Iterative Algebraic Soft-Decision List Decoding of Reed-Solomon Codes

In this paper, we present an iterative soft-decision decoding algorithm for Reed-Solomon codes offering both complexity and performance advantages over previously known decoding algorithms. Our algorithm is a list decoding algorithm which combines two powerful soft decision decoding techniques which were previously regarded in the literature as competitive, namely, the Koetter-Vardy algebraic soft-decision decoding algorithm and belief-propagation based on adaptive parity check matrices, recently proposed by Jiang and Narayanan. Building on the Jiang-Narayanan algorithm, we present a belief-propagation based algorithm with a significant reduction in computational complexity. We introduce the concept of using a belief-propagation based decoder to enhance the soft-input information prior to decoding with an algebraic soft-decision decoder. Our algorithm can also be viewed as an interpolation multiplicity assignment scheme for algebraic soft-decision decoding of Reed-Solomon codes.Comment: Submitted to IEEE for publication in Jan 200

Error-correction coding for high-density magnetic recording channels.

Finally, a promising algorithm which combines RS decoding algorithm with LDPC decoding algorithm together is investigated, and a reduced-complexity modification has been proposed, which not only improves the decoding performance largely, but also guarantees a good performance in high signal-to-noise ratio (SNR), in which area an error floor is experienced by LDPC codes.The soft-decision RS decoding algorithms and their performance on magnetic recording channels have been researched, and the algorithm implementation and hardware architecture issues have been discussed. Several novel variations of KV algorithm such as soft Chase algorithm, re-encoded Chase algorithm and forward recursive algorithm have been proposed. And the performance of nested codes using RS and LDPC codes as component codes have been investigated for bursty noise magnetic recording channels.Future high density magnetic recoding channels (MRCs) are subject to more noise contamination and intersymbol interference, which make the error-correction codes (ECCs) become more important. Recent research of replacement of current Reed-Solomon (RS)-coded ECC systems with low-density parity-check (LDPC)-coded ECC systems obtains a lot of research attention due to the large decoding gain for LDPC-coded systems with random noise. In this dissertation, systems aim to maintain the RS-coded system using recent proposed soft-decision RS decoding techniques are investigated and the improved performance is presented

Advanced channel coding techniques using bit-level soft information

In this dissertation, advanced channel decoding techniques based on bit-level soft information are studied. Two main approaches are proposed: bit-level probabilistic iterative decoding and bit-level algebraic soft-decision (list) decoding (ASD). In the first part of the dissertation, we first study iterative decoding for high density parity check (HDPC) codes. An iterative decoding algorithm, which uses the sum product algorithm (SPA) in conjunction with a binary parity check matrix adapted in each decoding iteration according to the bit-level reliabilities is proposed. In contrast to the common belief that iterative decoding is not suitable for HDPC codes, this bit-level reliability based adaptation procedure is critical to the conver-gence behavior of iterative decoding for HDPC codes and it significantly improves the iterative decoding performance of Reed-Solomon (RS) codes, whose parity check matrices are in general not sparse. We also present another iterative decoding scheme for cyclic codes by randomly shifting the bit-level reliability values in each iteration. The random shift based adaptation can also prevent iterative decoding from getting stuck with a significant complexity reduction compared with the reliability based parity check matrix adaptation and still provides reasonable good performance for short-length cyclic codes. In the second part of the dissertation, we investigate ASD for RS codes using bit-level soft information. In particular, we show that by carefully incorporating bit¬level soft information in the multiplicity assignment and the interpolation step, ASD can significantly outperform conventional hard decision decoding (HDD) for RS codes with a very small amount of complexity, even though the kernel of ASD is operating at the symbol-level. More importantly, the performance of the proposed bit-level ASD can be tightly upper bounded for practical high rate RS codes, which is in general not possible for other popular ASD schemes. Bit-level soft-decision decoding (SDD) serves as an efficient way to exploit the potential gain of many classical codes, and also facilitates the corresponding per-formance analysis. The proposed bit-level SDD schemes are potential and feasible alternatives to conventional symbol-level HDD schemes in many communication sys-tems

