Energy Efficiency Optimization Based on AFDM in Space-Air-Ground Networks

Space-ground integration networks (SGINs) has been widely studied in the sixth generation (6G) communication due to its ability to achieve global coverage. As a highly mobile platform, unmanned aerial vehicles (UAVs) can further improve the resource utilization efficiency of SGINs. To compensate for the performance loss caused by the high maneuverability of drones, we consider introducing integrated sensing and communications (ISAC) technology to break the traditional boundaries between communication and perception, in order to achieve spectrum reuse. Affine frequency division multiplexing (AFDM), with its flexible subcarrier allocation and dynamic parameter adjustment characteristics, can dynamically optimize signal transmission and improve communication reliability and anti-interference ability. Therefore, in order to further improve performances of SGINs, this paper proposes an AFDM-based UAV-ISAC system, which can simultaneously achieve communication and perception functions. Then, a a NP-hard optimization problem is established, which considers the sensing collection, transmit power and UAV trajectory. To solve the optimization problem, the original issue is divided into three sub-optimal issues, and a joint iteration algorithm is advanced to obtain the optimal solution. Numerical results reveal that the proposed system can maximum the energy efficiency while ensuring the quality of service for each user in SGINs.