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Suraj R. Gaikwad et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.560-564

RESEARCH ARTICLE

www.ijera.com

OPEN ACCESS

Review: Design of Highly Efficient Multirate Digital Filters
Suraj R. Gaikwad*, Prof. Gopal Gawande**
*(Department of Electronics Engineering, Amravati university, India)
** (Department of Electronics Engineering, Amravati university, India)

ABSTRACT
In this paper we propose the literature review related to design the multirate digital filters for audio application.
One of the main objectives of this survey paper is to find the comparison between various multirate digital
filters used in audio applications and communications. Another objective is to provide novel approach in order
to help the reader with choosing the most appropriate digital filter for the multirate digital signal processing.
Keywords: Digital Signal Processing, Multirate filter, Sampling rate, FIR and CIC.

I.

INTRODUCTION

In many practical application of digital
signal processing, there is a problem of changing the
sampling rate of a signal, either increasing it or
decreasing it by some amount. For example, in
telecommunication system that transmits and receives
the different types of signals (e.g. fax, speech, video,
etc), there is a requirement to process the various
signals at the different rates with corresponding
bandwidth of the signals. The process of converting a
signal from a given rate to a different rate is called as
“sampling rate conversion” and the systems that
employ multiple sampling rates in the processing of
digital signals are called as “Multirate digital signal
processing system”.
Multirate systems have gained popularity
since the early 1980s and they are commonly used for

Fig. 1 (a) Decimator (b) Interpolator

1.
Sr.
no.
1.

2.

LITERATURE REVIEW
Name
of
Paper
Author
Title/Reference
L.C
Design and
Loong
Development of a
And
Multirate Filters
N.C Kyun
in Software
Defined Radio
Environment [1]

audio and video processing, communications systems,
and transform analysis to name but a few [5]. In most
applications Multirate systems are used to improve
the performance, or for increased computational
efficiency. The two basic operations in a Multirate
system are decreasing (decimation) and increasing
(interpolation) the sampling-rate of a signal. Multirate
systems are sometimes used for sampling-rate
conversion, which involves both decimation and
interpolation [5].

Prasit
Kumar
Bandyopa
dhyay
And
Arindam
Biswas

FPGA Based
High Frequency
Noise Elimination
System From
Speech Signal
Using XILINX
System Generator
[2]

www.ijera.com

Publication
International
Journal of
Engineering
and
Technology,
Vol. 5, No. 2,
2008

Journal of
Electron
Devices, Vol.
17, 2013

Approach
& Concept
about Work
This paper present the
multirate filters design using
SDR concept. Two SDR
models are considered; one
with System Generator and
one which was based on
Matlab Simulink. The results
show that both models can
produce the desired audio
sample rate.
In this paper, they discuss the
implementation
of
FIR
Bandpass Filters on FPGAs
which will eliminate high
frequency noise from audio
speech signal. This paper
describes about the Noise
Extraction system that is
designed in Xilinx System

Advantages
Using SDR concept,
processing can be
done at any
sampling rate,
within a wide range
of rates.

They provide
excellent high
frequency noise
reduction.

Limitations
of
Works
Both models
are operated
at different
sampling
rates.

They required
more number
of hardware
(Multiplier,
Accumulator
and Dual port
RAM).

560 | P a g e
Suraj R. Gaikwad et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.560-564

3.

Rajesh
Mehra
And
Rashmi
Arora

FPGA-Based
Design of HighSpeed CIC
Decimator for
Wireless
Applications [4]

International
Journal of
Advanced
Computer
Science and
Applications,
Vol. 2, No. 5,
2011

4.

Yonghao
Wang and
Joshua
Reiss

Time domain
performance of
decimation filter
architectures for
high resolution
sigma delta
analogue to digital
conversion [9]

Audio
Engineering
Society

5.

Rajesh
Mehra
And
Shaily
Verma

FPGA Based
Design of Direct
Form FIR
Polyphase
Interpolator for
Wireless
Communication

6.

Juha YliKaakinen,
Ming Hu,
Riku
Uusikarta
no, Teemu
Kupiainen
, and
Markku
Renfors

Multirate Digital
Filter Design for a
PAL TV
Modulator [20]

7.

