Kullback-Leibler Divergence Based ISAC Constellation and Beamforming Design in the Presence of Clutter

doi:10.12142/ZTECOM.202403002

ZTE Communications ›› 2024, Vol. 22 ›› Issue (3): 4-12.DOI: 10.12142/ZTECOM.202403002

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Kullback-Leibler Divergence Based ISAC Constellation and Beamforming Design in the Presence of Clutter

TANG Shuntian, WANG Xinyi(), XIA Fanghao, FEI Zesong

Beijing Institute of Technology, Beijing 100081, China

Received:2024-07-02 Online:2024-09-25 Published:2024-09-29
About author:TANG Shuntian received his BE degree in electronic engineering from Beijing Institute of Technology (BIT), China in 2024. He is currently pursuing his master’s degree with BIT. His research interests include integrated sensing and communications and AFDM modulation.
WANG Xinyi ( bit_wangxy@163.com) received his BE and PhD degrees in electronic engineering from Beijing Institute of Technology (BIT), China in 2017 and 2022, respectively. He is currently a postdoctoral researcher at BIT. He was a recipient of the Best Paper Award in WOCC 2019 and has been recognized as an exemplary reviewer for the IEEE Transactions on Communications. His research interests include integrated sensing and communications, UAV communications, intelligent reflecting surface, polar codes, and OTFS modulation. He has published over 50 journals and conference papers in these areas.
XIA Fanghao received his BS degree in electronic engineering from Beijing Institute of Technology (BIT), China in 2021. He is currently pursuing his PhD degree with the Research Institute of Communication Technology, BIT. His research interests include integrated sensing and communications, intelligent reflection surface, and physical layer security.
FEI Zesong received his PhD degree in electronic engineering from Beijing Institute of Technology (BIT), China in 2004. He is currently a professor with the Research Institute of Communication Technology, BIT, where he is involved in the design of the next generation high-speed wireless communication. He is the chief investigator with the National Natural Science Foundation of China. His research interests include wireless communications and multimedia signal processing. He is a senior member of the Chinese Institute of Electronics and China Institute of Communications.
Supported by:
National Key R&D Program of China(2021YFB2900200);National Natural Science Foundation of China(U20B2039);China Postdoctoral Science Foundation(2023TQ0028)

Abstract

Abstract:

Integrated sensing and communication (ISAC) is regarded as a pivotal technology for 6G communication. In this paper, we employ Kullback-Leibler divergence (KLD) as the unified performance metric for ISAC systems and investigate constellation and beamforming design in the presence of clutters. In particular, the constellation design problem is solved via the successive convex approximation (SCA) technique, and the optimal beamforming in terms of sensing KLD is proven to be equivalent to maximizing the signal-to-interference-plus-noise ratio (SINR) of echo signals. Numerical results demonstrate the tradeoff between sensing and communication performance under different parameter setups. Additionally, the beampattern generated by the proposed algorithm achieves significant clutter suppression and higher SINR of echo signals compared with the conventional scheme.

Key words: constellation design, clutter suppression, integrated sensing and communications, Kullback-Leibler divergence

TANG Shuntian, WANG Xinyi, XIA Fanghao, FEI Zesong. Kullback-Leibler Divergence Based ISAC Constellation and Beamforming Design in the Presence of Clutter[J]. ZTE Communications, 2024, 22(3): 4-12.

