What is he best known for?
The fields of study he is best known for:
- Computer network
- The Internet
- Artificial intelligence
His scientific interests lie mostly in Computer network, Wireless network, Cognitive radio, Wireless ad hoc network and Throughput.
His Computer network study integrates concerns from other disciplines, such as Wireless, Distributed computing and Communication channel.
His study in the field of Wireless WAN is also linked to topics like Resource management.
Xinbing Wang has included themes like Mathematical optimization, Nash equilibrium, Access time and Game theory in his Cognitive radio study.
The concepts of his Wireless ad hoc network study are interwoven with issues in Mobile ad hoc network, Network packet, Directional antenna and Base station.
His Throughput research is multidisciplinary, incorporating elements of MIMO and Time division multiple access.
His most cited work include:
- Spectrum Trading in Cognitive Radio Networks: A Contract-Theoretic Modeling Approach (321 citations)
- Distributed scheduling scheme for video streaming over multi-channel multi-radio multi-hop wireless networks (229 citations)
- Spectrum Sharing in Cognitive Radio Networks—An Auction-Based Approach (221 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Computer network, Throughput, Wireless network, Cognitive radio and Distributed computing.
His studies in Computer network integrate themes in fields like Wireless and Wireless ad hoc network.
His work investigates the relationship between Wireless ad hoc network and topics such as Mobile ad hoc network that intersect with problems in Mobility model and Mobile computing.
His Throughput research includes themes of Relay, Transmission, MIMO, Base station and Scheduling.
His Wireless network research integrates issues from Network topology, Upper and lower bounds, Topology and Hop.
As a member of one scientific family, Xinbing Wang mostly works in the field of Cognitive radio, focusing on Game theory and, on occasion, Nash equilibrium.
He most often published in these fields:
- Computer network (46.30%)
- Throughput (22.69%)
- Wireless network (20.37%)
What were the highlights of his more recent work (between 2017-2021)?
- Social network (6.71%)
- Theoretical computer science (6.94%)
- Artificial intelligence (7.18%)
In recent papers he was focusing on the following fields of study:
Xinbing Wang mostly deals with Social network, Theoretical computer science, Artificial intelligence, Distributed computing and Graph.
His study in Social network is interdisciplinary in nature, drawing from both Wireless, Function, Maximization and Parameterized complexity.
His Artificial intelligence research incorporates elements of Machine learning, Reliability, Computer vision and Natural language processing.
He has included themes like Enhanced Data Rates for GSM Evolution, Server, Mobile edge computing and Online algorithm in his Distributed computing study.
Many of his studies involve connections with topics such as Computer network and Erasure code.
The various areas that Xinbing Wang examines in his Computer network study include Cognitive radio, Underlay, Wireless ad hoc network and Transmitter.
Between 2017 and 2021, his most popular works were:
- Coded Caching Under Arbitrary Popularity Distributions (53 citations)
- Crowdsensing-Based Consensus Incident Report for Road Traffic Acquisition (26 citations)
- Improve Accuracy of Fingerprinting Localization with Temporal Correlation of the RSS (26 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- The Internet
- Artificial intelligence
His main research concerns Social network, Data mining, Mobile computing, Reliability and Artificial intelligence.
The study incorporates disciplines such as Mathematical optimization, Combinatorial optimization, Steiner tree problem and Tree in addition to Mobile computing.
His work carried out in the field of Reliability brings together such families of science as Incentive, Sliding window protocol, Cellular network and Identification.
His study explores the link between Artificial intelligence and topics such as Machine learning that cross with problems in RSS and Key.
Computer network covers Xinbing Wang research in Server.
His work on Eavesdropping as part of his general Computer network study is frequently connected to Throughput, thereby bridging the divide between different branches of science.
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.
