Distributed Audio Coding in Wireless Sensor Networks

Abstract

The strict constrains of wireless sensor networks (WSN) on individual sensor node's resource brings great challenges to the information processing. In order to maximize compression and minimize energy cost in WSN, a novel wavelet-based distributed audio coding (WDAC) algorithm is proposed. This approach fully exploits the correlation of the signal in both spatial and frequency domain by using distributed lifting wavelet transform with boundary effects. A low-complexity change detection algorithm (LCDA) is developed to mark active blocks and we only encode these active regions to save energy significantly. The simulation results showed that these approaches is energy efficient and has low complexity with less memory requirements in implementation