Skip to main content
profile image
Selected Works of Hani Mehrpouyan
Contribution to Book
Joint Power Allocation in Interference-Limited Networks via Distributed Coordinated Learning
2018 IEEE 88th Vehicular Technology Conference (VTC-Fall): Proceedings
  • Roohollah Amiri, Boise State University
  • Hani Mehrpouyan, Boise State University
  • David Matolak, University of South Carolina
  • Maged Elkashlan, Queen Mary University of London
Download Find in your library
Document Type
Conference Proceeding
Publication Date
1-1-2018
Disciplines
Abstract

Dense deployment of small base stations (SBSs) is one of the main methods to meet the 5G data rate requirements. However, high density of independent SBSs will increase the interference within the network. To circumvent this interference, there is a need to develop self-organizing methods to manage the resources of the network. In this paper, we present a distributed power allocation algorithm based on multi-agent Q-learning in an interference-limited network. The proposed method leverages coordination through simple message passing between SBSs to achieve an optimal joint power allocation. Simulation results show the optimality of the proposed method for a two-user case.

Copyright Statement

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. doi: 10.1109/VTCFall.2018.8690565

Citation Information
Roohollah Amiri, Hani Mehrpouyan, David Matolak and Maged Elkashlan. "Joint Power Allocation in Interference-Limited Networks via Distributed Coordinated Learning" 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall): Proceedings (2018)
Available at: http://works.bepress.com/hani_mehrpouyan/85/