IEICE Communications Express
Online ISSN : 2187-0136
ISSN-L : 2187-0136
Special Cluster in Conjunction with IEICE General Conference 2019
Two-step path loss prediction by artificial neural network for wireless service area planning
Kentaro SaitoYongri JinCheChia KangJun-ichi TakadaJenq-Shiou Leu
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JOURNAL FREE ACCESS

2019 Volume 8 Issue 12 Pages 611-616

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Abstract

In recent years, wireless network systems are utilized in various industry fields and the wireless service area planning became one of the important tasks to realize efficient and high-quality wireless communication service. The machine learning technology attracts the interests of researchers to improve the efficiency of the area planning task because the radio propagation loss in unknown locations can be predicted by the training data without explicit algorithms. Our previous work showed that the path loss (PL) characteristics become complicated in the high PL region, and it can degrade the entire prediction accuracy. In this paper, we propose the two-step PL prediction method by the artificial neural network (ANN) to solve the issue. Firstly, the area is classified into several zones according to the PL range. And then the PL is predicted by ANNs that were trained for respective zones. Our proposal was evaluated by the ray-tracing simulation data, and the result showed that it improved the root mean square error (RMSE) of PL prediction from 7.9 dB to 4.1 dB. The method is expected to be utilized for the wireless service area planning in various environments.

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© 2019 The Institute of Electronics, Information and Communication Engineers
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