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Low-density parity-check (LDPC) codes are known to be one of the best error-correction coding (ECC) schemes in terms of correction performance. They have been utilized in many advanced data communication standards for which the codecs are typically implemented in custom integrated circuits (ICs). In this paper, we present a research work that shows that the LDPC coding scheme can also be applied in a system characterized by highly limited computational resources. We present a microcontroller-based application of an efficient LDPC encoding algorithm with efficient usage of memory resources for the code-parity-check matrix and the storage of the results of auxiliary computations. The developed implementation is intended for an IoT-type system, in which a low-complexity network node device encodes messages transmitted to a gateway. We present how the classic Richardson–Urbanke algorithm can be decomposed for the QC-LDPC subclass into cyclic shifts and GF(2) additions, directly corresponding to the CPU instructions. The experimental results show a significant gain in terms of memory usage and decoding timing of the proposed method in comparison with encoding with the direct parity check matrix representation. We also provide experimental comparisons with other known block codes (RS and BCH) showing that the memory requirements are not greater than for standard block codes, while the encoding time is reduced, which enables the energy consumption reduction. At the same time, the error-correction performance gain of LDPC codes is greater than for the mentioned standard block codes.

Efficient LDPC Encoder Design for IoT-Type Devices