On implementation of min-sum algorithm and its modifications for decoding low-density Parity-check (LDPC) codes
The effects of clipping and quantization on the performance of the min-sum algorithm for the decoding of low-density parity-check (LDPC) codes at short and intermediate block lengths are studied. It is shown that in many cases, only four quantization bits suffice to obtain close to ideal performance...
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| Published in: | IEEE transactions on communications Vol. 53; no. 4; pp. 549 - 554 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York, NY
IEEE
01.04.2005
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 0090-6778, 1558-0857 |
| Online Access: | Get full text |
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| Abstract | The effects of clipping and quantization on the performance of the min-sum algorithm for the decoding of low-density parity-check (LDPC) codes at short and intermediate block lengths are studied. It is shown that in many cases, only four quantization bits suffice to obtain close to ideal performance over a wide range of signal-to-noise ratios. Moreover, we propose modifications to the min-sum algorithm that improve the performance by a few tenths of a decibel with just a small increase in decoding complexity. A quantized version of these modified algorithms is also studied. It is shown that, when optimized, modified quantized min-sum algorithms perform very close to, and in some cases even slightly outperform, the ideal belief-propagation algorithm at observed error rates. |
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| AbstractList | The effects of clipping and quantization on the performance of the min-sum algorithm for the decoding of low-density parity-check (LDPC) codes at short and intermediate block lengths are studied. It is shown that in many cases, only four quantization bits suffice to obtain close to ideal performance over a wide range of signal-to-noise ratios. Moreover, we propose modifications to the min-sum algorithm that improve the performance by a few tenths of a decibel with just a small increase in decoding complexity. A quantized version of these modified algorithms is also studied. It is shown that, when optimized, modified quantized min-sum algorithms perform very close to, and in some cases even slightly outperform, the ideal belief-propagation algorithm at observed error rates. |
| Author | Banihashemi, A.H. Jianguang Zhao Zarkeshvari, F. |
| Author_xml | – sequence: 1 surname: Jianguang Zhao fullname: Jianguang Zhao organization: Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, Ont., Canada – sequence: 2 givenname: F. surname: Zarkeshvari fullname: Zarkeshvari, F. organization: Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, Ont., Canada – sequence: 3 givenname: A.H. surname: Banihashemi fullname: Banihashemi, A.H. organization: Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, Ont., Canada |
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| Keywords | max-product algorithm Quantization min-sum algorithm Iterative method iterative decoding algorithms Decoding max-sum algorithm Algorithm modified min-sum algorithms Simulation low-density parity-check (LDPC) codes Clipping Parity check codes |
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| SubjectTerms | Additive white noise Algorithms Applied sciences AWGN Blocking Broadband communication Clipping Coding, codes Decibels Decoding Errors Exact sciences and technology Information, signal and communications theory Iterative algorithms Iterative decoding iterative decoding algorithms low-density parity-check (LDPC) codes max-product algorithm max-sum algorithm min-sum algorithm modified min-sum algorithms Parity check codes Quantization Signal and communications theory Signal to noise ratio Systems engineering and theory Telecommunications and information theory Wireless communication |
| Title | On implementation of min-sum algorithm and its modifications for decoding low-density Parity-check (LDPC) codes |
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