Spectrum Matching in Licensed Spectrum Sharing
M. Majid Butt, Irene Macaluso, Eduard A. Jorswieck, Julie Bradford,, Nicola Marchetti, and Linda Doyle

TL;DR
This paper applies matching theory algorithms to optimize spectrum sharing in 5G networks, improving the alignment of spectrum provider and user preferences in both one-to-one and many-to-one scenarios.
Contribution
It introduces a matching theory-based framework for spectrum sharing that effectively resolves conflicting preferences between providers and users in 5G networks.
Findings
Enhanced preferred spectrum provider-user pairings.
Significant gains over uncoordinated spectrum allocation.
Effective in both one-to-one and many-to-one sharing scenarios.
Abstract
Spectrum sharing is one of the promising solutions to meet the spectrum demand in 5G networks that results from the emerging services like machine to machine and vehicle to infrastructure communication. The idea is to allow a set of entities access the spectrum whenever and wherever it is unused by the licensed users. In the proposed framework, different spectrum provider (SP) networks with surplus spectrum available may rank the operators requiring the spectrum, called spectrum users (SUs) hereafter, differently in terms of their preference to lease spectrum, based for example on target business market considerations of the SUs. Similarly, SUs rank SPs depending on a number of criteria, for example based on coverage and availability in a service area. Ideally, both SPs and SUs prefer to provide/get spectrum to/from the operator of their first choice, but this is not necessarily always…
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Taxonomy
TopicsCognitive Radio Networks and Spectrum Sensing · Advanced MIMO Systems Optimization · ICT Impact and Policies
