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This paper studies on-chip communication with non-ideal heat sinks. A channel model is proposed where the variance of the additive noise depends on the weighted sum of the past channel input powers. It is shown that, depending on the weights, the capacity can be either bounded or unbounded in the input power. A necessary condition and a sufficient condition for the capacity to be bounded are presented. | A Hot Channel | 7,500 |
Sparse Code Division Multiple Access (CDMA), a variation on the standard CDMA method in which the spreading (signature) matrix contains only a relatively small number of non-zero elements, is presented and analysed using methods of statistical physics. The analysis provides results on the performance of maximum likelihood decoding for sparse spreading codes in the large system limit. We present results for both cases of regular and irregular spreading matrices for the binary additive white Gaussian noise channel (BIAWGN) with a comparison to the canonical (dense) random spreading code. | Sparsely-spread CDMA - a statistical mechanics based analysis | 7,501 |
Given a multiple-input multiple-output (MIMO) channel, feedback from the receiver can be used to specify a transmit precoding matrix, which selectively activates the strongest channel modes. Here we analyze the performance of Random Vector Quantization (RVQ), in which the precoding matrix is selected from a random codebook containing independent, isotropically distributed entries. We assume that channel elements are i.i.d. and known to the receiver, which relays the optimal (rate-maximizing) precoder codebook index to the transmitter using B bits. We first derive the large system capacity of beamforming (rank-one precoding matrix) as a function of B, where large system refers to the limit as B and the number of transmit and receive antennas all go to infinity with fixed ratios. With beamforming RVQ is asymptotically optimal, i.e., no other quantization scheme can achieve a larger asymptotic rate. The performance of RVQ is also compared with that of a simpler reduced-rank scalar quantization scheme in which the beamformer is constrained to lie in a random subspace. We subsequently consider a precoding matrix with arbitrary rank, and approximate the asymptotic RVQ performance with optimal and linear receivers (matched filter and Minimum Mean Squared Error (MMSE)). Numerical examples show that these approximations accurately predict the performance of finite-size systems of interest. Given a target spectral efficiency, numerical examples show that the amount of feedback required by the linear MMSE receiver is only slightly more than that required by the optimal receiver, whereas the matched filter can require significantly more feedback. | Capacity of a Multiple-Antenna Fading Channel with a Quantized Precoding
Matrix | 7,502 |
It has been observed that particular rate-1/2 partially systematic parallel concatenated convolutional codes (PCCCs) can achieve a lower error floor than that of their rate-1/3 parent codes. Nevertheless, good puncturing patterns can only be identified by means of an exhaustive search, whilst convergence towards low bit error probabilities can be problematic when the systematic output of a rate-1/2 partially systematic PCCC is heavily punctured. In this paper, we present and study a family of rate-1/2 partially systematic PCCCs, which we call pseudo-randomly punctured codes. We evaluate their bit error rate performance and we show that they always yield a lower error floor than that of their rate-1/3 parent codes. Furthermore, we compare analytic results to simulations and we demonstrate that their performance converges towards the error floor region, owning to the moderate puncturing of their systematic output. Consequently, we propose pseudo-random puncturing as a means of improving the bandwidth efficiency of a PCCC and simultaneously lowering its error floor. | Pseudo-random Puncturing: A Technique to Lower the Error Floor of Turbo
Codes | 7,503 |
We investigate cooperative wireless relay networks in which the nodes can help each other in data transmission. We study different coding strategies in the single-source single-destination network with many relay nodes. Given the myriad of ways in which nodes can cooperate, there is a natural routing problem, i.e., determining an ordered set of nodes to relay the data from the source to the destination. We find that for a given route, the decode-and-forward strategy, which is an information theoretic cooperative coding strategy, achieves rates significantly higher than that achievable by the usual multi-hop coding strategy, which is a point-to-point non-cooperative coding strategy. We construct an algorithm to find an optimal route (in terms of rate maximizing) for the decode-and-forward strategy. Since the algorithm runs in factorial time in the worst case, we propose a heuristic algorithm that runs in polynomial time. The heuristic algorithm outputs an optimal route when the nodes transmit independent codewords. We implement these coding strategies using practical low density parity check codes to compare the performance of the strategies on different routes. | Optimal Routing for Decode-and-Forward based Cooperation in Wireless
Networks | 7,504 |
The interference channel with degraded message sets (IC-DMS) refers to a communication model in which two senders attempt to communicate with their respective receivers simultaneously through a common medium, and one of the senders has complete and a priori (non-causal) knowledge about the message being transmitted by the other. A coding scheme that collectively has advantages of cooperative coding, collaborative coding, and dirty paper coding, is developed for such a channel. With resorting to this coding scheme, achievable rate regions of the IC-DMS in both discrete memoryless and Gaussian cases are derived, which, in general, include several previously known rate regions. Numerical examples for the Gaussian case demonstrate that in the high-interference-gain regime, the derived achievable rate regions offer considerable improvements over these existing results. | On the Achievable Rate Regions for Interference Channels with Degraded
Message Sets | 7,505 |
We present an algorithm for systematic encoding of Hermitian codes. For a Hermitian code defined over GF(q^2), the proposed algorithm achieves a run time complexity of O(q^2) and is suitable for VLSI implementation. The encoder architecture uses as main blocks q varying-rate Reed-Solomon encoders and achieves a space complexity of O(q^2) in terms of finite field multipliers and memory elements. | A Low Complexity Algorithm and Architecture for Systematic Encoding of
Hermitian Codes | 7,506 |
This paper develops a contention-based opportunistic feedback technique towards relay selection in a dense wireless network. This technique enables the forwarding of additional parity information from the selected relay to the destination. For a given network, the effects of varying key parameters such as the feedback probability are presented and discussed. A primary advantage of the proposed technique is that relay selection can be performed in a distributed way. Simulation results find its performance to closely match that of centralized schemes that utilize GPS information, unlike the proposed method. The proposed relay selection method is also found to achieve throughput gains over a point-to-point transmission strategy. | Hybrid-ARQ in Multihop Networks with Opportunistic Relay Selection | 7,507 |
It has been shown that a decentralized relay selection protocol based on opportunistic feedback from the relays yields good throughput performance in dense wireless networks. This selection strategy supports a hybrid-ARQ transmission approach where relays forward parity information to the destination in the event of a decoding error. Such an approach, however, suffers a loss compared to centralized strategies that select relays with the best channel gain to the destination. This paper closes the performance gap by adding another level of channel feedback to the decentralized relay selection problem. It is demonstrated that only one additional bit of feedback is necessary for good throughput performance. The performance impact of varying key parameters such as the number of relays and the channel feedback threshold is discussed. An accompanying bit error rate analysis demonstrates the importance of relay selection. | Opportunistic Relay Selection with Limited Feedback | 7,508 |
We assess the practicality of random network coding by illuminating the issue of overhead and considering it in conjunction with increasingly long packets sent over the erasure channel. We show that the transmission of increasingly long packets, consisting of either of an increasing number of symbols per packet or an increasing symbol alphabet size, results in a data rate approaching zero over the erasure channel. This result is due to an erasure probability that increases with packet length. Numerical results for a particular modulation scheme demonstrate a data rate of approximately zero for a large, but finite-length packet. Our results suggest a reduction in the performance gains offered by random network coding. | On packet lengths and overhead for random linear coding over the erasure
channel | 7,509 |
We study universal compression of sequences generated by monotonic distributions. We show that for a monotonic distribution over an alphabet of size $k$, each probability parameter costs essentially $0.5 \log (n/k^3)$ bits, where $n$ is the coded sequence length, as long as $k = o(n^{1/3})$. Otherwise, for $k = O(n)$, the total average sequence redundancy is $O(n^{1/3+\epsilon})$ bits overall. We then show that there exists a sub-class of monotonic distributions over infinite alphabets for which redundancy of $O(n^{1/3+\epsilon})$ bits overall is still achievable. This class contains fast decaying distributions, including many distributions over the integers and geometric distributions. For some slower decays, including other distributions over the integers, redundancy of $o(n)$ bits overall is achievable, where a method to compute specific redundancy rates for such distributions is derived. The results are specifically true for finite entropy monotonic distributions. Finally, we study individual sequence redundancy behavior assuming a sequence is governed by a monotonic distribution. We show that for sequences whose empirical distributions are monotonic, individual redundancy bounds similar to those in the average case can be obtained. However, even if the monotonicity in the empirical distribution is violated, diminishing per symbol individual sequence redundancies with respect to the monotonic maximum likelihood description length may still be achievable. | Universal Source Coding for Monotonic and Fast Decaying Monotonic
Distributions | 7,510 |
A multiple antenna downlink channel where limited channel feedback is available to the transmitter is considered. In a vector downlink channel (single antenna at each receiver), the transmit antenna array can be used to transmit separate data streams to multiple receivers only if the transmitter has very accurate channel knowledge, i.e., if there is high-rate channel feedback from each receiver. In this work it is shown that channel feedback requirements can be significantly reduced if each receiver has a small number of antennas and appropriately combines its antenna outputs. A combining method that minimizes channel quantization error at each receiver, and thereby minimizes multi-user interference, is proposed and analyzed. This technique is shown to outperform traditional techniques such as maximum-ratio combining because minimization of interference power is more critical than maximization of signal power in the multiple antenna downlink. Analysis is provided to quantify the feedback savings, and the technique is seen to work well with user selection and is also robust to receiver estimation error. | Antenna Combining for the MIMO Downlink Channel | 7,511 |
Low density lattice codes (LDLC) are novel lattice codes that can be decoded efficiently and approach the capacity of the additive white Gaussian noise (AWGN) channel. In LDLC a codeword x is generated directly at the n-dimensional Euclidean space as a linear transformation of a corresponding integer message vector b, i.e., x = Gb, where H, the inverse of G, is restricted to be sparse. The fact that H is sparse is utilized to develop a linear-time iterative decoding scheme which attains, as demonstrated by simulations, good error performance within ~0.5dB from capacity at block length of n = 100,000 symbols. The paper also discusses convergence results and implementation considerations. | Low Density Lattice Codes | 7,512 |
Most design approaches for trellis-coded quantization take advantage of the duality of trellis-coded quantization with trellis-coded modulation, and use the same empirically-found convolutional codes to label the trellis branches. This letter presents an alternative approach that instead takes advantage of maximum-Hamming-distance convolutional codes. The proposed source codes are shown to be competitive with the best in the literature for the same computational complexity. | Trellis-Coded Quantization Based on Maximum-Hamming-Distance Binary
