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In this work, we propose a novel adaptive reduced-rank strategy based on joint interpolation, decimation and filtering (JIDF) for large multiuser multiple-input multiple-output (MIMO) systems. In this scheme, a reduced-rank framework is…

Information Theory · Computer Science 2013-03-18 Y. Cai , R. C. 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

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 work presents generalized low-rank signal decompositions with the aid of switching techniques and adaptive algorithms, which do not require eigen-decompositions, for space-time adaptive processing. A generalized scheme is proposed to…

Information Theory · Computer Science 2013-04-09 R. C. de Lamare

We present a tutorial on reduced-rank signal processing, design methods and algorithms for dimensionality reduction, and cover a number of important applications. A general framework based on linear algebra and linear estimation is employed…

Information Theory · Computer Science 2015-08-05 Rodrigo C. de Lamare

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

This paper presents a novel adaptive reduced-rank {multi-input multi-output} (MIMO) equalization scheme and algorithms based on alternating optimization design techniques for MIMO spatial multiplexing systems. The proposed reduced-rank…

Information Theory · Computer Science 2013-01-15 Rodrigo C. de Lamare , Raimundo Sampaio-Neto

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 paper proposes a novel distributed reduced--rank scheme and an adaptive algorithm for distributed estimation in wireless sensor networks. The proposed distributed scheme is based on a transformation that performs dimensionality…

Information Theory · Computer Science 2014-11-06 S. Xu , R. C. de Lamare , H. V. Poor

This paper presents novel adaptive space-time reduced-rank interference suppression least squares algorithms based on joint iterative optimization of parameter vectors. The proposed space-time reduced-rank scheme consists of a joint…

Information Theory · Computer Science 2013-01-15 Rodrigo C. de Lamare , Raimundo Sampaio-Neto

In this work, decision feedback (DF) detection algorithms based on multiple processing branches for multi-input multi-output (MIMO) spatial multiplexing systems are proposed. The proposed detector employs multiple cancellation branches with…

Information Theory · Computer Science 2013-08-14 R. 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

This paper presents a novel distributed low-rank scheme and adaptive algorithms for distributed estimation over wireless networks. The proposed distributed scheme is based on a transformation that performs dimensionality reduction at each…

Information Theory · Computer Science 2017-10-03 Rodrigo C. de Lamare

Symbol-level precoding is a new paradigm for multiuser downlink systems which aims at creating constructive interference among the transmitted data streams. This can be enabled by designing the precoded signal of the multiantenna…

Information Theory · Computer Science 2017-04-12 Maha Alodeh , Symeon Chatzinotas , Bjorn Ottersten

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

Rate splitting (RS) is a potentially powerful and flexible technique for multi-antenna downlink transmission. In this paper, we address several technical challenges towards its practical implementation for beyond 5G systems. To this end, we…

Information Theory · Computer Science 2020-02-19 Zheng Li , Chencheng Ye , Ying Cui , Sheng Yang , Shlomo Shamai

An adaptive joint power allocation (JPA) and linear receiver design algorithm using the minimum bit error rate (MBER) criterion for a cooperative Multiple-Input Multiple-Output (MIMO) network is proposed. The system employs multiple relays…

Information Theory · Computer Science 2013-03-21 Tong Peng , Rodrigo C. de Lamare , Anke Schmeink

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 work proposes a blind adaptive reduced-rank scheme and constrained constant-modulus (CCM) adaptive algorithms for interference suppression in wireless communications systems. The proposed scheme and algorithms are based on a two-stage…

Information Theory · Computer Science 2013-01-10 Rodrigo C. de Lamare , Raimundo Sampaio-Neto , Martin Haardt

In this paper, we propose a novel reduced-rank adaptive filtering algorithm by blending the idea of the Krylov subspace methods with the set-theoretic adaptive filtering framework. Unlike the existing Krylov-subspace-based reduced-rank…

Information Theory · Computer Science 2013-06-28 R. C. de Lamare , M. Yukawa , I. Yamada
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