Paper Abstract and Keywords |
Presentation |
2019-01-25 15:25
Efficient Radio Access for Massive Machine-Type Communication
-- Evaluation of the effect of space diversity and repetition transmission in fading environment -- Hayato Tezuka, Masafumi Moriyama, Kenichi Takizawa, Fumihide Kojima (NICT) RCC2018-111 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
A rapid increase of uplink traffic is predicted with the spread of IoT devices. In the 5G (5th generation mobile communications systems), base stations must effectively receive massive uplink signals transmitted from IoT devices. In addition, there are some communications that require low latency like automatic operation, so low latency communication is also important. To solve this problem, we have developed techniques based on non-orthogonal multiple access in uplink (UL-NOMA) in order to realize both massive device connectivity and low latency. Although our system can accommodate many user terminals by sharing communication resources, in a fading environment, the separation success rate which indicates the signal separation ratio when SIC is employed relatively decreases because of received power fluctuation, hence we must evaluate the system under the fading environment so that system can be improved. In this paper, we evaluated our system in an outdoor environment as well as in a laboratory using a channel emulator. We compared the results of the two experiments. As a result, we found that the experiment in the outdoor environment was similar to Rician and Nakagami fading, and using space diversity (SD) and repetition transmission (RT) made the performance improve. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
IoT / Massive Devices / Contention Based Communication / Low Latency / Successive Interference Cancellation / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 423, RCC2018-111, pp. 25-30, Jan. 2019. |
Paper # |
RCC2018-111 |
Date of Issue |
2019-01-18 (RCC) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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RCC2018-111 |
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