What is he best known for?
The fields of study he is best known for:
- Computer network
- Telecommunications
- Statistics
Computer network, Base station, Handover, Wireless network and Node are his primary areas of study.
His Computer network research integrates issues from Wireless, Relation and Signal quality.
His work carried out in the field of Relation brings together such families of science as Sensor fusion, Multipath propagation, Telecommunications service and Synchronization.
His research integrates issues of Terminal, Electronic engineering and Telecommunications link in his study of Base station.
His research in Handover intersects with topics in Automation, Real-time computing and Mobile telephony.
His study in Wireless network is interdisciplinary in nature, drawing from both Key and Power control.
His most cited work include:
- Particle filters for positioning, navigation, and tracking (1380 citations)
- Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements (819 citations)
- Network architecture, methods, and devices for a wireless communications network (374 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Computer network, Base station, Wireless, Node and Real-time computing.
His Computer network research is multidisciplinary, incorporating perspectives in Wireless network and Radio networks.
His Base station study combines topics in areas such as Terminal, Electrical engineering and Cellular network.
His Wireless research includes elements of Transmission and Signal.
The concepts of his Node study are interwoven with issues in Telecommunications network, Identifier and UMTS Terrestrial Radio Access Network, Radio access network.
His research investigates the link between Telecommunications link and topics such as Electronic engineering that cross with problems in Power control.
He most often published in these fields:
- Computer network (55.38%)
- Base station (26.51%)
- Wireless (22.31%)
What were the highlights of his more recent work (between 2015-2021)?
- Computer network (55.38%)
- Wireless (22.31%)
- Real-time computing (17.06%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Computer network, Wireless, Real-time computing, Node and User equipment.
Fredrik Gunnarsson interconnects Broadcast engineering, Relay and Wireless network in the investigation of issues within Computer network.
His biological study spans a wide range of topics, including Transmission, Signal and Random access.
The various areas that he examines in his Real-time computing study include Multilateration, OTDOA, Cellular network and Base station.
His studies deal with areas such as Handover and Time of arrival as well as Base station.
His studies in Node integrate themes in fields like Telecommunications network and Radio networks.
Between 2015 and 2021, his most popular works were:
- Network architecture, methods, and devices for a wireless communications network (374 citations)
- LTE release 14 outlook (99 citations)
- Positioning for the Internet of Things: A 3GPP Perspective (63 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Telecommunications
- Statistics
His scientific interests lie mostly in Computer network, Wireless, OTDOA, RSS and Telecommunications link.
His study looks at the intersection of Computer network and topics like Wireless network with Multiplexing.
His Wireless study integrates concerns from other disciplines, such as Node and Transmission.
Fredrik Gunnarsson combines subjects such as Detection theory and Radio networks with his study of Node.
Focus and Perspective is closely connected to Multimedia in his research, which is encompassed under the umbrella topic of OTDOA.
The Telecommunications link study combines topics in areas such as Key distribution in wireless sensor networks, Wi-Fi array and Base transceiver station.
This overview was generated by a machine learning system which analysed the scientist’s
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