On the Performance of End-to-End Cooperative NOMA-Based IoT Networks with Wireless Energy Harvesting

Sutanu Ghosh, Arafat Al-Dweik, Mohamed-Slim Alouini

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

This paper studies the end-to-end uplink (UL) and downlink (DL)-outage probability (OP) of an Internet of Things (IoT) network with radio frequency (RF) energy harvesting (EH) over Nakagami-m fading channels. Power-domain nonorthogonal multiple access (NOMA) is adopted to support both the UL and DL transmissions to increase the network spectral efficiency. The system end-to-end UL and DL outage probabilities are analyzed where exact closed-form expressions are derived. The system performance is explored for various system parameters such as time allocation for EH, transmission power, fading conditions, number of IoT devices (IoDs), and data rate. The obtained analytical results are corroborated using Monte Carlo simulation for various operating scenarios. The obtained results show that the optimum harvesting time may broadly vary based on the adopted system parameters. Moreover, the results show that the system OP is highly sensitive to the harvesting time where OP may vary drastically if the harvesting time deviates from the optimum. The impact of the perfect successive interference cancellation (SIC) (PSIC) is also evaluated and compared with imperfect SIC (ISIC), and the obtained results show that the OP of the system can be significantly underestimated with the PSIC assumption. Therefore, the commonly used PSIC assumption may cause substantial deviation from the practical case where the detection process experiences ISIC.
Original languageEnglish (US)
Pages (from-to)1-1
Number of pages1
JournalIEEE Internet of Things Journal
DOIs
StatePublished - Apr 17 2023

Bibliographical note

KAUST Repository Item: Exported on 2023-05-05
Acknowledgements: The work of A. Al-Dweik was supported by Khalifa University Competitive Internal Research Award (CIRA), Grant no. CIRA 2020-056.

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Information Systems and Management
  • Computer Science Applications
  • Hardware and Architecture
  • Computer Networks and Communications

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