Research On The Key Technologies Of Downlink MIMO System For 5G

Looking ahead beyond the 4G system, we seek an innovative approach that can overcome the fundamental problems in wireless communications to fulfill the explosive wireless data demand. By making full use of wireless resources in spatial dimension, massive MIMO offers the opportunity to upscale the spectral and energy efficiencies by orders of magnitude antennas, realizing the vision of high-performance green mobile radio. While the advantages of massive MIMO are conceptually straightforward, realizing massive MIMO in the network level is far from simple and several fundamental deadlocks remain. The applicants and partners intend to conduct research on the theories and approaches of massive MIMO wireless communication which include the channel modeling and channel capacity analysis of massive MIMO systems in complex wireless environments and channel state information acquisition.This article firstly introduces the key technologies of downlink multi-user MIMO system,including information-theoretic capacity, pre-coding, channel model, channel estimation and channel detection, etc. At the same time, the fundamental limits of massive MIMO corresponding to each key technology are addressed. Then this article studies the limited feedback pre-coding for massive MIMO and proposes a method to optimize the channel state information and an effective user selection algorithm. Through sub-sampled the codebook and rearrangement of the pre-coding matrix, the proposed method optimizes the channel state information, which can effectively reduce the feedback overhead and lower the performance loss leaded by feedback channel transmission errors. This article also considers the downlink multi-user massive MIMO that the complexity of traditional user selection algorithms increases exponentially to the transmit antennas, where the base station equipped with a large number of antennas simultaneously serves multiple users. An effective user selection algorithm for quantized pre-coding in massive MIMO systems is proposed. The algorithm relaxes the optimal problem to be convex and solves it using the Primal Newton’s Barrier Method which has a better trade off complexity and performance.Modeling a channel model of realistic transmission has an important impact on the study of massive MIMO. Only the channel modeling is accurate enough, can it used for the actual performance evaluation such as link level and system level simulation. The current general channel model is mainly in two dimensions, in order to describe the channel model more accurately, we rebuild a channel model in three dimensions by extending ITU channel model. At the same time, we has calibrated the platform, including UE distribution, Coupling Loss, UE Geometry, Wideband SINR and eigenvalue distribution of channel. This new channel model is based on three-dimensional space which is more accurately to the actual channel and is better for massive MIMO assessments in the future.