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. © 2014 Elsevier Ltd.
| Original language | English |
|---|---|
| Pages (from-to) | 73-78 |
| Journal | Neural Networks |
| Volume | 57 |
| DOIs | |
| Publication status | Published - Sept 2014 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Funding
This work is supported by Fundamental Research Funds for the Central Universities (Project No. XDJK2014C118, SWU114007) and Natural Science Foundation of China (Grant No. 61374078 , 61375102 ), and this publication was made possible by NPRP Grant No. NPRP 4-1162-1-181 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Research Keywords
- Global convergence
- Multiuser power control
- Nash game
- Neural network
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