Slawomir Stanczak

research

∙ 08/31/2023

Federated Learning in UAV-Enhanced Networks: Joint Coverage and Convergence Time Optimization

Federated learning (FL) involves several devices that collaboratively tr...

0 Mariam Yahya, et al. ∙

research

∙ 08/04/2023

Robust cell-free mmWave/sub-THz access using minimal coordination and coarse synchronization

This study investigates simpler alternatives to coherent joint transmiss...

0 Lorenzo Miretti, et al. ∙

research

∙ 07/10/2023

Coded Distributed Image Classification

In this paper, we present a coded computation (CC) scheme for distribute...

0 Jiepeng Tang, et al. ∙

research

∙ 07/10/2023

Distributed Convex Optimization "Over-the-Air" in Dynamic Environments

This paper presents a decentralized algorithm for solving distributed co...

0 Navneet Agrawal, et al. ∙

research

∙ 05/09/2023

On the Limits of HARQ Prediction for Short Deterministic Codes with Error Detection in Memoryless Channels (Extended Version with Proofs)

We provide a mathematical framework to analyze the limits of Hybrid Auto...

0 Barış Göktepe, et al. ∙

research

∙ 04/27/2023

BiSPARCs for Unsourced Random Access in Massive MIMO

This paper considers the massive MIMO unsourced random access problem in...

0 Patrick Agostini, et al. ∙

research

∙ 04/14/2023

Characterization of the weak Pareto boundary of resource allocation problems in wireless networks – Implications to cell-less systems

We establish necessary and sufficient conditions for a network configura...

0 Renato Luis Garrido Cavalcante, et al. ∙

research

∙ 02/23/2023

The Story of QoS Prediction in Vehicular Communication: From Radio Environment Statistics to Network-Access Throughput Prediction

As cellular networks evolve towards the 6th Generation (6G), Machine Lea...

0 Alexandros Palaios, et al. ∙

research

∙ 01/16/2023

UL-DL duality for cell-free massive MIMO with per-AP power and information constraints

We derive a novel uplink-downlink duality principle for optimal joint pr...

0 Lorenzo Miretti, et al. ∙

research

∙ 12/20/2022

Berlin V2X: A Machine Learning Dataset from Multiple Vehicles and Radio Access Technologies

The evolution of wireless communications into 6G and beyond is expected ...

0 Rodrigo Hernangomez, et al. ∙

research

∙ 12/20/2022

Towards an AI-enabled Connected Industry: AGV Communication and Sensor Measurement Datasets

This paper presents two wireless measurement campaigns in industrial tes...

0 Rodrigo Hernangomez, et al. ∙

research

∙ 11/24/2022

MIMO Systems with Reconfigurable Antennas: Joint Channel Estimation and Mode Selection

Reconfigurable antennas (RAs) are a promising technology to enhance the ...

0 Fariba Armandoust, et al. ∙

research

∙ 10/11/2022

Little or no equalization is needed in energy-efficient sub-THz mobile access

By trading coverage and hardware complexity for abundance of spectrum, s...

0 Lorenzo Miretti, et al. ∙

research

∙ 10/11/2022

Estimation of Doubly-Dispersive Channels in Linearly Precoded Multicarrier Systems Using Smoothness Regularization

In this paper, we propose a novel channel estimation scheme for pulse-sh...

0 Andreas Pfadler, et al. ∙

research

∙ 08/02/2022

Joint optimal beamforming and power control in cell-free massive MIMO

We derive a fast and optimal algorithm for solving practical weighted ma...

0 Lorenzo Miretti, et al. ∙

research

∙ 07/26/2022

Constant Weight Codes with Gabor Dictionaries and Bayesian Decoding for Massive Random Access

This paper considers a general framework for massive random access based...

0 Patrick Agostini, et al. ∙

research

∙ 07/12/2022

Parallel APSM for Fast and Adaptive Digital SIC in Full-Duplex Transceivers with Nonlinearity

This paper presents a kernel-based adaptive filter that is applied for t...

0 M. Hossein Attar, et al. ∙

research

∙ 06/13/2022

GPU-Accelerated Machine Learning in Non-Orthogonal Multiple Access

Non-orthogonal multiple access (NOMA) is an interesting technology that ...

0 Daniel Schäufele, et al. ∙

research

∙ 05/19/2022

A Learning-Based Approach to Approximate Coded Computation

Lagrange coded computation (LCC) is essential to solving problems about ...

0 Navneet Agrawal, et al. ∙

research

∙ 05/16/2022

Semantic Security with Infinite Dimensional Quantum Eavesdropping Channel

We propose a new proof method for direct coding theorems for wiretap cha...

0 Matthias Frey, et al. ∙

research

∙ 05/01/2022

Closed-form max-min power control for some cellular and cell-free massive MIMO networks

Many common instances of power control problems for cellular and cell-fr...

0 Lorenzo Miretti, et al. ∙

research

∙ 04/26/2022

Open or not open: Are conventional radio access networks more secure and trustworthy than Open-RAN?

The Open RAN architecture is a promising and future-oriented architectur...

0 Felix Klement, et al. ∙

research

∙ 03/09/2022

Unsupervised Domain Adaptation across FMCW Radar Configurations Using Margin Disparity Discrepancy

Commercial radar sensing is gaining relevance and machine learning algor...

0 Rodrigo Hernangomez, et al. ∙

research

∙ 03/02/2022

Superiorized Adaptive Projected Subgradient Method with Application to MIMO Detection

In this paper, we show that the adaptive projected subgradient method (A...

0 Jochen Fink, et al. ∙

research

∙ 01/13/2022

Real-Time GPU-Accelerated Machine Learning Based Multiuser Detection for 5G and Beyond

Adaptive partial linear beamforming meets the need of 5G and future 6G a...

