activity
20162021
most citedZero-touch Continuous Network Slicing Control via Scalable Actor-Critic Learning

12 citations · 12 across the 3 of their papers we have counts for

collaborators

7 papers

cs.NI202112 cited

Zero-touch Continuous Network Slicing Control via Scalable Actor-Critic Learning

Farhad Rezazadeh, Hatim Chergui, Christos Verikoukis

Artificial intelligence (AI)-driven zero-touch network slicing is envisaged as a promising cutting-edge technology to harness the full potential of heterogeneous 5G and beyond 5G (…

cs.NI2021

Continuous Multi-objective Zero-touch Network Slicing via Twin Delayed DDPG and OpenAI Gym

Farhad Rezazadeh, Hatim Chergui, Luis Alonso +1

Artificial intelligence (AI)-driven zero-touch network slicing (NS) is a new paradigm enabling the automation of resource management and orchestration (MANO) in multi-tenant beyond…

cs.IT2019

Self-Tuning Spectral Clustering for Adaptive Tracking Areas Design in 5G Ultra-Dense Networks

Brahim Aamer, Hatim Chergui, Nouamane Chergui +4

In this paper, we address the issue of automatic tracking areas (TAs) planning in fifth generation (5G) ultra-dense networks (UDNs). By invoking handover (HO) attempts and measurem…

cs.IT2018

Classification Algorithms for Semi-Blind Uplink/Downlink Decoupling in sub-6 GHz/mmWave 5G Networks

Hatim Chergui, Kamel Tourki, Redouane Lguensat +3

Reliability and latency challenges in future mixed sub-6 GHz/millimeter wave (mmWave) fifth generation (5G) cell-free massive multiple-input multiple-output (MIMO) networks is to g…

cs.DC2018

MaRe: a MapReduce-Oriented Framework for Processing Big Data with Application Containers

Marco Capuccini, Martin Dahlö, Salman Toor +1

Background. Life science is increasingly driven by Big Data analytics, and the MapReduce programming model has been proven successful for data-intensive analyses. However, current…

cs.IT2018

Rician -Factor-Based Analysis of XLOS Service Probability in 5G Outdoor Ultra-Dense Networks

Hatim Chergui, Mustapha Benjillali, Mohamed-Slim Alouini

In this report, we introduce the concept of Rician -factor-based radio resource and mobility management for fifth generation (5G) ultra-dense networks (UDN), where the informati…