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一种用于5G及以后降低峰均功率比的新型混合预编码-压扩技术。

A Novel Hybrid Precoding-Companding Technique for Peak-to-Average Power Ratio Reduction in 5G and beyond.

作者信息

Mounir Mohamed, El Mashade Mohamed B, Berra Salah, Gaba Gurjot Singh, Masud Mehedi

机构信息

Department of Electronics and Communications Engineering, El Gazeera High Institute for Engineering and Technology, Cairo 11751, Egypt.

Department of Electrical Engineering, Faculty of Engineering, Al-Azhar University, Cairo 11751, Egypt.

出版信息

Sensors (Basel). 2021 Feb 18;21(4):1410. doi: 10.3390/s21041410.

DOI:10.3390/s21041410
PMID:33670542
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7922168/
Abstract

Several high-speed wireless systems use Orthogonal Frequency Division Multiplexing (OFDM) due to its advantages. 5G has adopted OFDM and is expected to be considered beyond 5G (B5G). Meanwhile, OFDM has a high Peak-to-Average Power Ratio (PAPR) problem. Hybridization between two PAPR reduction techniques gains the two techniques' advantages. Hybrid precoding-companding techniques are attractive as they require small computational complexity to achieve high PAPR reduction gain. Many precoding-companding techniques were introduced to increasing the PAPR reduction gain. However, reducing Bit Error Rate (BER) and out-of-band (OOB) radiation are more significant than increasing PAPR reduction gain. This paper proposes a new precoding-companding technique to better reduce the BER and OOB radiation than previous precoding-companding techniques. Results showed that the proposed technique outperforms all previous precoding-companding techniques in BER enhancement and OOB radiation reduction. The proposed technique reduces the Error Vector Magnitude (EVM) by 15 dB compared with 10 dB for the best previous technique. Additionally, the proposed technique increases high power amplifier efficiency (HPA) by 11.4%, while the best previous technique increased HPA efficiency by 9.8%. Moreover, our proposal achieves PAPR reduction gain better than the most known powerful PAPR reduction technique with a 99% reduction in required computational complexity.

摘要

由于其优势,几种高速无线系统采用了正交频分复用(OFDM)。5G已经采用了OFDM,并有望在5G之后(B5G)得到考虑。同时,OFDM存在高峰均功率比(PAPR)问题。两种PAPR降低技术之间的混合获得了这两种技术的优势。混合预编码-压扩技术很有吸引力,因为它们实现高PAPR降低增益所需的计算复杂度较小。为了提高PAPR降低增益,人们引入了许多预编码-压扩技术。然而,降低误码率(BER)和带外(OOB)辐射比提高PAPR降低增益更为重要。本文提出了一种新的预编码-压扩技术,与以前的预编码-压扩技术相比,能更好地降低BER和OOB辐射。结果表明,所提出的技术在BER增强和OOB辐射降低方面优于所有以前的预编码-压扩技术。与之前最好的技术降低10 dB相比,所提出的技术将误差矢量幅度(EVM)降低了15 dB。此外,所提出的技术将高功率放大器效率(HPA)提高了11.4%,而之前最好的技术将HPA效率提高了9.8%。此外,我们的方案在所需计算复杂度降低99%的情况下,实现了比最著名的强大PAPR降低技术更好的PAPR降低增益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/3fb65395acf8/sensors-21-01410-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/1ed29f94819b/sensors-21-01410-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/1dda4fed3f03/sensors-21-01410-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/d24a180fdc8d/sensors-21-01410-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/e0982925bea5/sensors-21-01410-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/0a127db69faf/sensors-21-01410-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/de59c2c8663d/sensors-21-01410-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/7a9ab5cafd88/sensors-21-01410-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/e191f7b7ca95/sensors-21-01410-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/50357ac4ee13/sensors-21-01410-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/a44113f96494/sensors-21-01410-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/502318f4fc58/sensors-21-01410-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/bad3bfa61321/sensors-21-01410-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/3fb65395acf8/sensors-21-01410-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/1ed29f94819b/sensors-21-01410-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/1dda4fed3f03/sensors-21-01410-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/d24a180fdc8d/sensors-21-01410-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/e0982925bea5/sensors-21-01410-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/0a127db69faf/sensors-21-01410-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/de59c2c8663d/sensors-21-01410-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/7a9ab5cafd88/sensors-21-01410-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/e191f7b7ca95/sensors-21-01410-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/50357ac4ee13/sensors-21-01410-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/a44113f96494/sensors-21-01410-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/502318f4fc58/sensors-21-01410-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/bad3bfa61321/sensors-21-01410-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d7f/7922168/3fb65395acf8/sensors-21-01410-g013.jpg

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