Fog of everything: Energy-efficient networked computing architectures, research challenges, and a case study

E Baccarelli, PGV Naranjo, M Scarpiniti… - IEEE …, 2017 - ieeexplore.ieee.org
Fog computing (FC) and Internet of Everything (IoE) are two emerging technological
paradigms that, to date, have been considered standing-alone. However, because of their …

Unbiased finite impluse response filtering: An iterative alternative to Kalman filtering ignoring noise and initial conditions

YS Shmaliy, S Zhao, CK Ahn - IEEE Control Systems Magazine, 2017 - ieeexplore.ieee.org
If a system and its observation are both represented in state space with linear equations, the
system noise and the measurement noise are white, Gaussian, and mutually uncorrelated …

Channel estimation in narrowband wireless communication systems

H Arslan, GE Bottomley - Wireless Communications and …, 2001 - Wiley Online Library
Channel estimation is an integral part of standard adaptive receiver designs used in
narrowband, digital wireless communication systems. In this tutorial paper, commonly used …

An iterative Kalman-like algorithm ignoring noise and initial conditions

YS Shmaliy - IEEE Transactions on Signal Processing, 2011 - ieeexplore.ieee.org
We address a p-shift finite impulse response (FIR) unbiased estimator (UE) for linear
discrete time-varying filtering (p= 0), p-step prediction (p>; 0), and p-lag smoothing (p<; 0) in …

Design and energy-efficient resource management of virtualized networked Fog architectures for the real-time support of IoT applications

PG Vinueza Naranjo, E Baccarelli… - The journal of …, 2018 - Springer
With the incoming 5G access networks, it is forecasted that Fog computing (FC) and Internet
of Things (IoT) will converge onto the Fog-of-IoT paradigm. Since the FC paradigm spreads …

Learning-in-the-fog (LiFo): Deep learning meets fog computing for the minimum-energy distributed early-exit of inference in delay-critical IoT realms

E Baccarelli, M Scarpiniti, A Momenzadeh… - IEEE …, 2021 - ieeexplore.ieee.org
Fog Computing (FC) and Conditional Deep Neural Networks (CDDNs) with early exits are
two emerging paradigms which, up to now, are evolving in a standing-alone fashion …

Soft input channel estimation for turbo equalization

S Song, AC Singer, KM Sung - IEEE Transactions on Signal …, 2004 - ieeexplore.ieee.org
In this paper, we consider soft decision directed channel estimation for turbo equalization.
To take advantage of soft information provided by the decoder, a minimum mean square …

An accuracy vs. complexity comparison of deep learning architectures for the detection of COVID-19 disease

S Sarv Ahrabi, M Scarpiniti, E Baccarelli… - Computation, 2021 - mdpi.com
In parallel with the vast medical research on clinical treatment of COVID-19, an important
action to have the disease completely under control is to carefully monitor the patients. What …

Review of channel estimation for wireless communication systems

OO Oyerinde, SH Mneney - IETE Technical review, 2012 - Taylor & Francis
Wireless communication systems have evolved over the ages. However, there are some
undesirable effects of a wireless communication channel on the signals transmitted through …

EcoMobiFog–design and dynamic optimization of a 5G mobile-fog-cloud multi-tier ecosystem for the real-time distributed execution of stream applications

E Baccarelli, M Scarpiniti, A Momenzadeh - IEEE Access, 2019 - ieeexplore.ieee.org
The emerging 5G paradigm will enable multi-radio smartphones to run high-rate stream
applications. However, since current smartphones remain resource and battery-limited, the …