The myopic solution of the Multi-Armed Bandit Compressive Spectrum Sensing problem

Saeed Bagheri, Anna Scaglione

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

Abstract

In this paper we formulate a Multi-Armed Bandit Compressive Spectrum Sensing (MAB-CSS) problem, in which a Cognitive Receiver (CR) decides dynamically how to best sense N sub-channels states, that switch from being occupied to being available as independent and statistically identical Markov chains. We assume that the CR is endowed with K CSS samplers each sensing an arbitrary mixture of the N signals in the sub-channels, and upon deciding what channels are available, it collects an equal reward from each channel unoccupied that is sensed. The MAB-CSS problem accounts for the ability of the CR of sweeping a large spectrum and being able to reconstruct the exact support of the N channels occupancy pattern, as long as the latter is sufficiently sparse. This is a generalization of the typical model in which the CR can sense K out of the N sub-channels. In choosing the compressive sensing strategy, the CR needs to consider how to gather the most informative statistics on the spectrum while not exceeding the limits beyond which the occupancy is no longer identifiable. In this work, we study a simplified and noiseless discrete sensing model and establish the structure of the optimum MAB-CSS myopic policy.

Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7258-7262
Number of pages5
ISBN (Print)9781479928927
DOIs
StatePublished - 2014
Externally publishedYes
Event2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
Duration: May 4 2014May 9 2014

Other

Other2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
CountryItaly
CityFlorence
Period5/4/145/9/14

Fingerprint

Markov processes
Switches
Statistics

Keywords

  • cognitive radio
  • compressive sensing
  • multi-channel sensing
  • myopic policy
  • Opportunistic access

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

Cite this

Bagheri, S., & Scaglione, A. (2014). The myopic solution of the Multi-Armed Bandit Compressive Spectrum Sensing problem. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (pp. 7258-7262). [6855009] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2014.6855009

The myopic solution of the Multi-Armed Bandit Compressive Spectrum Sensing problem. / Bagheri, Saeed; Scaglione, Anna.

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. p. 7258-7262 6855009.

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

Bagheri, S & Scaglione, A 2014, The myopic solution of the Multi-Armed Bandit Compressive Spectrum Sensing problem. in ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings., 6855009, Institute of Electrical and Electronics Engineers Inc., pp. 7258-7262, 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, Florence, Italy, 5/4/14. https://doi.org/10.1109/ICASSP.2014.6855009
Bagheri S, Scaglione A. The myopic solution of the Multi-Armed Bandit Compressive Spectrum Sensing problem. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. p. 7258-7262. 6855009 https://doi.org/10.1109/ICASSP.2014.6855009
Bagheri, Saeed ; Scaglione, Anna. / The myopic solution of the Multi-Armed Bandit Compressive Spectrum Sensing problem. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 7258-7262
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