Preprint Article Version 1 This version is not peer-reviewed

A Spectrum Sharing Framework for Intelligent Next Generation Wireless Networks

Version 1 : Received: 30 September 2018 / Approved: 1 October 2018 / Online: 1 October 2018 (15:26:40 CEST)
Version 2 : Received: 12 October 2018 / Approved: 15 October 2018 / Online: 15 October 2018 (12:15:23 CEST)

How to cite: de Figueiredo, F.A.P.; Mennes, R.; Jiao, X.; Liu, W.; Moerman, I. A Spectrum Sharing Framework for Intelligent Next Generation Wireless Networks. Preprints 2018, 2018100017 (doi: 10.20944/preprints201810.0017.v1). de Figueiredo, F.A.P.; Mennes, R.; Jiao, X.; Liu, W.; Moerman, I. A Spectrum Sharing Framework for Intelligent Next Generation Wireless Networks. Preprints 2018, 2018100017 (doi: 10.20944/preprints201810.0017.v1).

Abstract

The explosive emergence of wireless technologies and standards, covering licensed and unlicensed spectrum bands has triggered the appearance of a huge amount of wireless technologies, with many of them coexisting in the same band. Unfortunately, the wireless spectrum is a scarce resource, and the available frequency bands will not scale with the foreseen demand for new capacity. Certain parts of the spectrum, in particular the license-free ISM bands, are overcrowded, while other parts, mostly licensed bands, may be significantly underutilized. As such, there is a need to introduce more advanced techniques to access and share the wireless medium, either to improve the coordination within a given band, or to explore the possibilities of intelligently using unused spectrum in underutilized (e.g., licensed) bands. Therefore, in this paper, we present an open source SDR-based framework that can be employed to devise disruptive techniques to optimize the sub-optimal use of radio spectrum that exists today. Additionally, we describe three use cases where the proposed framework can be employed along with intelligent algorithms to achieve improved spectrum utilization.

Subject Areas

Next Generation Wireless Networks; Cognitive Radios; Collaborative Intelligent Radio Networks; Spectrum Sharing; Coexistence; Experimental Evaluation

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