A method for blind estimation of interleaver parameter was recently reported which made additional data from a limited amount of received data. However, the process of making additional data creates undesirable linearity which degrades estimation performance. Promise for improved estimation therefore lies in enhancing blind estimation of interleaver parameter without making additional data. In this paper, we propose an improved method to blindly estimate interleaver parameter under the condition of scant data. We first generate a matrix by using the received data. From this matrix we then make square submatrices and obtain their rank deficiency distribution. Finally, we estimate the interleaver parameter by comparing the rank deficiency distribution of the square submatrices and that of random binary matrices. Through computer simulations, we validate the proposed method in terms of detection probability and the number of false alarms. Simulation results show that the proposed method works better than the conventional method given scarce received data.
In a non-cooperative context, a sequence acquired from remote sensing through satellites and aircraft can be recognized as an unknown sequence to a receiver who lacks the information of the transmission parameters. Therefore, the transmission parameters have to be estimated to reconstruct the unknown sequence. This paper focuses on the estimation of an interleaving period among transmission parameters and proposes an improved method to blindly estimate the interleaving period. Through computer simulations, we validate the method by analyzing the estimation performance in terms of the detection probability and the false alarm probability in a fading channel.
In non-cooperative contexts, one needs to estimate communication parameters by using collected data without any prior information. Particularly, when collecting only a limited number of data, estimation becomes a more challenging task. This paper presents a method for estimation of interleaver parameter when only a limited number of collected data are available. We first create additional data by combining a limited number of collected data. We then investigate the rank deficiency of the matrices composed of the collected and additionally-created data. Finally, we estimate the interleaver parameter by using the difference of average rank deficiencies. Through computer simulations, we validate the proposed method in terms of detection probability and the number of false alarms.
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