Joint Computation Offloading and Target Tracking in Integrated Sensing and Communication Enabled UAV Networks
arxiv(2024)
摘要
In this paper, we investigate a joint computation offloading and target
tracking in Integrated Sensing and Communication (ISAC)-enabled unmanned aerial
vehicle (UAV) network. Therein, the UAV has a computing task that is partially
offloaded to the ground UE for execution. Meanwhile, the UAV uses the
offloading bit sequence to estimate the velocity of a ground target based on an
autocorrelation function. The performance of the velocity estimation that is
represented by Cramer-Rao lower bound (CRB) depends on the length of the
offloading bit sequence and the UAV's location. Thus, we jointly optimize the
task size for offloading and the UAV's location to minimize the overall
computation latency and the CRB of the mean square error for velocity
estimation subject to the UAV's budget. The problem is non-convex, and we
propose a genetic algorithm to solve it. Simulation results are provided to
demonstrate the effectiveness of the proposed algorithm.
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