S
Samer Lahoud
Researcher at Saint Joseph's University
Publications - 131
Citations - 1143
Samer Lahoud is an academic researcher from Saint Joseph's University. The author has contributed to research in topics: Wireless network & Quality of service. The author has an hindex of 16, co-authored 121 publications receiving 926 citations. Previous affiliations of Samer Lahoud include University of Rennes & Institut de Recherche en Informatique et Systèmes Aléatoires.
Papers
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Journal ArticleDOI
LoRaWAN Network: Radio Propagation Models and Performance Evaluation in Various Environments in Lebanon
TL;DR: The results show that the proposed PL models for LoRaWAN communications are accurate and simple to be applied in Lebanon and other similar locations, and reveals the reliability of this promising technology for long-range IoT communications.
Journal ArticleDOI
A Network-Assisted Approach for RAT Selection in Heterogeneous Cellular Networks
TL;DR: A network-assisted approach to optimal, learning-based, and heuristic policies, such as blocking probability and average throughput, and a reinforcement learning approach is introduced to derive what to signal to mobiles.
Proceedings ArticleDOI
RRH clustering in cloud radio access networks
TL;DR: This paper investigates the BBU-RRH mapping, also known as the RRH clustering problem, and forms it as a bin packing problem and proves that the heuristic achieves close performance to the optimal solution.
Journal ArticleDOI
Survey of ICIC techniques in LTE networks under various mobile environment parameters
Mohamad Yassin,Mohamed A. Aboulhassan,Samer Lahoud,Marc Ibrahim,Dany Mezher,Bernard Cousin,Essam Sourour +6 more
TL;DR: A comprehensive survey on Inter-Cell Interference Coordination techniques is performed, and the most suitable ICIC technique for each network scenario is identified under several parameters such as different network loads, radio conditions, and user distributions.
Proceedings ArticleDOI
LoRa-MAB: A Flexible Simulator for Decentralized Learning Resource Allocation in IoT Networks
TL;DR: The proposed simulator provides a flexible and efficient environment to evaluate various network design parameters and self-management solutions as well as verify the effectiveness of distributed reinforcement-based learning algorithms for resource allocation problems in LoRaWAN.