Design of Joint Device and Data Detection for Massive Grant-Free Random Access in LEO Satellite Internet of Things

Abstract

Recently, low-Earth orbit (LEO) satellite Internet of Things (IoT) has received considerable interests due to its global coverage for massive IoT devices distributed over a large area, especially in remote areas, e.g., ocean, desert, and forest. Considering relatively long transmission distance between IoT devices and LEO satellite, we propose a low latency and small overhead sourced grant-free random access (GF-RA) framework, where active devices send their data signals directly without the grant of LEO satellite. In order to detect active device and recover the corresponding data, we design a joint device and data detection algorithm for massive GF-RA in LEO satellite IoT. In particular, the active device maps the data to a codeword of a predetermined and unique codebook, and then sends it to the LEO satellite. By detecting the codeword via maximizing the likelihood function of the received signal, the LEO satellite obtains the active device and recovers the corresponding data. Theoretical analysis shows that the proposed algorithm has a fast convergence behavior and low computational complexity. Finally, we provide extensive simulation results to confirm the effectiveness of the proposed algorithm over baseline ones in LEO satellite IoT.