Balazs Matuz

Generalized IRA Erasure Correcting Codes for Hybrid Iterative/Maximum Likelihood Decoding

The design of low-density parity-check (LDPC) codes under hybrid iterative / maximum likelihood decoding is addressed for the binary erasure channel (BEC). Specifically, we focus on generalized irregular repeat-accumulate (GeIRA) codes, which offer both efficient encoding and design flexibility. We show that properly designed GeIRA codes tightly approach the performance of an ideal maximum distance separable (MDS) code, even for short block sizes. For example, our (2048,1024) code reaches a codeword error rate of 10-5 at channel erasure probability isin= 0.450, where an ideal (2048,1024) MDS code would reach the same error rate at isin = 0.453.

Maximum Likelihood Erasure Decoding of LDPC Codes: Pivoting Algorithms and Code Design

This paper investigates efficient maximum-likelihood (ML) decoding of low-density parity-check (LDPC) codes over erasure channels. A set of algorithms, referred to as pivoting algorithms, is developed. The aim is to limit the average number of pivots (or reference variables) from which all the other erased symbols are recovered iteratively. The suggested algorithms exhibit different trade-offs between complexity of the pivoting phase and average number of pivots. Moreover, a systematic procedure to design LDPC code ensembles for efficient ML decoding is proposed. Numerical results illustrate that the designed LDPC codes achieve a near-optimum performance (very close to the Singleton bound, at least down to a codeword error rate level 10-8) with an affordable decoding complexity. For one of the presented codes and algorithms, a software implementation has been developed which is capable to provide data rates above 1.5 Gbps on a commercial computing platform.

Non-binary protograph low-density parity-check codes for space communications

SUMMARY Protograph-based non-binary low-density parity-check (LDPC) codes with ultra-sparse parity-check matrices are compared with binary LDPC and turbo codes (TCs) from space communication standards. It is shown that larger coding gains are achieved, outperforming the binary competitors by more than 0.3dB on the additive white Gaussian noise channel (AWGN). In the short block length regime, the designed codes gain more than 1dB with respect to the binary protograph LDPC codes recently proposed for the next generation up-link standard of the Consultative Committee for Space Data Systems. Copyright

Low-Complexity LDPC Codes with Near-Optimum Performance over the BEC

Recent works showed how low-density parity-check (LDPC) erasure correcting codes, under maximum likelihood (ML) decoding, are capable of tightly approaching the performance of an ideal maximum-distance-separable code on the binary erasure channel. Such result is achievable down to low error rates, even for small and moderate block sizes, while keeping the decoding complexity low, thanks to a class of decoding algorithms which exploits the sparseness of the parity-check matrix to reduce the complexity of Gaussian elimination (GE). In this paper the main concepts underlying ML decoding of LDPC codes are recalled. A performance analysis among various LDPC code classes is then carried out, including a comparison with fixed-rate Raptor codes. The results confirm that a judicious LDPC code design allows achieving achieving a near-optimum performance on the erasure channel, with very low error floors. Furthermore, it is shown that LDPC and Raptor codes, under ML decoding, provide almost identical performance in terms of decoding failure probability vs. overhead.

Short Turbo Codes over High Order Fields

Two classes of turbo codes constructed on high-order finite fields are introduced. The codes are derived from a particular protograph sub-ensemble of the (2,3) regular low-density parity-check (LDPC) code ensemble. The first construction results in a parallel concatenation of two non-binary, time-variant accumulators. The second construction consists of the serial concatenation of a non-binary time-variant differentiator with a non-binary time-variant accumulator, and provides a highly structured flexible encoding scheme for (2,4) LDPC codes. A cycle graph representation is also provided. The proposed codes can be decoded efficiently either as LDPC codes (via belief propagation decoding on their bipartite graphs) or as turbo codes (via the forward-backward algorithm applied to the component code trellises) by means of the fast Fourier transform. The proposed codes provide remarkable coding gains (more than 1 dB at a codeword error rate 10-4) over binary LDPC and turbo codes in the moderate-short block length regime.

