most citedInterference Prediction Using Gaussian Process Regression and Management Framework for Critical Services in Local 6G Networks

5 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

eess.SP2026

Improved GPR-Based CSI Acquisition via Spatial-Correlation Kernel

Syed Luqman Shah, Nurul Huda Mahmood, Italo Atzeni

Accurate channel estimation with low pilot overhead and computational complexity is key to efficiently utilizing multi-antenna wireless systems. Motivated by the evolution from pur…

eess.SP2025

A Novel Geometry-Aware GPR-Based Energy-Efficient and Low-Overhead Channel Estimation Scheme

Syed Luqman Shah, Nurul Huda Mahmood

Accurate channel state information (CSI) acquisition under tight pilot and training-energy constraints is essential for next-generation wireless networks. In this work, we model th…

eess.SP2025★ 2 cited

Low-Overhead CSI Prediction via Gaussian Process Regression

Syed Luqman Shah, Nurul Huda Mahmood, Italo Atzeni

Accurate channel state information (CSI) is critical for current and next-generation multi-antenna systems. Yet conventional pilot-based estimators incur prohibitive overhead as an…

cs.NI2025★ 2 cited

Energy-Efficient and Reliable Data Collection in Receiver-Initiated Wake-up Radio Enabled IoT Networks

Syed Luqman Shah, Ziaul Haq Abbas, Ghulam Abbas +1

In unmanned aerial vehicle (UAV)-assisted wake-up radio (WuR)-enabled internet of things (IoT) networks, UAVs can instantly activate the main radios (MRs) of the sensor nodes (SNs)…

eess.SP2025★ 5 cited

Interference Prediction Using Gaussian Process Regression and Management Framework for Critical Services in Local 6G Networks

Syed Luqman Shah, Nurul Huda Mahmood, Matti Latva-aho

Interference prediction and resource allocation are critical challenges in mission-critical applications where stringent latency and reliability constraints must be met. This paper…