Fast Converging Algorithm for Weighted Sum Rate Maximization in Multicell MISO Downlink

TL;DR

This paper introduces a fast, convergent algorithm for maximizing weighted sum rates in multicell MISO downlink systems, addressing the NP-hardness with an efficient iterative approach that outperforms existing methods.

Contribution

The authors develop a low-complexity, provably convergent algorithm based on second-order cone programming for weighted sum rate maximization in multicell MISO downlink systems.

Findings

Algorithm converges within few iterations

Numerical results show superior performance

Effective for NP-hard optimization problem

Abstract

The problem of maximizing weighted sum rates in the downlink of a multicell environment is of considerable interest. Unfortunately, this problem is known to be NP-hard. For the case of multi-antenna base stations and single antenna mobile terminals, we devise a low complexity, fast and provably convergent algorithm that locally optimizes the weighted sum rate in the downlink of the system. In particular, we derive an iterative second-order cone program formulation of the weighted sum rate maximization problem. The algorithm converges to a local optimum within a few iterations. Superior performance of the proposed approach is established by numerically comparing it to other known solutions.