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Broadband satellite services to fixed terminals are currently offered in the forward link by the 2nd Generation (2G) Digital Video Broadcasting Satellite (DVB-S2) standard. For this standard the use of powerful Low-Density Parity-Check (LDPC) error correcting codes has been adopted performing within approximately 1 dB from the Shannon capacity limit. This paper studies and compares for the first time in a systematic manner different approximation methods used in check node update computation of DVB-S2 LDPC decoding with the aim of reducing computational complexity. Various performance evaluation resuits are presented for a wide range of DVB-S2 parameters, such as LDPC codeword size, coding rate, modulation format and including several decoding algorithms. It is shown that the proposed check node update approximations have a robust behavior, i.e. the resulting performance is quite independent of the DVB-S2 modulation and coding parameters. It is further shown that these approximations perform very close to the optimal Sum-Product Algorithm (SPA) in degradation, which is less than 0.2 dB. Despite this small degradation, the reduction in computational complexity compared to the optimal SPA is significant and can be as high as 40% in computational time savings. Index Terms--Broadcasting, iterative decoding, Low-Density Parity-Check (LDPC) codes.

In this paper, we deal with practical implementation issues of the \max^ \ast operation in generalized form used for decoding of both turbo and low-density-parity-check (LDPC) codes. In particular, first, a unified framework for the so-called generalized \max^\ast operation is established, which includes most of the previously published algorithms already known for turbo decoding. Next, the hardware architectures used for the practical implementation of the generalized \max^\ast operation, which is derived from this novel framework, are revealed for the first time and further analyzed, in terms of hardware complexity reduction. It is also shown how this generalized \max^\ast operation can be adopted in LDPC decoding, achieving essentially optimal bit error rate performance with small computational complexity against other algorithms in joint turbo–LDPC architectures. This solution is useful in applications where joint decoding architectures are deployed to decode both turbo and LDPC codes. An important example of such application is in software radio receivers of 4G wireless communication systems, such as those proposed in conjunction with the WiMAX standard. [ABSTRACT FROM PUBLISHER]

Three non-data-aided signal-to-noise ratio (SNR) estimator techniques are derived and compared for turbo decoding, in conjunction with block-coded binary-phase-shift-keying (BPSK) signals received over fully interleaved (i.e., uncorrelated) Rayleigh fading channels. These estimators, which do not require knowledge at the receiver of the channel SNR nor the power of fading amplitude, are optimized in terms of minimizing the estimation error by choosing an appropriate curve fit model and comparing their estimation errors, as well as their turbo decoding bit-error-rate (BER) performance. Turbo decoding performance evaluation results have demonstrated that the two SNR estimators, which use the ratios of the second moment to the square of the mean absolute value and the fourth moment to the fourth power of the mean absolute value of the received signals, respectively, result in comparable BER performance to the case of perfect SNR knowledge at the receiver. Furthermore, they outperform the third SNR estimator, which makes use of the ratio of the square of the second moment to the fourth moment, particularly in applications with relatively short code blocks. [ABSTRACT FROM AUTHOR]