This document summarizes a research paper that describes implementing an OFDM transceiver using software-defined radio (SDR). It combines channel coding and clipping techniques to reduce peak-to-average power ratio (PAPR) in OFDM for WiMAX applications. The paper implements the SDR using GNU Radio for software and USRP N210 for hardware. It analyzes the effects of clipping threshold and number of clips on PAPR reduction and out-of-band radiation. Experimental results show that clipping significantly reduces PAPR as the clipping level and filtering increase. Channel coding is also analyzed and shown to improve bit error rate performance.

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Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013
Channel Coding and Clipping in OFDM for WiMAX
using SDR
B. Siva Kumar Reddy 1 and B. Lakshmi 2
1
Department of Electronics and Communication Engineering,
National Institute of Technology Warangal, Andhra Pradesh-506004, India.
Email: bsivakumar100@gmail.com
2
Department of Electronics and Communication Engineering,
National Institute of Technology Warangal, Andhra Pradesh-506004, India.
Email: lkodali93@gmail.com
tal Signal Processor (DSP) and Field Programmable Gate Array (FPGA) are used to build up the software radio elements.
The fundamental architecture of SDR is shown in Fig. 1. It
includes front-end, processing engine and application. The
Radio Frequency (RF) front-end module digitizes the radio
frequency data from antennas. After the baseband is digitized by front-end, the processing engine changes baseband
data and date frames. The application side receives data
frames at last.
Abstract— Recent developments in broadband wireless
technology heightened the need for WiMAX which assures
high-speed data services. Mobile WiMAX is grounded on
orthogonal frequency division multiplexing/orthogonal
frequency division multiplexing Access (OFDM/OFDMA)
technology which is an increasing important technique in
LTE systems. This paper describes the OFDM transceiver
implementation using software-defined radio system (SDR).
A SDR is a radio communication system where elements have
been generally implemented in hardware are rather
implemented by software on a personal computer. In this paper,
the software part is realized using GNU Radio and the
hardware part is implemented using USRP N210. OFDM poses
a problem of a Peak to Average Power Ratio (PAPR) or high
crest factor. To stave off this problem either High Power
Amplifiers (HPAs) with large dynamic range or PAPR reduction
techniques are used. The former scheme raises cost of the
system, while the latter induces redundancy or distortion.
This paper presents a novel architecture (which combines
channel coding and clipping) for the PAPR reduction and
analyzes various parameters which effects the performance
of OFDM such as power spectral density, the crest factor and
BER. Channel coding part is framed of three steps
randomization, Forward Error Correction (FEC) and
interleaving. In clipping, certain threshold limits the
amplitude of time domain samples. Without filtering, clipping
causes out-of-band radiation. The paper analyzes the out band
radiation value (at 2.395 GHz) and PAPR reduction with respect
to clipping threshold value. This scheme is preferred because
of its lower complexity and hence would be cheaper to
implement than conventional reduction techniques.
Experimental results prove that the clipping method reduced
PAPR significantly as the number of clip and filtering level is
increased.
Figure 1: Fundamental architecture of Software Defined Radio
(SDR)
In recent years, there has been an increasing interest in
WiMAX (Worldwide Interoperability for Microwave Access)
[2] technology that provides performance similar to Wi-Fi
(IEEE 802.11) networks with the coverage and QoS (quality
of service) of mobile networks. WiMAX can provide
broadband wireless access (BWA) up to 50 km for fixed
stations (called as Fixed WiMAX (IEEE 802.16d)), and 5-15
km for mobile stations (called as Mobile WiMAX (IEEE
802.16e-2005)). This BWA technology is based on Orthogonal
Frequency Division Multiplex (OFDM) technology [3] and
considers the radio frequency range up to 2-11 GHz and 1066 GHz. This provides strong performance in multipath and
non-line-of-sight (NLOS) environments. Mobile WiMAX
extends the OFDM PHY layer to support efficient multipleaccess (known as scalable OFDMA (Orthogonal Frequency
Division Multiple Access)) [3]. Scalability is carried out by
altering the FFT size from 128 to 512, 1024, and 2048 to support
channel bandwidths of 1.25 MHz, 5 MHz, 10 MHz and 20
MHz respectively.
