Joint Antenna Selection and Phase-Only Beamforming Using Mixed-Integer Nonlinear Programming

TL;DR

This paper addresses reducing hardware costs in multicast networks by jointly optimizing antenna selection and phase-only beamforming using mixed-integer nonlinear programming, proposing both optimal and heuristic solutions.

Contribution

It introduces a novel branch-and-cut algorithm for optimal joint antenna selection and beamforming, along with a low-complexity heuristic that performs near-optimally.

Findings

Heuristic solutions are optimal in most cases.

Optimal solutions can be improved by initializing with heuristic results.

The proposed methods effectively reduce hardware costs.

Abstract

In this paper, we consider the problem of joint antenna selection and analog beamformer design in downlink single-group multicast networks. Our objective is to reduce the hardware costs by minimizing the number of required phase shifters at the transmitter while fulfilling given distortion limits at the receivers. We formulate the problem as an L0 minimization problem and devise a novel branch-and-cut based algorithm to solve the resulting mixed-integer nonlinear program to optimality. We also propose a suboptimal heuristic algorithm to solve the above problem approximately with a low computational complexity. Computational results illustrate that the solutions produced by the proposed heuristic algorithm are optimal in most cases. The results also indicate that the performance of the optimal methods can be significantly improved by initializing with the result of the suboptimal method.