What is he best known for?
The fields of study he is best known for:
- Computer network
- Telecommunications
- Statistics
His primary areas of investigation include Wireless, Distributed computing, Cellular network, Computer network and Cognitive radio.
In Wireless, Honggang Zhang works on issues like Efficient energy use, which are connected to Algorithm design.
His study on Distributed computing also encompasses disciplines like
- Reinforcement learning which connect with Markov decision process, Base station and Software engineering,
- Mobile computing which is related to area like Software-defined networking.
His work on Cellular traffic as part of general Cellular network research is frequently linked to Broadband networks, bridging the gap between disciplines.
His Computer network study combines topics in areas such as Wireless network, Radio resource management, Spectrum management and Wireless WAN.
His Cognitive radio research incorporates themes from Radio spectrum and Electronic engineering, Bandwidth, Ultra-wideband.
His most cited work include:
- CogMesh: A Cluster-Based Cognitive Radio Network (264 citations)
- Network energy saving technologies for green wireless access networks (217 citations)
- Intelligent 5G: When Cellular Networks Meet Artificial Intelligence (212 citations)
What are the main themes of his work throughout his whole career to date?
Honggang Zhang spends much of his time researching Computer network, Distributed computing, Cognitive radio, Cellular network and Base station.
His biological study spans a wide range of topics, including Wireless, Wireless network, Efficient energy use and Communication channel.
The various areas that Honggang Zhang examines in his Wireless study include Compressed sensing and Signal processing.
His research in Distributed computing focuses on subjects like Reinforcement learning, which are connected to Markov decision process, Nash equilibrium and Scheduling.
His Cognitive radio research integrates issues from Radio spectrum, Electronic engineering, Spectral efficiency and Transmission.
His Cellular network research includes elements of Traffic generation model, Real-time computing, Mobile computing and Topology.
He most often published in these fields:
- Computer network (33.46%)
- Distributed computing (24.81%)
- Cognitive radio (22.93%)
What were the highlights of his more recent work (between 2018-2021)?
- Reinforcement learning (18.05%)
- Distributed computing (24.81%)
- Base station (19.55%)
In recent papers he was focusing on the following fields of study:
Honggang Zhang mostly deals with Reinforcement learning, Distributed computing, Base station, Artificial intelligence and Markov decision process.
The study incorporates disciplines such as Scheduling and Mathematical optimization, Nash equilibrium in addition to Reinforcement learning.
His Distributed computing research incorporates elements of Energy consumption, Edge computing, Local area network and Multi-agent system.
His study in Base station is interdisciplinary in nature, drawing from both Cellular network, Graph, Trade-off, Network topology and Multicast.
His Cellular network research is within the category of Computer network.
His work in Markov decision process tackles topics such as Network packet which are related to areas like Optimal control, Schedule, Radio resource management, State space and Server.
Between 2018 and 2021, his most popular works were:
- Optimized Computation Offloading Performance in Virtual Edge Computing Systems Via Deep Reinforcement Learning (171 citations)
- Deep Learning with Long Short-Term Memory for Time Series Prediction (69 citations)
- AI-Based Two-Stage Intrusion Detection for Software Defined IoT Networks (44 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Statistics
- Telecommunications
The scientist’s investigation covers issues in Reinforcement learning, Distributed computing, Resource management, Base station and Artificial intelligence.
The concepts of his Reinforcement learning study are interwoven with issues in Artificial neural network, Scheduling, Mobile device and Mobile edge computing.
His studies in Scheduling integrate themes in fields like Markov decision process, Vehicular ad hoc network and Radio resource management.
Honggang Zhang interconnects Wireless, Computation offloading, Edge computing and Nash equilibrium in the investigation of issues within Mobile edge computing.
His Distributed computing research is multidisciplinary, incorporating perspectives in Shared resource, Intrusion detection system, Network security, Exploit and Software.
His Base station research includes themes of Network virtualization, Spectral efficiency, Service and Communications system.
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