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|Title:||Resource allocation in satellite-based Internet of Things using pattern search method||Authors:||Li, Feng
|Keywords:||Engineering::Computer science and engineering||Issue Date:||2020||Source:||Li, F., Lam, K.-Y., Liu, X., & Wang, L. (2020). Resource allocation in satellite-based Internet of Things using pattern search method. IEEE Access, 8, 110908-110914. doi:10.1109/ACCESS.2020.3002834||Journal:||IEEE Access||Abstract:||The emergence of Internet of Things (IoT) and high throughput satellite communication networks enables the capability of anytime, anywhere environment monitoring and sensing. A key challenge of satellite-based IoT is to enhance spectrum and energy efficiency so as to meet the ever-increasing demand for satellite bandwidth and dynamic access of a massive number of IoT terminals. In this paper, we propose a novel power control algorithm for IoT terminals being deployed in satellite-based IoT systems where some terrestrial base station is available to acquire IoT devices' information as well as to perform resource management. We adopted the Poisson point process (PPP) theory to formulate the model for this power optimization problem. The PPP theory is applied to evaluate the distance distribution of random IoT devices in this satellite-based networks. Optimal power control scheme can be obtained by taking into consideration user distribution and signal interference plus noise ratio (SINR) demand for various IoT terminals. In addition, due to the complexity of the objective function of power control deduced by the PPP theory, we utilize the pattern search method to identify an optimal solution in global area. Furthermore, we provide numerical results from various perspectives including user rates and energy efficiency to testify the performances of our power proposal.||URI:||https://hdl.handle.net/10356/145631||ISSN:||2169-3536||DOI:||10.1109/ACCESS.2020.3002834||Rights:||© 2020 IEEE. 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:||SCSE Journal Articles|
Updated on Feb 28, 2021
Updated on Feb 28, 2021
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