On Radar Privacy in Shared Spectrum Scenarios

Dimas, Anastasios; Li, Bo; Psounis, Konstantinos; Petropulu, Athina P.

doi:10.1109/icassp.2019.8682745

Cited by 15 publications

(7 citation statements)

References 13 publications

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“…Accordingly, a number of performance trade-offs involving the radar detection and estimation performance, the communication rate and the secrecy rate remain to be studied. Some initial works on this topic can be found in [113]- [115].…”

Section: ) Learning Based Crssmentioning

confidence: 99%

Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead

Liu

Masouros

Petropulu

et al. 2020

IEEE Trans. Commun.

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602

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For the sake of enhancing the exploitation of the permanently allocated, but potentially under-utilized spectral resources, sharing the frequency bands between radar and communication systems has attracted substantial attention. More explicitly, there is increasing demand for sharing both the frequency band and the hardware platform between these two functionalities, but naturally, its success critically hinges on highquality joint sensing and communications. In this paper, we firstly overview the application scenarios and the research progress in the area of communication and radar spectrum sharing, with particular emphasis on: 1) Radar-communication coexistence; 2) Dual-functional radar-communication (DFRC) systems. In the remainder of the paper, we propose a novel transceiver architecture and frame structure for a DFRC base station (BS) operating in the millimeter wave (mmWave) band, using the hybrid analog-digital (HAD) beamforming technique. We assume that the BS is serving a multi-antenna aided user equipment (UE) operating in a mmWave channel, which in the meantime actively detects multiple targets. Note that part of the targets also play the role of scatterers for the communication signal. Given this framework, we then propose a novel scheme for joint target search and communication channel estimation relying on the omni-directional pilot signals generated by the HAD structure. Given a fully-digital communication precoder and a desired radar transmit beampattern, we propose to design the analog and digital precoders under non-convex constant-modulus (CM) and power constraints, such that the BS can formulate narrow beams towards all the targets, while pre-equalizing the impact of the communication channel. Furthermore, we design an HAD receiver that can simultaneously process signals from the UE and echo waves from the targets. By tracking the angular variation of the targets, we show that it is possible to recover the target echoes and mitigate the potential interference imposed on the UE signals by invoking the successive interference cancellation (SIC) technique, even when the radar and communication signals share the equivalent signal-to-noise ratio (SNR). The feasibility and the efficiency of the proposed approaches in realizing DFRC are verified via numerical simulations. Finally, our discussions are summarized by overviewing the open problems in the research field of CRSS.

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Section: ) Learning Based Crssmentioning

confidence: 99%

Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead

Liu

Masouros

Petropulu

et al. 2020

IEEE Trans. Commun.

Self Cite

1,012

602

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show abstract

“…The inclusion of data into the probing signal, used to illuminate targets, makes it prone to eavesdropping by potentially malicious radar targets [196]. Even if the data itself is protected with higher layer encryption, the existence of a communication link can still be detected by a malicious target that can jeopardize the communication privacy, reveal the AP's location and ID and make it prone to cyberattacks [197]- [199]. Classical communication-only PHY security solutions often involve reducing the signal power in the direction of the eavesdropper (target), which would severely deteriorate the sensing performance of ISAC.…”

Section: Sensing-assisted Phy Securitymentioning

confidence: 99%

Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond

Liu

Cui

Masouros

et al. 2022

IEEE J. Select. Areas Commun.

771

277

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As the standardization of 5G solidifies, researchers are speculating what 6G will be. The integration of sensing functionality is emerging as a key feature of the 6G Radio Access Network (RAN), allowing for the exploitation of dense cell infrastructures to construct a perceptive network. In this IEEE Journal on Selected Areas in Communications (JSAC) Special Issue overview, we provide a comprehensive review on the background, range of key applications and state-of-the-art approaches of Integrated Sensing and Communications (ISAC). We commence by discussing the interplay between sensing and communications (S&C) from a historical point of view, and then consider the multiple facets of ISAC and the resulting performance gains. By introducing both ongoing and potential use cases, we shed light on the industrial progress and standardization activities related to ISAC. We analyze a number of performance tradeoffs between S&C, spanning from information Manuscript

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“…The authors in [141] investigated whether or not a malicious opponent could infer the radar's location through veiled radar information contained in the system's precoder. An MLbased location inference attack was simulated for two specific precoder schemes.…”

Section: ) Privacy Protection For Pus In Ss Networkmentioning

confidence: 99%

When Machine Learning Meets Spectrum Sharing Security: Methodologies and Challenges

Wang

Sun

et al. 2022

IEEE Open J. Commun. Soc.

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The exponential growth of internet connected systems has generated numerous challenges, such as spectrum shortage issues, which require efficient spectrum sharing (SS) solutions. Complicated and dynamic SS systems can be exposed to different potential security and privacy issues, requiring protection mechanisms to be adaptive, reliable, and scalable. Machine learning (ML) based methods have frequently been proposed to address those issues. In this article, we provide a comprehensive survey of the recent development of ML based SS methods, the most critical security issues, and corresponding defense mechanisms. In particular, we elaborate the state-of-the-art methodologies for improving the performance of SS communication systems for various vital aspects, including ML based cognitive radio networks (CRNs), ML based database assisted SS networks, ML based LTE-U networks, ML based ambient backscatter networks, and other ML based SS solutions. We also present security issues from the physical layer and corresponding defending strategies based on ML algorithms, including Primary User Emulation (PUE) attacks, Spectrum Sensing Data Falsification (SSDF) attacks, jamming attacks, eavesdropping attacks, and privacy issues. Finally, extensive discussions on open challenges for ML based SS are also given. This comprehensive review is intended to provide the foundation for and facilitate future studies on exploring the potential of emerging ML for coping with increasingly complex SS and their security problems.

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On Radar Privacy in Shared Spectrum Scenarios

Cited by 15 publications

References 13 publications

Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead

Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead

Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond

When Machine Learning Meets Spectrum Sharing Security: Methodologies and Challenges

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