A Matching Game Solution for Optimal RAT Selection in 5G Multi-RAT HetNets

Author(s):  
Mohamed G. Anany ◽  
Mahmoud M. Elmesalawy ◽  
Eman Serag El Din
Keyword(s):  
1999 ◽  
Vol 106 (2) ◽  
pp. 168
Author(s):  
Donald E. Knuth ◽  
Philip D. Straffin
Keyword(s):  

Author(s):  
J. Pérez-Romero ◽  
O. Sallent ◽  
R. Agustí ◽  
J. Nasreddine ◽  
M. Muck

Author(s):  
Wei-Sheng Lai ◽  
Tsung-Hui Chang ◽  
Ta-Sung Lee

Game theoretical approaches have been used to develop distributed resource allocation technologies for cognitive heterogeneous networks. In this chapter, we present a novel distributed resource allocation strategy for cognitive small cell networks based on orthogonal frequency-division multiple access. In particular, we consider a heterogeneous network consisting of macrocell networks overlaid with cognitive small cells that opportunistically access the available spectrum. We focus on a regret-matching game approach, aiming at maximizing the total throughput of the small cell network subject to cross-tier interference and quality of service (QoS) constraints. The regret-matching game approach exploits a regret procedure to learn the optimal resource allocation strategy from the regrets of the actions of cognitive users. Furthermore, the regret-matching game approach is extended to the joint resource allocation and user admission control problem. Numerical results are presented to demonstrate the effectiveness of the proposed regre-matching approaches.


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