Dynamic Model for Network Selection in Next Generation HetNets with Memory-affecting Rational Users

11/11/2019
by   Shaohan Feng, et al.
0

Recently, due to the staggering growth of wireless data traffic, heterogeneous networks have drawn tremendous attention due to the capabilities of enhancing the capacity/coverage and to save energy consumption for the next generation wireless networks. In this paper, we study a long-run user-centric network selection problem in the 5G heterogeneous network, where the network selection strategies of the users can be investigated dynamically. Unlike the conventional studies on the long-run model, we incorporate the memory effect and consider the fact that the decision-making of the users is affected by their memory, i.e., their past service experience. Namely, the users select the network based on not only their instantaneous achievable service experience but also their past service experience within their memory. Specifically, we model and study the interaction among the users in the framework of fractional evolutionary game based on the classical evolutionary game theory and the concept of the power-law memory. We analytically prove that the equilibrium of the fractional evolutionary game exists, is unique and uniformly stable. We also numerically demonstrate the stability of the fractional evolutionary equilibrium. Extensive numerical results have been conducted to evaluate the performance of the fractional evolutionary game. The numerical results have revealed some insightful findings. For example, the user in the fractional evolutionary game with positive memory effect can achieve a higher cumulative utility compared with the user in the fractional evolutionary game with negative memory effect. Moreover, the fractional evolutionary game with positive memory effect can reduce the loss in the user's cumulative utility caused by the small-scale fading.

READ FULL TEXT
03/11/2021

Dynamic Network Service Selection in Intelligent Reflecting Surface-Enabled Wireless Systems: Game Theory Approaches

In this paper, we address dynamic network selection problems of mobile u...
09/28/2021

Dynamics in Coded Edge Computing for IoT: A Fractional Evolutionary Game Approach

Recently, coded distributed computing (CDC), with advantages in intensiv...
08/03/2020

Dynamic Network Service Selection in IRS-Assisted Wireless Networks: A Game Theory Approach

In this letter, we investigate the dynamic network service provider (SP)...
09/14/2017

An Evolutionary Game for User Access Mode Selection in Fog Radio Access Networks

The fog radio access network (F-RAN) is a promising paradigm for the fif...
02/26/2018

A Learning Approach for Low-Complexity Optimization of Energy Efficiency in Multi-Carrier Wireless Networks

This paper proposes computationally efficient algorithms to maximize the...
08/01/2017

Evolutionary game of N competing AIMD connections

This paper deals with modeling of network's dynamic using evolutionary g...
02/26/2018

Environmental Policy Regulation and Corporate Compliance in a Spatial Evolutionary Game Model

We use an evolutionary game model to study the interplay between corpora...