4.7 Article Proceedings Paper

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

Journal

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
Volume 17, Issue 4, Pages 2755-2770

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2018.2803045

Keywords

MU-MISO downlink; radar-communication co-existence; beampattern design; beamforming; Riemannian manifold

Funding

  1. Engineering and Physical Sciences Research Council [EP/M014150/1]
  2. China Scholarship Council
  3. National Natural Science Foundation of China [61771047]
  4. European Research Council's Advanced Fellow Grant
  5. Engineering and Physical Sciences Research Council [EP/M014150/1] Funding Source: researchfish
  6. EPSRC [EP/M014150/1] Funding Source: UKRI

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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.

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