125 citations · 414 across the 21 of their papers we have counts for
24 papers
Client Selection Approach in Support of Clustered Federated Learning over Wireless Edge Networks
Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha +1
Clustered Federated Multitask Learning (CFL) was introduced as an efficient scheme to obtain reliable specialized models when data is imbalanced and distributed in a non-i.i.d. (no…
Emotion Recognition for Healthcare Surveillance Systems Using Neural Networks: A Survey
Marwan Dhuheir, Abdullatif Albaseer, Emna Baccour +3
Recognizing the patient's emotions using deep learning techniques has attracted significant attention recently due to technological advancements. Automatically identifying the emot…
Fine-Grained Data Selection for Improved Energy Efficiency of Federated Edge Learning
Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha +1
In Federated edge learning (FEEL), energy-constrained devices at the network edge consume significant energy when training and uploading their local machine learning models, leadin…
Deep Reinforcement Learning for Radio Resource Allocation and Management in Next Generation Heterogeneous Wireless Networks: A Survey
Abdulmalik Alwarafy, Mohamed Abdallah, Bekir Sait Ciftler +2
Next generation wireless networks are expected to be extremely complex due to their massive heterogeneity in terms of the types of network architectures they incorporate, the types…
Deep Reinforcement Learning Powered IRS-Assisted Downlink NOMA
Muhammad Shehab, Bekir S. Ciftler, Tamer Khattab +2
In this work, we examine an intelligent reflecting surface (IRS) assisted downlink non-orthogonal multiple access (NOMA) scenario with the aim of maximizing the sum rate of users.…
Threshold-Based Data Exclusion Approach for Energy-Efficient Federated Edge Learning
Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha +1
Federated edge learning (FEEL) is a promising distributed learning technique for next-generation wireless networks. FEEL preserves the user's privacy, reduces the communication cos…
DQN-Based Multi-User Power Allocation for Hybrid RF/VLC Networks
Bekir Sait Ciftler, Abdulmalik Alwarafy, Mohamed Abdallah +1
In this paper, a Deep Q-Network (DQN) based multi-agent multi-user power allocation algorithm is proposed for hybrid networks composed of radio frequency (RF) and visible light com…
Federated Mimic Learning for Privacy Preserving Intrusion Detection
Noor Ali Al-Athba Al-Marri, Bekir Sait Ciftler, Mohamed Abdallah
Internet of things (IoT) devices are prone to attacks due to the limitation of their privacy and security components. These attacks vary from exploiting backdoors to disrupting the…
A Survey on Security and Privacy Issues in Edge Computing-Assisted Internet of Things
Abdulmalik Alwarafy, Khaled A. Al-Thelaya, Mohamed Abdallah +2
Internet of Things (IoT) is an innovative paradigm envisioned to provide massive applications that are now part of our daily lives. Millions of smart devices are deployed within co…
Outage Analysis of Cognitive Electric Vehicular Networks over Mixed RF/VLC Channels
Galymzhan Nauryzbayev, Mohamed Abdallah, Naofal Al-Dhahir
Modern transportation infrastructures are considered as one of the main sources of the greenhouse gases emitted into the atmosphere. This situation requires the decision-making pla…
Federated Learning for Localization: A Privacy-Preserving Crowdsourcing Method
Bekir Sait Ciftler, Abdullatif Albaseer, Noureddine Lasla +1
Received Signal Strength (RSS) fingerprint-based localization has attracted a lot of research effort and cultivated many commercial applications of location-based services due to i…
Exploiting Unlabeled Data in Smart Cities using Federated Learning
Abdullatif Albaseer, Bekir Sait Ciftler, Mohamed Abdallah +1
Privacy concerns are considered one of the main challenges in smart cities as sharing sensitive data brings threatening problems to people's lives. Federated learning has emerged a…
B-Ride: Ride Sharing with Privacy-preservation, Trust and Fair Payment atop Public Blockchain
Mohamed Baza, Noureddine Lasla, Mohamed Mahmoud +2
Ride-sharing is a service that enables drivers to share their trips with other riders, contributing to appealing benefits of shared travel costs. However, the majority of existing…
Detecting Sybil Attacks using Proofs of Work and Location in VANETs
Mohamed Baza, Mahmoud Nabil, Niclas Bewermeier +3
In this paper, we propose a Sybil attack detection scheme using proofs of work and location. The idea is that each road side unit (RSU) issues a signed time-stamped tag as a proof…
Efficient and Privacy-Preserving Ride Sharing Organization for Transferable and Non-Transferable Services
Mahmoud Nabil, Ahmed Sherif, Mohamed Mahmoud +2
Ride-sharing allows multiple persons to share their trips together in one vehicle instead of using multiple vehicles. This can reduce the number of vehicles in the street, which co…
Outage Probability of the EH-based Full-Duplex AF and DF Relaying Systems in α-μEnvironment
Galymzhan Nauryzbayev, Mohamed Abdallah, Khaled M. Rabie
Wireless power transfer and energy harvesting have attracted a significant research attention in terms of their application in cooperative relaying systems. Most of existing works…
Ergodic Capacity Analysis of Wireless Powered AF Relaying Systems over - Fading Channels
Galymzhan Nauryzbayev, Khaled M. Rabie, Mohamed Abdallah +1
In this paper, we consider a two-hop amplify-and-forward (AF) relaying system, where the relay node is energy-constrained and harvests energy from the source node. In the literatur…
On the Capacity of Wireless Powered Cognitive Relay Network with Interference Alignment
Sultangali Arzykulov, Galymzhan Nauryzbayev, Theodoros A. Tsiftsis +1
In this paper, a two-hop decode-and-forward cognitive radio system with deployed interference alignment is considered. The relay node is energy-constrained and scavenges the energy…
Error Performance of Wireless Powered Cognitive Relay Networks with Interference Alignment
Sultangali Arzykulov, Galymzhan Nauryzbayev, Theodoros A. Tsiftsis +1
This paper studies a two-hop decode-and-forward underlay cognitive radio system with interference alignment technique. An energy-constrained relay node harvests the energy from the…
On the Feasibility of Interference Alignment in Compounded MIMO Broadcast Channels with Antenna Correlation and Mixed User Classes
Galymzhan Nauryzbayev, Emad Alsusa, Mohamed Abdallah
This paper presents a generalized closed-form beamforming technique that can achieve the maximum degrees of freedom in compounded multiple-input multiple-output (MIMO) broadcast ch…
A Stochastic Sizing Approach for Sharing-based Energy Storage Applications
Islam Safak Bayram, Mohamed Abdallah, Ali Tajer +1
In order to foster renewable energy integration, improve power quality and reliability, and reduce hydrocarbon emissions, there is a strong need to deploy energy storage systems (E…
Capacity Planning Frameworks for Electric Vehicle Charging Stations with Multi-Class Customers
Islam Safak Bayram, Ali Tajer, Mohamed Abdallah +1
In order to foster electric vehicle (EV) adoption, there is a strong need for designing and developing charging stations that can accommodate different customer classes, distinguis…
A Survey on Energy Trading in Smart Grid
I. Safak Bayram, Muhammad Z. Shakir, Mohamed Abdallah +1
As the distributed energy generation and storage technologies are becoming economically viable, energy trading is gradually becoming a profit making option for end-users. This tren…
Random Subcarrier Allocation in OFDM-Based Cognitive Radio Networks
Sabit Ekin, Mohamed M. Abdallah, Khalid A. Qaraqe +1
This paper investigates the performance of an orthogonal frequency-division multiplexing (OFDM)-based cognitive radio (CR) spectrum sharing communication system that assumes random…