On particle filtering for digital communications
We analyze the problem of joint channel-data estimation in fast fading channels. We propose a hybrid structure which associates the Kalman filter and particle filtering, respectively, for the channel and data estimation. We compare this solution with the classical reduced complexity methods. We show...
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| creator | Bertozzi, T. Le Ruyett, D. Rigal, G. Vu-Thien, H. |
| description | We analyze the problem of joint channel-data estimation in fast fading channels. We propose a hybrid structure which associates the Kalman filter and particle filtering, respectively, for the channel and data estimation. We compare this solution with the classical reduced complexity methods. We show that the application of particle filtering to the discrete state space of the data leads to an approach similar to the T algorithm. Hence, this method cannot improve the trade-off between performance and computational complexity of the classical solutions. We conclude that it is preferable to use particle filtering for the joint estimation of discrete and continuous parameters. |
| doi_str_mv | 10.1109/SPAWC.2003.1319025 |
| format | Conference Proceeding |
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| identifier | ISBN: 9780780378582 |
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| language | eng |
| recordid | cdi_ieee_primary_1319025 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Computational complexity Detectors Digital communication Digital filters Fading Filtering algorithms Finite impulse response filter Monte Carlo methods Sliding mode control State-space methods |
| title | On particle filtering for digital communications |
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