Research On Signal Detection Based On Spatial Modulation

In recent years,spatial modulation?SM?,as a new type of MIMO tech-nology,has been widely studied in the academic world due to its simple structure of transceiver,low power consumption and many other excellent features.Spatial modulation utilizes the structure of single radio frequency chain at transmitter and feature of single activated antenna to improve the data rate by mining spatial domain information,thereby achieving the balance between spectral efficiency and energy efficiency.In addition,spatial multi-plexing technology can effectively circumvent the problem of inter-antenna interference?IAI?and inter-antenna synchronization?IAS?,thereby greatly simplifying the complexity of hardware design of transceiver.Hence,aiming at two application of scenarios of SM technology,this thesis mainly studies multi-user spatial modulation uplink signal detection algorithm,application of millimeter wave frequency band spatial modulation technology and its de-sign of signal detection algorithm,and has achieved the following stages.Firstly,in the single-cell multi-user communication scenario,for uplink detection of multiple access channel?MAC?SM signal,this thesis utilizes the inherent sparsity characteristics of MAC-SM signal to convert signal de-tection into the problem of sparse recovery.Based on the sparse Bayesian learning theory,the proposed algorithm first solves all possible indexes of activation antenna for problem of sparse recovery;Then,the corresponding index of activated antenna is sequentially extracted according to the number of transmitting antennas of each user terminal;A zero-forcing equalizer is utilized to demodulate the symbols based on the estimated index information.In addition,we also quantify the complexity of each detection algorithm.The simulation results show the proposed algorithm saves about 1.5dB of power consumption while the bit error rate is 10^-5,and the complexity is reduced to 5.1%approximately.Secondly,in millimeter wave communication,this thesis extends the ap-plication of spatial modulation technology and propose a generalized spatial scattering modulation?GSSM?scheme.The scheme not only effectively re-sists the defects of high transmission loss rate and sparse scattering cluster component in high frequency band communication,but also further improves the SE by mining the angular domain information.With reasonable hardware overhead settings,GSSM can be regarded as a compromise between SE and EE.Secondly,for GSSM signal detection,the current maximum likeli-hood?ML?detection algorithm cannot meet the requirement of performance.Therefore,considering the structure characteristics of GSSM signal,this the-sis proposes the maximum weight maximum?MWP?ML detection algorithm based on GSSM scheme.The proposed algorithm firstly estimates the se-lected set of scattering cluster components by using the criterion of maximum weight priority;Then,the ML is used to detect the transmitted symbols based on the estimated information.Next,we quantify the complexity of proposed algorithm and give its mathematical expression.The simulation results show that the complexity of proposed algorithm is reduced by about¹_Nc,and it is more suitable for GSSM signal detection.Finally,this thesis reviews the research content,and gives prospects for the robustness of MAC-SM and GSSM signals detection and the design of downlink precoding of MAC-SM MIMO system.