4 citations · 4 across the 4 of their papers we have counts for
5 papers
Hybrid SMI Realization via Matrix Completion and Riemannian Manifold Optimization on Narrowband Sub-Array Based Architectures
Tarun Suman Cousik, Rohit Rangaraj, Nishith Tripathi +3
Hybrid beamforming architectures reduce hardware complexity but restrict access to full array observations, rendering direct implementation of classical covariance based methods su…
Deep Learning based Fast and Accurate Beamforming for Millimeter-Wave Systems
Tarun S Cousik, Vijay K Shah, Jeffrey H. Reed Harry X Tran +1
The widespread proliferation of mmW devices has led to a surge of interest in antenna arrays. This interest in arrays is due to their ability to steer beams in desired directions,…
Deep Learning for Fast and Reliable Initial Access in AI-Driven 6G mmWave Networks
Tarun S. Cousik, Vijay K. Shah, Tugba Erpek +2
We present DeepIA, a deep neural network (DNN) framework for enabling fast and reliable initial access for AI-driven beyond 5G and 6G millimeter (mmWave) networks. DeepIA reduces t…
Fast Initial Access with Deep Learning for Beam Prediction in 5G mmWave Networks
Tarun S. Cousik, Vijay K. Shah, Jeffrey H. Reed +2
This paper presents DeepIA, a deep learning solution for faster and more accurate initial access (IA) in 5G millimeter wave (mmWave) networks when compared to conventional IA. By u…
CogRF: A New Frontier for Machine Learning and Artificial Intelligence for 6G RF Systems
Tarun Cousik, Rubayet Shafin, Zhou Zhou +3
The concept of CogRF, a novel tunable radio frequency (RF) frontend that uses artificial intelligence (AI) to meet mission requirements for beyond 5G and 6G systems, is introduced.…