Fredric J.
Harris and
Michael
Rice

Multirate Digital
Filters for Symbol
Timing
Synchronization
in Software
Defined Radios
[3]

www.ijera.com

Convention
Paper 8648
Presented at
the 132nd
Convention
2012 April
International
Journal of
Electrical
Electronics
&Telecommun
ication
Engineering,
2013
IEEE Journals,
June 28, 1999

IEEE Journal
vol. 19, no. 12,
December
2001

Generator software is used to
eliminate high frequency noise
from audio signal.
This paper provided design
and implementation of high
speed CIC decimator for
wireless applications like
GSM. The fully pipelined CIC
decimator is designed with
Matlab, simulated with Xilinx
AccelDSP, synthesized with
Xilinx Synthesis Tool (XST),
and implemented on Virtex-II
based XC2VP50-6 target
FPGA device.

www.ijera.com

It reduces the need
for expensive antialiasing analog
filters. It provides
enhanced
performance in
terms of speed and
area utilization.

The frequency
response is
not accurate.

They present the results of a
comparison
of
different
decimation architectures for
high resolution sigma delta
analogue to digital conversion
in
terms
of
passband,
transition band performance,
simulated signal to noise ratio,
and computational cost.

They provide
excellent
comparison of the
different multirate
filters for low group
delay audio
applications.

They provide
only
theoretical
overview of
different
multirate
filters.

In this paper an Interpolator
has been designed and
simulated by using Direct
Form Polyphase Serial and
Parallel structures to reduce
area and to enhance speed.

The result shows
that serial
interpolator can
enhance speed by
5.6% as compared
to MAC based
design.

They required
more
hardware

This paper develops a
multirate digital filter design
for the Vestigial SideBand
(VSB) modulator required in
the analog TV transmission
systems, like PAL. The
modulator takes as the input
the composite video signal
digitized at 13.5MHz sample
rate and the output is a VSB
signal modulated to the usual
38.9 MHz IF picture carrier
frequency and sampled at
121.5 MHz rate.
This paper describes the use of
a polyphase filter bank to
perform the interpolations
required for symbol timing
synchronization in a sampleddata
receiver.
Maximum
likelihood
timing
synchronization
techniques
can be easily incorporated into
the polyphase filter bank in a
natural way.

The resulting design
has significantly
lower complexity
than in the earlier
designs using FIR
filters and it is quite
feasible for
implementation as
an ASIC or even on
an FPGA circuit.

To avoid
overflow and
to satisfy
round-off
noise
requirements,
three more
additional
bits.

Separate
interpolating filter
following
the
matched filter is not
required.

Necessary of
auxiliary
control to
adjust the
clocking of
data into the
filter bank for
small
differences in
the sample
clock and data
clock.

561 | P a g e
Suraj R. Gaikwad et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.560-564
II.

www.ijera.com

MULTIRATE FILTERS

The role of a filter in decimation and
interpolation is to suppress aliasing and to remove
imaging, respectively. The performance of the
system for sampling rate conversion depends mainly
by filter characteristics. Since an ideal frequency
response is not achievable, the choice of an
appropriate specification is the first step in
designing a proper filter [6].
For decimation and interpolation filters,
and for multirate narrowband filters, additional
efficiency may be achieved by cascading several
stages, each of them consisting of a sub-filter and
down-sampler for decimation and an up-sampler
and subfilter for interpolation [7] and [8].
The finite-impulse response (FIR) filters or infiniteimpulse response (IIR) filters are used for
generating the overall system [6]. In some cases,
both filter types are in use for building the overall
conversion system. The selection of the filter type
depends on the criteria at hand. The advantage of
using linear phase FIR filters is that they preserve
the waveform of the signal components of interest at
the expense of a higher overall complexity
compared to their IIR counterparts. However,
multirate techniques significantly improve the
efficiency of FIR filters that makes them very
desirable in practice [6].
The efficiency of FIR filters for sampling
rate conversion is significantly improved using the
polyphase realization. Filtering is embedded in the
decimation/interpolation process and a polyphase
structure is used to simultaneously achieve the
interpolation/decimation by a given factor but
running at a low data rate.
The polyphase structure is obtained when
an Nth order filter transfer function is decomposed
into M (L) polyphase components, M, L<N. For FIR
filters, polyphase decomposition is obtained simply
by inspection of the transfer function [14], [8], and
[15]. Figure 2 shows the polyphase structures for an
Mto 1 decimator and a 1-to-L interpolator. Due to
the polyphase multirate implementation, the number
of arithmetic operations in a linear phase FIR filter
is decreased by a factor M (or L). An effective
method, which leads to high efficiency for a highorder FIR filter is proposed in [6].
For multirate IIR filters, several approaches
to polyphase decomposition have been developed
[6] and [16]. For a rational conversion factor LIM
an efficient decomposition of the Nth order IIR
filter, based on the method given in [6] is proposed
in [16]. Polyphase IIR filters require lower
computation rates among the known decimators and
interpolators [6]. If a strictly linear phase
characteristic is not requested, an IIR filter is an
adequate choice. Moreover, an IIR transfer function
can be designed to approximate a linear phase in the
pass-band [7], [10] and [14].

