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Joint optimization method for heterogeneous network user access and time domain interference coordination based on graph theory

A technology of time-domain interference coordination and joint optimization, which is applied in access restriction, wireless communication, electrical components, etc.

Active Publication Date: 2016-06-15
宁波赤元生态数据科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In addition, for users at the edge of a small cell, the user's access decision will affect the user's communication quality, and may cause continuous call drop due to the ping-pong effect

Method used

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  • Joint optimization method for heterogeneous network user access and time domain interference coordination based on graph theory
  • Joint optimization method for heterogeneous network user access and time domain interference coordination based on graph theory
  • Joint optimization method for heterogeneous network user access and time domain interference coordination based on graph theory

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specific Embodiment approach 1

[0037] Specific implementation mode one: as figure 1 As shown, the implementation process of the joint optimization method for heterogeneous network user access and time-domain interference coordination based on graph theory described in the implementation mode is as follows:

[0038] Step 1. Link the macro base station and the micro base station to the general control center, and the user access and time-domain interference coordination are all performed through the general control center;

[0039] Step 2. In the stage of user communication initiation, each base station obtains the channel information of the user through signaling, and each base station reports the channel information of the user connected to the base station to the general control center;

[0040] Step 3. Determine the optional range of ABSF ratio is 1 / 10 to 5 / 10, choose from small to large;

[0041] Step 4. Every time an ABSF ratio is selected, the general control center maximizes the objective function th...

specific Embodiment approach 2

[0043] Embodiment 2: This implementation method mainly explains in detail the user access algorithm in Step 4 of Embodiment 1. refer to figure 1 This embodiment will be described. The joint user access algorithm method described in this embodiment is implemented through the following steps:

[0044] Step 1. The UE counts and receives the RSSI values ​​from each base station. If the user's first and second strongest received signal strength difference Γ diff ≥Γ diff.threshold , the users are connected to the first strongest base station, and these users belong to the assigned user group. If Γ diff diff.threshold , such users belong to the user group to be assigned.

[0045] Step 2. Define another threshold Γ th , for each user, the received signal strength Γ BSi Greater than Γ th All micro base stations of , defined as mutual interference micro base stations. Through the vertex coloring method, the micro base stations are divided into several groups according to the m...

specific Embodiment approach 3

[0053] Specific implementation mode three: this implementation mode is to further illustrate the improved KM algorithm in the above-mentioned implementation mode:

[0054] Since each vertex in the KM algorithm can only be connected by one edge, and in our scenario there may be many users connected to the same vertex, so here we make an improvement. For a base station, if this base station exists in multiple candidate base stations of users to be allocated, then as many vertices as there are such users are established for this base station. For example, there are base station 1 among the candidate base stations of 5 users to be allocated, then 5 vertices are established for base station 1.

[0055] first according to figure 2 Introduce the definitions in several graph theory algorithms:

[0056] Adjacent: In graph theory, there is a connectable relationship between two points, which is called adjacent. The user and the candidate base station are in an adjacent relationship....

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Abstract

The invention provides a joint optimization method for heterogeneous network user access and time domain interference coordination based on the graph theory, and relates to the technical field of communication resource allocation optimization. In order to provide better overall communication quality of the user, the system capacity of a cellular network is increased. The joint optimization method comprises the following steps: linking a macro base station and a micro base station to a total control center; in a user communication initiation stage, obtaining channel information of the user by the base stations through signaling; determining an optional range of ABSF proportions, and sequentially selecting from small to large; once selecting an ABSF proportion, maximizing a target function by the total control center by user access; selecting an access decision through an improved KM algorithm; and comparing the sizes of the optimal target functions under the ABSF proportions, selecting the maximum proportion as the final time domain interference coordination parameter, and selecting the user access method of the maximum target function as the final access mode. The joint optimization method is suitable for a time domain interference coordination and access control joint user in a heterogeneous network with the coexistence of the macro base station and the micro base station.

Description

technical field [0001] The invention relates to a graph theory algorithm-based joint optimization method for heterogeneous network user access and time-domain interference coordination, and relates to the technical field of communication resource allocation optimization. technical background [0002] Nowadays, as people's demand for wireless data services increases, in order to ensure users have better communication quality and higher data transmission speed, wireless cellular network (such as 3G, LTE) base stations are deployed more and more intensively. Moreover, in order to deal with the problems of fast weakening of indoor wireless signals and high population density, micro base stations (small-cells) have begun to be deployed indoors. The dense deployment of small base stations with small coverage and low transmission power can provide better wireless network service quality for indoor personnel. The macro base station and the micro base station form a heterogeneous ne...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W48/20H04W72/08H04W72/54
CPCH04W48/20H04W72/541H04W72/542
Inventor 马琳陈亮徐玉滨刘宁庆
Owner 宁波赤元生态数据科技有限公司
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