Blind Interleaver Parameter Estimation From Scant Data

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초록

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.

키워드

EstimationLinearityChannel estimationReceiversData modelsConvolutional codesConvolutionBlind detectionnon-cooperative contextremote sensingspectrum surveillanceERROR-CORRECTING CODESMODULATION CLASSIFICATIONESTIMATION ALGORITHMSEQUENCE ESTIMATIONCYCLIC CODESRECONSTRUCTIONIDENTIFICATION
제목
Blind Interleaver Parameter Estimation From Scant Data
저자
Jang, MingyuKim, GeunbaeKim, DongyeongYoon, Dongweon
DOI
10.1109/ACCESS.2020.3041795
발행일
2020-12
유형
Article
저널명
IEEE Access
8
페이지
217282 ~ 217289

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