The rapid growth of mobile data traffic in a high-speed scenario imposes great challenges on wireless system design and optimization, where the inherent Doppler shift, frequent cell switching, and large penetration loss will significantly degrade the quality of transceiver signals. Wireless resource scheduling dynamically allocates wireless resources according to the user channel conditions and quality of service requirement, which is an enabling approach to maximize the resource utilization. In this paper, we develop a new wireless resource scheduling method in high mobility scenario to uplift the system performance. We first propose a feature extraction algorithm to extract the spatial traffic characteristics. On this basis, several time-series prediction algorithms are leveraged to predict the traffic volume. Then, we introduce cell switching indicator (CSI) into channel quality prediction to improve the signal-to-noise ratio (SNR) prediction performance. Based on the predicted results of service traffic and user channel quality variations, a resource scheduling strategy is proposed, which compromises the total system throughput and user satisfaction. Simulation results validate the effectiveness of the proposed scheduling algorithm.

中文翻译：

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高移动性场景的无线资源调度：流量和信道质量预测相结合的方法


高速场景下移动数据流量的快速增长给无线系统的设计和优化带来了巨大的挑战，其中固有的多普勒频移、频繁的小区切换和较大的穿透损耗将显着降低收发信号的质量。无线资源调度根据用户信道状况和服务质量要求动态分配无线资源，是实现资源利用率最大化的一种手段。在本文中，我们在高移动性场景中开发了一种新的无线资源调度方法，以提高系统性能。我们首先提出一种特征提取算法来提取空间交通特征。在此基础上，利用多种时间序列预测算法来预测交通量。然后，我们将小区切换指示符（CSI）引入到信道质量预测中，以提高信噪比（SNR）预测性能。基于业务流量和用户信道质量变化的预测结果，提出了一种兼顾系统总吞吐量和用户满意度的资源调度策略。仿真结果验证了所提调度算法的有效性。