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Cross-Layer Prioritized Video Transm...

Kambhatla, Kashyap Kodanda Ram.

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Cross-Layer Prioritized Video Transmission: Adaptive Packetization, FEC Protection and Scheduling Methods.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Cross-Layer Prioritized Video Transmission: Adaptive Packetization, FEC Protection and Scheduling Methods./
作者:	Kambhatla, Kashyap Kodanda Ram.
面頁冊數:	133 p.
附註:	Source: Dissertation Abstracts International, Volume: 75-09(E), Section: B.
Contained By:	Dissertation Abstracts International75-09B(E).
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3621589
ISBN:	9781303927874

Cross-Layer Prioritized Video Transmission: Adaptive Packetization, FEC Protection and Scheduling Methods.
Kambhatla, Kashyap Kodanda Ram.

Cross-Layer Prioritized Video Transmission: Adaptive Packetization, FEC Protection and Scheduling Methods. - 133 p.

Source: Dissertation Abstracts International, Volume: 75-09(E), Section: B.

Thesis (Ph.D.)--University of California, San Diego, 2014.

This item must not be sold to any third party vendors.

The quality of H.264/AVC compressed video delivery over time-varying and error-prone wireless channels is affected by packet losses. To support quality of service (QoS) for video delivery over wireless networks cross-layer schemes have been discussed in the literature. We introduce a cross-layer priority-aware packet fragmentation scheme at the medium access control (MAC) layer to enhance the quality of pre-encoded H.264/AVC compressed bitstreams over bit-rate limited error-prone links in wireless networks. Larger fragments are more likely to be in error but smaller fragments require more overhead. The H.264 slices are classified in four priorities at the encoder based on their cumulative mean square error (CMSE) contribution towards the received video quality. The slices of a priority class in each frame are aggregated into video packets of corresponding priority at the application (APP) layer. We derive the optimal fragment size for each priority class which achieves the maximum expected weighted goodput at different encoded video bit rates, slice sizes and bit error rates. Priority-aware packet fragmentation invokes slice discard in the buffer due to channel bit rate constraints on allocating fragment header bits. We propose a slice discard scheme using frame importance and slice CMSE contribution to control error propagation effects. Packet fragmentation is then extended to slice fragmentation by modifying the conventional H.264 decoder to handle partial slice decoding. Priority-aware slice fragmentation combined with the proposed slice discard scheme provides considerable peak signal-to-noise ratio (PSNR) and video quality metric gains as compared to priority-agnostic fragmentation.

ISBN: 9781303927874Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Cross-Layer Prioritized Video Transmission: Adaptive Packetization, FEC Protection and Scheduling Methods.
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245 1 0 $a Cross-Layer Prioritized Video Transmission: Adaptive Packetization, FEC Protection and Scheduling Methods.
300 $a 133 p.
500 $a Source: Dissertation Abstracts International, Volume: 75-09(E), Section: B.
500 $a Advisers: Pamela C. Cosman; Sunil Kumar.
502 $a Thesis (Ph.D.)--University of California, San Diego, 2014.
506 $a This item must not be sold to any third party vendors.
520 $a The quality of H.264/AVC compressed video delivery over time-varying and error-prone wireless channels is affected by packet losses. To support quality of service (QoS) for video delivery over wireless networks cross-layer schemes have been discussed in the literature. We introduce a cross-layer priority-aware packet fragmentation scheme at the medium access control (MAC) layer to enhance the quality of pre-encoded H.264/AVC compressed bitstreams over bit-rate limited error-prone links in wireless networks. Larger fragments are more likely to be in error but smaller fragments require more overhead. The H.264 slices are classified in four priorities at the encoder based on their cumulative mean square error (CMSE) contribution towards the received video quality. The slices of a priority class in each frame are aggregated into video packets of corresponding priority at the application (APP) layer. We derive the optimal fragment size for each priority class which achieves the maximum expected weighted goodput at different encoded video bit rates, slice sizes and bit error rates. Priority-aware packet fragmentation invokes slice discard in the buffer due to channel bit rate constraints on allocating fragment header bits. We propose a slice discard scheme using frame importance and slice CMSE contribution to control error propagation effects. Packet fragmentation is then extended to slice fragmentation by modifying the conventional H.264 decoder to handle partial slice decoding. Priority-aware slice fragmentation combined with the proposed slice discard scheme provides considerable peak signal-to-noise ratio (PSNR) and video quality metric gains as compared to priority-agnostic fragmentation.
520 $a Distortion due to channel errors can be alleviated by assigning stronger channel code rates, at the cost of reduced rate for source coding. Besides MAC layer fragmentation, aggregating H.264/AVC slices at the APP layer to form video packets with sizes adapted to their importance can also improve transmission reliability. We present a cross-layer dynamic programming (DP) approach to minimize the expected received video distortion by jointly addressing the priority-adaptive packet formation at the APP layer and rate compatible punctured convolutional (RCPC) code rate allocation at the physical layer for pre-encoded prioritized slices of each group of pictures (GOP). Our scheme discards some low priority slices in order to improve protection to more important slices and meet the channel bitrate limitations, whenever necessary. Simulation results show that our proposed approach significantly improves received video quality compared to other error protection schemes. Further, we extend our cross-layer DP-based scheme to slices of each frame by predicting the expected channel bit budget per frame for real-time transmission. The prediction uses a generalized linear model developed over the parameters---CMSE per frame, channel SNR, and normalized compressed frame bit budget determined over a video dataset that spans high, medium and low motion complexity. This predicted frame bit budget is used to derive the packet sizes and their corresponding RCPC code rates for transmission using our DP-based approach. Simulation results show good correlation with the results of our DP-based scheme applied over the GOP.
520 $a Unique characteristics of video traffic, such as the temporal and spatial dependencies between different video frames and their deadline constraints, pose a challenge in supporting the video quality rendered to the clients over time-varying, bandwidth-limited channels. Scalable Video Coding (H.264/SVC) enables the transmission and decoding of partial bit streams to provide video services with lower temporal or spatial resolutions or reduced fidelity while retaining a reconstruction quality that is high relative to the rate of the partial bit streams. We propose a sliding-window based flow control for scheduling the network abstraction layer (NAL) units in the post-encoding buffer of the streaming server for a real-time scalable video transmission scenario over a fast time-varying channel. Our scheduling scheme considers the importance of the NAL unit in terms of (i) its CMSE distortion contributed to the received video quality, (ii) its size in bits, and (iii) its time-to-expiry in seconds. The scheduling problem of determining the appropriate order of transmission is formulated as a 0-1 knapsack problem and a DP solution is proposed which runs in polynomial time. Our scheduling approach significantly reduces the number of whole frames discarded as compared to (a) a CMSE-based scheme which considers the importance of the NAL units only in terms of their CMSE contribution, and (b) the earliest deadline first scheme which minimizes the dwelling time of the NAL units in the post-encoding buffer. Simulation results show significant PSNR gains for different video sequences at different pre-roll delays.
590 $a School code: 0033.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, Computer. $3 1669061
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710 2 $a University of California, San Diego. $b Engineering Sciences (ElecCompEng). $3 3171216
773 0 $t Dissertation Abstracts International $g 75-09B(E).
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792 $a 2014
793 $a English
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