Skip to main content

Advertisement

SpringerLink
Log in

An Optimum Probabilistic Shaping Based Uplink SCMA Codebook Design using Hybrid Firefly-Bat Algorithm

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Sparse Code Multiple Access (SCMA) is a potential Non-Orthogonal Multiple Access (NOMA) scheme that is widely employed in 5G wireless networks to address rigid improvisations through system capacity, reduced latency, and user-controlled connection. The design of the optimum codebook is critical to the operation of the uplink SCMA-based NOMA system. This paper proposes an optimum parity check polar coding (PCPC)—Probabilistic Shaping(PS)-based uplink SCMA codebook design using a biologically inspired—Hybrid-Firefly—Bat algorithm (HFFBA) for the enhancement of average mutual information (AMI) and a reduction in the bit error rate (BER). The application of optimal PCPC aids in reducing the receiver complexity in the uplink NOMA systems. Furthermore, the diversity gain and process reliability has been improved with the merging of PCPC with SCMA. The proposed system’s performance is evaluated over Rayleigh and Additive White Gaussian Noise (AWGN) channels for codebook size of 8 and 16 and aims to improve the performance through AMI and BER. The proposed HFFBA codebook achieved an SNR of 12 dB for AWGN and 18 dB for the Rayleigh channel for M = 4 for a BER of 10–3. The same was attained at an SNR of 21.4 dB for AWGN and 23.6 dB for the Rayleigh channel for M = 16. The gain in SNR for M = 4 to16 for the AWGN and Rayleigh channels are 9.4 dB and 5.6 dB respectively. The optimized codebooks with such biologically inspired algorithms adapt to the changing wireless network conditions and could achieve an increase in data rate and reduced error rate compared to existing systems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Data availability

Data will be available upon request.

Code availability

The code that support the findings of this study are available on request from the corresponding author. The code is not publicly available due to containing information that could compromise the privacy of research participants.

References

  1. Mathur, H., & Deepa, T. (2021). A survey on advanced multiple access techniques for 5G and beyond wireless communications. Wireless Personal Communications, 118(2), 1775–1792. https://doi.org/10.1007/s11277-021-08115-w

    Article  Google Scholar 

  2. Alibakhshikenari, M., Ali, E. M., Soruri, M., Dalarsson, M., Naser-Moghadasi, M., Virdee, B. S., & Limiti, E. (2022). A comprehensive survey on antennas on-chip based on metamaterial, metasurface, and substrate integrated waveguide principles for millimeter-waves and terahertz integrated circuits and systems. IEEE Access. https://doi.org/10.1109/access.2021.3140156

    Article  Google Scholar 

  3. Alibakhshikenari, M., Virdee, B. S., Azpilicueta, L., Naser-Moghadasi, M., Akinsolu, M. O., See, C. H., & Limiti, E. (2020). A comprehensive survey of metamaterial transmission-line based antennas: Design, challenges, and applications. IEEE Access, 8, 144778–144808. https://doi.org/10.1109/access.2020.3013698

    Article  Google Scholar 

  4. Kazemian, M., Abouei, J., & Anpalagan, A. (2021). A low complexity enhanced-NOMA scheme to reduce inter-user interference, BER, and PAPR in 5G wireless systems. Physical Communication, 48, 101412. https://doi.org/10.1016/j.phycom.2021.101412

    Article  Google Scholar 

  5. Yu, L., Liu, Z., Wen, M., Cai, D., Dang, S., Wang, Y., & Xiao, P. (2021). Sparse code multiple access for 6G wireless communication networks: Recent advances and future directions. IEEE Communications Standards Magazine. https://doi.org/10.1109/mcomstd.001.2000049

    Article  Google Scholar 

  6. Liu, Y., Xiang, L., Yang, L. L., & Hanzo, L. (2021). Space-time coded generalized spatial modulation for sparse code division multiple access. IEEE Transactions on Wireless Communications, 20(8), 5359–5372. https://doi.org/10.1109/twc.2021.3067376

    Article  Google Scholar 

  7. Qu, Z., & Djordjevic, I. B. (2019). On the probabilistic shaping and geometric shaping in optical communication systems. IEEE Access, 7, 21454–21464. https://doi.org/10.1109/access.2019.2897381

    Article  Google Scholar 

  8. Barrueco, J., Montalban, J., Regueiro, C., Velez, M., Ordiales, J. L., Kim, H. M., & Kwon, S. (2017). Constellation design for bit-interleaved coded modulation (BICM) systems in advanced broadcast standards. IEEE Transactions on Broadcasting, 63(4), 603–614. https://doi.org/10.1109/tbc.2017.2677259

    Article  Google Scholar 

  9. Böcherer, G., Steiner, F., & Schulte, P. (2015). Bandwidth efficient and rate-matched low-density parity-check coded modulation. IEEE Transactions on communications, 63(12), 4651–4665. https://doi.org/10.1109/tcomm.2015.2494016