Codes | 7,513 |
We consider the problem of estimating the probability of an observed string drawn i.i.d. from an unknown distribution. The key feature of our study is that the length of the observed string is assumed to be of the same order as the size of the underlying alphabet. In this setting, many letters are unseen and the empirical distribution tends to overestimate the probability of the observed letters. To overcome this problem, the traditional approach to probability estimation is to use the classical Good-Turing estimator. We introduce a natural scaling model and use it to show that the Good-Turing sequence probability estimator is not consistent. We then introduce a novel sequence probability estimator that is indeed consistent under the natural scaling model. | A Better Good-Turing Estimator for Sequence Probabilities | 7,514 |
This paper presents new low-complexity lattice-decoding algorithms for noncoherent block detection of QAM and PAM signals over complex-valued fading channels. The algorithms are optimal in terms of the generalized likelihood ratio test (GLRT). The computational complexity is polynomial in the block length; making GLRT-optimal noncoherent detection feasible for implementation. We also provide even lower complexity suboptimal algorithms. Simulations show that the suboptimal algorithms have performance indistinguishable from the optimal algorithms. Finally, we consider block based transmission, and propose to use noncoherent detection as an alternative to pilot assisted transmission (PAT). The new technique is shown to outperform PAT. | GLRT-Optimal Noncoherent Lattice Decoding | 7,515 |
While most useful information theoretic inequalities can be deduced from the basic properties of entropy or mutual information, up to now Shannon's entropy power inequality (EPI) is an exception: Existing information theoretic proofs of the EPI hinge on representations of differential entropy using either Fisher information or minimum mean-square error (MMSE), which are derived from de Bruijn's identity. In this paper, we first present an unified view of these proofs, showing that they share two essential ingredients: 1) a data processing argument applied to a covariance-preserving linear transformation; 2) an integration over a path of a continuous Gaussian perturbation. Using these ingredients, we develop a new and brief proof of the EPI through a mutual information inequality, which replaces Stam and Blachman's Fisher information inequality (FII) and an inequality for MMSE by Guo, Shamai and Verd\'u used in earlier proofs. The result has the advantage of being very simple in that it relies only on the basic properties of mutual information. These ideas are then generalized to various extended versions of the EPI: Zamir and Feder's generalized EPI for linear transformations of the random variables, Takano and Johnson's EPI for dependent variables, Liu and Viswanath's covariance-constrained EPI, and Costa's concavity inequality for the entropy power. | Information Theoretic Proofs of Entropy Power Inequalities | 7,516 |
We describe and analyze the joint source/channel coding properties of a class of sparse graphical codes based on compounding a low-density generator matrix (LDGM) code with a low-density parity check (LDPC) code. Our first pair of theorems establish that there exist codes from this ensemble, with all degrees remaining bounded independently of block length, that are simultaneously optimal as both source and channel codes when encoding and decoding are performed optimally. More precisely, in the context of lossy compression, we prove that finite degree constructions can achieve any pair $(R, D)$ on the rate-distortion curve of the binary symmetric source. In the context of channel coding, we prove that finite degree codes can achieve any pair $(C, p)$ on the capacity-noise curve of the binary symmetric channel. Next, we show that our compound construction has a nested structure that can be exploited to achieve the Wyner-Ziv bound for source coding with side information (SCSI), as well as the Gelfand-Pinsker bound for channel coding with side information (CCSI). Although the current results are based on optimal encoding and decoding, the proposed graphical codes have sparse structure and high girth that renders them well-suited to message-passing and other efficient decoding procedures. | Low-density graph codes that are optimal for source/channel coding and
binning | 7,517 |
In this paper, we propose an achievable rate region for discrete memoryless interference channels with conferencing at the transmitter side. We employ superposition block Markov encoding, combined with simultaneous superposition coding, dirty paper coding, and random binning to obtain the achievable rate region. We show that, under respective conditions, the proposed achievable region reduces to Han and Kobayashi achievable region for interference channels, the capacity region for degraded relay channels, and the capacity region for the Gaussian vector broadcast channel. Numerical examples for the Gaussian case are given. | An Achievable Rate Region for Interference Channels with Conferencing | 7,518 |
In spatially distributed multiuser antenna systems, the received signal contains multiple carrier-frequency offsets (CFOs) arising from mismatch between the oscillators of transmitters and receivers. This results in a time-varying rotation of the data constellation, which needs to be compensated at the receiver before symbol recovery. In this paper, a new approach for blind CFO estimation and symbol recovery is proposed. The received base-band signal is over-sampled, and its polyphase components are used to formulate a virtual Multiple-Input Multiple-Output (MIMO) problem. By applying blind MIMO system estimation techniques, the system response can be estimated and decoupled versions of the user symbols can be recovered, each one of which contains a distinct CFO. By applying a decision feedback Phase Lock Loop (PLL), the CFO can be mitigated and the transmitted symbols can be recovered. The estimated MIMO system response provides information about the CFOs that can be used to initialize the PLL, speed up its convergence, and avoid ambiguities usually linked with PLL. | Blind Identification of Distributed Antenna Systems with Multiple
Carrier Frequency Offsets | 7,519 |
We prove that approximating the size of stopping and trapping sets in Tanner graphs of linear block codes, and more restrictively, the class of low-density parity-check (LDPC) codes, is NP-hard. The ramifications of our findings are that methods used for estimating the height of the error-floor of moderate- and long-length LDPC codes based on stopping and trapping set enumeration cannot provide accurate worst-case performance predictions. | On the Hardness of Approximating Stopping and Trapping Sets in LDPC
Codes | 7,520 |
We consider a cognitive network consisting of n random pairs of cognitive transmitters and receivers communicating simultaneously in the presence of multiple primary users. Of interest is how the maximum throughput achieved by the cognitive users scales with n. Furthermore, how far these users must be from a primary user to guarantee a given primary outage. Two scenarios are considered for the network scaling law: (i) when each cognitive transmitter uses constant power to communicate with a cognitive receiver at a bounded distance away, and (ii) when each cognitive transmitter scales its power according to the distance to a considered primary user, allowing the cognitive transmitter-receiver distances to grow. Using single-hop transmission, suitable for cognitive devices of opportunistic nature, we show that, in both scenarios, with path loss larger than 2, the cognitive network throughput scales linearly with the number of cognitive users. We then explore the radius of a primary exclusive region void of cognitive transmitters. We obtain bounds on this radius for a given primary outage constraint. These bounds can help in the design of a primary network with exclusive regions, outside of which cognitive users may transmit freely. Our results show that opportunistic secondary spectrum access using single-hop transmission is promising. | Scaling Laws of Cognitive Networks | 7,521 |
Power control is a fundamental task accomplished in any wireless cellular network; its aim is to set the transmit power of any mobile terminal, so that each user is able to achieve its own target SINR. While conventional power control algorithms require knowledge of a number of parameters of the signal of interest and of the multiaccess interference, in this paper it is shown that in a large CDMA system much of this information can be dispensed with, and effective distributed power control algorithms may be implemented with very little information on the user of interest. An uplink CDMA system subject to flat fading is considered with a focus on the cases in which a linear MMSE receiver and a non-linear MMSE serial interference cancellation receiver are adopted; for the latter case new formulas are also given for the system SINR in the large system asymptote. Experimental results show an excellent agreement between the performance and the power profile of the proposed distributed algorithms and that of conventional ones that require much greater prior knowledge. | Power control algorithms for CDMA networks based on large system
analysis | 7,522 |
This paper is focused on the cross-layer design problem of joint multiuser detection and power control for energy-efficiency optimization in a wireless data network through a game-theoretic approach. Building on work of Meshkati, et al., wherein the tools of game-theory are used in order to achieve energy-efficiency in a simple synchronous code division multiple access system, system asynchronism, the use of bandlimited chip-pulses, and the multipath distortion induced by the wireless channel are explicitly incorporated into the analysis. Several non-cooperative games are proposed wherein users may vary their transmit power and their uplink receiver in order to maximize their utility, which is defined here as the ratio of data throughput to transmit power. In particular, the case in which a linear multiuser detector is adopted at the receiver is considered first, and then, the more challenging case in which non-linear decision feedback multiuser detectors are employed is considered. The proposed games are shown to admit a unique Nash equilibrium point, while simulation results show the effectiveness of the proposed solutions, as well as that the use of a decision-feedback multiuser receiver brings remarkable performance improvements. | Power control and receiver design for energy efficiency in multipath
CDMA channels with bandlimited waveforms | 7,523 |
On a fading channel with no channel state information at the receiver, calculating true log-likelihood ratios (LLR) is complicated. Existing work assume that the power of the additive noise is known and use the expected value of the fading gain in a linear function of the channel output to find approximate LLRs. In this work, we first assume that the power of the additive noise is known and we find the optimum linear approximation of LLRs in the sense of maximum achievable transmission rate on the channel. The maximum achievable rate under this linear LLR calculation is almost equal to the maximum achievable rate under true LLR calculation. We also observe that this method appears to be the optimum in the sense of bit error rate performance too. These results are then extended to the case that the noise power is unknown at the receiver and a performance almost identical to the case that the noise power is perfectly known is obtained. | Optimum Linear LLR Calculation for Iterative Decoding on Fading Channels | 7,524 |
A main distinguishing feature of a wireless network compared with a wired network is its broadcast nature, in which the signal transmitted by a node may reach several other nodes, and a node may receive signals from several other nodes simultaneously. Rather than a blessing, this feature is treated more as an interference-inducing nuisance in most wireless networks today (e.g., IEEE 802.11). This paper shows that the concept of network coding can be applied at the physical layer to turn the broadcast property into a capacity-boosting advantage in wireless ad hoc networks. Specifically, we propose a physical-layer network coding (PNC) scheme to coordinate transmissions among nodes. In contrast to straightforward network coding which performs coding arithmetic on digital bit streams after they have been received, PNC makes use of the additive nature of simultaneously arriving electromagnetic (EM) waves for equivalent coding operation. And in doing so, PNC can potentially achieve 100% and 50% throughput increases compared with traditional transmission and straightforward network coding, respectively, in multi-hop networks. More specifically, the information-theoretic capacity of PNC is almost double that of traditional transmission in the SNR region of practical interest (higher than 0dB). We believe this is a first paper that ventures into EM-wave-based network coding at the physical layer and demonstrates its potential for boosting network capacity. | Physical Layer Network Coding | 7,525 |