4 Matthias Mehlhose, et al. ∙

research

∙ 07/16/2021

Deep Learning Beam Optimization in Millimeter-Wave Communication Systems

We propose a method that combines fixed point algorithms with a neural n...

0 Rafail Ismayilov, et al. ∙

research

∙ 07/16/2021

Deep Learning Based Hybrid Precoding in Dual-Band Communication Systems

We propose a deep learning-based method that uses spatial and temporal i...

0 Rafail Ismayilov, et al. ∙

research

∙ 07/14/2021

Hybrid Model and Data Driven Algorithm for Online Learning of Any-to-Any Path Loss Maps

Learning any-to-any (A2A) path loss maps, where the objective is the rec...

0 M. A. Gutierrez-Estevez, et al. ∙

research

∙ 07/13/2021

Transfer Learning in Multi-Agent Reinforcement Learning with Double Q-Networks for Distributed Resource Sharing in V2X Communication

This paper addresses the problem of decentralized spectrum sharing in ve...

0 Hammad Zafar, et al. ∙

research

∙ 05/05/2021

Leveraging Machine Learning for Industrial Wireless Communications

Two main trends characterize today's communication landscape and are fin...

0 Ilaria Malanchini, et al. ∙

research

∙ 03/21/2021

Robust Cell-Load Learning with a Small Sample Set

Learning of the cell-load in radio access networks (RANs) has to be perf...

0 Daniyal Amir Awan, et al. ∙

research

∙ 03/21/2021

Set-Theoretic Learning for Detection in Cell-Less C-RAN Systems

Cloud-radio access network (C-RAN) can enable cell-less operation by con...

0 Daniyal Amir Awan, et al. ∙

research

∙ 02/23/2021

Multi-Group Multicast Beamforming by Superiorized Projections onto Convex Sets

In this paper, we propose an iterative algorithm to address the nonconve...

0 Jochen Fink, et al. ∙

research

∙ 01/27/2021

Joint Source-Channel Coding for Semantics-Aware Grant-Free Radio Access in IoT Fog Networks

A fog-radio access network (F-RAN) architecture is studied for an Intern...

0 Johannes Dommel, et al. ∙

research

∙ 01/12/2021

Over-The-Air Computation in Correlated Channels

This paper addresses the problem of Over-The-Air (OTA) computation in wi...

0 Matthias Frey, et al. ∙

research

∙ 08/13/2020

Full-Duplex Amplify-and-Forward MIMO Relaying: Impairments Aware Design and Performance Analysis

Full-Duplex (FD) Amplify-and-Forward (AF) Multiple-Input Multiple-Output...

0 Omid Taghizadeh, et al. ∙

research

∙ 07/06/2020

Over-The-Air Computation for Distributed Machine Learning

Motivated by various applications in distributed Machine Learning (ML) i...

0 Matthias Frey, et al. ∙

research

∙ 01/09/2020

Securing Distributed Function Approximation via Coding for Continuous Compound Channels

We revisit the problem of distributed approximation of functions over mu...

0 Matthias Frey, et al. ∙

research

∙ 01/02/2020

Artificial Intelligence Enabled Wireless Networking for 5G and Beyond: Recent Advances and Future Challenges

The fifth generation (5G) wireless communication networks are currently ...

0 Cheng-Xiang Wang, et al. ∙

research

∙ 11/11/2019

Machine Learning-Based Adaptive Receive Filtering: Proof-of-Concept on an SDR Platform

Conventional multiuser detection techniques either require a large numbe...

0 Matthias Mehlhose, et al. ∙

research

∙ 10/25/2019

Joint Source-Channel Coding and Bayesian Message Passing Detection for Grant-Free Radio Access in IoT

Consider an Internet-of-Things (IoT) system that monitors a number of mu...

0 Johannes Dommel, et al. ∙

research

∙ 07/08/2019

Distributed Approximation of Functions over Fast Fading Channels with Applications to Distributed Learning and the Max-Consensus Problem

In this work, we consider the problem of distributed approximation of fu...

0 Igor Bjelaković, et al. ∙

research

∙ 03/23/2019

Connections between spectral properties of asymptotic mappings and solutions to wireless network problems

In this study we establish connections between asymptotic functions and ...

0 Renato Luis Garrido Cavalcante, et al. ∙

research

∙ 03/07/2019

A Scalable Max-Consensus Protocol For Noisy Ultra-Dense Networks

We introduce ScalableMax, a novel communication scheme for achieving max...

0 Navneet Agrawal, et al. ∙

research

∙ 04/23/2018

Error Bounds for FDD Massive MIMO Channel Covariance Conversion with Set-Theoretic Methods

We derive novel bounds for the performance of algorithms that estimate t...

0 Renato Luis Garrido Cavalcante, et al. ∙

research

∙ 04/05/2018

Towards Massive Connectivity Support for Scalable mMTC Communications in 5G networks

The fifth generation of cellular communication systems is foreseen to en...

0 Carsten Bockelmann, et al. ∙

research

∙ 03/15/2018

Spectral radii of asymptotic mappings and the convergence speed of the standard fixed point algorithm

Important problems in wireless networks can often be solved by computing...

0 Renato L. G. Cavalcante, et al. ∙

research

∙ 01/11/2018

Resolvability on Continuous Alphabets

We characterize the resolvability region for a large class of point-to-p...

0 Matthias Frey, et al. ∙

research

∙ 09/04/2017

Optimal deep neural networks for sparse recovery via Laplace techniques

This paper introduces Laplace techniques for designing a neural network,...

0 Steffen Limmer, et al. ∙

research

∙ 08/28/2017

The Convergence of Machine Learning and Communications

The areas of machine learning and communication technology are convergin...

0 Wojciech Samek, et al. ∙

Slawomir Stanczak

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