Individual-Driven Spiking-Mixer Deep Learning Model for IRS-Assisted mmWave Systems Beam Training. - Taisei Urakami; Haohui Jia; Dafang Zhao; Na Chen 004; Minoru Okada (GCCE, 2023)

IRS-Assisted mmWave Massive MIMO Systems Beam Training with Hybrid CNN Encoder-based Transformer Deep Learning Model. - Taisei Urakami; Haohui Jia; Na Chen 004; Minoru Okada (VTC Fall, 2023)

Spatial attention and quantization-based contrastive learning framework for mmWave massive MIMO beam training. - Haohui Jia; Na Chen 004; Taisei Urakami; Hui Gao 001; Minoru Okada (EURASIP J. Wirel. Commun. Netw., 2023)

Interdigital and Multi-Via Structures for Mushroom-Type Metasurface Reflectors. - Taisei Urakami; Tamami Maruyama; Shimpei Nishiyama; Manato Kusamizu; Akira Ono; Takahiro Shiozawa (IEICE Trans. Commun., 2024)

Self-enhanced multi-task and split federated learning framework for RIS-aided cell-free systems. - Taisei Urakami; Haohui Jia; Na Chen 004; Minoru Okada (Internet Things, 2024)