A Fractional Variable Partial Update Least Mean Square Algorithm (FVPULMS) for Communication Channel Estimation

Abstract

The study presents a study on communication channel estimation algorithms. Fractional Variable Partial Update Least Mean Square algorithm (FVPULMS) is proposed. The model consists of input signal, unknown channel, an adaptive filter and an adaptation algorithm. The adaptive filter is a finite impulse response transversal adaptive filter. The adaptation algorithm is a FVPULMS algorithm and the filter update uses coefficient with index factors of three and five. The proposed algorithm was compared with Variable Partial Update Least Mean Square (VPULMS) and Full Update Least Mean Square (FULMS) algorithms. The simulation was carried out using fixed step sizes and variable step sizes of (). The result showed that FVPULMS algorithm has enhanced average performance efficiency in terms of estimated signal error reduction at the receiver station compared with VPULMS and FULMS algorithms, and can help to achieve improved signal error at the receiver station.