163 research outputs found
On feedback in network source coding
We consider source coding over networks with
unlimited feedback from the sinks to the sources. We first show
examples of networks where the rate region with feedback is
a strict superset of that without feedback. Next, we find an
achievable region for multiterminal lossy source coding with
feedback. Finally, we evaluate this region for the case when one
of the sources is fully known at the decoder and use the result
to show that this region is a strict superset of the best known
achievable region for the problem without feedback
Secure Multiterminal Source Coding with Side Information at the Eavesdropper
The problem of secure multiterminal source coding with side information at
the eavesdropper is investigated. This scenario consists of a main encoder
(referred to as Alice) that wishes to compress a single source but
simultaneously satisfying the desired requirements on the distortion level at a
legitimate receiver (referred to as Bob) and the equivocation rate --average
uncertainty-- at an eavesdropper (referred to as Eve). It is further assumed
the presence of a (public) rate-limited link between Alice and Bob. In this
setting, Eve perfectly observes the information bits sent by Alice to Bob and
has also access to a correlated source which can be used as side information. A
second encoder (referred to as Charlie) helps Bob in estimating Alice's source
by sending a compressed version of its own correlated observation via a
(private) rate-limited link, which is only observed by Bob. For instance, the
problem at hands can be seen as the unification between the Berger-Tung and the
secure source coding setups. Inner and outer bounds on the so called
rates-distortion-equivocation region are derived. The inner region turns to be
tight for two cases: (i) uncoded side information at Bob and (ii) lossless
reconstruction of both sources at Bob --secure distributed lossless
compression. Application examples to secure lossy source coding of Gaussian and
binary sources in the presence of Gaussian and binary/ternary (resp.) side
informations are also considered. Optimal coding schemes are characterized for
some cases of interest where the statistical differences between the side
information at the decoders and the presence of a non-zero distortion at Bob
can be fully exploited to guarantee secrecy.Comment: 26 pages, 16 figures, 2 table
Wyner-Ziv coding based on TCQ and LDPC codes and extensions to multiterminal source coding
Driven by a host of emerging applications (e.g., sensor networks and wireless
video), distributed source coding (i.e., Slepian-Wolf coding, Wyner-Ziv coding and
various other forms of multiterminal source coding), has recently become a very active
research area.
In this thesis, we first design a practical coding scheme for the quadratic Gaussian
Wyner-Ziv problem, because in this special case, no rate loss is suffered due to
the unavailability of the side information at the encoder. In order to approach the
Wyner-Ziv distortion limit D??W Z(R), the trellis coded quantization (TCQ) technique
is employed to quantize the source X, and irregular LDPC code is used to implement
Slepian-Wolf coding of the quantized source input Q(X) given the side information
Y at the decoder. An optimal non-linear estimator is devised at the joint decoder
to compute the conditional mean of the source X given the dequantized version of
Q(X) and the side information Y . Assuming ideal Slepian-Wolf coding, our scheme
performs only 0.2 dB away from the Wyner-Ziv limit D??W Z(R) at high rate, which
mirrors the performance of entropy-coded TCQ in classic source coding. Practical
designs perform 0.83 dB away from D??W Z(R) at medium rates. With 2-D trellis-coded
vector quantization, the performance gap to D??W Z(R) is only 0.66 dB at 1.0 b/s and
0.47 dB at 3.3 b/s.
We then extend the proposed Wyner-Ziv coding scheme to the quadratic Gaussian
multiterminal source coding problem with two encoders. Both direct and indirect
settings of multiterminal source coding are considered. An asymmetric code design
containing one classical source coding component and one Wyner-Ziv coding component
is first introduced and shown to be able to approach the corner points on the
theoretically achievable limits in both settings. To approach any point on the theoretically
achievable limits, a second approach based on source splitting is then described.
One classical source coding component, two Wyner-Ziv coding components, and a
linear estimator are employed in this design. Proofs are provided to show the achievability
of any point on the theoretical limits in both settings by assuming that both
the source coding and the Wyner-Ziv coding components are optimal. The performance
of practical schemes is only 0.15 b/s away from the theoretical limits for the
asymmetric approach, and up to 0.30 b/s away from the limits for the source splitting
approach
Distributed Joint Source-Channel Coding With Copula-Function-Based Correlation Modeling for Wireless Sensors Measuring Temperature
Wireless sensor networks (WSNs) deployed for temperature monitoring in indoor environments call for systems that perform efficient compression and reliable transmission of the measurements. This is known to be a challenging problem in such deployments, as highly efficient compression mechanisms impose a high computational cost at the encoder. In this paper, we propose a new distributed joint source-channel coding (DJSCC) solution for this problem. Our design allows for efficient compression and error-resilient transmission, with low computational complexity at the sensor. A new Slepian-Wolf code construction, based on non-systematic Raptor codes, is devised that achieves good performance at short code lengths, which are appropriate for temperature monitoring applications. A key contribution of this paper is a novel Copula-function-based modeling approach that accurately expresses the correlation amongst the temperature readings from colocated sensors. Experimental results using a WSN deployment reveal that, for lossless compression, the proposed Copula-function-based model leads to a notable encoding rate reduction (of up to 17.56%) compared with the state-of-the-art model in the literature. Using the proposed model, our DJSCC system achieves significant rate savings (up to 41.81%) against a baseline system that performs arithmetic entropy encoding of the measurements. Moreover, under channel losses, the transmission rate reduction against the state-of-the-art model reaches 19.64%, which leads to energy savings between 18.68% to 24.36% with respect to the baseline system
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