Document Type
Conference Proceeding
Publication Date
2018
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
Publication Information
Amiri, Roohollah; Mehrpouyan, Hani; Matolak, David; and Elkashlan, Maged. (2018). "Joint Power Allocation in Interference-Limited Networks via Distributed Coordinated Learning". 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall): Proceedings, . http://dx.doi.org/10.1109/VTCFall.2018.8690565