Neural network for solving Nash equilibrium problem in application of multiuser power control

被引:31
作者
He, Xing [1 ]
Yu, Junzhi [2 ]
Huang, Tingwen [3 ]
Li, Chuandong [1 ]
Li, Chaojie [4 ]
机构
[1] Southwest Univ, Sch Elect & Informat Engn, Chongqing 400715, Peoples R China
[2] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
[3] Texas A&M Univ, Dept Math, Doha, Qatar
[4] RMIT Univ, Sch Elect & Comp Engn, Melbourne, Vic 3001, Australia
关键词
Neural network; Multiuser power control; Nash game; Global convergence; VARIATIONAL-INEQUALITIES; PSEUDOCONVEX OPTIMIZATION; SUBJECT;
D O I
10.1016/j.neunet.2014.06.002
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, based on an equivalent mixed linear complementarity problem, we propose a neural network to solve multiuser power control optimization problems (MPCOP), which is modeled as the noncooperative Nash game in modern digital subscriber line (DSL). If the channel crosstalk coefficients matrix is positive semidefinite, it is shown that the proposed neural network is stable in the sense of Lyapunov and global convergence to a Nash equilibrium, and the Nash equilibrium is unique if the channel crosstalk coefficients matrix is positive definite. Finally, simulation results on two numerical examples show the effectiveness and performance of the proposed neural network. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:73 / 78
页数:6
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