An improved adaptive constrained constant modulus reduced-rank algorithm with sparse updates for beamforming
| Autor: | Yunlong Cai, Haijian Zhang, Boya Qin |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
Beamforming
020301 aerospace & aeronautics Mathematical optimization Rank (linear algebra) Computational complexity theory Applied Mathematics Stability (learning theory) 020206 networking & telecommunications 02 engineering and technology Filter (signal processing) Computer Science Applications 0203 mechanical engineering Artificial Intelligence Hardware and Architecture Bounded function Signal Processing 0202 electrical engineering electronic engineering information engineering Constant (mathematics) Algorithm Adaptive beamformer Software Information Systems Mathematics |
| Zdroj: | Multidimensional Systems and Signal Processing. 27:321-340 |
| ISSN: | 1573-0824 0923-6082 |
| Popis: | In this work, we propose an adaptive set-membership (SM) reduced-rank filtering algorithm using the constrained constant modulus criterion for beamforming. We develop a stochastic gradient type algorithm based on the concept of SM techniques for adaptive beamforming. The filter weights are updated only if the bounded constraint cannot be satisfied. We also propose a scheme of time-varying bound and incorporate parameter dependence to characterize the environment for improving the tracking performance. A detailed analysis of the proposed algorithm in terms of computational complexity and stability is carried out. Simulation results verify the analytical results and show that the proposed adaptive SM reduced-rank beamforming algorithms with a dynamic bound achieve superior performance to previously reported methods at a reduced update rate. |
| Databáze: | OpenAIRE |
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