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creases exponentially with the increase in number of connected terminals.e performance evaluation results for the two methods are shown in Fig. 6. A histogram shows the number of terminals with successfully separated signals when the in-terference power ratio of the signal is changed. With the simultaneously connected number of UE terminals at ve, the horizontal axis shows the number of terminals for which separation was successful. We conducted 10,000 trials with the modulation method as QPSK and the coding rate of the turbo encoder at 1/3. In regard to the reference signal, a dierent cyclic shi number was given to each UE terminal, and in interference suppression/cancellation processing we used the channel impulse response esti-mated from the received reference signal. From the perfor-mance evaluation results, it is shown that in order to obtain a successful separation rate of 90% or more, SIR needs to be set at 3 dB or higher in SIC. On the other hand, in PIC, even if SIR is 0 dB, it can be seen that a successful signal separation rate of 90% or more is possible.In regard to these interference suppression/cancellation, hardware demonstration using FPGA has been reported in terms of achievable latency [11] [12]. Further, in regard to the number of accommodated UE terminals, we are also carrying out evaluations when using transmission without grant, which minimizes scheduling requests before data transmission [13]. In order to fulll the objective of this R&D, which is to realize a 5 ms or less latency even in a eld environment, we are working to improve algorithms for interference suppression/cancellation.3Future prospectsIn this paper, we showed our R&D directed toward realizing radio access technologies that accommodate small-size data derived from massive numbers of IoT de-vices within the network with high eciency and low la-tency. In order to improve frequency usage eciency, we are pursuing R&D on radio access technologies that use transmission without grant, which does not require trans-mission scheduling requests, to decrease the latency by making it possible for multiple UE terminals to share the same frequency at the same time. In the future, we plan to conduct performance evaluations in the eld considering mMTC usage scenarios.Acknowledgmentsis research was conducted under a contract of R&D for Expansion of Radio Wave Resources, organized by the Ministry of Internal Aairs and Communications, Japan.ReferenceR1Rec. ITU-R M.2083-0, IMT Vision -- Framework and overall objectives of the future development of IMT for 2020 and beyond, Sept. 2015. 23GPP TR 38.913, Study on Scenarios and Requirements for Next Generation Access Technologies, 2017.3M. Moriyama et al, “Efficient Radio Access for Massive Machine -Type Communication-Basic Studies of Frame Structure and Channel Estimation-,” IEICE Technical Report, RCS2016-175, pp.119–124, Oct. 2016. (in Japanese)43GPP TR 38.900, Study on channel model for frequency spectrum above 6 GHz, 2017.5M. Moriyama et al, “Efficient Radio Access for Massive Machine-Type Communication- Basic Studies of Channel Estimation Methods and Successive Interference Cancellation Techniques-,” IEICE Annual Conference, March 2017. (in Japanese)6M. Moriyama et al, “Efficient Radio Access for Massive Machine -Type Communication-Studies of Successive Interference Cancellation and Parallel Interference Cancellation-,” IEICE Technical Report, RCS2017-5, pp.23–28, April 2017. (in Japanese)7M. Moriyama et al, “Efficient Radio Access for Massive Machine-Type Communication -An Interference Cancellation and Suppression Technique Employing Selection Combining Diversity in Frequency Domain-,” IEICE Technical Report, RCS2017-52, pp.13–18, June 2017. (in Japanese)8K. Takizawa et al, “Efficient Radio Access for Massive Machine-Type Communication- FPGA Implementation on Successive Interference Cancellation Algorithm,” IEICE Technical Report, July 2017. (in Japanese).9K. Takizawa et al, “Efficient Radio Access for Massive Machine-Type Communication- Interference Cancellation and Suppression Technique-,” IEICE Technical Report, RCS2016-175, pp.119–124, Oct. 2016. (in Japanese)10K. Takizawa et al, “Efficient Radio Access for Massive Machine-Type Communication- Inter-User Interference Cancellation using Multiuser Detection,” IEICE Technical Report, July 2017. (in Japanese).11H. Tezuka et al, “Efficient Radio Access for Massive Machine -Type Communication –Evaluation of Interference Cancellation Technique Using Measurement Instrument-,” IEICE Annual Conference, March 2017. (in Japanese)12H. Tezuka et al, “Efficient Radio Access for Massive Machine -Type Communication- Studies of Radio Channel Estimation and Successive Interference Cancellation on Real Machine-,” IEICE Technical Report, July 2017. (in Japanese)13C. Pyo et al, “A Performance Study of Grant-Free Multiple Access for Massive Wireless Communications,” IEICE Technical Report, RCS2017-53, pp.19–23, June 2017.Kenichi TAKIZAWA, Dr. Eng.Research Manager, Wireless Systems Laboratory, Wireless Networks Research CenterMobile communication, Under water communication, Body area network, Image processing2 Terrestrial Communication Technology Research and Development16　　　Journal of the National Institute of Information and Communications Technology Vol. 64 No. 2 (2017)