353 research outputs found
Lossy Source Coding with Gaussian or Erased Side-Information
In this paper we find properties that are shared between two seemingly unrelated lossy source coding setups with side information. The first setup is when the source and side information are jointly Gaussian and the distortion measure is quadratic. The second setup is when the side information is an erased version of the source. We begin with the observation that in both these cases the Wyner-Ziv and conditional rate-distortion functions are equal. We further find that there is a continuum of optimal strategies for the conditional rate distortion problem in both these setups. Next, we consider the case when there are two decoders with access to different side-information sources. For the case when the encoder has access to the side information we establish bounds on the rate-distortion function and a sufficient condition for tightness. Under this condition, we find a characterization of the rate-distortion function for physically degraded side information. This characterization holds for both the Gaussian and erasure setups
Nonasymptotic noisy lossy source coding
This paper shows new general nonasymptotic achievability and converse bounds
and performs their dispersion analysis for the lossy compression problem in
which the compressor observes the source through a noisy channel. While this
problem is asymptotically equivalent to a noiseless lossy source coding problem
with a modified distortion function, nonasymptotically there is a noticeable
gap in how fast their minimum achievable coding rates approach the common
rate-distortion function, as evidenced both by the refined asymptotic analysis
(dispersion) and the numerical results. The size of the gap between the
dispersions of the noisy problem and the asymptotically equivalent noiseless
problem depends on the stochastic variability of the channel through which the
compressor observes the source.Comment: IEEE Transactions on Information Theory, 201
Source Coding with Fixed Lag Side Information
We consider source coding with fixed lag side information at the decoder. We
focus on the special case of perfect side information with unit lag
corresponding to source coding with feedforward (the dual of channel coding
with feedback) introduced by Pradhan. We use this duality to develop a linear
complexity algorithm which achieves the rate-distortion bound for any
memoryless finite alphabet source and distortion measure.Comment: 10 pages, 3 figure
Fixed-length lossy compression in the finite blocklength regime
This paper studies the minimum achievable source coding rate as a function of
blocklength and probability that the distortion exceeds a given
level . Tight general achievability and converse bounds are derived that
hold at arbitrary fixed blocklength. For stationary memoryless sources with
separable distortion, the minimum rate achievable is shown to be closely
approximated by , where
is the rate-distortion function, is the rate dispersion, a
characteristic of the source which measures its stochastic variability, and
is the inverse of the standard Gaussian complementary cdf
Heegard-Berger and Cascade Source Coding Problems with Common Reconstruction Constraints
For the HB problem with the CR constraint, the rate-distortion function is
derived under the assumption that the side information sequences are
(stochastically) degraded. The rate-distortion function is also calculated
explicitly for three examples, namely Gaussian source and side information with
quadratic distortion metric, and binary source and side information with
erasure and Hamming distortion metrics. The rate-distortion function is then
characterized for the HB problem with cooperating decoders and (physically)
degraded side information. For the cascade problem with the CR constraint, the
rate-distortion region is obtained under the assumption that side information
at the final node is physically degraded with respect to that at the
intermediate node. For the latter two cases, it is worth emphasizing that the
corresponding problem without the CR constraint is still open. Outer and inner
bounds on the rate-distortion region are also obtained for the cascade problem
under the assumption that the side information at the intermediate node is
physically degraded with respect to that at the final node. For the three
examples mentioned above, the bounds are shown to coincide. Finally, for the HB
problem, the rate-distortion function is obtained under the more general
requirement of constrained reconstruction, whereby the decoder's estimate must
be recovered at the encoder only within some distortion.Comment: to appear in IEEE Trans. Inform. Theor
Network coding meets TCP
We propose a mechanism that incorporates network coding into TCP with only
minor changes to the protocol stack, thereby allowing incremental deployment.
In our scheme, the source transmits random linear combinations of packets
currently in the congestion window. At the heart of our scheme is a new
interpretation of ACKs - the sink acknowledges every degree of freedom (i.e., a
linear combination that reveals one unit of new information) even if it does
not reveal an original packet immediately. Such ACKs enable a TCP-like
sliding-window approach to network coding. Our scheme has the nice property
that packet losses are essentially masked from the congestion control
algorithm. Our algorithm therefore reacts to packet drops in a smooth manner,
resulting in a novel and effective approach for congestion control over
networks involving lossy links such as wireless links. Our experiments show
that our algorithm achieves higher throughput compared to TCP in the presence
of lossy wireless links. We also establish the soundness and fairness
properties of our algorithm.Comment: 9 pages, 9 figures, submitted to IEEE INFOCOM 200
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