A low complexity algorithm of blind estimation of convolutional interleaver parameters

Interleaving plays an important role in many wireless communication systems, which is used to cope with burst errors and improve the reliability of data transmission. In this paper, we propose a new method to blindly estimate the parameters of convolutional interleaver in a non-cooperative context. The proposed method exploits both the property of interleaved stream and the deinterleaving technique. The product of the depth and width of the interleaver is firstly determined by analyzing interleaved data stream. Then the interleaved data stream is let to pass through a series of reconstructed deinterleavers. Thus the delay, the depth and width of the convolutional interleaver can be estimated by analyzing the deinterleaved data streams. Compared with other algorithms, the proposed method significantly reduces the searching scope and improves computational efficiency. Simulation results show that the algorithm has good performance even if errors exist.