  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 {\em 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.
