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A channel assignment and user association strategy based on amab model

A channel allocation and channel technology, applied in wireless communication, network topology, electrical components, etc., can solve problems such as unfavorable implementation, complex correlation process, and large time-consuming, and achieve the effect of solving large delay

Active Publication Date: 2018-07-13
SHANGHAI JIAOTONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0022] This invention aims at the problem of access-type load balancing initiated by STAs. After the AC obtains the association scheme, it needs to notify the STAs of the association results, and requires the participation of the STAs to complete the optimal association operation. The association process is complicated and time-consuming, and requires the STAs The protocol stack is modified, which is not conducive to the implementation

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  • A channel assignment and user association strategy based on amab model
  • A channel assignment and user association strategy based on amab model
  • A channel assignment and user association strategy based on amab model

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Embodiment 1

[0083] A channel allocation and user association strategy based on the AMAB model. The steps are: when APs and STAs are distributed in a highly dense network, and a new AP accesses the network, the following channel allocation and user association strategy is adopted.

[0084] Step 1: For any AP in the current scene, the number of channels that can be allocated is M. Each AP saves a probability distribution sequence for channel selection, and the channel probability sequence selected by the AP in the t-th round of decision-making is recorded as:

[0085] (1) where p j,t is the probability of selecting a channel in the t-th round of decision-making;

[0086] P t =(p 1,t ,p 2,t ,...,p M,t )

[0087] (2) The initial values ​​of the AP's channel selection probability sequence are all equally probable distributions.

[0088] Step 2: each AP according to the probability sequence P of the current round t t =(p 1,t ,p 2,t ,...,p M,t ) to select a channel, and count informat...

Embodiment 2

[0104] When APs and STAs are distributed in a high-density network, and a new STA accesses the network, the following channel allocation and user association strategies are adopted.

[0105] Step 1: For any STA in the current scene, the number of APs that can be associated is M. The STAs respectively store a probability distribution sequence associated with the AP, and the probability sequence selected by the STA in the t-th round of decision-making is recorded as:

[0106] P t =(p 1,t ,p 2,t ,...,p M,t )

[0107] (1) where p j,t is the probability of choosing AP in the t-th round of decision-making;

[0108] (2) The initial value of the probability sequence of each STA is an equal probability distribution.

[0109] Step 2: each STA a according to the probability sequence P of the current round t t =(p 1,t ,p 2,t ,...,p M,t ) to select the AP to associate with, and count the respective average data arrival rate, delay, and throughput information, and then obtain the...

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Abstract

The invention discloses a channel allocation and user association strategy based on the AMAB model. The steps are as follows: each AP and STA set the decision-making probability sequence as an equal probability distribution; each AP selects a channel according to its own probability sequence, and counts STAs The average data arrival rate, delay and throughput information of the current selected channel is calculated; the AP calculates the cumulative cost parameter; the AP calculates a new probability sequence according to the exponential average weighting strategy; each STA selects the AP according to its own probability sequence Association, and calculate the average data arrival rate, delay and throughput and other information, and calculate the gain of the current associated AP; STA calculates the cumulative cost function; STA calculates a new probability sequence according to the exponential weighted average strategy, and continues to execute until the strategy converges to optimize. The invention can converge to Nash equilibrium and obtain an optimal solution, effectively solving the problem of large network time delay caused by co-channel interference in dense scenes.

Description

technical field [0001] The present invention relates to the field of wireless local area network, in particular, to a channel allocation and user association strategy based on AMAB model. Background technique [0002] In order to adapt to the increase in demand for data services caused by the rapid development of mobile devices, WiFi networks are installed in public places such as shopping malls, restaurants and hotels. In the above sports and entertainment venues, the application of WiFi networks is also considered to improve customer experience and expand economic benefits. But unlike common office networks, many gymnasiums have tens of thousands of seats, and the user density is hundreds of times that of ordinary office networks. For example, in a stadium with 50,000 seats, approximately 400 APs are required to provide sufficient network capacity and cover the entire venue. Therefore, in these places, the WiFi network presents the characteristics of high density, large ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04W72/04H04W72/08H04W84/12
Inventor 化存卿王凌志
Owner SHANGHAI JIAOTONG UNIV
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