Abstract
As the use and scale of wireless sensor networks has grown, the lack of transmission spectrum has become a key factor affecting wireless sensor network quality of service. An effective solution is to collect unused spectrum from primary users (i.e. licensed users) and use that spectrum for wireless sensor networks. In this article, for a cognitive radio-based wireless sensor network, a spectrum sharing strategy between primary users and clusters is proposed. First, as a secondary user (i.e. an unlicensed user), the base station plays a Bertrand game with the monopolists (the primary users) to gain spectrum access on behalf of the clusters. Then, the base station allocates the spectrum band to the cluster heads using the ant colony optimization–based multiple knapsack problem. After obtaining the spectrum, each cluster head programs its nodes’ spectrum according to a timing sequence. Simulation results show that the Bertrand game model is a good choice for determining spectrum pricing and that the ant colony optimization–based multiple knapsack problem algorithm is an efficient way to allocate spectrum dynamically.
Highlights
As wireless communication technology develops, wireless sensor network (WSN) applications are becoming increasingly widespread and application environments have become increasingly complicated; the existing spectrum sharing scheme fails to meet WSN spectrum demand in many cases
We take a centralized WSN as an example, where the base station acts as a middleman between the primary users and the clusters
To find the solution of the spectrum pricing game, that is, the Nash equilibrium (NE), we quantify the utility of the primary user and the base station according to the utility function used in Singh and Vives.[27]
Summary
As wireless communication technology develops, wireless sensor network (WSN) applications are becoming increasingly widespread and application environments have become increasingly complicated; the existing spectrum sharing scheme fails to meet WSN spectrum demand in many cases. The cluster head assigns bandwidth to nodes while considering the timing sequence In this manner, we can achieve a spectrum pricing and dynamic allocation model. The major contributions of this article are as follows: Most existing studies focus on multiple sellers selling spectrum to one buyer or one seller selling spectrum to multiple buyers.[11,12] This article solves the problem of multiple sellers selling spectrum to multiple buyers in WSN using game theory and the MKP algorithm It improves the practicality of the spectrum sharing model by considering the importance and urgency of a node’s information and imposing a maximum waiting period for a node. Section ‘‘Performance evaluation’’ presents a quantitative performance analysis, and section ‘‘Conclusion and future work’’ summarizes the work and proposes future work
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