Pivoting Algorithms for Maximum Likelihood Decoding of LDPC Codes over Erasure Channels

This paper investigates efficient maximum-likelihood (ML) decoding algorithms for low-density parity-check (LDPC) codes over erasure channels. In particular, enhancements to a previously proposed structured Gaussian elimination approach are presented. The improvements are achieved by developing a set of algorithms, here referred to as pivoting algorithms, aiming to limit the average number of reference variables (or pivots) from which the erased symbols can be recovered. Four pivoting algorithms are compared, which exhibit different trade-offs between the complexity of the pivoting phase and the average number of pivots. Numerical results on the performance of LDPC codes under ML erasure decoding complete the analysis, confirming that a near-optimum performance can be obtained with an affordable decoding complexity, up to very high data rates. For example, for one of the presented algorithms, a software implementation has been developed, which is capable to provide data rates above 1.5 Gbps on a commercial computing platform.

Digital modulation and coding for satellite optical feeder links

In this paper, a digital transmission scheme protected by a packet-level forward error correction (FEC) coding technique is proposed for optical feeder links in a satellite communication system. The architectures of the gateway and the satellite are defined, including the building blocks of the interface between the radio frequency (RF) front-end and the optical front-end, as well as the digital signal processor. The system is designed to cater for Terabit/s high-throughput satellite (HTS) applications. In addition, the turbulent atmospheric optical channel is modeled for different elevation setups and optical ground station (OGS) altitudes in untracked and tracked beam scenarios. The performance of the digital transmission scheme is evaluated in the forward and return link channels. It is shown that fade mitigation techniques such as packet-level FEC coding in the forward link, as well as beam tracking, and large-aperture OGS telescope in the return link are essential to close the link budget of a Terabit/s satellite transmission link.

On Construction of Moderate-Length LDPC Codes over Correlated Erasure Channels

The design of moderate-length erasure correcting low-density parity-check (LDPC) codes over correlated erasure channels is considered. Although the asymptotic LDPC code design remains the same as for a memoryless erasure channel, robustness to the channel correlation shall be guaranteed for the finite length LDPC code. This further requirement is of great importance in several wireless communication scenarios where packet erasure correcting codes represent a simple countermeasure for correlated fade events (e.g., in mobile wireless broadcasting services) and where the channel coherence time is often comparable with the code length. In this paper, the maximum tolerable erasure burst length (MTBL) is adopted as a simple metric for measuring the code robustness to the channel correlation. Correspondingly, a further step in the code construction is suggested, consisting of improving the LDPC code MTBL. Numerical results conducted over a Gilbert erasure channel, under both iterative and maximum likelihood decoding, highlight both the importance of the MTBL improvement in the finite-length code construction and the possibility to tightly approach the performance of maximum distance separable codes.

Short non-binary IRA codes on large-girth Hamiltonian graphs

Short non-binary irregular repeat-accumulate (IRA) codes based on well-known Hamiltonian and Hypohamiltonian graphs with large girth are presented. The mapping of the code coordinates on the graph edges is discussed for Hamiltonian graphs, and two encoding methods on Hypohamiltonian graphs are introduced. The performance of the presented codes on order-256 finite fields (F256) is provided for both the additive white Gaussian (AWGN) channel and the binary erasure channel (BEC) under iterative (IT) decoding. For the latter case, the performance under maximum likelihood (ML) decoding is also presented, to illustrate that the proposed codes not only attain performances close to the random coding bound, but also show limited losses when decoded iteratively.

A decoding algorithm for LDPC codes over erasure channels with sporadic errors

An efficient decoding algorithm for low-density parity-check (LDPC) codes on erasure channels with sporadic errors (i.e., binary error-and-erasure channels with error probability much smaller than the erasure probability) is proposed and its performance analyzed. A general single-error multiple-erasure (SEME) decoding algorithm is first described, which may be in principle used with any binary linear block code. The algorithm is optimum whenever the non-erased part of the received word is affected by at most one error, and is capable of performing error detection of multiple errors. An upper bound on the average block error probability under SEME decoding is derived for the linear random code ensemble. The bound is tight and easy to implement. The algorithm is then adapted to LDPC codes, resulting in a simple modification to a previously proposed efficient maximum likelihood LDPC erasure decoder which exploits the parity-check matrix sparseness. Numerical results reveal that LDPC codes under efficient SEME decoding can closely approach the average performance of random codes.