Adaptive data compression for power line carrier services

Kuilin Huang; Mingyue Zhai; Wenbing Lu

doi:10.1117/12.3033166

5 July 2024 Adaptive data compression for power line carrier services

Kuilin Huang, Mingyue Zhai, Wenbing Lu

Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131843V (2024) https://doi.org/10.1117/12.3033166
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia

Abstract

In response to the demand for data transmission efficiency and accuracy for the diversity of power line carrier services in China, an adaptive data compression scheme is introduced in the paper, which is trained to compress and decompress the data after dividing it into data blocks, and selects an appropriate compression procedure by predicting the data entropy through deep neural network inference. By dividing the data blocks and compressing them according to the characteristics, this compression scheme avoids the worst compression rate and ensures that the compression rate of various types of business data is close to the optimal value. This scheme has some reference value for power line carrier multi-class service data transmission

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Kuilin Huang, Mingyue Zhai, and Wenbing Lu "Adaptive data compression for power line carrier services", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131843V (5 July 2024); https://doi.org/10.1117/12.3033166

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KEYWORDS

Image compression

Data compression

Neural networks

Data transmission

Education and training

Telecommunications

Terbium

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