Study of Distributed Robust Beamforming with Low-Rank and Cross-Correlation Techniques
This addresses performance degradation in wireless networks with relays, but it appears incremental as it builds on existing beamforming methods.
The paper tackles the problem of channel errors degrading performance in wireless relay networks by proposing a robust distributed beamforming approach using low-rank and cross-correlation techniques, which maximizes output SINR under power constraints and shows excellent performance in simulations without costly online optimization.
In this work, we present a novel robust distributed beamforming (RDB) approach based on low-rank and cross-correlation techniques. The proposed RDB approach mitigates the effects of channel errors in wireless networks equipped with relays based on the exploitation of the cross-correlation between the received data from the relays at the destination and the system output and low-rank techniques. The relay nodes are equipped with an amplify-and-forward (AF) protocol and the channel errors are modeled using an additive matrix perturbation, which results in degradation of the system performance. The proposed method, denoted low-rank and cross-correlation RDB (LRCC-RDB), considers a total relay transmit power constraint in the system and the goal of maximizing the output signal-to-interference-plus-noise ratio (SINR). We carry out a performance analysis of the proposed LRCC-RDB technique along with a computational complexity study. The proposed LRCC-RDB does not require any costly online optimization procedure and simulations show an excellent performance as compared to previously reported algorithms.