A Symbol Timing Estimation Method With FRI Sampling for RRC Shaped Communication Signals

This letter proposes a symbol timing estimator for root-raised cosine shaped digital communication signals under finite-rate-of-innovation sampling. By incorporating symbol period prior information into the traditional model, the number of unknown parameters is further reduced. The proposed method processes the signal via spectral truncation with the width of half the number of symbols and eliminating the effect of unknown symbols through statistical analysis. Timing estimation is finally achieved by detecting inter-symbol interference-free points. Simulations demonstrate accurate performance at both oversampling rates above and below 1.

Authors

Institutions

Publication Details

Journal
IEEE Communications Letters
Published
2025-08-19
DOI
https://doi.org/10.1109/lcomm.2025.3599503
Primary Topic
Blind Source Separation Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Symbol Timing Estimation Method With FRI Sampling for RRC Shaped Communication Signals

Xuguang Xu, Ming Tan, Lixun Han, Xiaojun Zou et al.
IEEE Communications Letters
Blind Source Separation Techniques
article

A Symbol Timing Estimation Method With FRI Sampling for RRC Shaped Communication Signals

Xuguang Xu, Ming Tan, Lixun Han, Xiaojun Zou, Hang Zhu, Wei Song
article en

Abstract

This letter proposes a symbol timing estimator for root-raised cosine shaped digital communication signals under finite-rate-of-innovation sampling. By incorporating symbol period prior information into the traditional model, the number of unknown parameters is further reduced. The proposed method processes the signal via spectral truncation with the width of half the number of symbols and eliminating the effect of unknown symbols through statistical analysis. Timing estimation is finally achieved by detecting inter-symbol interference-free points. Simulations demonstrate accurate performance at both oversampling rates above and below 1.

IEEE Communications LettersVol. 29(10)
PLA Information Engineering University (CN), Wuhan University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hubei Province
Openalex Percentile: Top 74%
Blind Source Separation Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.