Desconvolução autodidata concorrente para beamformers não supervisionados em antenas controladas por reatância

• Ano de defesa: 2007
• Autor(a) principal: Ortolan, Leonardo
• Orientador(a): Castro, Maria Cristina Felippetto de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Pontifícia Universidade Católica do Rio Grande do Sul; Porto Alegre
• Palavras-chave em Português: ENGENHARIA ELÉTRICA; PROCESSAMENTO DE SINAIS - TÉCNICAS DIGITAIS; ANTENAS (ELETRÔNICA); ALGORITMOS
• Link de acesso: http://hdl.handle.net/10923/3137

The electronically steerable parasitic array radiator (ESPAR) is a smart antenna suited for low-cost user terminal applications. Beamforming is achieved by adaptively adjusting the load reactances at parasitic elements surrounding the active central element. The main goal is to establish nulls in the interfering directions of the array radiation pattern. This work presents two new blind beamformers for use with reactance domain controlled arrays, such as ESPAR antennas. The new beamformers are based on the concurrent operation of two stochastic gradient algorithms, one which minimizes a cost function that measures the received signal energy dispersion and other which minimizes the Euclidean distance between the received digital modulation symbols and the ones in the reference constellation. The first algorithm applies the principle of operation of the Concurrent Self-learning Deconvolution Process (CSDP) to the Maximum Moment Criterion (MMC) algorithm. The second algorithm uses the original architecture of the CSDP, which relies upon the Constant Modulus Algorithm (CMA). These two approaches not only evaluate the energy of the received signal, but also the signal phase, needing no transmission of any training sequence. The results show that these two concurrent approaches result not only in a smaller mean square error (MSE) in relation to the reference constellation of the digital modulation but also result in a better signal to interference ratio.