122 citations · 148 across the 22 of their papers we have counts for
28 papers
RF Chain Count to Mitigate Beam Split in Wideband Hybrid Arrays: From Far-Field to Near-Field
Ahmed Hussain, Asmaa Abdallah, Asmaa Abdallah Senior Member +4
Deploying large antenna arrays transitions wireless communication into the radiative near-field (NF), where spherical wavefronts enable beamfocusing in the joint angle-distance dom…
WALoMA: A Multitask Wireless Foundation Model via Adaptive Low-Rank Masked Autoencoders
Madi Makin, Asmaa Abdallah, Abdulkadir Celik +1
This paper proposes a multitask wireless foundation model via adaptive low-rank masked autoencoders (WALoMA), a unified multi-task foundation model for sixth-generation (6G) wirele…
Enwar 3.0: An Agentic Multi-Modal LLM Orchestrator for Situation-Aware Beamforming, Blockage Prediction, and Handover Management
Ahmad M. Nazar, Abdulkadir Celik, Asmaa Abdallah +3
Maintaining robust millimeter-wave (mmWave) connectivity in vehicular networks requires real-time adaptation to environmental dynamics, sensor degradation, and link variability. Th…
Boosting Spectral Efficiency via Spatial Path Index Modulation in RIS-Aided mMIMO
Ahmet M. Elbir, Abdulkadir Celik, Asmaa Abdallah +1
Next generation wireless networks focus on improving spectral efficiency (SE) while reducing power consumption and hardware cost. Reconfigurable intelligent surfaces (RISs) offer a…
Array Geometry-Centric Axial Sidelobe Interference Analysis for Near-Field Multi-User MIMO
Ahmed Hussain, Asmaa Abdallah, Abdulkadir Celik +1
With the deployment of large antenna arrays at high-frequency bands, future wireless communication systems are likely to operate in the radiative near-field (NF). Unlike far-field…
End-to-End Deep Learning in Wireless Communication Systems: A Tutorial Review
Abdelrahman Elfiky, Zouheir Rezki, Jorge Cortez +4
The physical layer (PHY) in wireless communication systems has traditionally relied on model-based methods that are often optimized individually as independent blocks to perform ta…
Spatial Degrees of Freedom in Near Field MIMO: Experimental Validation of Beamspace Perspective
Ahmed Hussain, Asmaa Abdallah, Ahmed Nasser +2
Conventional far-field multiple-input multiple-output (MIMO) channels are limited to a single spatial degree of freedom (DoF) under a line-of-sight (LoS) condition. In contrast, th…
Analyzing URA Geometry for Enhanced Near-Field Beamfocusing and Spatial Degrees of Freedom
Ahmed Hussain, Asmaa Abdallah, Abdulkadir Celik +2
With the deployment of large antenna arrays at high-frequency bands, future wireless communication systems are likely to operate in the radiative near-field. Unlike far-field beam…
Sparse Array Design for Near-Field MU-MIMO: Reconfigurable Array Thinning Approach
Ahmed Hussain, Asmaa Abdallah, Abdulkadir Celik +2
Future wireless networks, deploying thousands of antenna elements, may operate in the radiative near-field (NF), enabling spatial multiplexing across both angle and range domains.…
Near Field Tapering with Slepian Window: Balancing the Range Angle Sidelobe Trade off
Ahmed Hussain, Ahmed Sultan, Asmaa Abdallah +2
Near-field beamforming enables target discrimination in both range (axial) and angle (lateral) dimensions. Elevated sidelobes along either dimension, however, increase susceptibili…
Uniform Circular Arrays in Near-Field: Omnidirectional Coverage with Limited Capacity
Ahmed Hussain, Asmaa Abdallah, Abdulkadir Celik +1
Recent studies suggest that uniform circular arrays (UCAs) can extend the angular coverage of the radiative near field region. This work investigates whether such enhanced angular…
Causal Beam Selection for Reliable Initial Access in AI-driven Beam Management
Nasir Khan, Asmaa Abdallah, Abdulkadir Celik +2
Efficient and reliable beam alignment is a critical requirement for mmWave multiple-input multiple-output (MIMO) systems, especially in 6G and beyond, where communication must be f…
