A Study on Low Level Quantizers for Block Turbo Decoding for Product Codes of Binary Linear Code

Shinichi Kageyama; Ken Ikuta; Takuya Kusaka; Yasuyuki Nogami

doi:10.1109/ITC-CSCC.2019.8793409

A Study on Low Level Quantizers for Block Turbo Decoding for Product Codes of Binary Linear Code

Shinichi Kageyama, Ken Ikuta, Takuya Kusaka, Yasuyuki Nogami

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Block Turbo Decodings (BTDs) with Soft-In Soft-Out (SISO) decodings for two dimensional product codes of linear codes can achieve good error performance, however, large computational complexity of the BTDs can be a problem. Therefore, to reduce the computational complexity, quantization methods can be employed for the BTDs by sacrificing the error performance. In this paper, a study on design for low level quantizers for the BTD with S1SO Ordered Statistics Decoding for product codes of binary linear code is shown. From simulation results for a 4-level quantizer, the authors propose a new 5-level quantizer. The proposed 5-level quantizer achieves better error performance than 4-level quantizer.

Original language	English
Title of host publication	34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728132716
DOIs	https://doi.org/10.1109/ITC-CSCC.2019.8793409
Publication status	Published - Jun 2019
Event	34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019 - JeJu, Korea, Republic of Duration: Jun 23 2019 → Jun 26 2019

Publication series

Name	34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019

Conference

Conference	34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019
Country	Korea, Republic of
City	JeJu
Period	6/23/19 → 6/26/19

Keywords

AWGN
Block Turbo Decoding
Quantization
Soft-in Soft-out OSD

ASJC Scopus subject areas

Information Systems
Electrical and Electronic Engineering
Artificial Intelligence
Computer Networks and Communications
Hardware and Architecture

Access to Document

10.1109/ITC-CSCC.2019.8793409

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Kageyama, S., Ikuta, K., Kusaka, T., & Nogami, Y. (2019). A Study on Low Level Quantizers for Block Turbo Decoding for Product Codes of Binary Linear Code. In 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019 [8793409] (34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITC-CSCC.2019.8793409

A Study on Low Level Quantizers for Block Turbo Decoding for Product Codes of Binary Linear Code. / Kageyama, Shinichi; Ikuta, Ken; Kusaka, Takuya ; Nogami, Yasuyuki.

34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8793409 (34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kageyama, S, Ikuta, K, Kusaka, T & Nogami, Y 2019, A Study on Low Level Quantizers for Block Turbo Decoding for Product Codes of Binary Linear Code. in 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019., 8793409, 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019, Institute of Electrical and Electronics Engineers Inc., 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019, JeJu, Korea, Republic of, 6/23/19. https://doi.org/10.1109/ITC-CSCC.2019.8793409

Kageyama S, Ikuta K, Kusaka T , Nogami Y. A Study on Low Level Quantizers for Block Turbo Decoding for Product Codes of Binary Linear Code. In 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8793409. (34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019). https://doi.org/10.1109/ITC-CSCC.2019.8793409

Kageyama, Shinichi ; Ikuta, Ken ; Kusaka, Takuya ; Nogami, Yasuyuki. / A Study on Low Level Quantizers for Block Turbo Decoding for Product Codes of Binary Linear Code. 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019).

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abstract = "Block Turbo Decodings (BTDs) with Soft-In Soft-Out (SISO) decodings for two dimensional product codes of linear codes can achieve good error performance, however, large computational complexity of the BTDs can be a problem. Therefore, to reduce the computational complexity, quantization methods can be employed for the BTDs by sacrificing the error performance. In this paper, a study on design for low level quantizers for the BTD with S1SO Ordered Statistics Decoding for product codes of binary linear code is shown. From simulation results for a 4-level quantizer, the authors propose a new 5-level quantizer. The proposed 5-level quantizer achieves better error performance than 4-level quantizer.",

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AB - Block Turbo Decodings (BTDs) with Soft-In Soft-Out (SISO) decodings for two dimensional product codes of linear codes can achieve good error performance, however, large computational complexity of the BTDs can be a problem. Therefore, to reduce the computational complexity, quantization methods can be employed for the BTDs by sacrificing the error performance. In this paper, a study on design for low level quantizers for the BTD with S1SO Ordered Statistics Decoding for product codes of binary linear code is shown. From simulation results for a 4-level quantizer, the authors propose a new 5-level quantizer. The proposed 5-level quantizer achieves better error performance than 4-level quantizer.

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