An Adaptive Fuzzy Filter Based on Two Different Sets for Nonlinear Channel Estimation
The opportune estimation of channel gain in wireless communication is significant to successful power control, but the channel's nonlinear characteristic degrades the performance of conventional estimation method. Based on fuzzy filter theory, a novel adaptive fuzzy least mean square (LMS) filter for channel estimation is proposed. Utilizing the human experiences and statistical knowledge of signal's fading, the filter builds two different type of fuzzy sets over the space of channel gain, which reflect the channel gain's value and its moving trends respectively, then adjusts the parameters of the member functions of the sets with LMS algorithm, thus adapts itself to the nonlinear characteristics of communication channel. The result of simulation experiment validates the efficiency of the algorithm