Multi-Modal Sensor Fusion for Proactive Blockage Prediction in mmWave Vehicular Networks
Ahmad M. Nazar, Abdulkadir Celik, Mohamed Y. Selim +3
Vehicular communication systems operating in the millimeter wave (mmWave) band are highly susceptible to signal blockage from dynamic obstacles such as vehicles, pedestrians, and i…
Joint Motion, Angle, and Range Estimation in Near-Field under Array Calibration Imperfections
Ahmed Hussain, Asmaa Abdallah, Abdulkadir Celik +1
Ultra-massive multiple-input multiple-output MIMO (UM-MIMO) leverages large antenna arrays at high frequencies, transitioning communication paradigm into the radiative near-field (…
Digital Twin-Assisted Explainable AI for Robust Beam Prediction in mmWave MIMO Systems
Nasir Khan, Asmaa Abdallah, Abdulkadir Celik +2
In line with the AI-native 6G vision, explainability and robustness are crucial for building trust and ensuring reliable performance in millimeter-wave (mmWave) systems. Efficient…
Analyzing URA Geometry for Enhanced Spatial Multiplexing and Extended Near-Field Coverage
Ahmed Hussain, Asmaa Abdallah, Abdulkadir Celik +1
With the deployment of large antenna arrays at high frequency bands, future wireless communication systems are likely to operate in the radiative near-field. Unlike far-field beam…
Near-Field Beam Prediction Using Far-Field Codebooks in Ultra-Massive MIMO Systems
Ahmed Hussain, Asmaa Abdallah, Abdulkadir Celik +1
Ultra-massive multiple-input multiple-output (UM-MIMO) technology is a key enabler for 6G networks, offering exceptional high data rates in millimeter-wave (mmWave) and Terahertz (…
Explainable Autoencoder Design for RSSI-Based Multi-User Beam Probing and Hybrid Precoding
Asmaa Abdallah, Abdulkadir Celik, Ahmed Alkhateeb +1
This paper introduces a novel neural network (NN) structure referred to as an ``Auto-hybrid precoder'' (Auto-HP) and an unsupervised deep learning (DL) approach that jointly design…
Explainable and Robust Millimeter Wave Beam Alignment for AI-Native 6G Networks
Nasir Khan, Asmaa Abdallah, Abdulkadir Celik +2
Integrated artificial intelligence (AI) and communication has been recognized as a key pillar of 6G and beyond networks. In line with AI-native 6G vision, explainability and robust…
Explainable AI-aided Feature Selection and Model Reduction for DRL-based V2X Resource Allocation
Nasir Khan, Asmaa Abdallah, Abdulkadir Celik +2
Artificial intelligence (AI) is expected to significantly enhance radio resource management (RRM) in sixth-generation (6G) networks. However, the lack of explainability in complex…
Near-Field ISAC: Synergy of Dual-Purpose Codebooks and Space-Time Adaptive Processing
Ahmed Hussain, Asmaa Abdallah, Abdulkadir Celik +1
Integrated sensing and communication (ISAC) has emerged as a transformative paradigm, enabling situationally aware and perceptive next-generation wireless networks through the co-d…
NetOrchLLM: Mastering Wireless Network Orchestration with Large Language Models
Asmaa Abdallah, Abdullatif Albaseer, Abdulkadir Celik +2
The transition to 6G networks promises unprecedented advancements in wireless communication, with increased data rates, ultra-low latency, and enhanced capacity. However, the compl…
Hybrid Beamforming for Integrated Sensing and Communications With Low Resolution DACs
Ahmet M. Elbir, Abdulkadir Celik, Ahmed M. Eltawil
Integrated sensing and communications (ISAC) has emerged as a means to efficiently utilize spectrum and thereby save cost and power. At the higher end of the spectrum, ISAC systems…
ENWAR: A RAG-empowered Multi-Modal LLM Framework for Wireless Environment Perception
Ahmad M. Nazar, Abdulkadir Celik, Mohamed Y. Selim +3
Large language models (LLMs) hold significant promise in advancing network management and orchestration in 6G and beyond networks. However, existing LLMs are limited in domain-spec…