Secure Dual-Functional Radar-Communication System via Exploiting Known Interference in the Presence of Clutter

This paper addresses the problem that designing the transmit waveform and receive beamformer aims to maximize the receive radar SINR for secure dual-functional radar- communication (DFRC) systems, where the undesired multi- user interference (MUI) is transformed to useful power. In this system, the DFRC base station (BS) serves communication users (CUs) and detects the target simultaneously, where the radar target is regarded to be malicious since it might eavesdrop the transmitted information from BS to CUs. Inspired by the constructive interference (CI) approach, the phases of received signals at CUs are rotated into the relaxed decision region, and the undesired MUI is designed to contribute in useful power. Then, the convex approximation method (SCA) is adopted to tackle the optimization problem. Finally, numerical results are given to validate the effectiveness of the proposed method, which shows that it is viable to ensure the communication data secure adopting the techniques that we propose.

[1]  Kee Chaing Chua,et al.  Secrecy wireless information and power transfer with MISO beamforming , 2013, 2013 IEEE Global Communications Conference (GLOBECOM).

[2]  Yurii Nesterov,et al.  Interior-point polynomial algorithms in convex programming , 1994, Siam studies in applied mathematics.

[3]  Christos Masouros,et al.  Composite Signalling for DFRC: Dedicated Probing Signal or Not? , 2020, ArXiv.

[4]  Christos Masouros,et al.  Exploiting Known Interference as Green Signal Power for Downlink Beamforming Optimization , 2015, IEEE Transactions on Signal Processing.

[5]  A. D. Wyner,et al.  The wire-tap channel , 1975, The Bell System Technical Journal.

[6]  Symeon Chatzinotas,et al.  Directional Modulation Via Symbol-Level Precoding: A Way to Enhance Security , 2016, IEEE Journal of Selected Topics in Signal Processing.

[7]  Wen-Qin Wang,et al.  Ergodic Interference Alignment for Spectrum Sharing Radar-Communication Systems , 2019, IEEE Transactions on Vehicular Technology.

[8]  Philip Wolfe,et al.  An algorithm for quadratic programming , 1956 .

[9]  Christos Masouros,et al.  An Efficient Manifold Algorithm for Constructive Interference Based Constant Envelope Precoding , 2017, IEEE Signal Processing Letters.

[10]  Christos Masouros,et al.  Secure Radar-Communication Systems With Malicious Targets: Integrating Radar, Communications and Jamming Functionalities , 2019, IEEE Transactions on Wireless Communications.

[11]  Anton van den Hengel,et al.  Semidefinite Programming , 2014, Computer Vision, A Reference Guide.

[12]  Stephen P. Boyd,et al.  General Heuristics for Nonconvex Quadratically Constrained Quadratic Programming , 2017, 1703.07870.

[13]  Hongbin Li,et al.  MIMO Radar Waveform Design With Constant Modulus and Similarity Constraints , 2014, IEEE Transactions on Signal Processing.

[14]  Pinyi Ren,et al.  Rethinking Secure Precoding via Interference Exploitation: A Smart Eavesdropper Perspective , 2019, IEEE Transactions on Information Forensics and Security.

[15]  Vishal Monga,et al.  Successive QCQP Refinement for MIMO Radar Waveform Design Under Practical Constraints , 2016, IEEE Transactions on Signal Processing.

[16]  Zhi-Quan Luo,et al.  Semidefinite Relaxation of Quadratic Optimization Problems , 2010, IEEE Signal Processing Magazine.

[17]  Christos Masouros,et al.  Dynamic linear precoding for the exploitation of known interference in MIMO broadcast systems , 2009, IEEE Transactions on Wireless Communications.

[18]  Shannon D. Blunt,et al.  Radar Spectrum Engineering and Management: Technical and Regulatory Issues , 2015, Proceedings of the IEEE.