Abstract
The opportunistic spectrum access with dynamic users and channel bonding technology in mesh networks is studied in this paper. Different from the traditional static and fixed transmitting model, nodes would change their states between active and silent, due to their traffic demand. Also, the channel bonding technology, which mitigates interference and improves throughput significantly, is employed in this paper. The interference mitigation problem with channel bonding is modeled as a distributed and non-cooperative game. We proved it to be an exact potential game. Based on the good property of the potential game, it guarantees the existence of at least one pure Nash equilibrium (NE). Due to the potential function is formulated as the aggregate interference of the network, the final optimal NE point also achieves the minimization of the system’s total interference. A multiple-agent learning algorithm is designed to approach the NE points. Compared with other algorithms, simulation results show that the modified algorithm achieves a lower interference performance, and the channel bonding contributes to the throughput performance.
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Notes
- 1.
For the without channel bonding situations, to make the total power same with the channel bonding situations, the power on each channel is set as 0.2Â W.
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Acknowledgment
This work was supported in part by the Natural Science Foundation for Distinguished Young Scholars of Jiangsu Province under Grant BK20160034, in part by the National Science Foundation of China under Grant 61631020, Grant 61401508, and Grant 61671473, and in part by the Open Research Foundation of Science and Technology on Communication Networks Laboratory.
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Pan, C., Cheng, Y., Yang, Z., Zhang, Y. (2018). Dynamic Opportunistic Spectrum Access with Channel Bonding in Mesh Networks: A Game-Theoretic Approach. In: Meng, L., Zhang, Y. (eds) Machine Learning and Intelligent Communications. MLICOM 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 251. Springer, Cham. https://doi.org/10.1007/978-3-030-00557-3_38
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