Iterative Signal Detection Technology In Spatial Modulation Communication System

Spatial Modulation(SM),as a sparse radio frequency(RF)based Multiple-Input Multiple-Output(MIMO)transmission technology,can provide a good trade-off between the transmission efficiency and bit error rate(BER)performance due to its low complexity and low power consumption.Therefore,it has become one of the key technologies of MIMO systems.Based on the sparse structure of transmit SM symbol,this dissertation focuses on the design of the iterative receivers with low-complexity and high performance,in order to deal with carrier frequency offset(CFO),clipping noise,multipath diversity,and channel estimation error.The main researches of this dissertation can be summarized as follows.Firstly,in the second chapter of this dissertation,based on the system model of SM in Rayleigh fading channel,Turbo equalization and message passing(MP)aided iterative detection algorithms are proposed for channel and data interference,respectively,in order to provide an algorithmic foundation for the follow-up research works.In the third chapter of this dissertation,for the sake of solving the problem caused by CFO and clipping noise,interference cancellation aided iterative detection algorithms are proposed to exploit the unique structure of SM Orthogonal Frequency Division Multiplexing(OFDM)system.First,based on the system model of SM-OFDM with multiple CFOs,several soft-input soft-output(SISO)aided iterative interference cancellation algorithms are proposed to exploit the prior probability information of SM symbol by employing MP algorithms introduced in Chapter 2 using different criterias.Second,according to the system model of clipped SM-OFDM,iterative detection algorithms based on hard-decision feedback and soft-decision feedback are proposed in order to achieve a better system performance.In the fourth chapter of this dissertation,in single-carrier(SC)SM system,based on the cyclic-prefix(CP)and the zero-prefix(ZP)aided frame structure model,frequency-domain Turbo equalizers(FDTEs)and Time-domain Turbo equalizers(TDTEs)are proposed,respectively.Firstly,based on the system model of CP-SC-SM,compared to the conventional linear FDTE,time-domain soft-decision feedback(TDSDF)and general approximate message passing(GAMP)aided FDTEs are proposed by introducing the concepts of time-domain feedback and compressed sensing,respectively,resulting in a better BER performance.Secondly,based on the system model of ZP-SC-SM,several TDTEs are proposed by exploiting different types of soft-decision feedback at the expense of different imposed complexity,which can provide a better trade-off between system performance and computational complexity.Finally,in the fifth chapter of this dissertation,a series of robust FDTEs are conceived for CP-SC-SM systems relying on realistic imperfect channel knowledge.Firstly,based on the realistic channel estimation,robust TDSDF and frequency-domain soft-decision feedback(FDSDF)aided FDTEs are proposed to make full use of the firstand second-moment information of the estimated channel,yielding an improved BER performance compared to FDSDF-FDTE conceived for the perfect channel state information(CSI).Secondly,in order to further cope with high channel error,data-aided channel estimation based robust FDTEs are proposed to improve the accuracy of channel estimation.The simulation results show that the proposed robust equalizers can make full use of the estimated channel information,leading to a better system performance.