Loss-aware adaptive scalable transmission in wireless high-speed railway networks

Abstract

Widespread deployment of High-Speed Railway (HSR) in recent years brings strong demand for high-quality onboard Internet services. However, the wireless link between the train and Base Station (BS) suffers from numerous problems, including frequent handover, severe Doppler shift, and great penetration loss, etc. It is still a challenge to provide HSR passengers with high-quality Internet services. In this paper, the Packet Loss Rate (PLR) of HSR networks is measured along Beijing-Shanghai railway line. Measurement results indicate that PLR remains at a high level for a long period and changes frequently in a large interval. To address this problem, we focus on frame loss problem of train-to-BS wireless link and propose a novel Loss-Aware Adaptive Scalable Transmission mechanism (LAAST) to fit for HSR networks. In LAAST, variable number of frame copies are transmitted according to Frame Loss Probability (FLP) to improve the scalability and efficiency of transmission over train-to-BS link. The optimal relationship between frame duplication number and FLP is derived through nonlinear programming model. Simulations demonstrate the effectiveness and fitness of LAAST for HSR networks.