Blind Interleaver Parameter Estimation From Scant Data

Mingyu Jang,Geunbae Kim,Dongyeong Kim,Dongweon Yoon

doi:10.1109/access.2020.3041795

Abstract

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.

Highlights

In non-cooperative contexts, a receiver cannot identify any information from the received data because the receiver lacks all information about transmission parameters
We estimate the interleaver parameter by comparing rank deficiency distribution of the square submatrices and that of random binary matrices
In this paper, we proposed an improved method for blind estimation of interleaver parameter from scant data

Summary

Introduction

In non-cooperative contexts, a receiver cannot identify any information from the received data because the receiver lacks all information about transmission parameters. To recover information in a non-cooperative context, the receiver has to blindly estimate communication parameters by using only the received data. It is an extensive work requiring much effort to estimate even a single communication parameter. Blind estimation of communication parameters has been researched separately: source coding [1]-[5], channel coding [6]-[11], interleaving [12]-[23], spreading sequence [24]-[26], scrambling [27][29], and modulation [30]-[38]. Reference [14] estimated helical scan interleaver for block channel coded data. [19] proposed a blind estimation method of a convolutional interleaver with denoising algorithm

Methods

Results

Conclusion