Adaptive Spatial Modulation Combining BCH Coding and Huffman Coding

Spatial modulation (SM), a modulation scheme that maps transmitted information onto the antenna parameter, appears as an attractive option for the emerging large-scale multiple-input multiple-output (MIMO) systems. Due to the reduced inter-channel interference (ICI) and signal processing complexity, SM has attracted vast attention to motivate further vigorous research, one of which is Huffman-based SM. To further decrease the bit error rate (BER) of SM with acceptable overhead signal processing complexity and power assumption, a new modulation scheme combining BCH coding and Huffman coding is proposed in this paper. Additionally, an adaptive quantization algorithm is derived and applied to the processing procedure of the probability matrix. Numerical results have illustrated that the proposed algorithm achieves considerable performance improvement over the existing schemes.

[1]  Harald Haas,et al.  Increasing spectral efficiency by data multiplexing using antenna arrays , 2002, The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[2]  Wei Zhang,et al.  Huffman Coding-Based Adaptive Spatial Modulation , 2017, IEEE Transactions on Wireless Communications.

[3]  David A. Huffman,et al.  A method for the construction of minimum-redundancy codes , 1952, Proceedings of the IRE.

[4]  Aria Nosratinia,et al.  Antenna selection in MIMO systems , 2004, IEEE Communications Magazine.

[5]  Chang Wook Ahn,et al.  Spatial Modulation - A New Low Complexity Spectral Efficiency Enhancing Technique , 2006, 2006 First International Conference on Communications and Networking in China.

[6]  Jim Esch.  Spatial Modulation for Generalized MIMO: Challenges, Opportunities, and Implementation , 2014, Proc. IEEE.

[7]  Muhammad Ali Imran,et al.  On the Energy Efficiency-Spectral Efficiency Trade-off over the MIMO Rayleigh Fading Channel , 2012, IEEE Transactions on Communications.

[8]  Lutz H.-J. Lampe,et al.  Multiple-antenna techniques for wireless communications - a comprehensive literature survey , 2009, IEEE Communications Surveys & Tutorials.

[9]  Xiaohu You,et al.  Belief propagation detection based on max-sum algorithm for massive MIMO systems , 2017, 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP).

[10]  Xiaohu You,et al.  Adjustable iterative soft-output detection for massive MIMO uplink , 2016, 2016 8th International Conference on Wireless Communications & Signal Processing (WCSP).

[11]  Wei-Ho Chung,et al.  New Space Shift Keying Modulation with Hamming Code-Aided Constellation Design , 2012, IEEE Wireless Communications Letters.

[12]  Erik G. Larsson,et al.  Massive MIMO for next generation wireless systems , 2013, IEEE Communications Magazine.

[13]  Donghun Lee.  Performance analysis of scheduled TAS-MRC MIMO systems with multiple interferers , 2017, IET Signal Process..

[14]  Xiaohu You,et al.  Low-complexity segmented CRC-aided SC stack decoder for polar codes , 2016, 2016 50th Asilomar Conference on Signals, Systems and Computers.

[15]  Xiaohu You,et al.  Graph-merged detection and decoding of polar-coded MIMO systems , 2017, 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP).