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Committee Date Time Place Paper Title / Authors Abstract Paper #
SIP, IT, RCS 2024-01-18
11:45
Miyagi
(Primary: On-site, Secondary: Online)
A Study on Massive MIMO Channel Estimation Based on Sparse Bayesian Learning Using Hierarchical Model
Kengo Furuta, Takumi Takahashi, Kenta Ito (Osaka Univ.), Shinsuke Ibi (Doshisha Uni.) IT2023-34 SIP2023-67 RCS2023-209
Massive multi-input multi-output (MIMO) channels are known to have pseudo-sparsity in the angular (beam) domain, and it ... [more] IT2023-34 SIP2023-67 RCS2023-209
pp.25-30
RCS 2022-06-17
09:30
Okinawa University of the Ryukyus, Senbaru Campus and online
(Primary: On-site, Secondary: Online)
A study on Joint Channel and Data Estimation via Parametric Bilinear Inference for OTFS Transmission
Kengo Furuta, Kenta Ito, Takumi Takahashi (Osaka Univ), Shinsuke Ibi (Doshisha Univ), Seiichi Sampei (Osaka Univ) RCS2022-56
In high-speed mobile communication environments, an orthogonal time frequency space (OTFS) scheme with robustness to dou... [more] RCS2022-56
pp.188-193
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