Adaptive re-weighting homotopy for sparse beamforming

Fernando Goncalves De Almeida Neto; V. Nascimento; Yury Zakharov; Rodrigo Caiado De Lamare

Adaptive re-weighting homotopy for sparse beamforming

Fernando Goncalves De Almeida Neto, V. Nascimento, Yury Zakharov, Rodrigo Caiado De Lamare

Electronic Engineering

Research output: Contribution to conference › Paper › peer-review

Abstract

In this paper, a complex adaptive re-weighting algorithm based on the homotopy technique is developed and used for beamforming. A multi-candidate scheme is also proposed and incorporated into the adaptive re-weighting homotopy algorithm to choose the regularization factor and improve the signal-to-interference plus noise (SINR) performance. The proposed algorithm is used to minimize the degradation caused by sparsity in arrays with faulty sensors, or when the required degrees of freedom to suppress interference is significantly less than the number of sensors. Simulations illustrate the algorithm's performance.

Original language	English
Pages	1287-1291
Number of pages	5
Publication status	Published - Sept 2014
Event	Signal Processing Conference (EUSIPCO) - Lisbon, Portugal Duration: 1 Sept 2014 → 5 Sept 2014

Conference

Conference	Signal Processing Conference (EUSIPCO)
Country/Territory	Portugal
City	Lisbon
Period	1/09/14 → 5/09/14

Cite this

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title = "Adaptive re-weighting homotopy for sparse beamforming",

abstract = "In this paper, a complex adaptive re-weighting algorithm based on the homotopy technique is developed and used for beamforming. A multi-candidate scheme is also proposed and incorporated into the adaptive re-weighting homotopy algorithm to choose the regularization factor and improve the signal-to-interference plus noise (SINR) performance. The proposed algorithm is used to minimize the degradation caused by sparsity in arrays with faulty sensors, or when the required degrees of freedom to suppress interference is significantly less than the number of sensors. Simulations illustrate the algorithm's performance.",

author = "{Goncalves De Almeida Neto}, Fernando and V. Nascimento and Yury Zakharov and {Caiado De Lamare}, Rodrigo",

year = "2014",

month = sep,

language = "English",

pages = "1287--1291",

note = "Signal Processing Conference (EUSIPCO) ; Conference date: 01-09-2014 Through 05-09-2014",

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TY - CONF

T1 - Adaptive re-weighting homotopy for sparse beamforming

AU - Goncalves De Almeida Neto, Fernando

AU - Nascimento, V.

AU - Zakharov, Yury

AU - Caiado De Lamare, Rodrigo

PY - 2014/9

Y1 - 2014/9

N2 - In this paper, a complex adaptive re-weighting algorithm based on the homotopy technique is developed and used for beamforming. A multi-candidate scheme is also proposed and incorporated into the adaptive re-weighting homotopy algorithm to choose the regularization factor and improve the signal-to-interference plus noise (SINR) performance. The proposed algorithm is used to minimize the degradation caused by sparsity in arrays with faulty sensors, or when the required degrees of freedom to suppress interference is significantly less than the number of sensors. Simulations illustrate the algorithm's performance.

AB - In this paper, a complex adaptive re-weighting algorithm based on the homotopy technique is developed and used for beamforming. A multi-candidate scheme is also proposed and incorporated into the adaptive re-weighting homotopy algorithm to choose the regularization factor and improve the signal-to-interference plus noise (SINR) performance. The proposed algorithm is used to minimize the degradation caused by sparsity in arrays with faulty sensors, or when the required degrees of freedom to suppress interference is significantly less than the number of sensors. Simulations illustrate the algorithm's performance.

M3 - Paper

SP - 1287

EP - 1291

T2 - Signal Processing Conference (EUSIPCO)

Y2 - 1 September 2014 through 5 September 2014

ER -