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This paper proposes a robust reduced-rank scheme for adaptive beamforming based on joint iterative optimization (JIO) of adaptive filters. The novel scheme is designed according to the constant modulus (CM) criterion subject to different…

Information Theory · Computer Science 2013-01-30 Lei Wang , Rodrigo C. de Lamare

This paper proposes a reduced-rank scheme for adaptive beamforming based on the constrained joint iterative optimization of filters. We employ this scheme to devise two novel reduced-rank adaptive algorithms according to the constant…

Information Theory · Computer Science 2013-03-08 Lei Wang , Rodrigo C. de Lamare

This paper presents a low-complexity robust data-dependent dimensionality reduction based on a modified joint iterative optimization (MJIO) algorithm for reduced-rank beamforming and steering vector estimation. The proposed robust…

Information Theory · Computer Science 2014-01-21 P. Li , R. C. de Lamare

This chapter presents reduced-rank linearly constrained minimum variance (LCMV) algorithms based on the concept of joint iterative optimization of parameters. The proposed reduced-rank scheme is based on a constrained robust joint iterative…

Information Theory · Computer Science 2013-02-12 R. C. de Lamare

This paper proposes a new adaptive algorithm for the implementation of the linearly constrained minimum variance (LCMV) beamformer. The proposed algorithm utilizes the set-membership filtering (SMF) framework and the reduced-rank joint…

Information Theory · Computer Science 2013-03-18 Lei Wang , Rodrigo C. de Lamare

This paper presents reduced-rank linearly constrained minimum variance (LCMV) beamforming algorithms based on joint iterative optimization of filters. The proposed reduced-rank scheme is based on a constrained joint iterative optimization…

Other Computer Science · Computer Science 2012-05-22 R. C. de Lamare , L. Wang , R. Fa

In this letter, we propose a novel adaptive reduced-rank strategy based on joint iterative optimization (JIO) of filters according to the minimization of the bit error rate (BER) cost function. The proposed optimization technique adjusts…

Information Theory · Computer Science 2013-02-19 Yunlong Cai , Rodrigo C. de Lamare

This letter proposes a novel adaptive reduced-rank filtering scheme based on joint iterative optimization of adaptive filters. The novel scheme consists of a joint iterative optimization of a bank of full-rank adaptive filters that forms…

Information Theory · Computer Science 2012-05-22 Rodrigo C. de Lamare , Raimundo Sampaio-Neto

In this paper, we propose a novel adaptive reduced-rank strategy for very large multiuser multi-input multi-output (MIMO) systems. The proposed reduced-rank scheme is based on the concept of joint iterative optimization (JIO) of filters…

Information Theory · Computer Science 2013-02-20 Yunlong Cai , Rodrigo C. de Lamare

This paper presents a new adaptive algorithm for the linearly constrained minimum variance (LCMV) beamformer design. We incorporate the set-membership filtering (SMF) mechanism into the reduced-rank joint iterative optimization (JIO) scheme…

Information Theory · Computer Science 2013-02-19 Lei Wang , Rodrigo C. de Lamare

We present a robust adaptive beamforming algorithm based on the worst-case criterion and the constrained constant modulus approach, which exploits the constant modulus property of the desired signal. Similarly to the existing worst-case…

Information Theory · Computer Science 2013-10-02 L. Landau , R. C. de Lamare , M. Haardt

A novel linear blind adaptive receiver based on joint iterative optimization (JIO) and the constrained constant modulus (CCM) design criterion is proposed for interference suppression in direct-sequence ultra-wideband (DS-UWB) systems. The…

Information Theory · Computer Science 2013-05-15 Sheng Li , Rodrigo C. de Lamare

In this work we propose schemes for joint model-order and step-size adaptation of reduced-rank adaptive filters. The proposed schemes employ reduced-rank adaptive filters in parallel operating with different orders and step sizes, which are…

Information Theory · Computer Science 2013-05-17 Rodrigo C. de Lamare , Vitor H. Nascimento

This paper proposes a novel adaptive reduced-rank filtering scheme based on the joint iterative optimization of adaptive filters. The proposed scheme consists of a joint iterative optimization of a bank of full-rank adaptive filters that…

Information Theory · Computer Science 2013-05-29 Rodrigo C. de Lamare , Raimundo Sampaio-Neto

In this work a constrained adaptive filtering strategy based on conjugate gradient (CG) and set-membership (SM) techniques is presented for adaptive beamforming. A constraint on the magnitude of the array output is imposed to derive an…

Information Theory · Computer Science 2013-02-05 L. Wang , R. C. de Lamare

This paper presents novel adaptive reduced-rank filtering algorithms based on joint iterative optimization of adaptive filters. The novel scheme consists of a joint iterative optimization of a bank of full-rank adaptive filters that…

Information Theory · Computer Science 2013-04-30 Rodrigo C. de Lamare , Raimundo Sampaio-Neto

We introduce a new linearly constrained minimum variance (LCMV) beamformer that combines the set-membership (SM) technique with the conjugate gradient (CG) method, and develop a low-complexity adaptive filtering algorithm for beamforming.…

Information Theory · Computer Science 2013-03-06 Lei Wang , Rodrigo C. de Lamare

This paper proposes an auxiliary vector filtering (AVF) algorithm based on a constrained constant modulus (CCM) design for robust adaptive beamforming. This scheme provides an efficient way to deal with filters with a large number of…

Information Theory · Computer Science 2013-03-14 Lei Wang , Rodrigo de Lamare

This paper presents a novel adaptive reduced-rank multi-input-multi-output (MIMO) decision feedback equalization structure based on joint iterative optimization of adaptive estimators. The novel reduced-rank equalization structure consists…

Information Theory · Computer Science 2013-04-30 Rodrigo C. de Lamare , Are Hjorungnes , Raimundo Sampaio-Neto

This work presents cost-effective low-rank techniques for designing robust adaptive beamforming (RAB) algorithms. The proposed algorithms are based on the exploitation of the cross-correlation between the array observation data and the…

Computational Engineering, Finance, and Science · Computer Science 2016-08-24 H. Ruan , R. C. de Lamare
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