Communication and computation efficiency in federated learning: A survey

ORA Almanifi, CO Chow, ML Tham, JH Chuah… - Internet of Things, 2023 - Elsevier
Federated Learning is a much-needed technology in this golden era of big data and Artificial
Intelligence, due to its vital role in preserving data privacy, and eliminating the need to …

Channel estimation techniques for millimeter-wave communication systems: Achievements and challenges

K Hassan, M Masarra, M Zwingelstein… - IEEE Open Journal of …, 2020 - ieeexplore.ieee.org
The fifth-generation (5G) of cellular networks and beyond requires massive connectivity,
high data rates, and low latency. Millimeter-wave (mmWave) communications is a key 5G …

Sparse synthetic aperture radar imaging from compressed sensing and machine learning: Theories, applications, and trends

G Xu, B Zhang, H Yu, J Chen, M Xing… - IEEE Geoscience and …, 2022 - ieeexplore.ieee.org
Synthetic aperture radar (SAR) image formation can be treated as a class of ill-posed linear
inverse problems, and the resolution is limited by the data bandwidth for traditional imaging …

Compressed channel estimation for intelligent reflecting surface-assisted millimeter wave systems

P Wang, J Fang, H Duan, H Li - IEEE signal processing letters, 2020 - ieeexplore.ieee.org
In this letter, we consider channel estimation for intelligent reflecting surface (IRS)-assisted
millimeter wave (mmWave) systems, where an IRS is deployed to assist the data …

Channel estimation with reconfigurable intelligent surfaces—A general framework

AL Swindlehurst, G Zhou, R Liu, C Pan… - Proceedings of the …, 2022 - ieeexplore.ieee.org
Optimally extracting the advantages available from reconfigurable intelligent surfaces (RISs)
in wireless communications systems requires estimation of the channels to and from the RIS …

Compressive sensing-based adaptive active user detection and channel estimation: Massive access meets massive MIMO

M Ke, Z Gao, Y Wu, X Gao… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
This paper considers massive access in massive multiple-input multiple-output (MIMO)
systems and proposes an adaptive active user detection and channel estimation scheme …

AMP-inspired deep networks for sparse linear inverse problems

M Borgerding, P Schniter… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Deep learning has gained great popularity due to its widespread success on many inference
problems. We consider the application of deep learning to the sparse linear inverse …

Orthogonal amp

J Ma, L Ping - IEEE Access, 2017 - ieeexplore.ieee.org
Approximate message passing (AMP) is a low-cost iterative signal recovery algorithm for
linear system models. When the system transform matrix has independent identically …

Channel estimation in broadband millimeter wave MIMO systems with few-bit ADCs

J Mo, P Schniter, RW Heath - IEEE Transactions on Signal …, 2017 - ieeexplore.ieee.org
We develop a broadband channel estimation algorithm for millimeter wave (mmWave)
multiple input multiple output (MIMO) systems with few-bit analog-to-digital converters …

Optimal errors and phase transitions in high-dimensional generalized linear models

J Barbier, F Krzakala, N Macris… - Proceedings of the …, 2019 - National Acad Sciences
Generalized linear models (GLMs) are used in high-dimensional machine learning,
statistics, communications, and signal processing. In this paper we analyze GLMs when the …