@inproceedings{a57dafa393794d43a33e5322d81c6d41,
title = "Improved Max-Log-MAP Turbo Decoding by Extrinsic Information Scaling and Combining",
abstract = "Turbo codes are among the best error-correcting codes, but trade-offs between performance and complexity in decoding are required for hardware implementation. In this paper, a novel extrinsic information scaling scheme for max-log-MAP decoder is proposed. It scales and combines extrinsic information generated at successive iteration round. The proposed method is evaluated for 3GPP LTE turbo codes in terms of decoding performance, complexity, and convergence. The simulation results show it has decoding gain near to log-MAP while keeps almost the same computation complexity as max-log-MAP with slight increment in memory resource. Moreover, it maintains insensitivity to SNR estimation error of max-log-MAP algorithm. Compared with conventional scaling scheme, it accelerates extrinsic information exchange between two constituent decoders to get better convergence and decoding performance.",
keywords = "Extrinsic information, Scaling factor, Turbo codes",
author = "Lei Sun and Hua Wang",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Singapore Pte Ltd.; International Conference on Communications, Signal Processing, and Systems, CSPS 2018 ; Conference date: 14-07-2018 Through 16-07-2018",
year = "2020",
doi = "10.1007/978-981-13-6504-1_42",
language = "English",
isbn = "9789811365034",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "336--344",
editor = "Qilian Liang and Xin Liu and Zhenyu Na and Wei Wang and Jiasong Mu and Baoju Zhang",
booktitle = "Communications, Signal Processing, and Systems - Proceedings of the 2018 CSPS Volume II",
address = "Germany",
}