Cluster-Based Quantization and Estimation for Distributed Systems

• Published in: Journal of Information and Communication Convergence Engineering, 14(4) Vol. 14; no. 4; pp. 215 - 221
• Main Author: Kim, Yoon Hak
• Format: Journal Article
• Language: English
• Published: 한국정보통신학회JICCE 31.12.2016; 한국정보통신학회
• Subjects: 전자/정보통신공학; Sensor networks; Distributed estimation; Distributed quantization; Clustering; Source localization
• ISSN: 2234-8255; 2234-8883
• DOI: 10.6109/jicce.2016.14.4.215

We consider a design of a combined quantizer and estimator for distributed systems wherein each node quantizes its measurement without any communication among the nodes and transmits it to a fusion node for estimation. Noting that the quantization partitions minimizing the estimation error are not independently encoded at nodes, we focus on the parameter regions created by the partitions and propose a cluster-based quantization algorithm that iteratively finds a given number of clusters of parameter regions with each region being closer to the corresponding codeword than to the other codewords. We introduce a new metric to determine the distance between codewords and parameter regions. We also discuss that the fusion node can perform an efficient estimation by finding the intersection of the clusters sent from the nodes. We demonstrate through experiments that the proposed design achieves a significant performance gain with a low complexity as compared to the previous designs. KCI Citation Count: 3