Study of Robust Distributed Beamforming Based on Cross-Correlation and Subspace Projection Techniques

TL;DR

This paper introduces a robust distributed beamforming method that leverages cross-correlation and subspace projection to improve signal quality in relay-based wireless networks with imperfect channel knowledge.

Contribution

It proposes a novel CCSP RDB technique that enhances robustness against channel errors without complex optimization, outperforming existing algorithms.

Findings

Excellent performance in simulations compared to prior algorithms

Does not require costly optimization procedures

Effective with imperfect channel state information

Abstract

In this work, we present a novel robust distributed beamforming (RDB) approach to mitigate the effects of channel errors on 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. The proposed RDB method, denoted cross-correlation and subspace projection (CCSP) RDB, considers a total relay transmit power constraint in the system and the objective of maximizing the output signal-to-interference-plus-noise ratio (SINR). The relay nodes are equipped with an amplify-and-forward (AF) protocol and we assume that the channel state information (CSI) is imperfectly known at the relays and there is no direct link between the sources and the destination. The CCSP does not require any costly optimization procedure and simulations show an excellent performance as compared to previously reported algorithms.