The spectrum bands of the multiplebase stations comprise the sets of orthogonal wireless channels and spectrum usage scenarios the device to device pairs transmit over the dedicated frequency bands and the device to device pairs operate on the shared cellular channels. The goal of each device pair is to jointly select the wireless channel and power level to maximize its reward, defined as the difference between the achieved throughput and the cost of power consumption, constrained by its minimum tolerable signal-to-interference-plus-noise ratio requirements. We formulate this problem as a stochastic non-cooperative game with multiple players where each player becomes a learning agent whose task is to learn its best strategyand develop a fully autonomous multi-agent Q-learning algorithm converging to a mixed-strategy Nash equilibrium.The learning algorithm shows relatively fast convergence and near-optimal performance after a small number of iterations.
Potential topics included, but not limited:
Reinforcement Learning for self organization and power control of two-tier heterogeneous networks
Optimal new site deployment algorithm for heterogeneous cellular networks
Energy cost minimization in heterogeneous cellular networks with hybrid energy supplies
Configuration algorithm for service scalability in heterogeneous cellular networks
Q-learning based heterogeneous network selection algorithm
Bayesian reinforcement learning-based algorithm for heterogeneous cellular networks
Machine learning paradigms for next-generation communication networks
Online distributed user association for heterogeneous radio access network
Deadline of Submissions: 30 May 2021Notification of First Round: 30 July 2021Submission of revision: 30 September 2021Acceptance: 30 November 2021Tentative Publication date: 30 March 2022
Lead Guest EditorDr. Sadia DinSchool of Computer Science Kyungpook National UniversitySouth Korea Guest EditorsDr. Sudir Dixit Hewlett-Packard, United States Dr. Mahasweta Sarkar, Department of Electrical and Computer EngineeringSan Diego State University, United StatesDr. Indika Anuradha MendisUniversity of Agder, Norway Authors should follow the WPC Journal manuscript format described at the journal site. Manuscripts should be submitted online through https://www.editorialmanager.com/wire/default.aspx.