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Published on 7 February 2024
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Zhao,L. (2024). Comparisons of PSK, APSK, and QAM over AWGN and fading channels. Applied and Computational Engineering,36,53-63.
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Comparisons of PSK, APSK, and QAM over AWGN and fading channels

Lingxiao Zhao *,1,
  • 1 University of Bristol

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/36/20230423

Abstract

In addition to the thermal noise, communication systems can normally experience various fading because of objects reflecting the signal. PSK, APSK, and QAM modulation schemes are widely used in communication systems. It is thus essential to know how well these schemes can perform in different fading channels. This research explores the BER performance of these modulation schemes in common and typical channel models including AWGN, Rayleigh fading, Rician fading, and Nakagami fading channels by simulations in MATLAB. The BER curves over a range of SNR and symbol constellation diagrams are obtained. It is found that Rayleigh and Nakagami fading distort signals most and impacts of Rician fading in LoS case and AWGN can be mitigated significantly by increasing the SNR. Furthermore, the QAM has better BER performance in fading channels while PSK and APSK perform better in AWGN channels when the number of bits of one symbol is relatively small. Selections of modulation schemes should depend on the specific circumstances and the optimization of them is required when large numbers of bits are transmitted by one symbol.

Keywords

APSK, QAM, fading channels

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Cite this article

Zhao,L. (2024). Comparisons of PSK, APSK, and QAM over AWGN and fading channels. Applied and Computational Engineering,36,53-63.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 2023 International Conference on Machine Learning and Automation

Conference website: https://2023.confmla.org/
ISBN:978-1-83558-297-8(Print) / 978-1-83558-298-5(Online)
Conference date: 18 October 2023
Editor:Mustafa İSTANBULLU
Series: Applied and Computational Engineering
Volume number: Vol.36
ISSN:2755-2721(Print) / 2755-273X(Online)

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