Research of Radio Frequency Channel Occupancy Prediction Based on Decision Tree

DOI

10.2991/tlicsc-18.2018.49How to use a DOI?

Keywords

spectrum management, frequency channel occupancy, decision tree, prediction, machine learning.

Abstract

Efficient utilization of finite spectrum resource is one of the purposes of spectrum management. Frequency channel occupancy is often used to evaluate the historical usage status of a frequency. Predicting the frequency channel occupancy is of great value to improve the utilization rate of spectrum resources. In this paper, an approach of extracting features from historical frequency channel occupancy data is proposed, and a method of frequency channel occupancy prediction based on decision tree is designed. Based on the actual spectrum monitoring data, we use big data and machine learning technology to predict the frequency channel occupancy of various radio services. The actual test results show that the prediction method is of high accuracy.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Fuyin Zhao
AU  - Yuqi Zeng
AU  - Xueling Zhang
AU  - Kai Zhou
PY  - 2018/12
DA  - 2018/12
TI  - Research of Radio Frequency Channel Occupancy Prediction Based on Decision Tree
BT  - Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)
PB  - Atlantis Press
SP  - 304
EP  - 309
SN  - 1951-6851
UR  - https://doi.org/10.2991/tlicsc-18.2018.49
DO  - 10.2991/tlicsc-18.2018.49
ID  - Zhao2018/12
ER  -