面向高空平台站（HAPS）的感知干扰下行功率控制：兼顾服务质量（QoS）与最大最小公平性
Interference-Aware Downlink Power Control for High-Altitude Platform Stations with QoS and Max-Min Fairness
- University of South Florida（南佛罗里达大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
该研究针对高空平台站（HAPS）系统，提出兼顾服务质量（QoS）与最大最小公平性的感知干扰下行功率控制方案，可降低发射功率、提升最差用户性能且计算成本远低于线性规划基准。
AI中文摘要：
高空平台站（HAPS）是非地面网络（NTN）中用于广域连接的极具前景的组成部分。然而，在大用户覆盖范围内服务多个用户，需要高效的功率控制机制，该机制需考虑HAPS独特的传播特性和严格的功率约束。本文针对HAPS系统在统计信道状态信息、3GPP NTN路径损耗以及莱斯衰落条件下的下行功率分配，开发了一种易于处理的分析与优化框架。推导了采用均值信道最大比传输（MRT）预编码时的信干噪比（SINR）闭式表达式，该表达式可捕获与几何相关的用户间干扰耦合。基于此，提出了两种功率控制方案：服务质量（QoS）约束下的功率最小化方案，以及最大最小SINR公平性方案。QoS方案可通过闭式形式或低复杂度的定点迭代获得，而最大最小方案则通过二分法求解。数值结果表明，与均匀功率分配、逆路径损耗分配以及几何感知启发式分配相比，所提方案在中高目标速率下可将所需发射功率降低多达6 dB，且能提升最差用户的SINR。在R_req = 2.5 bit/s/Hz、P_max = 35 dBm的条件下，所提QoS最优方案的QoS可行性概率约为0.95，而均匀功率、逆路径损耗及几何感知启发式分配的可行性概率均低于0.4。此外，所提方案的性能可与基于线性规划（LP）的基准方案相当，但计算成本仅为其极小一部分，当用户数K = 20时，平均计算时间减少约99.97%。
英文摘要：
High-altitude platform stations (HAPS) are a promising component of non-terrestrial networks (NTNs) for wide-area connectivity. However, serving multiple users over large user footprints requires efficient power-control mechanisms that account for the unique propagation characteristics and strict power constraints of HAPS. This paper develops a tractable analytical and optimization framework for downlink power allocation in HAPS systems under statistical channel state information, 3GPP NTN path loss, and Rician fading. A closed-form expression for the signal-to-interference-plus-noise ratio (SINR) with mean-channel maximal-ratio transmission (MRT) precoding is derived, capturing geometry-dependent inter-user interference coupling. Based on this, two power-control schemes are proposed: quality-of-service (QoS)-constrained power minimization and max-min SINR fairness. The QoS solution is obtained in closed form or through a low-complexity fixed-point iteration, while the max-min solution is obtained through bisection. Numerical results demonstrate up to 6 dB reduction in required transmit power at moderate-to-high target rates and improved worst-user SINR compared to the uniform power, inverse path-loss, and geometry-aware heuristic allocations. The proposed QoS-optimal scheme also achieves a QoS feasibility probability of approximately 0.95 at R_req = 2.5 bits/s/Hz and P_max = 35 dBm, while the uniform power, inverse path-loss, and geometry-aware heuristic allocations achieve less than 0.4. Moreover, the proposed schemes achieve performance comparable to the linear programming (LP)-based benchmarks at a fraction of the computational cost, reducing the average computation time by approximately 99.97% when K = 20.