    Article  Google Scholar 

  10. İşcan, O., Böhnke, R., & Xu, W. (2019). Probabilistic shaping using 5G new radio polar codes. IEEE Access, 7, 22579–22587. https://doi.org/10.1109/access.2019.2898103

    Article  Google Scholar 

  11. Di, B., Song, L., & Li, Y. (2018). Trellis coded modulation for non-orthogonal multiple access systems: Design, challenges, and opportunities. IEEE Wireless Communications, 25(2), 68–74. https://doi.org/10.1109/mwc.2018.1700133

    Article  Google Scholar 

  12. Tang, J., Luo, J., Liu, M., So, D. K., Alsusa, E., Chen, G., & Chambers, J. A. (2019). Energy efficiency optimization for NOMA with SWIPT. IEEE Journal of Selected Topics in Signal Processing, 13(3), 452–466. https://doi.org/10.1109/jstsp.2019.2898114

    Article  Google Scholar 

  13. Cai, D., Ding, Z., Fan, P., & Yang, Z. (2018). On the performance of NOMA with hybrid ARQ. IEEE Transactions on Vehicular Technology, 67(10), 10033–10038. https://doi.org/10.1109/tvt.2018.2854184

    Article  Google Scholar 

  14. Zheng, H., Hou, S., Li, H., Song, Z., & Hao, Y. (2018). Power allocation and user clustering for uplink MC-NOMA in D2D underlaid cellular networks. IEEE Wireless Communications Letters, 7(6), 1030–1033. https://doi.org/10.1109/lwc.2018.2845398

    Article  Google Scholar 

  15. Zhai, D. (2017). Adaptive codebook design and assignment for energy saving in SCMA networks. IEEE Access, 5, 23550–23562. https://doi.org/10.1109/access.2017.2764120

    Article  Google Scholar 

  16. Peng, J., Chen, W., Bai, B., Guo, X., & Sun, C. (2017). Joint optimization of constellation with mapping matrix for SCMA codebook design. IEEE Signal Processing Letters, 24(3), 264–268. https://doi.org/10.1109/lsp.2017.2653845

    Article  Google Scholar 

  17. Huang, H., Zhao, H., Wang, F., & Li, J. (2018). Uplink grant-free multi-codebook SCMA based on high-overload codebook grouping. In 2018 IEEE/CIC International Conference on Communications in China (ICCC Workshops) (pp. 112–116). IEEE. https://doi.org/10.1109/iccchinaw.2018.8674466.

  18. Kim, M., Kim, N. I., Lee, W., & Cho, D. H. (2018). Deep learning-aided SCMA. IEEE Communications Letters, 22(4), 720–723. https://doi.org/10.1109/LCOMM.2018.2792019

    Article  Google Scholar 

  19. Liu, S., Wang, J., Bao, J., & Liu, C. (2018). Optimized SCMA codebook design by QAM constellation segmentation with maximized MED. IEEE Access, 6, 63232–63242. https://doi.org/10.1109/access.2018.2876030

    Article  Google Scholar 

  20. Wang, Q., Li, T., Feng, R., & Yang, C. (2019). An efficient large resource-user scale SCMA codebook design method. IEEE Communications Letters, 23(10), 1787–1790. https://doi.org/10.1109/lcomm.2019.2929766

    Article  Google Scholar 

  21. Hasan, S. M., Mahata, K., & Hyder, M. M. (2020). Sparse code multiple access codebook design using equiangular tight frames. In ICC 2020–2020 IEEE International Conference on Communications (ICC) (pp. 1–6). IEEE. https://doi.org/10.1109/icc40277.2020.9148752.

  22. Hou, Z., Xiang, Z., Ren, P., & Cao, B. (2021). SCMA codebook design based on divided extended mother codebook. IEEE Access, 9, 71563–71576. https://doi.org/10.1109/access.2021.3078568

    Article  Google Scholar 

  23. Liang, Z., Liu, Y., Lok, T. M., & Huang, K. (2021). Multi-cell mobile edge computing: Joint service migration and resource allocation. IEEE Transactions on Wireless Communications, 20(9), 5898–5912. https://doi.org/10.1109/twc.2021.3070974

    Article  Google Scholar 

  24. Chen, Y. M., González, C. D. S., Wang, P. H., & Chen, K. P. (2021). Reinforcement learning-based SCMA codebook design for uplink rayleigh fading channels. IEEE Wireless Communications Letters, 10(8), 1717–1721. https://doi.org/10.1109/lwc.2021.3077986

    Article  Google Scholar 

  25. Thirunavukkarasu, R., & Balasubramanian, R. (2021). An efficient code domain NOMA scheme with enhanced spectral and energy efficiency for networks beyond 5G. Wireless Personal Communications, 120(1), 353–377. https://doi.org/10.1007/s11277-021-08464-6

    Article  Google Scholar 

  26. Wang, T., Qu, D., & Jiang, T. (2016). Parity-check-concatenated polar codes. IEEE Communications Letters, 20(12), 2342–2345.

