DOI QR코드

DOI QR Code

ZEUS: Handover algorithm for 5G to achieve zero handover failure

  • Park, Hyun-Seo (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Lee, Yuro (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Kim, Tae-Joong (Mobile Communication Research Division, Electronics and Telecommunications Research Institute) ;
  • Kim, Byung-Chul (Department of Radio and Information Communications Engineering, Chungnam National University) ;
  • Lee, Jae-Yong (Department of Radio and Information Communications Engineering, Chungnam National University)
  • 투고 : 2020.09.14
  • 심사 : 2021.10.12
  • 발행 : 2022.06.10

초록

In 5G, the required target for interruption time during a handover (HO) is 0 ms. However, when a handover failure (HOF) occurs, the interruption time increases significantly to more than hundreds of milliseconds. Therefore, to fulfill the requirement in as many scenarios as possible, we need to minimize HOF rate as close to zero as possible. 3GPP has recently introduced conditional HO (CHO) to improve mobility robustness. In this study, we propose "ZEro handover failure with Unforced and automatic time-to-execute Scaling" (ZEUS) algorithm to optimize HO parameters easily in the CHO. Analysis and simulation results demonstrate that ZEUS can achieve a zero HOF rate without increasing the ping-pong rate. These two metrics are typically used to assess an HO algorithm because there is a tradeoff between them. With the introduction of the CHO, which solves the tradeoff, only these two metrics are insufficient anymore. Therefore, to evaluate the optimality of an HO algorithm, we define a new integrated HO performance metric, mobility-aware average effective spectral efficiency (MASE). The simulation results show that ZEUS provides higher MASE than LTE and other CHO variants.

키워드

과제정보

The authors especially thank Karthik Vasudeva, _ Ismail Guvenc, and David Lopez Perez, for their previous works and valuable discussions on the theoretical analysis of the HO performance. This research was supported by "The Cross-Ministry Giga KOREA Project" grant funded by the Korea government (MSIT) (no. GK20P0500, Development of Ultra Low-Latency Radio Access Technologies for 5G URLLC Service).

