Sarvaghad-Moghaddam Moein, Ullah Waheed, Jayakody Dushantha Nalin K, Affes Sofiéne
Quantum Design Automation Lab, Amirkabir University of Technology, Tehran 424, Iran.
School of Electrical and Information Engineering, University of the Witwatersrand, WITS 2050, South Africa.
Sensors (Basel). 2020 Apr 17;20(8):2300. doi: 10.3390/s20082300.
Secure and reliable information flow is one of the main challenges in social IoT and mobile networks. Information flow and data integrity is still an open research problem. In this paper, we develop new methods of constructing systematic and regular Low-Density Parity-Check Matrices (LDPCM), inspired by the structure of the Sarrus method and geometric designs. Furthermore, these codes have cyclic structure and therefore, are less complex in computation and also require less memory in hardware implementation. Besides, an optimal method of post-processing for deleting girths four is presented. Numerical results show that the codes constructed by these methods perform well over the additive white Gaussian noise (AWGN) channel when decoded with the sum-product LDPC iterative algorithms. The proposed methods can be very efficient in terms of reducing memory consumption and improving the convergence speed of the decoder particularly in IoT and mobile networks.
安全可靠的信息流是社会物联网和移动网络中的主要挑战之一。信息流和数据完整性仍然是一个开放的研究问题。在本文中，我们受萨鲁斯方法和几何设计结构的启发，开发了构建系统且规则的低密度奇偶校验矩阵（LDPCM）的新方法。此外，这些码具有循环结构，因此，计算复杂度较低，在硬件实现中所需内存也较少。此外，还提出了一种用于删除四环的最优后处理方法。数值结果表明，当用和积LDPC迭代算法解码时，通过这些方法构建的码在加性高斯白噪声（AWGN）信道上表现良好。所提出的方法在减少内存消耗和提高解码器收敛速度方面非常有效，特别是在物联网和移动网络中。
