  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 possible due to
conflicting preferences. We apply matching theory algorithms with the aim to
resolve the conflicting preferences of the SPs and SUs and quantify the effect
of the proposed matching theory approach on establishing preferred (spectrum)
provider-user network pairs. We discuss both one-to-one and many-to-one
spectrum sharing scenarios and evaluate the performance using Monte Carlo
simulations. The results show that comprehensive gains in terms of preferred
matching of the provider-user network pairs can be achieved by applying
matching theory for spectrum sharing as compared to uncoordinated spectrum
allocation of the available spectrum to the SUs.
