What is he best known for?
The fields of study he is best known for:
- Statistics
- Telecommunications
- Computer network
His scientific interests lie mostly in Communication channel, Beamforming, MIMO, Mathematical optimization and Telecommunications link.
His Communication channel research is multidisciplinary, relying on both Transmission and Electronic engineering.
His biological study deals with issues like Transmitter, which deal with fields such as Rayleigh scattering.
His studies in Beamforming integrate themes in fields like Wireless, Backhaul, Throughput, Power control and Computer network.
His work carried out in the field of MIMO brings together such families of science as Channel state information, Channel capacity and Signal processing.
The various areas that Mats Bengtsson examines in his Mathematical optimization study include Estimation theory and Robustness.
His most cited work include:
- Convex Optimization-Based Beamforming (449 citations)
- Ketamine reduces muscle pain, temporal summation, and referred pain in fibromyalgia patients (331 citations)
- Hyperexcitability in fibromyalgia (283 citations)
What are the main themes of his work throughout his whole career to date?
Mats Bengtsson focuses on Communication channel, Electronic engineering, MIMO, Mathematical optimization and Precoding.
Mats Bengtsson has included themes like Algorithm, Throughput and Signal processing in his Communication channel study.
Specifically, his work in Electronic engineering is concerned with the study of Beamforming.
His MIMO course of study focuses on Covariance matrix and Covariance.
His work on Optimization problem, Iterative method and Nash equilibrium as part of his general Mathematical optimization study is frequently connected to Convex optimization, thereby bridging the divide between different branches of science.
His research investigates the connection between Precoding and topics such as Channel state information that intersect with issues in Overhead.
He most often published in these fields:
- Communication channel (27.80%)
- Electronic engineering (25.99%)
- MIMO (25.99%)
What were the highlights of his more recent work (between 2015-2021)?
- Communication channel (27.80%)
- Precoding (19.49%)
- Electronic engineering (25.99%)
In recent papers he was focusing on the following fields of study:
His main research concerns Communication channel, Precoding, Electronic engineering, Algorithm and Signal processing.
His research integrates issues of Upper and lower bounds, Transmission and Throughput in his study of Communication channel.
His Precoding research is multidisciplinary, incorporating perspectives in Channel state information, Wideband and Telecommunications link.
Mats Bengtsson is studying Beamforming, which is a component of Electronic engineering.
His work in the fields of Computational complexity theory overlaps with other areas such as Clipping.
His studies deal with areas such as Cognitive radio and Robustness as well as Signal processing.
Between 2015 and 2021, his most popular works were:
- IgG Endopeptidase in Highly Sensitized Patients Undergoing Transplantation. (121 citations)
- Subspace Estimation and Decomposition for Large Millimeter-Wave MIMO Systems (107 citations)
- Optimum and Suboptimum Transmit Beamforming (60 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Telecommunications
- Computer network
His primary areas of investigation include Communication channel, MIMO, Electronic engineering, Precoding and Algorithm.
His work deals with themes such as Upper and lower bounds and Transmission, which intersect with Communication channel.
His study in Electronic engineering is interdisciplinary in nature, drawing from both Transmitter, Telecommunications link and Signal processing.
The concepts of his Precoding study are interwoven with issues in Subspace topology, Channel state information, Cluster analysis and Control theory.
The study incorporates disciplines such as Distributed computing, Robustness and Base station in addition to Channel state information.
His Algorithm research is multidisciplinary, incorporating elements of Eigenvalues and eigenvectors, Mathematical optimization, Single point of failure and Fading.
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