The hybrid list decoding and Chase-like algorithm of Reed-Solomon codes.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, 2005Reed-Solomon (RS) codes are powerful error-correcting codes that can be found in a wide variety of digital communications and digital data-storage systems. Classical hard decoder of RS code can correct t = (dmin -1) /2 errors where dmin = (n - k+ 1) is the minimum distance of the codeword, n is the length of codeword and k is the dimension of codeword. Maximum likelihood decoding (MLD) performs better than the classical decoding and therefore how to approach the performance of the MLD with less complexity is a subject which has been researched extensively. Applying the bit reliability obtained from channel to the conventional decoding algorithm is always an efficient technique to approach the performance of MLD, although the exponential increase of complexity is always concomitant. It is definite that more enhancement of performance can be achieved if we apply the bit reliability to enhanced algebraic decoding algorithm that is more powerful than conventional decoding algorithm. In 1997 Madhu Sudan, building on previous work of Welch-Berlekamp, and others, discovered a polynomial-time algorithm for decoding low-rate Reed- Solomon codes beyond the classical error-correcting bound t = (dmin -1) /2. Two years later Guruswami and Sudan published a significantly improved version of Sudan's algorithm (GS), but these papers did not focus on devising practical implementation. The other authors, Kotter, Roth and Ruckenstein, were able to find realizations for the key steps in the GS algorithm, thus making the GS algorithm a practical instrument in transmission systems. The Gross list algorithm, which is a simplified one with less decoding complexity realized by a reencoding scheme, is also taken into account in this dissertation. The fundamental idea of the GS algorithm is to take advantage of an interpolation step to get an interpolation polynomial produced by support symbols, received symbols and their corresponding multiplicities. After that the GS algorithm implements a factorization step to find the roots of the interpolation polynomial. After comparing the reliability of these codewords which are from the output of factorization, the GS algorithm outputs the most likely one. The support set, received set and multiplicity set are created by Koetter Vardy (KV) front end algorithm. In the GS list decoding algorithm, the number of errors that can be corrected increases to tcs = n - 1 - lJ (k - 1) n J. It is easy to show that the GS list decoding algorithm is capable of correcting more errors than a conventional decoding algorithm. In this dissertation, we present two hybrid list decoding and Chase-like algorithms. We apply the Chase algorithms to the KV soft-decision front end. Consequently, we are able to provide a more reliable input to the KV list algorithm. In the application of Chase-like algorithm, we take two conditions into consideration, so that the floor cannot occur and more coding gains are possible. With an increase of the bits that are chosen by the Chase algorithm, the complexity of the hybrid algorithm increases exponentially. To solve this problem an adaptive algorithm is applied to the hybrid algorithm based on the fact that as signal-to-noise ratio (SNR) increases the received bits are more reliable, and not every received sequence needs to create the fixed number of test error patterns by the Chase algorithm. We set a threshold according to the given SNR and utilize it to finally decide which unreliable bits are picked up by Chase algorithm. However, the performance of the adaptive hybrid algorithm at high SNRs decreases as the complexity decreases. It means that the adaptive algorithm is not a sufficient mechanism for eliminating the redundant test error patterns. The performance of the adaptive hybrid algorithm at high SNRs motivates us to find out another way to reduce the complexity without loss of performance. We would consider the two following problems before dealing with the problem on hand. One problem is: can we find a terminative condition to decide which generated candidate codeword is the most likely codeword for received sequence before all candidates of received set are tested? Another one is: can we eliminate the test error patterns that cannot create more likely codewords than the generated codewords? In our final algorithm, an optimality lemma coming from the Kaneko algorithm is applied to solve the first problem and the second problem is solved by a ruling out scheme for the reduced list decoding algorithm. The Gross list algorithm is also applied in our final hybrid algorithm. After the two problems have been solved, the final hybrid algorithm has performance comparable with the hybrid algorithm combined the KV list decoding algorithm and the Chase algorithm but much less complexity at high SNRs

