Approximate ber expression of ML equalizer for OFDM over doubly selective channels
ABSTRACT Maximum Likelihood (ML) equalization for Orthogonal Frequency Division Multiplexing (OFDM) over time- and frequency- selective channels is analyzed in this paper. An approximate expression for bit error rate (BER) performance of the ML equalizer with a limited number of taps is developed, which subsumes the matched filter bound (MFB) equalization performance as a special case, and which saves on intensive time-consuming empirical simulations. Numerical simulations validate our approximate expression.
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ABSTRACT: In orthogonal frequency-division multiplexing (OFDM) systems operating over rapidly time-varying channels, the orthogonality between subcarriers is destroyed leading to inter-carrier interference (ICI) and resulting in an irreducible error floor. In this paper, a new and low-complexity maximum a posteriori probability (MAP) detection algorithm is proposed for OFDM systems operating over rapidly time-varying multipath channels. The detection algorithm exploits the banded structure of the frequency-domain channel matrix whose bandwidth is a parameter to be adjusted according to the speed of the mobile terminal. Based on this assumption, the received signal vector is decomposed into reduced dimensional sub-observations in such a way that all components of the observation vector contributing to the symbol to be detected are included in the decomposed observation model. The data symbols are then detected by the MAP algorithm by means of a Markov chain Monte Carlo (MCMC) technique in an optimal and computationally efficient way. Computational complexity investigation as well as simulation results indicate that this algorithm has significant performance and complexity advantages over existing suboptimal detection and equalization algorithms proposed earlier in the literature.Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE; 01/2010
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ABSTRACT: Orthogonal frequency-division multiplexing (OFDM) transmission in time-varying channels suffers from intercarrier interference (ICI). Existing ICI countermeasures usually address a few dominant ICI terms only and treat the residual as similar to white noise. We show that the residual ICI has high normalized autocorrelation and that this normalized autocorrelation is insensitive to the maximum Doppler frequency and the multipath channel profile, among other things. The residual ICI can thus be whitened in a largely channel-independent manner, leading to significantly improved detection performance. Simulation results confirm the theoretical analysis. In particular, they show that the proposed technique can lower the ICI-induced error floor by several orders of magnitude in maximum-likelihood sequence estimation (MLSE) designed to address a few dominant ICI terms.Proceedings of the 71st IEEE Vehicular Technology Conference, VTC Spring 2010, 16-19 May 2010, Taipei, Taiwan; 01/2010
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ABSTRACT: This paper is concerned with the challenging and timely problem of data detection for coded orthogonal frequency-division multiplexing (OFDM) systems in the presence of frequency-selective and very rapidly time varying channels. New low-complexity maximum a posteriori probability (MAP) data detection algorithms are proposed based on sequential detection with optimal ordering (SDOO) and sequential detection with successive cancellation (SDSC). The received signal vector is optimally decomposed into reduced dimensional subobservations by exploiting the banded structure of the frequency-domain channel matrix whose bandwidth is a parameter to be adjusted according to the speed of the mobile terminal. The data symbols are then detected by the proposed algorithms in a computationally efficient way by means of the Markov chain Monte Carlo (MCMC) technique with Gibbs sampling. The impact of the imperfect channel state information (CSI) on the bit error rate (BER) performance of these algorithms is investigated analytically and by computer simulations. A detailed computational complexity investigation and simulation results indicate that, particularly, the algorithm based on SDSC has significant performance and complexity advantages and is very robust against channel estimation errors compared with existing suboptimal detection and equalization algorithms proposed earlier in the literature.IEEE Transactions on Vehicular Technology 08/2011; · 2.06 Impact Factor