2 citations · 4 across the 10 of their papers we have counts for
20 papers
Evolutionary Deep Reinforcement Learning for Dynamic Slice Management in O-RAN
Fatemeh Lotfi, Omid Semiari, Fatemeh Afghah
The next-generation wireless networks are required to satisfy a variety of services and criteria concurrently. To address upcoming strict criteria, a new open radio access network…
Variational Autoencoders for Reliability Optimization in Multi-Access Edge Computing Networks
Arian Ahmadi, Omid Semiari, Mehdi Bennis +1
Multi-access edge computing (MEC) is viewed as an integral part of future wireless networks to support new applications with stringent service reliability and latency requirements.…
Performance Analysis and Optimization of Uplink Cellular Networks with Flexible Frame Structure
Fatemeh Lotfi, Omid Semiari
Future wireless cellular networks must support both enhanced mobile broadband (eMBB) and ultra reliable low latency communication (URLLC) to manage heterogeneous data traffic for e…
Reinforcement Learning for Optimized Beam Training in Multi-Hop Terahertz Communications
Arian Ahmadi, Omid Semiari
Communication at terahertz (THz) frequency bands is a promising solution for achieving extremely high data rates in next-generation wireless networks. While the THz communication i…
Reinforcement Learning for Mitigating Intermittent Interference in Terahertz Communication Networks
Reza Barazideh, Omid Semiari, Solmaz Niknam +1
Emerging wireless services with extremely high data rate requirements, such as real-time extended reality applications, mandate novel solutions to further increase the capacity of…
Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms
Tengchan Zeng, Omid Semiari, Mohammad Mozaffari +3
Unmanned aerial vehicle (UAV) swarms must exploit machine learning (ML) in order to execute various tasks ranging from coordinated trajectory planning to cooperative target recogni…