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Enhanced uplink non-orthogonal multiple access for 5G and beyond systems

Article

Abstract

Uplink non-orthogonal multiple access (NOMA) is a promising technique to meet the requirements of the fifth generation (5G) and beyond systems. Various NOMA schemes have been proposed in both academia and industry. However, most existing schemes assume equal average received power, which limits the performance. We propose three enhancements of uplink NOMA to achieve the requirements of massive connectivity and high reliability in 5G, where unequal average received power is exploited as part of the multiple access signature. First, the optimal sequences targeting to generalized Welch-bound equality (GWBE) are obtained for unequal average received power. Then user grouping with multi-level received powers is proposed for better successive interference cancellation (SIC) at the receiver. Finally, sequence grouping based on the cross-correlation properties of sequences is proposed to reduce inter- and intra-group interference. Simulation results show that by incorporating multi-level received powers and sequence grouping into existing NOMA schemes, for an NOMA system with 400% overloading and fixed signature allocation, 3 dB and 10 dB signal-to-noise ratio (SNR) gains at 0.1 block error rate (BLER) target can be achieved compared with existing NOMA schemes and orthogonal multiple access (OMA), respectively. Besides, 0.01 BLER target can be achieved while an error floor exists in existing NOMA schemes. Under random sequence selection, collision probability is reduced by multi-level powers. In addition, GWBE sequences achieve lower BLER than existing sequences and the gain is large especially for low BLER requirements. This shows that the proposed scheme can support larger connectivity and higher reliability.

Key words

Uplink non-orthogonal multiple access Generalized Welch-bound equality Multi-level received powers Sequence grouping 

