Spatial Modulation (SM) is an innovative digital modulation scheme, which is expected to be a competitive candidate for next generation networks. All the variants of SM exhibit poor performance under spatial correlation and line of sight (LOS) Rician channel conditions. To combat the adverse effects of spatial correlation, a new variant of SM designated as modified spatial modulation (MSM) is proposed for 8 × 8 multiple input multiple output configuration. MSM uses a unique and dynamic mapping, which activates either one antenna or two antennas at the transmitter. Optimum maximum likelihood (ML) detection at the receiver though give accurate results but leads to high computational complexity as it performs extensive search of all possible antennas and symbols. In order to reduce the computational complexity, signal vector based minimum mean square error (SVMMSE) detection scheme is employed for MSM scheme. Estimation of antenna indices and transmitted symbols is done for both single antenna active and double antenna active scenarios. Performance of SVMMSE detection scheme is also analyzed under spatial correlation and LOS Rician channel conditions. The promising performance of SVMMSE under spatially uncorrelated Rayleigh, Spatial correlation and LOS Rician channel conditions with low computational complexity justifies the suitability of the proposed scheme for 5G based compact battery driven wireless devices.
This is a preview of subscription content, log in to check access.
Buy single article
Instant unlimited access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Agiwal, M., Saxena, N., & Roy, A. (2018). Ten commandments of emerging 5G networks. Wireless Personal Communications,98(3), 2591–2621.
Andrews, J. G., Buzzi, S., Choi, W., Hanly, S. V., Lozano, A., Soong, A. C. K., et al. (2014). What will 5G be? IEEE Journal on Selected Areas in Communications,32(6), 1065–1082.
Rappaport, T. S., Roh, W., & Cheun, K. (2014). Wireless engineers long considered high frequencies worthless for cellular systems: They couldn’t be more wrong. IEEE Spectrum,51(9), 34–58.
Akyildiz, I. F., Nie, S., Lin, S. C., & Chandrasekaran, M. (2016). 5G roadmap: 10 key enabling technologies. Computer Networks,106, 17–48.
Panwar, N., Sharma, S., & Singh, A. K. (2016). A survey on 5G: The next generation of mobile communication. Physical Communication,18, 64–84.
Ericsson, L. (2011). More than 50 billion connected devices. White Paper,14, 124.
Marzetta, T. L. (2010). Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Transactions on Wireless Communications,11(9), 3590–3600.
Prasad, R. (2014). 5G: 2020 and beyond. River Publishers series in communication. Singapore: River Publishers.
Agiwal, M., Saxena, N., & Roy, A. (2018). Mobile assisted directional paging for 5G communications. Transactions on Emerging Telecommunications Technologies,29(2), e3270.
DoCoMo, N. T. T. (2016). New SID proposal: Study on new radio access technology. 3GPP RP, 160671.
Basar, E., Wen, M., Mesleh, R., Di Renzo, M., Xiao, Y., & Haas, H. (2017). Index modulation techniques for next-generation wireless networks. IEEE Access,5, 16693–16746.
Mesleh, R. Y. (2007). Spatial modulation: A spatial multiplexing technique for efficient wireless data transmission (Doctoral dissertation, Jacobs University, Bremen).
Simha, G. G., Koila, S., Neha, N., Raghavendra, M. A. N. S., & Sripati, U. (2017). Redesigned spatial modulation for spatially correlated fading channels. Wireless Personal Communications,97(4), 5003–5030.
Naidu, S., Pillay, N., & Xu, H. (2018). Transmit antenna selection schemes for quadrature spatial modulation. Wireless Personal Communications,99(1), 299–317.
Jeganathan, J., Ghrayeb, A., & Szczecinski, L. (2008). Spatial modulation: Optimal detection and performance analysis. IEEE Communications Letters,12(8), 545–547.
Serafimovski, N., Di Renzo, M., Sinanovic, S., Mesleh, R. Y., & Haas, H. (2010). Fractional bit encoded spatial modulation (FBE-SM). IEEE Communications Letters,14(5), 429–431.
Younis, A., Serafimovski, N., Mesleh, R., & Haas, H. (2010). Generalised spatial modulation. In Proceedings of 44th Asilomar conference on signals, systems and computers (ASILOMAR), (pp. 1498-1502).
Mesleh, R., Ikki, S. S., & Aggoune, H. M. (2015). Quadrature spatial modulation. IEEE Transactions on Vehicular Technology,64(6), 2738–2742.
Mesleh, R., Ikki, S. S., & Aggoune, H. M. (2017). Quadrature spatial modulation–performance analysis and impact of imperfect channel knowledge. Transactions on Emerging Telecommunications Technologies,28(1), e2905.
Younis, A. (2014). Spatial modulation: Theory to practice. Edinburgh: University of Edinburgh.
