publication . Preprint . 2016

Code Design for Short Blocks: A Survey

Liva, Gianluigi; Gaudio, Lorenzo; Ninacs, Tudor; Jerkovits, Thomas;
Open Access English
  • Published: 04 Oct 2016
Abstract
The design of block codes for short information blocks (e.g., a thousand or less information bits) is an open research problem which is gaining relevance thanks to emerging applications in wireless communication networks. In this work, we review some of the most recent code constructions targeting the short block regime, and we compare then with both finite-length performance bounds and classical error correction coding schemes. We will see how it is possible to effectively approach the theoretical bounds, with different performance vs. decoding complexity trade-offs.
Subjects
free text keywords: Computer Science - Information Theory
Download from
80 references, page 1 of 6

[1] C. Shannon, “A mathematical theory of communication,” Bell System Tech. J., vol. 27, pp. 379-423, 623-656, Jul./Oct. 1948.

[2] E. R. Berlekamp, Key papers in the development of coding theory. IEEE Press, 1974.

[3] P. Elias, “Error-free coding,” Transactions of the IRE, vol. 4, no. 4, pp. 29-37, September 1954.

[4] R. G. Gallager, Low-Density Parity-Check Codes. Cambridge, MA, USA: M.I.T. Press, 1963.

[5] G. D. Forney, Jr., Concatenated Codes. Cambridge, MA, USA: M.I.T. Press, 1966.

[6] D. J. Costello, Jr. and G. D. Forney, Jr., “Channel coding: The road to channel capacity,” Proceedings of the IEEE, vol. 95, no. 6, pp. 1150- 1177, June 2007.

[7] C. Berrou, A. Glavieux, and P. Thitimajshima, “Near Shannon limit error-correcting coding and decoding: Turbo-codes,” in Proc. IEEE Int. Conf. Commun. (ICC), Geneva, Switzerland, May 1993.

[8] D. J. C. MacKay, “Good error-correcting codes based on very sparse matrices,” IEEE Trans. Inf. Theory, vol. 45, no. 2, pp. 399-431, Mar 1999.

[9] T. Richardson, M. Shokrollahi, and R. Urbanke, “Design of capacityapproaching irregular low-density parity-check codes,” IEEE Trans. Inf. Theory, vol. 47, no. 2, pp. 619-637, Feb. 2001.

[10] T. Richardson and R. Urbanke, “The capacity of low-density paritycheck codes under message-passing decoding,” IEEE Trans. Inf. Theory, vol. 47, no. 2, pp. 599-618, Feb. 2001.

[11] M. Luby, M. Mitzenmacher, M. A. Shokrollahi, and D. A. Spielman, “Improved Low-Density Parity-Check Codes Using Irregular Graphs,” IEEE Trans. Inf. Theory, vol. 47, no. 2, pp. 585-598, Feb. 2001.

[12] H. D. Pfister, I. Sason, and R. Urbanke, “Capacity-achieving ensembles for the binary erasure channel with bounded complexity,” IEEE Trans. Inf. Theory, vol. 51, no. 7, pp. 2352-2379, Jul. 2005. [OpenAIRE]

[13] H. D. Pfister and I. Sason, “Accumulate-repeat-accumulate codes: Capacity-achieving ensembles of systematic codes for the erasure channel with bounded complexity,” IEEE Trans. Inf. Theory, vol. 53, no. 6, pp. 2088-2115, June 2007. [OpenAIRE]

[14] E. Arikan, “Channel polarization: A method for constructing capacityachieving codes for symmetric binary-input memoryless channels,” IEEE Trans. Inf. Theory, vol. 55, no. 7, pp. 3051-3073, July 2009.

[15] M. Lentmaier, A. Sridharan, D. Costello, Jr., and K. Zigangirov, “Iterative decoding threshold analysis for LDPC convolutional codes,” IEEE Trans. Inf. Theory, vol. 56, no. 10, pp. 5274-5289, Oct. 2010. [OpenAIRE]

80 references, page 1 of 6
Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue