Fourth Generation (4G) cellular technology Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) offers high data rate capabilities to mobile users; and, operators are trying to deliver a true mobile broadband experience over LTE networks. Mobile TV and Video on Demand (VoD) are expected to be the main revenue generators in the near future [36] and efficient video streaming over wireless is the key to enabling this. 3GPP recommends the use of H.264 baseline profiles for all video based services in Third Generation (3G) Universal Mobile Telecommunication System (UMTS) networks. However, LTE networks need to support mobile devices with different display resolution requirements like small resolution mobile phones and high resolution laptops. Scalable Video Coding (SVC) is required to achieve this goal. Feasibility study of SVC for LTE is one of the main agenda of 3GPP Release10. SVC enhances H.264 with a set of new profiles and encoding tools that may be used to produce scalable bit streams. Efficient adaptation methods for SVC video transmission over LTE networks are proposed in this thesis. Advantages of SVC over H.264 are analyzed using real time use cases of mobile video streaming. Further, we study the cross layer adaptation and scheduling schemes for delivering SVC video streams most efficiently to the users in LTE networks in unicast and multicast transmissions. We propose SVC based video streaming scheme for unicast and multicast transmissions in the downlink direction, with dynamic adaptations and a scheduling scheme based on channel quality information from users. Simulation results indicate improved video quality for more number of users in the coverage area and efficient spectrum usage with the proposed methods.
Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OOU-OLD./22657 |
Date | 19 March 2012 |
Creators | Radhakrishna, Rakesh |
Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
Language | English |
Detected Language | English |
Type | Thèse / Thesis |
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