Resarch On Relative Techniques Of MIMO Detection And Precoding

As the rapid development of the information industry and technology, the service of communications is gradually changed from low speed voice services to high speed data services, multimedia video, etc. These new data services ,demand higher transferring data rate and communication quality, which is far more than the traditional voice services can be achieved .MIMO(Multiple input multiple output )technology exploits the degrees of freedom in the space dimension to improve the spectral efficiency effectively, and had been used widely in the next generation of mobile communication system. The research MIMO theory and technology mainly involves MIMO channel estimation and modeling, transmission theory, transmission technology, etc. MIMO transmission technology is to solve the signal processing problem MIMO transmission in space and time, which is one of the key technologies of MIMO.The thesis is mainly focus on MIMO detection technology and precoding technology, both of which are closely related technology to MIMO transmission. These two technologies are used in the MIMO receiver and MIMO transmitter to solve the space time signal processing. In recent years, the application MIMO and turbo code technology make the MIMO detection not only solve the signal estimation problem, and also estimate the soft value of every bit in the signal; the purpose of precoding techniques is to improve the performance of the system by the pretreatment of precoding techniques in the transmitter which the signal processing techniques was done in the receiver traditionally. In this thesis, we firstly introduce the soft-output linear MIMO detection algorithm including zero-forcing (ZF) detection, minimum mean square error (MMSE) detection, decision feedback detection and non-linear detection, mainly about soft output sphere decoding algorithm. And then we simulate and analysis the performance of each algorithm.In this thesis we proposed a novel low complexity soft output sphere decoding algorithm for MIMO system. Based on the traditional Dijkstra sphere decoding algorithm, the algorithm use look-up table and single tree-search to update soft value (LLR) mechanism, improving enumeration of points and in or out of stack method in Dijkstra sphere decoding, reducing the cost of storage system. Without reducing the performance of the system, the proposed algorithm can reduce the complexity of the receiver efficiently. The simulation results show that the proposed sphere decoding algorithm and maximum likelihood (ML) decoding algorithm performance are almost the same with different modulation mode .Meanwhile the searching space of the algorithm which is the complexity of algorithm is reduced sharply.Finally, we study the MIMO broadcasting system of precoding techniques. Based on the system, we study the principle of vector permutation precoding and the solution of searching the optimal precoding vector by sphere encoding algorithm. According the research of MIMO detection technology in the receiver and the relationship between vector permutation precoding and sphere decoding, we propose two different sphere encoding algorithm to solve the problem of searching the optimal precoding vector ,including fixed complexity sphere encoding and metric-first sphere encoding algorithm. The simulation results show that, the two proposed sphere encoding algorithm can reduce the complexity of the transmitter precoding; meanwhile the performance of the system can be satisfied.In this thesis, we study the soft output sphere decoding algorithm and vector permutation precoding, and have achieved some achievements on the soft-output sphere decoding and vector permutation precoding. We also proposed some further research on the combined iteration of MIMO soft output sphere decoding and Turbo code for the high performance of the future wireless communication system and the vector permutation precoding on channel estimation error.