Blind Classification of Error-Correcting Codes for Enhancing Spectral Efficiency of Wireless Networks
- Authors
- Kwon, Soonhee; Shin, Dong-Joon
- Issue Date
- Sep-2021
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS IN
- Keywords
- Blind classification; error-correcting codes (ECCs); Gauss-Jordan elimination through pivoting (GJETP); broadcasting systems; random row permutation; rank calculation
- Citation
- IEEE TRANSACTIONS ON BROADCASTING, v.67, no.3, pp.651 - 663
- Indexed
- SCIE
SCOPUS
- Journal Title
- IEEE TRANSACTIONS ON BROADCASTING
- Volume
- 67
- Number
- 3
- Start Page
- 651
- End Page
- 663
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/141189
- DOI
- 10.1109/TBC.2021.3061984
- ISSN
- 0018-9316
- Abstract
- Error-correcting codes (ECCs) are essential to improve the reliability of digital communication systems. ECCs can detect or correct the errors by introducing and utilizing the systematic parity check bits, which however deteriorate the spectral efficiency of digital communication systems. In order to enhance the spectral efficiency, the used ECC may be blindly detected at the receiver. Also, blind detection of ECCs is important in the broadcasting systems. Recently, blind detection schemes of ECCs have been actively studied and most of them assume that the receiver knows which type of ECC, a block code or a non-block code, is used. However, in real situations, blind classification about whether the ECC is a block code or a non-block code should be performed first. In this paper, a blind classification scheme of ECCs in a noisy environment is proposed, which does not require the knowledge of parameters of the used ECC. The proposed scheme classifies whether the received bit-stream is encoded by an ECC or not, and if it is determined that the received bit-stream is encoded, the proposed scheme further classifies whether the used ECC is a block code or a non-block code. Also, a novel rank calculation scheme of the intercepted matrix is proposed by performing a probabilistic analysis of random row permutation for the intercepted matrix. Based on this analysis, the minimum number of random row permutations is theoretically derived for guaranteeing correct rank calculation with probability at least beta. Through various simulations, it is shown that the proposed rank calculation and blind classification schemes outperform the existing rank calculation and blind classification schemes. Furthermore, it is verified that the performance gap between the proposed schemes and the existing schemes becomes larger as beta is increased.
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