Turbo-codes: the ultimate error control codes?

Turbo-codes have attracted a great deal of interest since their discovery in 1993. This paper reviews the reasons for this, in particular their attainment of the ultimate limits of the capacity of a communication channel. The paper describes the two fundamental concepts on which they are based: concatenated coding and iterative decoding. This latter is the real 'turbo-principle', which is the real secret of their remarkable performance. The paper also reviews the direction of research in this area since 1993, and shows that, far from bringing coding research to an end, turbo-codes have led to a renaissance. In particular, other applications of the 'turbo-principle' have emerged, and these are discussed, along with the practical applications of turbo-codes that have appeared, from mobile radio to deep-space exploration.

[1]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[2]  Robert J. McEliece,et al.  RA Codes Achieve AWGN Channel Capacity , 1999, AAECC.

[3]  Peter Elias,et al.  Error-free Coding , 1954, Trans. IRE Prof. Group Inf. Theory.

[4]  Alister G. Burr Modulation and Coding for Wireless Communications , 2001 .

[5]  H. De Man,et al.  Adaptive turbo decoding for indoor wireless communication , 1998, 1998 URSI International Symposium on Signals, Systems, and Electronics. Conference Proceedings (Cat. No.98EX167).

[6]  Ramesh Pyndiah,et al.  Near-optimum decoding of product codes: block turbo codes , 1998, IEEE Trans. Commun..

[7]  A. Glavieux,et al.  Near Shannon limit error-correcting coding and decoding: Turbo-codes. 1 , 1993, Proceedings of ICC '93 - IEEE International Conference on Communications.

[8]  Shu Lin,et al.  Error control coding : fundamentals and applications , 1983 .

[9]  P. G. Farrell Coding as a cure for communication calamities: the successes and failures of error control , 1990 .

[10]  S. Brink Convergence of iterative decoding , 1999 .

[11]  Gérard Battail We Can Think of Good Codes, and Even Decode Them , 1993 .

[12]  X. Jin Factor graphs and the Sum-Product Algorithm , 2002 .

[13]  D.J.C. MacKay,et al.  Good error-correcting codes based on very sparse matrices , 1997, Proceedings of IEEE International Symposium on Information Theory.

[14]  C. Shannon Probability of error for optimal codes in a Gaussian channel , 1959 .

[15]  Robert G. Gallager,et al.  Low-density parity-check codes , 1962, IRE Trans. Inf. Theory.

[16]  Alister G. Burr Block versus trellis: an introduction to coded modulation , 1993 .