Theoretic study of the voice traffic capacity over cognitive radio networks
This project report presents the voice traffic capacity analysis over a Cognitive Radio environment. Investigations are performed to determine the traffic capacity for cognitive unlicensed users in a simulation system with presence of licensed users. Licensed users are people who have preemptive pri...
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2012
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sg-ntu-dr.10356-485152023-03-03T20:32:54Z Theoretic study of the voice traffic capacity over cognitive radio networks Tan, Cindy Shi Yan. School of Computer Engineering Wang Ping DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks This project report presents the voice traffic capacity analysis over a Cognitive Radio environment. Investigations are performed to determine the traffic capacity for cognitive unlicensed users in a simulation system with presence of licensed users. Licensed users are people who have preemptive priority. Unlicensed Users are the opportunistic people who access the network channel without any interference. Each of the unlicensed users equipped themselves with a spectrum sensing cognitive radio ability to detect unused radio frequency spectrum. For fairness, the investigations are done under different circumstances such as channel rate and primary activity. An analytical simulation model is implemented to analyze the licensed users’ voice traffic capacity. Sensing the availability of the channel is part of the simulation movement. The concept of Markov Chain Model simulates the sensing ability and the algorithm of Round-Robin Scheduler simulates the queue of the secondary users. In this project, voice codec such as G.711, G.723.1, G.726, G.728 and G.729 are used. Bachelor of Engineering (Computer Engineering) 2012-04-25T06:51:24Z 2012-04-25T06:51:24Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/48515 en Nanyang Technological University 32 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computer systems organization::Computer-communication networks Tan, Cindy Shi Yan. Theoretic study of the voice traffic capacity over cognitive radio networks |
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This project report presents the voice traffic capacity analysis over a Cognitive Radio environment. Investigations are performed to determine the traffic capacity for cognitive unlicensed users in a simulation system with presence of licensed users. Licensed users are people who have preemptive priority. Unlicensed Users are the opportunistic people who access the network channel without any interference. Each of the unlicensed users equipped themselves with a spectrum sensing cognitive radio ability to detect unused radio frequency spectrum.
For fairness, the investigations are done under different circumstances such as channel rate and primary activity. An analytical simulation model is implemented to analyze the licensed users’ voice traffic capacity. Sensing the availability of the channel is part of the simulation movement. The concept of Markov Chain Model simulates the sensing ability and the algorithm of Round-Robin Scheduler simulates the queue of the secondary users. In this project, voice codec such as G.711, G.723.1, G.726, G.728 and G.729 are used. |
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School of Computer Engineering |
author_facet |
School of Computer Engineering Tan, Cindy Shi Yan. |
format |
Final Year Project |
author |
Tan, Cindy Shi Yan. |
author_sort |
Tan, Cindy Shi Yan. |
title |
Theoretic study of the voice traffic capacity over cognitive radio networks |
title_short |
Theoretic study of the voice traffic capacity over cognitive radio networks |
title_full |
Theoretic study of the voice traffic capacity over cognitive radio networks |
title_fullStr |
Theoretic study of the voice traffic capacity over cognitive radio networks |
title_full_unstemmed |
Theoretic study of the voice traffic capacity over cognitive radio networks |
title_sort |
theoretic study of the voice traffic capacity over cognitive radio networks |
publishDate |
2012 |
url |
http://hdl.handle.net/10356/48515 |
_version_ |
1759855434611556352 |