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Large-scale MIMO fingerprint positioning method based on complex neural network

A neural network and fingerprint positioning technology, applied in biological neural network models, neural learning methods, and services based on location information, can solve problems such as large fluctuations and limited positioning accuracy, and achieve improved positioning accuracy, convenient implementation, The effect of enriching the expressive ability

Active Publication Date: 2021-06-18
SOUTHEAST UNIV +1
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Problems solved by technology

RSS is commonly used due to the convenience of collection, but it is affected by multipath effects and shadow fading, and fluctuates greatly in static environments, which can only roughly describe channel characteristics, resulting in limited positioning accuracy

Method used

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  • Large-scale MIMO fingerprint positioning method based on complex neural network
  • Large-scale MIMO fingerprint positioning method based on complex neural network
  • Large-scale MIMO fingerprint positioning method based on complex neural network

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Embodiment Construction

[0057] In order to enable those skilled in the art to better understand the present invention, the implementation process of the technical solution will be further described in detail below in conjunction with the accompanying drawings.

[0058] Such as figure 1 As shown, the complex neural network-based massive MIMO fingerprint location method disclosed in the embodiment of the present invention mainly includes two parts: an offline stage and an online stage.

[0059] Offline stage: First, divide the sample points at equal intervals in the positioning area. In the offline stage, the base station collects the uplink pilot signal of the user at each sample point for channel estimation, and obtains the channel frequency response (Channel Frequency Response) of the user at each sample point. , CFR) matrix H, where the CFR matrix at the kth sample point is H k , and then use the sparse domain transformation to reconstruct the location fingerprint G at the sample point k , record...

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Abstract

The invention discloses a large-scale MIMO fingerprint positioning method based on a complex neural network. The large-scale MIMO fingerprint positioning method mainly comprises an offline stage and an online stage. In the offline stage, firstly, sample points are divided at equal intervals in a positioning area, a base station end collects position fingerprint information of a user on each sample point in the positioning area, and a position fingerprint database is constructed; the position fingerprint information of each sample point is taken as the input of a complex neural network, the position of the corresponding sample point is taken as the output label of the complex neural network, the complex neural network is constructed, and the complex neural network is trained through the fingerprint database. In the online stage, the base station end uses the complex neural network trained in the offline stage, and uses the trained complex neural network to calculate and obtain the position coordinates of the user based on position fingerprints of the user received in real time, thereby realizing relatively high-precision user positioning.

Description

technical field [0001] The invention belongs to wireless communication technology, and in particular relates to a large-scale MIMO fingerprint positioning method based on a complex neural network. Background technique [0002] As one of the key technologies of 5G wireless communication, the massive MIMO (Multiple Input Multiple Output) system can greatly improve the spectral efficiency and throughput of the wireless communication system. By configuring a large-scale antenna array at the base station (BaseStation, BS) and using broadband Orthogonal Frequency Division Multiplexing (OFDM) technology, the system can obtain channel state information (Channel State) with extremely high angle and time resolution. Information, CSI). [0003] The rapid development of IoT technology has brought more demand for Location Based Service (LBS), such as self-driving cars, logistics warehouses, and unmanned moving vehicles. High-precision location information is the basis for providing goo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W4/02H04B17/309H04B7/0413G06N3/08G06N3/04G06F16/29
CPCH04W4/023H04W4/025H04B17/309H04B7/0413G06N3/084G06F16/29G06N3/048G06N3/045Y02D30/70
Inventor 潘志文蒋志函刘楠尤肖虎
Owner SOUTHEAST UNIV
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