Video Streaming over Cognitive Radio Networks
A Master of Science thesis in Electrical Engineering by Maram Wahed R. Helmy entitled, “Video Streaming over Cognitive Radio Networks”, submitted in July 2020. Thesis advisors is Mohamed S. Hassan and Mahmoud H. Ismail Ibrahim. Soft copy is available (Thesis, Approval Signatures, Completion Certific...
محفوظ في:
| المؤلف الرئيسي: | |
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| التنسيق: | doctoralThesis |
| منشور في: |
2020
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://hdl.handle.net/11073/19725 |
| الوسوم: |
إضافة وسم
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| _version_ | 1864513444521181184 |
|---|---|
| author | Helmy, Maram Wahed R. |
| author_facet | Helmy, Maram Wahed R. |
| author_role | author |
| dc.contributor.none.fl_str_mv | Hassan, Mohamed Ismail, Mahmoud H. |
| dc.creator.none.fl_str_mv | Helmy, Maram Wahed R. |
| dc.date.none.fl_str_mv | 2020-08-25T05:38:03Z 2020-08-25T05:38:03Z 2020-07 |
| dc.format.none.fl_str_mv | application/pdf application/pdf |
| dc.identifier.none.fl_str_mv | 35.232-2020.26 http://hdl.handle.net/11073/19725 |
| dc.language.none.fl_str_mv | en_US |
| dc.subject.none.fl_str_mv | Cognitive radio networks Video streaming Markov chain Method of moment Dynamic resource allocation CRN over LTE Scalable vidoe coding |
| dc.title.none.fl_str_mv | Video Streaming over Cognitive Radio Networks |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/doctoralThesis |
| description | A Master of Science thesis in Electrical Engineering by Maram Wahed R. Helmy entitled, “Video Streaming over Cognitive Radio Networks”, submitted in July 2020. Thesis advisors is Mohamed S. Hassan and Mahmoud H. Ismail Ibrahim. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form). |
| format | doctoralThesis |
| id | aus_2d5efe0127c1eda5b46f9f2b6fcda833 |
| identifier_str_mv | 35.232-2020.26 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/19725 |
| publishDate | 2020 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | Video Streaming over Cognitive Radio NetworksHelmy, Maram Wahed R.Cognitive radio networksVideo streamingMarkov chainMethod of momentDynamic resource allocationCRN over LTEScalable vidoe codingA Master of Science thesis in Electrical Engineering by Maram Wahed R. Helmy entitled, “Video Streaming over Cognitive Radio Networks”, submitted in July 2020. Thesis advisors is Mohamed S. Hassan and Mahmoud H. Ismail Ibrahim. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).The exponential increase in the demand for streaming video in wireless communication is obstructed by the problem of spectrum scarcity. In an effort to mitigate this problem, cognitive radio (CR) technology was proposed as a solution since it offers a great ad- vantage to unlicensed users, also known as secondary users (SUs), by allowing them to opportunistically access the licensed primary bands. However, it is more challenging to deliver video services over CR networks not only because of the intermittent availability of the PU channels but also due to the challenges stemming from wireless channels and the quality requirements of the videos. In this work, several frameworks are proposed to stream scalable video sequences from a base station to multiple SUs over CR networks. One approach is a moments matching-based approach that enabled us to quantify the total amount of data that can be provided by the available PU channels. Specifically, a closed-from approximation for the distribution of the total amount of data available for SU over all the available PU channels during any arbitrary interval of time was obtained. The correctness of the obtained closed-form approximation is verified using simulations and numerical investigations. Another approach is employing the CR network over long-term evolution (LTE) standard platform. The objective of this work is to guarantee continuous playback at the SUs end with acceptable perceptual quality. To achieve this objective, different resource allocation schemes are introduced to adaptively assign the available radio channels to SUs while taking into considerations the quality of their assigned channels as well as their buffer occupancies. In addition, a streaming algorithm is introduced to guarantee the delivery of scalable video frames, with base and enhancement layers, within the delay constraints with priority given to the base-layer frames to guarantee the continuity of video playback. Furthermore, adaptive modulation is used based on the channel state information (CSI) as fed-back by SUs. The performance of the proposed schemes is evaluated through extensive evaluation and Monte-Carlo simulations in Matlab.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE)Hassan, MohamedIsmail, Mahmoud H.2020-08-25T05:38:03Z2020-08-25T05:38:03Z2020-07info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdfapplication/pdf35.232-2020.26http://hdl.handle.net/11073/19725en_USoai:repository.aus.edu:11073/197252025-06-26T12:35:04Z |
| spellingShingle | Video Streaming over Cognitive Radio Networks Helmy, Maram Wahed R. Cognitive radio networks Video streaming Markov chain Method of moment Dynamic resource allocation CRN over LTE Scalable vidoe coding |
| status_str | publishedVersion |
| title | Video Streaming over Cognitive Radio Networks |
| title_full | Video Streaming over Cognitive Radio Networks |
| title_fullStr | Video Streaming over Cognitive Radio Networks |
| title_full_unstemmed | Video Streaming over Cognitive Radio Networks |
| title_short | Video Streaming over Cognitive Radio Networks |
| title_sort | Video Streaming over Cognitive Radio Networks |
| topic | Cognitive radio networks Video streaming Markov chain Method of moment Dynamic resource allocation CRN over LTE Scalable vidoe coding |
| url | http://hdl.handle.net/11073/19725 |