www.ijera.com

III.

MULTIRATE COMPLEMENTARY
FILTERS

This method can be used in designing
filters with any pass-band bandwidth. The multirate
techniques are included to reduce the computational
complexity. Using the complementary property, the
multirate, narrow pass-band filter designs can be
used to develop high-pass and low-pass filters with
wide pass-bands [6], [11]. When the output of a
lowpass multirate filter is subtracted from the
delayed replica of the input signal, the result is a
wideband high-pass filter. The delay has to be
selected to exactly equal the group delay of the
multirate filter. For a low-pass wideband filter the
multirate narrowband high-pass filter has to be used.
Efficient FIR filters with an arbitrary bandwidth can
be designed using multirate and complementary
filtering [6], [11].
The overall design is evaluated by
cascading complementary multirate filtering twoports composed of two series branches and one
parallel branch. The cascade is terminated with a
simple kernel filter. One series branch of the
cascade is a decimator (filter and down-sampler),
while the other is an interpolator (up-sampler and
filter). The parallel branch is a delay. The most
efficient solution is obtained when half-band filters
are used in the cascade.

IV.

HALF-BAND FILTERS

Half-band filters are basic building blocks
in multirate systems. A half–band filter divides the
basis band of a discrete-time system in two equal
bands with symmetry properties [11]. The FIR
filters are most often used as half-band filters. For a
linear-phase FIR half-band filter, half of the
constants are zero valued when the filter order is an
even number [8]. A half-band IIR filter can have
562 | P a g e
Suraj R. Gaikwad et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.560-564
fewer multipliers than the FIR filter for the same
sharp cutoff specification.
An IIR elliptic half-band filter when
implemented as a parallel connection of two all-pass
branches is an efficient solution [12]. The main
disadvantage of elliptic IIR filters is their very
nonlinear phase response. To overcome the phase
distortion one can use optimization to design an IIR
filter with an approximate linear phase response or
one can apply the double filtering with the block
processing technique for real-time processing [8].

www.ijera.com

design and development of highly efficient multirate
digital filter in terms of power consumption and
excellent frequency response, the various types of
multirate filters are discuss here.

VII.

CONCLUSION

The multirate filtering techniques are
widely used in sampling rate conversion systems,
and for constructing filters with equal input and
output sampling rates. Various multirate design
techniques provide that the overall filtering
characteristic is shared between several simplified
subfilters that operate at the lowest possible
sampling rates. Hence, by using the multistage
approach, the total number of coefficients is
significantly reduced. Also there are some multirates
filters that are provide the excellent frequency
response with consuming less power.

REFERENCE
[1]

[2]

V.

MULTIPLIERLESS SOLUTION

In [1981], an efficient way of performing
decimation and interpolation was introduced.
Hogenauer devised a exible, multiplier-free filter
suitable for hardware implementation, that can also
handle arbitrary and large rate changes. These are
known as “cascaded integrator comb filters, or CIC
filters” [18].
The efficiency of multirate filters is greatly
improved by simplifying arithmetic operations. This
is achieved by replacing a multiplier with a small
number of shifters-and-adders [13]. Generally,
implementing multiplierless design techniques in
sub-filters, at the cost of a slight derogation of
filtering performances, increases the efficiency of
the overall multirate filter. For instance, one can use
the optimization technique [6], the multiplier block
approach or design based on EMQF (Elliptic
Minimal Q-Factors) transfer functions [13] and [17].
A well-known solution for large conversion factors
in decimation is a cascaded integrated comb (CIC)
filter, which performs multiplierless filtering [6],
[13], [18].

