MU-MIMO Communications With MIMO Radar: From Co-Existence to Joint Transmission

TLDR

The authors propose beamforming techniques for a joint MIMO radar‑communication system in which a single device simultaneously serves as a radar and a communication base station, communicating with downlink users while detecting radar targets. They design two beamforming strategies—an antenna‑split scheme that places the radar signal in the null space of the downlink channel and a joint‑waveform scheme that shares a common waveform—optimizing the communication beamformer to match the radar beampattern, simplifying constraints with SINR penalty terms, and solving the weighted optimizations via efficient manifold algorithms. Numerical results show that the shared deployment outperforms the separated case significantly, and the proposed weighted optimizations achieve similar performance to the original optimizations with much lower computational complexity.

Abstract

Beamforming techniques are proposed for a joint multi-input-multi-output (MIMO) radar-communication (RadCom) system, where a single device acts as radar and a communication base station (BS) by simultaneously communicating with downlink users and detecting radar targets. Two operational options are considered, where we first split the antennas into two groups, one for radar and the other for communication. Under this deployment, the radar signal is designed to fall into the null-space of the downlink channel. The communication beamformer is optimized such that the beampattern obtained matches the radar's beampattern while satisfying the communication performance requirements. To reduce the optimizations' constraints, we consider a second operational option, where all the antennas transmit a joint waveform that is shared by both radar and communications. In this case, we formulate an appropriate probing beampattern, while guaranteeing the performance of the downlink communications. By incorporating the SINR constraints into objective functions as penalty terms, we further simplify the original beamforming designs to weighted optimizations, and solve them by efficient manifold algorithms. Numerical results show that the shared deployment outperforms the separated case significantly, and the proposed weighted optimizations achieve a similar performance to the original optimizations, despite their significantly lower computational complexity.