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Wireless Communications and Mobile Computing
Volume 2018 (2018), Article ID 4092681, 17 pages
Research Article

Coexistence of Cognitive Small Cell and WiFi System: A Traffic Balancing Dual-Access Resource Allocation Scheme

Chongqing Key Laboratory of Mobile Communication Technology, Chongqing University of Posts and Telecommunications, Chongqing, China

Correspondence should be addressed to Yangyang Li

Received 26 May 2017; Revised 17 November 2017; Accepted 11 December 2017; Published 8 January 2018

Academic Editor: Yang-Seok Choi

Copyright © 2018 Xiaoge Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We consider a holistic approach for dual-access cognitive small cell (DACS) networks, which uses the LTE air interface in both licensed and unlicensed bands. In the licensed band, we consider a sensing-based power allocation scheme to maximize the sum data rate of DACSs by jointly optimizing the cell selection, the sensing operation, and the power allocation under the interference constraint to macrocell users. Due to intercell interference and the integer nature of the cell selection, the resulting optimization problems lead to a nonconvex integer programming. We reformulate the problem to a nonconvex power allocation game and find the relaxed equilibria, quasi-Nash equilibrium. Furthermore, in order to guarantee the fairness of the whole system, we propose a dynamic satisfaction-based dual-band traffic balancing (SDTB) algorithm over licensed and unlicensed bands for DACSs which aims at maximizing the overall satisfaction of the system. We obtain the optimal transmission time in the unlicensed band to ensure the proportional fair coexistence with WiFi while guaranteeing the traffic balancing of DACSs. Simulation results demonstrate that the SDTB algorithm could achieve a considerable performance improvement relative to the schemes in literature, while providing a tradeoff between maximizing the total data rate and achieving better fairness among networks.