AI & ML
Resilience in Wireless: A Lyapunov-Constrained Integrated Sensing, Communication, and Control Approach
arXiv eess.SP0 views
arXiv:2610.32116v1 Announce Type: new Abstract: Traditional wireless networks mainly use reliability metrics to evaluate network stability. However, reliable data delivery alone cannot fully characterize network stability under variations in wireless environments and physical tasks. Wireless network resilience provides a broader perspective by describing the ability to maintain acceptable service and recover from disruptions. We develop an integrated sensing, communication, and control (ISCC) framework that incorporates communication reliability and sensing error into a state-dependent Lyapunov constraint for adaptive BS beamforming. The resulting transmit-power minimization problem is non-convex and solved via semidefinite relaxation and successive convex approximation with rank-one recovery. We establish conditional mean-square ultimate boundedness, while simulations demonstrate improved resilience and faster recovery over a static baseline.
Source:https://arxiv.org/abs/2610.32116PreviousQoE-Driven Hybrid Resource Allocation for Multi-User OFDMA Semantic CommunicationsNextType-based Over-the-Air Computation
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