Asif, Muhammad and Khan, Wali Ullah and Afzal, H. M. Rehan and Nebhen, Jamel and Ullah, Inam and Rehman, Ateeq Ur and Kaabar, Mohammed K. A. (2021) Reduced-complexity LDPC decoding for next-generation IoT networks. Wireless Communications & Mobile Computing, 2021. ISSN 1530-8669, DOI https://doi.org/10.1155/2021/2029560.
Full text not available from this repository.Abstract
Low-density parity-check (LDPC) codes have become the focal choice for next-generation Internet of things (IoT) networks. This correspondence proposes an efficient decoding algorithm, dual min-sum (DMS), to estimate the first two minima from a set of variable nodes for check-node update (CNU) operation of min-sum (MS) LDPC decoder. The proposed architecture entirely eliminates the large-sized multiplexing system of sorting-based architecture which results in a prominent decrement in hardware complexity and critical delay. Specifically, the DMS architecture eliminates a large number of comparators and multiplexors while keeping the critical delay equal to the most delay-efficient tree-based architecture. Based on experimental results, if the number of inputs is equal to 64, the proposed architecture saves 69%, 68%, and 52% area over the sorting-based, the tree-based, and the low-complexity tree-based architectures, respectively. Furthermore, the simulation results show that the proposed approach provides an excellent error-correction performance in terms of bit error rate (BER) and block error rate (BLER) over an additive white Gaussian noise (AWGN) channel.
| Item Type: | Article |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Communication; Algorithms; Optimization; Architecture |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Science > Institute of Mathematical Sciences |
| Depositing User: | Ms Zaharah Ramly |
| Date Deposited: | 22 Aug 2022 00:07 |
| Last Modified: | 22 Aug 2022 00:07 |
| URI: | http://eprints.um.edu.my/id/eprint/28786 |
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