Reconfigurable Intelligent Surface-Assisted OFDM-IM for beyond 5G Mobile Networks: ML and LLR Detector Designs

Ceniklioglu B., DEVELİ İ., Canbilen A. E.

1st IEEE International Conference on Contemporary Computing and Communications, InC4 2023, Bangalore, India, 21 - 22 April 2023 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/inc457730.2023.10262978
  • City: Bangalore
  • Country: India
  • Keywords: index modulation (IM), log-likelihood ratio (LLR), maximum likelihood (ML), Orthogonal frequency division multiplexing (OFDM), reconfigurable intelligent surface (RIS)
  • Erciyes University Affiliated: Yes

Abstract

The several countries of the world is intensified their investigative on the fifth generation and beyond (5GB) communications in order to reach the new requirements for new wireless applications. In this context, orthogonal frequency division multiplexing with index modulation (OFDM-IM) concept is suggested as one of the ideal solutions in the literature. Additionally, reconfigurable intelligent surfaces (RISs) can be occupied to enahance the quality of service (QoS). Considering that, the performance of RIS-assisted OFDM-IM system is examined by applying maximum likelihood (ML) and log-likelihood ratio (LLR) detectors in this paper. It is observed from the provided computer simulation results that integrating an RIS consisting of many low-cost and passive elements, into OFDM-IM systems considerably increase the overall system performance.