collaborators

6 papers

cs.NI2026

ML-Based Real-Time Downlink Performance Prediction in Standalone 5G NR Using Smartphones

Md Mahfuzur Rahman, Jareen Shuva, Nishith Tripathi +2

We propose a machine learning (ML)-based framework for downlink performance prediction in 5G networks using real-time measurements from commercial off-the-shelf (COTS) user equipme…

cs.NI2026

ML and Smartphones Assisted Real-Time Uplink Performance Prediction in 5G Cellular System

Md Mahfuzur Rahman, Jareen Shuva, Nishith Tripathi +2

We propose a machine learning (ML) and smartphone-assisted framework for uplink performance prediction in a private, realistic 5G cellular system using real-time measurements in bo…

cs.ET2025

Developing an NTN Architecture for End-to-End Performance Evaluation

Md Mahfuzur Rahman, Nishith Tripathi, Jeffrey H. Reed +1

Non-Terrestrial Networks (NTN) are emerging as critical enablers of global connectivity, particularly in remote, unserved, underserved, or maritime regions lacking traditional infr…

eess.SP2025

Communication in a Fractional World: MIMO MC-OTFS Precoder Prediction

Evan Allen, Karim Said, Robert Calderbank +1

As 6G technologies advance, international bodies and regulatory agencies are intensifying efforts to extend seamless connectivity especially for high-mobility scenarios such as Mob…

eess.SP2025

Mobile Distributed MIMO (MD-MIMO) for NextG: Mobility Meets Cooperation in Distributed Arrays

Karim A. Said, Yibin Liang, Usama Saeed +13

Distributed multiple-input multiple-output (D\mbox{-}MIMO) is a promising technology to realize the promise of massive MIMO gains by fiber-connecting the distributed antenna arrays…

eess.SP2025

Distributed Uplink Joint Transmission for 6G Communication

Kumar Sai Bondada, Usama Saeed, Yibin Liang +3

This paper investigates the spectral efficiency achieved through uplink joint transmission, where a serving user and the network users (UEs) collaborate by jointly transmitting to…