5 citations · 5 across the 8 of their papers we have counts for
9 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…
LWM-CDE: A Representation Space for Wireless Data Reasoning and Transferability
Sadjad Alikhani, Akshay Malhotra, Shahab Hamidi-Rad +1
Machine learning deployments in real-world wireless communication tasks face significant generalization challenges due to location and environment-specific signal structure, high d…
LWM-Temporal: Sparse Spatio-Temporal Attention for Wireless Channel Representation Learning
Sadjad Alikhani, Akshay Malhotra, Shahab Hamidi-Rad +1
LWM-Temporal is a new member of the Large Wireless Models (LWM) family that targets the spatiotemporal nature of wireless channels. Designed as a task-agnostic foundation model, LW…
LWM-Spectro: A Foundation Model for Wireless Baseband Signal Spectrograms
Namhyun Kim, Sadjad Alikhani, Ahmed Alkhateeb
The received in-phase and quadrature (I/Q) baseband signals inherently encode physical-layer and channel characteristics of wireless links. Learning robust and transferable represe…
Wireless Dataset Similarity: Measuring Distances in Supervised and Unsupervised Machine Learning
João Morais, Sadjad Alikhani, Akshay Malhotra +2
This paper introduces a task- and model-aware framework for measuring similarity between wireless datasets, enabling applications such as dataset selection/augmentation, simulation…
Digital Twin Aided Channel Estimation: Zone-Specific Subspace Prediction and Calibration
Sadjad Alikhani, Ahmed Alkhateeb
Effective channel estimation in sparse and high-dimensional environments is essential for next-generation wireless systems, particularly in large-scale MIMO deployments. This paper…
A Dataset Similarity Evaluation Framework for Wireless Communications and Sensing
Joao Morais, Sadjad Alikhani, Akshay Malhotra +2
This paper introduces a task-specific, model-agnostic framework for evaluating dataset similarity, providing a means to assess and compare dataset realism and quality. Such a frame…
Large Wireless Model (LWM): A Foundation Model for Wireless Channels
Sadjad Alikhani, Gouranga Charan, Ahmed Alkhateeb
This paper presents Large Wireless Model (LWM) -- the world's first foundation model for wireless channels. Designed as a task-agnostic model, LWM generates universal, rich, contex…
Digital Twin Aided RIS Communication: Robust Beamforming and Interference Management
Sadjad Alikhani, Ahmed Alkhateeb
Reconfigurable intelligent surfaces (RISs) are envisioned to play a key role in future wireless communication networks. However, channel estimation in RIS-aided wireless networks i…