Figures/Tables 7

References 21

1	LIU F, ZHENG L, CUI Y H, et al. Seventy years of radar and communications: the road from separation to integration [J]. IEEE signal processing magazine, 2023, 40( 5): 106– 121. DOI: 10.1109/MSP.2023.3272881
2	LIANG H, LIAO B. Robust hybrid beamforming for MIMO-ISAC system with CSI imperfection [C]// The 6th International Conference on Information Communication and Signal Processing (ICICSP). IEEE, 2023: 665– 669. DOI: 10.1109/ICICSP59554.2023.10390724
3	CHEN W J, DENG Y L, GUO C T, et al. Transmit beampattern optimization for MIMO-ISAC systems with hybrid beamforming [C]// The IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2024: 8651– 8655. DOI: 10.1109/ICASSP48485.2024.10447252
4	LIU R, LI M, LIU Q, et al. Dual-functional radar-communication waveform design: a symbol-level precoding approach [J]. IEEE journal of selected topics in signal processing, 2021, 15( 6): 1316– 1331. DOI: 10.1109/JSTSP.2021.3111438
5	ZHANG Y, QI H T, LU W D, et al. Beamforming design for IRS-assisted OFDM-ISAC system in C-RAN [J]. IEEE wireless communications letters, 2024, 13( 6): 1626– 1630. DOI: 10.1109/LWC.2024.3384249
6	LIU W X, XU H B, HE X L, et al. Bi-level deep unfolding based robust beamforming design for IRS-assisted ISAC system [J]. IEEE access, 2024, 12: 76663– 76672. DOI: 10.1109/ACCESS.2024.3406527
7	ZHAO Z Y, ZHANG L, JIANG R, et al. Joint beamforming scheme for ISAC systems via robust Cramér-Rao bound optimization [J]. IEEE wireless communications letters, 2024, 13( 3): 889– 893. DOI: 10.1109/LWC.2024.3349488
8	WANG X Y, FEI Z S, HUANG J X, et al. Joint waveform and discrete phase shift design for RIS-assisted integrated sensing and communication system under cramer-Rao bound constraint [J]. IEEE transactions on vehicular technology, 2022, 71( 1): 1004– 1009. DOI: 10.1109/TVT.2021.3122889
9	FUHRMANN D R, ANTONIO G SAN. Transmit beamforming for MIMO radar systems using signal cross-correlation [J]. IEEE transactions on aerospace and electronic systems, 2008, 44( 1): 171– 186. DOI: 10.1109/TAES.2008.4516997
10	TANG B, NAGHSH M M, TANG J. Relative entropy-based waveform design for MIMO radar detection in the presence of clutter and interference [J]. IEEE transactions on signal processing, 2015, 63( 14): 3783– 3796. DOI: 10.1109/TSP.2015.2423257
11	LI J, ZHOU G, GONG T T, et al. A framework for mutual information-based MIMO integrated sensing and communication beamforming design [J]. IEEE transactions on vehicular technology, 2024, 73( 6): 8352– 8366. DOI: 10.1109/TVT.2024.3355899
12	PIAO J H, WEI Z Q, YUAN X, et al. Mutual information metrics for uplink MIMO-OFDM integrated sensing and communication system [C]// IEEE Global Communications Conference. IEEE, 2023: 7387– 7392. DOI: 10.1109/GLOBECOM54140.2023.10437900
13	AL-JARRAH M, ALSUSA E, MASOUROS C. A unified performance framework for integrated sensing-communications based on KL-divergence [J]. IEEE transactions on wireless communications, 2023, 22( 12): 9390– 9411. DOI: 10.1109/TWC.2023.3270390
14	FEI Z, TANG S, WANG X, et al. Revealing the trade-off in ISAC systems: the KL divergence perspective [J]. IEEE wireless communications letters. 2024, 13( 10): 2747 - 2751. DOI: 10.1109/LWC.2024.3443409
15	KLOOB Y, AL-JARRAH M, ALSUSA E, et al. Novel KLD-based resource allocation for integrated sensing and communication [J]. IEEE transactions on signal processing, 2024, 72: 2292– 2307. DOI: 10.1109/TSP.2024.3392350
16	KAILATH T. The divergence and bhattacharyya distance measures in signal selection [J]. IEEE transactions on communication technology, 1967, 15( 1): 52– 60. DOI: 10.1109/TCOM.1967.1089532
17	WANG X Y, FEI Z S, LIU P, et al. Sensing aided covert communications: turning interference into allies [J]. IEEE transactions on wireless communications, 2024, PP(99): 1. DOI: 10.1109/TWC.2024.3374775
18	JEANNE R S, SAMUNDISWARY P. Power minimization in MIMO-OFDM network with energy harvesting node using Successive Convex Approximation (SCA) technique [C]// Proceedings of International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT). IEEE, 2016: 431– 436. DOI: 10.1109/ICCICCT.2016.7987988
19	WALDSPURGER I, D’ASPREMONT A, MALLAT S. Phase recovery, MaxCut and complex semidefinite programming [J]. Mathematical programming, 2015, 149( 1): 47– 81. DOI: 10.1007/s10107-013-0738-9
20	BUDHU J, GRBIC A. Accelerated optimization of metasurfaces with the Woodbury matrix identity [C]// International Applied Computational Electromagnetics Society Symposium (ACES). IEEE, 2021: 1– 3
21	SUN J G. Eigenvalues of Rayleigh quotient matrices [J]. Numerische mathematik, 1991, 59( 1): 603– 614. DOI: 10.1007/BF01385798

Kullback-Leibler Divergence Based ISAC Constellation and Beamforming Design in the Presence of Clutter

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