999 research outputs found
Deriving Good LDPC Convolutional Codes from LDPC Block Codes
Low-density parity-check (LDPC) convolutional codes are capable of achieving
excellent performance with low encoding and decoding complexity. In this paper
we discuss several graph-cover-based methods for deriving families of
time-invariant and time-varying LDPC convolutional codes from LDPC block codes
and show how earlier proposed LDPC convolutional code constructions can be
presented within this framework. Some of the constructed convolutional codes
significantly outperform the underlying LDPC block codes. We investigate some
possible reasons for this "convolutional gain," and we also discuss the ---
mostly moderate --- decoder cost increase that is incurred by going from LDPC
block to LDPC convolutional codes.Comment: Submitted to IEEE Transactions on Information Theory, April 2010;
revised August 2010, revised November 2010 (essentially final version).
(Besides many small changes, the first and second revised versions contain
corrected entries in Tables I and II.
Efficient Termination of Spatially-Coupled Codes
Spatially-coupled low-density parity-check codes attract much attention due
to their capacity-achieving performance and a memory-efficient sliding-window
decoding algorithm. On the other hand, the encoder needs to solve large linear
equations to terminate the encoding process. In this paper, we propose modified
spatially-coupled codes. The modified (\dl,\dr,L) codes have less rate-loss,
i.e., higher coding rate, and have the same threshold as (\dl,\dr,L) codes
and are efficiently terminable by using an accumulator
A 2.0 Gb/s Throughput Decoder for QC-LDPC Convolutional Codes
This paper propose a decoder architecture for low-density parity-check
convolutional code (LDPCCC). Specifically, the LDPCCC is derived from a
quasi-cyclic (QC) LDPC block code. By making use of the quasi-cyclic structure,
the proposed LDPCCC decoder adopts a dynamic message storage in the memory and
uses a simple address controller. The decoder efficiently combines the memories
in the pipelining processors into a large memory block so as to take advantage
of the data-width of the embedded memory in a modern field-programmable gate
array (FPGA). A rate-5/6 QC-LDPCCC has been implemented on an Altera Stratix
FPGA. It achieves up to 2.0 Gb/s throughput with a clock frequency of 100 MHz.
Moreover, the decoder displays an excellent error performance of lower than
at a bit-energy-to-noise-power-spectral-density ratio () of
3.55 dB.Comment: accepted to IEEE Transactions on Circuits and Systems
Short Block-length Codes for Ultra-Reliable Low-Latency Communications
This paper reviews the state of the art channel coding techniques for
ultra-reliable low latency communication (URLLC). The stringent requirements of
URLLC services, such as ultra-high reliability and low latency, have made it
the most challenging feature of the fifth generation (5G) mobile systems. The
problem is even more challenging for the services beyond the 5G promise, such
as tele-surgery and factory automation, which require latencies less than 1ms
and failure rate as low as . The very low latency requirements of
URLLC do not allow traditional approaches such as re-transmission to be used to
increase the reliability. On the other hand, to guarantee the delay
requirements, the block length needs to be small, so conventional channel
codes, originally designed and optimised for moderate-to-long block-lengths,
show notable deficiencies for short blocks. This paper provides an overview on
channel coding techniques for short block lengths and compares them in terms of
performance and complexity. Several important research directions are
identified and discussed in more detail with several possible solutions.Comment: Accepted for publication in IEEE Communications Magazin
Spatially Coupled LDPC Codes Constructed from Protographs
In this paper, we construct protograph-based spatially coupled low-density
parity-check (SC-LDPC) codes by coupling together a series of L disjoint, or
uncoupled, LDPC code Tanner graphs into a single coupled chain. By varying L,
we obtain a flexible family of code ensembles with varying rates and frame
lengths that can share the same encoding and decoding architecture for
arbitrary L. We demonstrate that the resulting codes combine the best features
of optimized irregular and regular codes in one design: capacity approaching
iterative belief propagation (BP) decoding thresholds and linear growth of
minimum distance with block length. In particular, we show that, for
sufficiently large L, the BP thresholds on both the binary erasure channel
(BEC) and the binary-input additive white Gaussian noise channel (AWGNC)
saturate to a particular value significantly better than the BP decoding
threshold and numerically indistinguishable from the optimal maximum
a-posteriori (MAP) decoding threshold of the uncoupled LDPC code. When all
variable nodes in the coupled chain have degree greater than two,
asymptotically the error probability converges at least doubly exponentially
with decoding iterations and we obtain sequences of asymptotically good LDPC
codes with fast convergence rates and BP thresholds close to the Shannon limit.
Further, the gap to capacity decreases as the density of the graph increases,
opening up a new way to construct capacity achieving codes on memoryless
binary-input symmetric-output (MBS) channels with low-complexity BP decoding.Comment: Submitted to the IEEE Transactions on Information Theor
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