CLC number

TN929.5 

References

  1. 3GPP, 2012. Physical channels and modulation (Release 11). Technical Report, TS-36.211.Google Scholar
  2. 3GPP, 2015. Study on downlink multiuser superposition transmission (MUST) for LTE (Release 13). Technical Report, TR-36.859. Belgrade, Serbia.Google Scholar
  3. 3GPP, 2016a. Sparse code multiple access (SCMA) for 5G radio transmission. Technical Report, TR1-162155. Busan, Korea.Google Scholar
  4. 3GPP, 2016b. Candidate new radio multiple access schemes. Technical Report, TR1-162202. Busan, Korea.Google Scholar
  5. 3GPP, 2016c. Discussion on multiple access for new radio interface. Technical Report, TR1-162226. Busan, Korea.Google Scholar
  6. 3GPP, 2016d. Candidate solution for new multiple access. Technical Report, TR1-162306. Busan, Korea.Google Scholar
  7. 3GPP, 2016e. Multiple access schemes for new radio interface. Technical Report, TR1-162385. Busan, Korea.Google Scholar
  8. 3GPP, 2016f. Considerations on downlink/uplink multiple access for new radio. Technical Report, TR1-162517. Busan, Korea.Google Scholar
  9. 3GPP, 2016g. Non-orthogonal multiple access candidate for new radio. Technical Report, TR1-163992. Nanjing, China.Google Scholar
  10. 3GPP, 2016h. Initial link-level simulation results for uplink non-orthogonal multiple access. Technical Report, TR1-164329. Nanjing, China.Google Scholar
  11. 3GPP, 2016i. Low code rate and signature based multiple access scheme for new radio. Technical Report, TR1-164869. Nanjing, China.Google Scholar
  12. 3GPP, 2016j. Non-orthogonal multiple access for new radio. Technical Report, TR1-165019. Nanjing, China.Google Scholar
  13. 3GPP, 2016k. Performance of interleave division multiple access (IDMA) in combination with OFDM family waveforms. Technical Report, TR1-165021. Nanjing, China.Google Scholar
  14. 3GPP, 2016l. On uplink non-orthogonal multiple access schemes. Technical Report, TR1-166552. Gothenburg, Sweden.Google Scholar
  15. 3GPP, 2016m. Non-orthogonal multiple access scheme based on non-orthogonal coded multiple access. Technical Report, TR1-166871. Gothenburg, Sweden.Google Scholar
  16. 3GPP, 2016n. Discussion on multiple access for uplink machine type communications. Technical Report, TR1-167392. Gothenburg, Sweden.Google Scholar
  17. 3GPP, 2016o. New uplink non-orthogonal multiple access schemes for new radio. Technical Report, TR1-167535. Gothenburg, Sweden.Google Scholar
  18. 3GPP, 2017a. Link-level simulation and preliminary performance comparison of non-orthogonal multiple access schemes. Technical Report, TR1-1720222. Reno, USA.Google Scholar
  19. 3GPP, 2017b. Study on new radio access technology physical layer aspects (Release 14). Technical Report, TR-38.802.Google Scholar
  20. 3GPP, 2017c. Study on channel model for frequencies from 0.5 to 100 GHz (Release 14). Technical Report, TR-38.901.Google Scholar
  21. Andrews JG, Buzzi S, Choi W, et al., 2014. What will 5G be? IEEE J Sel Areas Commun, 32(6):1065–1082. https://doi.org/10.1109/JSAC.2014.2328098 CrossRefGoogle Scholar
  22. Chen S, Ren B, Gao Q, et al., 2017. Pattern division multiple access—a novel nonorthogonal multiple access for the fifth-generation radio networks. IEEE Trans Veh Technol, 66(4):3185–3196. https://doi.org/10.1109/TVT.2016.2596438 CrossRefGoogle Scholar
  23. Chen X, Benjebbour A, Li A, et al., 2014. Multi-user proportional fair scheduling for uplink non-orthogonal multiple access (NOMA). 79th IEEE Conf on Vehicular Technology, p.1–5. https://doi.org/10.1109/VTCSpring.2014.7022998 Google Scholar
  24. Dahlman E, Mildh G, Parkvall S, et al., 2014. 5G wireless access: requirements and realization. IEEE Commun Mag, 52(12):42–47. https://doi.org/10.1109/MCOM.2014.6979985 CrossRefGoogle Scholar
  25. Dai L, Wang B, Yuan Y, et al., 2015. Non-orthogonal multiple access for 5G: solutions, challenges, opportunities, and future research trends. IEEE Commun Mag, 53(9):74–81. https://doi.org/10.1109/MCOM.2015.7263349 CrossRefGoogle Scholar
  26. Datta S, Howard S, Cochran D, 2012. Geometry of the Welch bounds. Linear Algebra & Its Appl, 437(10):2455–2470. https://doi.org/10.1016/j.laa.2012.05.036 MathSciNetCrossRefMATHGoogle Scholar
  27. Dhillon IS, Heath RW, Sustik MA, et al., 2005. Generalized finite algorithms for constructing Hermitian matrices with prescribed diagonal and spectrum. SIAM J Matr Anal Appl, 27(1):61–71. https://doi.org/10.1137/S0895479803438183 MathSciNetCrossRefMATHGoogle Scholar
  28. Ding Z, Adachi F, Poor HV, 2016a. The application of MIMO to non-orthogonal multiple access. IEEE Trans Wirel Commun, 15(1):537–552. https://doi.org/10.1109/TWC.2015.2475746 CrossRefGoogle Scholar
  29. Ding Z, Fan P, Poor HV, 2016b. Impact of user pairing on 5G nonorthogonal multiple-access downlink transmissions. IEEE Trans Veh Technol, 65(8):6010–6023. https://doi.org/10.1109/TVT.2015.2480766 CrossRefGoogle Scholar
  30. Endo Y, Kishiyama Y, Higuchi K, 2012. Uplink nonorthogonal access with MMSE-SIC in the presence of inter-cell interference. Int Symp on Wireless Communication Systems, p.261–265. https://doi.org/10.1109/ISWCS.2012.6328370 Google Scholar
  31. Guess T, Varanasi M, 2000. Error exponents for maximum-likelihood and successive decoders for the Gaussian CDMA channel. IEEE Trans Inform Theory, 46(4):1683–1691. https://doi.org/10.1109/18.850716 MathSciNetCrossRefMATHGoogle Scholar
