A Low-Complexity Coding Scheme for NOMA

This work focuses on exploiting the constructive interference among different users' data waveforms to introduce new coding and decoding techniques, which are specifically designed for nonorthogonal multiple access (NOMA) systems. In this article, a structured coding scheme is devised. In essen...

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Veröffentlicht in:IEEE systems journal 2023-09, Vol.17 (3), p.1-10
Hauptverfasser: Abd-Alaziz, Wael, Jebur, Bilal A., Fakhrey, Harih, Mei, Zhen, Rabie, Khaled
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container_issue 3
container_start_page 1
container_title IEEE systems journal
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creator Abd-Alaziz, Wael
Jebur, Bilal A.
Fakhrey, Harih
Mei, Zhen
Rabie, Khaled
description This work focuses on exploiting the constructive interference among different users' data waveforms to introduce new coding and decoding techniques, which are specifically designed for nonorthogonal multiple access (NOMA) systems. In this article, a structured coding scheme is devised. In essence, the proposed technique focuses on finding a relationship between the sent users' data waveforms and then uses this relationship in the decoding process at the receiving destination. It is worth pointing out that the proposed coding and decoding techniques exhibit better performance and reduced the complexity compared with the conventional uncoded NOMA. The complexity order evaluation shows that the proposed scheme attains a reduction in the required number of the floating point operations of \text{5} and \text{6}\,N at the second and third users, respectively, compared with that of the uncoded NOMA. Moreover, we have derived a closed-form expression for the bit error rate, which is verified using the Monte Carlo simulation. To demonstrate the practicality of the proposed system, the obtained results are compared with those of the uncoded and convolutional coding NOMA systems. Finally, the performance of the proposed system outperformed the conventional systems by an average of 5 dB in the case of two users and an average of 15 dB in the case of three users in the same work environment.
doi_str_mv 10.1109/JSYST.2023.3262174
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In this article, a structured coding scheme is devised. In essence, the proposed technique focuses on finding a relationship between the sent users' data waveforms and then uses this relationship in the decoding process at the receiving destination. It is worth pointing out that the proposed coding and decoding techniques exhibit better performance and reduced the complexity compared with the conventional uncoded NOMA. The complexity order evaluation shows that the proposed scheme attains a reduction in the required number of the floating point operations of <inline-formula><tex-math notation="LaTeX">\text{5}</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">\text{6}\,N</tex-math></inline-formula> at the second and third users, respectively, compared with that of the uncoded NOMA. Moreover, we have derived a closed-form expression for the bit error rate, which is verified using the Monte Carlo simulation. To demonstrate the practicality of the proposed system, the obtained results are compared with those of the uncoded and convolutional coding NOMA systems. 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To demonstrate the practicality of the proposed system, the obtained results are compared with those of the uncoded and convolutional coding NOMA systems. Finally, the performance of the proposed system outperformed the conventional systems by an average of 5 dB in the case of two users and an average of 15 dB in the case of three users in the same work environment.]]></abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JSYST.2023.3262174</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0003-1621-7733</orcidid><orcidid>https://orcid.org/0000-0003-4814-7899</orcidid><orcidid>https://orcid.org/0000-0002-9769-0604</orcidid><orcidid>https://orcid.org/0000-0002-7724-2636</orcidid><orcidid>https://orcid.org/0000-0002-2624-8616</orcidid><orcidid>https://orcid.org/0000-0002-9784-3703</orcidid><oa>free_for_read</oa></addata></record>
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subjects Binary phase shift keying
Bit error rate
Coding
Complexity
Complexity theory
Constructive interference
convolutional codes
Decoding
Encoding
Floating point arithmetic
Interference
low-complexity coding
Monte Carlo simulation
NOMA
Nonorthogonal multiple access
nonorthogonal multiple access (NOMA)
Resource management
Waveforms
Working conditions
title A Low-Complexity Coding Scheme for NOMA
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