Compressed Sensing for Feedback Generation in OFDM Based LiFi Systems

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

  • Javad Gholipour - , Vodafone Chair of Mobile Communications Systems (Author)
  • Kai Lennert Bober - , Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute (Author)
  • Malte Hinrichs - , Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute (Author)
  • Volker Jungnickel - , Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute (Author)

Abstract

In this paper, we evaluate the effectiveness of compressed-sensing-based channel estimation in LiFi orthogonal frequency-division multiplex (OFDM) systems with multiple-input multiple-output (MIMO). The sparseness of LiFi channels suggests that it is beneficial to utilize compressed sensing which has been investigated also for radio communications. In this paper, we formulate the mathematical problem of compressed-sensing for feedback generation in OFDM-based LiFi systems. We use well-known algorithms for both, sparse pilot design and sparse recovery and apply them to LiFi OFDM channels. We evaluate the effectiveness of these algorithms by measuring the achievable mean squared error (MSE) and vary the total numbers of subcarriers as well as the number of pilot subcarriers.

Details

Original languageEnglish
Title of host publication2023 IEEE Wireless Communications and Networking Conference, WCNC 2023 - Proceedings
Number of pages6
ISBN (electronic)978-1-6654-9122-8
Publication statusPublished - 2023
Peer-reviewedYes

External IDs

Scopus 85159789189

Keywords

ASJC Scopus subject areas

Keywords

  • LiFi, MIMO, OFDM, channel estimation, compressed sensing