Integrated Sensing, Communication, and Power Transfer for Fluid-Antenna LEO Satellite Systems

Abstract

Emerging technologies including wireless power transfer (WPT), integrated sensing and communication (ISAC), and fluid antennas (FAs), have significantly advanced the capabilities and performance of modern satellite communication systems. This paper investigates an FA-assisted integrated sensing, communication, and power transfer (ISCPT) framework for low Earth orbit (LEO) satellite networks, which operates in two phases: 1) an energy-transfer and target-sensing phase (Phase I), and 2) an information-transmission phase (Phase II). Specifically, in Phase I, a space solar power satellite (SSPS) transmits a dual-functional waveform to simultaneously charge multiple LEO satellites and illuminate a sensing target, while in Phase II, these LEO satellites coordinately serve multiple ground user equipments (UEs) leveraging the harvested energy. We formulate a sum-rate maximization problem subject to the SSPS’s transmit power constraint, LEO satellites’ energy harvesting and sensing requirements, UEs’ information rate demands, and the FAs’ movable regions. To tackle the highly-coupled and non-convex optimization problem, a three-stage alternating optimization (AO) algorithm is proposed, which decomposes it into resource allocation, SSPS-side FA placement, and LEO-side FA placement subproblems. In particular, the resource allocation subproblem is reformulated by adopting the Cauchy–Schwarz inequality and semidefinite relaxation (SDR), and is efficiently tackled via the successive convex approximation method. The two FA placement subproblems are addressed leveraging trust-region-based optimization. Simulation results validate the superior performance gains of the proposed algorithm over seven benchmarks and demonstrate that FAs can enhance multi-functional wireless services by adjusting inter-channel diversity according to service types. Notably, a non-trivial trade-off arises among FAs-enabled multi-functional services requiring distinct channel characteristics, as FAs cannot simultaneously provide optimal channel conditions for all services.