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For flat fast fading Multiple-Input Multiple-Output(MIMO) channels,this paper presents a sampling based channel estimation and an iterative Particle Filter(PF) signal detection scheme. The channel estimation is comprised of two parts:the adaptive iterative update on the channel distribution mean and a regular update on the “adaptability” via pilot. In the detection procedure,the PF is employed to produce the optimal decision given the known received signal and the sequence of the channel samples,where an asymptotic optimal importance density is constructed,and in terms of the asymptotic update order,the Parallel Importance Update(PIU) and the Serial Importance Update(SIU) scheme are performed respectively. The simulation results show that for the given fading channel,if an appropriate pilot mode is selected,the proposed scheme is more robust than the conventional Kalman filter based superimposed detection scheme.
For flat fast fading Multiple-Input Multiple-Output (MIMO) channels, this paper presents a sampling based channel estimation and an iterative Particle Filter (PF) signal detection scheme. The channel estimation is comprised of two parts: the adaptive iterative update on the channel of distribution mean and a regular update on the “adaptability” via pilot. In the detection procedure, the PF is employed to produce the optimal decision given the known received signal and the sequence of the channel samples, where an asymptotic optimal importance density is constructed, and in terms of the asymptotic update order, the Parallel Importance Update (PIU) and the Serial Importance Update (SIU) scheme are performed respectively. The simulation results show that for the given fading channel, if an appropriate pilot mode is selected , the proposed scheme is more robust than the conventional Kalman filter based superimposed detection scheme.