Implementation of a rate control algorithm for compressed sensed videos on a software defined radio
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Wireless Multimedia Sensor Networks (WMSNs) applications are multifaced. However, a key area of audio and video transmissions over a WMSN remains unexplored. Conventional video encoding techniques have high encoder complexity and low resiliency to channel errors. Network fairness and congestion also need to be addressed. In this work, a low complexity video encoder based on compressed sensing, and a rate controller for video streaming over wireless networks are implemented. This algorithm jointly regulates source and channel encoding rates. Compressed sensing (CS) is a tool to find a sparse solution for underdetermined linear systems. This allows sampling at sub-Nyquist rates and still enables recovery based on convex optimization techniques. This helps reduce the amount of data generated at the sources. Channel coding is based on a novel adaptive parity scheme that varies the strength of channel coding based on the current estimated bit error rate of the channel. The algorithm is implemented on an USRP2 Software Defined Radio (SDRs) considering the benefits it offers in terms of flexibility. It I tested in a real multihop OFDM network. Results show that the rate control algorithm converges under congested and uncongested network conditions. The algorithm also recovers under side traffic conditions.