Two-timescale weighted sum-rate maximization for large cellular and cell-free massive MIMO
Discover a groundbreaking two-timescale method for optimizing the weighted sum-rate in future multi-antenna wireless systems. Our innovative approach overcomes the severe scalability issues of traditional methods, namely the extreme computational...
User-Centric Monostatic Sensing Aided by Reconfigurable Intelligent Surfaces
We propose that deploying Reflecting Intelligent Surfaces (RIS) as auxiliary sensors can either enable (in cases of blockage) or assist UEs in improving sensing performance. This can be achieved by deploying larger surfaces, offering superior...
Load Balancing in O-RAN
Efficiently managing network load has long been a challenge in wireless networks, and open radio access networks (O-RAN) can offer a potential solution through open interfaces and optimization capabilities. This paper focuses on addressing the...
First Polymer-based Passive Optical Waveguide for the Visible Range from 633 nm down to 488 nm
We investigated the transmission properties of optical waveguide based on fluorinated acrylate polymer and Ormocer® based polymer in the visible range (VIS). Laser transmission-induced transparency (LTIT) and fluorescence were observed in the...
Explainable Concept Mappings of MRI: Revealing the Mechanisms Underlying Deep Learning-Based Brain Disease Classification
While recent studies show high accuracy in the classification of Alzheimer's disease using deep neural networks, the underlying learned concepts have not been investigated. We separated Alzheimer's patients (n=117) from normal controls (n=219) by...
PURE: Turning Polysemantic Neurons Into Pure Features by Identifying Relevant Circuits
Neurons in deep neural networks can act polysemantically, meaning that they encode for multiple (unrelated) features. As such, understanding the inner workings of machine learning models becomes more difficult. We present PURE to turn...
Model guidance via explanations turns image classifiers into segmentation models
Heatmaps generated on inputs of image classification networks via explainable AI methods have been observed to resemble segmentations of input images in many cases. We apply the "Right for the Right Reason" paradigm of imposing additional losses...
Neuromorphic Wireless Device-Edge Co-Inference via the Directed Information Bottleneck
We consider neuromorphic wireless device-edge co-inference for edge intelligence applications. The directed information bottleneck principle is applied to extract the most relevant information for the task. The model demonstrates superior...
Distributed Convex Optimization “Over-the-Air” in Dynamic Environments
The paper proposes a class of distributed algorithms where the consensus step is implemented in a scalable and truly decentralized fashion using a novel communication protocol based on the “over-the-air” function computation (OTA-C)...
Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations
With PCX, we introduce a method that summarizes similar single explanations via prototypical ones. As such, we can understand the whole model behavior quickly and in detail. PCX further allows to validate individual predictions by communicating...