Generalized Transceiver Beamforming for DFRC With MIMO Radar and MU-MIMO Communication

被引:108
作者
Chen, Li [1 ]
Wang, Zhiqin [2 ]
Du, Ying
Chen, Yunfei [3 ]
Yu, F. Richard [4 ]
机构
[1] Univ Sci & Technol China, CAS Key Lab Wireless Opt Commun, Hefei 101127, Peoples R China
[2] China Acad Informat & Commun Technol, Beijing 100190, Peoples R China
[3] Univ Warwick, Sch Engn, Coventry CV4 7AL, W Midlands, England
[4] Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON K1S 5B6, Canada
基金
中国国家自然科学基金;
关键词
Radar; Array signal processing; MIMO radar; Copper; Sensors; Interference; MIMO communication; Beamforming; multi-antenna; MU-MIMO; performance region; transceiver design; WAVE-FORM DESIGN; JOINT RADAR; SIDELOBE CONTROL; MILLIMETER-WAVE; SYSTEMS; OPTIMIZATION; COEXISTENCE; INFORMATION; TARGETS;
D O I
10.1109/JSAC.2022.3155515
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Spatial beamforming is an efficient way to realize dual-functional radar-communication (DFRC). In this paper, we study the DFRC design for a general scenario, where the dual-functional base station (BS) simultaneously detects the target as a multiple-input-multiple-output (MIMO) radar while communicating with multiple multi-antenna communication users (CUs). This necessitates a joint transceiver beamforming design for both MIMO radar and multi-user MIMO (MU-MIMO) communication. In order to characterize the performance tradeoff between MIMO radar and MU-MIMO communication, we first define the achievable performance region of the DFRC system. Then, both radar-centric and communication-centric optimizations are formulated to achieve the boundary of the performance region. For the radar-centric optimization, successive convex approximation (SCA) method is adopted to solve the non-convex constraint. For the communication-centric optimization, a solution based on weighted mean square error (MSE) criterion is obtained to solve the non-convex objective function. Furthermore, two low-complexity beamforming designs based on CU-selection and zero-forcing are proposed to avoid iteration, and the closed-form expressions of the low-complexity beamforming designs are derived. Simulation results are provided to verify the effectiveness of all proposed designs.
引用
收藏
页码:1795 / 1808
页数:14
相关论文
共 43 条
[1]   Internet of Radars: Sensing versus Sending with Joint Radar-Communications [J].
Akan, Ozgur B. ;
Arik, Muharrem .
IEEE COMMUNICATIONS MAGAZINE, 2020, 58 (09) :13-19
[2]  
[Anonymous], 1994, An Introduction to Signal Detection and Estimation
[3]   HIGH-RESOLUTION FREQUENCY-WAVENUMBER SPECTRUM ANALYSIS [J].
CAPON, J .
PROCEEDINGS OF THE IEEE, 1969, 57 (08) :1408-&
[4]   MIMO Radar Waveform Optimization With Prior Information of the Extended Target and Clutter [J].
Chen, Chun-Yang ;
Vaidyanathan, P. P. .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2009, 57 (09) :3533-3544
[5]   Joint Radar-Communication Transmission: A Generalized Pareto Optimization Framework [J].
Chen, Li ;
Liu, Fan ;
Wang, Weidong ;
Masouros, Christos .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2021, 69 :2752-2765
[6]   Time Allocation for Integrated Bi-Static Radar and Communication Systems [J].
Chen, Yunfei ;
Gu, Xueyun .
IEEE COMMUNICATIONS LETTERS, 2021, 25 (03) :1033-1036
[7]   Weighted Sum-Rate Maximization for Full-Duplex MIMO Interference Channels [J].
Cirik, Ali Cagatay ;
Wang, Rui ;
Hua, Yingbo ;
Latva-aho, Matti .
IEEE TRANSACTIONS ON COMMUNICATIONS, 2015, 63 (03) :801-815
[8]  
Gaudio L., 2019, 2019 IEEE INT C COMM, P1
[9]   Beampattern Synthesis With Sidelobe Control and Applications [J].
Gemechu, Ashenafi Yadessa ;
Cui, Guolong ;
Yu, Xianxiang ;
Kong, Lingjiang .
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, 2020, 68 (01) :297-310
[10]   Localization via ultra-wideband radios [J].
Gezici, S ;
Tian, Z ;
Giannakis, GB ;
Kobayashi, H ;
Molisch, AF ;
Poor, HV ;
Sahinoglu, Z .
IEEE SIGNAL PROCESSING MAGAZINE, 2005, 22 (04) :70-84