What is he best known for?
The fields of study he is best known for:
- Statistics
- Computer network
- Telecommunications
Feifei Gao focuses on Communication channel, Algorithm, Electronic engineering, Relay and MIMO.
Feifei Gao combines subjects such as Transmission, Telecommunications link and Control theory with his study of Communication channel.
His study in Algorithm is interdisciplinary in nature, drawing from both Estimator, Polynomial rooting, Orthogonal frequency-division multiplexing and Fading.
Feifei Gao has researched Electronic engineering in several fields, including Antenna array, Data transmission, Extremely high frequency, Node and Signal.
His Relay study integrates concerns from other disciplines, such as Signal-to-noise ratio, Estimation theory, Linear network coding and Modulation.
His studies in Cognitive radio integrate themes in fields like Transmitter, Transmitter power output and Beamforming.
His most cited work include:
- On channel estimation and optimal training design for amplify and forward relay networks (417 citations)
- Optimal channel estimation and training design for two-way relay networks (304 citations)
- A Unified Transmission Strategy for TDD/FDD Massive MIMO Systems With Spatial Basis Expansion Model (289 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Communication channel, Algorithm, MIMO, Electronic engineering and Telecommunications link.
Feifei Gao has included themes like Relay, Transmission, Beamforming and Control theory in his Communication channel study.
The Algorithm study combines topics in areas such as Fading, Signal-to-noise ratio, Estimator, Statistics and Carrier frequency offset.
His research in MIMO intersects with topics in Wireless, Channel state information and Duplex.
His Electronic engineering study combines topics from a wide range of disciplines, such as Cognitive radio, Data transmission, Backscatter and Signal processing.
His Telecommunications link research includes themes of Overhead, Antenna array, Computer engineering, Real-time computing and Base station.
He most often published in these fields:
- Communication channel (51.06%)
- Algorithm (34.11%)
- MIMO (28.81%)
What were the highlights of his more recent work (between 2018-2021)?
- Communication channel (51.06%)
- MIMO (28.81%)
- Algorithm (34.11%)
In recent papers he was focusing on the following fields of study:
His main research concerns Communication channel, MIMO, Algorithm, Telecommunications link and Base station.
His Communication channel research includes elements of Deep learning, Artificial intelligence and Electronic engineering, Beamforming.
His Electronic engineering research integrates issues from Transmission, Data transmission and Signal processing.
His MIMO research is multidisciplinary, incorporating perspectives in Antenna, Overhead, Orthogonal frequency-division multiplexing and Compressed sensing.
His work deals with themes such as Direction of arrival, Detector, Artificial neural network, Expectation–maximization algorithm and Estimator, which intersect with Algorithm.
His study in Telecommunications link is interdisciplinary in nature, drawing from both Scheduling, Duplex and Carrier frequency offset.
Between 2018 and 2021, his most popular works were:
- Model-Driven Deep Learning for Physical Layer Communications (99 citations)
- Deep Learning-Based Channel Estimation for Doubly Selective Fading Channels (74 citations)
- Sparse Bayesian Learning for the Time-Varying Massive MIMO Channels: Acquisition and Tracking (66 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Computer network
- Telecommunications
His primary areas of study are Communication channel, Telecommunications link, MIMO, Algorithm and Electronic engineering.
His research integrates issues of Topology, Transmission and Estimator in his study of Communication channel.
The concepts of his Telecommunications link study are interwoven with issues in Duplex, Direction of arrival, Compressed sensing and Wideband.
The study incorporates disciplines such as Computer engineering, Beamforming, Deep learning, Artificial intelligence and Base station in addition to MIMO.
His Algorithm study integrates concerns from other disciplines, such as Carrier frequency offset, Posterior probability, Entropy and Modulation.
His Electronic engineering study incorporates themes from Signal processing and Precoding.
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