4,583 research outputs found
A Unified Ensemble of Concatenated Convolutional Codes
We introduce a unified ensemble for turbo-like codes (TCs) that contains the
four main classes of TCs: parallel concatenated codes, serially concatenated
codes, hybrid concatenated codes, and braided convolutional codes. We show that
for each of the original classes of TCs, it is possible to find an equivalent
ensemble by proper selection of the design parameters in the unified ensemble.
We also derive the density evolution (DE) equations for this ensemble over the
binary erasure channel. The thresholds obtained from the DE indicate that the
TC ensembles from the unified ensemble have similar asymptotic behavior to the
original TC ensembles
ON TURBO CODES AND OTHER CONCATENATED SCHEMES IN COMMUNICATION SYSTEMS
The advent of turbo codes in 1993 represented a significant step towards realising
the ultimate capacity limit of a communication channel, breaking the link that was
binding very good performance with exponential decoder complexity. Turbo codes
are parallel concatenated convolutional codes, decoded with a suboptimal iterative
algorithm. The complexity of the iterative algorithm increases only linearly with block
length, bringing previously unprecedented performance within practical limits..
This work is a further investigation of turbo codes and other concatenated schemes
such as the multiple parallel concatenation and the serial concatenation. The analysis
of these schemes has two important aspects, their performance under optimal decoding
and the convergence of their iterative, suboptimal decoding algorithm.
The connection between iterative decoding performance and the optimal decoding
performance is analysed with the help of computer simulation by studying the iterative
decoding error events. Methods for good performance interleaver design and code
design are presented and analysed in the same way.
The optimal decoding performance is further investigated by using a novel method
to determine the weight spectra of turbo codes by using the turbo code tree representation,
and the results are compared with the results of the iterative decoder. The
method can also be used for the analysis of multiple parallel concatenated codes, but
is impractical for the serial concatenated codes. Non-optimal, non-iterative decoding
algorithms are presented and compared with the iterative algorithm.
The convergence of the iterative algorithm is investigated by using the Cauchy
criterion. Some insight into the performance of the concatenated schemes under iterative
decoding is found by separating error events into convergent and non-convergent
components. The sensitivity of convergence to the Eb/Ng operating point has been
explored.SateUite Research Centre
Department of Communication and Electronic Engineerin
Spatially Coupled Turbo Codes
In this paper, we introduce the concept of spatially coupled turbo codes
(SC-TCs), as the turbo codes counterpart of spatially coupled low-density
parity-check codes. We describe spatial coupling for both Berrou et al. and
Benedetto et al. parallel and serially concatenated codes. For the binary
erasure channel, we derive the exact density evolution (DE) equations of SC-TCs
by using the method proposed by Kurkoski et al. to compute the decoding erasure
probability of convolutional encoders. Using DE, we then analyze the asymptotic
behavior of SC-TCs. We observe that the belief propagation (BP) threshold of
SC-TCs improves with respect to that of the uncoupled ensemble and approaches
its maximum a posteriori threshold. This phenomenon is especially significant
for serially concatenated codes, whose uncoupled ensemble suffers from a poor
BP threshold.Comment: in Proc. 8th International Symposium on Turbo Codes & Iterative
Information Processing 2014, Bremen, Germany, August 2014. To appear. (The
PCC ensemble is changed with respect to the one in the previous version of
the paper. However, it gives identical thresholds
Spatially Coupled Turbo Codes: Principles and Finite Length Performance
In this paper, we give an overview of spatially coupled turbo codes (SC-TCs),
the spatial coupling of parallel and serially concatenated convolutional codes,
recently introduced by the authors. For presentation purposes, we focus on
spatially coupled serially concatenated codes (SC-SCCs). We review the main
principles of SC-TCs and discuss their exact density evolution (DE) analysis on
the binary erasure channel. We also consider the construction of a family of
rate-compatible SC-SCCs with simple 4-state component encoders. For all
considered code rates, threshold saturation of the belief propagation (BP) to
the maximum a posteriori threshold of the uncoupled ensemble is demonstrated,
and it is shown that the BP threshold approaches the Shannon limit as the
coupling memory increases. Finally we give some simulation results for finite
lengths.Comment: Invited paper, IEEE Int. Symp. Wireless Communications Systems
(ISWCS), Aug. 201
Self-concatenated code design and its application in power-efficient cooperative communications
In this tutorial, we have focused on the design of binary self-concatenated coding schemes with the help of EXtrinsic Information Transfer (EXIT) charts and Union bound analysis. The design methodology of future iteratively decoded self-concatenated aided cooperative communication schemes is presented. In doing so, we will identify the most important milestones in the area of channel coding, concatenated coding schemes and cooperative communication systems till date and suggest future research directions
A new class of parallel data convolutional codes
We propose a new class of parallel data convolutional
codes (PDCCs) in this paper. The PDCC encoders inputs
are composed of an original block of data and its interleaved version.
A novel single self-iterative soft-in/soft-out a posteriori probability
(APP) decoder structure is proposed for the decoding of
the PDCCs. Simulation results are presented to compare the performance
of PDCCs
Near-capacity iterative decoding of binary self-concatenated codes using soft decision demapping and 3-D EXIT charts
In this paper 3-D Extrinsic Information Transfer (EXIT) charts are used to design binary Self-Concatenated Convolutional Codes employing Iterative Decoding (SECCC-ID), exchanging extrinsic information with the soft-decision demapper to approach the channel capacity. Recursive Systematic Convolutional (RSC) codes are selected as constituent codes, an interleaver is used for randomising the extrinsic information exchange of the constituent codes, while a puncturer helps to increase the achievable bandwidth efficiency. The convergence behaviour of the decoder is analysed with the aid of bit-based 3-D EXIT charts, for accurately calculating the operating EbN0 threshold, especially when SP based soft demapper is employed. Finally, we propose an attractive system configuration, which is capable of operating within about 1 dB from the channel capacity
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