Cover
Vol. 21 No. 2 (2025)

Published: December 16, 2025

Pages: 251-264

Original Article

Performance of Sparse Code Multiple Access Communication System Based on Logarithmic Message Passing Algorithm and Low-Density Parity Check Code

Mustafa Moafaq 1 Maher Al-Azawi
1Electrical Engineering Department, College of Engineering, Mustansiriyah University, Baghdad, Iraq
History
  • Received: March 22, 2024
  • Revised: June 10, 2024
  • Accepted: June 20, 2024
  • Available Online: February 28, 2025
DOI

https://doi.org/10.37917/ijeee.21.2.23

Abstract

The performance of Sparse Code Multiple Access (SCMA) communication system with Logarithmic Message Passing Algorithm (log-MPA) decoder is introduced. To boost the performance, a Low-Density Parity-Check Code LDPC is used together with Belief Propagation (BP) decoder. LDPC is chosen due to its sparsity property that complements the sparsity nature of SCMA for maximum efficiency and minimum complexity. Three distinct SCMA configurations are used. These are: A (4 x 4 x 6), B (4 x 16 x 6), and C (5 x 4 x 10) where the (K x M x V) are numbers of resources, codewords and users respectively. The performance of these configuration is shown in various channel conditions, various LDPC code rates and various numbers of SCMA iterations (NSCMA), to find the local minimum value of log-MPA. Simulation results showed that the LDPC greatly boosted the performance in mentioned configurations: In A configuration, a gain of 13 dB was observed. Configuration B experienced a substantial improvement of 23.5 dB, while C achieved a gain of 20.5 dB. Notably, configuration B stood out with the highest gain, attributed to LDPC’s exceptional performance with high data rates, as the data transmitted in B was double that of A.

