Rudolf Mathar mainly focuses on Mathematical optimization, Communication channel, Base station, Electronic engineering and Computer network. His study in the field of Simulated annealing, Maximization and Heuristics also crosses realms of Weapon target assignment problem. His study in Communication channel is interdisciplinary in nature, drawing from both Wireless and Mathematical analysis.
Rudolf Mathar interconnects Code division multiple access, Frequency allocation, Real-time computing, GSM and Linear programming in the investigation of issues within Base station. His work carried out in the field of Electronic engineering brings together such families of science as Computer hardware, Transmitter power output, MIMO, Duplex and Topology. His Computer network research is multidisciplinary, incorporating elements of Key, Distributed computing and Radio resource management.
Communication channel, Mathematical optimization, Computer network, Algorithm and Electronic engineering are his primary areas of study. The Communication channel study combines topics in areas such as Control theory, Base station and Topology. His study looks at the relationship between Mathematical optimization and fields such as Resource allocation, as well as how they intersect with chemical problems.
His biological study spans a wide range of topics, including Wireless, Wireless network, Key distribution in wireless sensor networks and Transmission. His Algorithm study combines topics in areas such as Additive white Gaussian noise, Theoretical computer science and Probability mass function. His Electronic engineering research integrates issues from Cognitive radio, Wireless sensor network and Orthogonal frequency-division multiplexing.
His main research concerns Algorithm, MIMO, Duplex, Communication channel and Electronic engineering. His Algorithm study combines topics from a wide range of disciplines, such as Adversarial system, Sampling, Upper and lower bounds and Convex optimization. His Convex optimization research is multidisciplinary, relying on both Theoretical computer science, Mathematical optimization and Robustness.
His MIMO study also includes
His primary scientific interests are in Algorithm, Duplex, Artificial intelligence, MIMO and Artificial neural network. Rudolf Mathar has included themes like Sampling, Wireless sensor network and Estimator in his Algorithm study. His studies deal with areas such as Node and Channel state information, Single antenna interference cancellation, Communication channel as well as Duplex.
His research in Communication channel focuses on subjects like Network planning and design, which are connected to Wireless. The concepts of his MIMO study are interwoven with issues in Computer hardware and Electronic engineering. His Convex optimization research includes themes of Convergence, Distortion and Mathematical optimization.
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Estimating position and velocity of mobiles in a cellular radio network
M. Hellebrandt;R. Mathar;M. Scheibenbogen.
IEEE Transactions on Vehicular Technology (1997)
Optimum positioning of base stations for cellular radio networks
Rudolf Mathar;Thomas Niessen.
Wireless Networks (2000)
Location tracking of mobiles in cellular radio networks
M. Hellebrandt;R. Mathar.
IEEE Transactions on Vehicular Technology (1999)
Channel assignment in cellular radio networks
R. Mathar;J. Mattfeldt.
IEEE Transactions on Vehicular Technology (1993)
A cyclic projection algorithm via duality
Norbert Gaffke;Rudolf Mathar.
Metrika (1989)
Dynamic cell association for downlink sum rate maximization in multi-cell heterogeneous networks
Steven Corroy;Laetitia Falconetti;Rudolf Mathar.
international conference on communications (2012)
Power control, capacity, and duality of uplink and downlink in cellular CDMA systems
D. Catrein;L.A. Imhof;R. Mathar.
IEEE Transactions on Communications (2004)
Optimal Base Station Positioning and Channel Assignment for 3G Mobile Networks by Integer Programming
Rudolf Mathar;Michael Schmeink.
Annals of Operations Research (2001)
Deep Reinforcement Learning based Resource Allocation in Low Latency Edge Computing Networks
Tianyu Yang;Yulin Hu;M. Cenk Gursoy;Anke Schmeink.
international symposium on wireless communication systems (2018)
The majorization approach to multidimensional scaling for Minkowski distances
Patrick J. F. Groenen;Rudolf Mathar;Willem J. Heiser.
Journal of Classification (1995)
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