Matlab Based Decimeter Design Analysis Wimax Appliacation

IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661,p-ISSN: 2278-8727, Volume 17, Issue 6, Ver. III (Nov – Dec. 2015), PP 56-64
www.iosrjournals.org
DOI: 10.9790/0661-17635664 www.iosrjournals.org 56 | Page
Matlab Based Decimeter Design Analysis Wimax Appliacation
1
Shaveta, 2
Rajesh Mehra
ME Scholar, Associate Professor
Department of Electronics & Communication Engineering, National Institute of Technical Teachers’ Training
& Research Chandigarh, India-160019
Abstract: A Digital down Converter (DDC), which is basically used to convert an intermediate frequency (IF)
signal to its baseband form, forms an integral part of wireless receivers. The major functional blocks of a DDC
constitute a mixer, Numerically Controlled Oscillator (NCO) and an FIR filter chain. In this paper, We can
comparison of two window and see the costs of all Window filters
Keywords: Matlab, Filter, Interpolated,Decimeter,WIMAX
I. Introduction
Two Type of Communication wired and wireless. The invention of wireless communication has been a
boon to mankind. With The Help Of Wireless Communication Information can transmitted from one place to
another, without the use of a External electrical medium. It Is advances technology, information can be
transmitted from one place to another (Ex: Television remote control) to thousands of kilometers (Ex: Radio
communication). This would indeed come at the cost of on-chip area, speed and power where a lot of research is
being carried out to optimize the same . From the past few years wireless telecom technology has achieved
wide popularity across the globe mainly due to high usage of cellular phones . SDR is a wireless interface tech.
that provides compatibility between different communication standards so that they can be utilized into a single
transceiver. Software defined radio (SDR) is an emerging research topic where the reconfiguration of
transceiver architectures is reached by means of software based projects methodologies for all electronic product
lower circuit complexity is always an imported design target since it reduces cost[1]
1.1wimax
WiMAX (Worldwide Interoperability for Microwave Access) WiMAX refers to interoperable
implementations of the IEEE 802.16 family of wireless-networks standards ratified by the WiMAX Forum.
(Similarly, Wi-Fi refers to interoperable implementations of the IEEE 802.11 Wireless LAN standards certified
by the Wi-Fi Alliance.) WiMAX Forum certification permits vendors to sell fixed or mobile products as
WiMAX certified, thus ensuring a level of interoperability with other certified products, as long as they fit the
same profile. The structure of DDC depends upon conversion ratio required for WIMAX systems the
conversion ratio is typically 8 to 10.for this kind of low conversion factor DUC is typically constructed using
FIR filters only are normally used. IEEE 802.16d can be applied in NLOS transmission with frequency between
2-11 GHz and in LOS with frequency between 10-66 GHz. Designer of WIMAX system need to meet a number
of critical requirements such as processing speed, flexibility and time to market and it is these tight requirements
that ultimately drive the selection of hardware platform[2].
1.2FIR Filter
Finite impulse response (FIR) filter is a filter whose impulse response (or response to any finite length
input) is of finite duration, because it settles to zero in finite time. FIR filter is always stable, realizable &
provides a linear phase response under specific condition. These characteristics make FIR Filter attractive to
many filter designers. It requires no feedback , the present input does not depends on previous output.The
numeric error that occur when implementing fir filter in computing arithmetic occur separately with each
calculation. It does not remember its past numeric error,since they have no feedback elements, so any bounded
input results in bounded output.FIR filter is a stable filter as there is nil feedback and every poles are located at
origin and thus they are within the unit circle. The another important aspect of FIR filter is its linear phase
response where the phase response is a linear function of frequency.
To design a filter simply means to select the coefficients such that the system has specific
characteristics. The required characteristics are stated in filter specifications. Most of the time filter
specifications refer to the frequency response of the filter. This paper presents the windowing technique for
designing of FIR Filter. A window is a finite array consisting of coefficients selected to satisfy the desirable
requirements. When designing digital FIR filters using window functions it is necessary to specify:
 A window function to be used and
 The filter order according to the required specifications (selectivity and stopband attenuation).

