12,344 research outputs found
Information Spectrum Approach to the Source Channel Separation Theorem
A source-channel separation theorem for a general channel has recently been
shown by Aggrawal et. al. This theorem states that if there exist a coding
scheme that achieves a maximum distortion level d_{max} over a general channel
W, then reliable communication can be accomplished over this channel at rates
less then R(d_{max}), where R(.) is the rate distortion function of the source.
The source, however, is essentially constrained to be discrete and memoryless
(DMS). In this work we prove a stronger claim where the source is general,
satisfying only a "sphere packing optimality" feature, and the channel is
completely general. Furthermore, we show that if the channel satisfies the
strong converse property as define by Han & verdu, then the same statement can
be made with d_{avg}, the average distortion level, replacing d_{max}. Unlike
the proofs there, we use information spectrum methods to prove the statements
and the results can be quite easily extended to other situations
Distortion Metrics of Composite Channels with Receiver Side Information
We consider transmission of stationary ergodic sources over non-ergodic composite channels with channel state information at the receiver (CSIR). Previously we introduced alternative capacity definitions to Shannon capacity, including outage and expected capacity. These generalized definitions relax the constraint of Shannon capacity that all transmitted information must be decoded at the receiver. In this work alternative end- to-end distortion metrics such as outage and expected distortion are introduced to relax the constraint that a single distortion level has to be maintained for all channel states. Through the example of transmission of a Gaussian source over a slow-fading Gaussian channel, we illustrate that the end-to-end distortion metrics dictate whether the source and channel coding can be separated for a communication system. We also show that the source and channel need to exchange information through an appropriate interface to facilitate separate encoding and decoding
On the Separation of Lossy Source-Network Coding and Channel Coding in Wireline Networks
This paper proves the separation between source-network coding and channel
coding in networks of noisy, discrete, memoryless channels. We show that the
set of achievable distortion matrices in delivering a family of dependent
sources across such a network equals the set of achievable distortion matrices
for delivering the same sources across a distinct network which is built by
replacing each channel by a noiseless, point-to-point bit-pipe of the
corresponding capacity. Thus a code that applies source-network coding across
links that are made almost lossless through the application of independent
channel coding across each link asymptotically achieves the optimal performance
across the network as a whole.Comment: 5 pages, to appear in the proceedings of 2010 IEEE International
Symposium on Information Theory (ISIT
Minimum-Information LQG Control - Part I: Memoryless Controllers
With the increased demand for power efficiency in feedback-control systems,
communication is becoming a limiting factor, raising the need to trade off the
external cost that they incur with the capacity of the controller's
communication channels. With a proper design of the channels, this translates
into a sequential rate-distortion problem, where we minimize the rate of
information required for the controller's operation under a constraint on its
external cost. Memoryless controllers are of particular interest both for the
simplicity and frugality of their implementation and as a basis for studying
more complex controllers. In this paper we present the optimality principle for
memoryless linear controllers that utilize minimal information rates to achieve
a guaranteed external-cost level. We also study the interesting and useful
phenomenology of the optimal controller, such as the principled reduction of
its order
Joint Wyner-Ziv/Dirty Paper coding by modulo-lattice modulation
The combination of source coding with decoder side-information (Wyner-Ziv
problem) and channel coding with encoder side-information (Gel'fand-Pinsker
problem) can be optimally solved using the separation principle. In this work
we show an alternative scheme for the quadratic-Gaussian case, which merges
source and channel coding. This scheme achieves the optimal performance by a
applying modulo-lattice modulation to the analog source. Thus it saves the
complexity of quantization and channel decoding, and remains with the task of
"shaping" only. Furthermore, for high signal-to-noise ratio (SNR), the scheme
approaches the optimal performance using an SNR-independent encoder, thus it is
robust to unknown SNR at the encoder.Comment: Submitted to IEEE Transactions on Information Theory. Presented in
part in ISIT-2006, Seattle. New version after revie
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