Abstract
An iterative QR-based soft feedback segment interference cancellation (QRSFSIC) detection and decoder algorithm for a Reed–Muller (RM) space-time turbo system is proposed in this paper. It forms the sufficient statistic for the minimum-mean-square error (MMSE) estimate according to QR decomposition-based soft feedback successive interference cancellation, stemmed from the a priori log-likelihood ratio (LLR) of encoded bits. Then, the signal originating from the symbols of the reliable segment, the symbol reliability metric, in terms of an a posteriori LLR of encoded bits which is larger than a certain threshold, is iteratively cancelled with the QRSFSIC in order to further obtain the residual signal for evaluating the symbols in the unreliable segment. This is done until the unreliable segment is empty, resulting in the extrinsic information for a RM turbo-coded bit with the greatest likelihood. Bridged by de-multiplexing and multiplexing, an iterative QRSFSIC detection is concatenated with an iterative trellis-based maximum a posteriori probability RM turbo decoder as if a principal Turbo detection and decoder is embedded with an iterative subordinate QRSFSIC detection and a RM turbo decoder, exchanging each other’s detection and decoding soft-decision information iteratively. These three stages let the proposed algorithm approach the upper bound of the diversity. The simulation results also show that the proposed scheme outperforms the other suboptimum detectors considered in this paper.
Highlights
Multiple-input multiple-output (MIMO) systems achieve high data rate transmission and substantial gains in channel capacity over a rich-scattering environment [1,2], which makes very high spectral efficiency available for the emerging wireless standard IEEE 802.11n/ac [3], etc
The iterative QR-based soft feedback segment interference cancellation (QRSFSIC), based on a progressive partition of the transmitted symbols into the reliable/residual symbol segment according to a posterior likelihood ratio (LLR), gives rise to inner iterations to evaluate the minimum-mean-square error (MMSE) estimate of residual symbols which resort to soft feedback and interference cancellation of the reliable segment
The simulation results are described in two aspects, i.e., the performance of ISISOICSPDD over a number of iterations between the detector and the decoder loop and the bit error rate (BER), which, counted by comparisons between the estimated bits and the transmitted bits, is measured as a function of signal-to-noise ratio scenario log Pe (SNR), which is followed by a discussion of the diversity order of the proposed scheme
Summary
Multiple-input multiple-output (MIMO) systems achieve high data rate transmission and substantial gains in channel capacity over a rich-scattering environment [1,2], which makes very high spectral efficiency available for the emerging wireless standard IEEE 802.11n/ac [3], etc. It was shown that the QR decomposition [16] of the channel matrix led to a simple successive detection algorithm with reduced complexity In this way, we extend this idea to a SIOF detector and propose an iterative QR-based soft feedback segment interference cancellation (QRSFSIC). Using Reed–Muller (RM) [4,17], instead of convolutional codes as component codes, RM turbo codes, with a simple block interleaver, give very good performance for high code rates, and avoid the problem of trellis termination In this paper, it is serially concatenated with MIMO architecture to constitute a novel kind of MIMO system, named as the RM turbo space-time system. Indices [m, l] are used to mean the lth bit position of the constellation symbol for the mth transmit antenna while xk+1 and xk−1 denote [ xk+1 , · · · , x Nt ] T and [ x1 , · · · , xk−1 ] T , respectively, and the subscript k:l means that the range of index is from k to l
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