215 research outputs found
Noisy Gradient Descent Bit-Flip Decoding for LDPC Codes
A modified Gradient Descent Bit Flipping (GDBF) algorithm is proposed for
decoding Low Density Parity Check (LDPC) codes on the binary-input additive
white Gaussian noise channel. The new algorithm, called Noisy GDBF (NGDBF),
introduces a random perturbation into each symbol metric at each iteration. The
noise perturbation allows the algorithm to escape from undesirable local
maxima, resulting in improved performance. A combination of heuristic
improvements to the algorithm are proposed and evaluated. When the proposed
heuristics are applied, NGDBF performs better than any previously reported GDBF
variant, and comes within 0.5 dB of the belief propagation algorithm for
several tested codes. Unlike other previous GDBF algorithms that provide an
escape from local maxima, the proposed algorithm uses only local, fully
parallelizable operations and does not require computing a global objective
function or a sort over symbol metrics, making it highly efficient in
comparison. The proposed NGDBF algorithm requires channel state information
which must be obtained from a signal to noise ratio (SNR) estimator.
Architectural details are presented for implementing the NGDBF algorithm.
Complexity analysis and optimizations are also discussed.Comment: 16 pages, 22 figures, 2 table
Architectures for soft-decision decoding of non-binary codes
En esta tesis se estudia el dise¿no de decodificadores no-binarios para la correcci'on
de errores en sistemas de comunicaci'on modernos de alta velocidad. El objetivo
es proponer soluciones de baja complejidad para los algoritmos de decodificaci'on
basados en los c'odigos de comprobaci'on de paridad de baja densidad no-binarios
(NB-LDPC) y en los c'odigos Reed-Solomon, con la finalidad de implementar arquitecturas
hardware eficientes.
En la primera parte de la tesis se analizan los cuellos de botella existentes en los
algoritmos y en las arquitecturas de decodificadores NB-LDPC y se proponen soluciones
de baja complejidad y de alta velocidad basadas en el volteo de s'¿mbolos.
En primer lugar, se estudian las soluciones basadas en actualizaci'on por inundaci
'on con el objetivo de obtener la mayor velocidad posible sin tener en cuenta la
ganancia de codificaci'on. Se proponen dos decodificadores diferentes basados en
clipping y t'ecnicas de bloqueo, sin embargo, la frecuencia m'axima est'a limitada
debido a un exceso de cableado. Por este motivo, se exploran algunos m'etodos
para reducir los problemas de rutado en c'odigos NB-LDPC. Como soluci'on se
propone una arquitectura basada en difusi'on parcial para algoritmos de volteo
de s'¿mbolos que mitiga la congesti'on por rutado. Como las soluciones de actualizaci
'on por inundaci'on de mayor velocidad son sub-'optimas desde el punto de
vista de capacidad de correci'on, decidimos dise¿nar soluciones para la actualizaci'on
serie, con el objetivo de alcanzar una mayor velocidad manteniendo la ganancia
de codificaci'on de los algoritmos originales de volteo de s'¿mbolo. Se presentan dos
algoritmos y arquitecturas de actualizaci'on serie, reduciendo el 'area y aumentando
de la velocidad m'axima alcanzable. Por 'ultimo, se generalizan los algoritmos de
volteo de s'¿mbolo y se muestra como algunos casos particulares puede lograr una
ganancia de codificaci'on cercana a los algoritmos Min-sum y Min-max con una
menor complejidad. Tambi'en se propone una arquitectura eficiente, que muestra
que el 'area se reduce a la mitad en comparaci'on con una soluci'on de mapeo directo.
En la segunda parte de la tesis, se comparan algoritmos de decodificaci'on Reed-
Solomon basados en decisi'on blanda, concluyendo que el algoritmo de baja complejidad
Chase (LCC) es la soluci'on m'as eficiente si la alta velocidad es el objetivo principal. Sin embargo, los esquemas LCC se basan en la interpolaci'on, que introduce
algunas limitaciones hardware debido a su complejidad. Con el fin de reducir
la complejidad sin modificar la capacidad de correcci'on, se propone un esquema
de decisi'on blanda para LCC basado en algoritmos de decisi'on dura. Por 'ultimo
se dise¿na una arquitectura eficiente para este nuevo esquemaGarcía Herrero, FM. (2013). Architectures for soft-decision decoding of non-binary codes [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/33753TESISPremiad
An improvement and a fast DSP implementation of the bit flipping algorithms for low density parity check decoder
For low density parity check (LDPC) decoding, hard-decision algorithms are sometimes more suitable than the soft-decision ones. Particularly in the high throughput and high speed applications. However, there exists a considerable gap in performances between these two classes of algorithms in favor of soft-decision algorithms. In order to reduce this gap, in this work we introduce two new improved versions of the hard-decision algorithms, the adaptative gradient descent bit-flipping (AGDBF) and adaptative reliability ratio weighted GDBF (ARRWGDBF). An adaptative weighting and correction factor is introduced in each case to improve the performances of the two algorithms allowing an important gain of bit error rate. As a second contribution of this work a real time implementation of the proposed solutions on a digital signal processors (DSP) is performed in order to optimize and improve the performance of these new approchs. The results of numerical simulations and DSP implementation reveal a faster convergence with a low processing time and a reduction in consumed memory resources when compared to soft-decision algorithms. For the irregular LDPC code, our approachs achieves gains of 0.25 and 0.15 dB respectively for the AGDBF and ARRWGDBF algorithms
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Low-complexity high-speed VLSI design of low-density parity-check decoders
Low-Density Parity-check (LDPC) codes have attracted considerable attention due to their capacity approaching performance over AWGN channel and highly parallelizable decoding schemes. They have been considered in a variety of industry standards for the next generation communication systems. In general, LDPC codes achieve outstanding performance with large codeword lengths (e.g., N>1000 bits), which lead to a linear increase of the size of memory for storing all the soft messages in LDPC decoding. In the next generation communication systems, the target data rates range from a few hundred Mbit/sec to several Gbit/sec. To achieve those very high decoding throughput, a large amount of computation units are required, which will significantly increase the hardware cost and power consumption of LDPC decoders. LDPC codes are decoded using iterative decoding algorithms. The decoding latency and power consumption are linearly proportional to the number of decoding iterations. A decoding approach with fast convergence speed is highly desired in practice.
This thesis considers various VLSI design issues of LDPC decoder and develops efficient approaches for reducing memory requirement, low complexity implementation, and high speed decoding of LDPC codes. We propose a memory efficient partially parallel decoder architecture suited for quasi-cyclic LDPC (QC-LDPC) codes using Min-Sum decoding algorithm. We develop an efficient architecture for general permutation matrix based LDPC codes. We have explored various approaches to linearly increase the decoding throughput with a small amount of hardware overhead. We develop a multi-Gbit/sec LDPC decoder architecture for QC-LDPC codes and prototype an enhanced partially parallel decoder architecture for a Euclidian geometry based LDPC code on FPGA. We propose an early stopping scheme and an extended layered decoding method to reduce the number of decoding iterations for undecodable and decodable sequence received from channel. We also propose a low-complexity optimized 2-bit decoding approach which requires comparable implementation complexity to weighted bit flipping based algorithms but has much better decoding performance and faster convergence speed
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