Iterative beam forming method of millimeter wave precoding system

A beamforming and precoding technology, applied in the field of antenna training overhead, can solve the problem of high antenna training overhead

Inactive Publication Date: 2016-08-10
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0010] In order to overcome the defect that the antenna training overhead of the power iteration method in the massive MIMO system is too large, the present invention proposes an iterative beamforming method in the millimeter wave precoding system. This method utilizes the spatial sparsity of the millimeter wave channel to The estimation problem of the receiving vector in MIMO antenna training is transformed into a sparse reconstruction problem, so that the related theory of compressed sensing can be used to reduce the loss

Method used

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  • Iterative beam forming method of millimeter wave precoding system
  • Iterative beam forming method of millimeter wave precoding system
  • Iterative beam forming method of millimeter wave precoding system

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Embodiment

[0049] 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

[0050]

[0051] Define the sender dictionary matrix Among them, N represents the length of the dictionary at the receiving end, and M represents the length of the dictionary at the receiving end. The larger N, the finer the quantization, and the smaller the quantization error. The larger M, the finer the quantization, and the smaller the quantization error;

[0052] S2. Establish an angle quantization codebook, the codebook at the receiving end is The transmitter codebook is in, is the codebook size, N T is the number of transmit antennas, N R is the number of receiving antennas;

[0053] S3, initial stage processing, specifically as follows:

[0054] S31. The sender generates an N T ×1 ...

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Abstract

The invention belongs to the technical field of wireless communication, and particularly relates to a method for reducing antenna training overhead of iterative beam forming by utilizing inter-channel sparsity in a wireless multiple input multiple output (MIMO) communication system. The invention provides an iterative beam forming method of a millimeter wave precoding system, and is used for overcoming the defect of high antenna training overhead of a power iteration method of a large-scale MIMO system. According to the method, the spatial sparsity of a millimeter wave channel is utilized, and the estimation problem of receiving vectors of millimeter wave MIMO antenna training is converted into a sparse reconstruction problem so that the loss is reduced by utilizing the correlation theory of compression perception.

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 using inter-channel sparsity in a wireless Multiple Input Multiple Output (MIMO) communication system. Background technique [0002] Beamforming technology is an array signal processing technology, which can be regarded as spatial linear filtering. In MIMO systems, it can be used to overcome path loss, improve receiving signal-to-noise ratio, and increase system capacity. In the beamforming technology, the key is to obtain the optimal array signal weighting vector at the transceiver end that satisfies the set criteria under the current channel state. Under the optimal capacity criterion, the beamforming weight vector at the transceiver end is a singular vector obtained through the singular value decomposition (SVD) of the channel matrix. The specific principles are described as ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04B7/04H04B7/06
CPCH04B7/0413H04B7/0617
Inventor 娄念念成先涛
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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