2,674 research outputs found
Distributed Successive Approximation Coding using Broadcast Advantage: The Two-Encoder Case
Traditional distributed source coding rarely considers the possible link
between separate encoders. However, the broadcast nature of wireless
communication in sensor networks provides a free gossip mechanism which can be
used to simplify encoding/decoding and reduce transmission power. Using this
broadcast advantage, we present a new two-encoder scheme which imitates the
ping-pong game and has a successive approximation structure. For the quadratic
Gaussian case, we prove that this scheme is successively refinable on the
{sum-rate, distortion pair} surface, which is characterized by the
rate-distortion region of the distributed two-encoder source coding. A
potential energy saving over conventional distributed coding is also
illustrated. This ping-pong distributed coding idea can be extended to the
multiple encoder case and provides the theoretical foundation for a new class
of distributed image coding method in wireless scenarios.Comment: In Proceedings of the 48th Annual Allerton Conference on
Communication, Control and Computing, University of Illinois, Monticello, IL,
September 29 - October 1, 201
Lossy Compression via Sparse Linear Regression: Computationally Efficient Encoding and Decoding
We propose computationally efficient encoders and decoders for lossy
compression using a Sparse Regression Code. The codebook is defined by a design
matrix and codewords are structured linear combinations of columns of this
matrix. The proposed encoding algorithm sequentially chooses columns of the
design matrix to successively approximate the source sequence. It is shown to
achieve the optimal distortion-rate function for i.i.d Gaussian sources under
the squared-error distortion criterion. For a given rate, the parameters of the
design matrix can be varied to trade off distortion performance with encoding
complexity. An example of such a trade-off as a function of the block length n
is the following. With computational resource (space or time) per source sample
of O((n/\log n)^2), for a fixed distortion-level above the Gaussian
distortion-rate function, the probability of excess distortion decays
exponentially in n. The Sparse Regression Code is robust in the following
sense: for any ergodic source, the proposed encoder achieves the optimal
distortion-rate function of an i.i.d Gaussian source with the same variance.
Simulations show that the encoder has good empirical performance, especially at
low and moderate rates.Comment: 14 pages, to appear in IEEE Transactions on Information Theor
A Progressive Universal Noiseless Coder
The authors combine pruned tree-structured vector quantization (pruned TSVQ) with Itoh's (1987) universal noiseless coder. By combining pruned TSVQ with universal noiseless coding, they benefit from the “successive approximation” capabilities of TSVQ, thereby allowing progressive transmission of images, while retaining the ability to noiselessly encode images of unknown statistics in a provably asymptotically optimal fashion. Noiseless compression results are comparable to Ziv-Lempel and arithmetic coding for both images and finely quantized Gaussian sources
Successive Wyner-Ziv Coding Scheme and its Application to the Quadratic Gaussian CEO Problem
We introduce a distributed source coding scheme called successive Wyner-Ziv
coding. We show that any point in the rate region of the quadratic Gaussian CEO
problem can be achieved via the successive Wyner-Ziv coding. The concept of
successive refinement in the single source coding is generalized to the
distributed source coding scenario, which we refer to as distributed successive
refinement. For the quadratic Gaussian CEO problem, we establish a necessary
and sufficient condition for distributed successive refinement, where the
successive Wyner-Ziv coding scheme plays an important role.Comment: 28 pages, submitted to the IEEE Transactions on Information Theor
On Two-Pair Two-Way Relay Channel with an Intermittently Available Relay
When multiple users share the same resource for physical layer cooperation
such as relay terminals in their vicinities, this shared resource may not be
always available for every user, and it is critical for transmitting terminals
to know whether other users have access to that common resource in order to
better utilize it. Failing to learn this critical piece of information may
cause severe issues in the design of such cooperative systems. In this paper,
we address this problem by investigating a two-pair two-way relay channel with
an intermittently available relay. In the model, each pair of users need to
exchange their messages within their own pair via the shared relay. The shared
relay, however, is only intermittently available for the users to access. The
accessing activities of different pairs of users are governed by independent
Bernoulli random processes. Our main contribution is the characterization of
the capacity region to within a bounded gap in a symmetric setting, for both
delayed and instantaneous state information at transmitters. An interesting
observation is that the bottleneck for information flow is the quality of state
information (delayed or instantaneous) available at the relay, not those at the
end users. To the best of our knowledge, our work is the first result regarding
how the shared intermittent relay should cooperate with multiple pairs of users
in such a two-way cooperative network.Comment: extended version of ISIT 2015 pape
Multi-user lattice coding for the multiple-access relay channel
This paper considers the multi-antenna multiple access relay channel (MARC),
in which multiple users transmit messages to a common destination with the
assistance of a relay. In a variety of MARC settings, the dynamic decode and
forward (DDF) protocol is very useful due to its outstanding rate performance.
However, the lack of good structured codebooks so far hinders practical
applications of DDF for MARC. In this work, two classes of structured MARC
codes are proposed: 1) one-to-one relay-mapper aided multiuser lattice coding
(O-MLC), and 2) modulo-sum relay-mapper aided multiuser lattice coding
(MS-MLC). The former enjoys better rate performance, while the latter provides
more flexibility to tradeoff between the complexity of the relay mapper and the
rate performance. It is shown that, in order to approach the rate performance
achievable by an unstructured codebook with maximum-likelihood decoding, it is
crucial to use a new K-stage coset decoder for structured O-MLC, instead of the
one-stage decoder proposed in previous works. However, if O-MLC is decoded with
the one-stage decoder only, it can still achieve the optimal DDF
diversity-multiplexing gain tradeoff in the high signal-to-noise ratio regime.
As for MS-MLC, its rate performance can approach that of the O-MLC by
increasing the complexity of the modulo-sum relay-mapper. Finally, for
practical implementations of both O-MLC and MS-MLC, practical short length
lattice codes with linear mappers are designed, which facilitate efficient
lattice decoding. Simulation results show that the proposed coding schemes
outperform existing schemes in terms of outage probabilities in a variety of
channel settings.Comment: 32 pages, 5 figure
Quantization as Histogram Segmentation: Optimal Scalar Quantizer Design in Network Systems
An algorithm for scalar quantizer design on discrete-alphabet sources is proposed. The proposed algorithm can be used to design fixed-rate and entropy-constrained conventional scalar quantizers, multiresolution scalar quantizers, multiple description scalar quantizers, and Wyner–Ziv scalar quantizers. The algorithm guarantees globally optimal solutions for conventional fixed-rate scalar quantizers and entropy-constrained scalar quantizers. For the other coding scenarios, the algorithm yields the best code among all codes that meet a given convexity constraint. In all cases, the algorithm run-time is polynomial in the size of the source alphabet. The algorithm derivation arises from a demonstration of the connection between scalar quantization, histogram segmentation, and the shortest path problem in a certain directed acyclic graph
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