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A major challenge for fifth generation (5G) wireless communication, which is expected to be deployed around 2020 is to provide 10 times higher spectral efficiency and energy efficiency than fourth generation (4G). Spatial modulation (SM) is a novel multiple input and multiple output (MIMO) technique, which provides an exceptional trade-off between spectral efficiency and energy efficiency. All the conventional SM variants do not perform well under spatially correlated channel conditions. Hence, they cannot be employed for indoor wireless local area network (WLAN) and compact wireless mobile applications, where the effect of spatial correlation is imminent. In this paper, a new SM variant, dynamic spatial modulation (DSM) is introduced for 4 × 4 and 8 × 8 MIMO configurations, which activates either one or two transmit antennas based on input bit pattern. DSM employs dynamic mapping, which maximizes the Euclidean distance between active spatial bits by choosing antenna subsets with maximum spatial separation to minimize the effect of spatial correlation. The average bit error rate (ABER) performance of DSM under uncorrelated and spatially correlated channel conditions is quantified in comparison with conventional redesigned spatial modulation (ReSM). Later, a low complexity, suboptimal, ordered weight minimum mean square error based conditional maximum likelihood search (OWMMSE-CML) detection scheme is proposed for the DSM system. Through extensive simulations under various channel conditions and complexity analysis, it is shown that proposed OWMMSE-CML detection scheme offers performance nearer to optimal ML and also outperforms suboptimal signal vector based minimum mean square error (SVMMSE) detection scheme with a significant reduction in computational complexity. [ABSTRACT FROM AUTHOR]

The next-generation of networks should have better spectrum and energy efficiency. These competing design parameters can be dealt with spatial modulation (SM). Transmit antenna selection (TAS) strategies can enhance the average bit error rate (ABER) performance of SM. The purpose of this research is to examine the employment of machine learning (ML)-based TAS schemes for SM. The conventional Euclidean distance-based antenna selection (EDAS) scheme offers optimal performance at the expense of computational complexity. This paper discusses the application of four different ML algorithms to SM-TAS: Support vector machines (SVM), K -nearest neighbour (KNN), decision tree (DT), and naïve Bayes (NB). With reduced complexity, an SVM-based TAS scheme for SM can offer a minimum gain of ∼ 3.4 dB over SM with no transmit antenna selection (SM-NTAS). Furthermore, the ABER performance of all schemes is tested with a higher modulation order and a number of transmit antennas. In every scenario, ML-based TAS schemes outperform SM-NTAS in terms of ABER performance. [ABSTRACT FROM AUTHOR]

Spatial Modulation techniques (SMTs) offer an exceptional trade-off between spectral and energy efficiencies. In this work, we propose a new SMT termed as permutation index-quadrature spatial modulation (PI-QSM), aiming for enhanced spectral efficiency and better average bit error rate (ABER) performance compared to rival SMTs. To enhance spectral efficiency, PI-QSM exploits permutations of active transmit antennas by conveying additional information bits innovatively through indices of active antenna permutations. PI-QSM also alleviates the major constraint in some of the SMTs, where the total number of transmit antennas need to be a power of two. At any time instance, PI-QSM transmits real and imaginary parts of two complex modulated symbols separately using four different active antennas. To avoid any ambiguities at the receiver and to improve the error performance of the overall system, a rotation angle is introduced between the two modulated symbols before transmission. The rotation angle is optimized for different M -quadrature amplitude modulation (QAM) constellations using extensive Monte Carlo simulations. Performance of PI-QSM scheme is analyzed by deriving closed-form expressions for upper bound and asymptotic average bit error probability (ABEP) over Rayleigh fading channels. The Simulation results substantiate the accuracy of analytical analysis and also indicate that the proposed PI-QSM scheme offers better ABER performance than rival SMTs such as QSM and generalized QSM (GQSM). [ABSTRACT FROM AUTHOR]