A low-complexity iterative channel estimation and detection technique for doubly selective channels

In this paper, we propose a low-complexity iterativejoint channel estimation, detection and decoding technique fordoubly selective channels. The key to the proposed technique isa segment-by-segment processing strategy under the assumptionthat the channel is approximately static within a short segmentof a data block. Through a virtual zero-padding technique, theproposed segment-by-segment equalization approach inherits thelow-complexity advantage of the conventional frequency domainequalization (FDE), but does not need the assistance of guard interval(for cyclic-prefixing or zero-padding), thereby avoiding thespectral and power overheads. Furthermore, we develop a lowcomplexitybidirectional channel estimator, where the Gaussianmessage passing (GMP) technique is used to exploit the channelcorrelation information, and the intermediate channel estimationresults in the iterative process are employed to perform intertapinterference cancellation. Simulation results demonstrate theeffectiveness of the proposed detection and channel estimationalgorithms.