What is he best known for?
The fields of study he is best known for:
- Telecommunications
- Algorithm
- Computer network
David J. Love mainly investigates MIMO, Transmitter, Precoding, Communication channel and Electronic engineering.
His MIMO research is multidisciplinary, incorporating elements of Matrix decomposition and Greedy algorithm.
His studies deal with areas such as Codebook, Antenna array, Control theory, Beamforming and Orthogonal frequency-division multiplexing as well as Transmitter.
The Precoding study combines topics in areas such as Multi-user MIMO, Channel state information and MIMO-OFDM.
His Communication channel study is concerned with the field of Telecommunications as a whole.
His Electronic engineering research also works with subjects such as
- Wireless that intertwine with fields like Computer network,
- Transmission together with Diversity gain.
His most cited work include:
- An overview of limited feedback in wireless communication systems (1353 citations)
- Grassmannian beamforming for multiple-input multiple-output wireless systems (1167 citations)
- Limited feedback unitary precoding for spatial multiplexing systems (840 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Communication channel, MIMO, Electronic engineering, Precoding and Transmitter.
The study incorporates disciplines such as Wireless, Throughput, Codebook and Telecommunications link in addition to Communication channel.
His study in MIMO is interdisciplinary in nature, drawing from both Algorithm and Control theory.
His primary area of study in Electronic engineering is in the field of Beamforming.
His Precoding research is multidisciplinary, incorporating elements of Spatial correlation and Rayleigh fading.
His Transmitter research is multidisciplinary, incorporating perspectives in Antenna array, Fading, Channel code, Covariance matrix and Orthogonal frequency-division multiplexing.
He most often published in these fields:
- Communication channel (45.91%)
- MIMO (43.08%)
- Electronic engineering (39.62%)
What were the highlights of his more recent work (between 2019-2021)?
- Wireless (24.84%)
- Communication channel (45.91%)
- MIMO (43.08%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Wireless, Communication channel, MIMO, Algorithm and Overhead.
His Wireless research includes themes of Decoding methods, Beamforming, Interference and Modulation.
The various areas that David J. Love examines in his Beamforming study include Time diversity and Precoding.
His MIMO research is multidisciplinary, relying on both Wireless network, Channel state information, Distributed computing and Efficient energy use.
His research brings together the fields of Electronic engineering and Channel state information.
His Algorithm research focuses on Noise measurement and how it relates to Computational complexity theory.
Between 2019 and 2021, his most popular works were:
- Prospective Multiple Antenna Technologies for Beyond 5G (116 citations)
- Multi-Stage Hybrid Federated Learning over Large-Scale D2D-Enabled Fog Networks (7 citations)
- Multi-Stage Hybrid Federated Learning over Large-Scale Wireless Fog Networks. (5 citations)
In his most recent research, the most cited papers focused on:
- Telecommunications
- Algorithm
- Computer network
His scientific interests lie mostly in Set, Network topology, Distributed computing, Wireless and Artificial intelligence.
His Network topology study combines topics from a wide range of disciplines, such as Resource allocation, Transmitter power output and Hierarchy.
David J. Love has included themes like Edge computing, Enhanced Data Rates for GSM Evolution, Mobile edge computing, MIMO and Efficient energy use in his Distributed computing study.
His Artificial intelligence study deals with Radio frequency intersecting with Transmission.
His studies in Convolutional neural network integrate themes in fields like Speech recognition, Interference and Modulation.
His Topology study incorporates themes from Structure, Upper and lower bounds, Convergence and Star.
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