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

abstract

• 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.

authors

• Huang, Tingwen

published proceedings

• Neural Netw

altmetric score

• 0.25

author list (cited authors)

• He, X., Yu, J., Huang, T., Li, C., & Li, C.

citation count

• 28

complete list of authors

• He, Xing||Yu, Junzhi||Huang, Tingwen||Li, Chuandong||Li, Chaojie

publication date

• September 2014

publisher

• Elsevier  Publisher

published in

• Neural Networks  Journal

keywords

• Algorithms
• Computer Communication Networks
• Global Convergence
• Models, Theoretical
• Multiuser Power Control
• Nash Game
• Neural Network
• Neural Networks, Computer

PubMed Central ID

• 24945472

Digital Object Identifier (DOI)

• 10.1016/j.neunet.2014.06.002

start page

• 73

end page

• 78

volume

• 57

URL

• http%3A%2F%2Fdx.doi.org%2F10.1016%2Fj.neunet.2014.06.002