Pang-Chen Liu

dblp:277/2826 · DBLP profile ↗
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5ranked-venue papers
3as first author
4since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 5 · 3 first-author · 4 since 2021
YearPublicationVenuePosition
2023 Novel convergence of fixed-access and mobile network architectures with ultra-low latency multi-slicing
Pang-Chen Liu, Ping-Chang Tsai, Fei-Hua Kuo, Kou-Hsiang Lai
APNOMS1
2023 Coherent PON interconnect system with phase compensation
Ping-Chang Tsai, Pang-Chen Liu, Fei-Hua Kuo, Kou-Hsiang Lai
APNOMS2
2022 Double-layer access network architecture for intelligent building services
abstract
A double layer access network architecture that provides Internet and Intranet for smart building services. The Internet provides network services, and the Intranet provides information exchange for private devices. At the same time, it supports dual-rate design, so there is no need to replace the device when the user rate is upgraded. This architecture simplifies network device requirement and improves sustainability. This paper mainly discusses the construction of audio-visual services on the optical fiber access network and the improvement of the provision method in the community, and service requirements can be flexibly adjusted.
Ping-Chang Tsai, Pang-Chen Liu, Wen-Chien Chan, Fei-Hua Kuo, Kuo-Hsiang Lai
APNOMS2
2021 New Multi-Access Network Transmission Technology to Enhance Edge Computing
abstract
The 5G era is officially coming. It bringing many new applications, such as self-driving cars, 3D VR, etc. Among them, edge computing technology is particularly critical which can reduce latency and increase throughput, thereby promoting the resources expansion and services diversity. This paper proposes to use high-speed network transmission technology RDMA and multi-access network transmission architecture to apply to multi-access edge computing including collaborative computing, data synchronization and data backup, etc. It is to provide low-latency and high-throughput network transmission so that edge computing users have better user experience.
Pang-Chen Liu, Huai-En Tseng, Shun-Kai Yang, Fei-Hua Kuo
APNOMS1
2020 Prequalification of VDSL2 copper customers for G.fast services with artificial intelligence technology
abstract
In recent years, due to customers have higher requirements for 4K/BK video and high-speed internet, telecom operators have begun to deploy FTTH network, but found that it is generally difficult to deploy fiber to the home, so G.fast technology has been favored by most telecom operators around the world and have begun to actively deploy. For the most widely deploy VDSL2 line with maximum rate that can only provide 100M internet service, a intelligent and accurate G.fast 300M high speed service prequalification technology, is a major research topic for telecom operators to promote 300M high-speed internet service. This paper proposes to use AI machine learning to estimate the G.fast line rate by using VDSL2 line attenuation to meet the real-site provision needs of telecommunications operators.
Pang-Chen Liu, Shun-Kai Yang, Lung-Chin Huang, Huai-En Tseng, Fei-Hua Kuo, Tai-Chueh Shih
APNOMS1