DocumentCode :
177558
Title :
Matching theory for priority-based cell association in the downlink of wireless small cell networks
Author :
Semiari, Omid ; Saad, Walid ; Valentin, Stefan ; Bennis, Mehdi ; Maham, Behrouz
Author_Institution :
ECE Dept., Univ. of Miami, Coral Gables, FL, USA
fYear :
2014
fDate :
4-9 May 2014
Firstpage :
444
Lastpage :
448
Abstract :
The deployment of small cells, overlaid on existing cellular infrastructure, is seen as a key feature in next-generation cellular systems. In this paper, the problem of user association in the downlink of small cell networks (SCNs) is considered. The problem is formulated as a many-to-one matching game in which the users and SCBSs rank one another based on utility functions that account for both the achievable performance, in terms of rate and fairness to cell edge users, as captured by newly proposed priorities. To solve this game, a novel distributed algorithm that can reach a stable matching is proposed. Simulation results show that the proposed approach yields an average utility gain of up to 65% compared to a common association algorithm that is based on received signal strength. Compared to the classical deferred acceptance algorithm, the results also show a 40% utility gain and a more fair utility distribution among the users.
Keywords :
cellular radio; distributed algorithms; game theory; next generation networks; sensor placement; utility theory; wireless sensor networks; SCBS rank; acceptance algorithm; cell edge users; cellular infrastructure; distributed algorithm; many-to-one matching game; matching theory; next generation cellular system; priority-based cell association; received signal strength; small cell deployment; user association; utility distribution; utility functions; utility gain; wireless small cell network; Computer architecture; Downlink; Games; Interference; Microprocessors; Signal to noise ratio; Vectors; Cell association; Matching theory; Small cell networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICASSP.2014.6853635
Filename :
6853635
Link To Document :
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