머신러닝을 이용한 인터리버 제원 블라인드 추정

초록

In this paper, we propose a method for blind estimation of interleaver parameter using machine learning under the condition of scant received data. In non-cooperative contexts, since a receiver does not know communication parameters used by a transmitter, it has to estimate the communication parameters from a received data without any prior knowledge about the parameters to recover information from the received data. Specifically, it becomes more challenging under the condition of scant received data. Recently, estimation of interleaver parameter from scant received data has been researched. However, this method requires additional computational complexity in order to achieve an improved estimation performance. To deal with this problem, in this paper, we propose a blind interleaver parameter estimation method using machine learning with low computational complexity and, through computer simulations, we validate that the proposed method show the same estimation performance as in conventional methods with lower computational complexity.

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