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Dynamic Resource Allocation of Random Access for MTC Devices

  • Lee, Sung-Hyung (Department of Electrical and Computer Engineering, Ajou University) ;
  • Jung, So-Yi (Department of Electrical and Computer Engineering, Ajou University) ;
  • Kim, Jae-Hyun (Department of Electrical and Computer Engineering, Ajou University)
  • Received : 2016.11.14
  • Accepted : 2017.04.09
  • Published : 2017.08.01

Abstract

In a long term evolution-advanced (LTE-A) system, the traffic overload of machine type communication devices is a challenge because too many devices attempt to access a base station (BS) simultaneously in a short period of time. We discuss the challenge of the gap between the theoretical maximum throughput and the actual throughput. A gap occurs when the BS cannot change the number of preambles for a random access channel (RACH) until multiple numbers of RACHs are completed. In addition, a preamble partition approach is proposed in this paper that uses two groups of preambles to reduce this gap. A performance evaluation shows that the proposed approach increases the average throughput. For 100,000 devices in a cell, the throughput is increased by 29.7% to 114.4% and 23.0% to 91.3% with uniform and Beta-distributed arrivals of devices, respectively.

Keywords

References

  1. 3GPP TR 36.300, Evolved Universal Terrestrial Radio Access and Evolved Universal Terrestrial Radio Access Network; Overall Description, Stage 2, July 2016.
  2. A. Laya, L. Alonso, and J. Alonso-Zarate, "Is the Random Access Channel of LTE and LTE-A Suitable for M2M Communications? A Survey of Alternatives," IEEE Commun. Surveys Tutorials, vol. 16, no. 1, 2014, pp. 4- 16. https://doi.org/10.1109/SURV.2013.111313.00244
  3. S. Duan et al., "D-ACB: Adaptive Congestion Control Algorithm for Bursty M2M Traffic in LTE Networks," IEEE Trans. Veh. Technol., vol. 65, no. 12, Dec. 2016, pp. 9847-9867. https://doi.org/10.1109/TVT.2016.2527601
  4. Machina Research Sector Report, "Machine-to-Machine (M2M) Communication in Consumer Electronics 2012- 22," Feb. 2013.
  5. 3GPP TR 37.868, RAN Improvements for Machine-Type Communications, v11.0.0, Oct. 2011.
  6. ICT-317669 METIS Project, "Scenarios, Requirements and KPIs for 5G Mobile and Wireless System," Deliverable 1.1, Apr. 2013.
  7. C.H. Lee et al., "Mobile Small Cells for Further Enhanced 5G Heterogeneous Networks," ETRI J., vol. 37, no. 5, Oct. 2015, pp. 856-866. https://doi.org/10.4218/etrij.15.2415.0022
  8. 3GPP TR 36.321, Evolved Universal Terrestrial Radio Access; Medium Access Control (MAC) Protocol Specification, v12.6.0, June 2015.
  9. J. Choi, "On the Adaptive Determination of the Number of Preambles in RACH for MTC," IEEE Commun. Lett., vol. 20, no. 7, July 2016, pp. 1385-1388. https://doi.org/10.1109/LCOMM.2016.2546238
  10. Y.J. Choi et al., "Multichannel Random Access in OFDMA Wireless Networks," IEEE J. Sel. Areas Commun., vol. 24, no. 3, Mar. 2006, pp. 603-613. https://doi.org/10.1109/JSAC.2005.862422
  11. G. Khandelwal et al., "ASAP: a MAC Protocol for Dense and Time Constrained RFID Systems," IEEE Int. Conf. Commun., Istanbul, Turkey, June 11-15, 2006, pp. 4028- 4033.
  12. H. Vogt, "Efficient Object Identification with Passive RFID Tags," Int. Conf. Pervasive Comput., Zurich, Switzerland, Aug. 26-28, 2002.
  13. J.R. Cha and J.H. Kim, "Novel Anti-Collision Algorithms for Fast Object Identification in RFID System," Proc. Int. Conf. Parallel Distrib. Syst., Fukuoka, Japan, July 20-22, 2005, pp. 63-67.
  14. D. Lee et al., "A Time-Optimal Anti-Collision Algorithm for FSA-Based RFID Systems," ETRI J., vol. 33, no. 3, June 2011, pp. 458-461. https://doi.org/10.4218/etrij.11.0210.0243
  15. Y.B. Kim, "Determination of Optimal Frame Sizes in Frame Slotted ALOHA," IET Lett., vol. 54, no. 23, Nov. 2014, pp. 1764-1766.
  16. S. Duan, V. Shah-Mansouri, and V.W.S. Wong, "Dynamic Access Class Barring for M2M Communications in LTE Networks," IEEE Globecom Workshops, Atlanta, GA, USA, Dec. 2013, pp. 4747-4752.
  17. H. He et al., "Traffic-Aware ACB Scheme for Massive Access in Machine-to-Machine Networks," IEEE Int. Cconf. Commun., London, UK, June 8-12, 2015, pp. 617- 622.
  18. M. Tavana, V. Shah-Mansouri, and V.W.S. Wong, "Congestion Control for Bursty M2M Traffic in LTE Networks," IEEE Int. Conf. Commun., London, UK, June 8-12, 2015, pp. 5815-5820.
  19. R.G. Cheng et al., "Modeling and Analysis of an Extended Access Barring Algorithm for Machine-Type Communications in LTE-A Networks," IEEE Trans. Wireless Commun., vol. 14, no. 6, June 2015, pp. 2956-2968. https://doi.org/10.1109/TWC.2015.2398858
  20. G.Y. Lin, S.R. Chang, and H.-Y. Wei, "Estimation and Adaptation for Bursty LTE Random Access," IEEE Trans. Veh. Technol., vol. 65, no. 4, Apr. 2016, pp. 2560-2577. https://doi.org/10.1109/TVT.2015.2418811
  21. 3GPP TR 36.211, Evolved Universal Terrestrial Radio Access (E-UTRA); Physical Channels and Modulation, v.13.2.0, June 2016.
  22. 3GPP TR 36.331, Evolved Universal Terrestrial Radio Access; Radio Resource Control (RRC); Protocol Specification, v13.2.0, July 2016.
  23. O. Arouk and A. Ksentini, "General Model for RACH Procedure Performance Analysis," IEEE Commun. Lett., vol. 20, no. 2, Feb. 2016, pp. 372-375. https://doi.org/10.1109/LCOMM.2015.2505280