Enhancing the Physical Layer Security of Dual-Functional Radar Communication Systems

Abstract

Dual-functional radar communication (DFRC) system has recently attracted significant academic attentions as an enabling solution for realizing radar-communication spectrum sharing. During the DFRC transmission, however, the critical information could be leaked to the targets, which might be potential eavesdroppers. Therefore, the physical layer security has to be taken into consideration. In this paper, fractional programming (FP) problems are formulated to minimize the signal-to-interference-plus-noise ratio (SINR) at targets under the constraints for the SINR of legitimate users. By doing so, the secrecy rate of communication can be guaranteed. We first assume that communication CSI and the angle of the target are precisely known. After that, problem is extended to the cases with uncertainty in the target's location, which indicates that the target might appear in a certain angular interval. Finally, numerical results have been provided to validate the effectiveness of the proposed method showing that it is viable to guarantee both radar and secrecy communication performances by using the techniques we propose.Index Terms-DFRC system, physical layer security, FP problem, secrecy rate.

Optimal Transmit Beamforming for Secrecy Integrated Sensing and Communication

“…We consider the line of sight (LoS) channel from the BS to both trusted and untrusted targets, similarly as in prior works [12,13]. Let θ k denote the angle of departure (AoD) from the BS to target k. Accordingly, the steering vector with angle θ k is given as…”

“…For instance, the authors in [11] studied the secrecy ISAC system with one CU and one eavesdropping target, in which the transmit covariance matrices of both information signals and AN were jointly optimized to maximize the CU's secrecy rate while ensuring the received signal-to-interference-plus-noise ratio (SINR) for sensing. The authors in [12,13] further considered the scenario with multiple CUs and one eavesdropping target, in which the signal-to-noise ratio (SNR) at the eavesdropping target was minimized while ensuring the CUs' individual SINR constraints and certain sensing beampattern requirements. Due to the non-convexity of the formulated problems, only suboptimal beamforming/precoding designs were obtained in these prior works [11][12][13] under their respective setups.…”

“…The authors in [12,13] further considered the scenario with multiple CUs and one eavesdropping target, in which the signal-to-noise ratio (SNR) at the eavesdropping target was minimized while ensuring the CUs' individual SINR constraints and certain sensing beampattern requirements. Due to the non-convexity of the formulated problems, only suboptimal beamforming/precoding designs were obtained in these prior works [11][12][13] under their respective setups.…”

Interference and noise cancellation for joint communication radar (JCR) system based on contextual information

“…Therefore, beamforming designs for full and/or half-duplex transmit and receive communication mitigates the interference between radar and communications signals at the expense of the PLS of the communication signals. However, to ameliorate the PLS concerns, the communication signal and some artificial noise (AN) were embedded onto the beamforming weights of the radar transmission [12]. Furthermore, the DFRC system was implemented by using the main lobe for radar and the sidelobes for communication transmissions [13].…”

“…The communication signals were embedded in the signal waveforms determined by 2 different beamforming weights (representing 0 and 1). Although attempts were made by [12] and [13] to incorporate PLS in DFRC system, they were transmissioncentred, based on statistical knowledge of the channel impulse and required handshake between the communication transmitter and genuine receivers.…”