Performance Analysis of SWIPT-Assisted Cooperative NOMA Network With Non-Linear EH, Interference, and Imperfect SIC


Ashraf N., Sheikh S. A., Liaqat M., Khan S. A.

IEEE ACCESS, vol.13, pp.77481-77492, 2025 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 13
  • Publication Date: 2025
  • Doi Number: 10.1109/access.2025.3563111
  • Journal Name: IEEE ACCESS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
  • Page Numbers: pp.77481-77492
  • Keywords: cooperative nonorthogonal multiple access (C-NOMA), energy harvesting (EH), outage probability (OP), Simultaneous wireless information and power transfer (SWIPT)
  • Kocaeli University Affiliated: Yes

Abstract

Simultaneous wireless information and power transfer (SWIPT) provides an efficient approach towards prolonging the lifespan of wireless systems in 5G and beyond 5G communications by minimizing the reliance of devices on batteries and power sources. This paper suggests a SWIPT-assisted cooperative nonorthogonal multiple access (C-NOMA) network where a SWIPT enabled energy harvesting (EH) relay harvests energy from the source and utilizes it to forward the information to the end-user devices in the downlink. In order to obtain a realistic analysis, we aim to utilize a non-linear energy harvesting model and imperfect successive interference cancellation (imp-SIC) at the end user. The closed form expressions of outage probability (OP) and throughput are derived by considering multiple interfering signals at relay. Subsequently, the impact of the number of interferers on harvested energy and the OP, the power splitting (p.s.) ratio, distance between the nodes, and power allocation (p.a) factors are discussed in detail, and a comparison is presented against the traditional orthogonal multiple access (OMA) under the same conditions. The analysis clearly depicts that the proposed SWIPT-based C-NOMA system outperforms OMA in all aspects. Monte Carlo simulations are performed to corroborate the accuracy of the proposed analytical framework.