Particle filtering for joint data-channel estimation in fast fading channels

In this paper, we propose to use the particle filtering methods in order to estimate jointly the data and the channel coefficients in fast fading conditions. We compare the obtained reduced complexity maximum likelihood detector with the state-of-the-art solution represented by the per-survivor processing (PSP) detector. We show that the proposed particle detector (PD) presents a better trade-off between performance and computational complexity than the reduced complexity PSP detector. Moreover, we observe that the computational complexity of the PD is adapted according to the signal-to-noise ratio.