Research on a primary synchronization signal detection algorithm for LEO-5G system

Conference: CAIBDA 2022 - 2nd International Conference on Artificial Intelligence, Big Data and Algorithms
06/17/2022 - 06/19/2022 at Nanjing, China

Proceedings: CAIBDA 2022

Pages: 5Language: englishTyp: PDF

Authors:
Zhang, Peng; Zeng, Wei; Li, Yaxin; Tan, Lei (School of Mechanical and Electrical Engineering, Chengdu University of Technology Chenghua District, Chengdu, Sichuan, China)
Xia, Huan; Yu, Zhen (School of Computer Science, Chengdu University of Technology Chenghua District, Chengdu, Sichuan, China)

Abstract:
The article is based on the 5GNR (New Radio, NR) standard, and the 5GNR system has extremely high requirements for frequency offset. The article proposes two algorithms based on "direct cross-correlation" and "multi-block combined cross-correlation". The "piecewise cross-correlation" algorithm. The algorithm improves the anti-frequency offset performance by segmenting the received signal and the local signal; when the signal-to-noise ratio is the same, the increase or decrease of the number of segments will affect the synchronization performance. Based on the anti-frequency offset advantage of the "multi-block merged cross-correlation" and "segmented cross-correlation" algorithms, this paper proposes a "two-block merged and divided into two-segment cross-correlation" detection algorithm with better anti-frequency offset performance. The performance of PSS detection algorithm is simulated and analyzed. The simulation shows that, compared with the traditional PSS detection algorithm, the "two-block merge and two-stage cross-correlation" detection algorithm effectively reduces the detection error rate and improves the detection performance.