2.7k citations · 6.4k across the 135 of their papers we have counts for
145 papers
LWM-TF: A Wireless Foundation Model on 5G NR Time-Frequency Resource Grids
Namhyun Kim, Sadjad Alikhani, Ahmed Alkhateeb
Received OFDM grids preserve both pilot and payload observations, yet wireless foundation models are rarely pre-trained on them. We introduce LWM-TF, a 9.58M-parameter factorized m…
Energy-Efficient Spiking Neural Networks for Sensing-Aided Beam Prediction
Nhan Thanh Nguyen, Phuong Nam Tran, Mengyuan Ma +3
Sensing-aided beam prediction can reduce the beam-training overhead of millimeter-wave (mmWave) systems by leveraging environmental information from complementary modalities such a…
Freshness-Aware Constrained Sensing-Aided Beam Prediction with Knowledge Distillation
Abolfazl Zakeri, Nhan Thanh Nguyen, Ahmed Alkhateeb +1
Beam prediction leveraging environmental data reduces over-the-air beam training overhead. Existing frameworks, however, assume continuous access to fresh sensory data, an assumpti…
Beamforming Design Via GNN in mmWave Cell-Free Massive MIMO Using Sub-6 GHz CSI
Sina Tavakolian, Abolfazl Zakeri, Ahmed Alkhateeb +2
Beamforming methods in millimeter-wave (mmWave) cell-free massive multiple-input multiple-output (CFmMIMO) systems require accurate channel state information (CSI), whose acquisiti…
Digital Twin-Aided Prescreening for User Scheduling in MU-MIMO Downlink Systems
Namhyun Kim, Mahmoud Saad Abouamer, Jeonghun Park +2
In dense deployments, massive multi-user multiple-input multiple-output (MU-MIMO) base stations can acquire instantaneous channel state information (CSI) for only a limited subset…
Lightweight Vision-Aided Beam Tracking for Cross-Environment mmWave Communications
Mengyuan Ma, Ahmed Alkhateeb, Nhan Thanh Nguyen +2
Sensing-aided beam tracking is a promising approach to reduce the overhead for millimeter-wave beam management. However, real-world application remains challenging due to rapid cha…