19,462 research outputs found
Mobile Communication Networks and Digital Television Broadcasting Systems in the Same Frequency Bands – Advanced Co-Existence Scenarios
The increasing demand for wireless multimedia services provided by modern communication systems with stable services is a key feature of advanced markets. On the other hand, these systems can many times operate in a neighboring or in the same frequency bands. Therefore, numerous unwanted co-existence scenarios can occur. The aim of this paper is to summarize our results which were achieved during exploration and measurement of the co-existences between still used and upcoming mobile networks (from GSM to LTE) and digital terrestrial television broadcasting (DVB) systems. For all of these measurements and their evaluation universal measurement testbed has been proposed and used. Results presented in this paper are a significant part of our activities in work package WP5 in the ENIAC JU project “Agile RF Transceivers and Front-Ends for Future Smart Multi-Standard Communications Applications (ARTEMOS)”
Comb-based WDM transmission at 10 Tbit/s using a DC-driven quantum-dash mode-locked laser diode
Chip-scale frequency comb generators have the potential to become key
building blocks of compact wavelength-division multiplexing (WDM) transceivers
in future metropolitan or campus-area networks. Among the various comb
generator concepts, quantum-dash (QD) mode-locked laser diodes (MLLD) stand out
as a particularly promising option, combining small footprint with simple
operation by a DC current and offering flat broadband comb spectra. However,
the data transmission performance achieved with QD-MLLD was so far limited by
strong phase noise of the individual comb tones, restricting experiments to
rather simple modulation formats such as quadrature phase shift keying (QPSK)
or requiring hard-ware-based compensation schemes. Here we demonstrate that
these limitations can be over-come by digital symbol-wise phase tracking
algorithms, avoiding any hardware-based phase-noise compensation. We
demonstrate 16QAM dual-polarization WDM transmission on 38 channels at an
aggregate net data rate of 10.68 Tbit/s over 75 km of standard single-mode
fiber. To the best of our knowledge, this corresponds to the highest data rate
achieved through a DC-driven chip-scale comb generator without any
hardware-based phase-noise reduction schemes
Principles of Neuromorphic Photonics
In an age overrun with information, the ability to process reams of data has
become crucial. The demand for data will continue to grow as smart gadgets
multiply and become increasingly integrated into our daily lives.
Next-generation industries in artificial intelligence services and
high-performance computing are so far supported by microelectronic platforms.
These data-intensive enterprises rely on continual improvements in hardware.
Their prospects are running up against a stark reality: conventional
one-size-fits-all solutions offered by digital electronics can no longer
satisfy this need, as Moore's law (exponential hardware scaling),
interconnection density, and the von Neumann architecture reach their limits.
With its superior speed and reconfigurability, analog photonics can provide
some relief to these problems; however, complex applications of analog
photonics have remained largely unexplored due to the absence of a robust
photonic integration industry. Recently, the landscape for
commercially-manufacturable photonic chips has been changing rapidly and now
promises to achieve economies of scale previously enjoyed solely by
microelectronics.
The scientific community has set out to build bridges between the domains of
photonic device physics and neural networks, giving rise to the field of
\emph{neuromorphic photonics}. This article reviews the recent progress in
integrated neuromorphic photonics. We provide an overview of neuromorphic
computing, discuss the associated technology (microelectronic and photonic)
platforms and compare their metric performance. We discuss photonic neural
network approaches and challenges for integrated neuromorphic photonic
processors while providing an in-depth description of photonic neurons and a
candidate interconnection architecture. We conclude with a future outlook of
neuro-inspired photonic processing.Comment: 28 pages, 19 figure
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