activity
20162021
collaborators

7 papers

cs.IT2021

6G: Connectivity in the Era of Distributed Intelligence

Shilpa Talwar, Nageen Himayat, Hosein Nikopour +3

The confluence of 5G and AI is transforming wireless networks to deliver diverse services at the Edge, driving towards a vision of pervasive distributed intelligence. Future 6G net…

cs.DC2020

Coded Computing for Low-Latency Federated Learning over Wireless Edge Networks

Saurav Prakash, Sagar Dhakal, Mustafa Akdeniz +4

Federated learning enables training a global model from data located at the client nodes, without data sharing and moving client data to a centralized server. Performance of federa…

cs.NI2020

Handling Spontaneous Traffic Variations in 5G+ via Offloading onto mmWave-Capable UAV `Bridges'

Nikita Tafintsev, Dmitri Moltchanov, Sergey Andreev +4

Unmanned aerial vehicles (UAVs) are increasingly employed for numerous public and civil applications, such as goods delivery, medicine, surveillance, and telecommunications. For th…

cs.LG2020

Coded Federated Learning

Sagar Dhakal, Saurav Prakash, Yair Yona +2

Federated learning is a method of training a global model from decentralized data distributed across client devices. Here, model parameters are computed locally by each client devi…

cs.NI2019

Aerial Access and Backhaul in mmWave B5G Systems: Performance Dynamics and Optimization

Nikita Tafintsev, Dmitri Moltchanov, Mikhail Gerasimenko +7

The use of unmanned aerial vehicle (UAV)-based communication in millimeter-wave (mmWave) frequencies to provide on-demand radio access is a promising approach to improve capacity a…

cs.NI2016

Analysis of Human-Body Blockage in Urban Millimeter-Wave Cellular Communications

Margarita Gapeyenko, Andrey Samuylov, Mikhail Gerasimenko +7

The use of extremely high frequency (EHF) or millimeter-wave (mmWave) band has attracted significant attention for the next generation wireless access networks. As demonstrated by…