We consider a robust beamforming problem where large amount of downlink ...
Cell-free massive multiple-input-multiple-output (CF-mMIMO) is a
next-ge...
We consider massive multiple-input multiple-output (MIMO) systems in the...
In this work, we focus on the communication aspect of decentralized lear...
In this work, we consider a Federated Edge Learning (FEEL) system where
...
Antenna arrays can be either reciprocity calibrated (R-calibrated), whic...
Wireless communication technology has progressed dramatically over the p...
Distributed tensor decomposition (DTD) is a fundamental data-analytics
t...
We consider distributed average consensus in a wireless network with par...
The number of wireless devices is drastically increasing, resulting in m...
Federated Learning (FL) is a collaborative machine learning (ML) framewo...
Many real-world scenarios for massive machine-type communication involve...
Facing the upcoming era of Internet-of-Things and connected intelligence...
In this paper, we consider privacy aspects of wireless federated learnin...
RadioWeaves network operates a large number of distributed antennas usin...
We develop a new algorithm for activity detection for grant-free multipl...
RadioWeaves, in which distributed antennas with integrated radio and com...
The successful emergence of deep learning (DL) in wireless system
applic...
This letter considers the development of transmission strategies for the...
Reciprocity-based time-division duplex (TDD) Massive MIMO (multiple-inpu...
We provide the optimal receive combining strategy for federated learning...
This paper compares the sum rates and rate regions achieved by power-dom...
Future cellular networks are expected to support new communication parad...
We study joint unicast and multigroup multicast transmission in single-c...
Future wireless networks require the integration of machine learning wit...
In a distributed multi-antenna system, multiple geographically separated...
This paper presents a novel strategy to decentralize the soft detection
...
Future wireless networks need to support massive machine type communicat...
With the advances in virtual and augmented reality, gaming applications,...
A fundamental algorithm for data analytics at the edge of wireless netwo...
Deep learning (DL) architectures have been successfully used in many
app...
We study downlink (DL) channel estimation in a multi-cell Massive
multip...
Wireless-based activity sensing has gained significant attention due to ...
With its privacy preservation and communication efficiency, federated
le...
Federated Learning (FL) is a newly emerged decentralized machine learnin...
Massive access is one of the main use cases of beyond 5G (B5G) wireless
...
This paper studies the transmit power optimization in multi-cell massive...
This paper studies the transmit power optimization in a multi-cell massi...
We study downlink channel estimation in a multi-cell Massive multiple-in...
In this letter, we consider the uplink of a cell-free Massive multiple-i...
In this work, we consider the uplink of a scalable cell-free massive MIM...
Reconfigurable Intelligent Surface (RIS) is a promising solution to
reco...
Classification between different activities in an indoor environment usi...
Deep learning (DL) is becoming popular as a new tool for many applicatio...
In cell-free massive multiple-input multiple-output (MIMO) the fluctuati...
In this paper, we take a critical and fresh look at the downlink
multi-a...
Average consensus algorithms have wide applications in distributed compu...
Cell-free massive multiple-input-multiple-output (mMIMO) is an emerging
...
In this paper, we investigate optimal downlink power allocation in massi...
Employing massively distributed antennas brings radio access points (RAP...