Low-Complexity Weighted Sum-Rate Maximization Approach with Per-Antenna Power Constraints

Abstract

This paper considers the design of beamformers for a multiple-input single-output (MISO) downlink system that seek to maximize the weighted sum-rate (WSR) when we have a total power constraint or per-antenna power constraints (PAPCs) at the base station (BS). The goal of the design is to compute these beamformers at a low computational cost. We first use an approximation that is true for a system with large number of antennas to provide a good estimate for the required rates when we have a total power constraint. Using those rates, the WSR problem can be turned into a quality-of-service (QoS) problem that can be efficiently solved. We show that the computational cost is linear in the number of antennas and cubic in the number of users. Then, we extend the provided framework to the case of having total power constraint and PAPCs and show that it can be solved in an iterative manner with the same order of computational complexity. We show that our design approach is flexible to accommodate other possible utility functions; e.g., maximizing the minimum rate.