Parity-Check Matrix Partitioning for Efficient Layered Decoding of QC-LDPC Codes

نویسندگان

چکیده

In this paper, we consider how to partition the parity-check matrices (PCMs) reduce hardware complexity and increase decoding throughput for row layered of quasi-cyclic low-density (QC-LDPC) codes. First, formulate PCM partitioning as an optimization problem, which targets minimize maximum column weight each layer while maintaining a block cyclic shift property among different layers. As result, derive all feasible solutions problem propose tight lower bound ω LB on minimum possible evaluate solution. Second, define metric called distance measure data dependency between consecutive layers further illustrate identify with desired from those achieving value = 1, is preferred computation delay. Next, demonstrate that up-to-now, finding optimal solution polynomial time unachievable. Therefore, both enumerative greedy algorithms are proposed instead. After that, modify progressive edge-growth (QC-PEG) algorithm directly construct PCMs have straightforward scheme achieve or distance. Simulation results showed constructed codes better error correction performance less average number iterations than underlying 5G LDPC

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ژورنال

عنوان ژورنال: IEEE Transactions on Communications

سال: 2023

ISSN: ['1558-0857', '0090-6778']

DOI: https://doi.org/10.1109/tcomm.2023.3261380