Research On Linear Precoding And Correlative Techniques Of MIMO Systems

With the rapid development of multimedia service and mobile internet, it requires wireless communication systems to increase the data rate further. But due to limited radio spectrum resource, one of the key problems to solve is to improve spectrum efficiency for the next generation wireless communication system. Multiple Input Multiple Output(MIMO) technique has more freedom in space and can increase the system capacity highly without occupying more bandwidth and transmit power, so it becomes the mandatory technique for the next generation wireless communication systems. In MIMO systems, precoding technique is one of the key techniques which help MIMO systems to realize high performance.Under the support of HuaWei Foundation (Research on precoding of MIMO-OFDM systems), linear precoding and correlative techniques in the MIMO systems are investigated in the dissertation, involving MIMO Broadcast Channel (MIMO BC) systems and MIMO cooperative systems. The main contributions of the dissertation are as follows:(1) In the research of precoding technique in MIMO BC, the methods with partial interference cancellation have more advantage on the interference cancellation methods in term of system capacity. Considering a compromise between performance and complexity, a new linear precoding method with low complexity is proposed in MIMO BC with one antenna at each receiver. The proposed precoding method belongs to partial cancellation methods. In two-user system a novel model based on vector is established, and the optimal precoding vectors and power allocation are derived. And then it turns a multi-user system into a number of independent two-user or one-user systems. Simulations show that the proposed method has the similar capacity with minimum mean square error (MMSE) precoding but its complexity is lower than MMSE.(2) In order to avoid the defect that the feedback overhead is too large in the uplink when all user's Channel State Information (CSI) is required by the base station, a new user selection algorithm is proposed in MIMO BC systems based on BD precoding method. In the proposed algorithm, every user receives the matrix sending by the base station and calculates its channel state indicator using the received matrix according to the design method. Then every user feeds back the channel state indicator to the base station, and the base station selects the best ones and asks them for their CSI feedback but not all users. So it can reduce overhead in the uplink by allowing some users to feed back their CSI while it still maintains the high system performance and low complexity.(3) The CSI at transmitter used by BD precoding method is not only for multiuser interference cancellation in MIMO BC systems. So based on receiver capacity upperbound maximizing, an efficient quantization and feedback scheme is proposed in MIMO BC systems with limited feedback which using BD precoding method. The information fed back by the proposed scheme includes sub-channel gains except for the channel direction information which is utilized to cancel multiuser interference. Compared with the traditional scheme which only considers channel direction information, the proposed method improves the system capacity without any other additional complexity.(4) The existing user selection algorithms have big Signal to Interference plus Noise Ratio (SINR) estimation error and it constraines the capacity of MIMO BC system with limited feedback when using random vector quantization. So a new multiuser selection algorithm is proposed for MIMO BC system based on Zero Forcing Beamforming when limited channel state information is available at the transmitter. In this dissertation by combining the deduced upper and lower bound to estimate the user's received signal power, a novel user's SINR estimation method with smaller error is derived and a new corresponding multiuser selection algorithm is proposed. It is showed that better performance and lower complexity can be achieved with the proposed algorithm both in low SNR and in high SNR.(5) A joint precoding design is proposed for the MIMO cooperative system where exists CSI estimation error. The design is for minimizing mean square error of three-node relay system under the effect of CSI estimation error, so the precoder at source node and relay node are jointly designed using MMSE criterion. Simulations show that the proposed algorithm improves the bad effect brought by CSI estimation error and it is better than traditional method.