| Massive MIMO is the key technology of physical layer to improve system capacity in the next generation mobile communication network—5G.In Massive MIMO systems,when the number of transmitting antennas tends to be infinite,the system can eliminate the effects of channel fading and inter-cell interference.However,the antenna configuration of Massive MIMO increases the power consumption of the system greatly,which makes it difficult to meet the requirements of green communication mode in 5G,and the complexity of signal detection algorithm leads to many challenges in the popularization of this technology.Therefore,all kinds of transmission technologies that can be used in Massive MIMO systems to be rapidly studied.Solutions of high speed,low delay and low power consumption have become a research hot spot.Spatial modulation is a new MIMO transmission technology,which is very suitable for communication systems with Massive MIMO antennas,and can reduce link power consumption and receiver complexity significantly.This paper focuses on spatial modulation MIMO,introduces the principles of different multi-carrier modulation schemes,analyses and optimizes the performance of communication system when spatial modulation MIMO transmitting multi-carrier modulation signals,and introduces a signal reconstruction algorithm based on compressed sensing to study receiver detection algorithm in Massive MIMO spatial modulation MIMO scenarios.Initially,in order to avoid the phenomena of low speed and difficult detection in the application of generalized frequency division multiplexing,the system scheme of combining space modulation MIMO with GFDM is adopted;the frequency response characteristics of different pulse shaping filters in the system are analyzed,and then improved the system capacity is by optimization algorithm,and compared with the traditional space-time coding technology.The system is compared,and the performance and complexity of the modified multiple stage detection algorithm in Rayleigh fading channel environment are compared with other detection algorithms.The results show that the capacity of the system is improved significantly after the processing of the proposed optimization scheme,and resulting in lower computational complexity and better symbol error rate performance when using the modified detection.Furthermore,aiming at the problem of high complexity of traditional detection algorithms for generalized spatial modulation system,the theory of compressed sensing was used to construct a signal detection model.According to the sparse property of generalized spatial modulation signals,a stagewise orthogonal matching pursuit detection algorithm based on sparse reconstruction was proposed.The active antenna index sequence was selected according to the correlation threshold judgment and the foreseen sparsity was not needed in the iterative process of the algorithm,the index set and signal residuals were updated,then the sent data was restored based on optimized termination condition and signal quantization.Analysis and experiments show the algorithm has smaller root mean square error and the detection performance is improved compared with reconstruction algorithms of the same category,and has substantially lower complexity compared with the maximum likelihood algorithm.. |
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