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Dynamic spectrum access as a service

Authors: Chunsheng Xin; Min Song 0002;

Dynamic spectrum access as a service

Abstract

Recently there have been various studies on dynamic spectrum access (DSA) approaches, e.g., opportunistic spectrum access and spectrum auction, to address spectrum scarcity and inefficient spectrum utilization caused by today's static spectrum allocation policy. In this paper, we propose a new approach, demand spectrum access as a service (DSAS), to achieve DSA. We consider a spectrum service provider that dynamically offers spectrum service to users such that the users can set up dynamic topologies for data communication, e.g., transport a bulk data flow between two nodes, or carry out a video conference among a set of nodes. Through DSAS, the precious spectrum is dynamically shared and efficiently utilized by users. In this paper, we consider two spectrum services, SameBand and DiffBand, and develop efficient online algorithms to allocate spectrum for the two services, so that users can set up dynamic topologies. The performance of the algorithms is evaluated through both analysis and simulation.

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Powered by OpenAIRE graph
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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!
5
Average
Top 10%
Average
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