In a single carrier communication system, to avoid intersymbol interference (ISI), the symbol period must be
maintained greater than the delay time. Having long symbol
periods means low data rate and communication inefficiency
because data rate is inversely proportional to symbol period.
Index Terms—BER, Clipping, Coding, OFDM, OFDMA, SDR,
WIMAX.
I. INTRODUCTION
One of the most significant current discussions in the
communications is Software Defined Radio (SDR) [1]. SDR is
pertained to as a digitally programmable platform that can be
programmed to realize multiple wireless standards (GSM, WCDMA, Wi-Fi, WiMAX, etc). SDR has potential to realize the
structure of the device with high mobility, reconfigurability
and flexibility. In SDR, General-Purpose Processor (GPP), Digi
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OFDM is a multicarrier multiplexing digital communication
scheme to solve both issues, where data is transmitted
through several parallel frequency subchannels at a lower
rate. OFDM has become one of the most important building
block in the area of modern broadband wireless networks for
the following reasons: i) tolerance to multipath propagation
and frequency selective fading ii) high spectral efficiency
and iii) impulse noise rejection. However, a major problem
with this kind of application is high Peak to Average Power
ratio (PAPR). To reduce PAPR ratio, Channel coding [4] and
clipping [5] have been considered.
Recently, researchers have shown an increased interest
in Channel coding [4] which plays a vital role in the
performance of OFDM system. The role of channel coding in
conjunctive with frequency and time interleaving is to furnish
a link between bits transmitted on separated carriers of the
signal spectrum, in such a way that the data expressed by
faded carriers can be rebuilt in the receiver. Clipping is a
nonlinear process [5]. Thus, it must be executed in a controlled
manner to prevent any signal distortion. The results of
clipping are in-band distortion and out-of-hand distortion.
In-band distortion or the degradation in the wanted signal
strength happens since clipping modifies the signal artificially.
Clipping an over sampled signal induces lesser effect of
distortion to the signal within the original band. This is because
oversampling shortens the effect of clipping noise in the
required signal by spreading them in a wider bandwidth. By
acting clipping on an oversampled signals also resulted in a
lesser peak regrowth. The out-of-band radiation can be
reduced by performing frequency domain filtering [6]. This
filtering results in a lesser peak regrowth and also completely
decimates the out-of-band radiation thus allowing the original
unclipped signal to be retrieved. This paper will focus on the
description of the proposed novel architecture is shown in
Fig. 2, which combines Channel coding and Clipping
techniques for PAPR reduction for WiMAX.
software development toolkit that offers signal processing
blocks to implement Software Defined Radios (SDR). The
USRP [8] will digitize the incoming data from the air and passing it to the GNU Radio through the USB or Ethernet interface. GNU Radio will further process (demodulating and filtering) the signal until the signal is translated to a stream of
data or packet. In GNU Radio, all signal processing is done
through flow graphs, which consists of blocks. A block does
transforming, decoding, filtering, adding signals, hardware
access or many others. Data passes between blocks in various formats, complex or real integers, floats or basically any
kind of data type user can define. Every flow graph demands
at least one sink and source. In GNU Radio, signal processing blocks are written in C++ and they are connected by
using Python. SWIG (Simplified Wrapper and Interface Generator) is used as an interface compiler between C++ and
Python language [7]. GRC is a signal flow chart generator
tool in GNU Radio. Signal flow chart is built through the GUI
tool and also follow-up the source code to function this flow.
Each block has a relative parameter XML file, GRC will automatically identify the block’s definition when it is executing.
In other words, GRC has the automatic recognition error ability.
