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PAPR Reduction of NOMA Using Vandermonde Matrix-Particle Transmission Sequence

Arun Kumar1,*, Sandeep Gupta2, Himanshu Sharma3, Mehedi Masud4

1 Department of Electronics and Communication Engineering, JECRC University, Jaipur, 303905, India
2 Department of Electrical Engineering, JECRC University, Jaipur, 303905, India
3 Department of Computer Science and Engineering, JECRC University, Jaipur, 303905, India
4 Department of Computer Science, College of Computers and Information Technology, Taif University, 11099, Saudi Arabia

* Corresponding Author: Arun Kumar. Email:

Computer Systems Science and Engineering 2022, 43(1), 193-201.


Non-Orthogonal Multiple Access (NOMA) is an ideal choice for 5G waveforms due to their characteristics such as high data rate, massive device connectivity, high spectral access, and effective frequency selective fading. Thus, it permits gigantic connectivity. The spectrum overlaps with NOMA, which consents several operators to segment the spectrum at the same frequency. These features make NOMA more suitable for use beyond 5G. Peak to Average Power (PAPR) is a major problem in Multi-Carrier Techniques (MCT) like NOMA and it also degrades the performance of the amplifier. The Partial Transmission Sequence (PTS) is a superior algorithm for moderating the PAPR. However, it also increases the complexity of the structure. The PAPR is reduced in NOMA by multiplying the NOMA signal with optimised phase vectors (P). The phase vectors are generated by using the Vandermonde Matrix (VM). In this work, we proposed a VM-PTS algorithm for the NOMA system, and the number of computations to search the optimal phase vectors for NOMA high PAPR signal is less as compared with existing PTS. The outcomes demonstrate that the performance of the recommended PTS in terms of PAPR, Bit Error Rate (BER), and complexity is better than the conventional PTS (C-PTS).


Cite This Article

A. Kumar, S. Gupta, H. Sharma and M. Masud, "Papr reduction of noma using vandermonde matrix-particle transmission sequence," Computer Systems Science and Engineering, vol. 43, no.1, pp. 193–201, 2022.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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