A physical cell identification distribution method based on a maximum priority dyeing algorithm

A technology of physical cells and allocation methods, applied in character and pattern recognition, computing, computer components, etc., can solve the problem of limited number of PCI

Active Publication Date: 2019-04-09
BEIJING UNIV OF TECH
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Problems solved by technology

However, due to the limitation of physical spectrum

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  • A physical cell identification distribution method based on a maximum priority dyeing algorithm
  • A physical cell identification distribution method based on a maximum priority dyeing algorithm
  • A physical cell identification distribution method based on a maximum priority dyeing algorithm

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[0051] The invention adopts the K-means clustering algorithm to perform clustering processing on massive network user mobile data, and realizes the determination and division of hotspot areas. Then a PCI allocation method based on the maximum priority coloring algorithm is proposed. This method can quickly and effectively allocate and multiplex the small cell base stations in hotspots, while reducing the probability of PCI conflict and confusion, and improving the hotspots. The user’s network service quality.

[0052] The present invention adopts the following technical solutions and implementation steps.

[0053] Step 1. Build a deployment model of cellular network base stations. Macro cellular network base stations use the traditional Wrap-Around deployment model, such as figure 1 As shown, the scene is 1500×1500m 2 The macro cellular network base station simulation deployment diagram under. For the small cell network, the present invention uses the homogeneous Poisson point pro...

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Abstract

The invention relates to a physical cell identification distribution method based on a maximum priority dyeing algorithm. The problem that in the small cellular network technology, due to an extremelylimited number of physical cell identification (PCI) used for identifying a cellular network base station, the network quality of service (QoS, Quality of Service) of a user is greatly influenced since the small cellular network cannot be deployed smoothly is solved. The method comprises the following steps: firstly, clustering massive network user mobile data by using a K-means clustering algorithm, and dividing and determining a hot spot region of a user; and performing PCI allocation and multiplexing on the cellular base stations in different hot spot regions based on a maximum priority dyeing algorithm. According to the method, PCI allocation and multiplexing can be rapidly and effectively carried out on the cellular base station, meanwhile, the conflict confusion probability of the PCI is reduced, and the QoS of users in a hot spot region is guaranteed.

Description

technical field [0001] The invention uses a K-means clustering algorithm to perform clustering processing on a large amount of mobile data of network users, thereby realizing the determination and division of hotspot areas. Then a PCI allocation method based on the maximum degree priority coloring algorithm is proposed. This method can quickly and effectively allocate and multiplex PCI to small cell base stations in hotspot areas, and at the same time reduce the conflict and confusion probability of PCI, and improve the efficiency of hotspot areas. User's network quality of service. The PCI allocation method based on the maximum degree priority coloring algorithm belongs to the field of mobile communication networks. Background technique [0002] With the rapid development of wireless communication and mobile Internet technology, the global mobile network data traffic has increased twenty-fold in the past five years. As of the end of 2017, statistical results show that the...

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Application Information

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IPC IPC(8): H04W16/18H04W24/02H04W24/04H04L12/24G06K9/62
CPCH04L41/145H04W16/18H04W24/02H04W24/04G06F18/23213
Inventor 涂山山刘濛安明扬肖创柏
Owner BEIJING UNIV OF TECH
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