520 research outputs found
Sparse Regression Codes for Multi-terminal Source and Channel Coding
We study a new class of codes for Gaussian multi-terminal source and channel
coding. These codes are designed using the statistical framework of
high-dimensional linear regression and are called Sparse Superposition or
Sparse Regression codes. Codewords are linear combinations of subsets of
columns of a design matrix. These codes were recently introduced by Barron and
Joseph and shown to achieve the channel capacity of AWGN channels with
computationally feasible decoding. They have also recently been shown to
achieve the optimal rate-distortion function for Gaussian sources. In this
paper, we demonstrate how to implement random binning and superposition coding
using sparse regression codes. In particular, with minimum-distance
encoding/decoding it is shown that sparse regression codes attain the optimal
information-theoretic limits for a variety of multi-terminal source and channel
coding problems.Comment: 9 pages, appeared in the Proceedings of the 50th Annual Allerton
Conference on Communication, Control, and Computing - 201
A Study on the Impact of Locality in the Decoding of Binary Cyclic Codes
In this paper, we study the impact of locality on the decoding of binary
cyclic codes under two approaches, namely ordered statistics decoding (OSD) and
trellis decoding. Given a binary cyclic code having locality or availability,
we suitably modify the OSD to obtain gains in terms of the Signal-To-Noise
ratio, for a given reliability and essentially the same level of decoder
complexity. With regard to trellis decoding, we show that careful introduction
of locality results in the creation of cyclic subcodes having lower maximum
state complexity. We also present a simple upper-bounding technique on the
state complexity profile, based on the zeros of the code. Finally, it is shown
how the decoding speed can be significantly increased in the presence of
locality, in the moderate-to-high SNR regime, by making use of a quick-look
decoder that often returns the ML codeword.Comment: Extended version of a paper submitted to ISIT 201
Source and Physical-Layer Network Coding for Correlated Two-Way Relaying
In this paper, we study a half-duplex two-way relay channel (TWRC) with
correlated sources exchanging bidirectional information. In the case, when both
sources have the knowledge of correlation statistics, a source compression with
physical-layer network coding (SCPNC) scheme is proposed to perform the
distributed compression at each source node. When only the relay has the
knowledge of correlation statistics, we propose a relay compression with
physical-layer network coding (RCPNC) scheme to compress the bidirectional
messages at the relay. The closed-form block error rate (BLER) expressions of
both schemes are derived and verified through simulations. It is shown that the
proposed schemes achieve considerable improvements in both error performance
and throughput compared with the conventional non-compression scheme in
correlated two-way relay networks (CTWRNs).Comment: 15 pages, 6 figures. IET Communications, 201
Low-complexity dominance-based Sphere Decoder for MIMO Systems
The sphere decoder (SD) is an attractive low-complexity alternative to
maximum likelihood (ML) detection in a variety of communication systems. It is
also employed in multiple-input multiple-output (MIMO) systems where the
computational complexity of the optimum detector grows exponentially with the
number of transmit antennas. We propose an enhanced version of the SD based on
an additional cost function derived from conditions on worst case interference,
that we call dominance conditions. The proposed detector, the king sphere
decoder (KSD), has a computational complexity that results to be not larger
than the complexity of the sphere decoder and numerical simulations show that
the complexity reduction is usually quite significant
Iterative Soft Input Soft Output Decoding of Reed-Solomon Codes by Adapting the Parity Check Matrix
An iterative algorithm is presented for soft-input-soft-output (SISO)
decoding of Reed-Solomon (RS) codes. The proposed iterative algorithm uses the
sum product algorithm (SPA) in conjunction with a binary parity check matrix of
the RS code. The novelty is in reducing a submatrix of the binary parity check
matrix that corresponds to less reliable bits to a sparse nature before the SPA
is applied at each iteration. The proposed algorithm can be geometrically
interpreted as a two-stage gradient descent with an adaptive potential
function. This adaptive procedure is crucial to the convergence behavior of the
gradient descent algorithm and, therefore, significantly improves the
performance. Simulation results show that the proposed decoding algorithm and
its variations provide significant gain over hard decision decoding (HDD) and
compare favorably with other popular soft decision decoding methods.Comment: 10 pages, 10 figures, final version accepted by IEEE Trans. on
Information Theor
Cooperative Strategies for Simultaneous and Broadcast Relay Channels
Consider the \emph{simultaneous relay channel} (SRC) which consists of a set
of relay channels where the source wishes to transmit common and private
information to each of the destinations. This problem is recognized as being
equivalent to that of sending common and private information to several
destinations in presence of helper relays where each channel outcome becomes a
branch of the \emph{broadcast relay channel} (BRC). Cooperative schemes and
capacity region for a set with two memoryless relay channels are investigated.
The proposed coding schemes, based on \emph{Decode-and-Forward} (DF) and
\emph{Compress-and-Forward} (CF) must be capable of transmitting information
simultaneously to all destinations in such set.
Depending on the quality of source-to-relay and relay-to-destination
channels, inner bounds on the capacity of the general BRC are derived. Three
cases of particular interest are considered: cooperation is based on DF
strategy for both users --referred to as DF-DF region--, cooperation is based
on CF strategy for both users --referred to as CF-CF region--, and cooperation
is based on DF strategy for one destination and CF for the other --referred to
as DF-CF region--. These results can be seen as a generalization and hence
unification of previous works. An outer-bound on the capacity of the general
BRC is also derived. Capacity results are obtained for the specific cases of
semi-degraded and degraded Gaussian simultaneous relay channels. Rates are
evaluated for Gaussian models where the source must guarantee a minimum amount
of information to both users while additional information is sent to each of
them.Comment: 32 pages, 7 figures, To appear in IEEE Trans. on Information Theor
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