Blind recovery of k/n rate convolutional encoders in a noisy environment

In order to enhance the reliability of digital transmissions, error correcting codes are used in every digital communication system. To meet the new constraints of data rate or reliability, new coding schemes are currently being developed. Therefore, digital communication systems are in perpetual evolution and it is becoming very difficult to remain compatible with all standards used. A cognitive radio system seems to provide an interesting solution to this problem: the conception of an intelligent receiver able to adapt itself to a specific transmission context. This article presents a new algorithm dedicated to the blind recognition of convolutional encoders in the general k/n rate case. After a brief recall of convolutional code and dual code properties, a new iterative method dedicated to the blind estimation of convolutional encoders in a noisy context is developed. Finally, case studies are presented to illustrate the performances of our blind identification method.

[1]  Antoine Valembois,et al.  Detection and recognition of a binary linear code , 2001, Discret. Appl. Math..

[2]  Sebastien Houcke,et al.  Algebraic Approach for the Reconstruction of Linear and Convolutional Error Correcting Codes , 2008 .

[3]  Sébastien Houcke,et al.  Blind detection of interleaver parameters , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[4]  Janis Dingel,et al.  Parameter Estimation of a Convolutional Encoder from Noisy Observations , 2007, 2007 IEEE International Symposium on Information Theory.

[5]  G. David Forney,et al.  Structural analysis of convolutional codes via dual codes , 1973, IEEE Trans. Inf. Theory.

[6]  Feng-hua Wang,et al.  A Method for Blind Recognition of Convolution Code Based on Euclidean Algorithm , 2007, 2007 International Conference on Wireless Communications, Networking and Mobile Computing.

[7]  Roland Gautier,et al.  Blind recovery of the second convolutional encoder of a turbo-code when its systematic outputs are punctured , 2008 .

[8]  Nicolas Sendrier,et al.  Reconstruction of convolutional codes from noisy observation , 2009, 2009 IEEE International Symposium on Information Theory.

[9]  R. Gautier,et al.  Dual Code Method for Blind Identification of Convolutional Encoder for Cognitive Radio Receiver Design , 2009, 2009 IEEE Globecom Workshops.

[10]  Eric Filiol Reconstruction of Convolutional Encoders over GF(q) , 1997, IMACC.

[11]  Rolf Johannesson,et al.  Fundamentals of Convolutional Coding , 1999 .

[12]  Johann Barbier,et al.  Reconstruction of turbo-code encoders , 2005, SPIE Defense + Commercial Sensing.

[13]  R. Brualdi,et al.  Handbook Of Coding Theory , 2011 .

[14]  G. David Forney,et al.  Convolutional codes I: Algebraic structure , 1970, IEEE Trans. Inf. Theory.