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Translated title of the contribution: Average throughput performance of greedy policy in cognitive radio enabled vehicular networks

Omer Melih Gul*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

We consider a cognitive radio enabled vehicular network with many primary users and a multi-channel secondary user(SU). A channel is allocated to each primary user for data transmission. SU is data backlogged and selects channels for transmission. SU knows neither channel states nor statistics of channel evolution processes. If SU senses that a good-state selected channel is in good state,it sends data over that channel at that time. Otherwise,SU do not use that channel and make another selection in the next time. Under average throughput criteria,it is shown that greedy policy is optimal for certain fading channel evolution processes although it is generally suboptimal.

Translated title of the contributionAverage throughput performance of greedy policy in cognitive radio enabled vehicular networks
Original languageTurkish
Title of host publicationSIU 2021 - 29th IEEE Conference on Signal Processing and Communications Applications, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665436496
DOIs
Publication statusPublished - 9 Jun 2021
Externally publishedYes
Event29th IEEE Conference on Signal Processing and Communications Applications, SIU 2021 - Virtual, Istanbul, Turkey
Duration: 9 Jun 202111 Jun 2021

Publication series

NameSIU 2021 - 29th IEEE Conference on Signal Processing and Communications Applications, Proceedings

Conference

Conference29th IEEE Conference on Signal Processing and Communications Applications, SIU 2021
Country/TerritoryTurkey
CityVirtual, Istanbul
Period9/06/2111/06/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

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