7 citations · 12 across the 5 of their papers we have counts for
5 papers
Deep Reinforcement Learning-based Radio Resource Allocation and Beam Management under Location Uncertainty in 5G mmWave Networks
Yujie Yao, Hao Zhou, Melike Erol-Kantarci
Millimeter Wave (mmWave) is an important part of 5G new radio (NR), in which highly directional beams are adapted to compensate for the substantial propagation loss based on UE loc…
Variational Autoencoder Generative Adversarial Network for Synthetic Data Generation in Smart Home
Mina Razghandi, Hao Zhou, Melike Erol-Kantarci +1
Data is the fuel of data science and machine learning techniques for smart grid applications, similar to many other fields. However, the availability of data can be an issue due to…
Team Learning-Based Resource Allocation for Open Radio Access Network (O-RAN)
Han Zhang, Hao Zhou, Melike Erol-Kantarci
Recently, the concept of open radio access network (O-RAN) has been proposed, which aims to adopt intelligence and openness in the next generation radio access networks (RAN). It p…
Smart Home Energy Management: Sequence-to-Sequence Load Forecasting and Q-Learning
Mina Razghandi, Hao Zhou, Melike Erol-Kantarci +1
A smart home energy management system (HEMS) can contribute towards reducing the energy costs of customers; however, HEMS suffers from uncertainty in both energy generation and con…
Short-Term Load Forecasting for Smart HomeAppliances with Sequence to Sequence Learning
Mina Razghandi, Hao Zhou, Melike Erol-Kantarci +1
Appliance-level load forecasting plays a critical role in residential energy management, besides having significant importance for ancillary services performed by the utilities. In…