OFDMA-based unsourced random access in LEO satellite Internet of Things

This paper investigates the low earth orbit (LEO) satellite-enabled coded compressed sensing (CCS) unsourced random access (URA) in orthogonal frequency division multiple access (OFDMA) framework, where a massive uniform planar array (UPA) is equipped on the satellite. In LEO satellite communications, unavoidable timing and frequency offsets cause phase shifts in the transmitted signals, substantially diminishing the decoding performance of current terrestrial CCS URA receiver. To cope with this issue, we expand the inner codebook with predefined timing and frequency offsets and formulate the inner decoding as a tractable compressed sensing (CS) problem. Additionally, we leverage the inherent sparsity of the UPA-equipped LEO satellite angular domain channels, thereby enabling the outer decoder to support more active devices. Furthermore, the outputs of the outer decoder are used to reduce the search space of the inner decoder, which cuts down the computational complexity and accelerates the convergence of the inner decoding. Simulation results verify the effectiveness of the proposed scheme.