Multi-antenna Space-Time Coding And Decoding Design And Channel Capacity Analysis

Multiple-input Multiple-output(MIMO)transmission technology can inprove the capacity and frequency band utilization of the entire system without occypying additional bandwidth and increasing transmit power,which is the key technology in the fourth generation(4G)communication system.Massive MIMO technology is equipped with more antennas,which can provide extremely high rate transmission,end-to-end low latency,high mobility,high energy efficiency,large-scale links and other services,which is one of the key technologies of the fifth generation(5G)communication system.MIMO space-time coding technology,using both space and time dimensions,can reduce the system's Bit Error Rate(BER)through coding gain to increase channel capacity.However,the decoding complexity of the space-time coding scheme without special design will be very high.In response to this problem,this paper mainly carried out research on a low complexity space-time coding and decoding scheme.While enriching the space-time coding family,this paper applies the designed space-time coding scheme to massive MIMO systems,and also achieves the purpose of reducing the complexity of decoding.Firstly,this paper studies the existing Orthogonal Space Time Block Code(OSTBC)and Quasi-Orthogonal Space Time Block Code(QOSTBC)schemes and proposes a simply structured 4×2 MIMO full rate,full diversity QOSTBC.Through calculation and analysis,the proposed scheme has the largest coding gain and the best BER performance,and the channel capacity of the proposed scheme is close to the theoretical channel capacity of 4×2 MIMO.Additionally,for the decoding algorithms,this paper focuses on the decoding algorithms of OSTBC and QOSTBC.Among them,the decoding complexity of the conditional maximum likelihood decoding algorithm under 4×2 MIMO is O(4M4.5),where M is the size of the constellation.On this basis,three low complexity decoding algorithm schemes are proposed in this paper:conditional maximum likelihood plus successive interference cancellation algorithm and two algorithms based on double QR decomposition.Simulation results show that the proposed first decoding algorithm has a similar BER to conditional maximum likelihood decoding,and the complexity is O(4M4).The decoding complexities of the latter two double QR decomposition algorithms are O(8(?))and O(12(?)),respectively,which reduces the decoding complexity,but the BER performance is poor.Finally,in the field of massive MIMO omnidirectional STBC,for the transmission rate,the scheme proposed in this paper can be used to obtain twice the transmission rate;for the decoding complexity,this paper applies the low complexity decoding algorithms in the STBC to the existing omnidirectional STBC.The simulation results show that these low complexity decoding algorithm schemes are effective and can be applied in massive MIMO systems.