Low-Correlation Complementary Exponential Pilot for Grant-Free Random Access in Satellite-Integrated Internet

With the advent of the sixth-generation (6G) mobile communication era, Low Earth Orbit (LEO) satellite systems are critical for supporting massive device connectivity. Grantfree random access (GFRA) schemes have been proposed to reduce latency and signaling overhead, but pilot collisions remain a significant challenge. This paper introduces a novel low-correlation complementary exponential sequence (LCCES)-based pilot design for GFRA. By integrating generalized Boolean functions with Zadoff-Chu sequences (ZCS), LCCES achieves large-scale pilot set expansion while maintaining low cross-correlation properties. Theoretical analysis and simulations demonstrate that LCCES outperforms existing pilot schemes in terms of pilot collision probability, decoding failure probability, and access failure probability.

Authors

Institutions

Publication Details

Published
2025-08-10
DOI
https://doi.org/10.1109/icccworkshops67136.2025.11148172
Primary Topic
IoT Networks and Protocols
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Low-Correlation Complementary Exponential Pilot for Grant-Free Random Access in Satellite-Integrated Internet

Jian Jiao, Liang Xu, Yaosheng Zhang, Qinyu Zhang et al.
IoT Networks and Protocols
article

Low-Correlation Complementary Exponential Pilot for Grant-Free Random Access in Satellite-Integrated Internet

Jian Jiao, Liang Xu, Yaosheng Zhang, Qinyu Zhang, Ye Wang, H.P. Shen
article en

Abstract

With the advent of the sixth-generation (6G) mobile communication era, Low Earth Orbit (LEO) satellite systems are critical for supporting massive device connectivity. Grantfree random access (GFRA) schemes have been proposed to reduce latency and signaling overhead, but pilot collisions remain a significant challenge. This paper introduces a novel low-correlation complementary exponential sequence (LCCES)-based pilot design for GFRA. By integrating generalized Boolean functions with Zadoff-Chu sequences (ZCS), LCCES achieves large-scale pilot set expansion while maintaining low cross-correlation properties. Theoretical analysis and simulations demonstrate that LCCES outperforms existing pilot schemes in terms of pilot collision probability, decoding failure probability, and access failure probability.

Harbin Institute of Technology (CN), Peng Cheng Laboratory (CN)
Openalex Percentile: Top 76%
IoT Networks and Protocols
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.