| Paper: | SPTM-P12.12 | ||
| Session: | Adaptive Systems and Filtering I | ||
| Time: | Friday, May 19, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Signal Processing Theory and Methods: Adaptive Systems and Filtering | ||
| Title: | Low Complexity Blind Constrained Data-Reusing Algorithms Based on Minimum Variance and Constant Modulus Criteria | ||
| Authors: | Tiago Vinhoza, Pontifícia Universidade Católica do Rio de Janeiro, Brazil; Rodrigo de Lamare, University of York, United Kingdom; Raimundo Sampaio-Neto, Pontifícia Universidade Católica do Rio de Janeiro, Brazil | ||
| Abstract: | This work presents low complexity blind constrained data-reusing adaptive filtering algorithms based on the minimum variance and the constant modulus cost functions. Constrained constant modulus (CCM) and constrained minimum variance (CMV) affine projection type algorithms are developed and investigated in a CDMA interference suppression scenario. Computer simulations analyze the proposed techniques and compare them with existing stochastic gradient (SG) and recursive least-squares (RLS) type techniques. The results show that the new algorithms outperform previously reported SG techniques with small additional computational requirements and achieve a performance very close to RLS algorithms at a much inferior complexity. | ||
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