A convex approximation approach to Weighted Sum Rate Maximization of Multiuser MISO Interference Channel under outage constraints

TL;DR

This paper introduces a convex approximation method for efficiently maximizing the weighted sum rate in multiuser MISO interference channels under outage constraints, providing near-optimal solutions with reduced computational complexity.

Contribution

It proposes a novel convex optimization-based approximation approach for outage-constrained weighted sum rate maximization in MISO-IFC, improving efficiency over exhaustive search methods.

Findings

The method yields near-optimal solutions.

It significantly reduces computational complexity.

Simulation results validate effectiveness.

Abstract

This paper considers weighted sum rate maximization of multiuser multiple-input single-output interference channel (MISO-IFC) under outage constraints. The outage-constrained weighted sum rate maximization problem is a nonconvex optimization problem and is difficult to solve. While it is possible to optimally deal with this problem in an exhaustive search manner by finding all the Pareto-optimal rate tuples in the (discretized) outage-constrained achievable rate region, this approach, however, suffers from a prohibitive computational complexity and is feasible only when the number of transmitter-receive pairs is small. In this paper, we propose a convex optimization based approximation method for efficiently handling the outage-constrained weighted sum rate maximization problem. The proposed approximation method consists of solving a sequence of convex optimization problems, and thus can be efficiently implemented by interior-point methods. Simulation results show that the proposed method can yield near-optimal solutions.