Adaptive quantization for distributed estimation in cluster-based wireless sensor networks

详细信息    查看全文

• 作者：Guiyun Liu^a ; ^{liugy@gzhu.edu.cn" class="auth_mail} ; Bugong Xu^b ; ^{aubgxu@scut.edu.cn" class="auth_mail} ; Hongbin Chen^c ; ^{chbscut@guet.edu.cn" class="auth_mail} ; Chunliang Zhang^a ; ^{nhzcl@163.com" class="auth_mail} ; Jianhua Xiang^a ; ^{xiangjh@gzhu.edu.cn" class="auth_mail} ; Chao Zhou^a ; ^{superzc@tom.com" class="auth_mail}
• 关键词：Sensor network ; Distributed estimation ; Cluster ; Quantization
• 刊名：AEU - International Journal of Electronics and Communications
• 出版年：June, 2014
• 年：2014
• 卷：68
• 期：6
• 页码：484-488
• 全文大小：430 K

文摘

In this paper, the problem of parameter estimation in cluster-based wireless sensor networks is studied. Particularly, we focus on how to choose a suitable threshold in the one-bit adaptive quantization scheme. An adaptive quantization scheme for parameter estimation in cluster-free sensor networks is extended to this scenario. Intra-cluster and inter-cluster maximum likelihood estimators (MLEs) as well as the corresponding Cramr-Rao lower bounds (CRLBs) are derived. Due to the energy constraint of sensors, the performance-energy tradeoff of parameter estimation is also investigated. Simulation results show that parameter estimation in cluster-based sensor networks with adaptive quantization can be more energy-efficient than that in cluster-free sensor networks, while achieving close performance as the number of sensors increases.