    Article  Google Scholar 

  27. Jiang, C., & Wang, Y. (2020). An uplink SCMA codebook design combining probabilistic shaping and geometric shaping. IEEE Access, 8, 76726–76736. https://doi.org/10.1109/access.2020.2989448

    Article  Google Scholar 

  28. Qi, X., Zhu, S., & Zhang, H. (2017). A hybrid firefly algorithm. In 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) (pp. 287–291). IEEE. https://doi.org/10.1109/iaeac.2017.8054023.

  29. Singh, D., Salgotra, R., & Singh, U. (2017). A novel modified bat algorithm for global optimization. In 2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS) (pp. 1–5). IEEE. https://doi.org/10.1109/iciiecs.2017.8275904.

  30. Hariharan, B., & Raj, D. P. (2019). A hybrid framework for job scheduling on the cloud using firefly and BAT algorithm. International Journal of Business Intelligence and Data Mining, 15(4), 388–407. https://doi.org/10.1504/ijbidm.2019.102811

    Article  Google Scholar 

  31. Taherzadeh, M., Nikopour, H., Bayesteh, A., & Baligh, H. (2014). SCMA codebook design. In 2014 IEEE 80th Vehicular Technology Conference (VTC2014-Fall) IEEE (pp. 1–5). https://doi.org/10.1109/vtcfall.2014.6966170.

  32. Yu, L., Fan, P., Cai, D., & Ma, Z. (2018). Design and analysis of SCMA codebook based on star-QAM signaling constellations. IEEE transactions on vehicular technology, 67(11), 10543–10553. https://doi.org/10.1109/tvt.2018.2865920

    Article  Google Scholar 

  33. Hoshyar, R., Wathan, F. P., & Tafazolli, R. (2008). Novel low-density signature for synchronous CDMA systems over AWGN channel. IEEE Transactions on Signal Processing, 56(4), 1616–1626. https://doi.org/10.1109/tsp.2007.909320

    Article  MathSciNet  MATH  Google Scholar 

  34. Larsson, P., Rasmussen, L. K., & Skoglund, M. (2018). Golden angle modulation: Approaching the AWGN capacity. arXiv preprint arXiv:1802.10022. https://doi.org/10.48550/arXiv.1802.10022

  35. Larsson, P. (2017). Golden angle modulation. IEEE Wireless Communications Letters, 7(1), 98–101. https://doi.org/10.1109/lwc.2017.2756630

    Article  Google Scholar 

  36. Gao, M., Ge, W., Zhang, P., & Zhang, Y. (2020). An efficient codebook design for uplink SCMA. IEEE Access, 8, 211665–211675. https://doi.org/10.1109/access.2020.3038192

    Article  Google Scholar 

  37. Zhou, Y., Yu, Q., Meng, W., & Li, C. (2017). SCMA codebook design based on constellation rotation. In 2017 IEEE International Conference on Communications (ICC) IEEE (pp. 1–6). https://doi.org/10.1109/icc.2017.7996395.

  38. Mheich, Z., Wen, L., Xiao, P., & Maaref, A. (2018). Design of SCMA codebooks based on golden angle modulation. IEEE Transactions on Vehicular Technology, 68(2), 1501–1509. https://doi.org/10.1109/tvt.2018.2886953

    Article  Google Scholar 

  39. Zhang, X., Han, G., Zhang, D., Zhang, D., & Yang, L. (2019). An efficient SCMA codebook design based on lattice theory for information-centric IoT. IEEE Access, 7, 133865–133875. https://doi.org/10.1109/access.2019.2938637

    Article  Google Scholar 

Download references

Funding

No funding was received to assist with the preparation of this manuscript.

Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu District, Tamil Nadu, 603203, India

    Ramya Thirunavukkarasu, Ramachandran Balasubramanian & Vidhyacharan Bhaskar

  2. Department of Computer Engineering, San Jose State University, San Jose, CA, USA

    Vidhyacharan Bhaskar

  3. Department of Computer Science, University of California at Davis, Davis, CA, 95616, USA

    Vidhyacharan Bhaskar

Authors
  1. Ramya Thirunavukkarasu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ramachandran Balasubramanian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vidhyacharan Bhaskar
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

RT: Conceptualization, Methodology, Software. Writing—original draft. RB: Investigation, Visualization, Reviewing—original draft. VB: Supervision, Writing, Editing, review & editing.

Corresponding author

Correspondence to Ramya Thirunavukkarasu.

Ethics declarations

Conflicts of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Thirunavukkarasu, R., Balasubramanian, R. & Bhaskar, V. An Optimum Probabilistic Shaping Based Uplink SCMA Codebook Design using Hybrid Firefly-Bat Algorithm. Wireless Pers Commun 130, 527–549 (2023). https://doi.org/10.1007/s11277-023-10297-4

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-023-10297-4

Keywords

Search

Navigation