Active Reconfigurable Intelligent Surface-Assisted MISO Integrated Sensing and Communication Systems for Secure Operation

• Published in: IEEE transactions on vehicular technology Vol. 72; no. 4; pp. 1 - 13
• Main Authors: Salem, A. Abdelaziz, Ismail, Mahmoud H., Ibrahim, Ahmed S.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.04.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Active reconfigurable intelligent surfaces (RIS); alternating optimization; Beamforming; Budgets; Communications systems; Convexity; Eavesdropping; Integrated sensing and communication (ISAC); Mathematical programming; MISO (control systems); multiuser multi-input single-output (MU-MISO); Optimization; Passive radar; physical layer security (PLS); Radar; Radar detection; Reconfigurable intelligent surfaces; Reflection coefficient; Sensors; Signal to noise ratio; Unmanned aerial vehicles
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2022.3227319

Spectrum congestion has motivated the recent introduction of integrated sensing and communication (ISAC) systems where radar and communications functionalities co-exist and share the same spectrum. This is accompanied by extensive research in the area of reconfigurable intelligent surfaces (RIS), thanks to their ability to improve the ISAC systems. In this paper, the physical layer security of a multiuser multiple-input single-output (MU-MISO) ISAC system is investigated when the system is subject to eavesdropping by a malicious unmanned aerial vehicle (UAV). In particular, we propose using an active RIS to maximize the achievable secrecy rate of the system through jointly designing the radar receive beamformers, the active RIS reflection coefficients matrix and the transmit beamformers at the dual-function base station of the ISAC system. This is done while taking into account a minimum radar detection signal-to-noise ratio (SNR) and total system power budget constraints. The resulting non-convex optimization problem is tackled by exploiting fractional programming (FP) and majorization-minimization (MM) techniques to achieve a solution. Our numerical results show the superiority of active RIS to achieve the goal when compared with passive RIS or with an ISAC without an RIS. Results also show that passive RIS could still be a viable solution to achieve this goal but at the expense of a much larger needed size especially when lower power budgets are available.