The problem of designing high rate, full diversity noncoherent space-time block codes (STBCs) with low encoding and decoding complexity is addressed. First, the notion of $g$-group encodable and $g$-group decodable linear STBCs is introduced. Then for a known class of rate-1 linear designs, an explicit construction of fully-diverse signal sets that lead to four-group encodable and four-group decodable differential scaled unitary STBCs for any power of two number of antennas is provided. Previous works on differential STBCs either sacrifice decoding complexity for higher rate or sacrifice rate for lower decoding complexity. | Signal Set Design for Full-Diversity Low-Decoding-Complexity
Differential Scaled-Unitary STBCs | 7,526 |
The differential encoding/decoding setup introduced by Kiran et al, Oggier et al and Jing et al for wireless relay networks that use codebooks consisting of unitary matrices is extended to allow codebooks consisting of scaled unitary matrices. For such codebooks to be used in the Jing-Hassibi protocol for cooperative diversity, the conditions that need to be satisfied by the relay matrices and the codebook are identified. A class of previously known rate one, full diversity, four-group encodable and four-group decodable Differential Space-Time Codes (DSTCs) is proposed for use as Distributed DSTCs (DDSTCs) in the proposed set up. To the best of our knowledge, this is the first known low decoding complexity DDSTC scheme for cooperative wireless networks. | Noncoherent Low-Decoding-Complexity Space-Time Codes for Wireless Relay
Networks | 7,527 |
The Extended BP (EBP) Generalized EXIT (GEXIT) function introduced in \cite{MMRU05} plays a fundamental role in the asymptotic analysis of sparse graph codes. For transmission over the binary erasure channel (BEC) the analytic properties of the EBP GEXIT function are relatively simple and well understood. The general case is much harder and even the existence of the curve is not known in general. We introduce some tools from non-linear analysis which can be useful to prove the existence of EXIT like curves in some cases. The main tool is the Krasnoselskii-Rabinowitz (KR) bifurcation theorem. | Existence Proofs of Some EXIT Like Functions | 7,528 |
The problem of resource allocation is studied for a two-user fading orthogonal multiaccess relay channel (MARC) where both users (sources) communicate with a destination in the presence of a relay. A half-duplex relay is considered that transmits on a channel orthogonal to that used by the sources. The instantaneous fading state between every transmit-receive pair in this network is assumed to be known at both the transmitter and receiver. Under an average power constraint at each source and the relay, the sum-rate for the achievable strategy of decode-and-forward (DF) is maximized over all power allocations (policies) at the sources and relay. It is shown that the sum-rate maximizing policy exploits the multiuser fading diversity to reveal the optimality of opportunistic channel use by each user. A geometric interpretation of the optimal power policy is also presented. | Opportunistic Communications in an Orthogonal Multiaccess Relay Channel | 7,529 |
A transmitter without channel state information (CSI) wishes to send a delay-limited Gaussian source over a slowly fading channel. The source is coded in superimposed layers, with each layer successively refining the description in the previous one. The receiver decodes the layers that are supported by the channel realization and reconstructs the source up to a distortion. In the limit of a continuum of infinite layers, the optimal power distribution that minimizes the expected distortion is given by the solution to a set of linear differential equations in terms of the density of the fading distribution. In the optimal power distribution, as SNR increases, the allocation over the higher layers remains unchanged; rather the extra power is allocated towards the lower layers. On the other hand, as the bandwidth ratio b (channel uses per source symbol) tends to zero, the power distribution that minimizes expected distortion converges to the power distribution that maximizes expected capacity. While expected distortion can be improved by acquiring CSI at the transmitter (CSIT) or by increasing diversity from the realization of independent fading paths, at high SNR the performance benefit from diversity exceeds that from CSIT, especially when b is large. | Minimum Expected Distortion in Gaussian Layered Broadcast Coding with
Successive Refinement | 7,530 |
Motivated by on-chip communication, a channel model is proposed where the variance of the additive noise depends on the weighted sum of the past channel input powers. For this channel, an expression for the capacity per unit cost is derived, and it is shown that the expression holds also in the presence of feedback. | A Channel that Heats Up | 7,531 |
A wireless network in which packets are broadcast to a group of receivers through use of a random access protocol is considered in this work. The relation to previous work on networks of interacting queues is discussed and subsequently, the stability and throughput regions of the system are analyzed and presented. A simple network of two source nodes and two destination nodes is considered first. The broadcast service process is analyzed assuming a channel that allows for packet capture and multipacket reception. In this small network, the stability and throughput regions are observed to coincide. The same problem for a network with N sources and M destinations is considered next. The channel model is simplified in that multipacket reception is no longer permitted. Bounds on the stability region are developed using the concept of stability rank and the throughput region of the system is compared to the bounds. Our results show that as the number of destination nodes increases, the stability and throughput regions diminish. Additionally, a previous conjecture that the stability and throughput regions coincide for a network of arbitrarily many sources is supported for a broadcast scenario by the results presented in this work. | Random Access Broadcast: Stability and Throughput Analysis | 7,532 |
This paper studies a variant of the classical problem of ``writing on dirty paper'' in which the sum of the input and the interference, or dirt, is multiplied by a random variable that models resizing, known to the decoder but not to the encoder. The achievable rate of Costa's dirty paper coding (DPC) scheme is calculated and compared to the case of the decoder's also knowing the dirt. In the ergodic case, the corresponding rate loss vanishes asymptotically in the limits of both high and low signal-to-noise ratio (SNR), and is small at all finite SNR for typical distributions like Rayleigh, Rician, and Nakagami. In the quasi-static case, the DPC scheme is lossless at all SNR in terms of outage probability. Quasi-static fading broadcast channels (BC) without transmit channel state information (CSI) are investigated as an application of the robustness properties. It is shown that the DPC scheme leads to an outage achievable rate region that strictly dominates that of time division. | Writing on Dirty Paper with Resizing and its Application to Quasi-Static
Fading Broadcast Channels | 7,533 |
In wireless ad hoc networks, distributed nodes can collaboratively form an antenna array for long-distance communications to achieve high energy efficiency. In recent work, Ochiai, et al., have shown that such collaborative beamforming can achieve a statistically nice beampattern with a narrow main lobe and low sidelobes. However, the process of collaboration introduces significant delay, since all collaborating nodes need access to the same information. In this paper, a technique that significantly reduces the collaboration overhead is proposed. It consists of two phases. In the first phase, nodes transmit locally in a random access fashion. Collisions, when they occur, are viewed as linear mixtures of the collided packets. In the second phase, a set of cooperating nodes acts as a distributed antenna system and beamform the received analog waveform to one or more faraway destinations. This step requires multiplication of the received analog waveform by a complex number, which is independently computed by each cooperating node, and which enables separation of the collided packets based on their final destination. The scheme requires that each node has global knowledge of the network coordinates. The proposed scheme can achieve high throughput, which in certain cases exceeds one. | A High-Throughput Cross-Layer Scheme for Distributed Wireless Ad Hoc
Networks | 7,534 |
In this paper, we study a routing problem on the Gaussian multiple relay channel, in which nodes employ a decode-and-forward coding strategy. We are interested in routes for the information flow through the relays that achieve the highest DF rate. We first construct an algorithm that provably finds optimal DF routes. As the algorithm runs in factorial time in the worst case, we propose a polynomial time heuristic algorithm that finds an optimal route with high probability. We demonstrate that that the optimal (and near optimal) DF routes are good in practice by simulating a distributed DF coding scheme using low density parity check codes with puncturing and incremental redundancy. | Optimal Routing for the Gaussian Multiple-Relay Channel with
Decode-and-Forward | 7,535 |
In this paper non-group permutation modulated sequences for the Gaussian channel are considered. Without the restriction to group codes rather than subsets of group codes, arbitrary rates are achievable. The code construction utilizes the known optimal group constellations to ensure at least the same performance but exploit the Gray code ordering structure of multiset permutations as a selection criterion at the decoder. The decoder achieves near maximum likelihood performance at low computational cost and low additional memory requirements at the receiver. | Arbitrary Rate Permutation Modulation for the Gaussian Channel | 7,536 |
This work examines the problem of sequential detection of a change in the drift of a Brownian motion in the case of two-sided alternatives. Applications to real life situations in which two-sided changes can occur are discussed. Traditionally, 2-CUSUM stopping rules have been used for this problem due to their asymptotically optimal character as the mean time between false alarms tends to $\infty$. In particular, attention has focused on 2-CUSUM harmonic mean rules due to the simplicity in calculating their first moments. In this paper, we derive closed-form expressions for the first moment of a general 2-CUSUM stopping rule. We use these expressions to obtain explicit upper and lower bounds for it. Moreover, we derive an expression for the rate of change of this first moment as one of the threshold parameters changes. Based on these expressions we obtain explicit upper and lower bounds to this rate of change. Using these expressions we are able to find the best 2-CUSUM stopping rule with respect to the extended Lorden criterion. In fact, we demonstrate not only the existence but also the uniqueness of the best 2-CUSUM stopping both in the case of a symmetric change and in the case of a non-symmetric case. Furthermore, we discuss the existence of a modification of the 2-CUSUM stopping rule that has a strictly better performance than its classical 2-CUSUM counterpart for small values of the mean time between false alarms. We conclude with a discussion on the open problem of strict optimality in the case of two-sided alternatives. | Detection of two-sided alternatives in a Brownian motion model | 7,537 |
A new class of space time codes with high performance is presented. The code design utilizes tailor-made permutation codes, which are known to have large minimal distances as spherical codes. A geometric connection between spherical and space time codes has been used to translate them into the final space time codes. Simulations demonstrate that the performance increases with the block lengths, a result that has been conjectured already in previous work. Further, the connection to permutation codes allows for moderate complex en-/decoding algorithms. | Space Time Codes from Permutation Codes | 7,538 |
In this paper, the stability condition for low-density parity-check (LDPC) codes on the binary erasure channel (BEC) is extended to generalized LDPC (GLDPC) codes and doublygeneralized LDPC (D-GLDPC) codes. It is proved that, in both cases, the stability condition only involves the component codes with minimum distance 2. The stability condition for GLDPC codes is always expressed as an upper bound to the decoding threshold. This is not possible for D-GLDPC codes, unless all the generalized variable nodes have minimum distance at least 3. Furthermore, a condition called derivative matching is defined in the paper. This condition is sufficient for a GLDPC or DGLDPC code to achieve the stability condition with equality. If this condition is satisfied, the threshold of D-GLDPC codes (whose generalized variable nodes have all minimum distance at least 3) and GLDPC codes can be expressed in closed form. | Generalized Stability Condition for Generalized and Doubly-Generalized
