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The Scientific World Journal
Volume 2014, Article ID 798612, 9 pages
Research Article

Blind Identification of Convolutional Encoder Parameters

School of Mechatronics Engineering and Automation, National University of Defense Technology, Deya Road, Changsha, Hunan 410073, China

Received 13 March 2014; Accepted 5 May 2014; Published 21 May 2014

Academic Editor: Lei Cao

Copyright © 2014 Shaojing Su et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper gives a solution to the blind parameter identification of a convolutional encoder. The problem can be addressed in the context of the noncooperative communications or adaptive coding and modulations (ACM) for cognitive radio networks. We consider an intelligent communication receiver which can blindly recognize the coding parameters of the received data stream. The only knowledge is that the stream is encoded using binary convolutional codes, while the coding parameters are unknown. Some previous literatures have significant contributions for the recognition of convolutional encoder parameters in hard-decision situations. However, soft-decision systems are applied more and more as the improvement of signal processing techniques. In this paper we propose a method to utilize the soft information to improve the recognition performances in soft-decision communication systems. Besides, we propose a new recognition method based on correlation attack to meet low signal-to-noise ratio situations. Finally we give the simulation results to show the efficiency of the proposed methods.