Communication and computation efficiency in federated learning: A survey
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 …
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 …
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
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 …
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
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 …
millimeter wave (mmWave) systems, where an IRS is deployed to assist the data …
Channel estimation with reconfigurable intelligent surfaces—A general framework
Optimally extracting the advantages available from reconfigurable intelligent surfaces (RISs)
in wireless communications systems requires estimation of the channels to and from the RIS …
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
This paper considers massive access in massive multiple-input multiple-output (MIMO)
systems and proposes an adaptive active user detection and channel estimation scheme …
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 …
problems. We consider the application of deep learning to the sparse linear inverse …
Channel estimation in broadband millimeter wave MIMO systems with few-bit ADCs
We develop a broadband channel estimation algorithm for millimeter wave (mmWave)
multiple input multiple output (MIMO) systems with few-bit analog-to-digital converters …
multiple input multiple output (MIMO) systems with few-bit analog-to-digital converters …
Optimal errors and phase transitions in high-dimensional generalized linear models
Generalized linear models (GLMs) are used in high-dimensional machine learning,
statistics, communications, and signal processing. In this paper we analyze GLMs when the …
statistics, communications, and signal processing. In this paper we analyze GLMs when the …