Hard Decision Decoding Performance Improved Using Turbo Product Codes
DOI:
https://doi.org/10.14419/ijet.v7i3.12.16030Keywords:
MAP decoding, iterations, bit parity, product turbo code, soft decision, hard decision decoder, multiple dimensionsAbstract
The performance of soft decision decoding, whose for which the design is complex, is superior to the performance of hard decision decoding. In this paper, we propose a turbo product code with a bit flip algorithm to improve                                                                                                     the performance of hard decision decoding. The performance of hard decision decoding is improved with low complexity using multidimensional turbo product codes. The reliability of decoding in a communication system to detect and correct errors is discussed .Maximum a posterior probability (MAP) decoding is employed to improve the hard decision performance of turbo product codes with multiple dimensions. Our results include comparisons of multiple dimensions—2D, 3D, 4D, and 5D—and the number of iterations in soft and hard decision decoding.
Â
Â
References
[1] Burr, “Turbo-codes: the ultimate error control codes†in Electronics & Communication EngineeringJournal, vol. 13, pp. 155–165, IEEE, August 2001. ISSN: 0954-0695.
[2] C. Berrou, A.Glaxieux, and P. Thitimajhima, “Near Shannon limiterror-correcting coding and decoding: turbo codes (1),†in IEEE Int Conf. Communications ICC’93, vol. 2/3, May 1993, pp.1064-1071.
[3] P. Elias, “Error-free coding,†IRE Trans. Inform. Theory, vol IT-4, pp. 29-37, Sept. 1954.
[4] R. M. Pyndiah, “Near-optimum decoding of product codes: block turbo codes,†IEEE Trans. Commun, vol 46, pp. 1003-1010, Aug 1998.
[5] J. Lodge, R. Young, P. Hoeher, and J. Hagenauer, “Separable MAP â€filters†for the de-coding of product and concatenated codes,†in Proc. IEEE International Conference on Communications, Geneva, Switzerland, May 1993, pp. 1740–1745.
[6] J. Hagenauer, E. Offer, and L. Papke, “Iterative decoding of binary block and convolutional codes,†IEEE Trans. Inform. Theory, vol 42, pp. 429-445, Mar 1996.
[7] D. M. Rankin and T. A. Gulliver, “Single Parity Check Product Codesâ€, IEEE Trans, on Commun., vol. 49, no. 8, pp. 1354-1362, August 2001.
[8] C.Argon andW.McLaughlin, “An efficient Chase decoder for turbo product codes,†IEEE Trans. Commun., vol. 52, no. 6, pp. 896–898, Jun. 2004
[9] L.Ying-Chang X.Changlong, and L.Wing Seng, “A low complexity decoding algorithm for turbo product codesâ€, IEEE Wireless. Commun., vol. 7, no.1, pp. 43-47, Jan. 2008
[10] S.Zhiping, Z.Liang, F.Xiang, Y.Yang, HIHO Decoding Algorithms of Turbo Product Codes for High Rate Optical Communications, China Communications 2012, Vol. 9, pp. 114-123
[11] M. Baldi, F. Chiaraluce, G. Cancellieri, “Finite-Precision Analysis of Demappers and Decoders for LDPC-coded M-QAM Systemsâ€, IEEE Trans. on Broadcasting, Vol. 55, No. 2, pp. 239-250, June 200
[12] M. Hata., High-speed and robust error correcting code for future mobile communications of High-Dimensional Discrete Torus Knot,International symposium WPMC’01, Aalborg, Denmark, September 2001,
[13] A. J. Al-Dweik, S.L. Goff, B. S.Sharif, A Hybrid Decoder for BlockTurbo Codes, IEEE Transactions on Comm, vol. 57, No. 5, pp. 1229- 1232, May 2009
[14] A. J. Al-Dweik, B. S.Sharif, Non-Sequential Decoding Algorithm for Hard Iterative Turbo Product Codes, IEEE Transactions on Comm, vol.57, No. 6, pp. 1545-1549, June 2009
[15] H. Xu and F. Takawira, “A New Structure of Single Parity Check Product Codesâ€, IEEE Africon, September 2004
[16] D. M. Rankin and T. A. Gulliver, “Single Parity Check Product Codesâ€, IEEE Trans, on Commun., vol. 49, no. 8, pp. 1354-1362, August 2001.
[17] M. Rankin, T. A. Gulliver, “Parallel and Serial Concatenated Single Parity Check Product Codesâ€, EURASIP Journal on Applied Signal Processing, pp. 775-783, January 2005
Downloads
How to Cite
Received date: July 22, 2018
Accepted date: July 22, 2018
Published date: July 20, 2018