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段沛博 Associate professor
Personal Information
Supervisor of Master's Candidates
Name (Pinyin):duanpeibo
Date of Employment:2020-09-30
Education Level:With Certificate of Graduation for Doctorate Study
Gender:Male
Professional Title:Associate professor
Status:Employed
College:软件学院
Discipline:
Computer Applications Technology
智能科学与技术
Computer Applications Technology
智能科学与技术
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Applying DCOP to User Association Problem in Heterogeneous Networks with Markov Chain Based Algorithm
Release Time:2022-04-08Hits:
First Author:
段沛博
Co author:
张斌,张长胜
Title of Paper:
Applying DCOP to User Association Problem in Heterogeneous Networks with Markov Chain Based Algorithm
Journal:
arXiv preprint arXiv:1701.01289
Summary:
Multi-agent systems (MAS) is able to characterize the behavior of individual agent and the interaction between agents. Thus, it motivates us to leverage the distributed constraint optimization problem (DCOP), a framework of modeling MAS, to solve the user association problem in heterogeneous networks (HetNets). Two issues we have to consider when we take DCOP into the application of HetNet including: (i) How to set up an effective model by DCOP taking account of the negtive impact of the increment of users on the modeling process (ii) Which kind of algorithms is more suitable to balance the time consumption and the quality of soltuion. Aiming to overcome these issues, we firstly come up with an ECAV- (Each Connection As Variable) model in which a parameter with an adequate assignment ( in this paper) is able to control the scale of the model. After that, a Markov chain (MC) based algorithm is proposed on the basis of log-sum-exp function. Experimental results show that the solution obtained by DCOP framework is better than the one obtained by the Max-SINR algorithm. Comparing with the Lagrange dual decomposition based method (LDD), the solution performance has been improved since there is no need to transform original problem into a satisfied one. In addition, it is also apparent that the DCOP based method has better robustness than LDD when the number of users increases but the available resource at base stations are limited.
Translation or Not:
No
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