LDPC Codes | 7,539 |
We examine the problem of determining which nodes are neighbors of a given one in a wireless network. We consider an unsupervised network operating on a frequency-flat Gaussian channel, where $K+1$ nodes associate their identities to nonorthogonal signatures, transmitted at random times, synchronously, and independently. A number of neighbor-discovery algorithms, based on different optimization criteria, are introduced and analyzed. Numerical results show how reduced-complexity algorithms can achieve a satisfactory performance. | Neighbor Discovery in Wireless Networks:A Multiuser-Detection Approach | 7,540 |
The detection and estimation of signals in noisy, limited data is a problem of interest to many scientific and engineering communities. We present a computationally simple, sample eigenvalue based procedure for estimating the number of high-dimensional signals in white noise when there are relatively few samples. We highlight a fundamental asymptotic limit of sample eigenvalue based detection of weak high-dimensional signals from a limited sample size and discuss its implication for the detection of two closely spaced signals. This motivates our heuristic definition of the 'effective number of identifiable signals.' Numerical simulations are used to demonstrate the consistency of the algorithm with respect to the effective number of signals and the superior performance of the algorithm with respect to Wax and Kailath's "asymptotically consistent" MDL based estimator. | Sample size cognizant detection of signals in white noise | 7,541 |
In wireless packet-forwarding networks with selfish nodes, applications of a repeated game can induce the nodes to forward each others' packets, so that the network performance can be improved. However, the nodes on the boundary of such networks cannot benefit from this strategy, as the other nodes do not depend on them. This problem is sometimes known as the curse of the boundary nodes. To overcome this problem, an approach based on coalition games is proposed, in which the boundary nodes can use cooperative transmission to help the backbone nodes in the middle of the network. In return, the backbone nodes are willing to forward the boundary nodes' packets. The stability of the coalitions is studied using the concept of a core. Then two types of fairness, namely, the min-max fairness using nucleolus and the average fairness using the Shapley function are investigated. Finally, a protocol is designed using both repeated games and coalition games. Simulation results show how boundary nodes and backbone nodes form coalitions together according to different fairness criteria. The proposed protocol can improve the network connectivity by about 50%, compared with pure repeated game schemes. | Coalition Games with Cooperative Transmission: A Cure for the Curse of
Boundary Nodes in Selfish Packet-Forwarding Wireless Networks | 7,542 |
Collaborative beamforming (CB) and cooperative transmission (CT) have recently emerged as communication techniques that can make effective use of collaborative/cooperative nodes to create a virtual multiple-input/multiple-output (MIMO) system. Extending the lifetime of networks composed of battery-operated nodes is a key issue in the design and operation of wireless sensor networks. This paper considers the effects on network lifetime of allowing closely located nodes to use CB/CT to reduce the load or even to avoid packet-forwarding requests to nodes that have critical battery life. First, the effectiveness of CB/CT in improving the signal strength at a faraway destination using energy in nearby nodes is studied. Then, the performance improvement obtained by this technique is analyzed for a special 2D disk case. Further, for general networks in which information-generation rates are fixed, a new routing problem is formulated as a linear programming problem, while for other general networks, the cost for routing is dynamically adjusted according to the amount of energy remaining and the effectiveness of CB/CT. From the analysis and the simulation results, it is seen that the proposed method can reduce the payloads of energy-depleting nodes by about 90% in the special case network considered and improve the lifetimes of general networks by about 10%, compared with existing techniques. | Lifetime Improvement in Wireless Sensor Networks via Collaborative
Beamforming and Cooperative Transmission | 7,543 |
Extending network lifetime of battery-operated devices is a key design issue that allows uninterrupted information exchange among distributive nodes in wireless sensor networks. Collaborative beamforming (CB) and cooperative transmission (CT) have recently emerged as new communication techniques that enable and leverage effective resource sharing among collaborative/cooperative nodes. In this paper, we seek to maximize the lifetime of sensor networks by using the new idea that closely located nodes can use CB/CT to reduce the load or even avoid packet forwarding requests to nodes that have critical battery life. First, we study the effectiveness of CB/CT to improve the signal strength at a faraway destination using energy in nearby nodes. Then, a 2D disk case is analyzed to assess the resulting performance improvement. For general networks, if information-generation rates are fixed, the new routing problem is formulated as a linear programming problem; otherwise, the cost for routing is dynamically adjusted according to the amount of energy remaining and the effectiveness of CB/CT. From the analysis and simulation results, it is seen that the proposed schemes can improve the lifetime by about 90% in the 2D disk network and by about 10% in the general networks, compared to existing schemes. | Lifetime Improvement of Wireless Sensor Networks by Collaborative
Beamforming and Cooperative Transmission | 7,544 |
Cooperative transmission is an emerging communication technique that takes advantages of the broadcast nature of wireless channels. However, due to low spectral efficiency and the requirement of orthogonal channels, its potential for use in future wireless networks is limited. In this paper, by making use of multiuser detection (MUD) and network coding, cooperative transmission protocols with high spectral efficiency, diversity order, and coding gain are developed. Compared with the traditional cooperative transmission protocols with single-user detection, in which the diversity gain is only for one source user, the proposed MUD cooperative transmission protocols have the merits that the improvement of one user's link can also benefit the other users. In addition, using MUD at the relay provides an environment in which network coding can be employed. The coding gain and high diversity order can be obtained by fully utilizing the link between the relay and the destination. From the analysis and simulation results, it is seen that the proposed protocols achieve higher diversity gain, better asymptotic efficiency, and lower bit error rate, compared to traditional MUD and to existing cooperative transmission protocols. | Cooperative Transmission Protocols with High Spectral Efficiency and
High Diversity Order Using Multiuser Detection and Network Coding | 7,545 |
We establish the optimal diversity-multiplexing (DM) tradeoff of coherent time, frequency and time-frequency selective-fading MIMO channels and provide a code design criterion for DM-tradeoff optimality. Our results are based on the analysis of the "Jensen channel" associated to a given selective-fading MIMO channel. While the original problem seems analytically intractable due to the mutual information being a sum of correlated random variables, the Jensen channel is equivalent to the original channel in the sense of the DM-tradeoff and lends itself nicely to analytical treatment. Finally, as a consequence of our results, we find that the classical rank criterion for space-time code design (in selective-fading MIMO channels) ensures optimality in the sense of the DM-tradeoff. | Diversity-Multiplexing Tradeoff in Selective-Fading MIMO Channels | 7,546 |
Distributed estimation based on measurements from multiple wireless sensors is investigated. It is assumed that a group of sensors observe the same quantity in independent additive observation noises with possibly different variances. The observations are transmitted using amplify-and-forward (analog) transmissions over non-ideal fading wireless channels from the sensors to a fusion center, where they are combined to generate an estimate of the observed quantity. Assuming that the Best Linear Unbiased Estimator (BLUE) is used by the fusion center, the equal-power transmission strategy is first discussed, where the system performance is analyzed by introducing the concept of estimation outage and estimation diversity, and it is shown that there is an achievable diversity gain on the order of the number of sensors. The optimal power allocation strategies are then considered for two cases: minimum distortion under power constraints; and minimum power under distortion constraints. In the first case, it is shown that by turning off bad sensors, i.e., sensors with bad channels and bad observation quality, adaptive power gain can be achieved without sacrificing diversity gain. Here, the adaptive power gain is similar to the array gain achieved in Multiple-Input Single-Output (MISO) multi-antenna systems when channel conditions are known to the transmitter. In the second case, the sum power is minimized under zero-outage estimation distortion constraint, and some related energy efficiency issues in sensor networks are discussed. | Estimation Diversity and Energy Efficiency in Distributed Sensing | 7,547 |
In time hopping impulse radio, $N_f$ pulses of duration $T_c$ are transmitted for each information symbol. This gives rise to two types of processing gain: (i) pulse combining gain, which is a factor $N_f$, and (ii) pulse spreading gain, which is $N_c=T_f/T_c$, where $T_f$ is the mean interval between two subsequent pulses. This paper investigates the trade-off between these two types of processing gain in the presence of timing jitter. First, an additive white Gaussian noise (AWGN) channel is considered and approximate closed form expressions for bit error probability are derived for impulse radio systems with and without pulse-based polarity randomization. Both symbol-synchronous and chip-synchronous scenarios are considered. The effects of multiple-access interference and timing jitter on the selection of optimal system parameters are explained through theoretical analysis. Finally, a multipath scenario is considered and the trade-off between processing gains of a synchronous impulse radio system with pulse-based polarity randomization is analyzed. The effects of the timing jitter, multiple-access interference and inter-frame interference are investigated. Simulation studies support the theoretical results. | The Trade-off between Processing Gains of an Impulse Radio UWB System in
the Presence of Timing Jitter | 7,548 |
In this paper we address the problem of finding the sensing capacity of sensor networks for a class of linear observation models and a fixed SNR regime. Sensing capacity is defined as the maximum number of signal dimensions reliably identified per sensor observation. In this context sparsity of the phenomena is a key feature that determines sensing capacity. Precluding the SNR of the environment the effect of sparsity on the number of measurements required for accurate reconstruction of a sparse phenomena has been widely dealt with under compressed sensing. Nevertheless the development there was motivated from an algorithmic perspective. In this paper our aim is to derive these bounds in an information theoretic set-up and thus provide algorithm independent conditions for reliable reconstruction of sparse signals. In this direction we first generalize the Fano's inequality and provide lower bounds to the probability of error in reconstruction subject to an arbitrary distortion criteria. Using these lower bounds to the probability of error, we derive upper bounds to sensing capacity and show that for fixed SNR regime sensing capacity goes down to zero as sparsity goes down to zero. This means that disproportionately more sensors are required to monitor very sparse events. Our next main contribution is that we show the effect of sensing diversity on sensing capacity, an effect that has not been considered before. Sensing diversity is related to the effective \emph{coverage} of a sensor with respect to the field. In this direction we show the following results (a) Sensing capacity goes down as sensing diversity per sensor goes down; (b) Random sampling (coverage) of the field by sensors is better than contiguous location sampling (coverage). | On sensing capacity of sensor networks for the class of linear
observation, fixed SNR models | 7,549 |
