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Spectrum Sharing Between Wireless Networks

Authors: Leonard H. Grokop; David N. C. Tse;

Spectrum Sharing Between Wireless Networks

Abstract

We consider the problem of two wireless networks operating on the same (presumably unlicensed) frequency band. Pairs within a given network cooperate to schedule transmissions, but between networks there is competition for spectrum. To make the problem tractable, we assume transmissions are scheduled according to a random access protocol where each network chooses an access probability for its users. A game between the two networks is defined. We characterize the Nash Equilibrium behavior of the system. Three regimes are identified; one in which both networks simultaneously schedule all transmissions; one in which the denser network schedules all transmissions and the sparser only schedules a fraction; and one in which both networks schedule only a fraction of their transmissions. The regime of operation depends on the pathloss exponent $α$, the latter regime being desirable, but attainable only for $α>4$. This suggests that in certain environments, rival wireless networks may end up naturally cooperating. To substantiate our analytical results, we simulate a system where networks iteratively optimize their access probabilities in a greedy manner. We also discuss a distributed scheduling protocol that employs carrier sensing, and demonstrate via simulations, that again a near cooperative equilibrium exists for sufficiently large $α$.

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FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT)

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
21
Average
Top 10%
Top 10%
Green