Robust Energy-Efficient Design for MISO Non-Orthogonal Multiple Access Systems

Faezeh Alavi, Kanapathippillai Cumanan, Milad Fozooni, Zhiguo Ding, Sangarapillai Lambotharan, Octavia A. Dobre

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Non-orthogonal multiple access (NOMA) has been envisioned as a promising multiple access technique for 5G and beyond wireless networks due to its significant enhancement of spectral efficiency. In this paper, we investigate a robust energy efficiency design for multi-user multiple-input single-output (MISO) NOMA systems, where the imperfect channel state information is available at the base station (BS). A clustering algorithm is applied to group the users into different clusters, and then, the NOMA technique is employed to share the available resources fairly among the users in each cluster. To remove the interference between clusters, two different types of zero-forcing (ZF) designs, namely, hybrid-ZF and full-ZF, are employed at the BS. The full-ZF scheme completely removes the interference leakage at the cost of more number of antennas, and the hybrid-ZF scheme partially mitigates the interference leakage. To solve the problem, Dinkelbach's algorithm is employed to convert the non-linear fractional programming problem into a simple subtractive form. Finally, simulation results reveal that hybrid-ZF outperforms the full-ZF scheme with a few clusters, while full-ZF shows a better performance with higher number of clusters. Numerical results confirm that our proposed robust scheme outperforms the non-robust scheme in terms of the rate-satisfaction ratio at each user.

Original languageBritish English
Article number8781935
Pages (from-to)7937-7949
Number of pages13
JournalIEEE Transactions on Communications
Volume67
Issue number11
DOIs
StatePublished - Nov 2019

Keywords

  • Convex optimization
  • multiple-input single-output (MISO)
  • non-orthogonal multiple access (NOMA)
  • robust energy efficiency (EE)
  • worst-case performance optimization
  • zero-forcing (ZF)

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