Resource Allocation for Weighted Max-min Fairness in NOMA with Imperfect SIC

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Power domain Non-orthogonal multiple access (NOMA) is a candidate multiple access technique for future wireless networks, which can improve spectrum efficiency and user connectivity. NOMA requires superposition coding (SC) at the transmitter side and successive interference cancellation (SIC) at the receiver side that can be achieved with reasonable system complexity. A heterogeneous network (Het-net) assisted with unmanned aerial vehicles (UAVs) is considered an indispensable part of the future wireless networks. Hence, weighted max-min fairness (MMF) data rate-based power allocation optimization for UAV-assisted networks in a heterogeneous cellular system is studied. Since power allocation for weighted MMF-based optimization is a non-convex problem, we characterized Perron-Frobenius (PF) theory-based optimization algorithm that converges very fast. The theoretical base and simulation results with imperfect SIC conditions and different weights for user data rates are presented.

Original languageEnglish
Title of host publication2022 IEEE/SICE International Symposium on System Integration, SII 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages957-962
Number of pages6
ISBN (Electronic)9781665445405
DOIs
Publication statusPublished - 2022
Event2022 IEEE/SICE International Symposium on System Integration, SII 2022 - Virtual, Narvik, Norway
Duration: 2022 Jan 92022 Jan 12

Publication series

Name2022 IEEE/SICE International Symposium on System Integration, SII 2022

Conference

Conference2022 IEEE/SICE International Symposium on System Integration, SII 2022
Country/TerritoryNorway
CityVirtual, Narvik
Period22/1/922/1/12

Keywords

  • NOMA
  • Power allocation
  • UAV
  • Weighted max-min fairness

ASJC Scopus subject areas

  • Artificial Intelligence
  • Hardware and Architecture
  • Biomedical Engineering
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization

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