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http://dx.doi.org/10.3837/tiis.2017.03.005

Spectrum allocation strategy for heterogeneous wireless service based on bidding game  

Cao, Jing (School of Computer Science and Engineering, Northwestern Polytechnical University)
Wu, Junsheng (School of Software and Microelectronics, Northwestern Polytechnical University)
Yang, Wenchao (School of Computer Science and Engineering, Northwestern Polytechnical University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.11, no.3, 2017 , pp. 1336-1356 More about this Journal
Abstract
The spectrum scarcity crisis has resulted in a shortage of resources for many emerging wireless services, and research on dynamic spectrum management has been used to solve this problem. Game theory can allocate resources to users in an economic way through market competition. In this paper, we propose a bidding game-based spectrum allocation mechanism in cognitive radio network. In our framework, primary networks provide heterogeneous wireless service and different numbers of channels, while secondary users have diverse bandwidth demands for transmission. Considering the features of traffic and QoS demands, we design a weighted interference graph-based grouping algorithm to divide users into several groups and construct the non-interference user-set in the first step. In the second step, we propose the dynamic bidding game-based spectrum allocation strategy; we analyze both buyer's and seller's revenue and determine the best allocation strategy. We also prove that our mechanism can achieve balanced pricing schema in competition. Theoretical and simulation results show that our strategy provides a feasible solution to improve spectrum utilization, can maximize overall utility and guarantee users' individual rationality.
Keywords
cognitive radio network; dynamic game; heterogeneous service; Nash Equilibrium; weighted interference graph;
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