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Rate control for robust video transmission over burst-error wireless channels

TLDR
Simulation results demonstrate that both the video distortion at the decoder and packet loss rate can be significantly reduced when incorporating the channel information provided by the feedback channel and the a priori model into the rate control algorithm.
Abstract
We study the problem of rate control for transmission of video over burst-error wireless channels, i.e., channels such that errors tend to occur in clusters during fading periods. In particular we consider a scenario consisting of packet based transmission with automatic repeat request (ARQ) error control and a back channel. We start by showing how the delay constraints in real time video transmission can be translated into rate constraints at the encoder, where the applicable rate constraints at a given time depend on future channel rates. With the acknowledgments received through the back channel we have an estimate of the current channel state. This information, combined with an a priori model of the channel, allows us to statistically model the future channel rates. Thus the rate constraints at the encoder can be expressed in terms of the expected channel behavior. We can then formalize a rate distortion optimization problem, namely, that of assigning quantizers to each of the video blocks stored in the encoder buffer such that the quality of the received video is maximized. This requires that the rate constraints be included in the optimization, since violating a rate constraint is equivalent to violating a delay constraint and thus results in losing a video block. We formalize two possible approaches. The first one seeks to minimize the distortion for the expected rate constraints given the channel model and current observation. The second approach seeks to allocate bits so as to minimize the expected distortion for the given model. We use both dynamic programming and Lagrangian optimization approaches to solve these problems. Our simulation results demonstrate that both the video distortion at the decoder and packet loss rate can be significantly reduced when incorporating the channel information provided by the feedback channel and the a priori model into the rate control algorithm.

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Citations
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Journal ArticleDOI

Rate-distortion methods for image and video compression

TL;DR: An overview of rate-distortion (R-D) based optimization techniques and their practical application to image and video coding is provided and two popular techniques for resource allocation are introduced, namely, Lagrangian optimization and dynamic programming.
Patent

Wireless video transmission system

TL;DR: In this article, a transmission system suitable for video where a sender encodes video for transmission to a receiver at an adjustable date rate is presented, where the data rate may be adjusted using a delay constraint that constrains the expected delay of transmitted packets.
Proceedings ArticleDOI

Multiple description coding via polyphase transform and selective quantization

TL;DR: This paper first model such unreliable channels as erasure channels and then presents a MDC system using polyphase transform and selective quantization to recover channel erasures to achieve robust communication over unreliable channels such as a lossy packet network.
Journal ArticleDOI

Joint source coding and transmission power management for energy efficient wireless video communications

TL;DR: Experimental results show that simultaneously adjusting the source coding and transmission power is more energy efficient than considering these factors separately.
Patent

Sender-side bandwidth estimation for video transmission with receiver packet buffer

TL;DR: In this article, a method of adaptively encoding video in response to an estimation of bandwidth over a transmission channel is proposed, where bandwidth estimation uses feedback packets from a receiver acknowledging receipt of video packets transmitted during an interval when the transmitted packets are not stored in a buffer of a lower network layer.
References
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Book

Dynamic Programming

TL;DR: The more the authors study the information processing aspects of the mind, the more perplexed and impressed they become, and it will be a very long time before they understand these processes sufficiently to reproduce them.
Journal ArticleDOI

Capacity of a burst-noise channel

TL;DR: The capacity C of the model channel exceeds the capacity C(sym. bin.) of a memoryless symmetric binary channel with the same error probability; however, the difference is slight for some values of h, p, P; then, time-division encoding schemes may be fairly efficient.
Book

Dynamic Programming: Deterministic and Stochastic Models

TL;DR: As one of the part of book categories, dynamic programming deterministic and stochastic models always becomes the most wanted book.
Journal ArticleDOI

Estimates of error rates for codes on burst-noise channels

TL;DR: In this paper, the error structure on communication channels used for data transmission may be so complex as to preclude the feasibility of accurately predicting the performance of given codes when employed on these channels.
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In this paper, the authors proposed a method to improve the quality of the data collected by the data collection system. 

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