Figure 2: Novel Architecture composes of channel coding and
clipping
IV. OFDM TRNSEIVER MODEL
The rest of the paper is structured as follows. Section II
and III introduce the software and hardware platform
realizations for for SDR respectively. In Section IV, the system
model is presented by focussing the attention on OFDM
PHY layer used in WiMAX standords. Section V examine the
effect of clipping and channel coding on PAPR reduction. In
Section VI, numerical results evaluating impacts of various
parameters on PAPR, in-band and out-of band distortion,
BER. Some literature survey also has done here. Finally, the
paper has concluded in Section VI.
OFDM is one of the most widely used technique in LTE
(Long Term Evaluation) system. In OFDM, spectrally coincided sub-carriers can be used and since they are orthogonal, they do not interfere with each other. This causes OFDM
a bandwidth efficient modulation scheme [3]. OFDM is a technique as shown in Fig. 3, where the input data is converted to
parallel bits and mapped according to predefined standard.
Inverse Fast Fourier Transform (IFFT) is a part to convert
signal from frequency domain to time domain. After IFFT the
parallel data is again converted to serial data. Before it gets
converted from digital to analog data, Cyclic prefix is also
added. The input data should be prepared preserving specific standard. In the IFFT mapping, the total subcarriers in
frequency domain are converted to time domain. In order to
preserve the orthogonally of OFDM signal, preamble bits are
II. GNU RADIO COMPANION
Recent developments in the field of SDR have led to a
renewed interest in GNU Radio [7], which is a free and opensource
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III. UNIVERSAL SOFTWARE RADIO PERIPHERAL
USRP is a flexible hardware platform for the development
of SDRs [8]. Any USRP board consists of a motherboard and
daughterboard. In this paper, a network series USRP N210 is
suggested, because of its high-bandwidth, high-dynamic
range processing capability. This board includes a Xilinx
Spartan 3A-DSP 3400 FPGA, 100 MS/s dual ADC (Analog to
Digital Converter), 400 MS/s dual DAC (Digital to Analog
Converter) and Gigabit Ethernet connectivity to stream data
to and from host processors. The USRP N210 can stream up
to 50 MS/s to and from host applications. The FPGA (Field
Programmable Gate Array) also offers the potential to process
up to 100 MS/s in both transmit and receive directions. The
USRP N210 operates from DC to 6 GHz and an expansion port
allows using in MIMO configuration.

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Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013
added. Also the cyclic prefix enables synchronization as the
bits are used to detect the beginning and end of each frame
and it appends the OFDM symbols one after another. At the
receiver side, do reverse processes to demodulate the received sequences of data bits.
(3)
E[|Sn|2] is average power of transmitted symbol. Oversampling
is necessary to get right values of PAPR and it can be
performed by plodding IFFT source data with zeros. The time
domain signal is normally oversampled by factor of four or
greater.
The channel encoder includes three stages: data scrambling,
convolution coding, and data interleaving [4]. The data
scrambler uses generator polynomial S(x) = x7 + x4 + 1 with
“all ones” (1111111) as the initial state. The 127-bit binary
sequence is employed repeatedly to be XORed with the data
bit sequence. The output of the scrambler is shipped to a rate
1/2, K = 7 convolutional encoder with generator polynomials
g0 = 1338 (1011011) and g1 = 1718 (1111001) the encoded data
bits are then handed to an interleaver with the block size
representing to the number of bits in a single OFDM symbol.
The interleaver is defined by a two-step permutation. The
first permutation insures that the adjacent coded bits are
mapped onto nonadjacent subcarriers, while the second
permutation insures that the adjacent coded bits are mapped
alternately onto less and more significant bits of the
constellation and, thereby, long runs of low reliability (LSB)
bits are avoided. If the code rate is k/n, then k bits per second
input to the convolutional encoder and the output is n bits
per second.
