What is he best known for?
The fields of study he is best known for:
- Statistics
- Telecommunications
- Computer network
Fading, Electronic engineering, Algorithm, Rayleigh fading and Statistics are his primary areas of study.
His research integrates issues of Channel state information and Topology in his study of Fading.
His Electronic engineering study incorporates themes from Phase-shift keying, Additive white Gaussian noise, Signal-to-noise ratio, Frequency-shift keying and Bit error rate.
His Algorithm research incorporates themes from Noise, Estimator, Digital radio and Interference.
His Rayleigh fading study integrates concerns from other disciplines, such as Wireless, Rayleigh scattering and Diversity combining.
His studies deal with areas such as Spread spectrum and Signal as well as Statistics.
His most cited work include:
- A comparison of SNR estimation techniques for the AWGN channel (724 citations)
- Autoregressive modeling for fading channel simulation (462 citations)
- Resource Allocation in Spectrum-Sharing OFDMA Femtocells With Heterogeneous Services (321 citations)
What are the main themes of his work throughout his whole career to date?
Norman C. Beaulieu focuses on Fading, Algorithm, Electronic engineering, Communication channel and Statistics.
His research on Fading frequently connects to adjacent areas such as Bit error rate.
In Algorithm, Norman C. Beaulieu works on issues like Phase-shift keying, which are connected to Keying and Quadrature amplitude modulation.
His research investigates the connection between Electronic engineering and topics such as Interference that intersect with issues in Pulse shaping.
His study on Communication channel also encompasses disciplines like
- Control theory together with Intersymbol interference and Noise,
- Computer network, which have a strong connection to Wireless.
His biological study deals with issues like Topology, which deal with fields such as Relay.
He most often published in these fields:
- Fading (42.40%)
- Algorithm (35.43%)
- Electronic engineering (29.01%)
What were the highlights of his more recent work (between 2012-2021)?
- Computer network (8.93%)
- Communication channel (25.94%)
- Fading (42.40%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Computer network, Communication channel, Fading, Relay and Wireless.
The concepts of his Communication channel study are interwoven with issues in Algorithm, Beamforming, Interference and Control theory.
Fading and Electronic engineering are commonly linked in his work.
His Relay study combines topics from a wide range of disciplines, such as Co-channel interference, Hop and Topology.
His Wireless research is multidisciplinary, incorporating perspectives in Distributed computing, Wireless sensor network and Efficient energy use.
His research in Nakagami distribution intersects with topics in Probability density function, Phase-shift keying and Rician fading.
Between 2012 and 2021, his most popular works were:
- Resource Allocation in Spectrum-Sharing OFDMA Femtocells With Heterogeneous Services (321 citations)
- Resource Allocation for Cognitive Small Cell Networks: A Cooperative Bargaining Game Theoretic Approach (290 citations)
- Energy-Efficient Optimal Power Allocation for Fading Cognitive Radio Channels: Ergodic Capacity, Outage Capacity, and Minimum-Rate Capacity (79 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Computer network
- Telecommunications
His main research concerns Fading, Relay, Communication channel, Computer network and Wireless.
Fading is often connected to Phase-shift keying in his work.
His Relay research includes elements of Electronic engineering, Co-channel interference, Hop and Topology.
Within one scientific family, Norman C. Beaulieu focuses on topics pertaining to Upper and lower bounds under Electronic engineering, and may sometimes address concerns connected to Stochastic process, Additive white Gaussian noise and Poisson point process.
Norman C. Beaulieu has researched Channel state information in several fields, including Algorithm, Machine learning, Telecommunications link and Transmission.
In his work, Mathematical optimization is strongly intertwined with Sparse matrix, which is a subfield of Algorithm.
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