| Presentation | 2015-10-27 [Technology Exhibit] Hardware Demonstration of Wi-Fi Fingerprint based Millimeter Wave Beamforming Ehab Mahmoud Mohamed, Gia Khanh Tran, Kei Sakaguchi, Seiichi Sampei, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Millimeter wave (mmWave), especially the 60 GHz band, has been receiving much attention as a key enabler for the 5G cellular networks. Beamforming is tremendously used with mmWave transmissions to enhance the link quality and overcome the channel propagation loss. The current beamforming mechanism, proposed by the IEEE 802.11ad standard, is mainly based on exhaustive searching the best transmit (TX) and receive (RX) antenna beams. This beamforming mechanism requires a very high setup time, which makes it difficult to coordinate a multiple number of mmWave access points (APs) in mobile channel conditions as a 5G requirement. In this exhibition, we demonstrate a mmWave beamforming mechanism, which enables a mmWave AP to fast estimate the best beam to communicate with a user equipment (UE) using statistical learning. In this scheme, the fingerprints of the UE 5 GHz (Wi Fi) signal and 60 GHz (mmWave) best beam identification (ID) are collected in an offline phase on a grid of arbitrary learning points (LPs) in target environments. Therefore, by just comparing the current UE Wi-Fi signal with the pre-stored UE WiFi fingerprints, the mmWave AP can immediately estimate the best beam to communicate with the UE at its current position. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Millimeter WaveBeamformingWi-Fi FingerprintsBest Sector IDStatistical Learning |
| Paper # | SR2015-62,SRW2015-43 |
| Date of Issue | 2015-10-19 (SR, SRW) |
| Conference Information | |
| Committee | SR / SRW |
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| Conference Date | 2015/10/26(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | KKE |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Technical Exhibition, Product Exhibition, etc. |
| Chair | Takeo Fujii(Univ. of Electro-Comm.) / Hiroshi Harada(Kyoto Univ.) |
| Vice Chair | Kenta Umebayashi(Tokyo Univ. of Agric. and Tech.) / Masayuki Ariyoshi(NEC) / Masafumi Kato(Fujitsu) / Satoshi Denno(Okayama Univ.) |
| Secretary | Kenta Umebayashi(Shinshu Univ.) / Masayuki Ariyoshi(NICT) / Masafumi Kato(NTT) / Satoshi Denno(NICT) |
| Assistant | Kazuto Yano(ATR) / Mamiko Inamori(Tokai Univ.) / Hiroyuki Shiba(NTT) / Gia Khanh Tran(Tokyo Inst. of Tech.) / Wen Yun(Fujitsu) / Keiichi Mizutani(Kyoto Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Smart Radio / Technical Committee on Short Range Wireless Communications |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Technology Exhibit] Hardware Demonstration of Wi-Fi Fingerprint based Millimeter Wave Beamforming |
| Sub Title (in English) | |
| Keyword(1) | Millimeter WaveBeamformingWi-Fi FingerprintsBest Sector IDStatistical Learning |
| 1st Author's Name | Ehab Mahmoud Mohamed |
| 1st Author's Affiliation | Osaka University(Osaka Univ.) |
| 2nd Author's Name | Gia Khanh Tran |
| 2nd Author's Affiliation | Tokyo Institute of Technology(Tokyo Tech) |
| 3rd Author's Name | Kei Sakaguchi |
| 3rd Author's Affiliation | Tokyo Institute of Technology(Tokyo Tech) |
| 4th Author's Name | Seiichi Sampei |
| 4th Author's Affiliation | Osaka University(Osaka Univ.) |
| Date | 2015-10-27 |
| Paper # | SR2015-62,SRW2015-43 |
| Volume (vol) | vol.115 |
| Number (no) | SR-273,SRW-274 |
| Page | pp.pp.59-60(SR), pp.59-60(SRW), |
| #Pages | 2 |
| Date of Issue | 2015-10-19 (SR, SRW) |