activity
20102023
most citedEvolution of NOMA Toward Next Generation Multiple Access (NGMA) for 6G

600 citations · 3.6k across the 121 of their papers we have counts for

collaborators

130 papers

cs.IT2023

Meta Distribution of Partial-NOMA

Konpal Shaukat Ali, Arafat Al-Dweik, Ekram Hossain +1

This work studies the meta distribution (MD) in a two-user partial non-orthogonal multiple access (pNOMA) network. Compared to NOMA where users fully share a resource-element, pNOM…

eess.SP2023

Channel Estimation in RIS-Enabled mmWave Wireless Systems: A Variational Inference Approach

Firas Fredj, Amal Feriani, Amine Mezghani +1

Channel estimation in reconfigurable intelligent surfaces (RIS)-aided systems is crucial for optimal configuration of the RIS and various downstream tasks such as user localization…

cs.IT2023

From Multilayer Perceptron to GPT: A Reflection on Deep Learning Research for Wireless Physical Layer

Mohamed Akrout, Amine Mezghani, Ekram Hossain +2

Most research studies on deep learning (DL) applied to the physical layer of wireless communication do not put forward the critical role of the accuracy-generalization trade-off in…

cs.AI2023

Multi-agent Attention Actor-Critic Algorithm for Load Balancing in Cellular Networks

Jikun Kang, Di Wu, Ju Wang +3

In cellular networks, User Equipment (UE) handoff from one Base Station (BS) to another, giving rise to the load balancing problem among the BSs. To address this problem, BSs can w…

cs.LG2023★ 1 cited

Domain Generalization in Machine Learning Models for Wireless Communications: Concepts, State-of-the-Art, and Open Issues

Mohamed Akrout, Amal Feriani, Faouzi Bellili +2

Data-driven machine learning (ML) is promoted as one potential technology to be used in next-generations wireless systems. This led to a large body of research work that applies ML…

cs.LG2023★ 19 cited

Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey

Yulong Wang, Tong Sun, Shenghong Li +4

Adversarial attacks and defenses in machine learning and deep neural network have been gaining significant attention due to the rapidly growing applications of deep learning in the…