Joint Carrier Frequency Offset and Channel Estimation for Uplink MIMO-OFDMA Systems Using Parallel Schmidt Rao-Blackwellized Par

Joint carrier frequency offset (CFO) and channel estimation for uplink MIMO-OFDMA systems over time-varying channels is investigated. To cope with the prohibitive computational complexity involved in estimating multiple CFOs and channels, pilot-assisted and semi-blind schemes comprised of parallel Schmidt Extended Kalman filters (SEKFs) and Schmidt-Kalman Approximate Particle Filters (SK-APF) are proposed. In the SK-APF, a Rao-Blackwellized particle filter (RBPF) is developed to first estimate the nonlinear state variable, i.e. the desired user's CFO, through the sampling-importance-resampling (SIRS) technique. The individual user channel responses are then updated via a bank of Kalman filters conditioned on the CFO sample trajectories. Simulation results indicate that the proposed schemes can achieve highly accurate CFO/channel estimates, and that the particle filtering approach in the SK-APF outperforms the more conventional Schmidt Extended Kalman Filter. IEEE Transactions on ...

• Type: Journal
• Year: 2010
• Where: TCOM
• Authors: Kyeong Jin Kim, Man-On Pun, Ronald A. Iltis
• Keywords: Electric Research Laboratories, Mitsubishi Electric Research, Schmidt Extended Kalman, Software Engineering, TCOM 2010