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Title: Large-Scale Dynamic Spectrum Access with IEEE 1900.5.2 Spectrum Consumption Models
Next generation wireless services and applications, including Augmented Reality, Internet-of-Things, and Smart- Cities, will increasingly rely on Dynamic Spectrum Access (DSA) methods that can manage spectrum resources rapidly and efficiently. Advances in regulatory policies, standardization, networking, and wireless technology are enabling DSA methods on a more granular basis in terms of time, frequency, and geographical location which are key for the operation of 5G and beyond-5G networks. In this context, this paper proposes a novel DSA algorithm that leverages IEEE 1900.5.2 Spectrum Consumption Models (SCMs) which offer a mechanism for RF devices to: (i) “announce” or “declare” their intention to use the spectrum and their needs in terms of interference protection; and (ii) determine compatibility (i.e., non-interference) with existing devices. In this paper, we develop an SCM-based DSA algorithm for spectrum deconfliction in large-scale wireless network environments and evaluate this algorithm in terms of computation time, efficiency of spectrum allocation, and number of device reconfigurations due to interference using a custom simulation platform. The results demonstrate the benefits of using SCMs and their capabilities to perform fine grained spectrum assignments in dynamic and dense communication environments.  more » « less
Award ID(s):
2029295 2232459
NSF-PAR ID:
10457283
Author(s) / Creator(s):
; ; ; ; ; ; ;
Date Published:
Journal Name:
in Proc. IEEE WCNC’23, Mar. 2023
Page Range / eLocation ID:
1 to 6
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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