14 papers
Strange-quark-number-dependent response to partonic dynamics in baryon-rich Au+Au collisions
Di Zhao, Xun Zhu, Gao-Chan Yong
We identify a strange-quark-number-dependent hierarchy in the response to explicit partonic dynamics by comparing PHSD5.2 with its hadron--string limit in baryon-rich Au+Au collisi…
GCNO: Gramian Chebyshev Neural Operator for Physics-Based Compression of Wireless Channels
Rafid Umayer Murshed, Shahab Hamidi-Rad, Elahe Soltanaghai +1
Large antenna arrays allow wireless systems to serve more users and achieve higher data rates, but they also make channel feedback expensive: the receiving device must repeatedly r…
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…
From Fewer Samples to Fewer Bits: Reframing Dataset Distillation as Joint Optimization of Precision and Compactness
My H. Dinh, Aditya Sant, Akshay Malhotra +2
Dataset Distillation (DD) compresses large datasets into compact synthetic ones that maintain training performance. However, current methods mainly target sample reduction, with li…
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…
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…
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…
Sculpting the Latent Space: Disentanglement with WAE-MMD and Programmable Priors
Quentin Fruytier, Akshay Malhotra, Shahab Hamidi-Rad +3
Learning disentangled representations, where semantic features are independently captured in a latent space, is dominated by Variational Auto Encoders (VAE) and Adversarial Trainin…
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…
Data-Driven Subsampling in the Presence of an Adversarial Actor
Abu Shafin Mohammad Mahdee Jameel, Ahmed P. Mohamed, Jinho Yi +2
Deep learning based automatic modulation classification (AMC) has received significant attention owing to its potential applications in both military and civilian use cases. Recent…