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

被引：57

作者：

Yan, Shi ^{[1
]}

Peng, Mugen ^{[1
]}

Abana, Munzali Ahmed ^{[1
]}

Wang, Wenbo ^{[1
]}

机构：

[1] Beijing Univ Posts & Telecommun, Minist Educ, Key Lab Universal Wireless Commun, Beijing 100876, Peoples R China

来源：

IEEE ACCESS | 2017年 / 5卷

基金：

中国国家自然科学基金;

关键词：

Fog radio access networks; access mode selection; performance analysis; evolutionary game; ALLOCATION;

D O I：

10.1109/ACCESS.2017.2654266

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The fog radio access network (F-RAN) is a promising paradigm to provide high spectral efficiency and energy efficiency. Characterizing users to select an appropriate communication mode in F-RANs is critical for performance optimization. With evolutionary game theory, a dynamic mode selection is proposed for F-RANs, in which the competition among the groups of potential users' space is formulated as a dynamic evolutionary game, and the game is solved by an evolutionary equilibrium. Stochastic geometry tool is used to derive the proposals' payoff expressions for both fog access point and device-to-device users by considering node location, cache sizes, as well as the delay cost. The analytical results for the proposed game model and the corresponding solution are evaluated, which show that the evolutionary game-based access mode selection algorithm has a better payoff than the max rate-based algorithm.

引用

页码：2200 / 2210

页数：11

共 27 条

[1] Coverage and Rate Analysis in Heterogeneous Cloud Radio Access Networks With Device-to-Device Communication [J].