A fractional programming and alternating optimization algorithm is proposed for jointly tuning base station and RIS beamformers to maximize legitimate UAV sum-rate under a sensing SNR constraint.
Full-Duplex Integrated Sensing, Communication, and Computation over Low-Altitude Wireless Networks
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abstract
With low-altitude economies emerging as a pivotal sector, this study explores an integrated sensing, communication, and computation system over low-altitude wireless networks. A full-duplex autonomous aerial vehicle (AAV) operates as an AAV-enabled low-altitude platform (ALAP), concurrently executing data transmission, target sensing, and mobile edge computing services. To minimize systemic energy consumption under sensing beampattern constraints and computational demands, we formulate an optimization problem coordinating task allocation, computation resource allocation, and transmit/receive beamforming. Given the non-convexity and highly variable coupling, an efficient iterative convex approximation framework based on alternating optimization decomposes the problem into tractable subproblems. Moreover, the convergence and computational complexity of the proposed algorithm are rigorously analyzed. Simulations verify up to 54.12\% energy savings versus benchmarks.
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Coordinated Beamforming for RIS-Empowered ISAC Systems over Secure Low-Altitude Networks
A fractional programming and alternating optimization algorithm is proposed for jointly tuning base station and RIS beamformers to maximize legitimate UAV sum-rate under a sensing SNR constraint.