MAC Performance Analysis for Drive-Thru Internet Networks With Rayleigh Capture
In practical radio transmissions, channel capture is a dominating factor that affects wireless network performance. The capture effect can occur in wireless network when packets arrive with different powers. Packets with high power can effectively swamp low power packets, such that they are received...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2017-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/7936668/ |
| _version_ | 1818853692812558336 |
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| author | Baozhu Li Shanzhi Chen Gordon J. Sutton Yan Shi Ren Ping Liu |
| author_facet | Baozhu Li Shanzhi Chen Gordon J. Sutton Yan Shi Ren Ping Liu |
| author_sort | Baozhu Li |
| collection | DOAJ |
| description | In practical radio transmissions, channel capture is a dominating factor that affects wireless network performance. The capture effect can occur in wireless network when packets arrive with different powers. Packets with high power can effectively swamp low power packets, such that they are received successfully, when otherwise a collision would have occurred. We present a vehicular network performance-prediction model for a Rayleigh capture channel in Drive-thru Internet scenario. The model incorporates the capture effect into a 2-D Markov chain modeling the high-node mobility and distributed coordination function broadcast scheme. The performance-prediction model unveils the impacts of mobility velocity and number of vehicles on the throughput in a Rayleigh capture channel. We use a vehicular traffic flow model to predict vehicular movement on road by aggregating all vehicles into a flow. Simulation results confirm that our performance-prediction model accurately predicts the performance of traveling vehicles with Rayleigh capture channel in the Drive-thru Internet scenario. We demonstrate that using our performance-prediction model, we can obtain optimal contention window value, by which the best system throughput can be reached without wasting contention time. This is also proved by Anastasi et al. |
| first_indexed | 2024-12-19T07:40:52Z |
| format | Article |
| id | doaj.art-d4ced062534f46cf90ee39d1b50e2208 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T07:40:52Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d4ced062534f46cf90ee39d1b50e22082022-12-21T20:30:27ZengIEEEIEEE Access2169-35362017-01-015106491066110.1109/ACCESS.2017.27100527936668MAC Performance Analysis for Drive-Thru Internet Networks With Rayleigh CaptureBaozhu Li0https://orcid.org/0000-0002-4631-0317Shanzhi Chen1Gordon J. Sutton2Yan Shi3Ren Ping Liu4State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaState Key Laboratory of Wireless Mobile Communications, Datang Telecom Technology and Industry Group, China Academy of Telecommunications Technology, Beijing, ChinaGlobal Big Data Technologies Centre, University of Technology Sydney, Ultimo, NSW, AustraliaState Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, ChinaSchool of Computing and Communications, University of Technology Sydney, Ultimo, NSW, AustraliaIn practical radio transmissions, channel capture is a dominating factor that affects wireless network performance. The capture effect can occur in wireless network when packets arrive with different powers. Packets with high power can effectively swamp low power packets, such that they are received successfully, when otherwise a collision would have occurred. We present a vehicular network performance-prediction model for a Rayleigh capture channel in Drive-thru Internet scenario. The model incorporates the capture effect into a 2-D Markov chain modeling the high-node mobility and distributed coordination function broadcast scheme. The performance-prediction model unveils the impacts of mobility velocity and number of vehicles on the throughput in a Rayleigh capture channel. We use a vehicular traffic flow model to predict vehicular movement on road by aggregating all vehicles into a flow. Simulation results confirm that our performance-prediction model accurately predicts the performance of traveling vehicles with Rayleigh capture channel in the Drive-thru Internet scenario. We demonstrate that using our performance-prediction model, we can obtain optimal contention window value, by which the best system throughput can be reached without wasting contention time. This is also proved by Anastasi et al.https://ieeexplore.ieee.org/document/7936668/Capture effectperformance analysisMarkov chainDCFDrive-thru InternetVANETs |
| spellingShingle | Baozhu Li Shanzhi Chen Gordon J. Sutton Yan Shi Ren Ping Liu MAC Performance Analysis for Drive-Thru Internet Networks With Rayleigh Capture IEEE Access Capture effect performance analysis Markov chain DCF Drive-thru Internet VANETs |
| title | MAC Performance Analysis for Drive-Thru Internet Networks With Rayleigh Capture |
| title_full | MAC Performance Analysis for Drive-Thru Internet Networks With Rayleigh Capture |
| title_fullStr | MAC Performance Analysis for Drive-Thru Internet Networks With Rayleigh Capture |
| title_full_unstemmed | MAC Performance Analysis for Drive-Thru Internet Networks With Rayleigh Capture |
| title_short | MAC Performance Analysis for Drive-Thru Internet Networks With Rayleigh Capture |
| title_sort | mac performance analysis for drive thru internet networks with rayleigh capture |
| topic | Capture effect performance analysis Markov chain DCF Drive-thru Internet VANETs |
| url | https://ieeexplore.ieee.org/document/7936668/ |
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