Iterative beam forming method based on channel space sparse characteristic

A technology with sparse characteristics and beamforming, applied in the field of wireless communication, it can solve the problem of high antenna training overhead, and achieve the effect of easy expansion and good convergence

Inactive Publication Date: 2015-07-15
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Application Information

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Problems solved by technology

[0012] In order to overcome the defect that the antenna training overhead of the power iteration method is too large in the massive

Method used

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  • Iterative beam forming method based on channel space sparse characteristic
  • Iterative beam forming method based on channel space sparse characteristic
  • Iterative beam forming method based on channel space sparse characteristic

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Embodiment

[0053] S1. Use the geometric model of the sparse multipath channel to perform sparse modeling, express the estimation problem of the received signal associated with the channel as a recovery problem of the sparse signal, and define the dictionary matrix of the receiving end Among them, N represents the length of the dictionary at the receiving end. The larger the N, the finer the quantization, and the smaller the quantization error. Define the dictionary matrix at the sending end Among them, M represents the length of the dictionary at the receiving end, and the larger the M, the finer the quantization and the smaller the quantization error;

[0054] S2. Initialization processing, specifically as follows:

[0055] S21. The sender randomly generates a normalized N T ×1 vector f as the iteration initial vector, where, N T is the number of receiving antennas;

[0056] S22. Define the number of iterations N ITER , where N ITER = 4 or N ITER = 5;

[0057] S23, define the i...

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Abstract

The invention belongs to the technical field of wireless communications, particularly relates to a method for reducing iterative beam forming antenna training expenses through a channel space sparse characteristic in a wireless multiple input multiple output (MIMO) communication system, and provides an iterative beam forming method based on the channel space sparse characteristic. The method comprises the steps that sparse modeling is carried out through a geometric model of a sparse multipath channel; initialization is carried out; beam forming vector quantity training is received; the beam forming vector quantity training is sent. The space sparse characteristic of the millimeter wave channel is utilized, the estimating problem of vector quantity receiving in millimeter wave MIMO antenna training is converted into a sparse rebuilding problem, and therefore correlation theories of compressed sensing are utilized, and the expense of a power iteration method is further lowered by 50-60 percent with quite low performance losses.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a method for reducing antenna training overhead of iterative beamforming by utilizing inter-channel sparsity in a wireless multiple input multiple output (MIMO) communication system. Background technique [0002] like figure 1 As shown, in a MIMO system, according to the criterion of maximizing the signal-to-noise ratio at the receiving end, the method to obtain the optimal beamforming matrix is ​​the eigenbeamforming method. When the channel state information (Channel Statement Information, CSI) is known to both the transmitter and receiver, the optimal transmit and receive beamforming matrices can be obtained by performing singular value decomposition (SVD) on the channel matrix H. The specific principles are described as follows: [0003] Assume that the number of receiving antennas in the MIMO system is N T , the number of transmitting antennas i...

Claims

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Application Information

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IPC IPC(8): H04B7/04
CPCY02D30/70
Inventor 成先涛付自刚
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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