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Aditya Sant

5 accepted papers

2025

Physics-based Generative Models for Geometrically Consistent and Interpretable Wireless Channel Synthesis

Satyavrat Wagle, Akshay Malhotra, Shahab Hamidi-Rad, Aditya Sant, David J. Love, Christopher G. Brinton
IJCAI 2025

In recent years, machine learning (ML) methods have become increasingly popular in wireless communication systems for several applications. A critical bottleneck for designing ML systems for wireless communications is the availability of realistic wireless channel datasets, which are extremely resou

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2023

Regularized Neural Detection for Millimeter Wave Massive Mimo Communication Systems with One-Bit Adcs

Aditya Sant, Bhaskar D. Rao
ICASSP 2023accepted

Multi-user massive MIMO signal detection from one-bit received measurements strongly depends on the wireless channel. To this end, majority of the model and learning-based approaches address detector design for the rich-scattering, homogeneous Rayleigh fading channel. Our work proposes detection for…

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2022

Deep Sequential Beamformer Learning for Multipath Channels in Mmwave Communication Systems

Aditya Sant, Afshin Abdi, Joseph Soriaga
ICASSP 2022accepted

The highly directional nature of mmWave channels results in a mutlipath incoming signal, often with varying power levels. To exploit the complete diversity of this channel, beamformer design should incorporate this multipath. This increases pilot overhead for initial access. However, low latency mmW…

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2021

General Total Variation Regularized Sparse Bayesian Learning for Robust Block-Sparse Signal Recovery

Aditya Sant, Markus Leinonen, Bhaskar D. Rao
ICASSP 2021accepted

Block-sparse signal recovery without knowledge of block sizes and boundaries, such as those encountered in multi-antenna mmWave channel models, is a hard problem for compressed sensing (CS) algorithms. We propose a novel Sparse Bayesian Learning (SBL) method for block-sparse recovery based on popula…

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