We introduce the concept of $\delta$-sequence. A $\delta$-sequence $\Delta$ generates a well-ordered semigroup $S$ in $\mathbb{Z}^2$ or $\mathbb{R}$. We show how to construct (and compute parameters) for the dual code of any evaluation code associated with a weight function defined by $\Delta$ from the polynomial ring in two indeterminates to a semigroup $S$ as above. We prove that this is a simple procedure which can be understood by considering a particular class of valuations of function fields of surfaces, called plane valuations at infinity. We also give algorithms to construct an unlimited number of $\delta$-sequences of the different existing types, and so this paper provides the tools to know and use a new large set of codes. | $δ$-sequences and Evaluation Codes defined by Plane Valuations at
Infinity | 7,550 |
In this paper, a hierarchical cross-layer design approach is proposed to increase energy efficiency in ad hoc networks through joint adaptation of nodes' transmitting powers and route selection. The design maintains the advantages of the classic OSI model, while accounting for the cross-coupling between layers, through information sharing. The proposed joint power control and routing algorithm is shown to increase significantly the overall energy efficiency of the network, at the expense of a moderate increase in complexity. Performance enhancement of the joint design using multiuser detection is also investigated, and it is shown that the use of multiuser detection can increase the capacity of the ad hoc network significantly for a given level of energy consumption. | On Energy Efficient Hierarchical Cross-Layer Design: Joint Power Control
and Routing for Ad Hoc Networks | 7,551 |
This paper characterizes the capacity of a class of modulo additive noise relay channels, in which the relay observes a corrupted version of the noise and has a separate channel to the destination. The capacity is shown to be strictly below the cut-set bound in general and achievable using a quantize-and-forward strategy at the relay. This result confirms a conjecture by Ahlswede and Han about the capacity of channels with rate limited state information at the destination for this particular class of channels. | Capacity of a Class of Modulo-Sum Relay Channels | 7,552 |
Capacity improvement from transmitter and receiver cooperation is investigated in a two-transmitter, two-receiver network with phase fading and full channel state information available at all terminals. The transmitters cooperate by first exchanging messages over an orthogonal transmitter cooperation channel, then encoding jointly with dirty paper coding. The receivers cooperate by using Wyner-Ziv compress-and-forward over an analogous orthogonal receiver cooperation channel. To account for the cost of cooperation, the allocation of network power and bandwidth among the data and cooperation channels is studied. It is shown that transmitter cooperation outperforms receiver cooperation and improves capacity over non-cooperative transmission under most operating conditions when the cooperation channel is strong. However, a weak cooperation channel limits the transmitter cooperation rate; in this case receiver cooperation is more advantageous. Transmitter-and-receiver cooperation offers sizable additional capacity gain over transmitter-only cooperation at low SNR, whereas at high SNR transmitter cooperation alone captures most of the cooperative capacity improvement. | Capacity Gain from Two-Transmitter and Two-Receiver Cooperation | 7,553 |
A game-theoretic model is proposed to study the cross-layer problem of joint power and rate control with quality of service (QoS) constraints in multiple-access networks. In the proposed game, each user seeks to choose its transmit power and rate in a distributed manner in order to maximize its own utility while satisfying its QoS requirements. The user's QoS constraints are specified in terms of the average source rate and an upper bound on the average delay where the delay includes both transmission and queuing delays. The utility function considered here measures energy efficiency and is particularly suitable for wireless networks with energy constraints. The Nash equilibrium solution for the proposed non-cooperative game is derived and a closed-form expression for the utility achieved at equilibrium is obtained. It is shown that the QoS requirements of a user translate into a "size" for the user which is an indication of the amount of network resources consumed by the user. Using this competitive multiuser framework, the tradeoffs among throughput, delay, network capacity and energy efficiency are studied. In addition, analytical expressions are given for users' delay profiles and the delay performance of the users at Nash equilibrium is quantified. | Energy-Efficient Resource Allocation in Wireless Networks with
Quality-of-Service Constraints | 7,554 |
A unified approach to energy-efficient power control is proposed for code-division multiple access (CDMA) networks. The approach is applicable to a large family of multiuser receivers including the matched filter, the decorrelator, the linear minimum mean-square error (MMSE) receiver, and the (nonlinear) optimal detectors. It exploits the linear relationship that has been shown to exist between the transmit power and the output signal-to-interference-plus-noise ratio (SIR) in the large-system limit. It is shown that, for this family of receivers, when users seek to selfishly maximize their own energy efficiency, the Nash equilibrium is SIR-balanced. In addition, a unified power control (UPC) algorithm for reaching the Nash equilibrium is proposed. The algorithm adjusts the user's transmit powers by iteratively computing the large-system multiuser efficiency, which is independent of instantaneous spreading sequences. The convergence of the algorithm is proved for the matched filter, the decorrelator, and the MMSE receiver, and is demonstrated by means of simulation for an optimal detector. Moreover, the performance of the algorithm in finite-size systems is studied and compared with that of a conventional power control scheme, in which user powers depend on the instantaneous spreading sequences. | A Unified Approach to Energy-Efficient Power Control in Large CDMA
Systems | 7,555 |
In this two-part paper, we consider the multiantenna multihop relay channels in which the source signal arrives at the destination through N independent relaying hops in series. The main concern of this work is to design relaying strategies that utilize efficiently the relays in such a way that the diversity is maximized. In part I, we focus on the amplify-and-forward (AF) strategy with which the relays simply scale the received signal and retransmit it. More specifically, we characterize the diversity-multiplexing tradeoff (DMT) of the AF scheme in a general multihop channel with arbitrary number of antennas and arbitrary number of hops. The DMT is in closed-form expression as a function of the number of antennas at each node. First, we provide some basic results on the DMT of the general Rayleigh product channels. It turns out that these results have very simple and intuitive interpretation. Then, the results are applied to the AF multihop channels which is shown to be equivalent to the Rayleigh product channel, in the DMT sense. Finally, the project-and-forward (PF) scheme, a variant of the AF scheme, is proposed. We show that the PF scheme has the same DMT as the AF scheme, while the PF can have significant power gain over the AF scheme in some cases. In part II, we will derive the upper bound on the diversity of the multihop channels and show that it can be achieved by partitioning the multihop channel into AF subchannels. | Diversity of MIMO Multihop Relay Channels - Part I: Amplify-and-Forward | 7,556 |
This paper examines the joint problem of detection and identification of a sudden and unobservable change in the probability distribution function (pdf) of a sequence of independent and identically distributed (i.i.d.) random variables to one of finitely many alternative pdf's. The objective is quick detection of the change and accurate inference of the ensuing pdf. Following a Bayesian approach, a new sequential decision strategy for this problem is revealed and is proven optimal. Geometrical properties of this strategy are demonstrated via numerical examples. | Joint Detection and Identification of an Unobservable Change in the
Distribution of a Random Sequence | 7,557 |
In this paper, memories built from components subject to transient faults are considered. A fault-tolerant memory architecture based on low-density parity-check codes is proposed and the existence of reliable memories for the adversarial failure model is proved. The proof relies on the expansion property of the underlying Tanner graph of the code. An equivalence between the Taylor-Kuznetsov (TK) scheme and Gallager B algorithm is established and the results are extended to the independent failure model. It is also shown that the proposed memory architecture has lower redundancy compared to the TK scheme. The results are illustrated with specific numerical examples. | Reliable Memories Built from Unreliable Components Based on Expander
Graphs | 7,558 |
This paper introduces a new combinatorial construction for q-ary constant-weight codes which yields several families of optimal codes and asymptotically optimal codes. The construction reveals intimate connection between q-ary constant-weight codes and sets of pairwise disjoint combinatorial designs of various types. | Constructions of q-Ary Constant-Weight Codes | 7,559 |
We give an algorithm for finding network encoding and decoding equations for error-free multicasting networks with multiple sources and sinks. The algorithm given is efficient (polynomial complexity) and works on any kind of network (acyclic, link cyclic, flow cyclic, or even in the presence of knots). The key idea will be the appropriate use of the delay (both natural and additional) during the encoding. The resulting code will always work with finite delay with binary encoding coefficients. | An efficient centralized binary multicast network coding algorithm for
any cyclic network | 7,560 |
In this paper, the bit energy requirements of training-based transmission over block Rayleigh fading channels are studied. Pilot signals are employed to obtain the minimum mean-square-error (MMSE) estimate of the channel fading coefficients. Energy efficiency is analyzed in the worst case scenario where the channel estimate is assumed to be perfect and the error in the estimate is considered as another source of additive Gaussian noise. It is shown that bit energy requirement grows without bound as the snr goes to zero, and the minimum bit energy is achieved at a nonzero snr value below which one should not operate. The effect of the block length on both the minimum bit energy and the snr value at which the minimum is achieved is investigated. Flash training schemes are analyzed and shown to improve the energy efficiency in the low-snr regime. Energy efficiency analysis is also carried out when peak power constraints are imposed on pilot signals. | An Energy Efficiency Perspective on Training for Fading Channels | 7,561 |
The low-snr capacity of M-ary PSK transmission over both the additive white Gaussian noise (AWGN) and fading channels is analyzed when hard-decision detection is employed at the receiver. Closed-form expressions for the first and second derivatives of the capacity at zero snr are obtained. The spectral-efficiency/bit-energy tradeoff in the low-snr regime is analyzed by finding the wideband slope and the bit energy required at zero spectral efficiency. Practical design guidelines are drawn from the information-theoretic analysis. The fading channel analysis is conducted for both coherent and noncoherent cases, and the performance penalty in the low-power regime for not knowing the channel is identified. | On the Low-SNR Capacity of Phase-Shift Keying with Hard-Decision
Detection | 7,562 |
In this paper, pilot-assisted transmission over Gauss-Markov Rayleigh fading channels is considered. A simple scenario, where a single pilot signal is transmitted every T symbols and T-1 data symbols are transmitted in between the pilots, is studied. First, it is assumed that binary phase-shift keying (BPSK) modulation is employed at the transmitter. With this assumption, the training period, and data and training power allocation are jointly optimized by maximizing an achievable rate expression. Achievable rates and energy-per-bit requirements are computed using the optimal training parameters. Secondly, a capacity lower bound is obtained by considering the error in the estimate as another source of additive Gaussian noise, and the training parameters are optimized by maximizing this lower bound. | Training Optimization for Gauss-Markov Rayleigh Fading Channels | 7,563 |
In this paper, the error performance of on-off frequency shift keying (OOFSK) modulation over fading channels is analyzed when the receiver is equipped with multiple antennas. The analysis is conducted in two cases: the coherent scenario where the fading is perfectly known at the receiver, and the noncoherent scenario where neither the receiver nor the transmitter knows the fading coefficients. For both cases, the maximum a posteriori probability (MAP) detection rule is derived and analytical probability of error expressions are obtained. The effect of fading correlation among the receiver antennas is also studied. Simulation results indicate that for sufficiently low duty cycle values, lower probability of error values with respect to FSK signaling are achieved. Equivalently, when compared to FSK modulation, OOFSK with low duty cycle requires less energy to achieve the same probability of error, which renders this modulation a more energy efficient transmission technique. | Performance Analysis for Multichannel Reception of OOFSK Signaling | 7,564 |
