Open Access Open Access  Restricted Access Subscription Access

Performance Analysis of Different Inverse Filter Design Techniques


Affiliations
1 School of Electronics Engineering, V.I.T. University, Vellore, T.N., India
2 Department of Electronics Engineering, P.V.P.I.T., Budhgaon, Sangli, Maharashtra, India
 

In modern communication technology design of inverse filter i.e. channel equalizer on receiver side is important in order to combat the effects of channel distortion. In this paper we address different approaches of inverse filter design. The different approaches used are based on second order statistics methods such as Shank’s algorithm, Wiener-Hopf equations (both FIR and IIR), LMS algorithm. We have have modeled communication channel as FIR filter as most of the communication channels can be modeled as FIR channel and followed above mentioned approaches to design an inverse filter in order to get back best estimate of original source signal. Simulation results show performance of these with respect to computational complexity, inverse filter order and SNR vs. BER plots. Above effects have been observed for different channel distortion values.

Keywords

Inverse Filter, Channel Equalization, Least Square Method, Wiener-Hopf Equations, Wiener IIR Filters, LMS Algorithm.
User
Notifications
Font Size

Abstract Views: 94

PDF Views: 0




  • Performance Analysis of Different Inverse Filter Design Techniques

Abstract Views: 94  |  PDF Views: 0

Authors

R. Kulkarni Pranav
School of Electronics Engineering, V.I.T. University, Vellore, T.N., India
A. V. Datar
Department of Electronics Engineering, P.V.P.I.T., Budhgaon, Sangli, Maharashtra, India
Ajinkya Deshmukh
School of Electronics Engineering, V.I.T. University, Vellore, T.N., India
R. D. Patil
Department of Electronics Engineering, P.V.P.I.T., Budhgaon, Sangli, Maharashtra, India

Abstract


In modern communication technology design of inverse filter i.e. channel equalizer on receiver side is important in order to combat the effects of channel distortion. In this paper we address different approaches of inverse filter design. The different approaches used are based on second order statistics methods such as Shank’s algorithm, Wiener-Hopf equations (both FIR and IIR), LMS algorithm. We have have modeled communication channel as FIR filter as most of the communication channels can be modeled as FIR channel and followed above mentioned approaches to design an inverse filter in order to get back best estimate of original source signal. Simulation results show performance of these with respect to computational complexity, inverse filter order and SNR vs. BER plots. Above effects have been observed for different channel distortion values.

Keywords


Inverse Filter, Channel Equalization, Least Square Method, Wiener-Hopf Equations, Wiener IIR Filters, LMS Algorithm.