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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
RCS, SAT
(Joint)
2023-08-31
10:30
Nagano Naganoken Nokyo Building, and online
(Primary: On-site, Secondary: Online)
Enhancing CSI Feedback in FDD Massive MIMO Systems using Dropout-based Deep Neural Network
Junjie Gao, Mondher Bouazizi, Tomoaki Ohtsuki (Keio Univ.), Guan Gui (NJUPT) RCS2023-101
Accessing precise downlink channel state information (CSI) is crucial in maximizing the
benefits of frequency division ... [more]
RCS2023-101
pp.1-4
RCS, SR, SRW
(Joint)
2023-03-01
10:25
Tokyo Tokyo Institute of Technology, and Online
(Primary: On-site, Secondary: Online)
A Novel DNN-based CSI Feedback with Quantization for FDD Massive MIMO Systems
Junjie Gao, Mondher Bouazizi, Tomoaki Ohtsuki (Keio Univ.), Gui Guan (NJUPT) RCS2022-252
Accessing the accurate downlink channel state information
(CSI) is essential to take full advantage of frequency
divis... [more]
RCS2022-252
pp.31-35
MIKA
(3rd)
2022-10-14
10:40
Niigata Niigata Citizens Plaza
(Primary: On-site, Secondary: Online)
[Poster Presentation] A New CSI Feedback with Quantization Based on Adaptive DNN for FDD Massive MIMO Systems
Junjie Gao, Mondher Bouazizi, Tomoaki Ohtsuki (Keio Univ.), Guan Gui (NJUPT)
Accessing the accurate downlink channel state information (CSI) is essential to take full advantage of frequency divisio... [more]
 Results 1 - 3 of 3  /   
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