Physical layer forward error correcetion in DVB-S2 networks.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2012.The rapid growth of wireless systems has shown little sign of ceasing, due to increased consumer demand for reliable interactive services. A key component of the development has centered on satellite networks, which allows provision of services in scenarios where terrestrial systems are not viable. The Digital Video Broadcasting-Satellite Second Generation (DVB-S2) standard was developed for use in satellite broadcast applications, the foremost being video broadcasting. Inherent to DVB-S2 is a powerful forward error correction (FEC) module, present in both the Physical and Data Link Layer. Improving the error correcting capability of the FEC is a natural advent in improving the quality of service of the protocol. This is more crucial in real time satellite video broadcast where retransmission of data is not viable, due to high latency. The Physical Layer error correcting capability is implemented in the form of a concatenated BCH-LDPC code. The DVB-S2 standard does not define the decoding structure for the receiver system however many powerful decoding systems have been presented in the literature; the Belief Propagation-Chase concatenated decoder being chief amongst them. The decoder utilizes the concept of soft information transfer between the Chase and Belief Propagation (BP) decoders to provide improved error correcting capability above that of the component decoders. The following dissertation is motivated by the physical layer (PL) FEC scheme, focused on the concatenated Chase-BP decoder. The aim is to generate results based on the BP-Chase decoder in a satellite channel as well as improve the error correcting capability. The BP-Chase decoder has shown to be very powerful however the current literature provides performance results only in AWGN channels. The AWGN channel however is not an accurate representation of a land-mobile satellite (LMS) channel; it does not consider the effect of shadowing, which is prevalent in satellite systems. The development of Markov chain models have allowed for better description of the characteristics of the LMS channel. The outcome being the selection of a Ku band LMS channel model. The selected LMS channel model is composed of 3 states, each generating a different degree of shadowing. The PL system has been simulated using the LMS channel and BP-Chase receiver to provide a more accurate representation of performance of a DVB-S2 network. The effect of shadowing has shown to reduce coding performance by approximately 4dB, measured over several code lengths and decoders, when compared with AWGN performance results. The second body of work aims to improve the error correcting capability of the BP-Chase decoder, concentrating on improving the LDPC decoding module performance. The LDPC system is the basis for the powerful error correcting ability of the concatenated scheme. In attempting to improve the LDPC decoder a reciprocal improvement is expected in the overall decoding performance of the concatenated decoder. There have been several schemes presented which improve BP performance. The BP-Ordered statistics decoder (OSD) was selected through a process of literary review; a novel decoding structure is presented incorporating the BP-OSD decoder into the BP-Chase structure. The result of which is the BP-OSD-Chase decoder. The decoder contains two stages of concatenation; the first stage implements the BPOSD algorithm which decodes the LDPC code and the second stage decodes the BCH code using the Chase algorithm. Simulation results of the novel decoder implementation in the DVBS2 PL show a coding gain of 0.45dB and 0.15dB versus the BP and BP-Chase decoders respectively, across both the AWGN and LMS channel

Coded cooperative diversity with low complexity encoding and decoding algorithms.

