429 citations · 939 across the 56 of their papers we have counts for
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Deep Reinforcement Learning for Uplink Multi-Carrier Non-Orthogonal Multiple Access Resource Allocation Using Buffer State Information
Eike-Manuel Bansbach, Yigit Kiyak, Laurent Schmalen
For orthogonal multiple access (OMA) systems, the number of served user equipments (UEs) is limited to the number of available orthogonal resources. On the other hand, non-orthogon…
Deep Reinforcement Learning for Wireless Resource Allocation Using Buffer State Information
Eike-Manuel Bansbach, Victor Eliachevitch, Laurent Schmalen
As the number of user equipments (UEs) with various data rate and latency requirements increases in wireless networks, the resource allocation problem for orthogonal frequency-divi…
High Speed Data Transmission over GI-MMF Using Mode Group Division Multiplexing
Bernd Franz, Liaquat Ali, Laurent Schmalen +1
We transmitted 4x28 Gbit/s over 5-km standard GI-MMF using four different mode groups in combination with direct detection and on-off-keying format (OOK). Due to the square-law det…