🤖 AI Summary
研究提出了一种多通道速率公平算法(MCRF)来解决空中-地面异构网络中D2D通信的上行资源分配问题，通过共享复用来提高频谱效率和用户公平性。
📝 Abstract
This study investigates an Aerial-Ground Integrated Heterogeneous network (AGIHN) architecture that combines terrestrial macro base stations and unmanned aerial vehicles (UAVs) serving as aerial base stations to enhance uplink access for macrocell users. To address the complex uplink resource allocation challenge for multiple device-to-device (D2D) communication pairs, we propose a low-complexity Multi-Channel Rate-Fair (MCRF) algorithm. Distinct from traditional exclusive allocation methods, MCRF supports shared reuse, enabling multiple D2D pairs to simultaneously multiplex on the same resource block, thereby significantly improving spectral efficiency. To manage the severe intra-tier interference arising from this non-orthogonal sharing, a heuristic Interference Avoidance (IA) strategy is integrated to ensure the transmission quality of D2D users. The proposed framework jointly optimizes system throughput, user fairness, and energy efficiency without requiring computationally intensive offline training. Simulation results demonstrate distinct performance advantages depending on the reuse mode: Compared to traditional single-channel exclusive reuse schemes, MCRF achieves massive gains, increasing D2D energy efficiency and throughput by approximately 397% and 542%, respectively. Furthermore, relative to multi-channel benchmarks (e.g., MCRR), the proposed algorithm optimizes the efficiency-fairness trade-off, enhancing the fairness index by 7.43% while maintaining a robust fairness score exceeding 0.6 in interference-prone environments.