An efficient contention-based reporting protocol for collaborative spectrum sensing

Jung Min Park, June Hwang, Seong Lyun Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In cognitive radio systems, the collaborative spectrum sensing has been introduced to improve the sensing reliability against the deep fading or shadowing. This collaboration causes an additional signaling overhead, and then may degrade the throughput of the cognitive radio system. In this paper, we suggest remedying this problem by adopting an efficient contention-based reporting protocol where less reliable sensors do not report. When each spectrum sensor determines whether or not to report based on its sensing result, the data fusion center cannot know which spectrum sensor reports. Therefore, our protocol is not based on the centralized scheduling, but the contention among reporting sensors. To evaluate the performance, we formulate the secondary throughput maximization problem considering the reporting overhead while satisfying the target detection probability not to generate a harmful interference on the primary system. Our results are encouraging in that as the number of collaborative sensors increases, the contention-based reporting protocol significantly outperforms the conventional time-division multiple access (TDMA) scheme.

Original languageEnglish
Title of host publicationProceedings of the 4th International Conference on Cognitive Radio and Advanced Spectrum Management, CogART'11
DOIs
Publication statusPublished - 2011
Event4th International Conference on Cognitive Radio and Advanced Spectrum Management, CogART'11 - Barcelona, Spain
Duration: 2011 Oct 262011 Oct 29

Publication series

NameACM International Conference Proceeding Series

Other

Other4th International Conference on Cognitive Radio and Advanced Spectrum Management, CogART'11
Country/TerritorySpain
CityBarcelona
Period11/10/2611/10/29

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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