Genetic Algorithm Assisted Hybrid Beamforming for Wireless Fronthaul

TL;DR

This paper introduces a genetic algorithm-based hybrid beamforming method for wireless fronthaul that effectively optimizes one-bit phase shifters using distorted channel information, achieving near-digital performance.

Contribution

It presents a novel hybrid SLNR beamforming design with a genetic algorithm for one-bit phase shifters, relying only on distorted channel data, and analyzes its performance in multi-cell scenarios.

Findings

Hybrid beamforming achieves near-digital performance in single-cell scenarios.

Genetic algorithms effectively optimize one-bit phase shifters.

Intercell interference can be caused by hybrid beamforming in multi-cell scenarios.

Abstract

This paper proposes a genetic algorithm assisted hybrid signal to leakage plus noise ratio (SLNR) beamforming design for wireless fronthaul scenario. The digital precoder of the proposed hybrid SLNR beamforming is expressed in closed-form. Highly limited phase resolution (one-bit resolution) is assumed at the phase shifters at the analog precoder. The analog precoders maximizing the approximated sum rate are presented. Genetic algorithms are used to search for optimal solutions of one-bit analog precoders. In contrast to common assumptions on perfect knowledge of the true channel matrix at the transmitter, the proposed method relies only on the distorted channel matrix after the analog precoder. Performance of the proposed hybrid SLNR beamforming with limited phase resolution at the analog precoder can achieve performance close to digital beamforming in single cell wireless fronthaul scenarios. It is also shown that hybrid beamforming can result in undesired beams causing intercell interference in multicell wireless fronthaul scenarios.