Soft Input Turbo Frequency-Domain Channel Estimation for Single-Carrier Multiuser Detection

Soft decision directed Turbo frequency-domain channel estimation is investigated for single-carrier (SC) multiuser detection. A Kalman filtering based channel estimation algorithm is first proposed under an uncorrelated- channel-tap state space model, which is the optimal linear unbiased channel estimator for the case of interest. Then, a normalized Turbo recursive least-square (RLS) based channel estimation algorithm is proposed for a more realistic channel model. Simulation results show that both the proposed channel estimation algorithms provide a close performance to the case with perfect channel state information (CSI), and outperform the previously proposed Turbo frequency-domain channel estimation in fast fading channels.