Abstract:

A novel particle filter is proposed to estimate the channel response and the frequency offset for uplink multiple input multiple output-orthogonal frequency division multiple access (MIMO-OFDMA) systems. First, the channel response and the frequency offset are described as auto-regressive (AR) model and generalized auto-regressive (GAR) model, respectively. Then the Rao-Blackwellization theory is evolved to reduce the complexity of particle filtering. The frequency offset can be estimated using the particle filter, and the channel response is updated using the Kalman filter. Simulation results show that the proposed scheme has lower block error rate than the regular particle filter, while the processing complexity increases a little.

Key words: carrier frequency offset, channel estimation, particle filter