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A New Method for Channel Congestion and Multi information Fusion Localization in Communication Access Network of Power System

Published: 31 July 2024 Publication History

Abstract

Channel congestion in communication access networks may lead to communication interruption, making it impossible to transmit and communicate data normally. Therefore, a new multi information fusion localization method for channel congestion in power system communication access networks is proposed. Design a channel multi information receiving structure and receive and process channel multi monitoring information; Multi information fusion of power system communication access network channels through Fourier transform; Construct a communication channel model to estimate the congestion status of the communication access network channel in the power system; A direct localization algorithm based on sparse reconstruction is used to achieve channel congestion localization in power system communication access networks. The experimental results show that this method can accurately and efficiently locate channel congestion in communication access networks.

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  1. A New Method for Channel Congestion and Multi information Fusion Localization in Communication Access Network of Power System

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    PEAI '24: Proceedings of the 2024 International Conference on Power Electronics and Artificial Intelligence
    January 2024
    969 pages
    ISBN:9798400716638
    DOI:10.1145/3674225
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Published: 31 July 2024

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