Compressed-Sensing-Enabled Video Streaming for Wireless Multimedia Sensor Networks

Abstract—This paper presents the design of a networked system for joint compression, rate control and error correction of video over

resource-constrained embedded devices based on the theory of Compressed Sensing (CS). The objective of this work is to design a

cross-layer system that jointly controls the video encoding rate, the transmission rate, and the channel coding rate to maximize the

received video quality. First, compressed sensing-based video encoding for transmission over Wireless Multimedia Sensor Networks

(WMSNs) is studied. It is shown that compressed sensing can overcome many of the current problems of video over WMSNs, primarily

encoder complexity and low resiliency to channel errors. A rate controller is then developed with the objective of maintaining fairness

among different videos while maximizing the received video quality. It is shown that the rate of Compressed Sensed Video (CSV) can be

predictably controlled by varying only the compressed sensing sampling rate. It is then shown that the developed rate controller can be

interpreted as the iterative solution to a convex optimization problem representing the optimization of the rate allocation across the

network. The error resiliency properties of compressed sensed images and videos are then studied, and an optimal error detection and

correction scheme is presented for video transmission over lossy channels. Finally, the entire system is evaluated through simulation

and test bed evaluation. The rate controller is shown to outperform existing TCP-friendly rate control schemes in terms of both fairness

and received video quality. The test bed results show that the rates converge to stable values in real channels.