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In this letter, we investigate two iterative channel estimators for mobile orthogonal-frequency division multiplexing. The first estimator is based on iterative filtering and decoding whereas the second one uses an a posteriori probability (APP) algorithm. The first method consists of two cascaded one-dimensional Wiener filters, which interpolate the unknown time-varying two-dimensional frequency response in between the known pilot symbols. As will be shown, the performance can be increased by feeding back the likelihood values at the output of the APP-decoder to iteratively compute an improved estimate of the channel frequency response. The second method applies two APP estimators, one for the frequency and the other one for the time direction. The two estimators are embedded in an iterative loop similar to the turbo decoding principle. As will be shown in detail, this iterative estimator is superior and its performance is independent of whether the chosen time-frequency pilot grid satisfies the two-dimensional sampling theorem or not. The bit-error rate as a function of the signal-to-noise ratio is used as a performance measure. In addition, the convergence of the iterative decoding loop is studied with the extrinsic information transfer chart.

In this paper an adaptive channel estimator is proposed and investigated to improve the performance of the receiver for pilot aided wireless and mobile OFDM systems. The estimator consists of a two-dimensional Wiener filter which is implemented as a cascade of two one-dimensional filters. We propose an efficient algorithm for adaptation to time varying channels of the second filter. The method is applied to the Terrestrial Digital Video Broadcasting System (DVB-T), which was originally specified for fixed receivers and which is in the process of being extended for mobile reception. The results are shown after inner decoding. Depending on the channel conditions, the signal-to-noise ratio gain can be up to 1.6 dB. The method provides a compatible improvement to DVB-T receivers.

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Abstract-A new two-dimensional blind channel estimation scheme for coherent detection of OFDM signals in a mobile environment is presented. The channel estimation is based on the A Posteriori Probability (APP) calculation algorithm. The time-variant channel transfer function is completely recovered without phase ambiguity with no need for any pilot or reference symbols. The two-dimensional channel estimation is performed by applying a concatenation of two one-dimensional APP estimators for frequency and time direction in combination with an iterative estimation and decoding loop. The phase ambiguity problem is solved by using higher order modulation schemes with asymmetrical arrangement. The proposed approach maximizes the spectral efficiency by avoiding any reference or pilot symbols and minimizes the BER by using coherent demodulation. We investigate the performance of our algorithm with respect to the BER and study the convergence of the iterative estimation and decoding loop using Extrinsic Information Transfer (EXIT) charts.

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