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

Nana WANG; Zhaoting LIU; Yingbiao YAO

doi:10.11959/j.issn.1000-0801.2020041

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

Research and Development | 更新时间：2024-06-05

- One-bit maximum likelihood algorithm for sensor networks in non-ideal channels
- Telecommunications Science Vol. 36, Issue 3, Pages: 53-60(2020)
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- DOI：10.11959/j.issn.1000-0801.2020041
  CLC： TP393
- Published Online：2020-03，
  
  Published：20 March 2020
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Nana WANG, Zhaoting LIU, Yingbiao YAO. One-bit maximum likelihood algorithm for sensor networks in non-ideal channels[J]. Telecommunications science, 2020, 36(3): 53-60.
DOI：

Nana WANG, Zhaoting LIU, Yingbiao YAO. One-bit maximum likelihood algorithm for sensor networks in non-ideal channels[J]. Telecommunications science, 2020, 36(3): 53-60. DOI： 10.11959/j.issn.1000-0801.2020041.

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。

Abstract

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.

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references

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