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

By Fan Liu, Christos Masouros, Ang Li, Huafei Sun, Lajos Hanzo. IEEE Transactions on Wireless Communications, 2017

893 citations recorded by the source corpus.

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.

Subfields: Aerospace Engineering

View Paper: https://www.semanticscholar.org/paper/520fe5dfff2add7370ddf78f2584947c6c69d241

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In Aerospace Engineering

Citations in the corpus

Integrated Sensing and Communication Signals Toward 5G-A and 6G: A Survey (2023, methodology): “The transmit waveform matrix is optimized for designing the radar beam pattern under the constraints of transmit power and signal-to-interference plus noise ratio (SINR) in [124].”
Optimal Transmit Beamforming for Integrated Sensing and Communication (2021, neutral): “, [6], [11], [12], [13], [14], [15], [16], [17], [18]).”
Secure Radar-Communication Systems With Malicious Targets: Integrating Radar, Communications and Jamming Functionalities (2019, methodology): “Note that an ideal radar beampattern should be obtained before designing the beamforming and artificial noise, which can be generated by solving the following constrained least-squares (LS) problem [9], [43] as an example”
Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond (2021, methodology): “As discussed in [117], the extra DoFs provided by the dedicated sensing signals enable the formation of a better MIMO radar beampattern with guaranteed SINR of CUs; this is superior to the conventional ISAC scheme that exploits WCSC only [120].”
Bayesian Predictive Beamforming for Vehicular Networks: A Low-Overhead Joint Radar-Communication Approach (2020, methodology): “Later on, more advanced DFRC approaches were studied under various conditions and constraints, such as Non Line-of-Sight (NLoS) channels [13], multi-user interference and peak-to-average-power ratio (PAPR)-constrained transmission [14].”
A Survey on Fundamental Limits of Integrated Sensing and Communication (2021, background): “For example, recently, there have been an increasing number of academic publications on ISAC, ranging from transceiver architecture and frame structure [3], [8], ISAC waveform design [9], [10], [11], joint coding design [12], [13], [14], temporal-spectral-spatial signal processing [15], [16], [17], ”
Cramér-Rao Bound Optimization for Joint Radar-Communication Beamforming (2021, methodology): “Design 2,” and “Proposed CRB-Min Design” to represent the DFRC beamforming technique in [11], [12], and the proposed method, respectively.”
Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead (2019, background): “To this end, the authors of [89] proposed several beamforming designs to enable joint MIMO radar transmission and MUMIMO communication, in which the communication signal was exploited for target detection, hence it would not affect the DL data rate.”
Full-Duplex Communication for ISAC: Joint Beamforming and Power Optimization (2022, background): “Leveraging this strategy, the authors in [9] advocated the reuse of transmit signal for both multi-user communication and radar sensing in ISAC systems.”
Joint Transmit Waveform and Passive Beamforming Design for RIS-Aided DFRC Systems (2021, methodology): “In recent years, MIMO architectures, which can provide spatial-domain DoFs, have been widely employed in DFRC systems [33]-[38] to improve the waveform diversity for radar sensing, as well as to achieve beamforming gains and spatial multiplexing for multi-user communications.”
Massive MIMO is a Reality - What is Next? Five Promising Research Directions for Antenna Arrays (2019, background): “We foresee that the high spatial degrees of freedom provided by large antenna arrays in both systems are key to achieving seamless spectral coexistence between radar and communication services [139].”
Enabling Joint Communication and Radar Sensing in Mobile Networks—A Survey (2020, methodology): “In [41], waveform optimization is studied for minimizing the difference between the generated signal and the desired sensing waveform.”
An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing (2021, neutral): “As an example, the JCR BF design in [16] aims to approximate a baseline radar beampattern while guaranteeing the individual signal-to-interference-and-noise ratio (SINR) γ k for K single-antenna downlink users.”
Joint Radar-Communication Strategies for Autonomous Vehicles: Combining Two Key Automotive Technologies (2019, methodology): “This can be overcome by restricting the radar beampattern [14], [15], which is in turn achieved by constraining the signal covariance.”
Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar (2019, methodology): “These studies can be divided into two categories: information embedding [31]–[37], [39] and transmit beamforming [19], [40]–[42].”
Radar-Assisted Predictive Beamforming for Vehicular Links: Communication Served by Sensing (2020, background): “Therefore, the authors of [13] have proposed a novel DFRC beamforming design for NLOS communication scenarios, which allows the use of intra-pulse modulation, and hence improves the data rate.”