Energy-Efficient Optimization for Integrated Sensing and Communication Assisted Cell Free Urban Air Mobility

To ensure precise user perception, address low energy efficiency from the limited onboard loads of urban air mobility (UAM) aircraft, and mitigate frequent handovers due to the rapid movement of UAM aircraft in cellular networks, this paper investigates a novel cell-free urban air mobility integrated sensing and communication (CF-UAM-ISAC) system. Specifically, the expression for the communication rate in the cell free network is first derived, and radar mutual information is introduced from an information theory perspective to assess the system's perceptual performance. A minimum detection threshold is established, and a precision sensing strategy is proposed. An optimization problem is then formulated to maximize the UAM aircraft energy efficiency. Due to the non-convex nature of the problem, the optimization problem is decomposed into three subproblems: UAM aircraft scheduling optimization, UAM aircraft transmission power optimization, and UAM aircraft trajectory optimization. For each non-convex subproblem, a corresponding solution algorithm is proposed. An alternating optimization algorithm for joint scheduling, power, and trajectory (AOSPT) is then proposed to obtain the suboptimal solution for UAM aircraft energy efficiency. Simulation results show that, compared with the baseline algorithm, the proposed algorithm has the following performance advantages: i) The average energy efficiency of the UAM aircraft in the cell-free network increased by 175.41%, and the communication rate increased by 308.18%. ii) By implementing the precision sensing strategy, every user can be accurately detected, increasing the accuracy by 60%.