529 research outputs found
Capacity-achieving ensembles for the binary erasure channel with bounded complexity
We present two sequences of ensembles of non-systematic irregular
repeat-accumulate codes which asymptotically (as their block length tends to
infinity) achieve capacity on the binary erasure channel (BEC) with bounded
complexity per information bit. This is in contrast to all previous
constructions of capacity-achieving sequences of ensembles whose complexity
grows at least like the log of the inverse of the gap (in rate) to capacity.
The new bounded complexity result is achieved by puncturing bits, and allowing
in this way a sufficient number of state nodes in the Tanner graph representing
the codes. We also derive an information-theoretic lower bound on the decoding
complexity of randomly punctured codes on graphs. The bound holds for every
memoryless binary-input output-symmetric channel and is refined for the BEC.Comment: 47 pages, 9 figures. Submitted to IEEE Transactions on Information
Theor
Efficient Near Maximum-Likelihood Efficient Near Maximum-Likelihood Reliability-Based Decoding for Short LDPC Codes
In this paper, we propose an efficient decoding algorithm for short
low-density parity check (LDPC) codes by carefully combining the belief
propagation (BP) decoding and order statistic decoding (OSD) algorithms.
Specifically, a modified BP (mBP) algorithm is applied for a certain number of
iterations prior to OSD to enhance the reliability of the received message,
where an offset parameter is utilized in mBP to control the weight of the
extrinsic information in message passing. By carefully selecting the offset
parameter and the number of mBP iterations, the number of errors in the most
reliable positions (MRPs) in OSD can be reduced, thereby significantly
improving the overall decoding performance of error rate and complexity.
Simulation results show that the proposed algorithm can approach the
maximum-likelihood decoding (MLD) for short LDPC codes with only a slight
increase in complexity compared to BP and a significant decrease compared to
OSD. Specifically, the order-(m-1) decoding of the proposed algorithm can
achieve the performance of the order-m OSD
Modeling and Energy Optimization of LDPC Decoder Circuits with Timing Violations
This paper proposes a "quasi-synchronous" design approach for signal
processing circuits, in which timing violations are permitted, but without the
need for a hardware compensation mechanism. The case of a low-density
parity-check (LDPC) decoder is studied, and a method for accurately modeling
the effect of timing violations at a high level of abstraction is presented.
The error-correction performance of code ensembles is then evaluated using
density evolution while taking into account the effect of timing faults.
Following this, several quasi-synchronous LDPC decoder circuits based on the
offset min-sum algorithm are optimized, providing a 23%-40% reduction in energy
consumption or energy-delay product, while achieving the same performance and
occupying the same area as conventional synchronous circuits.Comment: To appear in IEEE Transactions on Communication
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