膨大な分散データの利活用が重要なインフラとなる次世代に向け、ワイヤレス、時空間統計、分散処理などの観点から研究を進めています。
キーワード: 無線ネットワーク, Beyond 5G/6G, センシング, 時空間統計, 分散機械学習, ガウス過程, ...
Our group works in research from various perspectives (e.g., wireless, spatio-temporal statistics, and distributed processing) for the next generation, in which data and sensors will become an essential social infrastructure.
Keywords: Wireless networks, spatio-temporal statistics, distributed machine learning, Gaussian processes, ...
A co-authored paper has been accepted for publication in IEEE Internet of Things Journal (Q1, IF: 8.2).
K. Ando et al., "Bayesian Optimization aided Low-Complexity Beamforming Design for Over-the-Air-Computing."
Our paper has been accepted for publication in IEEE Transactions on Cognitive Communications and Networking (Q1, IF: 7.4).
K. Sato and K. Ishibashi, "Adaptively Weighted Averaging Over-the-Air Computation and Its Application to Distributed Gaussian Process Regression." [IEEE Xplore]
A co-authored paper has been accepted for publication in IEEE Access (Q2, IF: 3.4).
M. Miura et al., "Fast Reflective Beamforming with Situational Awareness in IRS Assisted Communication Systems." [IEEE Xplore]
第4期生が配属
A co-authored has been accepted for publication in IEEE Wireless Communications Letters (Q1, IF: 4.6).
N. Suga et al., "RGB-D Sensor-Aided Radio Map Estimation Using Materials Classification." [IEEE Xplore]
博士前期課程学生2名が修了
M1 神崎が令和6年度電気通信大学 学生表彰を受賞
佐藤助教を研究代表者とした研究課題が科研費 基盤研究(B)に採択決定
題目: "デジタルツインに資するISACの時空間展開フレームワーク"
期間: 2025年4月-2029年3月