Paper Info
Title
Self-Superposition Transmission: A Novel Method for Enhancing Performance of Convolutional Codes
Abstract
In this paper, a novel method for enhancing the error performance of convolutional codes (CCs) is introduced. This method aims to extend the constraint length of CCs by simply superimposing the encoded bit sequences. Therefore, such construction is referred to as self-superposition. The encoding process of self-superposition convolutional codes (SSCCs) can be implemented as fast as that of the corresponding CCs, and a low-complexity iterative decoding algorithm can be applied to efficiently decode SSCCs. Numerical results show that in the high signal-to-noise ratio (SNR) region, the SSCC outperforms the corresponding CC within a wide range of code rates in terms of the bit error rate.
Year
DOI
Venue
2018
10.1109/ISTC.2018.8625313
2018 IEEE 10th International Symposium on Turbo Codes & Iterative Information Processing (ISTC)
Keywords
Field
DocType
encoded bit sequences,encoding process,self-superposition convolutional codes,low-complexity iterative decoding algorithm,bit error rate,self-superposition transmission,error performance,constraint length,SSCC decoding,high signal-to-noise ratio region,SNR
Superposition principle,Convolutional code,Computer science,Algorithm,Decoding methods,Bit error rate,Encoding (memory)
Conference
ISSN
ISBN
Citations 
2165-4700
978-1-5386-7049-1
0
PageRank 
References 
Authors
0.34
8
5
Name
Order
Citations
PageRank
Shuangyang Li111211.38
Ji Zhang25921.71
Baoming Bai335363.90
Xiao Ma448764.77
Jinhong Yuan52966202.61