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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.
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