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Channel Modeling for Digital Transmission Using Power Line
Author(s) -
Sasaki Norio,
Seino Kenichi,
Hanaumi Tasuku,
Oda Takeshi,
Adachi Fumiyuki
Publication year - 2014
Publication title -
electronics and communications in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.131
H-Index - 13
eISSN - 1942-9541
pISSN - 1942-9533
DOI - 10.1002/ecj.11544
Subject(s) - path loss , power delay profile , electronic engineering , radio propagation model , transmission line , electric power transmission , noise (video) , transmission loss , impulse (physics) , channel (broadcasting) , impulse response , transmission (telecommunications) , power line communication , noise power , propagation delay , delay spread , computer science , power (physics) , acoustics , radio propagation , telecommunications , mathematics , engineering , electrical engineering , physics , mathematical analysis , fading , wireless , image (mathematics) , quantum mechanics , artificial intelligence
SUMMARY Experiments on modeling a channel for digital transmission were performed, and an analysis of the results was used to clarify the characteristics of propagation loss and of the delay path profile, together with the noise characteristics of a power line carrier system using power transmission lines. To investigate the characteristics of propagation loss, the experimental results were subjected to multiple regression analysis and an equation for estimating propagation loss was derived with useful parameters. To investigate the characteristics of the delay path profile, the additional loss in the delay path was modeled and elucidated. The results showed that the delay path is traveled by both in‐phase propagation and out‐of‐phase propagation. Thus, it is important to consider these two propagation characteristics during modeling. The noise characteristics were shown to be superpositions of the characteristics of thermal noise and impulse noise, and these two characteristics were modeled on the basis of a theoretical analysis and the cumulative probability distribution. The simultaneous use of these models agreed well with the measured results, indicating that the models are practical for real‐world use.