Modified Spatial Modulation and Low Complexity Signal Vector Based Minimum Mean Square Error Detection for MIMO Systems under Spatially Correlated Channels

Abstract

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.