3 research outputs found
Iterative Soft-Input Soft-Output Decoding with Ordered Reliability Bits GRAND
Guessing Random Additive Noise Decoding (GRAND) is a universal decoding
algorithm that can be used to perform maximum likelihood decoding. It attempts
to find the errors introduced by the channel by generating a sequence of
possible error vectors in order of likelihood of occurrence and applying them
to the received vector. Ordered reliability bits GRAND (ORBGRAND) integrates
soft information received from the channel to refine the error vector sequence.
In this work, ORBGRAND is modified to produce a soft output, to enable its use
as an iterative soft-input soft-output (SISO) decoder. Three techniques
specific to iterative GRAND-based decoding are then proposed to improve the
error-correction performance and decrease computational complexity and latency.
Using the OFEC code as a case study, the proposed techniques are evaluated,
yielding substantial performance gain and astounding complexity reduction of
48\% to 85\% with respect to the baseline SISO ORBGRAND.Comment: Submitted to Globecom 202
Improved Decoding of Staircase Codes: The Soft-aided Bit-marking (SABM) Algorithm
Staircase codes (SCCs) are typically decoded using iterative bounded-distance
decoding (BDD) and hard decisions. In this paper, a novel decoding algorithm is
proposed, which partially uses soft information from the channel. The proposed
algorithm is based on marking certain number of highly reliable and highly
unreliable bits. These marked bits are used to improve the
miscorrection-detection capability of the SCC decoder and the error-correcting
capability of BDD. For SCCs with -error-correcting
Bose-Chaudhuri-Hocquenghem component codes, our algorithm improves upon
standard SCC decoding by up to ~dB at a bit-error rate (BER) of
. The proposed algorithm is shown to achieve almost half of the gain
achievable by an idealized decoder with this structure. A complexity analysis
based on the number of additional calls to the component BDD decoder shows that
the relative complexity increase is only around at a BER of .
This additional complexity is shown to decrease as the channel quality
improves. Our algorithm is also extended (with minor modifications) to product
codes. The simulation results show that in this case, the algorithm offers
gains of up to ~dB at a BER of .Comment: 10 pages, 12 figure
A Soft-Aided Staircase Decoder Using Three-Level Channel Reliabilities
The soft-aided bit-marking (SABM) algorithm is based on the idea of marking
bits as highly reliable bits (HRBs), highly unreliable bits (HUBs), and
uncertain bits to improve the performance of hard-decision (HD) decoders. The
HRBs and HUBs are used to assist the HD decoders to prevent miscorrections and
to decode those originally uncorrectable cases via bit flipping (BF),
respectively. In this paper, an improved SABM algorithm (called iSABM) is
proposed for staircase codes (SCCs). Similar to the SABM, iSABM marks bits with
the help of channel reliabilities, i.e., using the absolute values of the
log-likelihood ratios. The improvements offered by iSABM include: (i) HUBs
being classified using a reliability threshold, (ii) BF randomly selecting
HUBs, and (iii) soft-aided decoding over multiple SCC blocks. The decoding
complexity of iSABM is comparable of that of SABM. This is due to the fact that
on the one hand no sorting is required (lower complexity) because of the use of
a threshold for HUBs, while on the other hand multiple SCC blocks use soft
information (higher complexity). Additional gains of up to 0.53 dB with respect
to SABM and 0.91 dB with respect to standard SCC decoding at a bit error rate
of are reported. Furthermore, it is shown that using 1-bit
reliability marking, i.e., only having HRBs and HUBs, only causes a gain
penalty of up to 0.25 dB with a significantly reduced memory requirement