VI.

[3]

[4]

[5]

[6]

[7]

[8]

NEED FOR THE STUDY

Multirate filtering techniques are widely
used in both sampling rate conversion systems and
in constructing filters with equal input and output
rates in the case where the use of a conventional
method becomes extremely costly [6]. Thus to
www.ijera.com

[9]

L.C Loong and N.C Kyun, “Design and
Development of a Multirate Filters in
Software Defined Radio Environment”,
International Journal of Engineering and
Technology, Vol. 5, No. 2, 2008.
Prasit
Kumar
Bandyopadhyay
and
Arindam Biswas, “FPGA Based High
Frequency Noise Elimination System From
Speech Signal Using XILINX System
Generator”, Journal of Electron Devices,
Vol. 17, 2013.
Fredric J. Harris and Michael Rice,
“Multirate Digital Filters for Symbol
Timing Synchronization in Software
Defined Radios”, IEEE Journal vol. 19, no.
12, December 2001.
Rajesh Mehra and Rashmi Arora, “FPGABased Design of High-Speed CIC
Decimator for Wireless Applications”,
International Journal of Advanced
Computer Science and Applications, Vol. 2,
No. 5, 2011.
University of Newcastle upon Tyne,
“Multirate Signal Processing”, EEE305,
EEE801 Part A.
Ljiljana Milic, Tapio Saramaki and Robert
Bregovic,
“Multirate
Filters:
An
Overview”, IEEE Journal, 1-4244-0387,
2006.
L. D. Milic and M.D. Lutovac, “Design
multirate filtering”, Idea Group Publishing,
pp. 105-142, 2002.
S.K. Mitra, “Digital Signal Processing: A
Computer based approach”, The McGrowHill Companies, 2005.
Yonghao Wang and Joshua Reiss, “Time
domain performance of decimation filter
architectures for high resolution sigma
delta analogue to digital conversion”,
Audio Engineering Society Convention
563 | P a g e
Suraj R. Gaikwad et al Int. Journal of Engineering Research and Application
ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.560-564

[10]

[11]

[12]

[13]

[14]

[15]

[16]

[17]

[18]

[19]

[20]

[21]

www.ijera.com

Paper 8648 Presented at the 132nd
Convention, April 2012.
Kester, “Mixed-signal and DSP Design
Techniques. Norwood, MA: Analog
Devices, Ch.3, pp. 16-17. 2000.
Ljiljana D. Milić, “Efficient Multirate
Filtering”, Software & Systems Design,
2009.
Damjanović, S., Milić, L. & Saramäki, T.,
“Frequency transformations in two-band
wavelet IIR filter banks”, Proceedings of
the IEEE Region 8 International
Conference on“Computer as a Tool”,
EUROCON 2005.
Hogenauer, E. “An economical class of
digital filters for decimation and
interpolation”, IEEE Transactions on
Acoustics, Speech and Signal Processing,.
Vol. 29, No. 2, pp. 155-162. 1981
N. J. Fliege, Multirate digital signal
processing, New York: John Wiley & Sons,
1994.
P.P. Vaidyanathan, Multirate systems and
filter banks. Englewood Cliffs, NJ: Prentice
Hall, 1993.
A.I. Russel, "Efficient rational sampling
rate alteration using IIR filters," IEEE
Signal processing Letters, vol. 7, pp. 6-7,
Jan. 2000.
M. D. Lutovac, and L. D. Milic,
"Approximate linear phase multiplierless
IIR half-band filter," IEEE Signal
Processing Letters, vol.7, pp. 52-53, March
2000.
Matthew P. Donadio, “CIC Filter
Introduction”, m.p.donadio@ieee.org ,18
July 2000
Fredric J. Harris and Michael Rice,
“Multirate Digital Filters for Symbol
Timing Synchronization in Software
Defined Radios”, IEEE Journal vol. 19, no.
12, December 2001.
Juha Yli-Kaakinen, Ming Hu, Riku
Uusikartano, Teemu Kupiainen, and
Markku Renfors, “Multirate Digital Filter
Design for a PAL TV Modulator”, IEEE
Journals, June 28, 1999.
Sancho Salcedo-Sanz, Fernando CruzRoldán, Conor Heneghan, and Xin Yao,
“Evolutionary Design of Digital Filters
With Application to Subband Coding and
Data Transmission”, IEEE transactions on
signal processing, vol. 55, no. 4, april 2007

