2015 IEEE 26th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) 2015
DOI: 10.1109/pimrc.2015.7343516
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A new architecture for high throughput, low latency NB-LDPC check node processing

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Cited by 5 publications
(6 citation statements)
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“…Thanks to the DBV computation, the output of the EF processing is similar to (6) and (7) with the only difference that the set of deviation paths ∆ EF is input dependent, while it is predefined offline for the SB [7], [8].…”
Section: A Construction Of the Discard Binary Vectormentioning
confidence: 99%
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“…Thanks to the DBV computation, the output of the EF processing is similar to (6) and (7) with the only difference that the set of deviation paths ∆ EF is input dependent, while it is predefined offline for the SB [7], [8].…”
Section: A Construction Of the Discard Binary Vectormentioning
confidence: 99%
“…In the EF processing, the number of computed syndromes is typically 3×n m,out to compensate for the discarded redundant syndromes [7], [8]. However, even with this approach, the first simulation results of the EF algorithm showed significant performance degradation compared to the FB algorithm (red curve in Fig.…”
Section: B the Effect Of Re In Ecnsmentioning
confidence: 99%
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“…The SB algorithm, recently presented in [10] [11], is an efficient method to perform a parallel computation of the CN when q ≥ 16. This architecture was used for the first reported implementation of a GF(256) CN processor with degree d c = 4 [12].…”
Section: Introductionmentioning
confidence: 99%
“…Three categories of simplified EMS emerge frome state of the art. The Forward-Backward Check Node (FB-CN) algorithm [4] is efficiently implemented in [7] and [8] but can be limited in throughput due to its The Syndrome-Based Check Node (SB-CN) algorithm, recently presented in [10], [11], allows an efficient parallel computation of the CN function for high order Galois fields (q ≥ 16). However, the complexity of the SB-CN algorithm is dominated by the number z of syndromes to compute.…”
Section: Introductionmentioning
confidence: 99%