This paper investigates the massive connectivity of low Earth orbit (LEO) satellite-based Internet-of-Things (IoT) for seamless global coverage. We propose to integrate the grant-free non-orthogonal multiple access (GF-NOMA) paradigm with the emerging orthogonal time frequency space (OTFS) modulation to accommodate the massive IoT access, and mitigate the long round-trip latency and severe Doppler effect of terrestrial-satellite links (TSLs). On this basis, we put forward a two-stage successive active terminal identification (ATI) and channel estimation (CE) scheme as well as a low-complexity multi-user signal detection (SD) method. Specifically, at the first stage, the proposed training sequence aided OTFS (TS-OTFS) data frame structure facilitates the joint ATI and coarse CE, whereby both the traffic sparsity of terrestrial IoT terminals and the sparse channel impulse response are leveraged for enhanced performance. Moreover, based on the single Doppler shift property for each TSL and sparsity of delay-Doppler domain channel, we develop a parametric approach to further refine the CE performance. Finally, a least square based parallel time domain SD method is developed to detect the OTFS signals with relatively low complexity. Simulation results demonstrate the superiority of the proposed methods over the state-of-the-art solutions in terms of ATI, CE, and SD performance confronted with the long round-trip latency and severe Doppler effect.

翻译：本文调查了低地球轨道(LEO)基于卫星的互联网(IoT)的大规模连通性,以便无缝地覆盖全球。我们提议将无赠与非横向多功能访问(GF-NOMA)模式与新兴的正方位时频空间(OTFS)调制(OTFS)模式结合起来,以适应大规模IOT访问,并减轻地面卫星链接(TSLs)的长期双向流动悬浮和严重多普勒效应。在此基础上,我们提出了两阶段连续两阶段的主动终端识别(ATI)和频道估计(CEE)计划以及低兼容性多用户信号检测(SD)方法。具体地说,在第一阶段,拟议的培训序列辅助OTFS(TS-OTFS)数据框架结构便利了联合的ATI和粗化的CEE, 利用地面IOT终端的交通偏缓冲和稀薄的频道反应来提高性能。此外,根据每个TRE的单度转移属性和延迟-C的深度信号探测(C-SDSDR-S-L-L-SDTFS-S-S-L-S-S-S-S-S-SAL-SL-SL-SL-SL-S-S-S-S-SL-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-SL-S-SL-SL-S-SL-SL-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-S-