What is he best known for?
The fields of study he is best known for:
- Computer network
- Telecommunications
- Electrical engineering
His main research concerns Electronic engineering, Base station, Wireless, Algorithm and Compressed sensing.
The various areas that he examines in his Electronic engineering study include MIMO, Communication channel and Bandwidth.
He has included themes like Pilot signal, Cellular network, Telecommunications link and Electrical engineering in his Base station study.
His Wireless study integrates concerns from other disciplines, such as Transmitter, Terminal and Scheduling, Computer network.
His studies in Compressed sensing integrate themes in fields like Belief propagation, Message passing and Robustness.
His Beamforming research is multidisciplinary, incorporating elements of Spatial multiplexing and Cellular communication.
His most cited work include:
- Millimeter-Wave Cellular Wireless Networks: Potentials and Challenges (1661 citations)
- Millimeter Wave Channel Modeling and Cellular Capacity Evaluation (1515 citations)
- An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems (1344 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Electronic engineering, Computer network, Wireless, Base station and Algorithm.
His Electronic engineering research incorporates elements of Extremely high frequency, Communication channel and Spatial multiplexing.
His Wireless study incorporates themes from Terminal, Transmission and Real-time computing.
His Base station course of study focuses on Telecommunications link and Orthogonal frequency-division multiplexing.
The concepts of his Algorithm study are interwoven with issues in Message passing, Mathematical optimization and Theoretical computer science.
His work in Cellular network covers topics such as Wireless network which are related to areas like Femtocell.
He most often published in these fields:
- Electronic engineering (24.30%)
- Computer network (22.78%)
- Wireless (20.51%)
What were the highlights of his more recent work (between 2016-2021)?
- Communication channel (16.96%)
- Extremely high frequency (13.42%)
- Electronic engineering (24.30%)
In recent papers he was focusing on the following fields of study:
Sundeep Rangan mostly deals with Communication channel, Extremely high frequency, Electronic engineering, Wireless and Beamforming.
His study in Communication channel is interdisciplinary in nature, drawing from both Autoencoder, Handover, Throughput, Algorithm and Blocking.
He studied Electronic engineering and Key that intersect with Telecommunications, Cellular network and Spectrum management.
His Wireless research integrates issues from Network simulation, Computer network, Base station and End-to-end principle.
The Base station study combines topics in areas such as Real-time computing, Bandwidth and Antenna.
His Beamforming study combines topics from a wide range of disciplines, such as Spatial multiplexing, MIMO, Data transmission, Transmitter and Telecommunications link.
Between 2016 and 2021, his most popular works were:
- End-to-End Simulation of 5G mmWave Networks (179 citations)
- Toward 6G Networks: Use Cases and Technologies (176 citations)
- Improved Handover Through Dual Connectivity in 5G mmWave Mobile Networks (165 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Telecommunications
- Electrical engineering
The scientist’s investigation covers issues in Computer network, Communication channel, Wireless, Belief propagation and Handover.
Cellular network and Network congestion are among the areas of Computer network where Sundeep Rangan concentrates his study.
His Communication channel research incorporates themes from Extremely high frequency, Key and Communications system.
Key connects with themes related to Electronic engineering in his study.
He combines subjects such as Beamforming and Base station with his study of Wireless.
He interconnects Discrete mathematics, Approximation algorithm and Applied mathematics in the investigation of issues within Belief propagation.
This overview was generated by a machine learning system which analysed the scientist’s
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