QAM64 data symbols are passed through an inverse fast
Fourier transform (IFFT) module to realize the OFDM
modulation. If the digital OFDM signals are clipped instantly,
the resulting clipping noise will be fall in-band and may not
be reduced by filtering. Data symbols are sent through an
inverse fast Fourier transform (IFFT) module to realize the
OFDM modulation. In addition, the complex-valued baseband
OFDM signal is regulated up to a carrier frequency equal to
1/4 of the sampling frequency to descend the implementation
complexity. Then, the real-valued bandpass samples x, are
clipped at an amplitude A as follows [6]:
Figure 3: OFDM Transciever block diagram
OFDM symbol consists of N subcarriers which have
constant spacing Δf. Bandwidth of the signal is B= Δf.N and
symbol time T=1/ Δf. This conducts to sum of N sinsoids in
the time domain, that have exactly an integer number of cycles
in the intervel T. Each subcarrier is regulated by complex
value Xm,n , where m refers symbol index and n subcarrier
index.
M-th OFDM symbol can be defined as [5]:
(1)
where gn(t) = exp(j2πnΔft), for 0 d” t d”T and
gn(t) = 0, for other t.
Time domain signal is defined as sum of symbols [5]:
(2)
The complex value Xm,n based on partial modulation
(Usually M-PSK or M-QAM is used).
(4)
V. CHANNEL CODING AND CLIPPING
The novel architecture combines the use of channel
coding and Clipping method as shown in Fig. 2. These
channel codes improve the bit error rate performance by
appending redundant bits in the conveyed bit stream that
are used by the receiver to correct errors introduced by the
channel [4]. OFDM contains of lots of independent modulated
subcarriers (without considering coding). That causes to
problem with peak to average power ratio. If N subcarriers
are in phase with same symbols regulated on all subcarriers,
the peak power is N times average power. For sampled signal,
PAPR can be defined [9]:
© 2013 ACEEE
DOI: 01.IJRTET.9.1.526
In the following discussion, we will use a normalized clipping
level, which we call the clipping ratio (CR = A/α, where α is
the rms level of the OFDM signal). It is easy to show that, for
an OFDM signal with N subchannels, α =
baseband signal α =
N for a
N / 2 and for a bandpass signal. In
the following discussion, we will use a normalized clipping
level, which we call the clipping ratio (CR = A/α, where α is
the rms level of the OFDM signal). A CR of 1.4 denotes that
the clipping level is about 3 dB higher than the rms level.
Filtering after clipping is required to reduce the out-of-band
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Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013
clipping noise. Filtering after clipping is required to reduce
the out-of-band clipping noise [5].
TABLE I. SNR I N D B WITH AND WITHOUT ENCODER FOR QPSK
SNR (in dB)
AWGN
VI. EXPERIMENTAL RESULTS
SUI-1
SUI-2
With Encoder
5
5
5
Without Encoder
WiMAX confirms a various modulation and Forward Error
Correction (FEC) coding schemes and grants the scheme per
a user based on channel conditions accordingly. This causes
to Adaptive modulation and coding [10] which is an effective
mechanism to maximize throughput, fairness and BER
performance in a continuously time-varying channel. Figs 4,
5 and 6 present the effectiveness of encoding on AWGN,
SUI-1 and SUI-2 channel models. Simulation results show
the advantage of convolutional coding and for the QPSK
digital modulation scheme [11]. The Table 1 depicts the BER
under QPSK modulation technique over AWGN, SUI-1 and
SUI-2 fading channel with encoder for a SNR value of 5dB
but in the case of without encoder is found SNR value of
9dB, 10dB and 8dB respectively [11]. As shown in Fig. 7, the
BER performance has been improved for coded signal (due
to channel coding) than uncoded signal [12].
