Dual-Function Beamforming Design For Multi-Target Localization and Reliable Communications

TL;DR

This paper presents a dual-function beamforming approach for MIMO systems that simultaneously enhances multi-target localization accuracy and ensures reliable multi-user communications through novel optimization algorithms.

Contribution

It introduces a beamforming design that minimizes an upper bound on the asymptotic CRB for target angles while maintaining communication SINR, using two innovative iterative algorithms.

Findings

Achieves improved target angle estimation accuracy.

Ensures high-quality multi-user communication performance.

Demonstrates the effectiveness of dual-function beamforming in simulations.

Abstract

This paper investigates the transmit beamforming design for multiple-input multiple-output systems to support both multi-target localization and multi-user communications. To enhance the target localization performance, we derive the asymptotic Cram\'{e}r-Rao bound (CRB) for target angle estimation by assuming that the receive array is linear and uniform. Then we formulate a beamforming design problem based on minimizing an upper bound on the asymptotic CRB (which is shown to be equivalent to {maximizing} the harmonic mean of the weighted beampattern responses at the target directions). Moreover, we impose a constraint on the SINR of each received communication signal to guarantee reliable communication performance. Two iterative algorithms are derived to tackle the non-convex design problem: one is based on the alternating direction method of multipliers, and the other uses the majorization-minimization technique to solve an equivalent minimax problem. Numerical results show that, through elaborate dual-function beamforming matrix design, the proposed algorithms can simultaneously achieve superior angle estimation performance as well as high-quality multi-user communications.