70 citations · 169 across the 37 of their papers we have counts for
39 papers
Finite-SNR Closed Form for the Square Marčenko-Pastur MIMO Capacity
Mohamed Akrout, Robert W. Heath
For the canonical independent and identically distributed (IID) single-user multiple-input multiple-output (MIMO) channel with full channel state information at the transmitter (CS…
Enforcing LLM Safety through DMD-based Classification of Prompt-Response Embedding Dynamics
Mohamed Akrout, Olivera Kotevska, Dan Wilson
Large Language Models (LLMs) are increasingly deployed in high-stakes applications, yet their tendency to generate toxic, harmful, or policy-violating content poses significant ris…
Optimality of Bang-Bang Switching for Breaking the Chu Limit via Time-Modulated Matching
Mohamed Akrout, Miguel Rodrigo Castellanos
This paper shows that surpassing the Chu limit on -factors via time-modulated matching requires non-smooth switching strategies. We derive a nonlinear differential condition to…
Guarantees on Dynamical System Distinguishability for LLM Token Generation
Mohamed Akrout, Dan Wilson
Recent work has shown that classifying large language models (LLMs)' responses can be distinguished by modeling token embeddings as trajectories of a black-box dynamical system (DS…
Time-varying Wireless Channel Tracking with Online Parameter Learning via the Birth-Death-Drift Model
Tiancheng Gao, Mohamed Akrout, Faouzi Bellili +1
Accurate massive MIMO channel state information (CSI) acquisition with low pilot overhead is critical in dynamic propagation environments. Exploiting temporal correlation is key to…
Low-Cost Black-Box Detection of LLM Hallucinations via Dynamical System Prediction
Dan Wilson, Mohamed Akrout
Large Language Models (LLMs) frequently generate plausible but non-factual content, a phenomenon known as hallucination. While existing detection methods typically rely on computat…
Signal Processing Foundations of Reconfigurable Antennas in the Tri-Hybrid MIMO Architecture
Nitish Vikas Deshpande, Joseph Carlson, Siyun Yang +6
To enable larger apertures in multipleinput multipleoutput MIMO systems the trihybrid MIMO architecture offers a promising lowcost and lowpower solution by introducing reconfigurab…
Power Amplifier-aware Power Allocation for Noise-limited and Distortion-limited Regimes
Achref Tellili, Nathaniel Paul Epperson, Mohamed Akrout
The conventional power allocation strategy via water-filling relies on the premise that the power amplifier (PA) operates sufficiently below saturation such that a linear RF chain…
Uncertainty Quantification in Data-Driven Dynamical Models via Inverse Problem Solving
Mohamed Akrout, Dan Wilson
Data-driven model identification strategies can be used to obtain phenomenological models that capture the temporal evolution of observable data. While it is usually straightforwar…
Guided Wireless Technology for Near-Field Communication
Mohamed Akrout, Amine Mezghani, Faouzi Bellili +1
Guided wireless technology is an innovative approach that combines the strengths of guided waves and wireless communication. In traditional wireless systems, signals propagate thro…
Information Rates of Approximate Message Passing for Bandlimited Direct-Detection Channels
Daniel Plabst, Mohamed Akrout, Tobias Prinz +2
The capacity of bandlimited direct-detection channels is challenging to compute or approach due to the receiver non-linearity. A generalized vector approximate message passing (GVA…
The Tri-Hybrid MIMO Architecture
Robert W. Heath, Joseph Carlson, Nitish Vikas Deshpande +3
We present an evolution of multiple-input multiple-output (MIMO) wireless communications known as the tri-hybrid MIMO architecture. In this framework, the traditional operations of…
Unlabeled Compressed Sensing from Multiple Measurement Vectors
Mohamed Akrout, Amine Mezghani, Faouzi Bellili
This paper introduces an algorithmic solution to a broader class of unlabeled sensing problems with multiple measurement vectors (MMV). The goal is to recover an unknown structured…
Next-slot OFDM-CSI Prediction: Multi-head Self-attention or State Space Model?
Mohamed Akrout, Faouzi Bellili, Amine Mezghani +1
The ongoing fifth-generation (5G) standardization is exploring the use of deep learning (DL) methods to enhance the new radio (NR) interface. Both in academia and industry, researc…
Vector Approximate Message Passing With Arbitrary I.I.D. Noise Priors
Mohamed Akrout, Tiancheng Gao, Faouzi Bellili +1
Approximate message passing (AMP) algorithms are devised under the Gaussianity assumption of the measurement noise vector. In this work, we relax this assumption within the vector…
Representations Matter: Embedding Modes of Large Language Models using Dynamic Mode Decomposition
Mohamed Akrout
Existing large language models (LLMs) are known for generating "hallucinated" content, namely a fabricated text of plausibly looking, yet unfounded, facts. To identify when these h…
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…
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…
Physically Consistent Models for Intelligent Reflective Surface-assisted Communications under Mutual Coupling and Element Size Constraint
Mohamed Akrout, Faouzi Bellili, Amine Mezghani +1
We investigate the benefits of mutual coupling effects between the passive elements of intelligent reconfigurable surfaces (IRSs) on maximizing the achievable rate of downlink Inte…
Diffusion-based Data Augmentation for Skin Disease Classification: Impact Across Original Medical Datasets to Fully Synthetic Images
Mohamed Akrout, Bálint Gyepesi, Péter Holló +9
Despite continued advancement in recent years, deep neural networks still rely on large amounts of training data to avoid overfitting. However, labeled training data for real-world…
Continual Learning-Based MIMO Channel Estimation: A Benchmarking Study
Mohamed Akrout, Amal Feriani, Faouzi Bellili +2
With the proliferation of deep learning techniques for wireless communication, several works have adopted learning-based approaches to solve the channel estimation problem. While t…
Super-Wideband Massive MIMO
Mohamed Akrout, Volodymyr Shyianov, Faouzi Bellili +2
We present a unified model for connected antenna arrays with a large number of tightly integrated (i.e., coupled) antennas in a compact space within the context of massive multiple…
Dynamic Noises of Multi-Agent Environments Can Improve Generalization: Agent-based Models meets Reinforcement Learning
Mohamed Akrout, Amal Feriani, Bob McLeod
We study the benefits of reinforcement learning (RL) environments based on agent-based models (ABM). While ABMs are known to offer microfoundational simulations at the cost of comp…
Achievable Rate of Near-Field Communications Based on Physically Consistent Models
Mohamed Akrout, Volodymyr Shyianov, Faouzi Bellili +2
This paper introduces a novel information-theoretic approach for studying the effects of mutual coupling (MC), between the transmit and receive antennas, on the overall performance…