5 research outputs found
Reduced-Complexity Decoder of Long Reed-Solomon Codes Based on Composite Cyclotomic Fourier Transforms
Long Reed-Solomon (RS) codes are desirable for digital communication and
storage systems due to their improved error performance, but the high
computational complexity of their decoders is a key obstacle to their adoption
in practice. As discrete Fourier transforms (DFTs) can evaluate a polynomial at
multiple points, efficient DFT algorithms are promising in reducing the
computational complexities of syndrome based decoders for long RS codes. In
this paper, we first propose partial composite cyclotomic Fourier transforms
(CCFTs) and then devise syndrome based decoders for long RS codes over large
finite fields based on partial CCFTs. The new decoders based on partial CCFTs
achieve a significant saving of computational complexities for long RS codes.
Since partial CCFTs have modular and regular structures, the new decoders are
suitable for hardware implementations. To further verify and demonstrate the
advantages of partial CCFTs, we implement in hardware the syndrome computation
block for a shortened RS code over GF. In comparison
to previous results based on Horner's rule, our hardware implementation not
only has a smaller gate count, but also achieves much higher throughputs.Comment: 7 pages, 1 figur
Complexity Analysis of Reed-Solomon Decoding over GF(2^m) Without Using Syndromes
For the majority of the applications of Reed-Solomon (RS) codes, hard
decision decoding is based on syndromes. Recently, there has been renewed
interest in decoding RS codes without using syndromes. In this paper, we
investigate the complexity of syndromeless decoding for RS codes, and compare
it to that of syndrome-based decoding. Aiming to provide guidelines to
practical applications, our complexity analysis differs in several aspects from
existing asymptotic complexity analysis, which is typically based on
multiplicative fast Fourier transform (FFT) techniques and is usually in big O
notation. First, we focus on RS codes over characteristic-2 fields, over which
some multiplicative FFT techniques are not applicable. Secondly, due to
moderate block lengths of RS codes in practice, our analysis is complete since
all terms in the complexities are accounted for. Finally, in addition to fast
implementation using additive FFT techniques, we also consider direct
implementation, which is still relevant for RS codes with moderate lengths.
Comparing the complexities of both syndromeless and syndrome-based decoding
algorithms based on direct and fast implementations, we show that syndromeless
decoding algorithms have higher complexities than syndrome-based ones for high
rate RS codes regardless of the implementation. Both errors-only and
errors-and-erasures decoding are considered in this paper. We also derive
tighter bounds on the complexities of fast polynomial multiplications based on
Cantor's approach and the fast extended Euclidean algorithm.Comment: 11 pages, submitted to EURASIP Journal on Wireless Communications and
Networkin
Channel coding for network communication: an information theoretic perspective
2011 Fall.Includes bibliographical references.Channel coding helps a communication system to combat noise and interference by adding "redundancy" to the source message. Theoretical fundamentals of channel coding in point-to-point systems have been intensively studied in the research area of information theory, which was proposed by Claude Shannon in his celebrated work in 1948. A set of landmark results have been developed to characterize the performance limitations in terms of the rate and the reliability tradeoff bounds. However, unlike its success in point-to-point systems, information theory has not yielded as rich results in network communication, which has been a key research focus over the past two decades. Due to the limitations posed by some of the key assumptions in classical information theory, network information theory is far from being mature and complete. For example, the classical information theoretic model assumes that communication parameters such as the information rate should be jointly determined by all transmitters and receivers. Communication should be carried out continuously over a long time such that the overhead of communication coordination becomes negligible. The communication channel should be stationary in order for the coding scheme to transform the channel noise randomness into deterministic statistics. These assumptions are valid in a point-to-point system, but they do not permit an extensive application of channel coding in network systems because they have essentially ignored the dynamic nature of network communication. Network systems deal with bursty message transmissions between highly dynamic users. For various reasons, joint determination of key communication parameters before message transmission is often infeasible or expensive. Communication channels can often be non-stationary due to the dynamic communication interference generated by the network users. The objective of this work is to extend information theory toward network communication scenarios. We develop new channel coding results, in terms of the communication rate and error performance tradeoff, for several non-classical communication models, in which key assumptions made in classical channel coding are dropped or revised