Sense-and-predict: Opportunistic MAC based on spatial interference correlation for cognitive radio networks

Jeemin Kim, Seung Woo Ko, Han Cha, Seong Lyun Kim

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

8 Citations (Scopus)

Abstract

Opportunity detection at secondary transmitters (TXs) is a key technique enabling cognitive radio (CR) networks. Such detection however cannot guarantee reliable communication at secondary receivers (RXs), especially when their association distance is long. To cope with the issue, this paper proposes a novel MAC called sense-and-predict (SaP), where each secondary TX decides whether to access or not based on the prediction of the interference level at RX. Firstly, we provide the spatial interference correlation in a probabilistic form using stochastic geometry, and utilize it to maximize the area spectral efficiency (ASE) for secondary networks while guaranteeing the service quality of primary networks. Through simulations and testbed experiments using USRP, SaP is shown to always achieve ASE improvement compared with the conventional TX based sensing.

Original languageEnglish
Title of host publication2017 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509028306
DOIs
Publication statusPublished - 2017 May 5
Event2017 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2017 - Baltimore, United States
Duration: 2017 Mar 62017 Mar 9

Publication series

Name2017 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2017

Other

Other2017 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2017
CountryUnited States
CityBaltimore
Period17/3/617/3/9

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'Sense-and-predict: Opportunistic MAC based on spatial interference correlation for cognitive radio networks'. Together they form a unique fingerprint.

  • Cite this

    Kim, J., Ko, S. W., Cha, H., & Kim, S. L. (2017). Sense-and-predict: Opportunistic MAC based on spatial interference correlation for cognitive radio networks. In 2017 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2017 [7920787] (2017 IEEE International Symposium on Dynamic Spectrum Access Networks, DySPAN 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DySPAN.2017.7920787