9
10
8
Figure. 7. BER performance for coded and uncoded signal [12]
One of the simple and effective PAPR reduction
techniques is clipping, which cancels the signal components that outperform some unchanging amplitude called
clip level [5]. However, clipping affords distortion power,
which called clipping noise, and elaborates the transmitted
signal spectrum, which causes interfering. The technique of
iterative clipping and filtering reduces the PAPR without
spectrum expansion. However, the iterative signal carries
long time and it will gain the computational complexity of
an OFDM transmitter. But without performing interpolation
before clipping causes it out-of-band. To avoid out-of band,
signal should be clipped after interpolation. However, this
induces significant peak re-growth. So, it can employ iterative clipping and frequency domain filtering to avoid peak regrowth. Fig. 8 depicts the power spectral density (PSD) of
the Mobile WiMAX MC-OFDMA-256-QAM clipped signal.
The in-band signal attenuation as well as the out-of band
induced by clipping is apparent. In Normal OFDMA the outof band noise emission power is only 30 dB lower than the
signal power. But With hard clipping ratio CR= 0.5 and after
applying the filtering, it is observed that the spectral
sidelobes after filtering are at least 25 dB lower than the signal mainlobe [13]. Fig. 9 shows the effect of clipping level on
PAPR reduction. As clipping level increases, the PAPR reduction increases [14].
The discussed above two techniques ([11], [12] and [13])
are combined to get both the advantages in terms of BER and
PAPR reduction in novel approach. The experimental setup
has a USRP N210 platform and a General Purpose Processor
(laptop) is shown in Fig. 10. The required OFDM parameters
for WiMAX specifications have been shown in Table 2. The
flow graph of novel architecture is Source—>Scrambling—
>Convolutional Coding—>Interleaving—>OFDM block—
>Rail Clipping—>Multiply Const—>Channel Model—>Sink,
shown in Fig. 11. OFDM modulator modulates an OFDM
Figure 4. BER performance under AWGN channel for QPSK [11]
Figure 5. BER performance under SUI 1 channel for QPSK
Figure 6. BER performance under SUI 2 channel for QPSK
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Figure 10. Experimental setup for the development of Software
Defined Radio (SDR)
TABLE II. EXPERIMENTAL PARAMETERS DEFINED
Parameters
FFT size (NFFT)
Occupied Tones
Sampling rate
Center Frequency
Figure 8. PSD of Normal-OFDMA and MC-OFDMA for WiMAX2 5 6QAM
Convolutional Code
Cyclic Prefix length
Values
1024
840
10.66667M
2.48 GHz
1/2
184
Useful symbol duration
91.43 µs
Carrier spacing (1/Tu)
10.94 KHz
Guard time (Tg=(1/4)* Tu)
OFDM symbol duration
Mapping Schemes
From the experimental results, it can be observed that
OFDM signal is has higher PAPR (Shown in Figs. 12 and 13)
and after applying the proposed method, PAPR has been
reduced significantly (Shown in Figs. 14 and 15). The
amplitude clipping is simple method with minimal computing
complexity. The clipping is followed by filtering to reduce
out of band power. Figs 16, 17, 18 and 19 show the average
64QAM-OFDM signals with Clipping Thresholds (CT) 0.2,
0.6, 3 and 5 respectively. It can be concluded that the
difference between out-of band and in-band radiation has
been increased as clipping level increased. So, the selection
of clipping threshold value is carefully taken. The clipping is
the easiest technique to reduce the power by setting a
maximum level for the transmitted signal [5]. Though, this
technique has several disadvantages:
i) The performance of BER could be affected negatively due
to the in-band distortion caused by the clipping.
ii) Also out-of-band radiation usually appears with clipping
technique that could disturb the adjacent channels. However,
we can use filtering operation to decrease the appearance of
the out-of-band radiation but the signal may exceed the
maximum level of the clipping operation.
On the other hand, the BER performance is worsen badly
at it gets better when the CR get higher as shown in Fig. 20.
It is clear that the performance of the BER get worse as the
CR gets lower [15].
Figure 9. Clipping level effect on PAPR in OFDM [14]
stream based on the configurability such as FFT length, occupied tones, and cyclic prefix length. This block creates
OFDM symbols using specified modulation scheme (here in
64-QAM) shown in Fig. 11. The USRP N210 is connected as
source and captured a signal at 2.46 GHz from the environment using VERT 2450 antenna and the processing has done
using XCVR 2450 daughterboard in USRP. WiMAX PHY layer
processing has done in GNU Radio [7], shown in Fig. 11.
