An Interference Alignment and ICA-Based Semiblind Dual-User Downlink NOMA System for High-Reliability Low-Latency IoT



Wan, Xin, Zhu, Xu ORCID: 0000-0002-7371-4595, Jiang, Yufei, Liu, Yujie and Zhao, Jiahe
(2020) An Interference Alignment and ICA-Based Semiblind Dual-User Downlink NOMA System for High-Reliability Low-Latency IoT. IEEE Internet of Things Journal, 7 (11). pp. 10837-10851.

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Abstract

An interference alignment (IA) and independent component analysis (ICA)-based semiblind scheme, referred to as IA-ICA, is proposed for downlink dual-user power-domain nonorthogonal multiple access (NOMA) systems in high-reliability low-latency (HRLL) Internet of Things (IoT). At the base station (BS), one user is converted to constructive interference to the other user via phase alignment of each symbol. At both user ends, ICA is used for semiblind signal detection. The phase rotation via nonredundant precoding at the BS does not introduce any spectral overhead, while only 1-2 pilot symbols are required for elimination of ICA incurred ambiguity. Closed-form expressions are derived for the users' symbol error rate (SER) performance in Rayleigh fading with 4-quadrature amplitude modulation (4-QAM), which matches the simulation results very well. Based on the analytical results, we propose an efficient power allocation algorithm that is based on statistical channel state information (CSI) only, and therefore, the signaling overhead involved is negligible. In particular, a near-optimal SER performance can be achieved with equal power allocation between the two users. The proposed IA-ICA-based semiblind NOMA system demonstrates a much better SER performance than the existing approaches even though they are under perfect CSI. Hence, it is a feasible solution for HRLL IoT, with high reliability and very low spectral and signaling overheads.

Item Type: Article
Uncontrolled Keywords: NOMA, Resource management, Silicon carbide, Interference, Internet of Things, Reliability, Downlink, High-reliability low-latency (HRLL) Internet of Things (IoT), independent component analysis (ICA), interference alignment (IA), nonorthogonal multiple access (NOMA)
Divisions: Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User: Symplectic Admin
Date Deposited: 08 Apr 2021 10:09
Last Modified: 18 Jan 2023 22:54
DOI: 10.1109/JIOT.2020.2989376
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3118202