Original scientific paper
https://doi.org/10.1080/00051144.2022.2106532
An efficient SLM technique based on chaotic biogeography-based optimization algorithm for PAPR reduction in GFDM waveform
S. Selvin Pradeep Kumar
; Department of Electronics and communication Engineering, St. Xavier’s Catholic College of Engineering, Chunkankadai, India
C. Agees Kumar
; Department of Electrical and Electronics Engineering, Arunachala College of Engineering for Women, Vellichanthai, India
R. Jemila Rose
; Department of Computer Science and Engineering, St Xavier’s Catholic College of Engineering, Chunkankadai, India
Abstract
High data rates, extremely low power consumption, and minimal end-to-end latency are considered to be mandatory requirements for 5G wireless networks. Rapid improvements in design and performance of 5G physical layer waveforms have become necessary. The drawback of Orthogonal Frequency Division Multiplexing (OFDM) is high PAPR, that causes signal distortion, which reduces system efficiency. Generalized frequency division multiplexing (GFDM) is a promising non-orthogonal multicarrier transmission scheme, which has recently received a great deal of attention towards future fifth generation (5G) wireless networks. It overcomes the limitations of orthogonal frequency division multiplexing (OFDM), while preserving most of the advantages of it. Selective Level mapping (SLM) is one of the PAPR reduction techniques, that uses the phase shift technology. In this paper, SLM based on Chaotic Biogeography Based Optimization (CBBO) algorithm is proposed to offer an efficient solution to the problem of high PAPR, existing in the GFDM waveforms. Experimental results prove that, the proposed CBBO–SLM technique provides significant improvement in terms of PAPR reduction, as compared to the conventional SLM methods, such as conventional GFDM and OFDM-SLM. The proposed novel scheme is most suitable for QAM and QPSK applications, as it provides good PAPR reduction performance, at lower computational complexity.
Keywords
Generalized frequency division multiplexing; selective level mapping; peak to average power ratio; chaotic biogeography based optimization
Hrčak ID:
287949
URI
Publication date:
7.9.2022.
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