Federated learning (FL) involves several devices that collaboratively tr...
This study investigates simpler alternatives to coherent joint transmiss...
In this paper, we present a coded computation (CC) scheme for distribute...
This paper presents a decentralized algorithm for solving distributed co...
We provide a mathematical framework to analyze the limits of Hybrid Auto...
This paper considers the massive MIMO unsourced random access problem in...
We establish necessary and sufficient conditions for a network configura...
As cellular networks evolve towards the 6th Generation (6G), Machine Lea...
We derive a novel uplink-downlink duality principle for optimal joint
pr...
The evolution of wireless communications into 6G and beyond is expected ...
This paper presents two wireless measurement campaigns in industrial
tes...
Reconfigurable antennas (RAs) are a promising technology to enhance the
...
By trading coverage and hardware complexity for abundance of spectrum,
s...
In this paper, we propose a novel channel estimation scheme for pulse-sh...
We derive a fast and optimal algorithm for solving practical weighted ma...
This paper considers a general framework for massive random access based...
This paper presents a kernel-based adaptive filter that is applied for t...
Non-orthogonal multiple access (NOMA) is an interesting technology that
...
Lagrange coded computation (LCC) is essential to solving problems about
...
We propose a new proof method for direct coding theorems for wiretap cha...
Many common instances of power control problems for cellular and cell-fr...
The Open RAN architecture is a promising and future-oriented architectur...
Commercial radar sensing is gaining relevance and machine learning algor...
In this paper, we show that the adaptive projected subgradient method (A...
Adaptive partial linear beamforming meets the need of 5G and future 6G
a...
We propose a method that combines fixed point algorithms with a neural
n...
We propose a deep learning-based method that uses spatial and temporal
i...
Learning any-to-any (A2A) path loss maps, where the objective is the
rec...
This paper addresses the problem of decentralized spectrum sharing in
ve...
Two main trends characterize today's communication landscape and are fin...
Learning of the cell-load in radio access networks (RANs) has to be perf...
Cloud-radio access network (C-RAN) can enable cell-less operation by
con...
In this paper, we propose an iterative algorithm to address the nonconve...
A fog-radio access network (F-RAN) architecture is studied for an
Intern...
This paper addresses the problem of Over-The-Air (OTA) computation in
wi...
Full-Duplex (FD) Amplify-and-Forward (AF) Multiple-Input Multiple-Output...
Motivated by various applications in distributed Machine Learning (ML) i...
We revisit the problem of distributed approximation of functions over
mu...
The fifth generation (5G) wireless communication networks are currently ...
Conventional multiuser detection techniques either require a large numbe...
Consider an Internet-of-Things (IoT) system that monitors a number of
mu...
In this work, we consider the problem of distributed approximation of
fu...
In this study we establish connections between asymptotic functions and
...
We introduce ScalableMax, a novel communication scheme for achieving
max...
We derive novel bounds for the performance of algorithms that estimate t...
The fifth generation of cellular communication systems is foreseen to en...
Important problems in wireless networks can often be solved by computing...
We characterize the resolvability region for a large class of point-to-p...
This paper introduces Laplace techniques for designing a neural network,...
The areas of machine learning and communication technology are convergin...