An inverse QRD-RLS algorithm for linearly constrained minimum variance adaptive filtering

被引：0
|
作者：
Medina S., Cesar A. [1 ]
Sampaio-Neto, Raimundo [1 ]
机构：
[1] Pontif Catholic Univ Rio de Janeiro PUC Rio, Ctr Telecommun Studies CETUC, Rio De Janeiro, Brazil
来源：
SIGNAL PROCESSING | 2013年 / 93卷 / 05期
关键词：
Linearly constrained minimum variance; IQRD-RLS filtering; Constrained RLS; CDMA; Blind receiver estimation; LEAST-SQUARES ALGORITHM;
D O I：
10.1016/j.sigpro.2012.11.002
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper an inverse QR decomposition based recursive least-squares algorithm for linearly constrained minimum variance filtering is proposed. The proposed algorithm is numerically stable in finite precision environments and is suitable for implementation in systolic arrays or DSP vector architectures. Its performance is illustrated by simulations of a blind receiver for a multicarrier CDMA communication system and compared with previously proposed inverse QR decomposition recursive least-squares algorithms. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码：1308 / 1316
页数：9
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