scholarly journals Cross-Layer Perceptual ARQ for Video Communications over 802.11e Wireless Networks

2007 ◽  
Vol 2007 ◽  
pp. 1-12 ◽  
Author(s):  
P. Bucciol ◽  
E. Masala ◽  
E. Filippi ◽  
J. C. De Martin

This work presents an application-level perceptual ARQ algorithm for video streaming over 802.11e wireless networks. A simple and effective formula is proposed to combine the perceptual and temporal importance of each packet into a single priority value, which is then used to drive the packet-selection process at each retransmission opportunity. Compared to the standard 802.11 MAC-layer ARQ scheme, the proposed technique delivers higher perceptual quality because it can retransmit only the most perceptually important packets reducing retransmission bandwidth waste. Video streaming of H.264 test sequences has been simulated withnsin a realistic 802.11e home scenario, in which the various kinds of traffic flows have been assigned to different 802.11e access categories according to the Wi-Fi alliance WMM specification. Extensive simulations show that the proposed method consistently outperforms the standard link-layer 802.11 retransmission scheme, delivering PSNR gains up to 12 dB while achieving low transmission delay and limited impact on concurrent traffic. Moreover, comparisons with a MAC-level ARQ scheme which adapts the retry limit to the type of frame contained in packets and with an application-level deadline-based priority retransmission scheme show that the PSNR gain offered by the proposed algorithm is significant, up to 5 dB. Additional results obtained in a scenario in which the transmission relies on an intermediate node (i.e., the access point) further confirms the consistency of the perceptual ARQ performance. Finally, results obtained by varying network conditions such as congestion and channel noise levels show the consistency of the improvements achieved by the proposed algorithm.

Author(s):  
Monalisa Ghosh ◽  
Chetna Singhal

Video streaming services top the internet traffic surging forward a competitive environment to impart best quality of experience (QoE) to the users. The standard codecs utilized in video transmission systems eliminate the spatiotemporal redundancies in order to decrease the bandwidth requirement. This may adversely affect the perceptual quality of videos. To rate a video quality both subjective and objective parameters can be used. So, it is essential to construct frameworks which will measure integrity of video just like humans. This chapter focuses on application of machine learning to evaluate the QoE without requiring human efforts with higher accuracy of 86% and 91% employing the linear and support vector regression respectively. Machine learning model is developed to forecast the subjective quality of H.264 videos obtained after streaming through wireless networks from the subjective scores.


Multi hop wireless networks are being deployed in many video streaming applications because they have several potential features for next generation wireless communications. Though optimal encoding techniques offers significant quality retention in video transmission still it is insufficient to overcome the challenges ahead over wireless network transmission. In order to support wide range video communications in an efficient way certain Quality of service has to be retained in multi hop wireless network. To address this issue, this paper investigates several encoding and routing protocols video delivery over multi hop wireless networks. Specifically, we first investigate several encoding framework for videos and wireless data transmission over WMNs through individual paths; we then investigate the challenges ahead to formulate resistant routing model for least possible video quality dictions which incorporate channel status as well as the encoder properties over video characteristics. In this framework, routing techniques which can maximally used to achieve good video traffic with improved system performance. However, video streaming also have very stringent delay requirements, which makes it difficult to find optimal routes with the least possible distortions. To address this problem, we investigate several enhanced version of packet scheduling techniques for video communications over multi path multi hob multi user wireless network environment.


2009 ◽  
Vol 66 (6) ◽  
pp. 327-342 ◽  
Author(s):  
Shun Muraoka ◽  
Hiroyuki Masuyama ◽  
Shoji Kasahara ◽  
Yutaka Takahashi

2020 ◽  
Vol 19 (7) ◽  
pp. 1715-1730
Author(s):  
Tong Zhang ◽  
Fengyuan Ren ◽  
Wenxue Cheng ◽  
Xiaohui Luo ◽  
Ran Shu ◽  
...  

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