Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/155224
Title: | Two-tier trading strategy design for spectrum allocation in heterogeneous cognitive radio networks | Authors: | Huang, Xiaowen Zhang, Wenjie Yang, Jingmin Yang, Liwei Yeo, Chai Kiat |
Keywords: | Engineering::Computer science and engineering | Issue Date: | 2020 | Source: | Huang, X., Zhang, W., Yang, J., Yang, L. & Yeo, C. K. (2020). Two-tier trading strategy design for spectrum allocation in heterogeneous cognitive radio networks. IET Communications, 14(16), 2759-2768. https://dx.doi.org/10.1049/iet-com.2019.1074 | Journal: | IET Communications | Abstract: | The heterogeneous network structure is a promising paradigm to improve the quality of service across the entire network. Nevertheless, such a structure is challenging due to the presence of multiple-tier secondary users (SUs). In this study, the authors investigated the effect of spectrum allocation in heterogeneous cognitive radio networks with a primary network and two-tier secondary networks, and proposed a two-tier spectrum trading strategy which includes two trading processes. In Process One, they model the spectrum trading as a monopoly market, where the primary spectrum owner (PO) acts as the monopolist and the first-tier secondary users (FSUs) act as the buyers. They design an optimal quality-price contract to maximise the utility of PO, and the FSUs will choose the spectrum with appropriate quality and price to enhance their satisfaction. In Process Two, spectrum trading is modelled as a multi-seller, multi-buyer market. The dynamic behaviour of second-tier SUs is studied using the theory of evolution game, while the competition among FSUs is analysed via a non-cooperative game where the Nash equilibrium is considered as the solution. The existences of the optimal contract, evolutionary equilibrium and Nash equilibrium are demonstrated in the performance evaluation. | URI: | https://hdl.handle.net/10356/155224 | ISSN: | 1751-8628 | DOI: | 10.1049/iet-com.2019.1074 | Rights: | © 2020 The Institution of Engineering and Technology. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | SCSE Journal Articles |
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