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A Large Deviations Model for Latency Outage for URLLC

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Performance Evaluation Methodologies and Tools (VALUETOOLS 2022)

Abstract

In this paper, we develop an analytical model for radio resource dimensioning for latency-critical services in 5G networks. URLLC (Ultra-Reliable Low Latency Communications) service is introduced in the 5G networks to respond to the requirements of critical applications such as self driving cars, industry 4.0, etc. Its stringent requirements in terms of latency and reliability are challenging to meet and are usually tackled by resource over-dimensioning. In this paper, we develop large deviation bounds for the outage probability i.e., the probability that the packet delay exceeds a given target. Our numerical applications show that the bounds are sufficiently tight for mastering over-dimensioning. We then develop a resource dimensioning framework based on the developed bounds and apply it to a large scale system level simulator. Our simulation results show that the developed model, when coupled with field-based radio condition distributions, allows achieving the reliability targets with acceptable cost in terms of resource consumption.

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Notes

  1. 1.

    If the spectral efficiency of MCS i is equal to \(e_i\) (bit/s/Hz), a packet is of size P bit, and one RB spans over b Hz, the amount of consumed RBs is computed by:

    $$r_i=\lceil \frac{P}{e_ibT} \rceil ,$$

    where \(\lceil x \rceil \) is the smaller integer larger than x.

References

  1. 3GPP, TS 23.501: System Architecture for the 5G System (2017). Version 15.0.0 Release 15

    Google Scholar 

  2. 3GPP, TR 38.912: 5G; Study on New Radio (NR) access technology (2018). Version 15.0.0 Release 15

    Google Scholar 

  3. Alsenwi, M., Tran, N., Bennis, M., Pandey, S., Bairagi, A., Hong, C.S.: Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond: a deep reinforcement learning based approach. IEEE Trans. Wirel. Commun. PP, 1 (2021). https://doi.org/10.1109/TWC.2021.3060514

  4. Bennett, G.: Probability inequalities for the sum of independent random variables. J. Am. Stat. Assoc. 57(297), 33–45 (1962)

    Article  MATH  Google Scholar 

  5. Bennis, M., Debbah, M., Poor, H.V.: Ultra reliable and low-latency wireless communication: tail, risk, and scale. Proc. IEEE 106(10), 1834–1853 (2018)

    Article  Google Scholar 

  6. Bernšteın, S.: Theory of probability. Moscow. MR0169758 (1927)

    Google Scholar 

  7. Chagdali, A., Elayoubi, S.E., Masucci, A.M., Simonian, A.: Performance of URLLC traffic scheduling policies with redundancy. In: 2020 32nd International Teletraffic Congress (ITC 32), pp. 55–63. IEEE (2020)

    Google Scholar 

  8. Chen, Y., Cheng, L., Wang, L.: Prioritized resource reservation for reducing random access delay in 5G URLLC. In: 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pp. 1–5 (2017). https://doi.org/10.1109/PIMRC.2017.8292695

  9. Elayoubi, S.E., Brown, P., Deghel, M., Galindo-Serrano, A.: Radio resource allocation and retransmission schemes for URLLC over 5G networks. IEEE JSAC 37(4), 896–904 (2019). https://doi.org/10.1109/JSAC.2019.2898783

    Article  Google Scholar 

  10. Fountoulakis, E., Pappas, N., Liao, Q., Suryaprakash, V., Yuan, D.: An examination of the benefits of scalable TTI for heterogeneous traffic management in 5G networks. In: 2017 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), pp. 1–6 (2017). https://doi.org/10.23919/WIOPT.2017.7959871

  11. Han, Y., Elayoubi, S.E., Galindo-Serrano, A., Varma, V.S., Messai, M.: Periodic radio resource allocation to meet latency and reliability requirements in 5G networks. In: 2018 IEEE 87th Vehicular Technology Conference (VTC Spring), pp. 1–6. IEEE (2018)

    Google Scholar 

  12. Jang, H., Kim, J., Yoo, W., Chung, J.M.: URLLC mode optimal resource allocation to support HARQ in 5G wireless networks. IEEE Access 8, 126797–126804 (2020)

    Article  Google Scholar 

  13. Korrai, P., Lagunas, E., Sharma, S.K., Chatzinotas, S., Bandi, A., Ottersten, B.: A RAN resource slicing mechanism for multiplexing of eMBB and URLLC services in OFDMA based 5G wireless networks. IEEE Access 8, 45674–45688 (2020). https://doi.org/10.1109/ACCESS.2020.2977773

    Article  Google Scholar 

  14. Li, C.P., Jiang, J., Chen, W., Ji, T., Smee, J.: 5G ultra-reliable and low-latency systems design. In: 2017 European Conference on Networks and Communications (EuCNC), pp. 1–5 (2017). https://doi.org/10.1109/EuCNC.2017.7980747

  15. Li, Z., Uusitalo, M.A., Shariatmadari, H., Singh, B.: 5G URLLC: design challenges and system concepts. In: 2018 15th International Symposium on Wireless Communication Systems (ISWCS), pp. 1–6. IEEE (2018)

    Google Scholar 

  16. Morcos, M., Mhedhbi, M., Galindo-Serrano, A., Eddine Elayoubi, S.: Optimal resource preemption for aperiodic URLLC traffic in 5G networks. In: 2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1–6 (2020). https://doi.org/10.1109/PIMRC48278.2020.9217111

  17. Pedersen, K.I., Pocovi, G., Steiner, J., Khosravirad, S.R.: Punctured scheduling for critical low latency data on a shared channel with mobile broadband. In: 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), pp. 1–6 (2017). https://doi.org/10.1109/VTCFall.2017.8287951

  18. Pedersen, K.I., Berardinelli, G., Frederiksen, F., Mogensen, P., Szufarska, A.: A flexible 5G frame structure design for frequency-division duplex cases. IEEE Commun. Mag. 54(3), 53–59 (2016). https://doi.org/10.1109/MCOM.2016.7432148

    Article  Google Scholar 

  19. Sachs, J., Wikstrom, G., Dudda, T., Baldemair, R., Kittichokechai, K.: 5G radio network design for ultra-reliable low-latency communication. IEEE Netw. 32(2), 24–31 (2018). https://doi.org/10.1109/MNET.2018.1700232

    Article  Google Scholar 

  20. Singh, B., Tirkkonen, O., Li, Z., Uusitalo, M.A.: Contention-based access for ultra-reliable low latency uplink transmissions. IEEE Wirel. Commun. Lett. 7(2), 182–185 (2018)

    Article  Google Scholar 

  21. Stroock, D.W.: An Introduction to the Theory of Large Deviations. Springer, Heidelberg (2012)

    Google Scholar 

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Correspondence to Salah Eddine Elayoubi .

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Elayoubi, S.E., Naddeh, N., Chahed, T., Ben Jemaa, S. (2023). A Large Deviations Model for Latency Outage for URLLC. In: Hyytiä, E., Kavitha, V. (eds) Performance Evaluation Methodologies and Tools. VALUETOOLS 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 482. Springer, Cham. https://doi.org/10.1007/978-3-031-31234-2_14

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  • DOI: https://doi.org/10.1007/978-3-031-31234-2_14

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