One of the main concerns in designing the wireless communication systems is to provide sufficiently large data rates while considering the different aspects of the implementation complexity that is often constrained by limited battery power and signal processing capability of the devices. Thus, in this thesis, a low complexity encoding and decoding algorithms are investigated for systems with the transmission diversity, particularly the receiver diversity and the cooperative diversity. Design guidelines for such systems are provided to provide a good trade-off between the implementation complexity and the performance. The order statistics based list decoding techniques for linear binary block codes of small to medium block length are investigated to reduce the complexity of coded systems. The original order statistics decoding (OSD) is generalized by assuming segmentation of the most reliable independent positions of the received bits. The segmentation is shown to overcome several drawbacks of the original order statistics decoding. The complexity of the OSD is further reduced by assuming a partial ordering of the received bits in order to avoid the highly complex Gauss elimination. The bit error rate performance and the decoding complexity trade-off of the proposed decoding algorithms are studied by computer simulations. Numerical examples show that, in some cases, the proposed decoding schemes are superior to the original order statistics decoding in terms of both the bit error rate performance as well as the decoding complexity. The complexity of the order statistics based list decoding algorithms for linear block codes and binary block turbo codes (BTC) is further reduced by employing highly reliable cyclic redundancy check (CRC) bits. The results show that sending CRC bits for many segments is the most effective tecnhique in reducing the complexity. The coded cooperative diversity is compared with the conventional receiver coded diversity in terms of the pairwise error probability and the overall bit error rate (BER). The expressions for the pairwise error probabilities are obtained analytically and verified by computer simulations. The performance of the cooperative diversity is found to be strongly relay location dependent. Using the analytical as well as extensive numerical results, the geographical areas of the relay locations are obtained for small to medium signal-to-noise ratio values, such that the cooperative coded diversity outperforms the receiver coded diversity. However, for sufficiently large signal-to-noise ratio (SNR) values, or if the path-loss attenuations are not considered, then the receiver coded diversity always outperforms the cooperative coded diversity. The obtained results have important implications on the deployment of the next generation cellular systems supporting the cooperative as well as the receiver diversity

Efficient soft decoding techniques for reed-solomon codes

The main focus of this thesis is on finding efficient decoding methods for Reed-Solomon (RS) codes, i.e., algorithms with acceptable performance and affordable complexity. Three classes of decoders are considered including sphere decoding, belief propagation decoding and interpolation-based decoding. Originally proposed for finding the exact solution of least-squares problems, sphere decoding (SD) is used along with the most reliable basis (MRB) to design an efficient soft decoding algorithm for RS codes. For an (N, K ) RS code, given the received vector and the lattice of all possible transmitted vectors, we propose to look for only those lattice points that fall within a sphere centered at the received vector and also are valid codewords. To achieve this goal, we use the fact that RS codes are maximum distance separable (MDS). Therefore, we use sphere decoding in order to find tentative solutions consisting of the K most reliable code symbols that fall inside the sphere. The acceptable values for each of these symbols are selected from an ordered set of most probable transmitted symbols. Based on the MDS property, K code symbols of each tentative solution can he used to find the rest of codeword symbols. If the resulting codeword is within the search radius, it is saved as a candidate transmitted codeword. Since we first find the most reliable code symbols and for each of them we use an ordered set of most probable transmitted symbols, candidate codewords are found quickly resulting in reduced complexity. Considerable coding gains are achieved over the traditional hard decision decoders with moderate increase in complexity. Due to their simplicity and good performance when used for decoding low density parity check (LDPC) codes, iterative decoders based on belief propagation (BP) have also been considered for RS codes. However, the parity check matrix of RS codes is very dense resulting in lots of short cycles in the factor graph and consequently preventing the reliability updates (using BP) from converging to a codeword. In this thesis, we propose two BP based decoding methods. In both of them, a low density extended parity check matrix is used because of its lower number of short cycles. In the first method, the cyclic structure of RS codes is taken into account and BP algorithm is applied on different cyclically shifted versions of received reliabilities, capable of detecting different error patterns. This way, some deterministic errors can be avoided. The second method is based on information correction in BP decoding where all possible values are tested for selected bits with low reliabilities. This way, the chance of BP iterations to converge to a codeword is improved significantly. Compared to the existing iterative methods for RS codes, our proposed methods provide a very good trade-off between the performance and the complexity. We also consider interpolation based decoding of RS codes. We specifically focus on Guruswami-Sudan (GS) interpolation decoding algorithm. Using the algebraic structure of RS codes and bivariate interpolation, the GS method has shown improved error correction capability compared to the traditional hard decision decoders. Based on the GS method, a multivariate interpolation decoding method is proposed for decoding interleaved RS (IRS) codes. Using this method all the RS codewords of the interleaved scheme are decoded simultaneously. In the presence of burst errors, the proposed method has improved correction capability compared to the GS method. This method is applied for decoding IRS codes when used as outer codes in concatenated code

Iterative chase decoding of algebraic geometric codes

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