In this paper, the performance of signaling strategies with high peak-to-average power ratio is analyzed in both coherent and noncoherent fading channels. Two recently proposed modulation schemes, namely on-off binary phase-shift keying and on-off quaternary phase-shift keying, are considered. For these modulation formats, the optimal decision rules used at the detector are identified and analytical expressions for the error probabilities are obtained. Numerical techniques are employed to compute the error probabilities. It is concluded that increasing the peakedness of the signals results in reduced error rates for a given power level and hence improve the energy efficiency. | Error Probability Analysis of Peaky Signaling over Fading Channels | 7,565 |
We consider power allocation algorithms for fixed-rate transmission over Nakagami-m non-ergodic block-fading channels with perfect transmitter and receiver channel state information and discrete input signal constellations under both short- and long-term power constraints. Optimal power allocation schemes are shown to be direct applications of previous results in the literature. We show that the SNR exponent of the optimal short-term scheme is given by the Singleton bound. We also illustrate the significant gains available by employing long-term power constraints. Due to the nature of the expressions involved, the complexity of optimal schemes may be prohibitive for system implementation. We propose simple sub-optimal power allocation schemes whose outage probability performance is very close to the minimum outage probability obtained by optimal schemes. | Power Allocation for Discrete-Input Non-Ergodic Block-Fading Channels | 7,566 |
This paper proposes a novel algorithm for finding error-locators of algebraic-geometric codes that can eliminate the division-calculations of finite fields from the Berlekamp-Massey-Sakata algorithm. This inverse-free algorithm provides full performance in correcting a certain class of errors, generic errors, which includes most errors, and can decode codes on algebraic curves without the determination of unknown syndromes. Moreover, we propose three different kinds of architectures that our algorithm can be applied to, and we represent the control operation of shift-registers and switches at each clock-timing with numerical simulations. We estimate the performance in comparison of the total running time and the numbers of multipliers and shift-registers in three architectures with those of the conventional ones for codes on algebraic curves. | Inverse-free Berlekamp-Massey-Sakata Algorithm and Small Decoders for
Algebraic-Geometric Codes | 7,567 |
A key idea in coding for the broadcast channel (BC) is binning, in which the transmitter encode information by selecting a codeword from an appropriate bin (the messages are thus the bin indexes). This selection is normally done by solving an appropriate (possibly difficult) combinatorial problem. Recently it has been shown that binning for the Blackwell channel --a particular BC-- can be done by iterative schemes based on Survey Propagation (SP). This method uses decimation for SP and suffers a complexity of O(n^2). In this paper we propose a new variation of the Belief Propagation (BP) algorithm, named Reinforced BP algorithm, that turns BP into a solver. Our simulations show that this new algorithm has complexity O(n log n). Using this new algorithm together with a non-linear coding scheme, we can efficiently achieve rates close to the border of the capacity region of the Blackwell channel. | Encoding for the Blackwell Channel with Reinforced Belief Propagation | 7,568 |
We present a new class of irregular low-density parity-check (LDPC) codes for moderate block lengths (up to a few thousand bits) that are well-suited for rate-compatible puncturing. The proposed codes show good performance under puncturing over a wide range of rates and are suitable for usage in incremental redundancy hybrid-automatic repeat request (ARQ) systems. In addition, these codes are linear-time encodable with simple shift-register circuits. For a block length of 1200 bits the codes outperform optimized irregular LDPC codes and extended irregular repeat-accumulate (eIRA) codes for all puncturing rates 0.6~0.9 (base code performance is almost the same) and are particularly good at high puncturing rates where good puncturing performance has been previously difficult to achieve. | The Design of Efficiently-Encodable Rate-Compatible LDPC Codes | 7,569 |
This paper considers the multi-input multi-output (MIMO) relay channel where multiple antennas are employed by each terminal. Compared to single-input single-output (SISO) relay channels, MIMO relay channels introduce additional degrees of freedom, making the design and analysis of optimal cooperative strategies more complex. In this paper, a partial cooperation strategy that combines transmit-side message splitting and block-Markov encoding is presented. Lower bounds on capacity that improve on a previously proposed non-cooperative lower bound are derived for Gaussian MIMO relay channels. | Rate Bounds for MIMO Relay Channels | 7,570 |
The distributed source coding problem is considered when the sensors, or encoders, are under Byzantine attack; that is, an unknown number of sensors have been reprogrammed by a malicious intruder to undermine the reconstruction at the fusion center. Three different forms of the problem are considered. The first is a variable-rate setup, in which the decoder adaptively chooses the rates at which the sensors transmit. An explicit characterization of the variable-rate minimum achievable sum rate is stated, given by the maximum entropy over the set of distributions indistinguishable from the true source distribution by the decoder. In addition, two forms of the fixed-rate problem are considered, one with deterministic coding and one with randomized coding. The achievable rate regions are given for both these problems, with a larger region achievable using randomized coding, though both are suboptimal compared to variable-rate coding. | Variable-Rate Distributed Source Coding in the Presence of Byzantine
Sensors | 7,571 |
In this paper the benefits provided by multi-cell processing of signals transmitted by mobile terminals which are received via dedicated relay terminals (RTs) are assessed. Unlike previous works, each RT is assumed here to be capable of full-duplex operation and receives the transmission of adjacent relay terminals. Focusing on intra-cell TDMA and non-fading channels, a simplified uplink cellular model introduced by Wyner is considered. This framework facilitates analytical derivation of the per-cell sum-rate of multi-cell and conventional single-cell receivers. In particular, the analysis is based on the observation that the signal received at the base stations can be interpreted as the outcome of a two-dimensional linear time invariant system. Numerical results are provided as well in order to provide further insight into the performance benefits of multi-cell processing with relaying. | Cellular Systems with Full-Duplex Amplify-and-Forward Relaying and
Cooperative Base-Stations | 7,572 |
In this paper, achievable rates of imperfectly-known fading relay channels are studied. It is assumed that communication starts with the network training phase in which the receivers estimate the fading coefficients of their respective channels. In the data transmission phase, amplify-and-forward and decode-and-forward relaying schemes are considered, and the corresponding achievable rate expressions are obtained. The achievable rate expressions are then employed to identify the optimal resource allocation strategies. | Achievable Rates and Optimal Resource Allocation for Imperfectly-Known
Fading Relay Channels | 7,573 |
In previous work, an ordering result was given for the symbolwise probability of error using general Markov channels, under iterative decoding of LDPC codes. In this paper, the ordering result is extended to mutual information, under the assumption of an iid input distribution. For certain channels, in which the capacity-achieving input distribution is iid, this allows ordering of the channels by capacity. The complexity of analyzing general Markov channels is mitigated by this ordering, since it is possible to immediately determine that a wide class of channels, with different numbers of states, has a smaller mutual information than a given channel. | Ordering Finite-State Markov Channels by Mutual Information | 7,574 |
In wireless data networks, communication is particularly susceptible to eavesdropping due to its broadcast nature. Security and privacy systems have become critical for wireless providers and enterprise networks. This paper considers the problem of secret communication over the Gaussian broadcast channel, where a multi-antenna transmitter sends independent confidential messages to two users with perfect secrecy. That is, each user would like to obtain its own message reliably and confidentially. First, a computable Sato-type outer bound on the secrecy capacity region is provided for a multi-antenna broadcast channel with confidential messages. Next, a dirty-paper secure coding scheme and its simplified version are described. For each case, the corresponding achievable rate region is derived under the perfect secrecy requirement. Finally, two numerical examples demonstrate that the Sato-type outer bound is consistent with the boundary of the simplified dirty-paper coding secrecy rate region. | Multiple Antenna Secure Broadcast over Wireless Networks | 7,575 |
Convexity/concavity properties of symbol error rates (SER) of the maximum likelihood detector operating in the AWGN channel (non-fading and fading) are studied. Generic conditions are identified under which the SER is a convex/concave function of the SNR. Universal bounds for the SER 1st and 2nd derivatives are obtained, which hold for arbitrary constellations and are tight for some of them. Applications of the results are discussed, which include optimum power allocation in spatial multiplexing systems, optimum power/time sharing to decrease or increase (jamming problem) error rate, and implication for fading channels. | Symbol Error Rates of Maximum-Likelihood Detector: Convex/Concave
Behavior and Applications | 7,576 |
Diversity-multiplexing tradeoff (DMT) presents a compact framework to compare various MIMO systems and channels in terms of the two main advantages they provide (i.e. high data rate and/or low error rate). This tradeoff was characterized asymptotically (SNR-> infinity) for i.i.d. Rayleigh fading channel by Zheng and Tse [1]. The asymptotic DMT overestimates the finite-SNR one [2]. In this paper, using the recent results on the asymptotic (in the number of antennas) outage capacity distribution, we derive and analyze the finite-SNR DMT for a broad class of channels (not necessarily Rayleigh fading). Based on this, we give the convergence conditions for the asymptotic DMT to be approached by the finite-SNR one. The multiplexing gain definition is shown to affect critically the convergence point: when the multiplexing gain is defined via the mean (ergodic) capacity, the convergence takes place at realistic SNR values. Furthermore, in this case the diversity gain can also be used to estimate the outage probability with reasonable accuracy. The multiplexing gain definition via the high-SNR asymptote of the mean capacity (as in [1]) results in very slow convergence for moderate to large systems (as 1/ln(SNR)^2) and, hence, the asymptotic DMT cannot be used at realistic SNR values. For this definition, the high-SNR threshold increases exponentially in the number of antennas and in the multiplexing gain. For correlated keyhole channel, the diversity gain is shown to decrease with correlation and power imbalance of the channel. While the SNR-asymptotic DMT of Zheng and Tse does not capture this effect, the size-asymptotic DMT does. | Diversity-Multiplexing Tradeoff via Asymptotic Analysis of Large MIMO
Systems | 7,577 |
A unified analytical framework for optimum power allocation in the unordered V-BLAST algorithm and its comparative performance analysis are presented. Compact closed-form approximations for the optimum power allocation are derived, based on average total and block error rates. The choice of the criterion has little impact on the power allocation and, overall, the optimum strategy is to allocate more power to lower step transmitters and less to higher ones. High-SNR approximations for optimized average block and total error rates are given. The SNR gain of optimization is rigorously defined and studied using analytical tools, including lower and upper bounds, high and low SNR approximations. The gain is upper bounded by the number of transmitters, for any modulation format and type of fading channel. While the average optimization is less complex than the instantaneous one, its performance is almost as good at high SNR. A measure of robustness of the optimized algorithm is introduced and evaluated. The optimized algorithm is shown to be robust to perturbations in individual and total transmit powers. Based on the algorithm robustness, a pre-set power allocation is suggested as a low-complexity alternative to the other optimization strategies, which exhibits only a minor loss in performance over the practical SNR range. | On Optimum Power Allocation for the V-BLAST | 7,578 |
