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A Non-Gaussian Noise 3d-mimo Channel Estimation Method

A 3D-MIMO, non-Gaussian noise technique used in the field of channel estimation

Active Publication Date: 2019-12-24
XI AN JIAOTONG UNIV
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Problems solved by technology

[0003] In order to solve the non-Gaussian noise 3D-MIMO channel estimation problem, the present invention proposes a sparse Bayesian learning channel estimation method, thereby accurately estimating the 3D-MIMO channel matrix under non-Gaussian noise

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  • A Non-Gaussian Noise 3d-mimo Channel Estimation Method

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Embodiment Construction

[0041] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0042] In order to more clearly illustrate the purpose, technical solutions and advantages of the present invention, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, and are not intended to limit the present invention.

[0043] Consider a single-cell uplink OFDM system, the base station antenna is a uniform planar array, and the number of antenna elements on the array is N r , the number of users served by the base station is K, and the number of pilot signals is N p , the received signal model is as figure 2 shown. After the signal sent by the user is transmitted, the received signal at the base station is:

[0044]

[0045] In the above formula, L is t...

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Abstract

The invention discloses a non-Gaussian noise 3D-MIMO channel estimation algorithm, which comprises the following steps of obtaining a support set of a channel matrix by utilizing a judgment condition,selecting a dictionary matrix under the support set, and carrying out order selection calculation of a Gaussian mixture model according to the characteristics of a received signal; computing a weightleast square matrix; obtaining a coefficient and a variance of the Gaussian mixture model; estimating the channel matrix column by column in order to obtain an estimated value of the first time; judging whether an iteration result tends to be stable or reaches the number of iterations, and obtaining a channel matrix under the support set; otherwise repeating the steps until the condition is met;and generating a full-zero matrix when the iteration result is met, inserting the channel matrix under the support set into the all-zero matrix line by line according to positions where non-zero elements in the support set are located, making the rest of positions unchanged, and obtaining an actual channel matrix. A normalization mean square error of the estimation algorithm is obviously superiorto that of other algorithms, and an ideal estimation performance is still achieved under a condition that a signal-to-noise ratio is low.

Description

technical field [0001] The present invention relates to the field of communication technology, in particular to a channel estimation method. Background technique [0002] With the rise of technologies such as data AI, big data, and cloud computing, various terminals in mobile communications have higher and higher requirements for data transmission rates. The massive Multi-Input Multi-Output (MIMO) technology using multiple antennas at the transmitting end and the receiving end can increase the channel capacity of the system without increasing bandwidth and transmitting power. Therefore, 3D-MIMO has become one of the key technologies for the upcoming commercial 5G network. Traditional MIMO can only process signals in the horizontal direction. 3D-MIMO develops the spatial degree of freedom in the vertical direction by dynamically adjusting the downtilt angle of the antenna, thereby reducing inter-cell interference and greatly improving system throughput and spectrum efficienc...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L25/02H04B7/0456H04B7/0452
CPCH04B7/0452H04B7/0456H04L25/0202H04L25/024
Inventor 李锋陈伟彭伊婷
Owner XI AN JIAOTONG UNIV
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