High Gain Coding Schemes for Space Communications

In 1948, Claude E. Shannon showed that forward error correction was able to lower the bit error ratio of a numeric transmission as long as the channel capacity is not exceeded. This discovery lead to amazing progress in the field of telecommunication and today’ s compact–discs, cellular phones, submarines and space probes use error control schemes to make their transmissions reliable. The scientific community has been recently astonished by the discovery f parallel concatenation now referred to as T urbo Codes and its amazing performance and simplicity. In this report, we present another type of concatenation: serial concatenation and we study the properties of a new way to build iterative decoders based on the MAP algorithm. The main aim of this project is to find a way to replace the current coding scheme to be implemented on the NASA space observation probe Galileo. The spacecraft was launched in 1989 and is currently heading to Jupiter . A slightly more powerful error correcting scheme and its associated iterative MAP decoder are described. We also present in this report other powerful codes and the way they were derived.

[1]  Punya Thitimajshima.  Les codes convolutifs récursifs systématiques et leurs applications à la concatenation parallèle , 1993 .

[2]  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.

[3]  S. Dolinar,et al.  Enhanced decoding for the Galileo low-gain antenna mission , 1994, Proceedings of 1994 IEEE International Symposium on Information Theory.

[4]  S. S. Pietrobon.  Implementation and performance of a serial MAP decoder for use in an iterative turbo decoder , 1995, Proceedings of 1995 IEEE International Symposium on Information Theory.

[5]  S. Dolinar.  A New Code for Galileo , 1988 .

[6]  S. S. Pietrobon,et al.  Interleaver design for three dimensional turbo codes , 1995, Proceedings of 1995 IEEE International Symposium on Information Theory.

[7]  Sergio Benedetto,et al.  Unveiling turbo codes: some results on parallel concatenated coding schemes , 1996, IEEE Trans. Inf. Theory.

[8]  Kar-Ming Cheung,et al.  Quantization loss in convolutional decoding , 1993, IEEE Trans. Commun..

[9]  Pierre L'Ecuyer,et al.  Efficient and portable combined random number generators , 1988, CACM.

[10]  John Cocke,et al.  Optimal decoding of linear codes for minimizing symbol error rate (Corresp.) , 1974, IEEE Trans. Inf. Theory.

[11]  S. S. Pietrobon.  Low Rate Convolutional Codes Optimised for Use in Concatenated Codecs , 1994 .

[12]  S. S. Pietrobon,et al.  Terminating the trellis of turbo-codes in the same state , 1995 .

[13]  J. D. Andersen.  'Turbo' coding for deep space applications , 1995, Proceedings of 1995 IEEE International Symposium on Information Theory.

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

[15]  S. S. Pietrobon,et al.  A Simplification of the Modified Bahl Decoding Algorithm for Systematic Convolutional Codes , 1994 .