26 citations · 62 across the 10 of their papers we have counts for
11 papers
Uncertainty-Aware Federated Learning for Joint Communication and Computation in XR Systems
Robert-Jeron Reifert, Hayssam Dahrouj, Alaa Alameer Ahmad +2
The convergence of communication and computation, empowered by artificial intelligence (AI) enhanced capabilities, emerges as a key enabler for realizing the promising functionalit…
Agentic AI-Based Joint Computing and Networking via Mixture of Experts and Large Language Models
Robert-Jeron Reifert, Alaa Alameer Ahmad, Hayssam Dahrouj +1
Future sixth-generation (6G) mobile networks are envisioned to be equipped with a diverse set of powerful, yet highly specialized, optimization experts. Such a promising vision is…
Advancing Agentic Systems: Dynamic Task Decomposition, Tool Integration and Evaluation using Novel Metrics and Dataset
Adrian Garret Gabriel, Alaa Alameer Ahmad, Shankar Kumar Jeyakumar
Advancements in Large Language Models (LLMs) are revolutionizing the development of autonomous agentic systems by enabling dynamic, context-aware task decomposition and automated t…
Robust Communication and Computation using Deep Learning via Joint Uncertainty Injection
Robert-Jeron Reifert, Hayssam Dahrouj, Alaa Alameer Ahmad +2
The convergence of communication and computation, along with the integration of machine learning and artificial intelligence, stand as key empowering pillars for the sixth-generati…
Comeback Kid: Resilience for Mixed-Critical Wireless Network Resource Management
Robert-Jeron Reifert, Stefan Roth, Alaa Alameer Ahmad +1
The future sixth generation (6G) of communication systems is envisioned to provide numerous applications in safety-critical contexts, e.g., driverless traffic, modular industry, an…
Energy Efficiency in Rate-Splitting Multiple Access with Mixed Criticality
Robert-Jeron Reifert, Stefan Roth, Alaa Alameer Ahmad +1
Future sixth generation (6G) wireless communication networks face the need to similarly meet unprecedented quality of service (QoS) demands while also providing a larger energy eff…
Synergistic Benefits in IRS- and RS-enabled C-RAN with Energy-Efficient Clustering
Kevin Weinberger, Alaa Alameer Ahmad, Aydin Sezgin +1
The potential of intelligent reflecting surfaces (IRSs) is investigated as a promising technique for enhancing the energy efficiency of wireless networks. Specifically, the IRS ena…
Distributed Resource Management in Downlink Cache-Enabled Multi-Cloud Radio Access Networks
Robert-Jeron Reifert, Alaa Alameer Ahmad, Hayssam Dahrouj +4
In light of the premises of beyond fifth generation (B5G) networks, the need for better exploiting the capabilities of cloud-enabled networks arises, so as to cope with the large-s…
On Synergistic Benefits of Rate Splitting in IRS-assisted Cloud Radio Access Networks
Kevin Weinberger, Alaa Alameer Ahmad, Aydin Sezgin
The concept of intelligent reflecting surfaces (IRSs) is considered as a promising technology for increasing the efficiency of mobile wireless networks. This is achieved by employi…
Rate Splitting Multiple Access in C-RAN: A Scalable and Robust Design
Alaa Alameer Ahmad, Yijie Mao, Aydin Sezgin +1
Cloud radio access networks (C-RAN) enable a network platform for beyond the fifth generation of communication networks (B5G), which incorporates the advances in cloud computing te…
A Reinforcement Learning based approach for Multi-target Detection in Massive MIMO radar
Aya Mostafa Ahmed, Alaa Alameer Ahmad, Stefano Fortunati +3
This paper considers the problem of multi-target detection for massive multiple input multiple output (MMIMO) cognitive radar (CR). The concept of CR is based on the perception-act…