Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding

Forskningsoutput: KonferensbidragAnnan

Standard

Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding. / Zhou, Wei; Lentmaier, Michael.

2019. 12th International ITG Conference on Systems, Communications and Coding, Rostock, Tyskland.

Forskningsoutput: KonferensbidragAnnan

Harvard

APA

Zhou, W., & Lentmaier, M. (2019). Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding. 12th International ITG Conference on Systems, Communications and Coding, Rostock, Tyskland.

CBE

Zhou W, Lentmaier M. 2019. Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding. 12th International ITG Conference on Systems, Communications and Coding, Rostock, Tyskland.

MLA

Vancouver

Zhou W, Lentmaier M. Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding. 2019. 12th International ITG Conference on Systems, Communications and Coding, Rostock, Tyskland.

Author

Zhou, Wei ; Lentmaier, Michael. / Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding. 12th International ITG Conference on Systems, Communications and Coding, Rostock, Tyskland.

RIS

TY - CONF

T1 - Generalized Two-Magnitude Check Node Updating with Self Correction for 5G LDPC Codes Decoding

AU - Zhou, Wei

AU - Lentmaier, Michael

PY - 2019

Y1 - 2019

N2 - The min-sum (MS) and approximate-min* (a-min*) algorithms are alternatives of the belief propagation (BP) algorithm for decoding low-density parity-check (LDPC) codes. To lower the BP decoding complexity, both algorithms compute two magnitudes at each check node (CN) and pass them to the neighboring variable nodes (VNs).In this work we propose a new algorithm, ga-min*, that generalizes the MS and a-min* in terms of number of incoming messages to a CN.We analyze and demonstrate a condition to improve the performance when applying self-correction to the ga-min*. Simulations on 5G LDPC codes show that the proposed decoding algorithm yields comparable performance to the a-min* with a significant reduction in complexity, and it is robust against LLR mismatch.

AB - The min-sum (MS) and approximate-min* (a-min*) algorithms are alternatives of the belief propagation (BP) algorithm for decoding low-density parity-check (LDPC) codes. To lower the BP decoding complexity, both algorithms compute two magnitudes at each check node (CN) and pass them to the neighboring variable nodes (VNs).In this work we propose a new algorithm, ga-min*, that generalizes the MS and a-min* in terms of number of incoming messages to a CN.We analyze and demonstrate a condition to improve the performance when applying self-correction to the ga-min*. Simulations on 5G LDPC codes show that the proposed decoding algorithm yields comparable performance to the a-min* with a significant reduction in complexity, and it is robust against LLR mismatch.

KW - LDPC codes

KW - Iterative Decoding

KW - Generalized Min Sum

M3 - Other

ER -