The min-sum (MS) algorithm is arguably the second most fundamental algorithm in the realm of message passing due to its optimality (for a tree code) with respect to the {\em block error} probability \cite{Wiberg}. There also seems to be a fundamental relationship of MS decoding with the linear programming decoder \cite{Koetter}. Despite its importance, its fundamental properties have not nearly been studied as well as those of the sum-product (also known as BP) algorithm. We address two questions related to the MS rule. First, we characterize the stability condition under MS decoding. It turns out to be essentially the same condition as under BP decoding. Second, we perform a degree distribution optimization. Contrary to the case of BP decoding, under MS decoding the thresholds of the best degree distributions for standard irregular LDPC ensembles are significantly bounded away from the Shannon threshold. More precisely, on the AWGN channel, for the best codes that we find, the gap to capacity is 1dB for a rate 0.3 code and it is 0.4dB when the rate is 0.9 (the gap decreases monotonically as we increase the rate). We also used the optimization procedure to design codes for modified MS algorithm where the output of the check node is scaled by a constant $1/\alpha$. For $\alpha = 1.25$, we observed that the gap to capacity was lesser for the modified MS algorithm when compared with the MS algorithm. However, it was still quite large, varying from 0.75 dB to 0.2 dB for rates between 0.3 and 0.9. We conclude by posing what we consider to be the most important open questions related to the MS algorithm. | Degree Optimization and Stability Condition for the Min-Sum Decoder | 7,579 |
In this paper, a family of low-density parity-check (LDPC) degree distributions, whose decoding threshold on the binary erasure channel (BEC) admits a simple closed form, is presented. These degree distributions are a subset of the check regular distributions (i.e. all the check nodes have the same degree), and are referred to as $p$-positive distributions. It is given proof that the threshold for a $p$-positive distribution is simply expressed by $[\lambda'(0)\rho'(1)]^{-1}$. Besides this closed form threshold expression, the $p$-positive distributions exhibit three additional properties. First, for given code rate, check degree and maximum variable degree, they are in some cases characterized by a threshold which is extremely close to that of the best known check regular distributions, under the same set of constraints. Second, the threshold optimization problem within the $p$-positive class can be solved in some cases with analytic methods, without using any numerical optimization tool. Third, these distributions can achieve the BEC capacity. The last property is shown by proving that the well-known binomial degree distributions belong to the $p$-positive family. | A Class of LDPC Erasure Distributions with Closed-Form Threshold
Expression | 7,580 |
We characterize the capacity of the general class of noncoherent underspread wide-sense stationary uncorrelated scattering (WSSUS) time-frequency-selective Rayleigh fading channels, under peak constraints in time and frequency and in time only. Capacity upper and lower bounds are found which are explicit in the channel's scattering function and allow to identify the capacity-maximizing bandwidth for a given scattering function and a given peak-to-average power ratio. | Capacity of Underspread Noncoherent WSSUS Fading Channels under Peak
Signal Constraints | 7,581 |
We analyze fading interference relay networks where M single-antenna source-destination terminal pairs communicate concurrently and in the same frequency band through a set of K single-antenna relays using half-duplex two-hop relaying. Assuming that the relays have channel state information (CSI), it is shown that in the large-M limit, provided K grows fast enough as a function of M, the network "decouples" in the sense that the individual source-destination terminal pair capacities are strictly positive. The corresponding required rate of growth of K as a function of M is found to be sufficient to also make the individual source-destination fading links converge to nonfading links. We say that the network "crystallizes" as it breaks up into a set of effectively isolated "wires in the air". A large-deviations analysis is performed to characterize the "crystallization" rate, i.e., the rate (as a function of M,K) at which the decoupled links converge to nonfading links. In the course of this analysis, we develop a new technique for characterizing the large-deviations behavior of certain sums of dependent random variables. For the case of no CSI at the relay level, assuming amplify-and-forward relaying, we compute the per source-destination terminal pair capacity for M,K converging to infinity, with K/M staying fixed, using tools from large random matrix theory. | Crystallization in large wireless networks | 7,582 |
This paper addresses the performance of bit-interleaved coded multiple beamforming (BICMB) [1], [2] with imperfect knowledge of beamforming vectors. Most studies for limited-rate channel state information at the transmitter (CSIT) assume that the precoding matrix has an invariance property under an arbitrary unitary transform. In BICMB, this property does not hold. On the other hand, the optimum precoder and detector for BICMB are invariant under a diagonal unitary transform. In order to design a limited-rate CSIT system for BICMB, we propose a new distortion measure optimum under this invariance. Based on this new distortion measure, we introduce a new set of centroids and employ the generalized Lloyd algorithm for codebook design. We provide simulation results demonstrating the performance improvement achieved with the proposed distortion measure and the codebook design for various receivers with linear detectors. We show that although these receivers have the same performance for perfect CSIT, their performance varies under imperfect CSIT. | Bit-Interleaved Coded Multiple Beamforming with Imperfect CSIT | 7,583 |
This paper characterizes the effect of finite rate channel state feedback on the sum rate of a multi-access multiple-input multiple-output (MIMO) system. We propose to control the users jointly, specifically, we first choose the users jointly and then select the corresponding beamforming vectors jointly. To quantify the sum rate, this paper introduces the composite Grassmann manifold and the composite Grassmann matrix. By characterizing the distortion rate function on the composite Grassmann manifold and calculating the logdet function of a random composite Grassmann matrix, a good sum rate approximation is derived. According to the distortion rate function on the composite Grassmann manifold, the loss due to finite beamforming decreases exponentially as the feedback bits on beamforming increases. | Multi-Access MIMO Systems with Finite Rate Channel State Feedback | 7,584 |
This paper considers the quantization problem on the Grassmann manifold with dimension n and p. The unique contribution is the derivation of a closed-form formula for the volume of a metric ball in the Grassmann manifold when the radius is sufficiently small. This volume formula holds for Grassmann manifolds with arbitrary dimension n and p, while previous results are only valid for either p=1 or a fixed p with asymptotically large n. Based on the volume formula, the Gilbert-Varshamov and Hamming bounds for sphere packings are obtained. Assuming a uniformly distributed source and a distortion metric based on the squared chordal distance, tight lower and upper bounds are established for the distortion rate tradeoff. Simulation results match the derived results. As an application of the derived quantization bounds, the information rate of a Multiple-Input Multiple-Output (MIMO) system with finite-rate channel-state feedback is accurately quantified for arbitrary finite number of antennas, while previous results are only valid for either Multiple-Input Single-Output (MISO) systems or those with asymptotically large number of transmit antennas but fixed number of receive antennas. | Quantization Bounds on Grassmann Manifolds of Arbitrary Dimensions and
MIMO Communications with Feedback | 7,585 |
This paper quantifies the information rate of multiple-input multiple-output (MIMO) systems with finite rate channel state feedback and power on/off strategy. In power on/off strategy, a beamforming vector (beam) is either turned on (denoted by on-beam) with a constant power or turned off. We prove that the ratio of the optimal number of on-beams and the number of antennas converges to a constant for a given signal-to-noise ratio (SNR) when the number of transmit and receive antennas approaches infinity simultaneously and when beamforming is perfect. Based on this result, a near optimal strategy, i.e., power on/off strategy with a constant number of on-beams, is discussed. For such a strategy, we propose the power efficiency factor to quantify the effect of imperfect beamforming. A formula is proposed to compute the maximum power efficiency factor achievable given a feedback rate. The information rate of the overall MIMO system can be approximated by combining the asymptotic results and the formula for power efficiency factor. Simulations show that this approximation is accurate for all SNR regimes. | On the Information Rate of MIMO Systems with Finite Rate Channel State
Feedback and Power On/Off Strategy | 7,586 |
This paper considers broadcast channels with L antennas at the base station and m single-antenna users, where each user has perfect channel knowledge and the base station obtains channel information through a finite rate feedback. The key observation of this paper is that the optimal number of on-users (users turned on), say s, is a function of signal-to-noise ratio (SNR) and other system parameters. Towards this observation, we use asymptotic analysis to guide the design of feedback and transmission strategies. As L, m and the feedback rates approach infinity linearly, we derive the asymptotic optimal feedback strategy and a realistic criterion to decide which users should be turned on. Define the corresponding asymptotic throughput per antenna as the spatial efficiency. It is a function of the number of on-users s, and therefore, s should be appropriately chosen. Based on the above asymptotic results, we also develop a scheme for a system with finite many antennas and users. Compared with other works where s is presumed constant, our scheme achieves a significant gain by choosing the appropriate s. Furthermore, our analysis and scheme is valid for heterogeneous systems where different users may have different path loss coefficients and feedback rates. | How Many Users should be Turned On in a Multi-Antenna Broadcast Channel? | 7,587 |
The Grassmann manifold G_{n,p}(L) is the set of all p-dimensional planes (through the origin) in the n-dimensional Euclidean space L^{n}, where L is either R or C. This paper considers an unequal dimensional quantization in which a source in G_{n,p}(L) is quantized through a code in G_{n,q}(L), where p and q are not necessarily the same. It is different from most works in literature where p\equiv q. The analysis for unequal dimensional quantization is based on the volume of a metric ball in G_{n,p}(L) whose center is in G_{n,q}(L). Our chief result is a closed-form formula for the volume of a metric ball when the radius is sufficiently small. This volume formula holds for Grassmann manifolds with arbitrary n, p, q and L, while previous results pertained only to some special cases. Based on this volume formula, several bounds are derived for the rate distortion tradeoff assuming the quantization rate is sufficiently high. The lower and upper bounds on the distortion rate function are asymptotically identical, and so precisely quantify the asymptotic rate distortion tradeoff. We also show that random codes are asymptotically optimal in the sense that they achieve the minimum achievable distortion with probability one as n and the code rate approach infinity linearly. Finally, we discuss some applications of the derived results to communication theory. A geometric interpretation in the Grassmann manifold is developed for capacity calculation of additive white Gaussian noise channel. Further, the derived distortion rate function is beneficial to characterizing the effect of beamforming matrix selection in multi-antenna communications. | Unequal dimensional small balls and quantization on Grassmann Manifolds | 7,588 |
