Optimizing Trade-Offs in Reliability, Security, and Freshness for Integrated Communication, Sensing, and Over-the-Air Computing

This paper addresses the trade-offs and optimization problems among reliability, security, and information freshness in integrated communication, sensing, and over-the-air computation (AirComp) systems. Internet of things (IoT) applications with stringent latency requirements pose challenges to the reliability and information freshness of such integrated systems. Given the security risks and resource constraints, it is crucial to study the trade-offs among reliability, security, and information freshness. To tackle this issue, this paper proposes an integrated sensing, communication, and computation over-the-air (ISCCO) framework and presents effective system design and optimization strategies. Specifically, considering statistical CSI, the target detection and AirComp aggregation errors are derived, and the upper bound of the security information age violation probability is obtained using stochastic network calculus and moment generating function theory. This paper optimizes the AirComp transceiver design to balance reliability, security, and information freshness, subject to constraints on information leakage probability and resources. It proposes a multi-objective minimization problem that includes the security information age violation probability, AirComp error, and target detection error. To address the issues of slow convergence and local optima in traditional algorithms, a faster converging and lower complexity equilibrium stochastic continuous convex approximation (SSCA) algorithm is proposed. Simulation results validate that this algorithm exhibits better convergence and optimization performance compared to traditional convex optimization methods, approaching the ideal case of perfect CSI.