Windowing Optimization for Fingerprint-Spectrum-Based Passive Sensing in Perceptive Mobile Networks

Autor:	Wang, Xiao-Yang, Yang, Shaoshi, Zhai, Hou-Yu, Masouros, Christos, Zhang, J. Andrew
Rok vydání:	2024
Předmět:	Electrical Engineering and Systems Science - Signal Processing Computer Science - Networking and Internet Architecture
Druh dokumentu:	Working Paper
DOI:	10.1109/TCOMM.2024.3446610
Popis:	Perceptive mobile networks (PMN) have been widely recognized as a pivotal pillar for the sixth generation (6G) mobile communication systems. However, the asynchronicity between transmitters and receivers results in velocity and range ambiguity, which seriously degrades the sensing performance. To mitigate the ambiguity, carrier frequency offset (CFO) and time offset (TO) synchronizations have been studied in the literature. However, their performance can be significantly affected by the specific choice of the window functions harnessed. Hence, we set out to find superior window functions capable of improving the performance of CFO and TO estimation algorithms. We firstly derive a near-optimal window, and the theoretical synchronization mean square error (MSE) when utilizing this window. However, since this window is not practically achievable, we then test a practical "window function" by utilizing the multiple signal classification (MUSIC) algorithm, which may lead to excellent synchronization performance. Comment: 16 pages, 12 figures, accepted to publish on IEEE Transactions on Communications, Aug. 2024
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2409.00950 Zobrazit plný text záznamu View this record from Arxiv