The different window functions(Rectangular,Hamming, Hanning, Bartlett, Blackman, Kaiser) can be
compared each other and the best filter specification can be obtained .fir filter ′s performance can be analyzed
using multirate filter,enables one to convert a digital signal of a specified sampling rate into another signal with
the desired sampling rate without significantly destroying the signal components of interest.They are suited to
multi-rate applications. By multi-rate, we mean either "decimation"(reducing the sampling rate), "interpolation"
(increasing the sampling rate), or both.Whether decimating or interpolating, the use of FIR Filters allows some
of thecalculations to be omitted, thus providing an important computational efficiency. The principle objective
this paper is to determine the coefficients of the FIR Filters that met desired specifications. The determinations
of coefficients involve channel equalization, system identification using LMS algorithm. This paper is to
investigate the performance of an FIR filter equalizer for data transmission over a channel that causes
intersymbol interference.[3]
II. Digital Down Converter
A digital down converter (DDC) gives the link between the analog RF front end and the digital
baseband of a receiver. The data is demodulated from the high frequency carrier and subsequently the sampling
frequency of the data stream is reduced. The data stream is then compatible with the baseband modem.The
algorithm consists of 3 stages shown in Figure 1:
1. Mixer – A numerically controlled oscillator (NCO) generates two orthogonal sinusoids at the carrier
frequency and these are mixed with the input stream from the analog-digital-converter (ADC).
2. Decimation – The sampling frequency of the intermediate frequency (IF) samples is reduced. Filtering is
needed to guard against aliasing in the decimation process.
3. Channel Filter – Applies pulse shaping to attenuate any out of band energy in the baseband data.Figure 1.
Digital Down Converter Block DiagramThe headings and subheadings, starting with "1.
For this DDC reference design, the sampling rate parameters are given by:
IF: 91.392 MSPS
Baseband: 11.424 MSPS[1]
2.1 Design of NCO
The Numerically Controlled Oscillator has been implemented using the widely used, Look-up Table
(LUT) approach. The NCO produces a cosine signal having IF frequency. The mixer, upon mixing this signal
with the received input signal, produces the baseband frequency signal, which is then fed to the filter chain.[5]
NCO Compiler generates numerically controlled oscillators customized for Altera devices. This particular
design utilizes the oscillators quadrature carrier generators in the I-Q Mixer stage to modulate the I-Q channels
onto orthogonal carriers.[6]
In DDC digital radio receivers often have fast ADC converters delivering large amounts of data; but in
many cases, the signal of interest represents a small proportion of that bandwidth. A DDC permits the rest of
that data to be discarded, allowing more intensive processing to be performed on the signal of interest. As an
example, consider a radio signal lying in the range 39-40MHz. The signal bandwidth is 1MHz. However, it is
often digitised with a sampling rate over 100MHZ, representing in the region of 200Mbyte/second.The DDC
permits us to select the 39-40MHz band, and to transfer its frequency down to baseband. Once this is over, the
sampling rate can be decreased – with a 1MHz bandwidth, a sampling rate of 2.5MHz would be ok - giving a
data rate of only 5Mbyte/second. This is shown in Figure 1.
III. Matlab Based Design And Simulation
The magnitude response of decimator has been derived from MATLAB. It should fulfill spectral mask
regulations otherwise it can lead to interference with other spectrums. The filters are designed using MATLAB
filter design toolbox. Filter design and analysis tool is a powerful source for designing and analyzing filters
immediately. FDA tool equipped you to design digital FIR or IIR filters by setting filters specifications by

