Fluid Antenna Empowered Integration of Sensing, Communications and Computing With Hybrid Multi-Task Offloading

This paper proposes a fluid antenna (FA)-empowered integration of sensing, communications and computing (ISCC) system, where an access node dynamically adjusts the positions of its transmit antennas to enhance the ISCC performance. In particular, the access node can offload its hybrid multi-task containing both computational tasks and collected sensing data to a group of computational nodes via multi-access edge computing (MEC) for efficient processing. We formulate a joint optimization of the beamforming, FAs’ positions, offloading strategies, and computing resource allocations, with the objective of maximizing the processing efficiency of the sensing task, which quantifies the system’s ability to process the sensing data in the hybrid multi-task MEC scenario and is defined as the ratio of the collected sensing data volume to its processing latency. We propose an efficient algorithm based on the block coordinate descent optimization to solve this non-convex problem. Numerical results evaluate the effectiveness and performance advantages of the proposed FA-empowered ISCC with hybrid multi-task MEC.