www.ijera.com

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Cr36560564

  • 1. Suraj R. Gaikwad et al Int. Journal of Engineering Research and Application ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.560-564 RESEARCH ARTICLE www.ijera.com OPEN ACCESS Review: Design of Highly Efficient Multirate Digital Filters Suraj R. Gaikwad*, Prof. Gopal Gawande** *(Department of Electronics Engineering, Amravati university, India) ** (Department of Electronics Engineering, Amravati university, India) ABSTRACT In this paper we propose the literature review related to design the multirate digital filters for audio application. One of the main objectives of this survey paper is to find the comparison between various multirate digital filters used in audio applications and communications. Another objective is to provide novel approach in order to help the reader with choosing the most appropriate digital filter for the multirate digital signal processing. Keywords: Digital Signal Processing, Multirate filter, Sampling rate, FIR and CIC. I. INTRODUCTION In many practical application of digital signal processing, there is a problem of changing the sampling rate of a signal, either increasing it or decreasing it by some amount. For example, in telecommunication system that transmits and receives the different types of signals (e.g. fax, speech, video, etc), there is a requirement to process the various signals at the different rates with corresponding bandwidth of the signals. The process of converting a signal from a given rate to a different rate is called as “sampling rate conversion” and the systems that employ multiple sampling rates in the processing of digital signals are called as “Multirate digital signal processing system”. Multirate systems have gained popularity since the early 1980s and they are commonly used for Fig. 1 (a) Decimator (b) Interpolator 1. Sr. no. 1. 2. LITERATURE REVIEW Name of Paper Author Title/Reference L.C Design and Loong Development of a And Multirate Filters N.C Kyun in Software Defined Radio Environment [1] audio and video processing, communications systems, and transform analysis to name but a few [5]. In most applications Multirate systems are used to improve the performance, or for increased computational efficiency. The two basic operations in a Multirate system are decreasing (decimation) and increasing (interpolation) the sampling-rate of a signal. Multirate systems are sometimes used for sampling-rate conversion, which involves both decimation and interpolation [5]. Prasit Kumar Bandyopa dhyay And Arindam Biswas FPGA Based High Frequency Noise Elimination System From Speech Signal Using XILINX System Generator [2] www.ijera.com Publication International Journal of Engineering and Technology, Vol. 5, No. 2, 2008 Journal of Electron Devices, Vol. 17, 2013 Approach & Concept about Work This paper present the multirate filters design using SDR concept. Two SDR models are considered; one with System Generator and one which was based on Matlab Simulink. The results show that both models can produce the desired audio sample rate. In this paper, they discuss the implementation of FIR Bandpass Filters on FPGAs which will eliminate high frequency noise from audio speech signal. This paper describes about the Noise Extraction system that is designed in Xilinx System Advantages Using SDR concept, processing can be done at any sampling rate, within a wide range of rates. They provide excellent high frequency noise reduction. Limitations of Works Both models are operated at different sampling rates. They required more number of hardware (Multiplier, Accumulator and Dual port RAM). 560 | P a g e
  • 2. Suraj R. Gaikwad et al Int. Journal of Engineering Research and Application ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.560-564 3. Rajesh Mehra And Rashmi Arora FPGA-Based Design of HighSpeed CIC Decimator for Wireless Applications [4] International Journal of Advanced Computer Science and Applications, Vol. 2, No. 5, 2011 4. Yonghao Wang and Joshua Reiss Time domain performance of decimation filter architectures for high resolution sigma delta analogue to digital conversion [9] Audio Engineering Society 5. Rajesh Mehra And Shaily Verma FPGA Based Design of Direct Form FIR Polyphase Interpolator for Wireless Communication 6. Juha YliKaakinen, Ming Hu, Riku Uusikarta no, Teemu Kupiainen , and Markku Renfors Multirate Digital Filter Design for a PAL TV Modulator [20] 7. Fredric J. Harris and Michael Rice Multirate Digital