Two regularization constant selection methods for recursive least squares algorithm with convex regularization and their performance comparison in the sparse acoustic communication channel estimation

Jun-Seok Lim; Wooyoung Hong

doi:10.7776/ASK.2016.35.5.383

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Two regularization constant selection methods for recursive least squares algorithm with convex regularization and their performance comparison in the sparse acoustic communication channel estimation 볼록 규준화 RLS의 규준화 상수를 정하기 위한 두 가지 방법과 희소성 음향 통신 채널 추정 성능 비교

30 September 2016. pp. 383-388

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Abstract

We develop two methods to select a constant in the RLS (Recursive Least Squares) with the convex regularization. The RLS with the convex regularization was proposed by Eksioglu and Tanc in order to estimate the sparse acoustic channel. However the algorithm uses the regularization constant which needs the information about the true channel response for the best performance. In this paper, we propose two methods to select the regularization constant which don’t need the information about the true channel response. We show that the estimation performance using the proposed methods is comparable with the Eksioglu and Tanc’s algorithm.

Keywords

Acoustic communication

Sparse channel

Channel estiamtion

본 논문은 볼록 규준화 RLS(Recursive Least Squares)에 쓰이는 규준화를 위한 상수를 정하는 법을 제안한다. Eksioglu와 Tanc는 희소성 음향 채널 추정을 위해서 볼록 규준화 RLS 알고리즘을 구현하였다. 그러나 이 알고리즘은 더 좋은 추정 성능을 위해서 채널의 참 임펄스 응답 정보가 사용된다. 본 논문에서는 이 같은 참 임펄스 응답 정보가 필요 없는 규준화 상수를 위한 두 가지 선정법을 제안한다. 그리고 제안한 방법을 사용했을 때 Eksioglu와 Tanc의 방법에 필적한 추정 성능을 유지함을 보인다.

키워드

음향 통신

희소성 채널

채널 추정

References

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Information

Publisher :The Acoustical Society of Korea
Publisher(Ko) :한국음향학회
Journal Title :The Journal of the Acoustical Society of Korea
Journal Title(Ko) :한국음향학회지
Volume : 35
No :5
Pages :383-388
Received Date : 2016-07-18
Accepted Date : 2016-09-02
DOI :https://doi.org/10.7776/ASK.2016.35.5.383

The Journal of the Acoustical Society of KoreaISSN:1225-4428(Print) 2287-3775(Online)한국음향학회

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