Robust Time-Invariant Filtering for Wireless Relay Optimization

This book presents the design, implementation, and performance evaluation of an Adaptive Joint SCAMP Filter and Relay Weight Optimization Scheme for a wireless Amplify-and-Forward (AF) cooperative relay network operating over frequency-selective fading channels. Conventional AF systems suffer from compounded noise and Inter-Symbol Interference (ISI) due to cascaded multi-tap channel effects. To address these limitations, this work employs a Joint Adaptive Filtering approach that simultaneously optimizes the source pre-coding filter and the relay amplification weight to minimize the end-to-end Mean Squared Error (MSE) and enhance the achievable data rate.The joint optimization problem is solved using the Projected Subgradient Method (PSGM), which provides robustness against non-linear constraints such as sparsity while maintaining low computational complexity. The algorithm is implemented and tested in a MATLAB simulation environment under a time-varying Auto-Regressive (AR(1)) fading model. Key performance metrics such as MSE convergence, filter characteristics, achievable rate, and robustness to parameter variations are analyzed.