Channel Modeling with Gaussian Noise and Rayleigh Fading: Performance Analysis of Combining Methods and Relaying Protocols

The communication channel is modeled by incorporating both Gaussian noise and Rayleigh fading components. In this research project, we implemented and compared different signal combining methods and relaying protocols through MATLAB simulations. Our performance analysis focused on two key metrics: Bit Error Rate (BER) and Throughput. The relaying protocols implemented include Amplify & Forward (AF) and Detect & Forward (DF). Through Monte Carlo simulations, we observed that the Amplify and Forward protocol demonstrated superior performance characteristics. Among the combining schemes evaluated, Maximal Ratio Combining (MRC) showed optimized BER and Throughput performance curves, which we implemented using weighted combining based on channel state information. To enhance network performance, we extended the system to a four-node communication architecture with two relay nodes functioning as distributed antennas. This implementation achieves spatial diversity benefits without requiring physical antenna arrays, effectively creating a virtual MIMO system. The code structure includes separate modules for channel modeling, protocol implementation, and performance metric calculation, allowing for modular testing and optimization. Index Terms: Cooperative Diversity, Fading channels, combining techniques, transmission protocols, Relay channel, Bit error rate, Throughput, Amplify and forward, Detect and Forward, Maximal Ratio Combining, Distributed antennas.