Energy-Efficient Hybrid Beamforming for Integrated Sensing and Communication Enabled mmWave MIMO Systems

TL;DR

This paper introduces an energy-efficient hybrid beamforming approach for integrated sensing and communication in mmWave MIMO systems, optimizing system performance while considering QoS and sensing constraints.

Contribution

It proposes a novel hybrid beamforming design that maximizes energy efficiency in ISAC-enabled mmWave MIMO systems using advanced optimization techniques.

Findings

The proposed algorithm improves energy efficiency compared to benchmarks.

The hybrid beamforming scheme effectively balances communication and sensing performance.

Simulation results validate the superiority of the method in various scenarios.

Abstract

This paper conceives a hybrid beamforming design (HBF) that maximizes the energy efficiency (EE) of an integrated sensing and communication (ISAC)-enabled millimeter wave (mmWave) multiple-input multiple-output (MIMO) system. In the system under consideration, an ISAC base station (BS) with the hybrid MIMO architecture communicates with multiple users and simultaneously detects multiple targets. The proposed scheme seeks to maximize the EE of the system, considering the signal-to-interference and noise ratio (SINR) as the user's quality of service (QoS) and the sensing beampattern gain of the targets as constraints. To solve this non-convex problem, we initially adopt Dinkelbach's method to convert the fractional objective function to subtractive form and subsequently obtain the sub-optimal fully-digital transmit beamformer by leveraging the principle of semi-definite relaxation. Subsequently, we propose a penalty-based manifold optimization scheme in conjunction with an alternating minimization method to determine the baseband (BB) and analog beamformers based on the designed fully-digital transmit beamformer. Finally, simulation results are given to demonstrate the efficacy of our proposed algorithm with respect to the benchmarks.