Create README.md

README.md

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+---
+language: en
+license: mit
+tags:
+- signal-processing
+- time-series
+- telecommunications
+- carrier-analysis
+---
+
+# Data Signal & Carrier Classifier
+
+## Overview
+This model is designed for high-frequency telecommunications monitoring. It analyzes the **Data Signal** (তথ্য সংকেত) integrity and identifies the underlying **Carrier** (বাহক) modulation type in real-time. By processing raw I/Q samples, it can distinguish between various modulation schemes and detect signal degradation caused by environmental interference.
+
+
+
+## Model Architecture
+The model utilizes a **Temporal-Frequency Transformer** architecture:
+- **Feature Extraction**: A 1D-Convolutional front-end processes the raw waveform to extract local spectral features.
+- **Contextual Encoder**: 8 layers of Multi-Head Self-Attention capture long-range dependencies across the **Carrier** wave.
+- **Classification Head**: A linear layer that maps the hidden state of the `[CLS]` token to the specific modulation class.
+- **Loss Function**: Weighted Cross-Entropy to handle class imbalance in noisy environments:
+$$L = -\sum_{c=1}^{M} y_{o,c} \log(p_{o,c})$$
+
+## Intended Use
+- **Spectrum Sensing**: Automated identification of occupied bands in cognitive radio networks.
+- **Quality of Service (QoS)**: Monitoring the health of a **Data Signal** to trigger automated re-routing.
+- **Anomaly Detection**: Identifying unauthorized **Carrier** frequencies in restricted zones.
+
+## Limitations
+- **Signal-to-Noise Ratio (SNR)**: Performance degrades significantly when the SNR drops below 3dB.
+- **Frequency Offset**: Requires external synchronization; high frequency-offset values may lead to misclassification.
+- **Hardware constraints**: Optimized for FPGA or GPU inference; may require quantization for edge deployment on low-power microcontrollers.