7 research outputs found
Deep Neural Network Equalization for Optical Short Reach Communication
Nonlinear distortion has always been a challenge for optical communication due to the
nonlinear transfer characteristics of the fiber itself. The next frontier for optical communication is a
second type of nonlinearities, which results from optical and electrical components. They become the
dominant nonlinearity for shorter reaches. The highest data rates cannot be achieved without effective
compensation. A classical countermeasure is receiver-side equalization of nonlinear impairments
and memory effects using Volterra series. However, such Volterra equalizers are architecturally
complex and their parametrization can be numerical unstable. This contribution proposes an
alternative nonlinear equalizer architecture based on machine learning. Its performance is evaluated
experimentally on coherent 88 Gbaud dual polarization 16QAM 600 Gb/s back-to-back measurements.
The proposed equalizers outperform Volterra and memory polynomial Volterra equalizers up to 6th
orders at a target bit-error rate (BER) of 10
−2
by 0.5 dB and 0.8 dB in optical signal-to-noise ratio
(OSNR), respectively
FDMA Point-to-Multi-Point Fibre Access System for Latency Sensitive Applications
We present a demo for a multiple uplink access system with real-time services. Several terminals transmit and are detected simultaneously through FDMA. The system can allow latency-sensitive and best-effort applications to share the network
FDMA in Point-to-Multipoint Fibre Access Systems for Non-Residential Applications
Optical access networks are seeing growing applications for use cases beyond residential, for example in campus and as Industry 4.0 intra-factory networks, which introduce different requirements in terms of bandwidth delivery and latency. We present an uplink access system with simultaneous transmission and detection of several users by means of frequency division multiplexing (FDM). We demonstrate a multiple uplink access system with differential binary phase shift keying (DBPSK) signals and coherent detection that targets a low and deterministic latency. We achieve receiver (Rx) sensitivities of -43.5dBm, -40dBm, and -34dBm at a pre forward error correction (FEC) bit error ratio (BER) of 10 -3 at 2.5 GBaud, 5 GBaud, and 8 GBaud respectively after 20km of fibre with coherent detection. Furthermore, we show the possibility of employing time-division multiplexing (TDM) within the frequency bands. We also present real-time services showing that the system can allow latency-sensitive and best-effort applications to share the network
A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles
In recent years, there has been a dramatic increase in the use of unmanned
aerial vehicles (UAVs), particularly for small UAVs, due to their affordable
prices, ease of availability, and ease of operability. Existing and future
applications of UAVs include remote surveillance and monitoring, relief
operations, package delivery, and communication backhaul infrastructure.
Additionally, UAVs are envisioned as an important component of 5G wireless
technology and beyond. The unique application scenarios for UAVs necessitate
accurate air-to-ground (AG) propagation channel models for designing and
evaluating UAV communication links for control/non-payload as well as payload
data transmissions. These AG propagation models have not been investigated in
detail when compared to terrestrial propagation models. In this paper, a
comprehensive survey is provided on available AG channel measurement campaigns,
large and small scale fading channel models, their limitations, and future
research directions for UAV communication scenarios
Experimental demonstration of SDN-controlled variable-rate fronthaul for converged LTE-over-PON
Zur Rolle von implizitem Wissen im Innovationsprozess
Die Verfasser setzen sich zunaechst auf definitorischer Ebene mit dem Begriff des impliziten Wissens auseinander, um vor diesem Hintergrund nach Erwerb und Verbreitung von implizitem Wissen im Unternehmen zu fragen. Sie entwickeln ein Modell, das den Wissensfluss innerhalb von Innovationsprozessen in Unternehmen abbildet. Die Bedeutung impliziten Wissens im Innovationsprozess wird anhand einer Fallstudie zu einer Unternehmensneugruendung aus dem Biotechnologiebereich verdeutlicht. Die Verfasser fassen die Ergebnisse dieser Fallstudie in vier Thesen zusammen: (1) Implizites Wissen ist im Innovationsprozess von Bedeutung. (2) Implizites Wissen kann eher durch direkte als durch indirekte Kommunikation aktiviert werden. (3) Implizites Wissen ist kontextabhaengig. (4) Es existiert eine Wahrnehmungsschwelle, die zur Erschliessung impliziten Wissens ueberschritten werden muss. (ICE)SIGLEAvailable from http://www.ku-eichstaett.de/WWF/MKT/innovation.pdf / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman