Impact of Hybrid PAPR Reduction Techniques on FBMC for 5G Applications

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal on Smart Sensing and Intelligent Systems Pub Date : 2020-01-01 DOI:10.21307/ijssis-2020-024

Satwinder Kaur, Lavish Kansal, G. S. Gaba, Fahad Alraddady, Sandeep Kumar Arora

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引用次数: 3

Abstract

The filter bank multicarrier (FBMC) system suffers from the non-linear effects that arise due to a high peak-to-average power ratio (PAPR). Diverse precoding techniques are utilized to enhance the efficiency and robustness of FBMC. A high PAPR in the FBMC system can be overcome by a unique combination of precoding and conventional PAPR reduction techniques proposed in this paper. Different precoding schemes, discrete sine transform (DST) and discrete cosine transform (DCT), are combined with different PAPR reduction techniques, such as clipping and companding, to decrease the effects of the elevated PAPR in the FBMC system. The simulation results show a significant reduction in PAPR for both the transforms applied individually as well as in combination with conventional PAPR reduction methodologies. The MATLAB simulation outcome also depicts a substantial reduction in bit error rate (BER) in the range of 5 to 10 dB on the incorporation of DST/DCT precoding transforms in the conventional FBMC system.

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混合PAPR降低技术对5G应用中FBMC的影响

滤波器组多载波(FBMC)系统由于峰值平均功率比(PAPR)高而产生非线性效应。为了提高FBMC的效率和鲁棒性，采用了多种预编码技术。本文提出的预编码和传统的PAPR降低技术的独特组合可以克服FBMC系统中的高PAPR。不同的预编码方案，离散正弦变换(DST)和离散余弦变换(DCT)，结合不同的PAPR降低技术，如裁剪和压缩，以减少提高的PAPR在FBMC系统的影响。仿真结果表明，无论是单独应用的变换，还是与传统的PAPR降低方法相结合，都能显著降低PAPR。MATLAB仿真结果还描述了在传统FBMC系统中加入DST/DCT预编码变换后，误码率(BER)在5至10 dB范围内的大幅降低。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal on Smart Sensing and Intelligent Systems ENGINEERING, ELECTRICAL & ELECTRONIC-

CiteScore

2.70

自引率

8.30%

发文量

审稿时长

8 weeks

期刊介绍： nternational Journal on Smart Sensing and Intelligent Systems (S2IS) is a rapid and high-quality international forum wherein academics, researchers and practitioners may publish their high-quality, original, and state-of-the-art papers describing theoretical aspects, system architectures, analysis and design techniques, and implementation experiences in intelligent sensing technologies. The journal publishes articles reporting substantive results on a wide range of smart sensing approaches applied to variety of domain problems, including but not limited to: Ambient Intelligence and Smart Environment Analysis, Evaluation, and Test of Smart Sensors Intelligent Management of Sensors Fundamentals of Smart Sensing Principles and Mechanisms Materials and its Applications for Smart Sensors Smart Sensing Applications, Hardware, Software, Systems, and Technologies Smart Sensors in Multidisciplinary Domains and Problems Smart Sensors in Science and Engineering Smart Sensors in Social Science and Humanity