With the increasing demands from passengers for data-intensive services, millimeter-wave (mmWave) communication is considered as an effective technique to release the transmission pressure on high speed train (HST) networks. However, mmWave signals ncounter severe losses when passing through the carriage, which decreases the quality of services on board. In this paper, we investigate an intelligent refracting surface (IRS)-assisted HST communication system. Herein, an IRS is deployed on the train window to dynamically reconfigure the propagation environment, and a hybrid time division multiple access-nonorthogonal multiple access scheme is leveraged for interference mitigation. We aim to maximize the overall throughput while taking into account the constraints imposed by base station beamforming, IRS discrete phase shifts and transmit power. To obtain a practical solution, we employ an alternating optimization method and propose a two-stage algorithm. In the first stage, the successive convex approximation method and branch and bound algorithm are leveraged for IRS phase shift design. In the second stage, the Lagrangian multiplier method is utilized for power allocation. Simulation results demonstrate the benefits of IRS adoption and power allocation for throughput improvement in mmWave HST networks.

翻译：随着乘客对数据密集型服务需求的不断增长，毫米波通信被视为缓解高速列车网络传输压力的有效技术。然而，毫米波信号在穿越车厢时遭受严重损耗，导致车载服务质量下降。本文研究了一种智能折射表面辅助的高速列车通信系统。在该系统中，智能折射表面部署于列车车窗上以动态重构传播环境，并采用混合时分多址-非正交多址接入方案以减轻干扰。我们旨在最大化总吞吐量，同时考虑基站波束赋形、智能折射表面离散相移和发射功率的约束。为获取可行解，我们采用交替优化方法并提出两阶段算法：第一阶段利用逐次凸近似法和分支定界算法设计智能折射表面相移；第二阶段采用拉格朗日乘子法进行功率分配。仿真结果表明，智能折射表面的应用及功率分配对提升毫米波高速列车网络吞吐量具有显著优势。