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Qian Zhao 0010

dblp:82/4299-10 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0000-8300-7600ORCID · verified

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

Computer networks · 1 · 1 since 2021

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
1 paper
Physical-layer communications · 30% Internet of things and sensor networks · 30% Vehicular, aerial and satellite networks · 30%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications
synchronization
1.012026
Robust Timing Synchronization in Vehicular Communication Systems via Sensing Information · IEEE Trans. Commun. 2026
Internet of things and sensor networks
time synchronization
1.012026
Robust Timing Synchronization in Vehicular Communication Systems via Sensing Information · IEEE Trans. Commun. 2026
Vehicular, aerial and satellite networks
vehicular networks
1.012026
Robust Timing Synchronization in Vehicular Communication Systems via Sensing Information · IEEE Trans. Commun. 2026
Cellular and mobile networks
integrated sensing and communication
0.312026
Robust Timing Synchronization in Vehicular Communication Systems via Sensing Information · IEEE Trans. Commun. 2026

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

iterative path identification · 1.0delay-doppler domain detection · 1.0correlation matching · 1.0
YearPublicationVenuePosition
2026 Robust Timing Synchronization in Vehicular Communication Systems via Sensing Information
abstract
As the frame synchronization of the physical layer signal processing, timing synchronization (TS) is crucial for signal demodulation in vehicular communication systems (VCSs). However, existing TS methods primary rely on known training sequence to identify the first-arriving path, facing significant challenges in the scenarios with prominent Doppler and multipath interfere. Inspired by integrated sensing and communication (ISAC) technology, a sensing-aided TS method is proposed to address these challenges in VCSs. In this method, a detection threshold in the delay-Doppler (DD) domain is designed to extract echo paths. Based on the echo paths, we perform correlation matching between the Doppler prior information and the received communication signal, thereby further refining the sensing prior information for TS. With the assistance of Doppler prior information, the correctness of TS is improved by rectifying the local training sequence to compensate for the Doppler frequency shift of the received communication signal. In addition, an iterative method is developed to identify the first-arriving path by eliminating the impacts of paths stronger than the first one. Simulation results demonstrate that the proposed method significantly reduces TS error probability and exhibits its robustness against parameter variations.
Chaojin Qing, Yuxin Huang 0006, Qian Zhao 0010
IEEE Trans. Commun.3