Journal of Shandong University(Engineering Science) ›› 2025, Vol. 55 ›› Issue (3): 100-110.doi: 10.6040/j.issn.1672-3961.0.2024.067

• Machine Learning & Data Mining • Previous Articles     Next Articles

A dynamic pricing spectrum strategy responded customized requirements in heterogeneous cognitive radio-based Internet of Things

WANG Shi, XU Xiaohui*, ZHU Xiaoying, JIANG Han, CAO Dayan   

  1. WANG Shi, XU Xiaohui*, ZHU Xiaoying, JIANG Han, CAO Dayan(School of Electronic and Information Engineering, Liaoning Technical University, Huludao 125105, Liaoning, China
  • Published:2025-06-05

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Abstract: To address the resource allocation problem in multi-user multi-channel heterogeneous cognitive radio-based Internet of Things(CR-IoT)network under the context of spectrum trading, a mathematical analysis method for communication performance was designed, which was developed to meet the need for evaluating the cost-effectiveness of spectrum pricing for multi-service secondary users(SUs)and was applicable to various network environments and operator-specific spectrum allocation strategies. Closed-form expressions for spectrum transaction costs and performance metrics, such as throughput and packet loss rate, were derived. The cost and communication performance of SUs were analyzed independently. A dynamic pricing strategy with customized performance requirements for users was proposed to achieve multi-objective optimization of spectrum trading costs and communication performance. Simulation results demonstrated that the proposed dynamic pricing strategy effectively ensured SUs' quality of service, outperforming fixed pricing strategies and demand-based dynamic pricing strategies.

Key words: cognitive radio-Internet of Things, resource allocation, dynamic spectrum sharing, dynamic spectrum trading, performance evaluation

CLC Number: 

  • TP391.4
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