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access icon free On information-theoretic limits of code-domain NOMA for 5G

© The Institution of Engineering and Technology
Received 31/01/2018, Accepted 10/07/2018, Revised 28/06/2018, Published 13/07/2018

Motivated by recent theoretical challenges for 5G, this study aims to position relevant results in the literature on code-domain non-orthogonal multiple access (NOMA) from an information-theoretic perspective, given that most of the recent intuition of NOMA relies on another domain, that is, the power domain. Theoretical derivations for several code-domain NOMA schemes are reported and interpreted, adopting a unified framework that focuses on the analysis of the NOMA spreading matrix, in terms of load, sparsity, and regularity features. The comparative analysis shows that it is beneficial to adopt extreme low-dense code-domain NOMA in the large system limit, where the number of resource elements and number of users grow unboundedly while their ratio, called load, is kept constant. Particularly, when optimum receivers are used, the adoption of a regular low-dense spreading matrix is beneficial to the system achievable rates, which are higher than those obtained with either irregular low-dense or dense formats, for any value of load. For linear receivers, which are more favourable in practice due to lower complexity, the regular low-dense NOMA still has better performance in the underloaded regime (load ), while the irregular counterpart outperforms all the other schemes in the overloaded scenario (load ).

Inspec keywords: matrix algebra; information theory; multi-access systems; 5G mobile communication

Other keywords: extreme low-dense code-domain NOMA; regular low-dense NOMA; sparsity feature; NOMA spreading matrix; 5G; load feature; information-theoretic limits; system achievable rates; code-domain nonorthogonal multiple access; regular low-dense spreading matrix; number-of-resource elements; regularity feature; code-domain NOMA schemes

