Full text
| |
| Author(s): |
Murilo Bellezoni Loiola
Total Authors: 1
|
| Document type: | Doctoral Thesis |
| Press: | Campinas, SP. |
| Institution: | Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação |
| Defense date: | 2009-05-18 |
| Examining board members: |
Renato da Rocha Lopes;
Paulo Sergio Ramirez Diniz;
Richard Demo Souza;
Amauri Lopes;
Michel Daoud Yacoub
|
| Advisor: | Renato da Rocha Lopes; João Marcos Travassos Romano |
| Abstract | |
In this work we use Kalman filters to estimate time-varying wireless channels in multiple-input, multiple-output (MIMO) systems. First, we propose an optimal estimator (in the minimum mean squared error sense) to track flat channels in orthogonal space-time block coded systems. Due to the orthogonality inherent to these codes, the Kalman filter equations can be simplified. We also show that the channel estimates provided by the proposed estimator correspond to weighted sums of instantaneous maximum likelihood channel estimates. For constant modulus signal constellations, we propose a steady-state Kalman filter. The proposed steady-state Kalman filter suffers negligible performance degradation compared to the optimal Kalman filter while requiring just a fraction of its complexity. After that, we propose an extended Kalman filter-based receiver that jointly performs the estimation of time-varying frequency-selective MIMO channels and the detection of transmitted signals in spatial multiplexing systems. Finally, we adapt this joint estimator to a turbo receiver. Therefore, the joint estimator can benefit from the error correction capabilities of channel codes to iteratively improve channel and signal estimates (AU) | |