Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/138022
Title: Trading-based dynamic spectrum access and allocation in cognitive internet of things
Authors: Li, Feng
Lam, Kwok-Yan
Meng, Limin
Luo, Hao
Wang, Li
Keywords: Engineering::Computer science and engineering
Issue Date: 2019
Source: Li, F., Lam, K.-Y., Meng, L., Luo, H., & Wang, L. (2019). Trading-based dynamic spectrum access and allocation in cognitive internet of things. IEEE Access, 7, 125952-125959. doi:10.1109/ACCESS.2019.2937582
Journal: IEEE Access
Abstract: Next-generation mobile communication networks promise the support for vast number of IoT devices with strong demand for spectrum access. The cater for the continuous growth of IoT applications, one of the challenges to mobile communication network providers is to allow dynamic spectrum access to a gigantic number of densely distributed and low-power IoT networks. In this paper, a novel dynamic spectrum access method is proposed based on spectrum trading for distributed IoT devices. The notion of access benefit is introduced which is based on the purchased band number and modulation mode provided to the mobile user. In the proposed solution, IoT users aim achieve optimization of their spectrum access by ensuring that the spectrum price will not exceed the access benefits from the spectrum trading by solving the spectrum optimization function. Due to the complexity of optimization objective function, pattern search algorithm is utilized to complete the final spectrum allocation optimization. Numerical results are also provided to testify the performances of the proposed spectrum optimization method.
URI: https://hdl.handle.net/10356/138022
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2019.2937582
Rights: This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:RTP Journal Articles

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