Estimation of Probability Density Function Using Multi-bandwidth Kernel Density Estimation for Throughput

Norisato Suga, Kazuto Yano, Julian Webber, Yafei Hou, Toshihide Higashimori, Yoshinori Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In manufacturing and logistics, various applications exploiting IoT devices are started to be used. Although there is a demand for wireless connection between the IoT devices to networks, obstacles such as radio frequency interference, multipath-rich propagation, and movement of objects make communication unstable. The instability can cause a system failure of IoT applications. Estimation of probability density function (PDF) of throughput is an important technique for the communication failure prediction and control of data rate of wireless communication applications. Because wireless environment in factories change complicatedly, the PDF of throughput is a mixture of narrow and wide distributions. For such PDF, the conventional kernel density estimation which uses uni-bandwidth kernel can not accurately estimate the distribution. To overcome this problem, we propose a novel kernel density estimation method which uses multiple bandwidths kernels. In addition, we extend a likelihood cross validation method to the multi-bandwidth kernel density estimation to determined the suboptimum bandwidths of kernels and combining weights. To confirm the effectiveness of the proposed method, we conduct numerical simulation assuming image transmission for car body inspection at an automobile factory.

Original languageEnglish
Title of host publication2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages171-176
Number of pages6
ISBN (Electronic)9781728149851
DOIs
Publication statusPublished - Feb 2020
Event2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 - Fukuoka, Japan
Duration: Feb 19 2020Feb 21 2020

Publication series

Name2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020

Conference

Conference2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
CountryJapan
CityFukuoka
Period2/19/202/21/20

Keywords

  • multi-bandwidth kernel density estimation
  • throughput prediction
  • wireless LAN

ASJC Scopus subject areas

  • Information Systems and Management
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Signal Processing

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    Suga, N., Yano, K., Webber, J., Hou, Y., Higashimori, T., & Suzuki, Y. (2020). Estimation of Probability Density Function Using Multi-bandwidth Kernel Density Estimation for Throughput. In 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 (pp. 171-176). [9065033] (2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAIIC48513.2020.9065033