Dual-UAV-Enabled Secure Communication and Sensing for A2G-ISAC Systems with Maneuverable Jamming

In this paper, we propose a dual-unmanned aerial vehicle (UAV)-enabled secure communication and sensing (SCS) scheme for an air-to-ground integrated sensing and communication (ISAC) system, in which a dual-functional source UAV and jamming UAV collaborate to enhance both the secure communication and target sensing performance. From a perspective of hybrid monostatitc-bistatic radar, the jamming UAV maneuvers to aid the source UAV to detect multiple ground targets by emitting artificial noise, meanwhile interfering with the ground eavesdropper. Residual interference is considered to reflect the effects of imperfect successive interference cancellation (SIC) on the receive signal-plus-interference-to-noise ratios, which results in a degraded system performance. To maximize the average secrecy rate (ASR), the dual-UAV trajectory and dual-UAV beamforming are jointly optimized subject to the transmit power budget, UAV maneuvering constraint, and sensing requirements. To tackle the highly complicated non-convex ASR maximization problem, the dual-UAV trajectory and dual-UAV beamforming are optimized for the secure communication (SC) purpose and the SCS purpose, sequentially. In the SC phase, a block coordinate descent algorithm is proposed to optimize the dual-UAV trajectory and dual-UAV beamforming iteratively, using the trust-region successive convex approximation (SCA) and semidefinite relaxation (SDR) techniques. Then, a weighted distance minimization problem is formulated to determine the dual-UAV maneuvering positions suitable for the SCS purpose, which is solved by a heuristic greedy algorithm, followed by the joint optimization of source beamforming and jamming beamforming.

Extreme Level Crossing Rate: A New Performance Indicator for URLLC Systems

Level crossing rate (LCR) is a well-known statistical tool that is related to the duration of a random stationary fading process \emph{on average}. In doing so, LCR cannot capture the behavior of \emph{extremely rare} random events. Nonetheless, the latter events play a key role in the performance of ultra-reliable and low-latency communication systems rather than their average (expectation) counterparts. In this paper, for the first time, we extend the notion of LCR to address this issue and sufficiently characterize the statistical behavior of extreme maxima or minima. This new indicator, entitled as extreme LCR (ELCR), is analytically introduced and evaluated by resorting to the extreme value theory and risk assessment. Capitalizing on ELCR, some key performance metrics emerge, i.e., the maximum outage duration, minimum effective duration, maximum packet error rate, and maximum transmission delay. They are all derived in simple closed-form expressions. The theoretical results are cross-compared and verified via extensive simulations whereas some useful engineering insights are manifested.