참고문헌

  1. J. Zhu et al., Ultra dense networks: General introduction and design overview, In Signal Processing for 5G: Algorithms and Implementations, John Wiley & Sons, Chichester, UK, 2016, pp. 483-508.
  2. N. Bhushan et al., Network densification: The dominant theme for wireless evolution into 5G, IEEE Commun. Mag. 52 (2014), 82-89. https://doi.org/10.1109/MCOM.2014.6736747
  3. 3GPP R2-1808482, Remaining essential issue for NR SA Handover, Samsung, RAN2#102, May 2018.
  4. J. Kim et al., Design of cellular, satellite, and integrated systems for 5G and beyond, ETRI J. 42 (2020), no. 5, 669-685. https://doi.org/10.4218/etrij.2020-0156
  5. H. Shokri-Ghadikolaei et al., Millimeter wave cellular networks: A MAC layer perspective, IEEE Trans. Commun. 63 (2015), 3437-3458. https://doi.org/10.1109/TCOMM.2015.2456093
  6. H. Park et al., Handover mechanism in NR for ultra-reliable low-latency communications, IEEE Network 32 (2018), 41-47. https://doi.org/10.1109/mnet.2018.1700235
  7. I. Viering et al., Zero-zero mobility: intra-frequency handovers with zero interruption and zero failures, IEEE Netw. 32 (2018), 48-54. https://doi.org/10.1109/MNET.2018.1700223
  8. 3GPP TR 36.881, Study on Latency Reduction Techniques for LTE (Release 14), June 2016.
  9. 3GPP TR 36.839, E-UTRA; Mobility Enhancements in Heterogeneous Networks (Release 11), Dec. 2012.
  10. 3GPP TR 36.878, Study on performance enhancements for high speed scenario in LTE (Release 13), Jan. 2016.
  11. E. Calvanese Strinati et al., 5GCHAMPION-Disruptive 5G technologies for roll-out in 2018, ETRI J. 40 (2018), no. 1, 10-25. https://doi.org/10.4218/etrij.2017-0237
  12. Y. Kim et al., Feasibility of mobile cellular communications at millimeter wave frequency, IEEE J. Sel. Top. Signal Process. 10 (2016), 589-599. https://doi.org/10.1109/JSTSP.2016.2520901
  13. 3GPP TS 36.331, Evolved Universal Terrestrial Radio Access (E-UTRA); Radio Resource Control (RRC), Sept. 2020.
  14. T. Jansen et al., Handover parameter optimization in LTE self-organizing networks, in Proc. IEEE Veh. Technol. Conf., Ottawa, ON, Canada, Sept. 2010.
  15. H. Chen et al., Mobility and handover management, In Heterogeneous Cellular Networks: Theory, Simulation And Deployment, Cambridge University Press, Cambridge, UK, 2013, pp. 245-283.
  16. A. Karandikar, N. Akhtar, and M. Mehta, Mobility management in LTE heterogeneous networks, Springer, Singapore, Singapore, 2017.
  17. 3GPP RP-090452, LS on Conclusions for LTE Mobility Study Item, RAN#57, Mar. 2009.
  18. 3GPP TS 36.300, E-UTRA and E-UTRAN; overall description; Stage2.
  19. 3GPP TR 36.842, Study on small cell enhancements for E-UTRA and E-UTRAN; higher layer aspects, 2013.
  20. J. Acharya et al., Dense small cell deployments, In Heterogeneous Networks in LTE-Advanced, John Wiley & Sons, Chichester, UK, 2014, pp. 205-229.
  21. 3GPP TS 38.300, NR; NR and NG-RAN Overall Description; Stage 2.
  22. 3GPP RP-200738, WI summary for WI: Even further mobility enhancement in E-UTRAN, China Telecom, RAN#88, June 2020.
  23. 3GPP RP-201274, WI summary for WI: NR mobility enhancements, Intel Corporation, RAN#88, June 2020.
  24. 3GPP R2-1818048, Simulation Results on Conditional Handover, ETRI, RAN2#104, Nov. 2018.
  25. 3GPP RP-201195, RAN2 CRs to Even further mobility enhancement in E-UTRAN, RAN2, RAN#88, June 2020.
  26. 3GPP RP-201177, RAN2 CRs to NR Mobility Enhancements, RAN2, RAN#88, June 2020.
  27. Q. Kuang et al., Mobility performance of LTE-advanced heterogeneous networks with control channel protection, Proc. World Telecommun. Congr. (WTC 2014), Berlin, Germany, June 2014.
  28. K. Adachi et al., A distributed resource reservation scheme for handover failure reduction, IEEE Wirel. Commun. Lett. 4 (2015), 537-540. https://doi.org/10.1109/LWC.2015.2453987
  29. X. Zhang et al., Dynamic user equipment-based hysteresisadjusting algorithm in LTE femtocell networks, IET Commun. 8 (2014), 3050-3060. https://doi.org/10.1049/iet-com.2014.0277