Luna-Rivera, J. M., & Gonzalez-Perez, M. G. (2012). An improved spatial modulation scheme for MIMO channels. In Proceedings of 6th European conference on antennas and propagation (EUCAP) (pp. 1–5).
Cheng, C. C., Sari, H., Sezginer, S., & Su, Y. T. (2014). Enhanced spatial modulation with multiple constellations. In Proceedings of IEEE international black sea conference on communications and networking (BlackSeaCom) (pp. 1–5).
Cheng, C. C., Sari, H., Sezginer, S., & Su, Y. T. (2015). Enhanced spatial modulation with multiple signal constellations. IEEE Transactions on Communications,63(6), 2237–2248.
Mesleh, R., Hiari, O., & Younis, A. (2018). Generalized space modulation techniques: Hardware design and considerations. Physical Communication,26, 87–95.
Mesleh, R., Di Renzo, M., Haas, H., & Grant, P. M. (2010). Trellis coded spatial modulation. IEEE Transactions on Wireless Communications,9(7), 2349–2361.
Xiao, Y., Yang, Z., Dan, L., Yang, P., Yin, L., & Xiang, W. (2014). Low-complexity signal detection for generalized spatial modulation. IEEE Communications Letters,18(3), 403–406.
Younis, A., Di Renzo, M., Mesleh, R., & Haas, H. (2011). Sphere decoding for spatial modulation. In Proceedings of 2011 IEEE international conference on communications (ICC) (pp. 1–6).
Baraniuk, R. G. (2007). Compressive sensing (lecture notes). IEEE Signal Processing Magazine,24(4), 118–121.
Glover, F., & Laguna, M. (2013) Tabu search. In Handbook of combinatorial optimization (pp. 3261–3362). Springer New York.
Del Moral, P., Doucet, A., & Jasra, A. (2012). An adaptive sequential Monte Carlo method for approximate Bayesian computation. Statistics and Computing,22(5), 1009–1020.
Wang, J., Jia, S., & Song, J. (2012). Signal vector based detection scheme for spatial modulation. IEEE Communications Letters,16(1), 19–21.
Zheng, J. (2012). Signal vector based list detection for spatial modulation. IEEE Wireless Communications Letters,1(4), 265–267.
Zhang, W., & Yin, Q. (2014). Adaptive signal vector based detection for spatial modulation. IEEE Communications Letters,18(11), 2059–2062.
Younis, A., Sinanovic, S., Di Renzo, M., Mesleh, R., & Haas, H. (2013). Generalised sphere decoding for spatial modulation. IEEE Transactions on Communications,61(7), 2805–2815.
Serafimovski, N., Younis, A., Mesleh, R., Chambers, P., Di Renzo, M., Wang, C. X., et al. (2013). Practical implementation of spatial modulation. IEEE Transactions on Vehicular Technology,62(9), 4511–4523.
Li, J., Jiang, X., Yan, Y., Yu, W., Song, S., & Lee, M. H. (2017). Low complexity detection for quadrature spatial modulation systems. Wireless Personal Communications,95(4), 4171–4183.
Xiangbin, Y., Qing, P., Yang, L., Yaping, H., & Tao, L. (2018). Adaptive spatial modulation and thresholds optimization for MIMO systems in correlated Rayleigh channels. International Journal of Electronics and Communications,89, 167–173.
Quitin, F., Oestges, C., Horlin, F., & De Doncker, P. (2010). A polarized clustered channel model for indoor multiantenna systems at 3.6 GHz. IEEE Transactions on Vehicular Technology,59(8), 3685–3693.
Oestges, C. (2006). Validity of the Kronecker model for MIMO correlated channels. In Proceedings of 63rd IEEE vehicular technology conference (VTC), 6 (pp. 2818–2822).
Jagannatham, A. K. (2015). Principles of modern wireless communication systems. New York: McGraw-Hill Education.
Liu, X., & Wesel, R. D. (1998). Profile optimal 8-QAM and 32-QAM constellations. In Thirty-sixth annual allerton conference on communications, control, and computing.
Wang, F., Xiong, Y., & Yang, X. (2007). Approximate ML detection based on MMSE for MIMO systems. Progress in Electromagnetics Research Symposium (PIERS) Online,4(3), 475–480.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Jaiswal, G., Gudla, V.V., Kumaravelu, V.B. et al. Modified Spatial Modulation and Low Complexity Signal Vector Based Minimum Mean Square Error Detection for MIMO Systems under Spatially Correlated Channels. Wireless Pers Commun 110, 999–1020 (2020) doi:10.1007/s11277-019-06770-8
- Modified spatial modulation (MSM)
- Multiple input multiple output (MIMO)
- Optimum maximum likelihood (ML) detection
- Signal vector based minimum mean square error detection (SVMMSE)
- Spatial modulation (SM)
- Spatial correlation