An efficient SLM technique based on migrating birds optimization algorithm with cyclic bit flipping mechanism for PAPR reduction in UFMC waveform


TAŞPINAR N., Şimşir Ş.

Physical Communication, cilt.43, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 43
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.phycom.2020.101225
  • Dergi Adı: Physical Communication
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC
  • Anahtar Kelimeler: PAPR, 5G, UFMC, SLM, Migrating birds optimization, AVERAGE POWER RATIO, CARRIER AGGREGATION, PAR REDUCTION, OFDM, PERFORMANCE, SCHEMES, SIGNALS
  • Erciyes Üniversitesi Adresli: Evet

Özet

© 2020 Elsevier B.V.The peak-to-average power ratio (PAPR) is one of the most serious issues to be dwelled on, carefully, in wireless communication. It is not possible to take the advantage of multicarrier transmission strategy without handling the problem of high PAPR arising from the usage of multiple subcarriers for generating the time domain transmission signals. As being a kind of multicarrier waveform, universal filtered multicarrier (UFMC) which is developed a short time ago as a contender waveform for the fifth generation (5G) telecommunication systems, suffers from the high PAPR values of its transmission signals as well. By considering the related issue, we developed a new selective mapping (SLM) technique based on migrating birds optimization (MBO) algorithm to offer an efficient solution to the problem of high PAPR in the UFMC waveform. In the proposed MBO-based SLM (MBO–SLM) scheme, in order to perform an effective phase optimization in discrete space, cyclic bit flipping mechanism is integrated to the MBO algorithm. According to the simulation results, with our proposed MBO–SLM technique, significant improvement is achieved in the PAPR reduction performance of the conventional SLM method thanks to the MBO-based phase optimization process supported by the cyclic bit flipping mechanism.