A novel generalized oppositional biogeography-based optimization algorithm: application to peak to average power ratio reduction in OFDM systems

• Autorzy: Sotirios K. Goudos
• Języki publikacji: EN

Abstrakty

EN

A major drawback of orthogonal frequency division multiplexing (OFDM) signals is the high value of peak to average power ratio (PAPR). Partial transmit sequences (PTS) is a popular PAPR reduction method with good PAPR reduction performance, but its search complexity is high. In this paper, in order to reduce PTS search complexity we propose a new technique based on biogeography-based optimization (BBO). More specifically, we present a new Generalized Oppositional Biogeography Based Optimization (GOBBO) algorithm which is enhanced with Oppositional Based Learning (OBL) techniques. We apply both the original BBO and the new Generalized Oppositional BBO (GOBBO) to the PTS problem. The GOBBO-PTS method is compared with other PTS schemes for PAPR reduction found in the literature. The simulation results show that GOBBO and BBO are in general highly efficient in producing significant PAPR reduction and reducing the PTS search complexity.

Słowa kluczowe

EN

Evolutionary algorithms; Biogeography-based optimization (BBO); Opposition based Learning; Combinatorial optimization; OFDM; PAPR; PTS

Kategorie tematyczne

• 94A14: Modulation and demodulation
• 94A12: Signal theory (characterization, reconstruction, filtering, etc.)
• 68Q32: Computational learning theory
• 68T05: Learning and adaptive systems
• 68W40: Analysis of algorithms

• Wydawca: De Gruyter Open
• Czasopismo: Open Mathematics
• Rocznik: 2016
• Tom: 14
• Numer: 1
• Strony: 705-722

Daty

wydano

2016-01-01

otrzymano

2016-03-31

zaakceptowano

2016-09-09

online

2016-10-10

Twórcy

autor

Sotirios K. Goudos

• Radiocommunications Laboratory, Section of Applied and Environmental Physics, Department of Physics, Aristotle University of Thessaloniki, 54124 Thessaloniki,

Identyfikatory

DOI

10.1515/math-2016-0066