Distributional Substitution for Intersensor Distances in Random Fields

The distance between wireless sensors in random fields is crucial for performance analysis and sensor network deployment. However, the exact distribution models are normally of great complexity and can hardly lead to closed-form analytics for most cases. In this letter, we investigate the intersensor distance distribution in random fields, propose a polynomial intersensor distance distributional substitute, and develop two strategies for distributional parameter mapping for different application scenarios. Simulation results presented in this letter verify the effectiveness and efficiency of the low-complexity distributional substitution technique. The verified analyses given in this letter can help to provide mathematically tractable performance metrics for wireless sensor networks where sensors are randomly distributed over the 2-D space.

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Publication Details

Journal
IEEE Sensors Letters
Published
2024-12-24
DOI
https://doi.org/10.1109/lsens.2024.3521994
Citations
2
Primary Topic
Distributed Sensor Networks and Detection Algorithms
Type
article
Field-Weighted Citation Impact
0.70
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article

Distributional Substitution for Intersensor Distances in Random Fields

Marwa Chafii, Raed M. Shubair, Shuaishuai Guo, Shuping Dang et al.
2 citations
IEEE Sensors Letters
Distributed Sensor Networks and Detection Algorithms
0.70
article

Distributional Substitution for Intersensor Distances in Random Fields

Marwa Chafii, Raed M. Shubair, Shuaishuai Guo, Shuping Dang, Jia Ye
article en
2 citations

Abstract

The distance between wireless sensors in random fields is crucial for performance analysis and sensor network deployment. However, the exact distribution models are normally of great complexity and can hardly lead to closed-form analytics for most cases. In this letter, we investigate the intersensor distance distribution in random fields, propose a polynomial intersensor distance distributional substitute, and develop two strategies for distributional parameter mapping for different application scenarios. Simulation results presented in this letter verify the effectiveness and efficiency of the low-complexity distributional substitution technique. The verified analyses given in this letter can help to provide mathematically tractable performance metrics for wireless sensor networks where sensors are randomly distributed over the 2-D space.

IEEE Sensors LettersVol. 9(2)
Shandong University (CN), Chongqing University (CN), University of Bristol (GB), New York University (US)
Openalex Percentile: Top 26%
Distributed Sensor Networks and Detection Algorithms
0.70
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Distributional Substitution for Intersensor Distances in Random Fields — Marwa Chafii, Raed M. Shubair, et al. · IEEE Sensors Letters (2024) | TGRS Research Map | TGRS