Scalable distributed source coding

This paper considers the problem of scalable distributed coding of correlated sources that are communicated to a central unit. The general setting is typically encountered in sensor networks. The conditions of communication channels between the source encoders and fusion center may be time-varying and it is often desirable to guarantee a base layer of coarse information during channel fades. In addition the desired system should be robust to various scenarios of channel failure and should utilize all the available information to attain the best possible compression efficiency. Although a standard dasiaLloyd-stylepsila distributed coder design algorithm can be generalized to scalable distributed source coding, the resulting algorithm depends heavily on initialization and will virtually always converge to a poor local minimum on the distortion-cost surface. We propose an efficient initialization scheme for such a system, which employs a properly designed multi-stage distributed coder. In our prior work, we highlighted the fundamental conflict that arises when multi-stage coding is directly combined with distributed quantization. Here we use the multi-stage distributed coding system to initialize a scalable distributed coder and propose an iterative algorithm for joint design of all system components once the structural constraint is removed. Simulation results show considerable gains over randomly initialized scalable distributed coder design.