Filters for Symbol Timing Synchronization in Software Defined Radios [3] www.ijera.com Convention Paper 8648 Presented at the 132nd Convention 2012 April International Journal of Electrical Electronics &Telecommun ication Engineering, 2013 IEEE Journals, June 28, 1999 IEEE Journal vol. 19, no. 12, December 2001 Generator software is used to eliminate high frequency noise from audio signal. This paper provided design and implementation of high speed CIC decimator for wireless applications like GSM. The fully pipelined CIC decimator is designed with Matlab, simulated with Xilinx AccelDSP, synthesized with Xilinx Synthesis Tool (XST), and implemented on Virtex-II based XC2VP50-6 target FPGA device. www.ijera.com It reduces the need for expensive antialiasing analog filters. It provides enhanced performance in terms of speed and area utilization. The frequency response is not accurate. They present the results of a comparison of different decimation architectures for high resolution sigma delta analogue to digital conversion in terms of passband, transition band performance, simulated signal to noise ratio, and computational cost. They provide excellent comparison of the different multirate filters for low group delay audio applications. They provide only theoretical overview of different multirate filters. In this paper an Interpolator has been designed and simulated by using Direct Form Polyphase Serial and Parallel structures to reduce area and to enhance speed. The result shows that serial interpolator can enhance speed by 5.6% as compared to MAC based design. They required more hardware This paper develops a multirate digital filter design for the Vestigial SideBand (VSB) modulator required in the analog TV transmission systems, like PAL. The modulator takes as the input the composite video signal digitized at 13.5MHz sample rate and the output is a VSB signal modulated to the usual 38.9 MHz IF picture carrier frequency and sampled at 121.5 MHz rate. This paper describes the use of a polyphase filter bank to perform the interpolations required for symbol timing synchronization in a sampleddata receiver. Maximum likelihood timing synchronization techniques can be easily incorporated into the polyphase filter bank in a natural way. The resulting design has significantly lower complexity than in the earlier designs using FIR filters and it is quite feasible for implementation as an ASIC or even on an FPGA circuit. To avoid overflow and to satisfy round-off noise requirements, three more additional bits. Separate interpolating filter following the matched filter is not required. Necessary of auxiliary control to adjust the clocking of data into the filter bank for small differences in the sample clock and data clock. 561 | P a g e
  • 3. Suraj R. Gaikwad et al Int. Journal of Engineering Research and Application ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.560-564 II. www.ijera.com MULTIRATE FILTERS The role of a filter in decimation and interpolation is to suppress aliasing and to remove imaging, respectively. The performance of the system for sampling rate conversion depends mainly by filter characteristics. Since an ideal frequency response is not achievable, the choice of an appropriate specification is the first step in designing a proper filter [6]. For decimation and interpolation filters, and for multirate narrowband filters, additional efficiency may be achieved by cascading several stages, each of them consisting of a sub-filter and down-sampler for decimation and an up-sampler and subfilter for interpolation [7] and [8]. The finite-impulse response (FIR) filters or infiniteimpulse response (IIR) filters are used for generating the overall system [6]. In some cases, both filter types are in use for building the overall conversion system. The selection of the filter type depends on the criteria at hand. The advantage of using linear phase FIR filters is that they preserve the waveform of the signal components of interest at the expense of a higher overall complexity compared to their IIR counterparts. However, multirate techniques significantly improve the efficiency of FIR filters that makes them very desirable in practice [6]. The efficiency of FIR filters for sampling rate conversion is significantly improved using the polyphase realization. Filtering is embedded in the decimation/interpolation process and a polyphase structure is used to simultaneously achieve the interpolation/decimation by a given factor but running at a low data