10,105 research outputs found
Distortion Exponent in MIMO Channels with Feedback
The transmission of a Gaussian source over a block-fading multiple antenna
channel in the presence of a feedback link is considered. The feedback link is
assumed to be an error and delay free link of capacity 1 bit per channel use.
Under the short-term power constraint, the optimal exponential behavior of the
end-to-end average distortion is characterized for all source-channel bandwidth
ratios. It is shown that the optimal transmission strategy is successive
refinement source coding followed by progressive transmission over the channel,
in which the channel block is allocated dynamically among the layers based on
the channel state using the feedback link as an instantaneous automatic repeat
request (ARQ) signal.Comment: Presented at the IEEE Information Theory Workshop (ITW), Taormina,
Italy, Oct. 200
Hybrid M-FSK/DQPSK Modulations for CubeSat Picosatellites
Conventional CubeSat radio systems typically use one of several basic modulations, such as AFSK, GMSK, BPSK, QPSK and OOK or switch between them on demand if possible. These modulations represent a bal¬anced trade-off between good energy efficiency of high order M-FSK modulation and good spectral efficiency of high order M-QAM modulation. Utilization of modulations with the best energy efficiency is not possible due to strict limits on occupied frequency bandwidth. In this paper the proposed group of hybrid modulations and proposed hybrid modulator and demodulator are presented. Novel solution offer interesting possibilities of increasing spectral efficiency as well as energy efficiency of basic M-FSK modulation by embedding DQPSK symbols between two M-FSK symbols. Such group of hybrid modulations offers suitable properties for picosatellite, e.g. simple realization onboard the picosatellite, better energy and spectral efficiency, low PAPR, wide range of adaptation by changing the order of M-FSK, suitable for easy non-coherent demodulation, good immunity to Doppler effect with DM-FSK coding
Energy Management Policies for Energy-Neutral Source-Channel Coding
In cyber-physical systems where sensors measure the temporal evolution of a
given phenomenon of interest and radio communication takes place over short
distances, the energy spent for source acquisition and compression may be
comparable with that used for transmission. Additionally, in order to avoid
limited lifetime issues, sensors may be powered via energy harvesting and thus
collect all the energy they need from the environment. This work addresses the
problem of energy allocation over source acquisition/compression and
transmission for energy-harvesting sensors. At first, focusing on a
single-sensor, energy management policies are identified that guarantee a
maximal average distortion while at the same time ensuring the stability of the
queue connecting source and channel encoders. It is shown that the identified
class of policies is optimal in the sense that it stabilizes the queue whenever
this is feasible by any other technique that satisfies the same average
distortion constraint. Moreover, this class of policies performs an independent
resource optimization for the source and channel encoders. Analog transmission
techniques as well as suboptimal strategies that do not use the energy buffer
(battery) or use it only for adapting either source or channel encoder energy
allocation are also studied for performance comparison. The problem of
optimizing the desired trade-off between average distortion and delay is then
formulated and solved via dynamic programming tools. Finally, a system with
multiple sensors is considered and time-division scheduling strategies are
derived that are able to maintain the stability of all data queues and to meet
the average distortion constraints at all sensors whenever it is feasible.Comment: Submitted to IEEE Transactions on Communications in March 2011; last
update in July 201
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
Joint Source-Channel Codes for MIMO Block Fading Channels
We consider transmission of a continuous amplitude source over an L-block
Rayleigh fading MIMO channel when the channel state
information is only available at the receiver. Since the channel is not
ergodic, Shannon's source-channel separation theorem becomes obsolete and the
optimal performance requires a joint source -channel approach. Our goal is to
minimize the expected end-to-end distortion, particularly in the high SNR
regime. The figure of merit is the distortion exponent, defined as the
exponential decay rate of the expected distortion with increasing SNR. We
provide an upper bound and lower bounds for the distortion exponent with
respect to the bandwidth ratio among the channel and source bandwidths. For the
lower bounds, we analyze three different strategies based on layered source
coding concatenated with progressive, superposition or hybrid digital/analog
transmission. In each case, by adjusting the system parameters we optimize the
distortion exponent as a function of the bandwidth ratio. We prove that the
distortion exponent upper bound can be achieved when the channel has only one
degree of freedom, that is L=1, and . When we have more
degrees of freedom, our achievable distortion exponents meet the upper bound
for only certain ranges of the bandwidth ratio. We demonstrate that our
results, which were derived for a complex Gaussian source, can be extended to
more general source distributions as well.Comment: 36 pages, 11 figure
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