Liu, Yuxin and Effros, Michelle (2020) Finite-Blocklength and Error-Exponent Analyses for LDPC Codes in Point-to-Point and Multiple Access Communication. In: 2020 IEEE International Symposium on Information Theory (ISIT). IEEE , Piscataway, NJ, pp. 361-366. ISBN 978-1-7281-6432-8. https://resolver.caltech.edu/CaltechAUTHORS:20200527-072536184
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Abstract
This paper applies error-exponent and dispersionstyle analyses to derive finite-blocklength achievability bounds for low-density parity-check (LDPC) codes over the point-to-point channel (PPC) and multiple access channel (MAC). The errorexponent analysis applies Gallager’s error exponent to bound achievable symmetrical and asymmetrical rates in the MAC. The dispersion-style analysis begins with a generalization of the random coding union (RCU) bound from random code ensembles with i.i.d. codewords to random code ensembles in which codewords may be statistically dependent; this generalization is useful since the codewords of random linear codes such as LDPC codes are dependent. Application of the RCU bound yields finiteblocklength error bounds and asymptotic achievability results for both i.i.d. random codes and LDPC codes. For discrete, memoryless channels, these results show that LDPC codes achieve first- and second-order performance that is optimal for the PPC and identical to the best prior results for the MAC.
| Item Type: | Book Section | |||||||||
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| Additional Information: | © 2020 IEEE. This material is based upon work supported in part by the National Science Foundation under Grant No. 1817241. The work of Y. Liu is supported in part by the Oringer Fellowship Fund in Information Science and Technology. | |||||||||
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| Record Number: | CaltechAUTHORS:20200527-072536184 | |||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20200527-072536184 | |||||||||
| Official Citation: | Y. Liu and M. Effros, "Finite-Blocklength and Error-Exponent Analyses for LDPC Codes in Point-to-Point and Multiple Access Communication," 2020 IEEE International Symposium on Information Theory (ISIT), Los Angeles, CA, USA, 2020, pp. 361-366, doi: 10.1109/ISIT44484.2020.9173963 | |||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | |||||||||
| ID Code: | 103481 | |||||||||
| Collection: | CaltechAUTHORS | |||||||||
| Deposited By: | Tony Diaz | |||||||||
| Deposited On: | 27 May 2020 15:59 | |||||||||
| Last Modified: | 28 Aug 2020 17:29 |
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