importing filters from your MATLAB workspace. FDA tool also gives you tools for analyzing filters such as
magnitude, phase response and step response . The transmit spectral mask for WIMAX is defined in
IEEE802.16-200 standard. Equipment manufacturers of WIMAX are require to ensure that their system
compatiable with spectral mask regulations to prevent interference with other telecommunication devices in
order to have interference free communication possible. This lead to need that filter and power amplifier must
be designed such that no spectral bandwidth beyond allowed channel bandwidth. Decimator can be designed
using filter design tool in MATLAB and we have three stages in total for both of these. First we have single rate
filter giving the pulse shaping and secondly interpolation by factor of 2 and then interpolation by factor of 4
with different low pass filters and window methods. In this we can see the comparison of window method which
decreased the cost of filters and give better band limiting. The 2 decimator filter required very sharp transition
so number of taps required will be large as compared to other two stages. The first filter is used to attenuate the
spectral energy outside the spectral mask, this filter required the sharpest roll off and hence the maximum
numbers of taps. The second filter is associated with rate change of 4 this filter attenuates the spectral images of
baseband data in applies band limiting in DDC [7].
4.1 Nyquist Filter
The Nyquist frequency, named after electronic engineer Harry Nyquist, is half of the sampling
rate of processing system. It is also known as the folding frequency of a sampling system, e.g. folding is
depicted in where fs is the sampling rate and 0.5 fs is the corresponding Nyquist frequency. The black dot plotted
at 0.6 fs represents the amplitude and frequency of a sinusoidal function whose frequency is 60% of the sample-
rate (fs). The other three dots indicate the frequencies and amplitudes of three other sinusoids that would give
the same set of samples as the actual sinusoid that was sampled. The symmetry about 0.5 fs is known as folding.
The Nyquist frequency should not be confused with the Nyquist rate, which is the minimum sampling
rate that satisfies the Nyquist sampling criterion for a given signal or family of signals. The Nyquist rate is
double the maximum component frequency of the function being sampled. For example, the Nyquist rate for the
sinusoid at 0.6 fs is 1.2 fs, which implies that at the fs rate, it is being undersampled. Thus, Nyquist rate is a
property of a continuous-time signal, whereas Nyquist frequency is a property of a discrete-time system.
When the function domain is time, sample rates are usually described in samples/second, and the unit of Nyquist
frequency is cycles/second (hertz). When the function domain is distance, as in an image sampling system, the
sample rate might be dots per inch and the corresponding Nyquist frequency would be in cycles/inch.
4.2kaiser Window
The Kaiser window, also known as the Kaiser-Bessel window, was developed by James Kaiser
at Bell Laboratories. It is a one-parameter family of window functions used for digital signal processing, and is
defined by the formula :
---------(1)
where:
 N is the length of the sequence.
 I0 is the zeroth order Modified Bessel function of the first kind.
 α is an arbitrary, non-negative real number that finds the shape of the window. In the frequency
domain, it finds the trade-off between main-lobe width and side lobe level, which is a central decision
in window design.
When N is an odd number, the peak value of the window is and when N is even, the
peak values are

Fig 2 Kaiser window
4.3Blackman–Harris window
Fig 3 Blackman–Harris window; B = 2.0044
A generalization of the Hamming family, produced by adding more shifted sinc functions, meant to minimize
side-lobe levels.
---------------------(2)
IV. Filter Response And charcterics
0 5 10 15 20 25 30 35 40 45
-70
-60
-50
-40
-30
-20
-10
0
Frequency (Hz)
Magnitude(dB)
Magnitude Response (dB)
Fig 4 Magnitude response of Nquist filter decimator 2 kaiser window

0 5 10 15 20 25 30 35 40 45
-45
-40
-35
-30
-25
-20
-15
-10
-5
0
Frequency (Hz)
Phase(radians)
Phase Response
Fig 5 Phase response of Nquist filter decimator 2 kaiser window
0 0.2 0.4 0.6 0.8 1 1.2
0
0.2
0.4
0.6
0.8
1
Time (seconds)
Amplitude
Step Response
Fig 6 Step response of Nquist filter decimator 2 kaiser window
In this filter, decimator 2 is used at sampling frequency of 91.392 MHz by using Kaiser window. In
this filter there is direct form FIR. The length of filter is 111 and it’s in stable form . The figure shown is linear
phase if yes(type1) . Now we came to the cost of filter which we analyzed in a way that the multipliers which
are being used to design the filter is 85.Adder we used are 84 in this filter. States we used are 110 in this
filter Multiplier and addition per input sample is 85 and 84 respectively.
0 5 10 15 20 25 30 35 40 45
-90
-80
-70
-60
-50
-40
-30
-20
-10
0
Frequency (MHz)
Magnitude(dB)
Fig 7 Magnitude response of Nquist filter decimator 2 blackman window

0 5 10 15 20 25 30 35 40 45
-14
-12
-10
-8
-6
-4
-2
0
Frequency (MHz)
Phase(radians)
Phase Response
Fig 8 Phase response of Nquist filter decimator 2 blackman window
0 10 20 30 40 50 60 70 80 90 100
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Time (nseconds)
Amplitude
Step Response
Fig 9 Step response of Nquist filter decimator 2 blackman window
In this filter, decimator 2 is used at sampling frequency of 91.392 MHz by using blackman window.
In this filter there is direct form FIR. The length of filter is 11 and it’s in stable form . The figure shown is
linear phase if yes(type1) . Now we came to the cost of filter which we analyzed in a way that the multipliers
which are being used to design the filter is 9.Adder we used are 8 in this filter. States we used are 110 in this
filter Multiplier and addition per input sample is 9 and 8 respectively.
0 5 10 15 20
-70
-60
-50
-40
-30
-20
-10
0
Frequency (kHz)
Magnitude(dB)
Fig 10 Magnitude response of Nquist filter decimator 4 kaiser window

0 5 10 15 20
-45
-40
-35
-30
-25
-20
-15
-10
-5
0
Frequency (kHz)
Phase(radians)
Phase Response
Fig 12 Phase response of Nquist filter decimator 4 kaiser window
0 0.5 1 1.5 2
0
0.2
0.4
0.6
0.8
1
Time (mseconds)
Amplitude
Step Response
Fig 13 Step response of Nquist filter decimator 4 kaiser window
In this filter, decimator 4 is used at sampling frequency of 91.392 MHz by using kaiser window. In
this filter there is direct form FIR. The length of filter is 111 and it’s in stable form . The figure shown is linear
phase if yes(type1) . Now we came to the cost of filter which we analyzed in a way that the multipliers which
are being used to design the filter is 85.Adder we used are 84 in this filter. States we used are 110 in this
filter Multiplier and addition per input sample is 21.26 and 21 respectively.
0 5 10 15 20 25 30 35 40 45
-140
-120
-100
-80
-60
-40
-20
0
Frequency (Hz)
Magnitude(dB)
Fig 14 Magnitude response of Nquist filter decimator 4 blackman window

0 5 10 15 20 25 30 35 40 45
-50
-40
-30
-20
-10
0
Frequency (Hz)
Phase(radians)
Phase Response
Fig 15 Phase response of Nquist filter decimator 4 blackman window
0 0.2 0.4 0.6 0.8 1 1.2
0
0.2
0.4
0.6
0.8
1
Time (seconds)
Amplitude
Step Response
Fig 16 Step response of Nquist filter decimator 4 blackman window of frequency
In this filter, decimator 4 is used at sampling frequency of 91.392 MHz by using blackman window.
In this filter there is direct form FIR. The length of filter is 111 and it’s in stable form . The figureshown is
linear phase if yes(type1) . Now we came to the cost of filter which we analyzed in a way that the multipliers
which are being used to design the filter is 85.Adder we used are 84 in this filter. States we used are 110 in
this filter Multiplier and addition per input sample is 85 and 21 respectively
5.1. Performance Comparison
0 5 10 15 20 25 30 35 40 45
-90
-80
-70
-60
-50
-40
-30
-20
-10
0
Frequency (MHz)
Magnitude(dB)
2 blackman
2 kaiser
Fig 17 Comparison of Kaiser and blackman decimator 2

