Ronald Nissel
Team Leader at Huawei
Gothenburg, Sweden
Summary
👤
Senior🎓
Top SchoolRonald Nissel is a team leader and research-engineering specialist with eight years’ experience shaping 5G/6G base station architecture and leading small expert teams at Huawei. He holds five academic degrees including a PhD and combines deep theoretical expertise in signal processing and Massive MIMO with hands-on simulation and prototyping in Matlab and Python. Ronald has a track record of identifying disruptive root technologies and even uncovered a decade-old, field‑impacting error in the Massive MIMO literature. Rapidly promoted to project lead within 1.5 years, he has steered research directions that attracted additional investment and delivered multiple “excellent” project evaluations. Beyond corporate research he runs a consulting company and contributes code on GitHub (200+ stars), reflecting a rare blend of academic influence (h-index 17) and practical product-facing engineering. Based in Gothenburg, he excels at translating advanced algorithms into scalable baseband and hardware-aware solutions across link- and system-level domains.
8 years of coding experience
5 years of employment as a software developer
Vienna University of TechnologyMSc, Economics, Graduated with highest distinction, GPA 3.86, MSc, Economics, Graduated with highest distinction, GPA 3.86 at University of ViennaBSc, Business, Economics and Social Sciences, BSc, Business, Economics and Social Sciences at WU (Vienna University of Economics and Business)Technical High School, Electronics and Computer Engineering, Graduated with highest distinction, Technical High School, Electronics and Computer Engineering, Graduated with highest distinction at HTL Mödling
German, English
Github Skills (11)
filterbank10
matlab10
multipath10
ber10
signal-processing10
modulation10
dft9
5g9
python7
mobile6
low-latency2
Programming languages (2)
Github contributions (5)
rnissel/FBMC
Mar 2018 - May 2018
Compares FBMC to OFDM based schemes. Reproduces all figures from “Filter bank multicarrier modulation schemes for future mobile communications”, IEEE Journal on Selected Areas in Communications, 2017.
Contributions:9 commits, 8 pushes, 1 branch in 1 month
filterbankmobile5gnew-radiofbmc
rnissel/Pruned-DFT-s-FBMC_Python
Mar 2018 - Jul 2018
Simulates pruned DFT spread FBMC and compares the performance to OFDM, SC-FDMA and conventional FBMC. The included classes (QAM, DoublySelectiveChannel, OFDM, FBMC) can be reused in other projects.
Contributions:3 releases, 10 commits, 9 pushes in 3 months
dftfbmcofdmsc-fdmapython
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