rate. The polyphase structure is obtained when an Nth order filter transfer function is decomposed into M (L) polyphase components, M, L<N. For FIR filters, polyphase decomposition is obtained simply by inspection of the transfer function [14], [8], and [15]. Figure 2 shows the polyphase structures for an Mto 1 decimator and a 1-to-L interpolator. Due to the polyphase multirate implementation, the number of arithmetic operations in a linear phase FIR filter is decreased by a factor M (or L). An effective method, which leads to high efficiency for a highorder FIR filter is proposed in [6]. For multirate IIR filters, several approaches to polyphase decomposition have been developed [6] and [16]. For a rational conversion factor LIM an efficient decomposition of the Nth order IIR filter, based on the method given in [6] is proposed in [16]. Polyphase IIR filters require lower computation rates among the known decimators and interpolators [6]. If a strictly linear phase characteristic is not requested, an IIR filter is an adequate choice. Moreover, an IIR transfer function can be designed to approximate a linear phase in the pass-band [7], [10] and [14]. www.ijera.com III. MULTIRATE COMPLEMENTARY FILTERS This method can be used in designing filters with any pass-band bandwidth. The multirate techniques are included to reduce the computational complexity. Using the complementary property, the multirate, narrow pass-band filter designs can be used to develop high-pass and low-pass filters with wide pass-bands [6], [11]. When the output of a lowpass multirate filter is subtracted from the delayed replica of the input signal, the result is a wideband high-pass filter. The delay has to be selected to exactly equal the group delay of the multirate filter. For a low-pass wideband filter the multirate narrowband high-pass filter has to be used. Efficient FIR filters with an arbitrary bandwidth can be designed using multirate and complementary filtering [6], [11]. The overall design is evaluated by cascading complementary multirate filtering twoports composed of two series branches and one parallel branch. The cascade is terminated with a simple kernel filter. One series branch of the cascade is a decimator (filter and down-sampler), while the other is an interpolator (up-sampler and filter). The parallel branch is a delay. The most efficient solution is obtained when half-band filters are used in the cascade. IV. HALF-BAND FILTERS Half-band filters are basic building blocks in multirate systems. A half–band filter divides the basis band of a discrete-time system in two equal bands with symmetry properties [11]. The FIR filters are most often used as half-band filters. For a linear-phase FIR half-band filter, half of the constants are zero valued when the filter order is an even number [8]. A half-band IIR filter can have 562 | P a g e
  • 4. Suraj R. Gaikwad et al Int. Journal of Engineering Research and Application ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.560-564 fewer multipliers than the FIR filter for the same sharp cutoff specification. An IIR elliptic half-band filter when implemented as a parallel connection of two all-pass branches is an efficient solution [12]. The main disadvantage of elliptic IIR filters is their very nonlinear phase response. To overcome the phase distortion one can use optimization to design an IIR filter with an approximate linear phase response or one can apply the double filtering with the block processing technique for real-time processing [8]. www.ijera.com design and development of highly efficient multirate digital filter in terms of power consumption and excellent frequency response, the various types of multirate filters are discuss here. VII. CONCLUSION The multirate filtering techniques are widely used in sampling rate conversion systems, and for constructing filters with equal input and output sampling rates. Various multirate design techniques provide that the overall filtering characteristic is shared between several simplified subfilters that operate at the lowest possible sampling rates. Hence, by using the multistage approach, the total number of coefficients is significantly reduced. Also there are some multirates filters that are provide the excellent frequency response with consuming less power. REFERENCE [1] [2] V. MULTIPLIERLESS SOLUTION In [1981], an efficient way of performing decimation and interpolation was introduced. Hogenauer devised a exible, multiplier-free filter suitable for hardware