Secure Radar-Communication Systems With Malicious Targets: Integrating Radar, Communications and Jamming Functionalities

Su, Nanchi; Liu, Fan; Masouros, Christos

doi:10.1109/twc.2020.3023164

Cited by 156 publications

(119 citation statements)

References 46 publications

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“…In addition to those general advantages, one may also leverage the sensing results to facilitate communication, where significant performance gain can be obtained over that of the conventional communicationonly schemes. Examples are sensing-assisted BF [45]- [48] and sensing-assisted secure communications [49]. Below we briefly review the recent state-of-the-art on sensing-assisted BF.…”

Section: E Sensing Assisted Communicationsmentioning

confidence: 99%

An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing

Zhang

Liu

Masouros

et al. 2021

IEEE J. Sel. Top. Signal Process.

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481

152

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Joint communication and radar sensing (JCR) represents an emerging research field aiming to integrate the above two functionalities into a single system, by sharing the majority of hardware, signal processing modules and, in a typical case, the transmitted signal. The close cooperation of the communication and sensing functions can enable significant improvement of spectrum efficiency, reduction of device size, cost and power consumption, and improvement of performance of both functions. Advanced signal processing techniques are critical for making the integration efficient, from transmission signal design to receiver processing. This paper provides a comprehensive overview of the state-of-the-art on JCR systems from the signal processing perspective. A balanced coverage on both transmitter and receiver is provided for three types of JCR systems, namely, communicationcentric, radar-centric, and joint design and optimization.

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Section: E Sensing Assisted Communicationsmentioning

confidence: 99%

An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing

Zhang

Liu

Masouros

et al. 2021

IEEE J. Sel. Top. Signal Process.

Self Cite

481

152

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“…In particular, we assume that the DFRC BS employs a uniform linear array (ULA) with half-wavelength spacing between adjacent antennas. The channel between the BS and the R-user is assumed to have pure line-of-sight (LoS) associated with the path loss of L R = L 0 + 20log 10 d R , while between the BS and C-user it is assumed to obey the Rayleigh channel model with the path loss of [17,24], where L 0 is the path loss at the reference distance d = 1 meter (m), and d R and d C represents the distance from the BS to the R-user and to the C-user, respectively. The parameters adopted in simulations are set as follows: L 0 = 40 dB, d R = 1000 m, and d C = 100 m. The noise power in the receiver of users is assumed to be the same, which is set to σ 2 = −100 dBm.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Moreover, Huang et al [22] and Ma et al [23] employed index modulation and spatial modulation techniques for DFRC, respectively. Su et al [24] studied the secure transmission for DFRC, where the radar target was treated as an eavesdropper and artificial noise was employed for degrading its received SINR, while satisfying the communication requirements of the legitimate users. To reveal the fundamental performance limits of DFRC, Chen et al [25] proposed a Pareto optimization framework, where a performance region was defined relying on the difference between the peak and sidelobe (DPSL) of the radar and the SINR achieved by the communication user.…”

Section: ) Studies On Dfrcmentioning

confidence: 99%

NOMA-Aided Joint Radar and Multicast-Unicast Communication Systems

Mu,

Liu,

Guo

et al. 2021

Preprint

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The novel concept of non-orthogonal multiple access (NOMA) aided joint radar and multicastunicast communication (Rad-MU-Com) is investigated. Employing the same spectrum resource, a multiinput-multi-output (MIMO) dual-functional radar-communication (DFRC) base station detects the radarcentric users (R-user), while transmitting mixed multicast-unicast messages both to the R-user and to the communication-centric user (C-user). In particular, the multicast information is intended for both the R-and C-users, whereas the unicast information is only intended for the C-user. More explicitly, NOMA is employed to facilitate this double spectrum sharing, where the multicast and unicast signals are superimposed in the power domain and the superimposed communication signals are also exploited as radar probing waveforms. First, a beamformer-based NOMA-aided joint Rad-MU-Com framework is proposed for the system having a single R-user and a single C-user. Based on this framework, the unicast rate maximization problem is formulated by optimizing the beamformers employed, while satisfying the rate requirement of multicast and the predefined accuracy of the radar beam pattern. The resultant non-convex optimization problem is solved by a penalty-based iterative algorithm to find a high-quality near-optimal solution. Next, the system is extended to the scenario of multiple pairs of R-and C-users, where a cluster-based NOMA-aided joint Rad-MU-Com framework is proposed. A joint beamformer design and power allocation optimization problem is formulated for the maximization of the sum of the unicast rate at each C-user, subject to the constraints on both the minimum multicast rate for each

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“…Sun et al [24] consider IRS-assisted base station when both jammer and ED are present and develop an interesting JTRB design without the knowledge of jammer's transmit beamformer and ED's CSI. Some recent works [15,[25][26][27] also consider IRS-aided secrecy for dual-function sensing-communications [28].…”

Section: Introductionmentioning

confidence: 99%

Joint Transmit and Reflective Beamformer Design for Secure Estimation in IRS-Aided WSNs

Ahmed¹,

Rajput²,

Venkategowda³

et al. 2022

Preprint

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Wireless sensor networks (WSNs) are vulnerable to eavesdropping as the sensor nodes (SNs) communicate over an open radio channel. Intelligent reflecting surface (IRS) technology can be leveraged for physical layer security in WSNs. In this paper, we propose a joint transmit and reflective beamformer (JTRB) design for secure parameter estimation at the fusion center (FC) in the presence of an eavesdropper (ED) in a WSN. We develop a semidefinite relaxation (SDR)-based iterative algorithm, which alternately yields the transmit beamformer at each SN and the corresponding reflection phases at the IRS, to achieve the minimum mean-squared error (MSE) parameter estimate at the FC, subject to transmit power and ED signal-to-noise ratio constraints. Our simulation results demonstrate robust MSE and security performance of the proposed IRS-based JTRB technique.

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Secure Radar-Communication Systems With Malicious Targets: Integrating Radar, Communications and Jamming Functionalities

Cited by 156 publications

References 46 publications

An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing

An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing

NOMA-Aided Joint Radar and Multicast-Unicast Communication Systems

Joint Transmit and Reflective Beamformer Design for Secure Estimation in IRS-Aided WSNs

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