88 research outputs found

    Soft-Decision Low-Complexity Chase Decoders for the RS(255,239) Code

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    [EN] In this work, we present a new architecture for soft-decision Reed-Solomon (RS) Low-Complexity Chase (LCC) decoding. The proposed architecture is scalable and can be used for a high number of test vectors. We propose a novel Multiplicity Assignment stage that sorts and stores only the location of the errors inside the symbols and the powers of a that identify the positions of the symbols in the frame. Novel schematics for the Syndrome Update and Symbol Modification blocks that are adapted to the proposed sorting stage are also presented. We also propose novel solutions for the problems that arise when a high number of test vectors is processed. We implemented three decoders: a h = 4 LCC decoder and two decoders that only decode 31 and 60 test vectors of true h = 5 and h = 6 LCC decoders, respectively. For example, our h = 4 decoder requires 29% less look-up tables in Virtex-V Field Programmable Gate Array (FPGA) devices than the best soft-decision RS decoder published to date, while has a 0.07 dB coding gain over that decoder.This research was funded by the Spanish Ministerio de Economia y Competitividad and FEDER grant number TEC2015-70858-C2-2-RTorres Carot, V.; Valls Coquillat, J.; Canet Subiela, MJ.; GarcĂ­a Herrero, FM. (2019). Soft-Decision Low-Complexity Chase Decoders for the RS(255,239) Code. Electronics. 8(1):1-13. https://doi.org/10.3390/electronics8010010S11381Cideciyan, R., Gustlin, M., Li, M., Wang, J., & Wang, Z. (2013). Next generation backplane and copper cable challenges. IEEE Communications Magazine, 51(12), 130-136. doi:10.1109/mcom.2013.6685768Koetter, R., & Vardy, A. (2003). Algebraic soft-decision decoding of reed-solomon codes. IEEE Transactions on Information Theory, 49(11), 2809-2825. doi:10.1109/tit.2003.819332Sudan, M. (1997). Decoding of Reed Solomon Codes beyond the Error-Correction Bound. Journal of Complexity, 13(1), 180-193. doi:10.1006/jcom.1997.0439Guruswami, V., & Sudan, M. (1999). Improved decoding of Reed-Solomon and algebraic-geometry codes. IEEE Transactions on Information Theory, 45(6), 1757-1767. doi:10.1109/18.782097Jiang, J., & Narayanan, K. R. (2008). Algebraic Soft-Decision Decoding of Reed–Solomon Codes Using Bit-Level Soft Information. IEEE Transactions on Information Theory, 54(9), 3907-3928. doi:10.1109/tit.2008.928238Jiangli Zhu, Xinmiao Zhang, & Zhongfeng Wang. (2009). Backward Interpolation Architecture for Algebraic Soft-Decision Reed–Solomon Decoding. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 17(11), 1602-1615. doi:10.1109/tvlsi.2008.2005575Jiangli Zhu, & Xinmiao Zhang. (2008). Efficient VLSI Architecture for Soft-Decision Decoding of Reed–Solomon Codes. IEEE Transactions on Circuits and Systems I: Regular Papers, 55(10), 3050-3062. doi:10.1109/tcsi.2008.923169Zhongfeng Wang, & Jun Ma. (2006). High-Speed Interpolation Architecture for Soft-Decision Decoding of Reed–Solomon Codes. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 14(9), 937-950. doi:10.1109/tvlsi.2006.884046Zhang, X. (2006). Reduced Complexity Interpolation Architecture for Soft-Decision Reed–Solomon Decoding. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 14(10), 1156-1161. doi:10.1109/tvlsi.2006.884177Xinmiao Zhang, & Parhi, K. K. (2005). Fast factorization architecture in soft-decision Reed-Solomon decoding. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 13(4), 413-426. doi:10.1109/tvlsi.2004.842914Bellorado, J., & Kavcic, A. (2010). Low-Complexity Soft-Decoding Algorithms for Reed–Solomon Codes—Part I: An Algebraic Soft-In Hard-Out Chase Decoder. IEEE Transactions on Information Theory, 56(3), 945-959. doi:10.1109/tit.2009.2039073GarcĂ­a-Herrero, F., Valls, J., & Meher, P. K. (2011). High-Speed RS(255, 239) Decoder Based on LCC Decoding. Circuits, Systems, and Signal Processing, 30(6), 1643-1669. doi:10.1007/s00034-011-9327-4Zhang, W., Wang, H., & Pan, B. (2013). Reduced-Complexity LCC Reed–Solomon Decoder Based on Unified Syndrome Computation. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 21(5), 974-978. doi:10.1109/tvlsi.2012.2197030Peng, X., Zhang, W., Ji, W., Liang, Z., & Liu, Y. (2015). Reduced-Complexity Multiplicity Assignment Algorithm and Architecture for Low-Complexity Chase Decoder of Reed-Solomon Codes. IEEE Communications Letters, 19(11), 1865-1868. doi:10.1109/lcomm.2015.2477495Lin, Y.-M., Hsu, C.-H., Chang, H.-C., & Lee, C.-Y. (2014). A 2.56 Gb/s Soft RS (255, 239) Decoder Chip for Optical Communication Systems. IEEE Transactions on Circuits and Systems I: Regular Papers, 61(7), 2110-2118. doi:10.1109/tcsi.2014.2298282Wu, Y. (2015). New Scalable Decoder Architectures for Reed–Solomon Codes. IEEE Transactions on Communications, 63(8), 2741-2761. doi:10.1109/tcomm.2015.2445759Garcia-Herrero, F., Canet, M. J., Valls, J., & Meher, P. K. (2012). High-Throughput Interpolator Architecture for Low-Complexity Chase Decoding of RS Codes. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 20(3), 568-573. doi:10.1109/tvlsi.2010.210396

