Work

Joint User Identification, Channel Estimation, and Data Detection for Grant-Free NOMA in LEO Satellite Communications

Year: 2024

Type: article

Abstract: Satellite Internet of things (S-IoT) aims to provide globally covered network services. In this paper, we conceive an uplink grant-free random access scheme for S-IoT network, where ground devices transmit data packets to the low Earth orbit (LEO) satellite, reducing signaling cost and making efficient use of spectrum resources by employing the non-orthogonal multiple access scheme. The impact of high operational speed of the LEO satellite is also taken into account. We further propose an iterative Gaussian approximated message passing-aided sparse Bayesian learning (GAMP-SBL) algorithm to address the joint channel estimation (CE), active user identification (UID) and data detection (DD) problem, where the three steps interacts with each other during the iterative process. Simulation results have demonstrated that our proposed joint receiver design outperforms the existing AMP-based schemes in terms of bit error rate (BER), convergence speed, as well as false alarm rate (FAR).

Source: IEEE Journal on Selected Areas in Communications

DOI: 10.1109/jsac.2024.3460059

Authors: Chen Zhang, Yusha Liu, Jie Hu, Kun Yang

Institutions: University of Electronic Science and Technology of China, Nanjing University

Language: English

Topic: Satellite Communication Systems

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

Funders: National Natural Science Foundation of China, Ministry of Science and Technology of Thailand, Key Research and Development Program of Zhejiang Province