OCTOBER 19-20, 2012 - YMCA University of Science & Technology

Proceedings of the National Conference on
Trends and Advances in Mechanical Engineering,
YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012
DESIGN OF IIR BAND PASS FILTER USING TIME DOMAIN
APPROACH
Ruchika Singh 1 ,Munish Vashisht 2
1 Research Scholar, Deptt. of Electrical & Electronics Engineering, YMCA University of Science & Technology,
Faridabad
2 Associate Professor, Deptt. of Electrical & Electronics Engineering, YMCA University of Science &
Technology, Faridabad
Corresponding Author: 1 helloruchi09@yahoo.com munish276@yahoo.com
Abstract
Filter design is the process of designing a filter (in the sense in which the term is used in signal processing,
statistics, and applied mathematics), often a linear shift-invariant filter, that satisfies a set of requirements,
some of which are contradictory. The purpose is to find a realization of the filter that meets each of the
requirements to a sufficient degree to make it useful. The filter design process can be described as an
optimization problem where each requirement contributes with a term to an error function which should be
minimized. Certain parts of the design process can be automated, but normally an experienced electrical
engineer is needed to get a good result.This paper deals with the design and implementation of IIR filter for
wireless communication of a occupied channel. When a user of mobile occupies a channel, it assigns a range
of frequencies for the same channel. For this purpose, we have designed a IIR filter to select a particular
frequency range assigned to a particular channel. In our design, we have designed the appropriate type of band
pass filter to implement this operation.
Key words: IIR filter, Wireless communication, Band pass filter.
1. Introduction
IIR filters are digital filters with infinite impulse response. Unlike FIR filters, they have the feedback (a
recursive part of a filter) and are known as recursive digital filters therefore. For this reason IIR filters have
much better frequency response than FIR filters of the same order. Unlike FIR filters, their phase characteristic
is not linear which can cause a problem to the systems which need phase linearity. For this reason, it is not
preferable to use IIR filters in digital signal processing when the phase is of the essence.
Otherwise, when the linear phase characteristic is not important, the use of IIR filters is an excellent solution.
There is one problem known as a potential instability that is typical of IIR filters only. FIR filters do not have
such a problem as they do not have the feedback. For this reason, it is always necessary to check after the design
process whether the resulting IIR filter is stable or not.
IIR filters can be designed using different methods. One of the most commonly used is via the reference analog
prototype filter. This method is the best for designing all standard types of filters such as low-pass, high-pass,
band-pass and band-stop filters. FIR filters can have linear phase characteristic, which is not typical of IIR
filters. When it is necessary to have linear phase characteristic, FIR filters are the only available solution. In
other cases when linear phase characteristic is not necessary, such as speech signal processing, FIR filters are
not good solution. IIR filters should be used instead. The resulting filter order is considerably lower for the same
frequency response.
The ability to communicate with people on the move has evolved remarkably. People throughout the world have
enthusiastically adopted the new wireless communication methods and services. For past few years, the mobile
radio communication industries have grown by orders of magnitude, fueled by digital and RF circuit fabrication
improvements, new large scale circuit integration, and other miniaturization technologies which makes portable
radio equipment smaller, cheaper and more reliable. Digital switching techniques have facilitated the large-scale
deployment of affordable and easy to use radio communication network [7].
Recursive digital filters have been recognized as a very efficient and powerful implementation of many signalprocessing
applications. While the problem of choosing the coefficients of a nonrecursive digital filter to
approximate a specified magnitude characteristic has been thoroughly explored, the corresponding problem for
recursive digital filter remains open. Design procedures for recursive digital filters generally deal only with the
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