China
Africa
Explore chapters and articles related to this topic
Coding
Published in Goff Hill, The Cable and Telecommunications Professionals' Reference, 2012
In soft-decision decoding, the input to the decoder is the unsliced (analogue) sample stream. Because the decoder implementation is usually digital, the sample stream has to be digitized before input to the decoder, but it has been found that in practice very low-resolution digitization (for example, to only 8 or 16 levels) is often adequate. Soft decision decoding is computationally more demanding than hard-decision decoding. It has long been used with convolutional codes (see the Convolutional Codes section) to give extra coding gain, typically of about 2 dB. Its use for block codes was less common until recently, but the most recent block codes, that is, Turbo and LDPC (see the Turbo and LDPC Codes section) usually use soft-decision decoding.
Error Control Coding
Published in Jerry D. Gibson, Mobile Communications Handbook, 2017
As a rule of thumb, at high signal-to-noise ratio (SNR), there is approximately a 2 dB gain associated with soft-decision decoding, compared to hard-decision decoding [7]. However, soft-decision decoding of algebraically constructed block codes is computationally complex; indeed, it was shown in Reference 8 that optimal (ML) soft-decision decoding of Reed–Solomon codes is NP-hard, although suboptimal algorithms that exploit soft information remain a subject of considerable research interest [9]. (ML soft-decision decoding selects as its estimate of the transmitted codeword the one that minimizes the Euclidean distance between the received signal and the modulated codeword.)
Performance Analysis of Reliability-Based Decoding Algorithm for Short Block Length Turbo Codes
Published in IETE Journal of Research, 2022
P. Salija, B. Yamuna, T. R. Padmanabhan, Deepak Mishra
Efforts to improve the performance of short block length Turbo codes have been reported in literature. Reliability-based soft-decision decoding methods reported in literature have shown coding gain improvement for short to moderate length codewords [16]. Reliability value of a received bit indicates its certainty and hence decoding with reliability information gives improved error correction performance. Most of the reliability-based Turbo decoders take advantage of ordered statistics decoding (OSD) algorithm along with the iterative process [6,7,17,18]. The methods reported in literature have considered LLR values of each bit as reliability information. Once the iterative process is completed, reliability-based decoder performs OSD or flip and check, or CRC check [4,6,19,20]. This results in additional computational complexity and decoding delay. None of the reported methods guarantee the complete elimination of error floor at high SNRs. Thus iterative reliability-based Turbo decoder is not suitable for applications involving short block length Turbo codes.
LDPC Codes and Digital Forensics – A Perspective Approach
Published in IETE Journal of Research, 2022
The SPA is a suboptimal (soft-decision) decoding algorithm which gives the best error performance but requires the highest computational complexity. Using quasi-cyclic structured LDPC code, the designed parity check matrix (H) will devise into a reduced complexity iterative decoding algorithm SPA. The above SPA algorithm can be illustrated as follows: The parity-check matrix has columns and rows. is the set of parity nodes connected to the code bit . is the received version of and is the variance of noise. is the set of bit nodes connected to the parity-check.The initial message, , sent from bit node to the check node is the wavelet domain LLR of the (soft) received signal, given knowledge of the channel properties. is the extrinsic message from check node to bit node . It is the wavelet domain LLR of the probability that parity-check is satisfied if bit is assumed to be a 1. is the estimated log-APP of each bit and is the structured parity-check matrix.