Orthogonal Spatial Domain Subspace Projection Based Time-Varying Channel Estimation

Rong Zeng,Qiang Huang,Hao Wang

doi:10.1109/access.2020.2990316

Abstract

Time-varying channel estimation is a well-known challenge for the wireless communications in the high mobility environments. In this paper, we propose a basis expansion model (BEM) based channel estimation algorithm utilizing orthogonal spatial domain subspace projection. The channel estimation is taken on each subspace and the estimation results of all subspaces are combined to obtain the final time-varying channel parameters. In our proposed scheme, the wave number spectrum shifting is utilized to suppress the time-varying level on each subspace and the wave number spectrum recovery is adopted in the combination process. Simulation results are provided to verify our proposed scheme.

Highlights

Due to the large-scale deployment of high speed railway (HSR) systems and the increasing popularity of highway vehicle communication systems, wireless communication in high mobility environments has recently attracted considerable attention [1]–[4]
We address the problem of time-varying channel estimation in high mobility environments
In order to meet this requirements, we propose an orthogonal spatial domain subspace projection based time-varying channel estimation algorithm

Summary

INTRODUCTION

Due to the large-scale deployment of high speed railway (HSR) systems and the increasing popularity of highway vehicle communication systems, wireless communication in high mobility environments has recently attracted considerable attention [1]–[4]. One of the main challenges for OFDM systems in high mobility communications is the time-varying channel estimation [6], [7]. A 2D complex Support Vector Machine Regression (SVR) algorithm based on the Radial Basis Function (RBF) kernel was proposed in [10], which performs simultaneous interpolation in frequency and time domains. The basis expansion model (BEM) is widely used to characterize the time-varying channel recently by utilizing the basis functions scaled with corresponding coefficients. R. Zeng et al.: Orthogonal Spatial Domain Subspace Projection Based Time-Varying Channel Estimation. We address the problem of time-varying channel estimation in high mobility environments. In order to meet this requirements, we propose an orthogonal spatial domain subspace projection based time-varying channel estimation algorithm.

SYSTEM MODEL

CHANNEL ESTIMATION The discrete-time BEM channel model can be expressed as

SIMULATION RESULTS

CONCLUSION