TU Berlin

Department of Telecommunication SystemsJohannes Dommel, Dipl.-Ing.

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Johannes Dommel, Dipl.-Ing.

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Johannes Dommel was born in Lübben (Spreewald), German Democratic Republic, in 1984. He received the Dipl.-Ing. degree in Electrical Engineering from the Technische Universität Ilmenau, Germany, in 2010. He joined the Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute (HHI), Berlin, in 2010.

Since then, he is involved in national- and international research projects in the field of wireless communications ("5G and beyond") and standardization (3GPP Rel.15/16) as a research associate and project manager (PMP). Currently, his work focusses on Industrial NB-IoT and Non-Orthogonal Multiple Access (NOMA).

His research interests includes the application of information theory, digital signal processing and optimization in wireless communication systems, where he is working towards his PhD since 2016.

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Publications

Joint Source-Channel Coding for Grant-Free Radio Access in IoT Fog Networks: Edge vs Cloud Processing
Citation key Dom2020SSP
Author J. Dommel, Z. Utkovski, O. Simeone and S. Stanczak
Year 2020
Journal IEEE Statistical Signal Processing Workshop 2020, Rio de Janeiro, Brazil, 12-15 July, 2020
Abstract A multi-cell Fog-Radio Access Network (F-RAN) architecture is considered in which Internet of Things (IoT) devices monitor a number of multi-valued events and transmit in the uplink using grant-free random access. The devices in each cell are connected to an Edge Node (EN), which has a finite-capacity fronthaul link to a Central Processor (CP). In contrast to conventional information-agnostic protocols based on Separate Source-Channel (SSC) coding, where each device uses a separate codebook, this paper considers an information-centric approach based on Joint Source-Channel (JSC) coding via a non-orthogonal generalization of Type-Based Multiple Access (TBMA). According to this transmission protocol, all sensors measuring the same event share the same codebook (with non-orthogonal codewords), and the multi-cell F-RAN architecture directly detects the events' values without first performing individual decoding for each device. Cloud and edge detection schemes based on Bayesian message passing are designed and trade-offs between cloud and edge processing are assessed.
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