| Presentation | 2020-12-18 K-Factor Estimation based on Spectrogram Images by Convolutional Neural Network Shun Kojima, Kosuke Shima, Kazuki Maruta, Chang-Jun Ahn, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In the next generation mobile communications systems, accurate and fast acquisition of the communication environment is essential to achieve high-speed and low-latency communication. A $K$-factor in Rician fading is a major determinant of the link quality. Therefore, $K$-factor estimation is a very important task in order to achieve high performance of adaptive control in wireless communications that is dependent on the link quality. Conventional methods for estimating the $K$-factor have been widely studied, including the method using moments of the received signal and the method based on the received signal envelope and channel statistics. These methods require sampling of the signal on a large scale, which increases the amount of computation and processing time. In this paper, we focus on spectrograms containing features of the $K$-factor and propose a novel its estimation method using convolutional neural network (CNN) from a single packet. Simulation results reveal its effectiveness in terms of estimation accuracy and resultant adaptive modulation performance. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Spectrogram / CNN / K factor estimation |
| Paper # | RCS2020-153 |
| Date of Issue | 2020-12-10 (RCS) |
| Conference Information | |
| Committee | NS / RCS |
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| Conference Date | 2020/12/17(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Multi-hop/Relay/Cooperation, Disaster-resistant wireless network, Sensor/Mesh network, Ad-hoc network, D2D/M2M, Wireless network coding, Handover/AP switching/Connected cell control/Load balancing among base stations/Mobile network dynamic reconfiguration, QoS/QoE assurance, Wireless VoIP, IoT, Edge computing, etc. |
| Chair | Akihiro Nakao(Univ. of Tokyo) / Eiji Okamoto(Nagoya Inst. of Tech.) |
| Vice Chair | Tetsuya Oishi(NTT) / Fumiaki Maehara(Waseda Univ.) / Toshihiko Nishimura(Hokkaido Univ.) / Tomoya Tandai(Toshiba) |
| Secretary | Tetsuya Oishi(NTT) / Fumiaki Maehara(Chuo Univ.) / Toshihiko Nishimura(Kyushu Univ.) / Tomoya Tandai(NEC) |
| Assistant | Shinya Kawano(NTT) / Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Manabu Sakai(Mitsubishi Electric) / Masashi Iwabuchi(NTT) / Tatsuki Okuyama(NTT DOCOMO) |
| Paper Information | |
| Registration To | Technical Committee on Network Systems / Technical Committee on Radio Communication Systems |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | K-Factor Estimation based on Spectrogram Images by Convolutional Neural Network |
| Sub Title (in English) | |
| Keyword(1) | Spectrogram |
| Keyword(2) | CNN |
| Keyword(3) | K factor estimation |
| 1st Author's Name | Shun Kojima |
| 1st Author's Affiliation | Chiba University(Chiba Univ.) |
| 2nd Author's Name | Kosuke Shima |
| 2nd Author's Affiliation | Chiba University(Chiba Univ.) |
| 3rd Author's Name | Kazuki Maruta |
| 3rd Author's Affiliation | Tokyo Institute of Technology(Tokyo Tech) |
| 4th Author's Name | Chang-Jun Ahn |
| 4th Author's Affiliation | Chiba University(Chiba Univ.) |
| Date | 2020-12-18 |
| Paper # | RCS2020-153 |
| Volume (vol) | vol.120 |
| Number (no) | RCS-298 |
| Page | pp.pp.103-108(RCS), |
| #Pages | 6 |
| Date of Issue | 2020-12-10 (RCS) |