Iterative channel estimation method in multi-user large-scale MIMO system

A channel estimation, large-scale technology, applied in diversity/multi-antenna systems, baseband system components, space transmit diversity, etc., can solve the problems of large training overhead, channel estimation meaninglessness, and overshooting, and achieve the effect of reducing overhead

Inactive Publication Date: 2015-11-11
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

In this case, the number of pilot signals is proportional to the number of BS antennas N. Due to the huge number of antennas in massive MIMO systems, conventional channel estimation methods (suc

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  • Iterative channel estimation method in multi-user large-scale MIMO system
  • Iterative channel estimation method in multi-user large-scale MIMO system
  • Iterative channel estimation method in multi-user large-scale MIMO system

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Embodiment Construction

[0054] The technical solution of the present invention will be described in detail below in combination with the embodiments and the accompanying drawings.

[0055] Such as figure 1 As shown in the schematic diagram of a multi-user massive MIMO channel, it is assumed that the number of MSs is K=40, the BS is configured with a uniform linear array (ULA), and the number of BS antennas is N=150, and each user has a single antenna, that is, M=1. In addition, assuming that the sparse support number (sparse degree) of each MS channel is the same and s=17, the common sparse support number s c =9.

[0056] figure 2 It is a comparison chart of the performance of the algorithm of the present invention when it is applied to multi-user massive MIMO channel estimation and other sparse signal recovery algorithms when it is applied to the same channel estimation for different overheads. It can be seen from the figure that the algorithm of the present invention achieves optimal performanc...

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Abstract

The invention belongs to the technical field of wireless communication and specifically relates to a channel estimation algorithm of a single-antenna multi-user large-scale MIMO (MU-Massive MIMO) system under a frequency division duplex (FDD) mode. The method is an algorithm for reducing channel estimation expenditure by using united sparsity of the multi-user large-scale MIMO system under a Bayes compression sensing framework, and the basic mode of the algorithm is to use a BS to serve for a plurality of users. A large-scale antenna array is configured at a BS end, and mobile subscriber is a single antenna. By using the united sparsity of the channel and introducing an iterative algorithm based on a bayes method to perform channel estimation, the method of the invention greatly reduces the expenditure of the channel estimation and enables the time of channel estimation to be far less than the coherence time of the channel.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a channel estimation algorithm of a single-antenna multi-user massive MIMO (MU-Massive MIMO) system in a frequency division duplex (FDD) mode. Background technique [0002] The massive MIMO system is one of the key technologies of the fifth-generation mobile communication system. Its main advantages are: (1), the system capacity increases with the number of antennas; (2), the transmission signal power is reduced; (3), simple The linear precoder and detector can achieve the optimal performance; (4), the channels tend to be orthogonal, so the co-channel interference in the cell is eliminated. [0003] The prerequisite for realizing these advantages is that the BS knows the channel state information. In the TDD system, channel estimation is performed in the MS by utilizing the reciprocity of the uplink and downlink channels. Therefore, the channel estima...

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Application Information

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IPC IPC(8): H04L25/02H04B7/04
Inventor 成先涛付自刚
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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