非理想信道下的传感器网络一比特最大似然算法  

One-bit maximum likelihood algorithm for sensor networks in non-ideal channels

作　　者：王娜娜 刘兆霆 姚英彪[1] WANG Nana;LIU Zhaoting;YAO Yingbiao(School of Communication Engineering,Hangzhou Dianzi University,Hangzhou 310018,China)

机构地区：[1]杭州电子科技大学通信工程学院,浙江杭州310018

出　　处：《电信科学》2020年第3期53-60,共8页Telecommunications Science

基　　金：国家自然科学基金资助项目(No.61671192);浙江省自然科学基金资助项目(No.LY16F010012)。

摘　　要：无线传感器网络通常由分布在一定空间范围内的无线传感器节点构成。一般情况下,节点的能量存储、计算和通信能力都极为有限。直接传输各个节点的采样信号到融合中心将导致较多的能量消耗与较大的网络通信负载。若将每个传感器节点的采样信号值压缩为一比特测量值后再传输,则可以在很大程度上降低能量消耗和减轻通信负载。研究了在乘性噪声环境下,基于传感器网络一比特测量的参数估计问题。考虑节点和融合中心之间是存在干扰的非理想二值信道,提出了基于最大似然的参数估计算法,分析了参数估计的克拉美罗下界,并通过一系列仿真实验,验证了算法的有效性。Wireless sensor networks typically consist of wireless sensor nodes that are distributed in a certain spatial range.In general,the energy storage,computing and communication capabilities of nodes are extremely limited.Direct transmission of the sampled signals of the various nodes to the fusion center will result in more energy consumption and greater network communication load.If the sampled signal value of each sensor node is compressed into a one-bit measurement value and then transmitted,the energy consumption and the communication load can be greatly reduced.The parameter estimation problem based on one-bit measurement of sensor networks in multiplicative noise environment was studied.Considering the non-ideal binary channel with interference between the node and the fusion center,a parameter estimation algorithm based on maximum likelihood was proposed,Cramér-Rao lower bound of the parameter estimation was analyzed,and the effectiveness of the algorithm was verified through a series of simulation experiments.

关 键 词：传感器网络 非理想信道 参数估计 一比特量化 最大似然算法 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]