Evaluations of SiC by power difference in im-noma

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

Abstract

In most NOMA studies, power allocation is fixed. However, in reality, the optimal power allocation varies depending on the environment in which it is used. Therefore, the goal of this paper is to automatically perform the optimal power allocation in NOMA. SIC is a technique for separating signals using the power difference, and it is known that signals fail to separate if the power difference is small. However, there are few researches to discuss how much power difference is required for successful separation. In addition, IM-NOMA enables flexible communication by adding index modulation to conventional NOMA. In this paper, we investigate the success of signal separation in SIC in terms of BER, SNR, Throughput, Sumrate, and Fairness Index by varying the power ratio in NOMA-based multi-user system. In addition, in comparison of conventional NOMA scheme, IM-NOMA with flexible power allocation were examined in terms of BER, SNR, Throughput, Sumrate, and Fairness Index. It was found that it was easier to maintain communication quality to some extent even for terminals with low power allocation, which are prone to relatively poor communication quality.

Original languageEnglish
Title of host publicationProceedings - 12th Wireless Days Conference, WD 2021
PublisherIEEE Computer Society
ISBN (Electronic)9781665425599
DOIs
Publication statusPublished - 2021
Event12th Wireless Days Conference, WD 2021 - Paris, France
Duration: 2021 Jun 302021 Jul 2

Publication series

NameIFIP Wireless Days
Volume2021-June
ISSN (Print)2156-9711
ISSN (Electronic)2156-972X

Conference

Conference12th Wireless Days Conference, WD 2021
Country/TerritoryFrance
CityParis
Period21/6/3021/7/2

Keywords

  • Index modulation (IM)
  • Non-orthogonal multiple access (NOMA)
  • Orthogonal frequency division multiplexing (OFDM)
  • Successive interference cancellation (SIC)

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Electrical and Electronic Engineering

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