Skip to main content
SpringerLink
Log in

Multiplexing of URLLC and eMBB Traffic in a Downlink Channel with MU-MIMO

  • DATA TRANSMISSION IN COMPUTER NETWORKS
  • Published:
Journal of Communications Technology and Electronics Aims and scope Submit manuscript

Abstract

In the paper, we study the problem of multiplexing Ultra-Reliable Low-Latency Communications (URLLC) and enhanced Mobile Broadband (eMBB) traffic in the downlink channel of 5G systems. The Multi-User Multiple Input Multiple Output (MU-MIMO) technology is used for multiplexing, which allows a base station to transmit data simultaneously to several users in the same time–frequency resources. We propose a new algorithm (scheduler) that allocates time–frequency resources and transmission parameters for eMBB and URLLC users and dynamically distributes the base station transmission power between users. Simulation shows that the proposed scheduler increases the coverage for URLLC users and the throughput for eMBB users compared with the existing schedulers.

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.

Similar content being viewed by others

REFERENCES

  1. “Framework and overall objectives of the future development of IMT for 2020 and beyond,” ITU-R. Recommendation M.2083 (2015).

  2. W. Yang, C. P. Li, A. Fakoorian, K. Hosseini, and W. Chen, “Dynamic URLLC and eMBB multiplexing design in 5G new radio,” in Proc. IEEE 17th Annual Consumer Communications Networking Conf. (CCNC), 2020 (IEEE, New York, 2020), pp. 1–5.

  3. A. A. Esswie and K. I. Pedersen, “Null space based preemptive scheduling for joint URLLC and eMBB traffic in 5G networks,” in IEEE Globecom Workshops (GC Wkshps), Abu Dhabi, Dec. 9–13, 2018 (IEEE, New York, 2018), p. 1–6.

  4. A. A. Esswie and K. I. Pedersen, “Opportunistic spatial preemptive scheduling for URLLC and eMBB coexistence in multi-user 5G networks,” IEEE Access. 6, 38451–38463 (2018).

  5. A. A. Esswie and K. I. Pedersen, “Multi-user preemptive scheduling for critical low latency communications in 5G networks,” in IEEE Symp. on Computers and Commun. (ISCC),Natal, Brazil, June 25—28, 2018 (IEEE, New York, 2018), pp. 136–141.

  6. A. Karamyshev, E. Khorov, A. Krasilov, and I. F. Akyildiz, “Fast and accurate analytical tools to estimate network capacity for URLLC in 5G systems,” Comput. Networks 178, (2020).

  7. E. Khorov, A. Krasilov, I. Selnitskiy, and I. F. Akyildiz, “A framework to maximize the capacity of 5G systems for ultra-reliable low-latency communications,” IEEE Trans. on Mobile Comput. 20, 2111–2123 (2021).

  8. E. Khorov, A. Krasilov, and A. Malyshev, “Radio resource and traffic management for ultra-reliable low latency communications,” in IEEE Wireless Commun. & Networking Conf. (WCNC), Barselona, Spain, Apr. 15–18, 2018, (IEEE, New York, 2018), pp. 1– 6.

  9. C. Lu, W. Wang, W. Zhong, and X. Gao, “User scheduling and beam allocation for massive MIMO systems with two-stage precoding,” in IEEE 27th Annual Int. Symp. on Personal, Indoor, and Mobile Radio Commun. (PIMRC), Valencia, Spain, Sept. 4–8, 2016 (IEEE, New York, 2018), pp. 1– 6.

  10. R. Kwan, C. Leung, and J. Zhang, “Proportional Fair Multiuser Scheduling in LTE,” IEEE Signal Process. Lett. 16, 461–464 (2009).

  11. T. Yoo and A. Goldsmith, “On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming,” IEEE J. on Selected Areas in Commun. 24, 528–541 (2006).

  12. A. Duran, M. Toril, F. Ruiz, and A. Mendo, “Self-optimization algorithm for outer loop link adaptation in LTE,” IEEE Commun. Lett. 19, 2005–2008 (2015).

  13. A. Belogaev, E. Khorov, A. Krasilov, D. Shmelkin, and S. Tang, “Conservative link adaptation for ultra reliable low latency communications,” IEEE BlackSeaCom, 1–5 (2019).

  14. A. Krasilov, I. Lebedeva, R. Yusupov, and E. Khorov, “Efficient multiplexing of downlink eMBB and URLLC traffic with massive MU-MIMO,” IEEE BlackSeaCom, 1–6 (2022).

  15. “Network Simulator 3” [Online]. Available: https://www.nsnam.org/.

Download references

Funding

The work was carried out at the National Research University Higher School of Economics and supported by the Russian Science Foundation grant no. 21-79-10158, https://rscf.ru/en/project/21-79-10158/.

Author information

Authors and Affiliations

  1. HSE University, 101000, Moscow, Russia

    R. R. Yusupov & A. N. Krasilov

  2. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, 127051, Moscow, Russia

    I. V. Lebedeva, R. R. Yusupov, A. N. Krasilov & E. M. Khorov

Authors
  1. I. V. Lebedeva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. R. R. Yusupov
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. A. N. Krasilov
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. E. M. Khorov
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to I. V. Lebedeva, R. R. Yusupov, A. N. Krasilov or E. M. Khorov.

Ethics declarations

The authors declare that they have no conflicts of interest.

Additional information

Translated by M. Chubarova

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lebedeva, I.V., Yusupov, R.R., Krasilov, A.N. et al. Multiplexing of URLLC and eMBB Traffic in a Downlink Channel with MU-MIMO. J. Commun. Technol. Electron. 67, 1506–1512 (2022). https://doi.org/10.1134/S1064226922120129

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1064226922120129

Search

Navigation