JOURNAL ARTICLE

An Enhanced Probabilistic-Shaped SCMA NOMA for Wireless Networks.

  • Published In: Journal of Interconnection Networks, 2023, v. 23, n. 4. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Thirunavukkarasu, Ramya; Balasubramanian, Ramachandran 3 of 3

Abstract

The future digital evolution poses challenges that need to be spectral and energy-efficient, as well as highly reliable and resilient. The non-orthogonal multiple access (NOMA) accomplishes massive connectivity, spectral efficiency, effective bandwidth utilization, and low latency. The proposed work involves the code domain NOMA scheme called Sparse Code Multiple Access (SCMA) which provides shaping gain through multi-dimensional constellation and the best performance in terms of bit error rate (BER). It achieves overloading of users through the non-orthogonal allocation of resources which enhances the spectral efficiency and serves more users. The shaping gain can be further improved by reducing the BER and enhancing the capacity of the channel through constellation shaping. This work employs a probabilistic-shaped (PS) constellation where each symbol is transmitted with different probabilities which achieves a reduction of average symbol power and forward error correction (FEC) through channel coding using polar codes which aid in energy efficiency. The output is two-dimensionally spread over Orthogonal Frequency Code Division Multiplexing (OFCDM) subcarriers to achieve a flexible transmission rate through a variable spreading factor. Computer simulations showed better BER performance under AWGN and Rayleigh channels with remarkable gain in SNR which paves the way for future applications in Fifth Generation (5G) beyond networks. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Interconnection Networks. 2023/12, Vol. 23, Issue 4, p1
  • Document Type:Article
  • Subject Area:Communication and Mass Media
  • Publication Date:2023
  • ISSN:0219-2659
  • DOI:10.1142/S0219265923500032
  • Accession Number:163950220
  • Copyright Statement:Copyright of Journal of Interconnection Networks is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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