标题： 上行链路多用户OTFS的时间和频率同步 显示英文标题

标题： Time and Frequency Synchronization for Multiuser OTFS in Uplink

摘要： 本文中，我们提出了用于高速移动场景下上行多用户OTFS（MU-OTFS）系统的时域和频域同步技术。 本工作专注于准确估计和校正定时偏移（TOs）和载波频率偏移（CFOs）。 具体而言，TO估计对于在时延-时间平面上定位用户的导频信号至关重要，而CFO估计则提高了信道估计的准确性。 首先，我们提出了一种针对MU-OTFS中现有多用户导频结构的TO估计技术。 我们将该导频结构中的脉冲导频（IMP）替换为具有循环前缀的更实用的导频（PCP），称为单用户启发式PCP（SU-PCP）。 该结构使用不同的Zadoff-Chu（ZC）序列，这使得接收端可以通过相关性实现导频分离。 因此，我们引入了一种基于相关性的TO估计技术，用于上行MU-OTFS系统，利用此导频结构。 接下来，提出了一种频谱高效且实用的导频模式，其中每个用户在时延-多普勒平面上的共享导频区域内发送一个PCP，称为MU-PCP。 在接收端，第二种TO估计技术利用一组滤波器来分离不同用户的信号并准确估计它们的TOs。 随后，我们推导出一个数学阈值范围，通过在相关函数中寻找第一个主要峰值而不是仅依赖最高峰值来提高TO估计的准确性。 在使用所提出的TO估计技术之一定位接收到的用户导频信号后，我们提出的CFO估计技术将多维最大似然（ML）搜索问题转化为多个一维搜索问题。 在此技术中，我们应用了第一类切比雪夫多项式基展开模型（CPF-BEM），以有效处理在获取所有用户CFO估计时信道的时间变化。 显示英文摘要

摘要： In this paper, we propose time and frequency synchronization techniques for uplink multiuser OTFS (MU-OTFS) systems in high-mobility scenarios. This work focuses on accurately estimating and correcting timing offsets (TOs) and carrier frequency offsets (CFOs). Specifically, TO estimation is essential for locating users' pilots on the delay-time plane, while CFO estimation enhances channel estimation accuracy. First, we propose a TO estimation technique for an existing multiuser pilot structure in MU-OTFS. We replace the impulse pilot (IMP) in this pilot structure with a more practical pilot with a cyclic prefix (PCP), referred to as single-user-inspired PCP (SU-PCP). This structure employs different Zadoff-Chu (ZC) sequences, which enables pilot separation via correlation at the receiver side. Consequently, we introduce a correlation-based TO estimation technique for uplink MU-OTFS using this pilot structure. Next, a spectrally efficient and practical pilot pattern is proposed, where each user transmits a PCP within a shared pilot region on the delay-Doppler plane, referred to as MU-PCP. At the receiver, the second TO estimation technique utilizes a bank of filters to separate different users' signals and accurately estimate their TOs. Then, we derive a mathematical threshold range to enhance TO estimation accuracy by finding the first major peak in the correlation function rather than relying solely on the highest peak. After locating the received users' pilot signals using one of the proposed TO estimation techniques, our proposed CFO estimation technique reduces the multi-dimensional maximum likelihood (ML) search problem into multiple one-dimensional search problems. In this technique, we apply the Chebyshev polynomials of the first kind basis expansion model (CPF-BEM) to effectively handle the time-variations of the channel in obtaining the CFO estimates for all the users.