Clustering transmission opportunity length (CTOL) model over cognitive radio network

This paper investigated the throughput performance of a secondary user (SU) for a random primary user (PU) activity in a realistic experimental model. This paper proposed a sensing and frame duration of the SU to maximize the SU throughput under the collision probability constraint. The throughput o...

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Main Authors: Mohamad, Mas Haslinda, Sali, Aduwati, Hashim, Fazirulhisyam, Nordin, Rosdiadee, Takyu, Osamu
Format: Article
Language:English
Published: MDPI 2018
Online Access:http://psasir.upm.edu.my/id/eprint/15362/
http://psasir.upm.edu.my/id/eprint/15362/1/15362.pdf
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author Mohamad, Mas Haslinda
Sali, Aduwati
Hashim, Fazirulhisyam
Nordin, Rosdiadee
Takyu, Osamu
author_facet Mohamad, Mas Haslinda
Sali, Aduwati
Hashim, Fazirulhisyam
Nordin, Rosdiadee
Takyu, Osamu
author_sort Mohamad, Mas Haslinda
building UPM Institutional Repository
collection Online Access
description This paper investigated the throughput performance of a secondary user (SU) for a random primary user (PU) activity in a realistic experimental model. This paper proposed a sensing and frame duration of the SU to maximize the SU throughput under the collision probability constraint. The throughput of the SU and the probability of collisions depend on the pattern of PU activities. The pattern of PU activity was obtained and modelled from the experimental data that measure the wireless local area network (WLAN) environment. The WLAN signal has detected the transmission opportunity length (TOL) which was analyzed and clustered into large and small durations in the CTOL model. The performance of the SU is then analyzed and compared with static and dynamic PU models. The results showed that the SU throughput in the CTOL model was higher than the static and dynamic models by almost 45% and 12.2% respectively. Furthermore, the probability of collisions in the network and the SU throughput were influenced by the value of the minimum contention window and the maximum back-off stage. The simulation results revealed that the higher contention window had worsened the SU throughput even though the channel has a higher number of TOLs.
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spelling upm-153622019-07-08T07:30:32Z http://psasir.upm.edu.my/id/eprint/15362/ Clustering transmission opportunity length (CTOL) model over cognitive radio network Mohamad, Mas Haslinda Sali, Aduwati Hashim, Fazirulhisyam Nordin, Rosdiadee Takyu, Osamu This paper investigated the throughput performance of a secondary user (SU) for a random primary user (PU) activity in a realistic experimental model. This paper proposed a sensing and frame duration of the SU to maximize the SU throughput under the collision probability constraint. The throughput of the SU and the probability of collisions depend on the pattern of PU activities. The pattern of PU activity was obtained and modelled from the experimental data that measure the wireless local area network (WLAN) environment. The WLAN signal has detected the transmission opportunity length (TOL) which was analyzed and clustered into large and small durations in the CTOL model. The performance of the SU is then analyzed and compared with static and dynamic PU models. The results showed that the SU throughput in the CTOL model was higher than the static and dynamic models by almost 45% and 12.2% respectively. Furthermore, the probability of collisions in the network and the SU throughput were influenced by the value of the minimum contention window and the maximum back-off stage. The simulation results revealed that the higher contention window had worsened the SU throughput even though the channel has a higher number of TOLs. MDPI 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/15362/1/15362.pdf Mohamad, Mas Haslinda and Sali, Aduwati and Hashim, Fazirulhisyam and Nordin, Rosdiadee and Takyu, Osamu (2018) Clustering transmission opportunity length (CTOL) model over cognitive radio network. Sensors, 18 (12). art. no. 4351. pp. 1-15. ISSN 1424-8220 https://www.mdpi.com/1424-8220/18/12/4351 10.3390/s18124351
spellingShingle Mohamad, Mas Haslinda
Sali, Aduwati
Hashim, Fazirulhisyam
Nordin, Rosdiadee
Takyu, Osamu
Clustering transmission opportunity length (CTOL) model over cognitive radio network
title Clustering transmission opportunity length (CTOL) model over cognitive radio network
title_full Clustering transmission opportunity length (CTOL) model over cognitive radio network
title_fullStr Clustering transmission opportunity length (CTOL) model over cognitive radio network
title_full_unstemmed Clustering transmission opportunity length (CTOL) model over cognitive radio network
title_short Clustering transmission opportunity length (CTOL) model over cognitive radio network
title_sort clustering transmission opportunity length (ctol) model over cognitive radio network
url http://psasir.upm.edu.my/id/eprint/15362/
http://psasir.upm.edu.my/id/eprint/15362/
http://psasir.upm.edu.my/id/eprint/15362/
http://psasir.upm.edu.my/id/eprint/15362/1/15362.pdf