implementation, that can also handle arbitrary and large rate changes. These are known as “cascaded integrator comb filters, or CIC filters” [18]. The efficiency of multirate filters is greatly improved by simplifying arithmetic operations. This is achieved by replacing a multiplier with a small number of shifters-and-adders [13]. Generally, implementing multiplierless design techniques in sub-filters, at the cost of a slight derogation of filtering performances, increases the efficiency of the overall multirate filter. For instance, one can use the optimization technique [6], the multiplier block approach or design based on EMQF (Elliptic Minimal Q-Factors) transfer functions [13] and [17]. A well-known solution for large conversion factors in decimation is a cascaded integrated comb (CIC) filter, which performs multiplierless filtering [6], [13], [18]. VI. [3] [4] [5] [6] [7] [8] NEED FOR THE STUDY Multirate filtering techniques are widely used in both sampling rate conversion systems and in constructing filters with equal input and output rates in the case where the use of a conventional method becomes extremely costly [6]. Thus to www.ijera.com [9] L.C Loong and N.C Kyun, “Design and Development of a Multirate Filters in Software Defined Radio Environment”, International Journal of Engineering and Technology, Vol. 5, No. 2, 2008. Prasit Kumar Bandyopadhyay and Arindam Biswas, “FPGA Based High Frequency Noise Elimination System From Speech Signal Using XILINX System Generator”, Journal of Electron Devices, Vol. 17, 2013. Fredric J. Harris and Michael Rice, “Multirate Digital Filters for Symbol Timing Synchronization in Software Defined Radios”, IEEE Journal vol. 19, no. 12, December 2001. Rajesh Mehra and Rashmi Arora, “FPGABased Design of High-Speed CIC Decimator for Wireless Applications”, International Journal of Advanced Computer Science and Applications, Vol. 2, No. 5, 2011. University of Newcastle upon Tyne, “Multirate Signal Processing”, EEE305, EEE801 Part A. Ljiljana Milic, Tapio Saramaki and Robert Bregovic, “Multirate Filters: An Overview”, IEEE Journal, 1-4244-0387, 2006. L. D. Milic and M.D. Lutovac, “Design multirate filtering”, Idea Group Publishing, pp. 105-142, 2002. S.K. Mitra, “Digital Signal Processing: A Computer based approach”, The McGrowHill Companies, 2005. Yonghao Wang and Joshua Reiss, “Time domain performance of decimation filter architectures for high resolution sigma delta analogue to digital conversion”, Audio Engineering Society Convention 563 | P a g e
  • 5. Suraj R. Gaikwad et al Int. Journal of Engineering Research and Application ISSN : 2248-9622, Vol. 3, Issue 6, Nov-Dec 2013, pp.560-564 [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] www.ijera.com Paper 8648 Presented at the 132nd Convention, April 2012. Kester, “Mixed-signal and DSP Design Techniques. Norwood, MA: Analog Devices, Ch.3, pp. 16-17. 2000. Ljiljana D. Milić, “Efficient Multirate Filtering”, Software & Systems Design, 2009. Damjanović, S., Milić, L. & Saramäki, T., “Frequency transformations in two-band wavelet IIR filter banks”, Proceedings of the IEEE Region 8 International Conference on“Computer as a Tool”, EUROCON 2005. Hogenauer, E. “An economical class of digital filters for decimation and interpolation”, IEEE Transactions on Acoustics, Speech and Signal Processing,. Vol. 29, No. 2, pp. 155-162. 1981 N. J. Fliege, Multirate digital signal processing, New York: John Wiley & Sons, 1994. P.P. Vaidyanathan, Multirate systems and filter banks. Englewood Cliffs, NJ: Prentice Hall, 1993. A.I. Russel, "Efficient rational sampling rate alteration using IIR filters," IEEE Signal processing Letters, vol. 7, pp. 6-7, Jan. 2000. M. D. Lutovac, and L. D. Milic, "Approximate linear phase multiplierless IIR half-band filter," IEEE Signal Processing Letters, vol.7, pp. 52-53, March 2000. Matthew P. Donadio, “CIC Filter Introduction”, m.p.donadio@ieee.org ,18 July 2000 Fredric J. Harris and Michael Rice, “Multirate Digital Filters for Symbol Timing Synchronization in Software Defined Radios”, IEEE Journal vol. 19, no. 12, December 2001. Juha Yli-Kaakinen, Ming Hu, Riku Uusikartano, Teemu Kupiainen, and Markku Renfors, “Multirate Digital Filter Design for a PAL TV Modulator”, IEEE Journals, June 28, 1999. Sancho Salcedo-Sanz, Fernando CruzRoldán, Conor Heneghan, and Xin Yao, “Evolutionary Design of Digital Filters With Application to Subband Coding and Data Transmission”, IEEE transactions on signal processing, vol. 55, no. 4, april 2007 www.ijera.com 564 | P a g e