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Supporting Real-Time Data Transmissions in Cognitive Radio Networks Using Queue Shifting Mechanism

Supporting Real-Time Data Transmissions in Cognitive Radio Networks Using Queue Shifting Mechanism

B. Seetha Ramanjaneyulu, K. Annapurna
Copyright: © 2021 |Volume: 12 |Issue: 1 |Pages: 18
ISSN: 1947-3176|EISSN: 1947-3184|EISBN13: 9781799861645|DOI: 10.4018/IJERTCS.20210101.oa1
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MLA

Ramanjaneyulu, B. Seetha, and K. Annapurna. "Supporting Real-Time Data Transmissions in Cognitive Radio Networks Using Queue Shifting Mechanism." IJERTCS vol.12, no.1 2021: pp.1-18. http://doi.org/10.4018/IJERTCS.20210101.oa1

APA

Ramanjaneyulu, B. S. & Annapurna, K. (2021). Supporting Real-Time Data Transmissions in Cognitive Radio Networks Using Queue Shifting Mechanism. International Journal of Embedded and Real-Time Communication Systems (IJERTCS), 12(1), 1-18. http://doi.org/10.4018/IJERTCS.20210101.oa1

Chicago

Ramanjaneyulu, B. Seetha, and K. Annapurna. "Supporting Real-Time Data Transmissions in Cognitive Radio Networks Using Queue Shifting Mechanism," International Journal of Embedded and Real-Time Communication Systems (IJERTCS) 12, no.1: 1-18. http://doi.org/10.4018/IJERTCS.20210101.oa1

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Abstract

As cognitive radio networks are conceptualized to make use of the opportunistic spectrum access, the users of these networks may face problems in satisfying their quality of service (QoS) requirements. Some services of users like real-time audio and video which cannot tolerate inter-packet delays will be affected more due to this. The problem occurs due to the non-availability of channels to these applications at some instants. This problem can be addressed if the available channels are judiciously distributed among the competing users. One such mechanism that dynamically allocates the competing users to multiple queues, and shifting the users to higher-level queues as the time elapses is introduced in this work. This is found to help the users of cognitive radio networks to communicate reasonably well even when fewer channels are available for opportunistic use. Results are indicated in terms of blocking probabilities of real-time data. Markov chain-based analysis and discrete event simulation studies are carried out.