  30. S. Lee et al., Mobility enhancement of dense small-cell network, Proc. Ann. IEEE Consum. Commun. Netw. Conf. (CCNC), Las Vegas, NV, USA, Jan. 2015, pp. 297-303.
  31. 3GPP R2-134171, Effect of Handover Delay on Handover Failure and Ping-Pong in Dense HetNet, Samsung, RAN2#84, Nov. 2013.
  32. 5G PPP METIS II project, Deliverable D6.2, 5G Asynchronous Control Functions and Overall Control Plane Design (Apr. 2017).
  33. H. Martikainen et al., On the basics of conditional handover for 5G mobility, Proc. IEEE Ann. Int. Symp. Pers., Indoor Mob. Radio Commun. (PIMRC), Bologna, Italy, Sept. 2018.
  34. T. Deng et al., A network assisted fast handover scheme for high speed rail wireless networks, Proc. IEEE Veh. Technol. Conf. (VTC Spring), Nanjing, China, May 2016.
  35. C. Lee et al., Prediction-based conditional handover for 5G mmwave networks: A deep-learning approach, IEEE Veh. Technol. Mag. 15 (2020), 54-62. https://doi.org/10.1109/mvt.2019.2959065
  36. D. Lopez-Perez, I. Guvenc, and X. Chu, Theoretical analysis of handover failure and ping-pong rates for heterogeneous networks, Proc. Int. Workshop Small Cell Wirel. Netw., Ottawa, ON, Canada, June 2012, pp. 6774-6779.
  37. K. Vasudeva, M. Simsek, and I. Guvenc, Analysis of handover failures in HetNets with Layer-3 filtering, Proc. IEEE Wirel. Commun. Netw. Conf.erence (WCNC), Istanbul, Turkey, Apr. 2014, pp. 2647-2652.
  38. K. Vasudeva et al., Analysis of handover failures in heterogeneous networks with fading, IEEE Trans. Veh. Technol. 66 (2017), 6060-6074. https://doi.org/10.1109/TVT.2016.2640310
  39. H. Park et al., Two-step handover for LTE HetNet mobility enhancements, Proc. Int. Conf. ICT Converg. (ICTC), Jeju, Republic of Korea, Oct. 2013, pp. 763-766.
  40. 3GPP R2-134432, Early HO command with ping-pong avoidance, further information, ETRI, RAN2#84, Nov. 2013.
  41. H. Park et al., LTE mobility enhancements for evolution into 5G, ETRI J. 37 (2015) no. 6, 1065-1076. https://doi.org/10.4218/etrij.15.0115.0529
  42. D. Lopez-Perez, X. Chu, and I. Guvenc, On the expanded region of Picocells in heterogeneous networks, IEEE J. Sel. Top. Signal Process. 6 (2012), 281-294. https://doi.org/10.1109/JSTSP.2012.2190381
  43. 3GPP R2-114950, Discussion on the mobility performance enhancement for co-channel HetNet deployment, ZTE, RAN2#75bis, Oct. 2011.
  44. 3GPP TS 36.133, E-UTRA; Requirements for support of radio resource management.
  45. OPNET. https://www.riverbed.com/sg/products/steelcentral/opnet.html
  46. D. Liu et al., User association in 5G networks: A survey and an outlook, IEEE Commun. Surv. Tutor. 18 (2016), 1018-1044. https://doi.org/10.1109/COMST.2016.2516538
  47. D. Xenakis et al., Mobility management for femtocells in LTE-advanced: key aspects and survey of handover decision algorithms, IEEE Commun. Surv. Tutor. 16 (2014), 64-91. https://doi.org/10.1109/SURV.2013.060313.00152
  48. N. Amirrudin et al., Analysis of handover performance in LTE femtocells network, Wirel. Pers. Commun. 97 (2017), 1929-1946. https://doi.org/10.1007/s11277-017-4222-3
  49. M. G. Khoshkholgh and V. C. M. Leung, Coverage analysis of Max-SIR cell association in HetNets under Nakagami fading, IEEE Trans. Veh. Technol. 67 (2018), 2420-2438. https://doi.org/10.1109/tvt.2017.2772035
  50. 3GPP TR 37.817, Study on enhancement for data collection for NR and ENDC (Release 17), to be released in Mar. 2022.
  51. M. Nguyen and S. Kwon, Machine learning-based mobility robustness optimization under dynamic cellular networks, IEEE Access 9 (2021), 77830-77844. https://doi.org/10.1109/ACCESS.2021.3083554
  52. A. Mohajer, M. Bavaghar, and H. Farrokhi, Mobility-aware load balancing for reliable self-organization networks: Multiagent deep reinforcement learning, Reliab. Eng. Syst. Saf. 202 (2020), 107056. https://doi.org/10.1016/j.ress.2020.107056