4.8 Article

Outage Performance for NOMA-Based FSO-RF Systems With Transmit Antenna Selection and Nonlinear Energy Harvesting

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 10, Issue 7, Pages 6491-6506

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2022.3227043

Keywords

NOMA; Radio frequency; Internet of Things; Transmitting antennas; Signal to noise ratio; Relays; Closed-form solutions; Antenna selection (AS); free space optical-radio frequency (FSO-RF); nonlinear energy harvesting (EH); non-orthogonal multiple access (NOMA); outage probability (OP)

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In this article, the outage performance of a dual-hop free space optical-radio frequency communication system is investigated. The system consists of a source node, two users, and a single-aperture and multi-antenna relay. The relay can harvest energy from a power beacon, and two transmitting antenna selection (AS) criteria are considered to improve the outage performance. The closed-form expressions of the outage probability for each user under both AS schemes are derived and validated through Monte-Carlo simulation.
In this article, we investigate the outage performance for a dual-hop free space optical-radio frequency communication system, in which a source node communicates with two users on a non-orthogonal multiple access basis via a single-aperture and multi-antenna relay, which can harvest energy from a power beacon under a nonlinear energy harvesting mode. In particular, two transmitting antenna selection (AS) criteria, namely, the random-maximum AS (RA-AS) and the minimum-maximum AS (IA-AS) schemes, are considered to improve the outage performance of the system. In addition, an adaptive power allocation algorithm, which allocates the power to each user according to the instantaneous channel power gain, is adopted for the RA-AS scheme. Considering the Gamma-Gamma distribution and the Rayleigh fading, the closed-form expressions of the outage probability for each user under both the RA-AS and IA-AS schemes are derived. Moreover, the Monte-Carlo simulation verifies the correctness of the theoretical derivations.

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