Sphere decoding (SD) is a low complexity maximum likelihood (ML) detection algorithm, which has been adapted for different linear channels in digital communications. The complexity of the SD has been shown to be exponential in some cases, and polynomial in others and under certain assumptions. The sphere radius and the number of nodes visited throughout the tree traversal search are the decisive factors for the complexity of the algorithm. The radius problem has been addressed and treated widely in the literature. In this paper, we propose a new structure for SD, which drastically reduces the overall complexity. The complexity is measured in terms of the floating point operations per second (FLOPS) and the number of nodes visited throughout the algorithm tree search. This reduction in the complexity is due to the ability of decoding the real and imaginary parts of each jointly detected symbol independently of each other, making use of the new lattice representation. We further show by simulations that the new approach achieves 80% reduction in the overall complexity compared to the conventional SD for a 2x2 system, and almost 50% reduction for the 4x4 and 6x6 cases, thus relaxing the requirements for hardware implementation. | Reduced Complexity Sphere Decoding for Square QAM via a New Lattice
Representation | 7,589 |
Based on Planck's blackbody equation it is argued that a single mode light pulse, with a large number of photons, carries one entropy unit. Similarly, an empty radiation mode carries no entropy. In this case, the calculated entropy that a coded sequence of light pulses is carrying is simply the Gibbs mixing entropy, which is identical to the logical Shannon information. This approach is supported by a demonstration that information transmission and amplification, by a sequence of light pulses in an optical fiber, is a classic Carnot machine comprising of two isothermals and two adiabatic. Therefore it is concluded that entropy under certain conditions is information. | Informatics Carnot Machine | 7,590 |
This paper studies the ergodic capacity of time- and frequency-selective multipath fading channels in the ultrawideband (UWB) regime when training signals are used for channel estimation at the receiver. Motivated by recent measurement results on UWB channels, we propose a model for sparse multipath channels. A key implication of sparsity is that the independent degrees of freedom (DoF) in the channel scale sub-linearly with the signal space dimension (product of signaling duration and bandwidth). Sparsity is captured by the number of resolvable paths in delay and Doppler. Our analysis is based on a training and communication scheme that employs signaling over orthogonal short-time Fourier (STF) basis functions. STF signaling naturally relates sparsity in delay-Doppler to coherence in time-frequency. We study the impact of multipath sparsity on two fundamental metrics of spectral efficiency in the wideband/low-SNR limit introduced by Verdu: first- and second-order optimality conditions. Recent results by Zheng et. al. have underscored the large gap in spectral efficiency between coherent and non-coherent extremes and the importance of channel learning in bridging the gap. Building on these results, our results lead to the following implications of multipath sparsity: 1) The coherence requirements are shared in both time and frequency, thereby significantly relaxing the required scaling in coherence time with SNR; 2) Sparse multipath channels are asymptotically coherent -- for a given but large bandwidth, the channel can be learned perfectly and the coherence requirements for first- and second-order optimality met through sufficiently large signaling duration; and 3) The requirement of peaky signals in attaining capacity is eliminated or relaxed in sparse environments. | Capacity of Sparse Multipath Channels in the Ultra-Wideband Regime | 7,591 |
In contrast to the prevalent assumption of rich multipath in information theoretic analysis of wireless channels, physical channels exhibit sparse multipath, especially at large bandwidths. We propose a model for sparse multipath fading channels and present results on the impact of sparsity on non-coherent capacity and reliability in the wideband regime. A key implication of sparsity is that the statistically independent degrees of freedom in the channel, that represent the delay-Doppler diversity afforded by multipath, scale at a sub-linear rate with the signal space dimension (time-bandwidth product). Our analysis is based on a training-based communication scheme that uses short-time Fourier (STF) signaling waveforms. Sparsity in delay-Doppler manifests itself as time-frequency coherence in the STF domain. From a capacity perspective, sparse channels are asymptotically coherent: the gap between coherent and non-coherent extremes vanishes in the limit of large signal space dimension without the need for peaky signaling. From a reliability viewpoint, there is a fundamental tradeoff between channel diversity and learnability that can be optimized to maximize the error exponent at any rate by appropriately choosing the signaling duration as a function of bandwidth. | Non-Coherent Capacity and Reliability of Sparse Multipath Channels in
the Wideband Regime | 7,592 |
We study and compare the Shannon capacity region and the stable throughput region for a random access system in which source nodes multicast their messages to multiple destination nodes. Under an erasure channel model which accounts for interference and allows for multipacket reception, we first characterize the Shannon capacity region. We then consider a queueing-theoretic formulation and characterize the stable throughput region for two different transmission policies: a retransmission policy and random linear coding. Our results indicate that for large blocklengths, the random linear coding policy provides a higher stable throughput than the retransmission policy. Furthermore, our results provide an example of a transmission policy for which the Shannon capacity region strictly outer bounds the stable throughput region, which contradicts an unproven conjecture that the Shannon capacity and stable throughput coincide for random access systems. | On the Shannon capacity and queueing stability of random access
multicast | 7,593 |
A transmitter without channel state information (CSI) wishes to send a delay-limited Gaussian source over a slowly fading channel. The source is coded in superimposed layers, with each layer successively refining the description in the previous one. The receiver decodes the layers that are supported by the channel realization and reconstructs the source up to a distortion. The expected distortion is minimized by optimally allocating the transmit power among the source layers. For two source layers, the allocation is optimal when power is first assigned to the higher layer up to a power ceiling that depends only on the channel fading distribution; all remaining power, if any, is allocated to the lower layer. For convex distortion cost functions with convex constraints, the minimization is formulated as a convex optimization problem. In the limit of a continuum of infinite layers, the minimum expected distortion is given by the solution to a set of linear differential equations in terms of the density of the fading distribution. As the bandwidth ratio b (channel uses per source symbol) tends to zero, the power distribution that minimizes expected distortion converges to the one that maximizes expected capacity. While expected distortion can be improved by acquiring CSI at the transmitter (CSIT) or by increasing diversity from the realization of independent fading paths, at high SNR the performance benefit from diversity exceeds that from CSIT, especially when b is large. | Distortion Minimization in Gaussian Layered Broadcast Coding with
Successive Refinement | 7,594 |
In this paper, a transmission protocol is studied for a two relay wireless network in which simple repetition coding is applied at the relays. Information-theoretic achievable rates for this transmission scheme are given, and a space-time V-BLAST signalling and detection method that can approach them is developed. It is shown through the diversity multiplexing tradeoff analysis that this transmission scheme can recover the multiplexing loss of the half-duplex relay network, while retaining some diversity gain. This scheme is also compared with conventional transmission protocols that exploit only the diversity of the network at the cost of a multiplexing loss. It is shown that the new transmission protocol offers significant performance advantages over conventional protocols, especially when the interference between the two relays is sufficiently strong. | Recovering Multiplexing Loss Through Successive Relaying Using
Repetition Coding | 7,595 |
In random-access communication systems, the number of active users varies with time, and has considerable bearing on receiver's performance. Thus, techniques aimed at identifying not only the information transmitted, but also that number, play a central role in those systems. An example of application of these techniques can be found in multiuser detection (MUD). In typical MUD analyses, receivers are based on the assumption that the number of active users is constant and known at the receiver, and coincides with the maximum number of users entitled to access the system. This assumption is often overly pessimistic, since many users might be inactive at any given time, and detection under the assumption of a number of users larger than the real one may impair performance. The main goal of this paper is to introduce a general approach to the problem of identifying active users and estimating their parameters and data in a random-access system where users are continuously entering and leaving the system. The tool whose use we advocate is Random-Set Theory: applying this, we derive optimum receivers in an environment where the set of transmitters comprises an unknown number of elements. In addition, we can derive Bayesian-filter equations which describe the evolution with time of the a posteriori probability density of the unknown user parameters, and use this density to derive optimum detectors. In this paper we restrict ourselves to interferer identification and data detection, while in a companion paper we shall examine the more complex problem of estimating users' parameters. | Multiuser detection in a dynamic environment Part I: User identification
and data detection | 7,596 |
We study the problem of constructing coded modulation schemes over multidimensional signal sets in Nakagami-$m$ block-fading channels. In particular, we consider the optimal diversity reliability exponent of the error probability when the multidimensional constellation is obtained as the rotation of classical complex-plane signal constellations. We show that multidimensional rotations of full dimension achieve the optimal diversity reliability exponent, also achieved by Gaussian constellations. Multidimensional rotations of full dimension induce a large decoding complexity, and in some cases it might be beneficial to use multiple rotations of smaller dimension. We also study the diversity reliability exponent in this case, which yields the optimal rate-diversity-complexity tradeoff in block-fading channels with discrete inputs. | Multidimensional Coded Modulation in Block-Fading Channnels | 7,597 |
We analyze fading relay networks, where a single-antenna source-destination terminal pair communicates through a set of half-duplex single-antenna relays using a two-hop protocol with linear processing at the relay level. A family of relaying schemes is presented which achieves the entire optimal diversity-multiplexing (DM) tradeoff curve. As a byproduct of our analysis, it follows that delay diversity and phase-rolling at the relay level are optimal with respect to the entire DM-tradeoff curve, provided the delays and the modulation frequencies, respectively, are chosen appropriately. | Distributed Transmit Diversity in Relay Networks | 7,598 |
In this paper, a novel decoding algorithm for low-density parity-check (LDPC) codes based on convex optimization is presented. The decoding algorithm, called interior point decoding, is designed for linear vector channels. The linear vector channels include many practically important channels such as inter symbol interference channels and partial response channels. It is shown that the maximum likelihood decoding (MLD) rule for a linear vector channel can be relaxed to a convex optimization problem, which is called a relaxed MLD problem. The proposed decoding algorithm is based on a numerical optimization technique so called interior point method with barrier function. Approximate variations of the gradient descent and the Newton methods are used to solve the convex optimization problem. In a decoding process of the proposed algorithm, a search point always lies in the fundamental polytope defined based on a low-density parity-check matrix. Compared with a convectional joint message passing decoder, the proposed decoding algorithm achieves better BER performance with less complexity in the case of partial response channels in many cases. | Interior Point Decoding for Linear Vector Channels | 7,599 |
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