    Architectures for soft-decision decoding of non-binary codes

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    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

    Coordinated design of coding and modulation systems

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    The joint optimization of the coding and modulation systems employed in telemetry systems was investigated. Emphasis was placed on formulating inner and outer coding standards used by the Goddard Spaceflight Center. Convolutional codes were found that are nearly optimum for use with Viterbi decoding in the inner coding of concatenated coding systems. A convolutional code, the unit-memory code, was discovered and is ideal for inner system usage because of its byte-oriented structure. Simulations of sequential decoding on the deep-space channel were carried out to compare directly various convolutional codes that are proposed for use in deep-space systems

    Perturbed Adaptive Belief Propagation Decoding for High-Density Parity-Check Codes

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    Algebraic codes such as BCH code are receiving renewed interest as their short block lengths and low/no error floors make them attractive for ultra-reliable low-latency communications (URLLC) in 5G wireless networks. This article aims at enhancing the traditional adaptive belief propagation (ABP) decoding, which is a soft-in-soft-out (SISO) decoding for high-density parity-check (HDPC) algebraic codes, such as Reed-Solomon (RS) codes, Bose-Chaudhuri-Hocquenghem (BCH) codes, and product codes. The key idea of traditional ABP is to sparsify certain columns of the parity-check matrix corresponding to the least reliable bits with small log-likelihood-ratio (LLR) values. This sparsification strategy may not be optimal when some bits have large LLR magnitudes but wrong signs. Motivated by this observation, we propose a Perturbed ABP (P-ABP) to incorporate a small number of unstable bits with large LLRs into the sparsification operation of the parity-check matrix. In addition, we propose to apply partial layered scheduling or hybrid dynamic scheduling to further enhance the performance of P-ABP. Simulation results show that our proposed decoding algorithms lead to improved error correction performances and faster convergence rates than the prior-art ABP variants

