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- Title
Upper Bound on the Bit Error Probability of Systematic Binary Linear Codes via Their Weight Spectra.
- Authors
Liu, Jia; Zhang, Mingyu; Wang, Chaoyong; Chen, Rongjun; An, Xiaofeng; Wang, Yufei
- Abstract
In this paper, upper bound on the probability of maximum a posteriori (MAP) decoding error for systematic binary linear codes over additive white Gaussian noise (AWGN) channels is proposed. The proposed bound on the bit error probability is derived with the framework of Gallager's first bounding technique (GFBT), where the Gallager region is defined to be an irregular high-dimensional geometry by using a list decoding algorithm. The proposed bound on the bit error probability requires only the knowledge of weight spectra, which is helpful when the input-output weight enumerating function (IOWEF) is not available. Numerical results show that the proposed bound on the bit error probability matches well with the maximum-likelihood (ML) decoding simulation approach especially in the high signal-to-noise ratio (SNR) region, which is better than the recently proposed Ma bound.
- Subjects
ERROR probability; LINEAR codes; ERROR-correcting codes; ADDITIVE white Gaussian noise; BINARY codes; DECODING algorithms; SIGNAL-to-noise ratio
- Publication
Discrete Dynamics in Nature & Society, 2020, p1
- ISSN
1026-0226
- Publication type
Article
- DOI
10.1155/2020/1469090