His primary areas of study are Computer network, Communication channel, Decoding methods, Topology and Fading. Computer network is closely attributed to Relay in his work. His Communication channel research is multidisciplinary, relying on both Relay channel and Transmitter.
His Transmitter study combines topics in areas such as Transmission, Real-time computing and Communications system. His work deals with themes such as MIMO, Multiplexing, Secrecy and Shared secret, which intersect with Topology. Much of his study explores Fading relationship to Mathematical optimization.
His primary areas of investigation include Communication channel, Computer network, Topology, Algorithm and Transmission. The study incorporates disciplines such as Transmitter, Decoding methods and Wireless in addition to Communication channel. His research in Transmitter intersects with topics in Real-time computing and Communications system.
His Computer network research incorporates themes from Relay channel, Relay and Wireless network. Deniz Gunduz usually deals with Topology and limits it to topics linked to MIMO and Multiplexing and Spectral efficiency. The various areas that Deniz Gunduz examines in his Fading study include Mathematical optimization and Channel state information.
His scientific interests lie mostly in Communication channel, Wireless, Computer network, Algorithm and Distributed computing. In his study, Electronic engineering is inextricably linked to Modulation, which falls within the broad field of Communication channel. Many of his research projects under Wireless are closely connected to Contextual image classification with Contextual image classification, tying the diverse disciplines of science together.
His biological study spans a wide range of topics, including Adversarial system and Federated learning. Deniz Gunduz has researched Distributed computing in several fields, including Energy consumption, Energy harvesting, Markov decision process and Reinforcement learning. His study explores the link between Fading and topics such as Analog transmission that cross with problems in Decoding methods and Broadband.
Deniz Gunduz mainly focuses on Wireless, Communication channel, Computer network, Edge device and Fading. His work in the fields of Wireless, such as Wireless network and Channel state information, overlaps with other areas such as Perspective. In his study, which falls under the umbrella issue of Wireless network, Computer engineering, Throughput and Efficient energy use is strongly linked to Transmission.
His Communication channel study also includes fields such as
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.
The Multiway Relay Channel
D. Gunduz;A. Yener;A. Goldsmith;H. V. Poor.
IEEE Transactions on Information Theory (2013)
Designing intelligent energy harvesting communication systems
Deniz Gunduz;Kostas Stamatiou;Nicolo Michelusi;Michele Zorzi.
IEEE Communications Magazine (2014)
Opportunistic cooperation by dynamic resource allocation
D. Gunduz;E. Erkip.
IEEE Transactions on Wireless Communications (2007)
Learning-based optimization of cache content in a small cell base station
Pol Blasco;Deniz Gündüz.
international conference on communications (2014)
The multi-way relay channel
Deniz Gunduz;Aylin Yener;Andrea Goldsmith;H. Vincent Poor.
international symposium on information theory (2009)
A general framework for the optimization of energy harvesting communication systems with battery imperfections
B. Devillers;D. Gunduz.
Journal of Communications and Networks (2012)
A Learning Theoretic Approach to Energy Harvesting Communication System Optimization
Pol Blasco;Deniz Gunduz;Mischa Dohler.
IEEE Transactions on Wireless Communications (2013)
Wireless Content Caching for Small Cell and D2D Networks
Maria Gregori;Jesus Gomez-Vilardebo;Javier Matamoros;Deniz Gunduz.
IEEE Journal on Selected Areas in Communications (2016)
Two-hop communication with energy harvesting
Deniz Gunduz;Bertrand Devillers.
ieee international workshop on computational advances in multi sensor adaptive processing (2011)
Machine Learning at the Wireless Edge: Distributed Stochastic Gradient Descent Over-the-Air
Mohammad Mohammadi Amiri;Deniz Gunduz.
IEEE Transactions on Signal Processing (2020)
Profile was last updated on December 6th, 2021.
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