Search Based Weighted Multi-Bit Flipping Algorithm for High-Performance Low-Complexity Decoding of LDPC Codes
الموضوعات :Ehsan Olyaei Torshizi 1 , Mohammad Amir Nazari Siahsar 2 , Ali Akbar Khazaei 3 , Hossein Sharifi 4
1 - Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran
2 - Young Researchers and Elite Club, Mashhad Branch, Islamic Azad University, Mashhad, Iran
3 - Department of Electrical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
4 - Department of Electrical & Computer Engineering, Shahid Beheshti University, Tehran, Iran
الکلمات المفتاحية: Belief Propagation (BP), Low-Density Parity-Check (LDPC) Codes, Modified Weighted Bit-Flipping Algorithm, Hybrid Iterative Decoding, Error Performance,
ملخص المقالة :
In this paper, two new hybrid algorithms are proposed for decoding Low Density Parity Check (LDPC) codes. Original version of the proposed algorithms named Search Based Weighted Multi Bit Flipping (SWMBF). The main idea of these algorithms is flipping variable multi bits in each iteration, change in which leads to the syndrome vector with least hamming weight. To achieve this, the proposed algorithms do multi-dimensional searching between all possible bit position(s) that could flip in each iteration to select the best choices. It goes without saying that each iterative decoding algorithm provides a distinct trade-off between complexity and performance. SBWMBF algorithm, which while having the capacity for flipping several bits per iteration, offers a faster convergence rate and less hardware complexity compared to the modified WBF algorithm and the other version of hybrid algorithms. Then, in order to simplicity and reduction in run time of original version, we have introduced a simplified version that is new and highly efficient algorithm with an acceptable performance compared with the BP algorithm and less complexity and fewer iterations required. Simulation results, when compared to other known decoding algorithms, illustrate that the proposed algorithms converge significantly faster and have a tangible reduction in iteration number and computational complexity and also have superior performance but with little performance penalty than the robust BP algorithm.
