Skip to Main content Skip to Navigation
New interface
Conference papers

Dual Code Method for Blind Identification of Convolutional Encoder for Cognitive Radio Receiver Design

Mélanie Marazin 1 Roland Gautier 1, * Gilles Burel 1 
* Corresponding author
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance, UBO - Université de Brest
Abstract : Digital communication systems are in perpetual evolution in order to respond to the new user expectations and to new applications transmissions constraints, in term of data rate or reliability. With this fast development of new communication standards, it becomes very difficult for users and also for communications devices producers, to stay compatible with all standards used and with the oncoming ones. For that reason, cognitive radio systems seem to provide an interesting solution to this problem. The conception of intelligent receiver able to adapt itself to a specific transmission context and to blindly estimate the transmitter parameters is a promising solution for the future. In such context, new coding schemes like turbocodes, Low-Density Parity-Check (LDPC) or concatenated codes are developed to increase transmission robustness without significant degradation of the data rate. It is why we have developed a method, described in this paper, dedicated to the blind identification of convolutional encoders usually used in many standards. Moreover, an analysis of the method performances is detailed.
Complete list of metadata
Contributor : Roland Gautier Connect in order to contact the contributor
Submitted on : Friday, May 21, 2010 - 6:28:41 PM
Last modification on : Monday, March 14, 2022 - 11:08:11 AM



Mélanie Marazin, Roland Gautier, Gilles Burel. Dual Code Method for Blind Identification of Convolutional Encoder for Cognitive Radio Receiver Design. 5-th IEEE Broadband Wireless Access Workshop, IEEE GLOBECOM 2009,, Nov 2009, Honolulu, Hawaii, United States. pp.1-6, ⟨10.1109/GLOCOMW.2009.5360726⟩. ⟨hal-00485837⟩



Record views