Home   >   CSC-OpenAccess Library   >    Manuscript Information
Generalised Spatial Modulation with LR-aided K-best Decoder for MIMO Systems
Mehnaz Rahman, Raymundo Ramirez-Gutierrez, Thomas A. Tetzlaff, Farhana Sheikh
Pages - 1 - 18     |    Revised - 31-01-2018     |    Published - 30-04-2018
Volume - 12   Issue - 1    |    Publication Date - April 2018  Table of Contents
Generalized Spatial Modulation, K-best Decoder, Lattice Reduction, MIMO.
This paper presents a generalised spatial modulation (GSM) with lattice reduction (LR) aided K-best decoder for multiple-input multiple-output (MIMO) systems, achieving near optimal performance with low complexity. GSM is one of the current feasible solutions alleviating the requirement of high number of transmit RF chains in large scale MIMO systems. It conveys information by activating a subset of transmit antennas to reduce the transmit power and design complexity. In our proposed system, either the same or multiple information bits can be transmitted through multiple antennas achieving diversity gain and spatial multiplexing (SMx) respectively. In addition, as a MIMO decoder at the receiver side, a LR-aided K-best decoder for both real and complex domain is incorporated in order to obtain near optimal performance with less complexity, compared to a maximum likelihood (ML) decoder. Following IEEE 802.11 standard, we develop the decoder for 4x4 MIMO for different modulation schemes, with 2 active antennas at the transmitter side. The simulation results show comparable bit error rate (BER) performance between GSM with ML and the proposed scheme using both SMx and diversity gain. However, GSM with SMx utilises lower modulation order to achieve same spectral efficiency and thereby reduces the computational complexity.
1 Google Scholar 
2 BibSonomy 
3 Doc Player 
4 Scribd 
5 SlideShare 
A. Younis, N. Serafimovski, R. Mesleh, H. Haas, "Generalised spatial modulation", Proc. 44th ASILOMAR, pp. 1498-1502, 2010.
A. Younis, N. Serafimovski, R. Mesleh, H. Haas, "Generalised spatial modulation", Proc. 44th ASILOMAR, pp. 1498-1502, 2010.
D. Wubben, R. Bohnke, V. Kuhn, K. Kammeyer, "Near-maximum-likelihood detection of MIMO systems using MMSE-based lattice reduction", Proc. IEEE Int. Conf. Commun., vol. 2, pp. 798-802, 2004.
E. Agrell, T. Eriksson, A. Vardy, and K. Zeger, "Closest point search in lattices," IEEE Trans. Inf. Theory, vol. 48, no. 8, pp. 2201-2214, 2002.
F. Sheikh, E. Wexler, M. Rahman, W. Wang, B. Alexandrov, D. Yoon, A. Chun and A. Hossein. "Channel-Adaptive Complex K-Best MIMO Detection Using Lattice Reduction." IEEE Workshop on Signal Processing Systems (SiPS), pp. 1-6, Oct. 2014.
H. Yao, G. Wornell, "Lattice-reduction-aided detectors for MIMO communication systems", Proc. IEEE GLOBECOM, vol. 1, pp. 424-428, 2002.
J. Cassels, An introduction to the geometry of numbers. Springer Verlag, 1997.
J. Hoydis, S. Ten Brink, M. Debbah, "Massive MIMO: How many antennas do we need?", Proc. 49th Annu. Allerton Conf. Commun. Control Comput., pp. 545-550, 2011.
J. Jalden and B. Otterston. "On the Complexity of Sphere Decoding in Digital Communications." IEEE Transaction on Signal Processing, vol. 53, no. 4, pp. 1474-1484, Apr. 2005.
J. Jeganathan, A. Ghrayeb, L. Szczecinski, "Spatial modulation: Optimal detection and performance analysis", IEEE Commun. Lett., vol. 12, no. 8, pp. 545-547, Aug. 2008.
J. Niu, I. Lu, "A new lattice-reduction-based receiver for MIMO systems", Proc. 41st Annu. CISS, pp. 499-504, 2007.
M. Di Renzo, H. Haas, A. Ghrayeb, S. Sugiura, and L. Hanzo, "Spatial modulation for generalized mimo: challenges, opportunities, and implementation," IEEE Proc., vol. 102, no. 1, pp. 56-103, 2014.
M. Rahman, and G. Choi. "K-Best Decoders for 5G+ Wireless Communication." Switzerland: Springer, 2016.
M. Rahman, E. Rohani and G. Choi. "An Iterative LR-Aided MMSE Extended Soft MIMO Decoding Algorithm." International Conference on Computing, Networking and Communications, California, Feb. 2015.
M. Rahman, E. Rohani, J. Xu and G. Choi. "An Improved Soft Decision Based MIMO Detection Using Lattice Reduction." International Journal of Computer and Communication Engineering, vol. 3, no. 4, pp. 264-268, Apr. 2014
M. Rahman, G. S. Choi, "Iterative soft decision based complex K-best MIMO decoder." An International Journal on Signal Processing 9.5 (2015): 54-65.
M. Shabany and P. Glenn Gulak. "The Application of Lattice-Reduction to the K-Best Algorithm for Near-Optimal MIMO Detection." IEEE International Symposium on Circuits and Systems (ISCAS), May 2008, pp. 316-319.
M. Taherzadeh, A. Mobasher, and A. Khandani, "Lattice-basis reduction achieves the precoding diversity in MIMO broadcast systems," in 39th Conf. Inf. Sci. and Syst. (CISS) 2005, 2005.
P. Yang, Y. Xiao, Y. Yu, S. Li, "Adaptive spatial modulation for wireless MIMO transmission systems", IEEE Commun. Lett, vol. 15, no. 6, pp. 602-604, Jun. 2011.
R. Mesleh, H. Haas, S. Sinanovic, C. Ahn, S. Yun, "Spatial modulation", IEEE Trans. Veh. Technol., vol. 57, no. 4, pp. 2228-2241, Jul. 2008.
R. Ramirez-Gutierrez. "Transmission and Detection Techniques for MIMO Channels." PhD thesis. University of Leeds, UK, 2015.
Y. Jiang, M. Varanasi, and J. Li, "Performance analysis of ZF and MMSE equalizers for MIMO systems: an in-depth study of the high SNR regime," vol. 57, no. 4. IEEE, 2011, pp. 2008-2026.
Dr. Mehnaz Rahman
Intel Research Lab - United States of America
Mr. Raymundo Ramirez-Gutierrez
Intel Labs Guadalajara Zapopan, Mexico - Mexico
Mr. Thomas A. Tetzlaff
Intel Labs Santa Clara Oregon, USA - United States of America
Miss Farhana Sheikh
Intel Labs Santa Clara Oregon, USA - United States of America

View all special issues >>