The Research On Preocding In Multi-User MIMO System

Multiple Input Multiple Output (MIMO) technique can greatly enhance the capacity and improve the performance of the wireless communication system. As one of the major techniques of 3G and next generation mobile communication system, MIMO technique is getting more and more attentions. Some theories and key techniques about MIMO have been focused world widely, including the research on precoding techniques. Modern communication systems require higher data transmission ratethan ever. This promotes the application and study of new and sophisticated signal processing methods. Precoding is one of the signal processing methods which requires channel state information at transmitter. This technique is widely studied now.In the case of multiple user broadcast channel, as the different geographic locations of users, they can not receive signals cooperatively. The user interference can not be eliminated by simple multiple user detection. However, the problem of user interference in MU-MIMO can be solved by precoding technique. In theory, the full capacity region of MIMO broadcast channel can be achieved by DPC. Thus the precoding is the key problem in MIMO application and is worthy of being studied.Therefore, the precoding of MU-MIMO system is studied in this thesis. To summarize, the research includes the following aspects:Firstly, a low-complexity algorithm in null-space calculation is introduced in the user antenna selection problem with block diagonalization precoding. In the processing of optimal user antenna selection, SVD is generally needed for calculating the null-space in each case which results high complexity. The newly proposed algorithm utilizes the relations of difference selection case. Adjust the existing null-space result recursively to get the new one. It can be showed that the calculation complexity of the new algorithm is relatively lower than using the SVD method directly.Secondly, the precoding technique based on limited feedback has been researched in this thesis. The quantization error of channel vector greatly influences the system capacity in MU-MIMO precoding. The codebook size should be enlarged to improve the upper bound of the sum capacity. However, larger codebook means greater costs in precoding. In the thesis, a new quantization method has been proposed, using the linear combination of two code words to represent the channel information. Simulation results show that by utilizing the new method, the code book size can be reduces and so do the quantization costs.Next, a new precoding method has also been proposed for the case of multiple antenna receivers. Such method can increase the system capacity. With fixed codebook, the quantization error can be reduced by forming the effective antennas by combining the receiving signals. And by a way of effective antennas selection, the performance of precoding can be further increased.Finally, the thesis explains the topics for future research, including antenna selection algorithm, code book design and precoding method in limited feedback system.