Abstract

High-speed railway communication implemented based on Long-Term Evolution-Railway (LTE-R) Platform has strict requirements for quality of services to support high data-rate transmission for numerous mobile users. In such environment, there often exists inter-carrier interference. In this paper, we exploit a robust channel estimation method in the time domain for very fast time-varying LTE-railway channels, and then, we propose an effective and adaptive frequency-domain equalizer that can offer a tradeoff between performance and computational complexity. The simulation results show the robustness of our proposed method compared with previous ones. The computational complexity of the proposed method retain at a decent number by exploiting specified properties of channel matrices.

Highlights

  • 1 Introduction Long-Term Evolution-Railway (LTE-R) is becoming a key feature supported for intelligent transportation systems (ITS) for the last two decades to replace the current Global System for Mobile Communication-Railway (GSM-R) technology

  • A number of standardizations for high-speed railway (HSR) have been set up, which are known as European Train Control System (ETCS) or International Union of Railway (UIC)

  • A partial Fast Fourier transform (FFT) method was introduced in [13] in order to avoid the frequency-domain equalizer. This approach has an acceptable complexity, it only assumes that channel parameters vary slowly compared to the orthogonal frequencydivision multiplexing (OFDM) symbol duration

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Summary

Introduction

Long-Term Evolution-Railway (LTE-R) is becoming a key feature supported for intelligent transportation systems (ITS) for the last two decades to replace the current Global System for Mobile Communication-Railway (GSM-R) technology. A partial FFT method was introduced in [13] in order to avoid the frequency-domain equalizer This approach has an acceptable complexity, it only assumes that channel parameters vary slowly compared to the OFDM symbol duration. That makes this method weak against the LTE-R scenario. In [14], a low-complexity equalizer was proposed using channel matrix in the frequency domain. After that, corresponding to this channel, we utilize an optimal training sequence together with an effective estimator proposed in [17] This estimation method is designed to meet requirements of the LTE-R scenario.

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