Joint Transmit Waveform and Receive Filter Design for Dual-Function Radar-Communication Systems

被引:88
作者
Tsinos, Christos G. [1 ,2 ]
Arora, Aakash
Chatzinotas, Symeon [1 ]
Ottersten, Bjorn [1 ]
机构
[1] Univ Luxembourg, Interdisciplinary Ctr Secur Reliabil & Trust SnT, Luxembourg, Luxembourg
[2] Natl & Kapodistrian Univ Athens, Gen Dept, Athens 15772, Greece
关键词
Radar; Interference; Radar antennas; Signal to noise ratio; Optimization; MIMO communication; Transmitting antennas; Radar-communication; beamforming; precoding; waveform design; MIMO; spectrum sharing; multiuser interference; nonconvex optimization; alternating optimization; gradient-projection (GP); OF-THE-ART; MIMO RADAR; CONSTANT MODULUS; SYMBOL-LEVEL; COEXISTENCE; SIGNAL; OPTIMIZATION;
D O I
10.1109/JSTSP.2021.3112295
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
In this paper, the problem of joint transmit waveform and receive filter design for dual-function radar-communication (DFRC) systems is studied. The considered system model involves a multiple antenna base station (BS) of a cellular system serving multiple single antenna users on the downlink. Furthermore, the BS simultaneously introduces sensing capabilities in the form of point-like target detection from the reflected return signals in a signal-dependent interference environment. A novel framework based on constrained optimization problems is proposed for the joint design of the transmit waveform and the radar receive filter such that different constraints related to the power amplifiers and the radar waveform are satisfied. In contrast to the existing approaches in the DFRC systems' literature, the proposed approach does not require the knowledge of a predetermined radar beampattern in order to optimize the performance of the radar part through its approximation. Instead, a beampattern is generated by maximizing the radar receive signal-to-interference ratio (SINR) thus, enabling a more flexible design. Moreover, the radar receive filter processing and its optimization is considered for the first time on DFRC systems, enabling the effective exploitation of the available degrees of freedom in the radar receive array. Efficient algorithmic solutions with guaranteed convergence are developed for the defined constrained nonconvex optimization problems. The effectiveness of the proposed solutions is verified via numerical results.
引用
收藏
页码:1378 / 1392
页数:15
相关论文
共 46 条
[1]   Symbol-Level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-Art, Classification, and Challenges [J].
Alodeh, Maha ;
Spano, Danilo ;
Kalantari, Ashkan ;
Tsinos, Christos G. ;
Christopoulos, Dimitrios ;
Chatzinotas, Symeon ;
Ottersten, Bjorn .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2018, 20 (03) :1733-1757
[2]  
[Anonymous], 2012, FCC PROP INN SMALL C
[3]  
[Anonymous], 2014, FUNDAMENTALS RADAR S
[4]   Knowledge-Aided (Potentially Cognitive) Transmit Signal and Receive Filter Design in Signal-Dependent Clutter [J].
Aubry, A. ;
De Maio, A. ;
Farina, A. ;
Wicks, M. .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2013, 49 (01) :93-117
[5]   Optimizing Radar Waveform and Doppler Filter Bank via Generalized Fractional Programming [J].
Aubry, Augusto ;
De Maio, Antonio ;
Naghsh, Mohammad Mahdi .
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2015, 9 (08) :1387-1399
[6]  
Bertsekas D. P, 1999, ATHENA SCI OPTIMIZAT, V2nd
[7]   Training-based MIMO channel estimation: A study of estimator tradeoffs and optimal training signals [J].
Biguesh, M ;
Gershman, AB .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2006, 54 (03) :884-893
[8]   Multiobjective Signal Processing Optimization [The way to balance conflicting metrics in 5G systems] [J].
Bjoernson, Emil ;
Jorswieck, Eduard ;
Debbah, Merouane ;
Ottersten, Bjoern .
IEEE SIGNAL PROCESSING MAGAZINE, 2014, 31 (06) :14-23
[9]   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
[10]  
Cisco, 2018, CISCO VISUAL NETWORK