8 papers · 1 filter
Unlocking Realism and Interpretability in Wireless Channel Synthesis: A Physics-Guided Generative Approach
Satyavrat Wagle, Akshay Malhotra, Shahab Hamidi-Rad +3
In recent years, machine learning (ML) methods have become increasingly popular for wireless communication systems. These require large amounts of data reflecting the behavior of r…
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…
Comparing Stochastic and Ray-tracing Datasets in Machine Learning for Wireless Applications
João Morais, Akshay Malhotra, Shahab Hamidi-Rad +1
Machine learning for wireless systems is commonly studied using standardized stochastic channel models (e.g., TDL/CDL/UMa) because of their legacy in wireless communication standar…
Physics-based Generative Models for Geometrically Consistent and Interpretable Wireless Channel Synthesis
Satyavrat Wagle, Akshay Malhotra, Shahab Hamidi-Rad +3
In recent years, machine learning (ML) methods have become increasingly popular in wireless communication systems for several applications. A critical bottleneck for designing ML s…
Physics-Informed Generative Approaches for Wireless Channel Modeling
Satyavrat Wagle, Akshay Malhotra, Shahab Hamidi-Rad +3
In recent years, machine learning (ML) methods have become increasingly popular in wireless communication systems for several applications. A critical bottleneck for designing ML s…
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…
Deep OFDM Channel Estimation: Capturing Frequency Recurrence
Abu Shafin Mohammad Mahdee Jameel, Akshay Malhotra, Aly El Gamal +1
In this paper, we propose a deep-learning-based channel estimation scheme in an orthogonal frequency division multiplexing (OFDM) system. Our proposed method, named Single Slot Rec…
Vandermonde Constrained Tensor Decomposition for Hybrid Beamforming in Multi-Carrier MIMO Systems
Mohamed Salah Ibrahim, Akshay Malhotra, Mihaela Beluri +2
Hybrid beamforming has evolved as a promising technology that offers the balance between system performance and design complexity in mmWave MIMO systems. Existing hybrid beamformin…