Keywords

References

  1. Y. Zhou, Q. Yu, W. Meng, and C. Li, “SCMA codebook design based on constellation rotation,” in 2017 IEEE International Conference on Communications (ICC), (Paris, France), pp. 1–6, 2017.
  2. L. Dai, B. Wang, Y. Yuan, S. Han, C. I, and Z. Wang, “Nonorthogonal multiple access for 5G: Solutions, challenges, opportunities, and future research trends,” IEEE Communication Magazine, vol. 53, pp. 74–81, Sept. 2015.
  3. S. M. R. Islam, M. Zeng, and O. A. Dobre, “NOMA in 5G systems: Exciting possibilities for enhancing spectral efficiency,” IEEE 5G Tech Focus, vol. 1, pp. 1–6, Jun. 2017.
  4. D. Evans, “The Internet of Things: How the Next Evolution of the Internet is Changing Everything,” 2011. [Online].
  5. R. Hoshyar, R. Razavi, and M. Al-Imari, “LDS-OFDM an Efficient Multiple Access Technique,” in 2010 IEEE 71st Vehicular Technology Conference, (Taipei, Taiwan), pp. 1–5, 2010.
  6. R. Razavi, R. Hoshyar, M. A. Imran, and Y. Wang, “Information Theoretic Analysis of LDS Scheme,” IEEE Communications Letters, vol. 15, pp. 798–800, August 2011.
  7. H. Nikopour and H. Baligh, “Sparse code multiple access,” in 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), (London, UK), pp. 332–336, 2013.
  8. R. Hoshyar, F. P. Wathan, and R. Tafazolli, “Novel Low-Density Signature for Synchronous CDMA Systems Over AWGN Channel,” IEEE Transactions on Signal Processing, vol. 56, pp. 1616–1626, April 2008.
  9. Y. Wu, S. Zhang, and Y. Chen, “Iterative multiuser receiver in sparse code multiple access systems,” in Proc. IEEE ICC, (London, U.K.), pp. 2918–2923, 2015.
  10. S. Zhang et al., “Sparse code multiple access: An energy efficient up link approach for 5G wireless systems,” in Proc. IEEE Global Commun. Conf. (GLOBECOM’14), (Austin, TX, USA), pp. 4782–4787, 2014.
  11. Z. Pan, E. Li, L. Zhang, J. Lei, and C. Tang, “Design and Optimization of Joint Iterative Detection and Decoding Receiver for Uplink Polar Coded SCMA System,” IEEE Access, vol. 6, pp. 52014–52026, 2018.
  12. B. Tahir, S. Schwarz, and M. Rupp, “BER comparison between Convolutional, Turbo, LDPC, and Polar codes,” in 2017 24th International Conference on Telecommunications (ICT), (Limassol, Cyprus), pp. 1–7, 2017.
  13. Y. A. Muhammed and R. Z. Yousif, “Investigating the Effect of Different Channel Coding on the Performance of Sparse Code Multiple Access over AWGN Channel,” Wireless Pers Commun, 2023.
  14. C. Berrou, A. Glavieux, and P. Thitimajshima, “Near Shannon limit error-correcting coding and decoding: Turbo-codes,” IEEE Transactions on Communications, vol. 44, no. 10, pp. 1261–1271, 1993.
  15. E. Arıkan, “Channel polarization: A method for constructing capacity-achieving codes for symmetric binaryinput memoryless channels,” IEEE Transactions on Information Theory, vol. 55, no. 7, pp. 3051–3073, 2009.
  16. R. G. Gallager, Low-Density Parity-Check Codes. Cambridge, MA: MIT Press, 1963.
  17. “The Performance Evaluation of Multi User OFDM Orthogonal Chaotic Vector Shift Keying Supported by LDPC,” J. eng. sustain. dev., vol. 26, pp. 62–72, May 2022.
  18. S. Chaturvedi, Z. Liu, V. A. Bohara, A. Srivastava, and P. Xiao, “A Tutorial on Decoding Techniques of Sparse Code Multiple Access,” IEEE Access, vol. 10, pp. 58503– 58524, 2022.
  19. European Telecommunications Standards Institute, “ETSI Standard EN 302 307 V1.4.1: Digital Video Broadcasting (DVB); Second generation framing structure, channel coding and modulation systems for Broadcasting, Interactive Services, News Gathering and other broadband satellite applications (DVB-S2),” 2005.
  20. “IEEE Std 802.11-2020 (Revision of IEEE Std 802.11- 2016). Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. IEEE Standard for Information technology — Telecommunications and information exchange between systems. Local and metropolitan area networks — Specific requirements,” 2020.
  21. D. E. Hocevar, “A reduced complexity decoder architecture via layered decoding of LDPC codes,” in IEEE Workshop on Signal Processing Systems, 2004. SIPS 2004., (Austin, TX, USA), pp. 107–112, 2004.
  22. E. A. Hussien and G. Abdulkareem, “Rayleigh fading channel estimation based on Generalized RegressionNeural Networks,” J. eng. sustain. dev., vol. 27, Mar. 2023.
  23. G. A. A.-K. Al-Rubyai, “Diversity Combining for DS CDMA System in a Rayleigh Fading Channel with Three Spreading Codes,” J. eng. sustain. dev., vol. 11, Mar. 2007.
  24. V. P. Klimentyev and A. B. Sergienko, “Detection of SCMA signal with channel estimation error,” in 2016 18th Conference of Open Innovations Association and Seminar on Information Security and Protection of Information Technology (FRUCT-ISPIT), (St. Petersburg, Russia), pp. 106–112, 2016.
  25. S. ten Brink, “Convergence behavior of iteratively decoded parallel concatenated codes,” IEEE Transactions on Communications, vol. 49, pp. 1727–1737, Oct. 2001.
  26. Z. Liu and L. L. Yang, “Sparse or dense: A comparative study of code-domain NOMA systems,” IEEE Transactions on Wireless Communications, vol. 20, pp. 4768– 4780, Mar. 2021.
  27. F. Wei and W. Chen, “Low Complexity Iterative Receiver Design for Sparse Code Multiple Access,” IEEE Transactions on Communications, vol. 65, pp. 621–634, Feb. 2017.
  28. W. C. Sun, Y. C. Su, Y. L. Ueng, and C. H. Yang, “An LDPC-Coded SCMA ReceiverWith Multi-User Iterative Detection and Decoding,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 66, pp. 3571–3584, Sept. 2019.