  32. Islam SMR, Avazov N, Dobre OA, et al., 2017a. Powerdomain non-orthogonal multiple access (NOMA) in 5G systems: potentials and challenges. IEEE Commun Surv Tutor, 19(2):721–742. https://doi.org/10.1109/COMST.2016.2621116 CrossRefGoogle Scholar
  33. Islam SMR, Zeng M, Dobre OA, 2017b. Non-orthogonal multiple access in 5G systems: exciting possibilities for enhancing spectral efficiency. https://arxiv.org/abs/1706.08215 Google Scholar
  34. ITU-R, 2015. IMT vision—framework and overall objectives of the future development of IMT for 2020 and beyond. Technical Report, M.2083-0.Google Scholar
  35. Li A, Chen X, Jiang H, 2017. Contention based uplink transmission with non-orthogonal multiple access for latency reduction. 85th IEEE Conf on Vehicular Technology, p.1–6. https://doi.org/10.1109/VTCSpring.2017.8108486 Google Scholar
  36. Li L, Goldsmith A, 2001. Capacity and optimal resource allocation for fading broadcast channels. I. Ergodic capacity. IEEE Trans Inform Theory, 47(3):1083–1102. https://doi.org/10.1109/18.915665 MathSciNetCrossRefMATHGoogle Scholar
  37. Massey JL, Mittelholzer T, 1993. Welch’s Bound and Sequence Sets for Code-Division Multiple-Access Systems. Springer, New York, USA.MATHGoogle Scholar
  38. Medra A, Davidson TN, 2014. Flexible codebook design for limited feedback systems via sequential smooth optimization on the Grassmannian manifold. IEEE Trans Signal Process, 62(5):1305–1318. https://doi.org/10.1109/TSP.2014.2301137 MathSciNetCrossRefGoogle Scholar
  39. Nagata S, Wang L, Takeda K, 2017. Industry perspectives. IEEE Wirel Commun, 24(3):2–4. https://doi.org/10.1109/MWC.2017.7955902 CrossRefGoogle Scholar
  40. Nikopour H, Baligh H, 2013. Sparse code multiple access. 24th Int Symp on Personal Indoor and Mobile Radio Communications, p.332–336. https://doi.org/10.1109/PIMRC.2013.6666156 Google Scholar
  41. Osseiran A, Boccardi F, Braun V, et al., 2014. Scenarios for 5G mobile and wireless communications: the vision of the METIS project. IEEE Commun Mag, 52(5):26–35. https://doi.org/10.1109/MCOM.2014.6815890 CrossRefGoogle Scholar
  42. Ping L, Liu L, Wu K, et al., 2006. Interleave division multiple access. IEEE Trans Wirel Commun, 5(4):938–947. https://doi.org/10.1109/TWC.2006.1618943 CrossRefGoogle Scholar
  43. Saito Y, Kishiyama Y, Benjebbour A, et al., 2013. Nonorthogonal multiple access (NOMA) for cellular future radio access. 77th IEEE Conf on Vehicular Technology, p.1–5. https://doi.org/10.1109/VTCSpring.2013.6692652 Google Scholar
  44. She C, Yang C, Quek TQS, 2017. Radio resource management for ultra-reliable and low-latency communications. IEEE Commun Mag, 55(6):72–78. https://doi.org/10.1109/MCOM.2017.1601092 CrossRefGoogle Scholar
  45. Sun Q, Han S, Chin-Lin I, et al., 2015. On the ergodic capacity of MIMO NOMA systems. IEEE Wirel Commun Lett, 4(4):405–408. https://doi.org/10.1109/LWC.2015.2426709 CrossRefGoogle Scholar
  46. Taherzadeh M, Nikopour H, Bayesteh A, et al., 2014. Sparse code multiple access codebook design. 80th IEEE Conf on Vehicular Technology, p.1–5. https://doi.org/10.1109/VTCFall.2014.6966170 Google Scholar
  47. Teng CF, Liao CC, Cheng HY, et al., 2017. Reliable compressive sensing (CS)-based multi-user detection with power-based Zadoff-Chu sequence design. IEEE Int Workshop on Signal Processing Systems, p.1–5. https://doi.org/10.1109/SiPS.2017.8110015 Google Scholar
  48. Tse D, Viswanath P, 2015. Fundamentals of Wireless Communication. Cambridge University Press, Cambridge, UK. https://doi.org/10.1017/CBO9780511807213 MATHGoogle Scholar
  49. Viswanath P, Anantharam V, 1999. Optimal sequences and sum capacity of synchronous CDMA systems. IEEE Trans Inform Theory, 45(6):1984–1991. https://doi.org/10.1109/18.782121 MathSciNetCrossRefMATHGoogle Scholar
  50. Viswanath P, Anantharam V, Tse D, 1999. Optimal sequences, power control, and user capacity of synchronous CDMA systems with linear MMSE multi-user receivers. IEEE Trans Inform Theory, 45(6):1968–1983. https://doi.org/10.1109/18.782119 MathSciNetCrossRefMATHGoogle Scholar
  51. Wang C, Chen Y, Wu Y, et al., 2017. Performance evaluation of grant-free transmission for uplink URLLC services. 85th IEEE Conf on Vehicular Technology, p.1–6. https://doi.org/10.1109/VTCSpring.2017.8108593 Google Scholar
  52. Welch L, 1974. Lower bounds on the maximum cross correlation of signals (Corresp). IEEE Trans Inform Theory, 20(3):397–399. https://doi.org/10.1109/TIT.1974.1055219 CrossRefMATHGoogle Scholar
  53. Wu Y, Zhang S, Chen Y, 2015. Iterative multiuser receiver in sparse code multiple access systems. IEEE Int Conf on Communications, p.2918–2923. https://doi.org/10.1109/ICC.2015.7248770 Google Scholar
  54. Yuan Z, Yu G, Li W, et al., 2016. Multi-user shared access for Internet of Things. 83rd IEEE Conf on Vehicular Technology, p.1–5. https://doi.org/10.1109/VTCSpring.2016.7504361 Google Scholar
  55. Zeng M, Yadav A, Dobre OA, et al., 2017a. Capacity comparison between MIMO-NOMA and MIMO-OMA with multiple users in a cluster. IEEE J Sel Areas Commun, 35(10):2413–2424. https://doi.org/10.1109/JSAC.2017.2725879 CrossRefGoogle Scholar
  56. Zeng M, Yadav A, Dobre OA, et al., 2017b. On the sum rate of MIMO-NOMA and MIMO-OMA systems. IEEE Wirel Commun Lett, 6(4):534–537. https://doi.org/10.1109/LWC.2017.2712149 CrossRefGoogle Scholar

Copyright information

© Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.DOCOMO Beijing Communications Laboratories Co., Ltd.BeijingChina

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