406 citations · 527 across the 20 of their papers we have counts for
26 papers
Communication-Efficient Orchestrations for URLLC Service via Hierarchical Reinforcement Learning
Wei Shi, Milad Ganjalizadeh, Hossein Shokri Ghadikolaei +1
Ultra-reliable low latency communications (URLLC) service is envisioned to enable use cases with strict reliability and latency requirements in 5G. One approach for enabling URLLC…
Reinforcement Learning-based Joint Handover and Beam Tracking in Millimeter-wave Networks
Sara Khosravi, Hossein S. Ghadikolaei, Jens Zander +1
In this paper, we develop an algorithm for joint handover and beam tracking in millimeter-wave (mmWave) networks. The aim is to provide a reliable connection in terms of the achiev…
BSAC-CoEx: Coexistence of URLLC and Distributed Learning Services via Device Selection
Milad Ganjalizadeh, Hossein Shokri Ghadikolaei, Deniz Gündüz +1
Recent advances in distributed intelligence have driven impressive progress across a diverse range of applications, from industrial automation to autonomous transportation. Neverth…
A-LAQ: Adaptive Lazily Aggregated Quantized Gradient
Afsaneh Mahmoudi, José Mairton Barros Da Silva Júnior, Hossein S. Ghadikolaei +1
Federated Learning (FL) plays a prominent role in solving machine learning problems with data distributed across clients. In FL, to reduce the communication overhead of data betwee…
Interplay between Distributed AI Workflow and URLLC
Milad Ganjalizadeh, Hossein S. Ghadikolaei, Johan Haraldson +1
Distributed artificial intelligence (AI) has recently accomplished tremendous breakthroughs in various communication services, ranging from fault-tolerant factory automation to sma…
Beam Alignment Using Trajectory Information in Mobile Millimeter-wave Networks
Sara Khosravi, Hossein S. Ghadikolaei, Jens Zander +1
Millimeter-wave and terahertz systems rely on beamforming/combining codebooks to determine the best beam directions during the initial access and data transmission. Existing approa…
Location-Aided Beamforming in Mobile Millimeter-Wave Networks
Sara Khosravi, Hossein S. Ghadikolaeiy, Jens Zander +1
Due to the large bandwidth available, millimeter-Wave (mmWave) bands are considered a viable opportunity to significantly increase the data rate in cellular and wireless networks.…
FedCau: A Proactive Stop Policy for Communication and Computation Efficient Federated Learning
Afsaneh Mahmoudi, Hossein S. Ghadikolaei, José Mairton Barros Da Silva Júnior +1
This paper investigates efficient distributed training of a Federated Learning~(FL) model over a wireless network of wireless devices. The communication iterations of the distribut…
Learning-based Load Balancing Handover in Mobile Millimeter Wave Networks
Sara Khosravi, Hossein S. Ghadikolaei, Marina Petrova
Millimeter-wave (mmWave) communication is a promising solution to the high data rate demands in the upcoming 5G and beyond communication networks. When it comes to supporting seaml…
A Hybrid Model-based and Data-driven Approach to Spectrum Sharing in mmWave Cellular Networks
Hossein S. Ghadikolaei, Hadi Ghauch, Gabor Fodor +2
Inter-operator spectrum sharing in millimeter-wave bands has the potential of substantially increasing the spectrum utilization and providing a larger bandwidth to individual user…
Communication-efficient Variance-reduced Stochastic Gradient Descent
Hossein S. Ghadikolaei, Sindri Magnusson
We consider the problem of communication efficient distributed optimization where multiple nodes exchange important algorithm information in every iteration to solve large problems…
Efficient Beamforming for Mobile mmWave Networks
Sara Khosravi, Hossein S. Ghadikolaei, Marina Petrova
We design a lightweight beam-searching algorithm for mobile millimeter-wave systems. We construct and maintain a set of path skeletons, i.e., potential paths between a user and the…
On Maintaining Linear Convergence of Distributed Learning and Optimization under Limited Communication
Sindri Magnússon, Hossein Shokri-Ghadikolaei, Na Li
In distributed optimization and machine learning, multiple nodes coordinate to solve large problems. To do this, the nodes need to compress important algorithm information to bits…
Fast and Reliable Initial Access with Random Beamforming for mmWave Networks
Yanpeng Yang, Hossein S. Ghadikolaei, Carlo Fischione +2
Millimeter-wave (mmWave) communications rely on directional transmissions to overcome severe path loss. Nevertheless, the use of narrow beams complicates the initial access procedu…
Learning Kolmogorov Models for Binary Random Variables
Hadi Ghauch, Mikael Skoglund, Hossein Shokri-Ghadikolaei +2
We summarize our recent findings, where we proposed a framework for learning a Kolmogorov model, for a collection of binary random variables. More specifically, we derive condition…
A Unified Framework for Training Neural Networks
Hadi Ghauch, Hossein Shokri-Ghadikolaei, Carlo Fischione +1
The lack of mathematical tractability of Deep Neural Networks (DNNs) has hindered progress towards having a unified convergence analysis of training algorithms, in the general sett…
Reducing Initial Cell-search Latency in mmWave Networks
Yanpeng Yang, Hossein S. Ghadikolaei, Carlo Fischione +2
Millimeter-wave (mmWave) networks rely on directional transmissions, in both control plane and data plane, to overcome severe path-loss. Nevertheless, the use of narrow beams compl…
Interference Model Similarity Index and Its Applications to mmWave Networks: Extended version
Hossein Shokri-Ghadikolaei, Carlo Fischione, Eytan Modiano
In wireless communication networks, interference models are routinely used for tasks such as performance analysis, optimization, and protocol design. These tasks are heavily affect…
Distributed Association and Relaying with Fairness in Millimeter Wave Networks
Yuzhe Xu, Hossein Shokri-Ghadikolaei, Carlo Fischione
Millimeter wave (mmWave) systems are emerging as an essential technology to enable extremely high data rate wireless communications. The main limiting factors of mmWave systems are…
On the Accuracy of Interference Models in Wireless Communications
Hossein Shokri-Ghadikolaei, Carlo Fischione, Eytan Modiano
We develop a new framework for measuring and comparing the accuracy of any wireless interference models used in the analysis and design of wireless networks. Our approach is based…
On the Relay-Fallback Tradeoff in Millimeter Wave Wireless System
Roberto Congiu, Hossein Shokri-Ghadikolaei, Carlo Fischione +1
Millimeter wave (mmWave) communications systems are promising candidate to support extremely high data rate services in future wireless networks. MmWave communications exhibit high…
The Transitional Behavior of Interference in Millimeter Wave Networks and Its Impact on Medium Access Control
Hossein Shokri-Ghadikolaei, Carlo Fischione
Millimeter wave (mmWave) communication systems use large number of antenna elements that can potentially overcome severe channel attenuation by narrow beamforming. Narrow-beam oper…
Millimeter Wave Ad Hoc Networks: Noise-limited or Interference-limited?
Hossein Shokri-Ghadikolaei, Carlo Fischione
In millimeter wave (mmWave) communication systems, narrow beam operations overcome severe channel attenuations, reduce multiuser interference, and thus introduce the new concept of…
Millimeter Wave Cellular Networks: A MAC Layer Perspective
Hossein Shokri-Ghadikolaei, Carlo Fischione, Gabor Fodor +2
The millimeter wave (mmWave) frequency band is seen as a key enabler of multi-gigabit wireless access in future cellular networks. In order to overcome the propagation challenges,…