In time-selective fading channel, the Alamouti orthogonality principle is lost due to the variation of channel from symbol-to-symbol in space–time block-coded orthogonal frequency division multiplexing (STBC-OFDM) system and causes co-channel interference (CCI) effects. To combat the CCI effects, various signal detection schemes have been proposed earlier by assuming that a priori channel state information (CSI) is known to the receiver. However, in practice, the CSI is unknown and therefore accurate estimation of channel is required for efficient signal detection. In this paper, by exploiting circulant properties of the channel frequency response (CFR) autocorrelation matrix [Formula: see text], we propose an efficient low complexity linear-minimum-mean-square-error (LMMSE) estimator. This estimator applies an expectation–maximization (EM) iterative process to reduce the computational complexity significantly. Finally, we compare the proposed LMMSE-EM estimator with conventional least square (LS) and LMMSE estimator in terms of performance and computational complexity. The simulation results show that the proposed LMMSE-EM estimator achieves exactly the same performance as the optimal LMMSE estimator with much lower computational complexity.
Most existing quasi-orthogonal space time Block coding (QO-STBC) schemes have been developed relying on the assumption that the channel is at or remains static during the length of the code word symbol periods to achieve an optimal antenna diversity gain. However, in time-selective fading channels, this assumption does not hold and causes intertransmit-antenna-interferences (ITAI). Therefore, the simple pairwise maximum likelihood decoding scheme is not sufficient to recover original transmitted signals at the receiver side. To avoid the interferences, we have analyzed several signal detection schemes, namely zero forcing (ZF), two-step zero forcing (TS-ZF), minimum mean square error (MMSE), zero forcing - interference cancelation - decision feedback equalizer (ZF-IC-DFE) and minimum mean square error - interference cancelation { decision feedback equalizer (MMSE-IC-DFE). We have proposed two efficient iterative signal detection schemes, namely zero forcing - iterative interference cancelation - zero forcing { decision feedback equalization (ZF-IIC-ZF-DFE) and minimum mean square error - parallel interference cancelation - zero forcing – decision feedback equalization (MMSE-IIC-ZF-DFE). The simulation results show that these two proposed detection schemes significantly outperform all conventional methods for QOSTBC system over time selective channel.
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