Enhanced PAPR reduction in DCO-OFDM using multi-point constellations and DPSO optimization

AYDIN V., HACIOĞLU G.

NEURAL COMPUTING & APPLICATIONS, cilt.36, ss.5747-5756, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 36
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1007/s00521-023-09409-9
  • Dergi Adı: NEURAL COMPUTING & APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, Biotechnology Research Abstracts, Compendex, Computer & Applied Sciences, Index Islamicus, INSPEC, zbMATH
  • Sayfa Sayıları: ss.5747-5756
  • Karadeniz Teknik Üniversitesi Adresli: Evet

Özet

DC-biased optical OFDM (DCO-OFDM) is a commonly used method of OFDM in visible light communication (VLC). Unfortunately, VLC systems that use OFDM often experience a high peak-to-average power ratio (PAPR). To address this issue, this study proposes a novel method called the multi-point constellation method (MPC) to reduce PAPR in DCO-OFDM. The MPC method involves adding extra alternative constellation points around the existing points and using the discrete particle swarm optimization (DPSO) algorithm to select the constellation points with the lowest PAPR. The proposed MPC method is also combined with selective mapping (SLM), a well-known PAPR reduction technique in the literature. Simulation results show that the proposed MPC method outperforms the SLM method in reducing PAPR in 4-QAM and 16-QAM modulations when used in combination with SLM. Furthermore, increasing the number of iterations and particles in the DPSO algorithm improves the PAPR reduction performance of the proposed method even further.