JOURNAL ARTICLE

A cross layer resource allocation for multiuser video transmission over wireless networks

Abstract

A Multimedia transmission such as video streaming over wireless networks has grown dramatically in recent years. The downlink transmission of multiple video sequences to multiple users over a shared resource-limited wireless channel, however, is a tough task. We face many challenges in this area like time-varying channel conditions, limited available resources, such as bandwidth and power, and the different transmission requirements of different video content. This work takes into account the time-varying nature of the wireless channels, as well as the importance of individual video packets, to develop a cross-layer resource allocation and packet scheduling scheme for multiuser video streaming over wireless networks. Assuming that accurate channel feedback is not available at the scheduler, random channel losses combined with complex error concealment at the receiver make it impossible for the scheduler to determine the actual distortion of the sequence at the receiver. Therefore, the objective of the optimization is to minimize the expected distortion of the received sequence, where the expectation is calculated at the scheduler with respect to the packet loss probability in the channel. The expected distortion is used to order the packets in the transmission queue of each user, and then gradients of the expected distortion are used to efficiently allocate resources across users.

Keywords:
Computer science Computer network Network packet Wireless network Wireless Channel (broadcasting) Resource allocation Scheduling (production processes) Telecommunications link Transmission (telecommunications) Real-time computing Telecommunications Engineering

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FWCI (Field Weighted Citation Impact)
2
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0.11
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Topics

Advanced Wireless Network Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing
Image and Video Quality Assessment
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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