Channel estimation in OFDM systems operating under high mobility using Wiener filter combined basis expansion model

Abstract

In this article, we first thoroughly analyze Wiener filter combined least squares based channel estimation (WF-LS) and then illustrate its limitation in high-speed mobile environments. Based on the analysis, we propose to combine WF with basis expansion model (BEM) based channel estimation to deal with channel estimation in various mobile environments, especially in high-speed cases. The expression for Wiener filter combined BEM based channel estimation (WF-BEM) is derived and the result explicitly considers the effect of intercarrier interference (ICI) that occurs in orthogonal frequency division multiplexing (OFDM) systems when operating under high mobility. The simulation results demonstrate that our proposed WF-BEM is better than WF-LS in time-varying channels, and the performance improvement is significant especially in fast time-varying channels.

Quality Analysis for Real-Time Data in MIMO Communication Using Adaptive Kalman Filtration

“…Under the user mobility, the channel effect is focused on minimization. An estimation approach based on channel estimation and superimposition of training sequence on the MIMO-OFDM system is outlined in [8]. The signal boundness losses to the actual value with the increase in block length in such system, to obtain minimum channel interference in block fading channels as presented in [9], a random upper bound [10,11] and a lower bound coding [12], with instantaneous channel capacity developed for the improvement of MIMO system.…”

Blind channel estimation for multiple antenna OFDM system subject to unknown carrier frequency offset

“…In general, channel estimation algorithms for single-input single-output (SISO) OFDM can be divided into two categories: non-blind channel estimation methods (using training sequence [7], pilots [8][9][10][11]) and blind/semi-blind channel estimation methods (exploiting virtual carriers [12], cyclostationarity [13], subspace method [12,[14][15][16], finite-alphabet method [17]). Compressive sensing methods [18,19] as well as other methods [20,21] have also been used for channel estimation in OFDM systems. Manuscript Several training sequence-based channel estimators were developed in [7], and pilot-aided channel estimation methods [8][9][10][11] in OFDM systems exploit some pilot symbols which are inserted at the given locations to estimate channel parameters.…”