What is he best known for?
The fields of study he is best known for:
- Computer network
- Telecommunications
- Statistics
His scientific interests lie mostly in Computer network, Wireless network, Communication channel, Resource allocation and Scheduling.
His Computer network research includes elements of Wireless ad hoc network, Channel allocation schemes and Distributed computing.
His study in Wireless network is interdisciplinary in nature, drawing from both Throughput, Game theory and Fading.
His Communication channel study combines topics in areas such as Transmitter and Transmission.
His research in Resource allocation intersects with topics in Wireless, Physical layer, Mathematical optimization and Telecommunications link.
His Wireless research incorporates themes from Access network and Real-time computing.
His most cited work include:
- Communication over fading channels with delay constraints (719 citations)
- Distributed interference compensation for wireless networks (698 citations)
- Auction-based spectrum sharing (571 citations)
What are the main themes of his work throughout his whole career to date?
Randall A. Berry mainly investigates Computer network, Wireless network, Wireless, Communication channel and Mathematical optimization.
The concepts of his Computer network study are interwoven with issues in Distributed computing and Throughput.
His Wireless network research integrates issues from Distributed algorithm, Channel allocation schemes and Power control.
His work is dedicated to discovering how Wireless, Real-time computing are connected with Packet loss and other disciplines.
His Communication channel study combines topics from a wide range of disciplines, such as Transmitter, Transmission and Theoretical computer science.
His study in the field of Nash equilibrium and Optimization problem is also linked to topics like Set.
He most often published in these fields:
- Computer network (43.02%)
- Wireless network (21.94%)
- Wireless (20.23%)
What were the highlights of his more recent work (between 2018-2021)?
- Telecommunications (11.11%)
- Service provider (11.68%)
- Competition (7.41%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Telecommunications, Service provider, Competition, Spectrum management and Wireless.
The various areas that Randall A. Berry examines in his Telecommunications study include Energy, Game theory and Bandwidth.
In the subject of general Spectrum management, his work in Licensed spectrum is often linked to Economic surplus, thereby combining diverse domains of study.
The concepts of his Wireless study are interwoven with issues in Cournot competition and Network pricing.
Randall A. Berry combines subjects such as Payment and Mobile broadband with his study of Computer network.
His Resource allocation research incorporates elements of Quantization, Wireless network, Mathematical optimization, Pricing strategies and Mechanism design.
Between 2018 and 2021, his most popular works were:
- The Impact of Unlicensed Access on Small-Cell Resource Allocation (5 citations)
- A Business Model Analysis of Mobile Data Rewards (5 citations)
- Crowdsourcing with Heterogeneous Workers in Social Networks (4 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Telecommunications
- Statistics
Crowdsourcing, Service provider, Stackelberg competition, Revenue and Computer network are his primary areas of study.
Randall A. Berry integrates Service provider and Spectrum management in his research.
His study on Spectrum management also encompasses disciplines like
- Monopoly together with Competition and Telecommunications,
- Heterogeneous network and related Resource allocation.
The Resource allocation study combines topics in areas such as Incentive, Incentive compatibility, Finite set and Strategic dominance.
Randall A. Berry usually deals with Revenue and limits it to topics linked to Payment and Cellular network and Operations research.
His Wireless research is multidisciplinary, incorporating perspectives in Investment decisions and Investment.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
