Enhanced MMSE Channel Estimation Using Timing Error Statistics for Wireless OFDM Systems

Abstract

Abstract-Estimation and tracking of the frequency-selective time-varying channel response is a challenging task for wireless communication systems incorporating coherent OFDM. In pilot-symbol-assisted (PSA) OFDM systems, the minimum mean-square-error (MMSE) estimator provides the optimum performance based on the channel statistics (channel correlation function and SNR). In OFDM systems, FFT-block timing error introduces a linear phase rotation to data modulated on individual subcarriers. An MMSE channel estimator designed only using the wireless channel statistics performs only sub-optimally when subcarrier phase rotations due to block timing errors are present. In this paper, we show that by using the block timing error statistics of the OFDM time-synchronizer the performance of the MMSE channel estimation can be significantly improved. Numerical results show that the bit-error-probability (BEP) performance degradation due to timing errors can be almost completely recovered by the proposed technique.

Pilot-Assisted Time-Varying Channel Estimation for OFDM Systems

“…Next, we use this estimate to update the covariance matrix , which in turn is used to produce the BLUE for the next iteration and so on Note that a similar idea is adopted in [34] though applied in a different context. To ensure that this iterative procedure will converge, we can simply initialize with , which results in the following expression for the first iteration: (24) From a2), (24) is the maximum-likelihood estimator (MLE) [33] that is obtained by ignoring the interference . The resulting is actually the LS fit as obtained in Section IV-Bbut weighted by the noise covariance.…”

“…The receiver can find no subcarrier that solely depends on pilots and thus is not contaminated by data symbols. For this reason, many existing works view the frequency-domain channel matrix either as diagonal [6], [23], [24] thus ignoring the ICI completely, or strictly banded as in [13] that relies on a CE-BEM assumption. Apparently, these approaches suffer from a large estimation error for channels with a high Doppler spread, but admit a clustered pilot scheme in the frequency domain, which is adopted in many OFDM standards, e.g., terrestrial digital video broadcasting (DVB-T) [25].…”

A Maximum Likelihood Fine Timing Estimation for Wireless OFDM Systems

“…Thus they may result in signif- icant performance degradation. In a coherent OFDM system, timing offset has another, possibly even more severe, impact on system performance due to its adverse effect on channel estimation [6], [8], [10], [12]. In practice, when some portions of the effective channel are shifted outside the channel estimation window due to timing offsets, the channel estimates will suffer additional errors [6].…”

“…In practice, when some portions of the effective channel are shifted outside the channel estimation window due to timing offsets, the channel estimates will suffer additional errors [6]. This error effect is more pronounced for high-performance channel estimators which usually have a narrow channel estimation window matched to the channel impulse response (CIR) [6], [12]. Such estimators include the FFTbased optimum interpolator [10], the minimum mean-squareerror (MMSE) channel estimator [12] and the enhanced channel estimators based on a reduced signal space [13]- [15].…”

“…This error effect is more pronounced for high-performance channel estimators which usually have a narrow channel estimation window matched to the channel impulse response (CIR) [6], [12]. Such estimators include the FFTbased optimum interpolator [10], the minimum mean-squareerror (MMSE) channel estimator [12] and the enhanced channel estimators based on a reduced signal space [13]- [15]. All these high-performance channel estimators demand a high precision timing recovery at the receiver.…”