments in
Lossy Compression and Denoising | 7,292 |
We consider a general multiple antenna network with multiple sources, multiple destinations and multiple relays in terms of the diversity-multiplexing tradeoff (DMT). We examine several subcases of this most general problem taking into account the processing capability of the relays (half-duplex or full-duplex), and the network geometry (clustered or non-clustered). We first study the multiple antenna relay channel with a full-duplex relay to understand the effect of increased degrees of freedom in the direct link. We find DMT upper bounds and investigate the achievable performance of decode-and-forward (DF), and compress-and-forward (CF) protocols. Our results suggest that while DF is DMT optimal when all terminals have one antenna each, it may not maintain its good performance when the degrees of freedom in the direct link is increased, whereas CF continues to perform optimally. We also study the multiple antenna relay channel with a half-duplex relay. We show that the half-duplex DMT behavior can significantly be different from the full-duplex case. We find that CF is DMT optimal for half-duplex relaying as well, and is the first protocol known to achieve the half-duplex relay DMT. We next study the multiple-access relay channel (MARC) DMT. Finally, we investigate a system with a single source-destination pair and multiple relays, each node with a single antenna, and show that even under the idealistic assumption of full-duplex relays and a clustered network, this virtual multi-input multi-output (MIMO) system can never fully mimic a real MIMO DMT. For cooperative systems with multiple sources and multiple destinations the same limitation remains to be in effect. | Multi-Antenna Cooperative Wireless Systems: A Diversity-Multiplexing
Tradeoff Perspective | 7,293 |
In the design of multiple description lattice vector quantizers (MDLVQ), index assignment plays a critical role. In addition, one also needs to choose the Voronoi cell size of the central lattice v, the sublattice index N, and the number of side descriptions K to minimize the expected MDLVQ distortion, given the total entropy rate of all side descriptions Rt and description loss probability p. In this paper we propose a linear-time MDLVQ index assignment algorithm for any K >= 2 balanced descriptions in any dimensions, based on a new construction of so-called K-fraction lattice. The algorithm is greedy in nature but is proven to be asymptotically (N -> infinity) optimal for any K >= 2 balanced descriptions in any dimensions, given Rt and p. The result is stronger when K = 2: the optimality holds for finite N as well, under some mild conditions. For K > 2, a local adjustment algorithm is developed to augment the greedy index assignment, and conjectured to be optimal for finite N. Our algorithmic study also leads to better understanding of v, N and K in optimal MDLVQ design. For K = 2 we derive, for the first time, a non-asymptotical closed form expression of the expected distortion of optimal MDLVQ in p, Rt, N. For K > 2, we tighten the current asymptotic formula of the expected distortion, relating the optimal values of N and K to p and Rt more precisely. | Optimal Design of Multiple Description Lattice Vector Quantizers | 7,294 |
We refine and extend an earlier MDL denoising criterion for wavelet-based denoising. We start by showing that the denoising problem can be reformulated as a clustering problem, where the goal is to obtain separate clusters for informative and non-informative wavelet coefficients, respectively. This suggests two refinements, adding a code-length for the model index, and extending the model in order to account for subband-dependent coefficient distributions. A third refinement is derivation of soft thresholding inspired by predictive universal coding with weighted mixtures. We propose a practical method incorporating all three refinements, which is shown to achieve good performance and robustness in denoising both artificial and natural signals. | MDL Denoising Revisited | 7,295 |
We introduce a general framework for treating channels with memory and feedback. First, we generalize Massey's concept of directed information and use it to characterize the feedback capacity of general channels. Second, we present coding results for Markov channels. This requires determining appropriate sufficient statistics at the encoder and decoder. Third, a dynamic programming framework for computing the capacity of Markov channels is presented. Fourth, it is shown that the average cost optimality equation (ACOE) can be viewed as an implicit single-letter characterization of the capacity. Fifth, scenarios with simple sufficient statistics are described. | The Capacity of Channels with Feedback | 7,296 |
An elementary combinatorial Tanner graph construction for a family of near-regular low density parity check codes achieving high girth is presented. The construction allows flexibility in the choice of design parameters like rate, average degree, girth and block length of the code and yields an asymptotic family. The complexity of constructing codes in the family grows only quadratically with the block length. | A Combinatorial Family of Near Regular LDPC Codes | 7,297 |
Message-passing iterative decoders for low-density parity-check (LDPC) block codes are known to be subject to decoding failures due to so-called pseudo-codewords. These failures can cause the large signal-to-noise ratio performance of message-passing iterative decoding to be worse than that predicted by the maximum-likelihood decoding union bound. In this paper we address the pseudo-codeword problem from the convolutional-code perspective. In particular, we compare the performance of LDPC convolutional codes with that of their ``wrapped'' quasi-cyclic block versions and we show that the minimum pseudo-weight of an LDPC convolutional code is at least as large as the minimum pseudo-weight of an underlying quasi-cyclic code. This result, which parallels a well-known relationship between the minimum Hamming weight of convolutional codes and the minimum Hamming weight of their quasi-cyclic counterparts, is due to the fact that every pseudo-codeword in the convolutional code induces a pseudo-codeword in the block code with pseudo-weight no larger than that of the convolutional code's pseudo-codeword. This difference in the weight spectra leads to improved performance at low-to-moderate signal-to-noise ratios for the convolutional code, a conclusion supported by simulation results. | Pseudo-Codeword Performance Analysis for LDPC Convolutional Codes | 7,298 |
We present a novel iterative algorithm for detection of binary Markov random fields (MRFs) corrupted by two-dimensional (2D) intersymbol interference (ISI) and additive white Gaussian noise (AWGN). We assume a first-order binary MRF as a simple model for correlated images. We assume a 2D digital storage channel, where the MRF is interleaved before being written and then read by a 2D transducer; such channels occur in recently proposed optical disk storage systems. The detection algorithm is a concatenation of two soft-input/soft-output (SISO) detectors: an iterative row-column soft-decision feedback (IRCSDF) ISI detector, and a MRF detector. The MRF detector is a SISO version of the stochastic relaxation algorithm by Geman and Geman in IEEE Trans. Pattern Anal. and Mach. Intell., Nov. 1984. On the 2 x 2 averaging-mask ISI channel, at a bit error rate (BER) of 10^{-5}, the concatenated algorithm achieves SNR savings of between 0.5 and 2.0 dB over the IRCSDF detector alone; the savings increase as the MRFs become more correlated, or as the SNR decreases. The algorithm is also fairly robust to mismatches between the assumed and actual MRF parameters. | Detection of Markov Random Fields on Two-Dimensional Intersymbol
Interference Channels | 7,299 |
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