Subjects: Algebra; Mobile radio systems; Multiple access communication

References

    1. 1)
      • 5. Learned, R.E., Willsky, A.S., Boroson, D.M.: ‘Low complexity optimal joint detection for oversaturated multiple access communications’, IEEE Trans. Signal Process., 1997, 45, (1), pp. 113–123.
    2. 2)
      • 12. Ferrante, G.C., Di Benedetto, M.G.: ‘Spectral efficiency of random time-hopping CDMA’, IEEE Trans. Inf. Theory, 2015, 61, (12), pp. 6643–6662.
    3. 3)
      • 28. Yoshida, M., Tanaka, T.: ‘Analysis of sparsely-spread CDMA via statistical mechanics’. Proc. IEEE Symp. Information Theory Workshop (ISIT), Seattle, WA, USA, 2006, pp. 2378–2382.
    4. 4)
      • 6. Andrews, J.G.: ‘Interference cancellation for cellular systems: a contemporary overview’, IEEE Wirel. Commun., 2005, 12, (2), pp. 19–29.
    5. 5)
      • 7. Ding, Z., Liu, Y., Choi, J., et al: ‘Application of non-orthogonal multiple access in LTE and 5G networks’, IEEE Commun. Mag., 2017, 55, (2), pp. 185–191.
    6. 6)
      • 29. Guo, D., Wang, C.: ‘Multiuser detection of sparsely spread CDMA’, IEEE J. Sel. Areas Commun., 2008, 26, (3), pp. 421–431.
    7. 7)
      • 17. Dai, X., Chen, S., Sun, S., et al: ‘Successive interference cancelation amenable multiple access (SAMA) for future wireless communications’. Proc. IEEE Int. Conf. Communications (ICC), Macau, China, 2014, pp. 222–226.
    8. 8)
      • 8. Shamai, S., Verdú, S.: ‘The impact of frequency-flat fading on the spectral efficiency of CDMA’, IEEE Trans. Inf. Theory, 2001, 47, (4), pp. 1302–1327.
    9. 9)
      • 20. Zeng, J., Li, B., Su, X., et al: ‘Pattern division multiple access (PDMA) for cellular future radio access’. Proc. IEEE Wireless Communications and Signal Processing (WCSP), Nanjing, China, 2015, pp. 1–5.
    10. 10)
      • 13. Le, M.T.P., Ferrante, G.C., Quek, T.Q.S., et al: ‘Fundamental limits of low-density spreading NOMA with fading’, IEEE Trans. Wirel. Commun., 2018, 17, (7), pp. 4648–4659.
    11. 11)
      • 25. Tulino, A.M., Verdú, S.: ‘Spectral efficiency of multicarrier CDMA’, IEEE Trans. Inf. Theory, 2005, 51, (2), pp. 479–505.
    12. 12)
      • 18. Yuan, Z., Yu, G., Li, W., et al: ‘Multi-user shared access for internet of things’. Proc. IEEE Vehicular Technology Conf. (VTC- Spring), Nanjing, China, 2016, pp. 1–5.
    13. 13)
      • 3. Lien, S.Y., Shieh, S.L., Huang, Y., et al: ‘5G new radio: waveform, frame structure, multiple access, and initial access’, IEEE Commun Mag, 2017, 55, (6), pp. 64–71.
    14. 14)
      • 16. Hoshyar, R., Wathan, F.P., Tafazolli, R.: ‘Novel low-density signature for synchronous CDMA systems over AWGN channel’, IEEE Trans. Signal Process., 2008, 56, (4), pp. 1616–1626.
    15. 15)
      • 10. Shental, O., Zaidel, B.M., Shamai, S.: ‘Low-density code-domain NOMA: better be regular’. Proc. IEEE Int. Symp. on Inf. Theory (ISIT), Aachen, Germany, 2017, pp. 2628–2632.
    16. 16)
      • 27. Montanari, A., Tse, D.: ‘Analysis of belief propagation for non-linear problems: the example of CDMA (or: how to prove Tanaka's formula)’. Proc. IEEE Symp. Information Theory Workshop (ISIT), Punta del Este, Uruguay, 2006, pp. 160–164.
    17. 17)
      • 15. Ping, L., Liu, L., Wu, K., et al: ‘Interleave division multiple-access’, IEEE Trans. Wirel. Commun., 2006, 4, (5), pp. 938–947.
    18. 18)
      • 24. Moltafet, M., Mokari, N., Javan, M.R., et al: ‘A new multiple access technique for 5G: power domain sparse code multiple access (PSMA)’, IEEE Access, 2018, 6, pp. 747–759.
    19. 19)
      • 4. Dai, L., Wang, B., Yuan, Y., et al: ‘Non-orthogonal multiple access for 5G: solutions, challenges, opportunities, and future research trends’, IEEE J. Sel. Areas Commun., 2015, 53, (9), pp. 74–81.
    20. 20)
      • 22. AI-Imari, M., Imran, M.A., Xiao, P.: ‘Radio resource allocation for multicarrier low-density-spreading multiple access’, IEEE Trans on Veh Tech, 2017, 66, (3), pp. 2382–2393.
    21. 21)
      • 19. Chen, S., Ren, B., Gao, Q., et al: ‘Pattern division multiple access- a novel nonorthogonal multiple access for fifth- generation radio networks’, IEEE Trans. Veh. Technol., 2017, 66, (4), pp. 3185–3196.
    22. 22)
      • 1. Ding, Z., Lei, X., Karagiannidis, G.K., et al: ‘A survey on non-orthogonal multiple access for 5 g networks: research challenges and future trends’, IEEE J Sel. Areas Commun., 2017, 35, (10), pp. 2181–2195.
    23. 23)
      • 2. ‘3GPP Portal, Available at https://portal.3gpp.org/’, accessed 20 June, 2018.
    24. 24)
      • 9. Raymond, J., Saad, D.: ‘Sparsely spread CDMA: a statistical mechanics-based analysis’, J. Phys. A, Math. Theor., 2007, 40, (41), pp. 12315–12333.
    25. 25)
      • 26. Qin, Z., Yue, X., Liu, Y., et al: ‘User association and resource allocation in unified non-orthogonal multiple access enabled heterogeneous ultra dense networks’, IEEE Commun. Mag., 2018, 56, (6), pp. 86–92.
    26. 26)
      • 30. Zaidel, B.M., ‘Personal communications’, 2018.
    27. 27)
      • 14. Li, K., Wang, X., Ping, L.: ‘Analysis and optimization of interleave-division multiple-access communication systems’, IEEE Trans. Wirel. Commun., 2007, 5, (6), pp. 1973–1982.
    28. 28)
      • 11. Zaidel, B.M., Shental, O., Shamai, S.: ‘Sparse NOMA: a closed-form characterization’. Proc. IEEE Int. Symp. on Inf. Theory (ISIT), Vail, CO, USA, 2018, pp. 1106–1110.
    29. 29)
      • 23. Nikopour, H., Baligh, H.: ‘Sparse code multiple access’. Proc. IEEE Annual Int. Symp. Personal, Indoor, and Mobile Radio Communications (PIMRC), London, UK, 2013, pp. 332–336.
    30. 30)
      • 21. Verdú, S., Shamai, S.: ‘Spectral efficiency of CDMA with random spreading’, IEEE Trans. Inf. Theory, 1999, 45, (2), pp. 622–640.
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