1 citations · 2 across the 4 of their papers we have counts for
10 papers
SPOT: Single-Shot Positioning via Trainable Near-Field Rainbow Beamforming
Yeyue Cai, Jianhua Mo, Meixia Tao
Phase-time arrays, which integrate phase shifters (PSs) and true-time delays (TTDs), have emerged as a cost-effective architecture for generating frequency-dependent rainbow beams…
MARBLE-Net: Learning to Localize in Multipath Environment with Adaptive Rainbow Beams
Qiushi Liang, Yeyue Cai, Jianhua Mo +1
Integrated sensing and communication (ISAC) systems demand precise and efficient target localization, a task challenged by rich multipath propagation in complex wireless environmen…
Fed-PELAD: Communication-Efficient Federated Learning for Massive MIMO CSI Feedback with Personalized Encoders and a LoRA-Adapted Shared Decoder
Yixiang Zhou, Tong Wu, Meixia Tao +1
This paper addresses the critical challenges of communication overhead, data heterogeneity, and privacy in deep learning for channel state information (CSI) feedback in massive MIM…
SemCSINet: A Semantic-Aware CSI Feedback Network in Massive MIMO Systems
Ruonan Ren, Jianhua Mo, Meixia Tao
Massive multiple-input multiple-output (MIMO) technology is a key enabler of modern wireless communication systems, which demand accurate downlink channel state information (CSI) f…
CFARNet: Learning-Based High-Resolution Multi-Target Detection for Rainbow Beam Radar
Qiushi Liang, Yeyue Cai, Jianhua Mo +1
Millimeter-wave (mmWave) OFDM radar equipped with rainbow beamforming, enabled by phase-time arrays (PTAs), provides wide-angle coverage and is well-suited for fast real-time targe…
Beam Management with Orientation and RSRP using Deep Learning for Beyond 5G Systems
Khuong N. Nguyen, Anum Ali, Jianhua Mo +3
Beam management (BM), i.e., the process of finding and maintaining a suitable transmit and receive beam pair, can be challenging, particularly in highly dynamic scenarios. Side-inf…