Message Passing Algorithm for Distributed Downlink Regularized Zero-forcing Beamforming with Cooperative Base Stations

TL;DR

This paper introduces distributed message passing algorithms for regularized zero-forcing beamforming in cooperative base stations, reducing complexity and communication overhead while maintaining near-optimal performance.

Contribution

The paper develops belief propagation-based algorithms for distributed RZFBF, enabling scalable, low-complexity implementation with reduced reliance on instantaneous channel information.

Findings

Algorithms converge quickly to exact RZFBF

Significant reduction in computational complexity

Faster convergence compared to conventional methods

Abstract

Base station (BS) cooperation can turn unwanted interference to useful signal energy for enhancing system performance. In the cooperative downlink, zero-forcing beamforming (ZFBF) with a simple scheduler is well known to obtain nearly the performance of the capacity-achieving dirty-paper coding. However, the centralized ZFBF approach is prohibitively complex as the network size grows. In this paper, we devise message passing algorithms for realizing the regularized ZFBF (RZFBF) in a distributed manner using belief propagation. In the proposed methods, the overall computational cost is decomposed into many smaller computation tasks carried out by groups of neighboring BSs and communications is only required between neighboring BSs. More importantly, some exchanged messages can be computed based on channel statistics rather than instantaneous channel state information, leading to significant reduction in computational complexity. Simulation results demonstrate that the proposed algorithms converge quickly to the exact RZFBF and much faster compared to conventional methods.