Active Terminal Identification, Channel Estimation, and Signal Detection for Grant-Free NOMA-OTFS in LEO Satellite Internet-of-Things

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