Research Of MU-MIMO System Precoding Technique

Multiple Input Multiple Output (MIMO) systems use multiple transmitting antennas and multiple receiving antennas to send and receive datas. This method can effectively suppress multi-path fading channels. Without increasing the system bandwidth and transmiting power of the antennas, it can make channel capacity as the antenna number linear increase, thereby enhance the spectral efficiency. Therefore, MIMO technology has become the core technology of the next generation (B3G) or the fourth generation (4G) mobile communications. The Pre-coding technology is to conduct a pre-processing to the transmitter to adjust the transmiting strategy to adapt to the corresponding channel environment by using channel state information, it can enhance the performance of MIMO systems. Therefore, precoding becomes one of the hot technologies in the MIMO research field at present. This paper focuses mainly on multi-user case, how to use pre-encoded to optimize system performance under different coditions, such as the system fully known to the transmitter channel state information, the existence of channel estimation error conditions, as well as with partial channel state information.This article first introduces the research background and the research status quo of the subject,then introduces the MIMO systems' wireless fading channel propagation characteristics, including the characteristics of mobile radio channel, MIMO multiplexing systems and sub-assembly technology, as well as the derivation of the channel capacity and the space channel model. All these knowledges are base of MU-MIMO pre-coding technology researching.In the third chapter, the pre-coding techniques are introduced under the condition of perfect channel state information, including a linear pre-equalization, block diagonalization algorithm, and the pre-coding techniques with joint transmit and receive optimization, which is included those based on singular value decomposition and the eigenvalue decomposition. Aslo it giv es out the simulation results and analysis. At the end of this chapter, the non-linear pre-coding algorithms are given which are mainly about dirty paper coding, including the source of the theory, the capacity, as well as the simulation methods. Chapter IV which is also the key part of this article introduces details of the limited feedback precoding method, such as the design of the codebook and the codebook selection principles. It also gives a simple pre-coding matrix selection algorithm, based on the pre-coding codebook from 3GPP-LTE. This method can greatly decrease the complexity in the case of having almost the same performance compared with the optimal solution. Then, the paper fouces on the combination of the pre-coding and multi-user selection. Based on the algorithm of per-user unitary and rate control, the article gives out an algorithm which relaxes the orthogonal definition of the PU2RC algorithm. This algorithm does not require any changes to the mobile terminals. The base station expands the scope of the user scheduling by the use of pre-designed relationship table between the codebook vectors. Although there is a slight increase on the computational complexity, this method could greatly improve the system performance.At the end of this paper, there is a summary of the entire text. What remains to be done in the next step and some future research directions are also given.