Study on Soft-Decision Fusion Rules for Coding Approach in Wireless Sensor Networks

• Main Authors: Wang Yung Ti, 王永迪
• Other Authors: Yunghsiang S. Han
• Format: Others
• Language: en_US
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/10889169786416289216

碩士 === 國立臺北大學 === 通訊工程研究所 === 94 === In this thesis, we study three soft-decision fusion rules, which are named the maximum a posteriori probability (MAP) fusion rule, the minimum Euclidean distance (MED) fusion rule and the distributed classification fusion using soft-decision (DCSD) fusion rule. The performance comparison of the MAP rule, the MED fusion rule, and the DCSD rule proposed in earlier work is also conducted. By simulation, we show that, in fault-free situation, the MAP fusion rule performs the best, while the DSCD rule outperforms the MED rule. When the number of faulty sensors is small, the MAP fusion rule remains the best at either low sensor observation signal-to-noise ratios (OSNRs) or low communication channel signal-to-noise ratios (CSNRs), and yet, the DCSD fusion rule gives the best performance at middle to high OSNRs and high CSNRs. When the number of faulty sensors grows larger, the MED fusion rule, which requires the least computational complexity, outperforms the MAP fusion rule at high OSNRs and high CSNRs.