    New Decoding of Reed-Solomon Codes Based on FFT and Modular Approach

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    Decoding algorithms for Reed--Solomon (RS) codes are of great interest for both practical and theoretical reasons. In this paper, an efficient algorithm, called the modular approach (MA), is devised for solving the Welch--Berlekamp (WB) key equation. By taking the MA as the key equation solver, we propose a new decoding algorithm for systematic RS codes. For (n,k)(n,k) RS codes, where nn is the code length and kk is the code dimension, the proposed decoding algorithm has both the best asymptotic computational complexity O(nlog⁡(n−k)+(n−k)log⁡2(n−k))O(n\log(n-k) + (n-k)\log^2(n-k)) and the smallest constant factor achieved to date. By comparing the number of field operations required, we show that when decoding practical RS codes, the new algorithm is significantly superior to the existing methods in terms of computational complexity. When decoding the (4096,3584)(4096, 3584) RS code defined over F212\mathbb{F}_{2^{12}}, the new algorithm is 10 times faster than a conventional syndrome-based method. Furthermore, the new algorithm has a regular architecture and is thus suitable for hardware implementation

    Polar coding for optical wireless communication

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    High Performance Decoder Architectures for Error Correction Codes

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    Due to the rapid development of the information industry, modern communication and storage systems require much higher data rates and reliability to server various demanding applications. However, these systems suffer from noises from the practical channels. Various error correction codes (ECCs), such as Reed-Solomon (RS) codes, convolutional codes, turbo codes, Low-Density Parity-Check (LDPC) codes and so on, have been adopted in lots of current standards. With the increasing data rate, the research of more advanced ECCs and the corresponding efficient decoders will never stop.Binary LDPC codes have been adopted in lots of modern communication and storage applications due their superior error performance and efficient hardware decoder implementations. Non-binary LDPC (NB-LDPC) codes are an important extension of traditional binary LDPC codes. Compared with its binary counterpart, NB-LDPC codes show better error performance under short to moderate block lengths and higher order modulations. Moreover, NB-LDPC codes have lower error floor than binary LDPC codes. In spite of the excellent error performance, it is hard for current communication and storage systems to adopt NB-LDPC codes due to complex decoding algorithms and decoder architectures. In terms of hardware implementation, current NB-LDPC decoders need much larger area and achieve much lower data throughput.Besides the recently proposed NB-LDPC codes, polar codes, discovered by Ar{\i}kan, appear as a very promising candidate for future communication and storage systems. Polar codes are considered as a major breakthrough in recent coding theory society. Polar codes are proved to be capacity achieving codes over binary input symmetric memoryless channels. Besides, polar codes can be decoded by the successive cancelation (SC) algorithm with of complexity of O(Nlog⁥2N)\mathcal{O}(N\log_2 N), where NN is the block length. The main sticking point of polar codes to date is that their error performance under short to moderate block lengths is inferior compared with LDPC codes or turbo codes. The list decoding technique can be used to improve the error performance of SC algorithms at the cost higher computational and memory complexities. Besides, the hardware implementation of current SC based decoders suffer from long decoding latency which is unsuitable for modern high speed communications.ECCs also find their applications in improving the reliability of network coding. Random linear network coding is an efficient technique for disseminating information in networks, but it is highly susceptible to errors. K\ {o}tter-Kschischang (KK) codes and Mahdavifar-Vardy (MV) codes are two important families of subspace codes that provide error control in noncoherent random linear network coding. List decoding has been used to decode MV codes beyond half distance. Existing hardware implementations of the rank metric decoder for KK codes suffer from limited throughput, long latency and high area complexity. The interpolation-based list decoding algorithm for MV codes still has high computational complexity, and its feasibility for hardware implementations has not been investigated.In this exam, we present efficient decoding algorithms and hardware decoder architectures for NB-LDPC codes, polar codes, KK and MV codes. For NB-LDPC codes, an efficient shuffled decoder architecture is presented to reduce the number of average iterations and improve the throughput. Besides, a fully parallel decoder architecture for NB-LDPC codes with short or moderate block lengths is also presented. Our fully parallel decoder architecture achieves much higher throughput and area efficiency compared with the state-of-art NB-LDPC decoders. For polar codes, a memory efficient list decoder architecture is first presented. Based on our reduced latency list decoding algorithm for polar codes, a high throughput list decoder architecture is also presented. At last, we present efficient decoder architectures for both KK and MV codes
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