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Juan Fang 0003

dblp:69/5289-3 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2025
0000-0001-8488-5149ORCID · conflict

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

Computer networks · 1 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
2 papers
Physical-layer communications · 65% Wireless networking · 32% Cellular and mobile networks · 3%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 10 heaviest of 11, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
modulation
0.912025
Probabilistic Shaping for Wi-Fi 8 · IEEE J. Sel. Areas Commun. 2025
Physical-layer communications › modulation
probabilistic shaping
0.912025
Probabilistic Shaping for Wi-Fi 8 · IEEE J. Sel. Areas Commun. 2025
Wireless networking
WLAN
0.912025
Probabilistic Shaping for Wi-Fi 8 · IEEE J. Sel. Areas Commun. 2025
Embedded and real-time systems › cyber-physical system platforms
industrial automation
0.412019
Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems · Proc. IEEE 2019
Embedded and real-time systems › real-time communication › real-time networks
time-sensitive networking
0.412019
Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems · Proc. IEEE 2019
Physical-layer communications
channel coding
0.312025
Probabilistic Shaping for Wi-Fi 8 · IEEE J. Sel. Areas Commun. 2025
Physical-layer communications › channel coding › error control coding › block codes
LDPC codes
0.312025
Probabilistic Shaping for Wi-Fi 8 · IEEE J. Sel. Areas Commun. 2025
Cellular and mobile networks
5g
0.112019
Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems · Proc. IEEE 2019
Wireless networking › reliable wireless communication › mission-critical wireless communication
industrial wireless
0.112019
Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems · Proc. IEEE 2019
Wireless networking › wireless network protocols
wireless synchronization
0.112019
Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems · Proc. IEEE 2019

Methods — techniques the papers use, named apart from their topics

unequal modulation · 0.9probabilistic shaping · 0.9LDPC coding · 0.9
YearPublicationVenuePosition
2025 Probabilistic Shaping for Wi-Fi 8
abstract
The IEEE 802.11 working group has formed a new Task Group, 802.11bn, to develop a new amendment to support ultra-high reliability (UHR) for Wi-Fi networks, which will eventually shape what Wi-Fi 8 will look like. In this paper, we propose a probabilistic shaping (PS) scheme to improve the spectrum and power efficiency in medium to high signal to noise ratio (SNR) regime forWi-Fi 8. The integration and compatibility with legacy Wi-Fi systems, as well as other Wi-Fi 8 candidate technologies like unequal modulation (UEQM) are addressed. An architecture with a single low-density parity-check (LDPC) encoder and multiple shaping encoders is devised to adapt to different qualities of spatial channels. Furthermore, we propose practical techniques to resolve issues like error propagation, scrambler re-synchronization, and packet length determination to ensure compatibility with legacy scrambling, subframe detection, and packaging flow. It is shown that the proposed constellation shaping scheme provides average 0.89 dB shaping gains over the legacy Wi-Fi scheme, and the shaping gains remain when UEQM and lifted LDPC are applied.
Juan Fang 0003, Cheng Chen 0007, Assaf Gurevitz, Yaron Yoffe
IEEE J. Sel. Areas Commun.1
2019 Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems
abstract
Many industrial automation systems rely on time-synchronized (and timely) communication among sensing, computing, and actuating devices. Advances in Ethernet enabled by time-sensitive networking (TSN) standards, being developed by the IEEE 802.1 TSN Task Group, are significantly improving time synchronization as well as worst case latencies. Next-generation industrial systems are expected to leverage advances in distributed time coordinated computing and wireless communications to enable greater levels of automation, efficiency, and flexibility. Significant progress has been made in extending accurate time synchronization over the air (e.g., 802.1AS profile for IEEE 802.11/Wi-Fi). Given the inherently unreliable, varying capacity and latency prone characteristics associated with wireless communications, proving the feasibility of worst case latency performance over the wireless medium is a major research challenge. More specifically, understanding what levels of capacity, reliability, and latency could be guaranteed over wireless links with high reliability are important research questions to guide the development of new radios, protocols, and time coordinated applications. This paper provides an overview of the potential applications, requirements, and unique research challenges to extend TSN capabilities over wireless. The paper also describes advances in wireless technologies (e.g., next-generation 802.11 and 5G standards) toward achieving reliable and accurate time distribution and timeliness capabilities. It also provides a classification of wireless applications and a reference architecture for enabling the integration of wired and wireless TSN capabilities in future industrial automation systems.
Dave Cavalcanti 0001, Javier Perez-Ramirez, Mohammad Mamunur Rashid, Juan Fang 0003, Mikhail Galeev, Kevin B. Stanton
Proc. IEEE4