M
Maximilian Matthe
Researcher at Dresden University of Technology
Publications - 60
Citations - 2754
Maximilian Matthe is an academic researcher from Dresden University of Technology. The author has contributed to research in topics: Orthogonal frequency-division multiplexing & MIMO. The author has an hindex of 21, co-authored 55 publications receiving 2263 citations. Previous affiliations of Maximilian Matthe include Vodafone.
Papers
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Journal ArticleDOI
Generalized Frequency Division Multiplexing for 5th Generation Cellular Networks
Nicola Michailow,Maximilian Matthe,Ivan Gaspar,Ainoa Navarro Caldevilla,Luciano Leonel Mendes,Andreas Festag,Gerhard Fettweis +6 more
TL;DR: The flexible nature of GFDM makes this waveform a suitable candidate for future 5G networks, and its main characteristics are analyzed.
Journal ArticleDOI
Latency Critical IoT Applications in 5G: Perspective on the Design of Radio Interface and Network Architecture
Philipp Schulz,Maximilian Matthe,Henrik Klessig,Meryem Simsek,Gerhard Fettweis,Junaid Ansari,Ashraf Shehzad Ali,Bjoern Almeroth,Jens Voigt,Ines Riedel,André Puschmann,Andreas Mitschele-Thiel,Michael Muller,Thomas Elste,Marcus Windisch +14 more
TL;DR: The design challenges and proposed solutions for the radio interface and network architecture to fulfill latency critical IoT applications requirements are discussed, which mainly benefit from flexibility and service-centric approaches.
Proceedings ArticleDOI
Influence of pulse shaping on bit error rate performance and out of band radiation of Generalized Frequency Division Multiplexing
TL;DR: Simulation results show that GFDM reduces the OOB radiation by 46dB compared to OFDM, while at the same time, the OFDM BER can be achieved when using the Dirichlet pulse filter.
Journal ArticleDOI
Generalized Frequency Division Multiplexing in a Gabor Transform Setting
TL;DR: This letter shows the equivalence of the recently proposed generalized frequency division multiplexing (GFDM) communications scheme with a finite discrete critically sampled Gabor expansion and transform with an efficient algorithm for calculation of specific GFDM receiver filters.
Journal ArticleDOI
Expectation Propagation for Near-Optimum Detection of MIMO-GFDM Signals
Dan Zhang,Luciano Leonel Mendes,Maximilian Matthe,Ivan Gaspar,Nicola Michailow,Gerhard Fettweis +5 more
TL;DR: It is shown that the resulting iterative MIMo-GFDM receiver with affordable complexity can approach optimum decoding performance and outperform MIMO-OFDM in a rich multipath environment.