A Model Reduction Approach for OFDM Channel Estimation Under High Mobility Conditions

Abstract

Abstract-Orthogonal frequency-division multiplexing (OFDM) combines the advantages of high performance and relatively low implementation complexity. However, for reliable coherent detection of the input signal, the OFDM receiver needs accurate channel information. When the channel exhibits fast time variation as it is the case with several recent OFDM-based mobile broadband wireless standards (e.g., WiMAX, LTE, DVB-H), channel estimation at the receiver becomes quite challenging for two main reasons: 1) the receiver needs to perform this estimation more frequently and 2) channel time-variations introduce intercarrier interference among the OFDM subcarriers which can degrade the performance of conventional channel estimation algorithms significantly. In this paper, we propose a new pilot-aided algorithm for the estimation of fast time-varying channels in OFDM transmission. Unlike many existing OFDM channel estimation algorithms in the literature, we propose to perform channel estimation in the frequency domain, to exploit the structure of the channel response (such as frequency and time correlations and bandedness), optimize the pilot group size and perform most of the computations offline resulting in high performance at substantial complexity reductions.

OFDM blind signal detection based on the probability-enhanced genetic algorithm

“…If H(i) is in the frequency direction (m index), it's illustrated in [1] that H(m+1,n) is approximate to H(m,n). At the same time, the Doppler effect is trivial and H(m,n+1) is approximate to H(m,n) when f d is small [9].…”

“…Blind channel estimation and signal detection of timevarying (TV) orthogonal frequency division multiplexing (OFDM) systems is a challenging task for the irregularity and variance of OFDM time-frequency response [1] [2]. Some bind detectors of TV OFDM are presented with the form of quadratic programs (QP) [2][3] [4].…”

Iterative Channel Estimation and Detection for High-Mobility MIMO-OFDM Systems: Mitigating Error Propagation by Exploiting Error Information

“…To explore the time-frequency correlation in the channel model, an appropriate two-dimensional BEM using Prolate functions is evaluated in [8]. Furthermore, to reduce the computational complexity, channel estimation using banded structure of the channel matrix in the frequency domain is used to reduce the dimensionality of the parameter estimation space in [9]. In comparison with the joint channel estimation and data detection, the performance of bit error rate is improved in the iterative scheme using turbo receivers [10][11][12].…”

Iterative channel estimation and detection for fast time-varying MIMO-OFDM channels

“…To explore the efficiency of the timefrequency correlation in the channel model, an appropriate two-dimensional basis expansion model (BEM) using Prolate functions is evaluated in [3]. Furthermore, to reduce the computation complexity, channel estimation using banded structure of the channel matrix in the frequency domain is used to reduce the dimensionality of the parameter estimation space in [4]. Besides, an iterative scheme composed of least square (LS) channel estimation and parallel interference cancellation (PIC) coupled with decision statistical combining (DSC) has been recently evaluated to reduce the complexity of detection in [5].…”