Worst-Case SINR Constrained Robust Coordinated Beamforming for Multicell Wireless Systems

TL;DR

This paper develops a robust multicell coordinated beamforming method that accounts for channel state information errors, optimizing power and SINR constraints to improve wireless system performance under worst-case conditions.

Contribution

It introduces a worst-case robust design framework for multicell beamforming that reformulates nonconvex SINR constraints as linear matrix inequalities, enabling efficient optimization.

Findings

Robust MCBF outperforms robust SBF in SINR guarantees.

The reformulation simplifies the complex optimization problem.

Simulation confirms improved power efficiency and reliability.

Abstract

Multicell coordinated beamforming (MCBF) has been recognized as a promising approach to enhancing the system throughput and spectrum efficiency of wireless cellular systems. In contrast to the conventional single-cell beamforming (SBF) design, MCBF jointly optimizes the beamforming vectors of cooperative base stations (BSs) (via a central processing unit(CPU)) in order to mitigate the intercell interference. While most of the existing designs assume that the CPU has the perfect knowledge of the channel state information (CSI) of mobile stations (MSs), this paper takes into account the inevitable CSI errors at the CPU, and study the robust MCBF design problem. Specifically, we consider the worst-case robust design formulation that minimizes the weighted sum transmission power of BSs subject to worst-case signal-to-interference-plus-noise ratio (SINR) constraints on MSs. The associated optimization problem is challenging because it involves infinitely many nonconvex SINR constraints. In this paper, we show that the worst-case SINR constraints can be reformulated as linear matrix inequalities, and the approximation method known as semidefinite relation can be used to efficiently handle the worst-case robust MCBF problem. Simulation results show that the proposed robustMCBF design can provide guaranteed SINR performance for the MSs and outperforms the robust SBF design.