Design Of Detection Algorithm Based On Compressed Sensing Signal In MIMO Communication System

Multiple input multiple output technology is the foundation of key technologies for 5G wireless communication systems.Multiple antennas bring gain,which is accompanied by high requirements for data processing capabilities and increasing hardware costs.The development of MIMO system technology is diverse,and the spatial modulation technology can activate the number of single antennas to reduce the multilink of the system in lower power consumption.The generalized spatial modulation system extends the technology and activates multiple antennas at each symbol time.Although the system capacity and transmission rate are better,the complexity of signal detection is also increased.Traditional signal detection is not designed based on the sparse characteristics of the generalized spatially modulated MIMO system,which involves a large number of matrix inversion operations,resulting in computational redundancy.Therefore,the balance between complexity and bit error rate of the detection algorithm needs further research.Firstly,this paper studies the transmission model of Generalized Spatially Modulated MIMO System(GSM-MIMO)and analyzes the sparsity of its transmission structure.Then the traditional linear algorithm and the principle of interference cancellation algorithm are studied to analyze the combinability with the compressed sensing matching pursuit algorithm.the compressed compression recovery algorithm is specifically studied for propose a recovery algorithm with a better recovery probability with fewer iterations.Based on the segmented weak orthogonal matching pursuit(SWOMP)algorithm,the segmented backtracking weak selection positive is improved.the stage backtracking weak orthogonal matching pursuit(SCWOMP)algorithm.This algorithm addresses the problem of low recovery probability in the SWOMP algorithm.From the perspectives of the method of selecting the atomic columns with segmental changes and setting a second threshold backtracking,the recovery probability is improved with fewer iterations.Based on the research on the principle of compressed sensing,the application conditions of GSM-MIMO wireless communication are summarized.Finally,the two algorithms proposed in this paper,the segmented backtracking weak selection orthogonal matching tracking(SCWOMP)algorithm and the traditional MMSE algorithm is applied to the symbol detection of the generalized spatial modulation MIMO system(GSM-MIMO).The proposed algorithm first uses the recoveryalgorithm The position of the active antenna is detected,and then the final detection is performed by the MMSE algorithm,which achieves a relative balance between complexity and bit error rate.Simulation results show that the bit error rate of the detection algorithm combined with compressed sensing is lower than that of MMSE and common matching pursuit algorithms.