Channel Estimation Based On The Particle Filter For Low Voltage Power Line

Power line communication using power network for data transmission,greatly reduce the operating costs and facilitate the connection, and so become apopular research field. In order to realize the accurate signal transmission,OFDM technology with its high bandwidth efficiency, strong anti-interferenceability, resistance to frequency selective fading has been on the power line signalmodulation technology of choice. Channel estimation is the key of OFDM.Based on the introduction of the low voltage power line communicationtechnology development status, the OFDM system basic principle, realizationmethod and advantages and disadvantages are analyzed. Two methods are usedfor OFDM system channel estimation.1. Based on the least mean square adaptive algorithm, LMS algorithm on thebasis of Wiener filter, developed with the steepest descent method. In this paperthis method was used in the OFDM system adaptive channel estimation, and wasimproved on the basis of the traditional adaptive LMS algorithm, Throughintroducing the memory factor established a nonlinear function relationshipbetween the step-size and the error signal. The results indicate that VFSS-LMSalgorithm has smaller error and faster convergence speed than LMS.2. Channel estimation method based on particle filter, which is combined bythe Monte Carlo method and the Recursive Bayesian estimation method. Thispaper establishes a model of AR OFDM, and particle filtering algorithm isapplied to this. Simulation results show that, channel estimation based on particlefilter has better estimation performance than VFSS-LMS.