Home // International Journal On Advances in Telecommunications, volume 12, numbers 1 and 2, 2019 // View article
Authors:
Abheek Saha
Keywords: mean-field games; stochastic control; distributed resource allocation; distributed optimization; adaptive rate contro
Abstract:
Mean-field theory is a significant recent development in the field of stochastic optimal control. By allowing the optimal control functions to take into account not only the state of the individual agent, but also the common state of an entire ensemble of mutually inter-dependent agents, mean-field theory allows us to model ensembles of autonomous agents pursuing individually optimal trajectories in a shared environment. In this paper, the application of stochastic optimal control has been shown for a very standard problem of cellular networks, the optimum resource allocation problem. In modern cellular networks, the optimal resource assignment for individual cells has to take into account the loading of the entire network, since user stations are free to adjust transmission rates and migrate among cells, while cells can also trade bandwidth between themselves. The problem is to achieve an optimal matching of available resources to the individual demands for capacity, taking into account the temporal and spatial variation in demand. By modelling the demand and capacity and their mutual interaction using mean-field theory, it has been shown that the matching problem can be cast as a distributed optimal control function. We have used a novel method to solve the corresponding mean-field game and demonstrated that the solution provides an effective mechanism for demand regulation and capacity assignment.
Pages: 1 to 19
Copyright: Copyright (c) to authors, 2019. Used with permission.
Publication date: June 30, 2019
Published in: journal
ISSN: 1942-2601