A Chase-type algorithm for soft-decision Reed-Solomon decoding on Rayleigh fading channels
ABSTRACT A soft-decision Reed-Solomon decoding algorithm has been proposed by Koetter and Vardy, which provides a significant coding gain by utilizing channel output reliability information. In this paper we present a Chase-type soft-decision algorithm which provides additional gains at the expense of a small increase in complexity. We evaluate the performance of this decoding algorithm on additive white Gaussian noise channel and Rayleigh fading channels. Simulation results show that coding gains on the order of several dB can be achieved on uncorrelated Rayleigh fading channels over traditional hard-decision Reed-Solomon decoding algorithms.
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ABSTRACT: We propose a soft-decision Reed-Solomon (RS) decoding algorithm, which uses the combined approaches of the Chase and the generalized minimum distance (GMD) algorithms and exploits the recursive property of interpolation-based RS decoding algorithms. We evaluate the performance of this Chase- GMD type algorithm on perpendicular magnetic recording systems, and present simulation results that show that we can achieve better performance with fairly short latency and lower decoding complexity than the current state-of-art algorithms.Communications, 2008. ICC '08. IEEE International Conference on; 06/2008
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ABSTRACT: In this paper, we present an algebraic methodology for implementing low-complexity, Chase-type, decoding of Reed-Solomon (RS) codes of length n . In such, a set of 2 <sup>Â¿</sup> test-vectors that are equivalent on all except Â¿ Â¿ n coordinate positions is first produced. The similarity of the test-vectors is utilized to reduce the complexity of interpolation, the process of constructing a set of polynomials that obey constraints imposed by each test-vector. By first considering the equivalent indices, a polynomial common to all test-vectors is constructed. The required set of polynomials is then produced by interpolating the final Â¿ dissimilar indices utilizing a binary-tree structure. In the second decoding step ( factorization ) a candidate message is extracted from each interpolation polynomial such that one may be chosen as the decoded message. Although an expression for the direct evaluation of each candidate message is provided, carrying out this computation for each polynomial is extremely complex. Thus, a novel, reduced-complexity, methodology is also given. Although suboptimal, simulation results affirm that the loss in performance incurred by this procedure is decreasing with increasing code length n , and negligible for long (n > 100) codes. Significant coding gains are shown to be achievable over traditional hard-in hard-out decoding procedures (e.g., Berlekamp-Massey) at an equivalent (and, in some cases, lower) computational complexity. Furthermore, these gains are shown to be similar to the recently proposed soft-in-hard-out algebraic techniques (e.g., Sudan, KoÂ¿tter-Vardy) that bear significantly more complex implementations than the proposed algorithm.IEEE Transactions on Information Theory 04/2010; · 2.65 Impact Factor
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ABSTRACT: Algebraic soft-decision Reed–Solomon (RS) decoding algorithms with improved error-correcting capability and comparable complexity to standard algebraic hard-decision algorithms could be very attractive for possible implementation in the next generation of read channels. In this work, we investigate the performance of a low-complexity Chase (LCC)-type soft-decision RS decoding algorithm, recently proposed by Bellorado and Kavčić, on perpendicular magnetic recording channels for sector-long RS codes of practical interest. Previous results for additive white Gaussian noise channels have shown that for a moderately long high-rate code, the LCC algorithm can achieve a coding gain comparable to the Koetter–Vardy algorithm with much lower complexity. We present a set of numerical results that show that this algorithm provides small coding gains, on the order of a fraction of a dB, with similar complexity to the hard-decision algorithms currently used, and that larger coding gains can be obtained if we use more test patterns, which significantly increases its computational complexity.Journal of Magnetism and Magnetic Materials 11/2008; · 2.00 Impact Factor