Hybrid Beamforming for Millimeter Wave MIMO Integrated Sensing and Communications

TL;DR

This paper proposes a hybrid beamforming method for mmWave MIMO systems that integrates sensing and communications, optimizing radar and communication performance simultaneously using an iterative approach.

Contribution

It introduces a novel alternating minimization algorithm that jointly designs transmit and phase vectors, along with analog and digital beamformers, for integrated sensing and communication systems.

Findings

Larger antenna arrays improve radar beam quality under SINR constraints.

The proposed method effectively balances radar and communication performance.

Simulation results validate the beamforming approach's effectiveness.

Abstract

In this letter, we consider hybrid beamforming for millimeter wave (mmWave) MIMO integrated sensing and communications (ISAC). We design the transmit beam of a dual-functional radar-communication (DFRC) base station (BS), aiming at approaching the objective radar beam pattern, subject to the constraints of the signal to interference-plus-noise ratio (SINR) of communication users and total transmission power of the DFRC BS. To provide additional degree of freedom for the beam design problem, we introduce a phase vector to the objective beam pattern and propose an alternating minimization method to iteratively optimize the transmit beam and the phase vector, which involves second-order cone programming and constrained least squared estimation, respectively. Then based on the designed transmit beam, we determine the analog beamformer and digital beamformer subject to the constant envelop constraint of phase shifter network in mmWave MIMO, still using the alternating minimization method. Simulation results show that under the same SINR constraint of communication users, larger antenna array can achieve better radar beam quality.