4 citations · 5 across the 9 of their papers we have counts for
9 papers
Budget-Aware Federated Dual-Side Channel Estimation for Hybrid mmWave Massive MIMO
Jiawei Chen, Ruining Fan, Mouli Chakraborty +2
This work studies communication-constrained federated dual-side channel state information (CSI) estimation in hybrid millimeter-wave (mmWave) massive multiple input multiple output…
Comparative Analysis of Differential and Collision Entropy for Finite-Regime QKD in Hybrid Quantum Noisy Channels
Mouli Chakraborty, Subhash Chandra, Avishek Nag +3
In this work, a comparative study between three fundamental entropic measures, differential entropy, quantum Renyi entropy, and quantum collision entropy for a hybrid quantum chann…
Grover's Search-Inspired Quantum Reinforcement Learning for Massive MIMO User Scheduling
Ruining Fan, Xingyu Huang, Mouli Chakraborty +2
The efficient user scheduling policy in the massive Multiple Input Multiple Output (mMIMO) system remains a significant challenge in the field of 5G and Beyond 5G (B5G) due to its…
Quantum Deep Learning for Massive MIMO User Scheduling
Xingyu Huang, Ruining Fan, Mouli Chakraborty +2
We introduce a hybrid Quantum Neural Networks (QNN) architecture for the efficient user scheduling in 5G/Beyond 5G (B5G) massive Multiple Input Multiple Output (MIMO) systems, addr…
On the Achievable Rate of Satellite Quantum Communication Channel using Deep Autoencoder Gaussian Mixture Model
Mouli Chakraborty, Subhash Chandra, Avishek Nag +1
We present a comparative study of the Gaussian mixture model (GMM) and the Deep Autoencoder Gaussian Mixture Model (DAGMM) for estimating satellite quantum channel capacity, consid…
On the Impact of Classical and Quantum Communication Networks Upon Modular Quantum Computing Architecture System Performance
Pau Escofet, Abhijit Das, Sahar Ben Rached +15
Modular architectures are a promising approach to scaling quantum computers beyond the limits of monolithic designs. However, non-local communications between different quantum pro…
An Explainable AI Framework for Dynamic Resource Management in Vehicular Network Slicing
Haochen Sun, Yifan Liu, Ahmed Al-Tahmeesschi +4
Effective resource management and network slicing are essential to meet the diverse service demands of vehicular networks, including Enhanced Mobile Broadband (eMBB) and Ultra-Reli…
Optimized Resource Allocation for Cloud-Native 6G Networks: Zero-Touch ML Models in Microservices-based VNF Deployments
Swarna Bindu Chetty, Avishek Nag, Ahmed Al-Tahmeesschi +4
6G, the next generation of mobile networks, is set to offer even higher data rates, ultra-reliability, and lower latency than 5G. New 6G services will increase the load and dynamis…
An Unsupervised Machine Learning to Optimize Hybrid Quantum Noise Clusters for Gaussian Quantum Channel
Mouli Chakraborty, Anshu Mukherjee, Ioannis Krikidis +2
This work focuses on optimizing the hybrid quantum noise model to improve the capacity of Gaussian quantum channels using Machine Learning (ML) generated clusters. The work specifi…