0 5 10 15 20 25 30 35 40 45
-90
-80
-70
-60
-50
-40
-30
-20
-10
0
Frequency (MHz)
Magnitude(dB)
4 kaiser
4 blackman
Fig 18 Comparison of 4 decimator of Kaiser and blackman window
The cost of both the filters along with resource consumption are compared and its results have are
shown in Table1. Hence, the requirement of multipliers and adders are less in case of Blackman FIR Filter, for
same decimator 2 and 4 with Fs =91.31. Both the filters have linear phase and stability.
Description Kaiser window
2 and 4
decimator
Blackman
window 2 and
4 decimator
multipliers 85 85 9 85
Adder 84 84 8 84
NO. States 110 108 10 110
Multiplier per input sample 85 21.26 9 85
Addition per input sample 84 21 8 84
V. Conclusion
In this paper, an analysis and comparison of 2 fractional rate converter use FIR filter and fractional rate converter
use Nyquist FIR filters with decimator 2 and 4 has been presented with sampling frequency 99.31 MHZ and magnitude
response, phase response and impulse response have been observed. The number of adders and multipliers, Filter length are
also on a comparison, hence finding the better one for optimizing area and speed simultaneously. The whole design can be
implemented by using sampling frequency as 99.31 MHz. From the developed design it is clear that the kaiser window is
more cost effective solution of ddc wimax communication systems.
References
[1] Rajesh Mehra, Sumeet Prashar, Design and Analysis of Multirate Filter for Wimax Application International Journal of
Engineering Research and Development Volume 5, Issue 2 (December 2012), PP. 60-63
[3] Shalu Pandey, Surabhi Agrawal,Urvashi Agrahari ‘FIR FILTERIMPLEMENTATION AND ITS PERFORMANCE ANALYSIS’
International Journal of Computer Applications (0975 – 8887) Volume 120, pp-18 , June 2015
[4] Altera (Accelerating DUC & DDC System Designs for WiMAX) may 2007, version 2.2
[5] Shrita G, A.R Aswatha, Design and Implementation of an Efficient 4G Digital down Converter used in Wireless Receiver Systems
International Journal of Computer Applications , Volume 120 ,pp.18, June 2015
[6] Altera (Accelerating DUC & DDC System Designs for WiMAX) may 2007,version 2.2
Authors Profile
Dr. Rajesh Mehra: Dr. Mehra is currently associated with Electronics and Communication Engineering
Department of National Institute of Technical Teachers’ Training & Research, Chandigarh, India since
1996. He has received his Doctor of Philosophy in Engineering and Technology from Panjab University,
Chandigarh, India in 2015. Dr. Mehra received his Master of Engineering from Panjab Univeristy,
Chandigarh, India in 2008 and Bachelor of Technology from NIT, Jalandhar, India in 1994. Dr. Mehra
has 20 years of academic and industry experience. He has more than 325 papers to his credit which are
published in refereed International Journals and Conferences. Dr. Mehra has guided 70 ME thesis and he is also guiding 02
independent PhD scholars in his research areas. He has also authored one book on PLC & SCADA. He has developed 06
video films in VLSI area. His research areas are Advanced Digital Signal Processing, VLSI Design, FPGA System Design,
Embedded System Design, and Wireless & Mobile Communication. Dr. Mehra is member of IEEE and ISTE
SHAVETA she is currently pursuing her masters in electronic and communication from
national instruction of technical teacher training and research Chandigarh , India. She
completed her Bachelors of Engineering degree in electronics and communication from
Himachal Pradesh Technical university, Hamipur, India.

Matlab Based Decimeter Design Analysis Wimax Appliacation

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