Constant Modulus Beamforming via Convex Optimization

TL;DR

This paper introduces new convex optimization methods for blind beamforming of constant modulus signals, achieving globally optimal, parameter-free solutions that outperform existing techniques in simulations.

Contribution

The paper proposes the first globally optimal, parameter-free convex optimization solutions for blind beamforming of constant modulus signals.

Findings

Superior performance in simulated data

Global optimality of the solutions

Parameter-free approach

Abstract

We present novel convex-optimization-based solutions to the problem of blind beamforming of constant modulus signals, and to the related problem of linearly constrained blind beamforming of constant modulus signals. These solutions ensure global optimality and are parameter free, namely, do not contain any tuneable parameters and do not require any a-priori parameter settings. The performance of these solutions, as demonstrated by simulated data, is superior to existing methods.