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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 4 of 4  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
MW 2023-03-02
10:40
Tottori Tottori Univ.
(Primary: On-site, Secondary: Online)
Memory-Driven MLP-Mixer Deep Learning Model for Intelligent Reflecting Surface-Assisted mmWave Systems Beam Prediction
Taisei Urakami, Haohui Jia, Na Chen, Minoru Okada (NAIST) MW2022-159
Although deep learning (DL) based beam prediction for intelligent reflecting surface (IRS)-assisted millimeter wave (mmW... [more] MW2022-159
pp.13-18
RCS, NS
(Joint)
2022-12-15
09:45
Aichi Nagoya Institute of Technology, and Online
(Primary: On-site, Secondary: Online)
Efficient Beam Prediction for Intelligent Reflecting Surface-Assisted mmWave Systems based on Memory Driven Simple Transformer Deep Learning Model
Taisei Urakami, Haohui Jia, Na Chen, Minoru Okada (NAIST) RCS2022-185
In this paper, we propose a memory driven simple transformer (MDST) deep learning (DL) model with the autoregressive mod... [more] RCS2022-185
pp.1-6
NS, SR, RCS, SeMI, RCC
(Joint)
2022-07-14
15:25
Ishikawa The Kanazawa Theatre + Online
(Primary: On-site, Secondary: Online)
Temporal Sequence Modeling and Spatial Attention for High Reliable mmWave Massive MIMO Beam Prediction
Haohui Jia, Zaoshi Wang, Na Chen, Minoru Okada (NAIST) RCC2022-30
 [more] RCC2022-30
pp.57-62
RCC, ITS, WBS 2019-11-06
11:00
Nara Nara Institute of Science and Technology [Poster Presentation] Precision comparison of channel estimation in single-carrier FDMA using compressed sensing technique
Haohui Jia, Takeshi Higashino, Minoru Okada (NAIST) WBS2019-29 ITS2019-20 RCC2019-60
Single carrier frequency division multiple access (SC-FDMA) system re- duces a peak to average power ratio comparing wit... [more] WBS2019-29 ITS2019-20 RCC2019-60
pp.31-36
 Results 1 - 4 of 4  /   
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