Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar

By Xiang Liu, Tianyao Huang, Yimin Liu, Jie Zhou. IEEE Transactions on Signal Processing, 2019

941 citations recorded by the source corpus.

Future wireless communication systems are expected to explore spectral bands typically used by radar systems, in order to overcome spectrum congestion of traditional communication bands. Since in many applications radar and communication share the same platform, spectrum sharing can be facilitated by joint design as a dual-function radar-communications system. In this paper, we propose a joint transmit beamforming model for a dual-function multiple-input-multiple-output (MIMO) radar and multiuser MIMO communication transmitter. The proposed dual-function system transmits the weighted sum of independent radar waveforms and communication symbols, forming multiple beams towards the radar targets and the communication receivers, respectively. The design of the weighting coefficients is formulated as an optimization problem whose objective is the performance of the MIMO radar transmit beamforming, while guaranteeing that the signal-to-interference-plus-noise ratio (SINR) at each communication user is higher than a given threshold. Despite the non-convexity of the proposed optimization problem, we prove that it can be relaxed into a convex one, where the relaxation is tight. We then propose a reduced complexity design based on zero-forcing the inter-user interference and radar interference. Unlike previous works, which focused on the transmission of communication symbols to synthesize a radar transmit beam pattern, our method provides more degrees of freedom for MIMO radar and is thus able to obtain improved radar performance, as demonstrated in our simulation study. Furthermore, the proposed dual-function scheme approaches the radar performance of the radar-only scheme, i.e., without spectrum sharing, under reasonable communication quality constraints.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/821e4c255f237f8b881dfdb5f1bf7cc4ee26dae2

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Citations in the corpus

Waveform Design and Performance Analysis for Full-Duplex Integrated Sensing and Communication (2021, background): “…efforts towards to the joint radar-communication (JRC) design [35]–[38], where the performance metrics for both communication and sensing are jointly considered, such as those based on mutual information (MI) [35], waveform similarity [36], Cramer-Rao lower bound (CRLB) [37], and joint coding [38].”
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 Maneuver and Beamforming Design for UAV-Enabled Integrated Sensing and Communication (2021, methodology): “, [3], [4], [5], [6], [7], [8], [9], [10]).”
Enabling Joint Communication and Radar Sensing in Mobile Networks—A Survey (2020, background): “Decomposed spatial precoder Multibeam optimization where two pre-generated sub-beams are optimally combined, to support fast varying scanning directions and multiple targets [29], [77], [134], [135].”
Full-Duplex Communication for ISAC: Joint Beamforming and Power Optimization (2022, methodology): “Here, s 0 ∈ C N t × 1 represents a dedicated radar signal with covariance matrix V 0 E s 0 s H 0 } , for extending the DoF of the transmit signal x to achieve enhanced sensing performance [10].”
Throughput Maximization for UAV-Enabled Integrated Periodic Sensing and Communication (2022, neutral): “, E (sk[n]sk′ [n]) = 0, where k = k′, and k, k′ ∈ K [41].”
Integrated Sensing and Communications: Recent Advances and Ten Open Challenges (2023, methodology): “Inspired by the aforementioned beneﬁts of integration, sensing-assisted communication and communication-assisted sensing have attracted tremendous research attention in recent years [51], [52], [53], [54], [55], [56], [57], [58], [59].”
UAV-Enabled Integrated Sensing and Communication: Opportunities and Challenges (2022, methodology): “On the other hand, a target and users with small angular separation tend to be jointly served to improve energy efficiency, since the leakage power of the sensing beam towards a user can be utilized for information conveying [2], [10].”
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 to improve the waveform diversity for radar sensing, as well as to achieve beamforming gains and spatial multiplexing for multi-user communications [33], [34].”
Optimal Transmit Beamforming for Integrated Sensing and Communication (2021, neutral): “, [6], [11], [12], [13], [14], [15], [16], [17], [18]).”
Joint Radar-Communication Strategies for Autonomous Vehicles: Combining Two Key Automotive Technologies (2019, background): “, maximizing the signal-tointerference-plus-noise ratio (SINR) at the communications receiver while meeting a given radar beampattern [25].”
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].”