Research Of The Diagonalization Pre-coding Algorithm On LTE Downlink Multiuser MIMO Block

As a communications standard 3GPP long term evolution(LTE) not only has the third generation mobile communication systems but also standards to adapt to the advantages of high-speed mobile transmission quality and can reach 100 Mps downlink transmission rate has recently been proposed by ITU. Besides,long-term evolution LTE Advanced(LTE-A), as the LTE evolution goal post, has had all ITU standards for 4G communications technology and improved innovation in some areas of technology. Multiple-input multiple-output(MIMO) and pre-coding technology which can improve the performance of MIMO is essential for whether LTE-A or LTE to get high speed downlink transmission rate of the link. Pre-coding algorithm which can improve the performance of a MIMO system is an important way to study MIMO development. In this paper, in order to improve the performance of the LTE downlink further, I did further research on pre-coding algorithm and its power distribution.First of all, a type of power allocation method called SINR was put forward,which has lower computation complexity in the pre-coding relative to the water-filling power allocation. The current situation of pre-coding algorithm was also analyzed. An algorithm, which used SVD singular value decomposition getting pre-coding matrix, with SINR to achieve total power allocation was studied. Without iterative operation, computation complexity reduced as a consequence. What’s more,both of system capacity and error rate were promoted obviously relative to traditional average power a allocation scheme.In addition, in order to ensure that the system BER performance without loss of conditions to maximize the extent of the case reduce the computational complexity of block diagonalization pre-coding algorithm, another algorithm research. The algorithm for solving the channel pseudo-inverse matrix for Gram-Schmidt orthogonalization and orthogonal Matrix then LDL~H decomposed MIMO pre-coding block diagonalization algorithm improvements, here referred to as the GSO-LDL~Halgorithm. This pre-determined by the first coding algorithm to defy the channel matrix null space vector for Gram- Schmidt obtain equivalent channel matrix, and then using the equivalent matrix provides a uniform way to achieve gain LDL~H decomposition channel optimized to get the last of the pre-coding matrix. Finally, to simplify the search algorithm fast water injection line method to allocate system power. The simulation shows that compared to the traditional block diagonalization algorithm, GSO-LDL~H algorithm and the premise of improving error performance and capacity did not change, the system calculates the complications decreased significantly.