Distributed Vector Quantization over Sensor Network

A vector quantizer is a system for encoding the original data to reduce the bits needed for communication and storage saving while maintaining the necessary fidelity of the data. Signal processing over distributed network has received a lot of attention in recent years, due to the rapid development of sensor network. Gathering data to a central processing node is usually infeasible for sensor network due to limited communication resource and power. As a kind of data compression methods, vector quantization is an appealing technique for distributed network signal processing. In this paper, we develop two distributed vector quantization algorithms based on the Linde-Buzo-Gray (LBG) algorithm and the self-organization map (SOM). In our algorithms, each node processes the local data and transmits the local processing results to its neighbors. Each node then fuses the information from the neighbors. Our algorithms remarkably reduce the communication complexity compared with traditional algorithms processing all the distributed data in one central fusion node. Simulation results show that both of the proposed distributed algorithms have good performance.