© 2013 ACEEE
DOI: 01.IJRTET.9.1.526
11.43 µs
102.86 µs
BPSK, 4QAM, 16QAM
and 256QAM
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Figure 11. GNU Schematic for the implementation of Channel coding and clipping for mobile WiMAX
TABLE III. OBTAINED RESULTS FOR MOBILE WIMAX WITH C HANNEL CODING AND C LIPPING USING SDR
Clipping
Threshold
Value (CT)
5
3
2
1
0.8
0.6
0.4
0.2
Scope Sink
Peak to peak Amp
(in counts)
-900 to +900
-850 to +850
-800 to +800
-500 to +500
-400 to +400
-300 to +300
-200 to +200
-100 to +100
Average Amp
(in counts)
-200 to +200
-200 to +200
-200 to +200
-200 to +200
-200 to +200
-200 to +200
-180 to +180
-100 to +100
FFT sink
Peak to peak Amp
Average Amp
(in db)
(in db)
4 to 32
16 to 28
5 to 32
19 to 26
5 to 31
18 to 26
5 to 29
18 to 24
10 to 28
16 to 23
5 to 24
16 to 23
5 to 21
15 to 20
-5 to 15
8 to 15
Table 3 shows (Where β = Out of band radiation at
2.395GHz, γ = Difference between out-of- band and in band
radiation), as clipping threshold value (CT) decreases, out of
band value is increased and the difference between in band
radiation to out of band radiation is decreased. So it can be
concluded that there is a tradeoff between clipping threshold
and out of band radiation. In FFT sink peak to peak amplitude
value and average amplitude values are increased as CT value
increases. Out of band radiation value has been controlled
by filtering [5]. Fig. 21 shows, particularly fast way of
calculating auto-correlations [16]. Table 4 shows the
comparison of various PAPR reduction techniques, each
© 2013 ACEEE
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PAPR
β
(in db)
γ
(in db)
20.25
18.06
16
6.25
4
2.25
1.11
1
-13
-10
-5
2
3
5
6
8
37
35
28
18
14
10
5
2
technique has its own advantages and disadvantages. A
proper PAPR reduction technique selection is based on the
application.
Through our SDR platform consists of GNU Radio
software [7] and USRP hardware device [8], we can
dynamically adjust the central frequency of the digital data
communication service and choose the unlicensed band as
long as we want. Because GNU Radio provides high
instantaneous and accurate spectrum sensing ability, we can
efficiently utilize SDR to achieve digital data communication
under the current limited spectrum resource. Due to simple
complexity, clipping technique is preferred more.
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Figure 12. Without clipping, 64QAM-OFDM signal on Scope sink
Figure 15. Peak to Peak OFDM signal at CT=0.8 on FFT sink
Figure 13. Without clipping, 64QAM-OFDM signal on FFT sink
Figure 16. Average OFDM signal at CT=0.2 for 64-QAM mod
scheme
Figure 14. Clipped signal at CT=0.6 on scope plot
Figure 17. Average OFDM signal at CT=0.6 for 64-QAM mod
scheme
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Int. J. on Recent Trends in Engineering and Technology, Vol. 9, No. 1, July 2013
Figure 21. Fast Autocorrelation for OFDM at CT=5
TABLE IV. C OMPARISON OF VARIOUS PAPR REDUCTION TECHNIQUES
Reduction
Technique
Parameters
Operation
required at
Transmitter
(TX)/Receive
r (RX)
Figure 18. Average OFDM signal at CT=3 for 64-QAM mod
scheme
Decrease
distortion
Power
Raise
NO
No
Defeat
Data
rate
No
Yes
No
Yes
Block
Coding
Yes
No
Yes
Partial
Transmit
Sequence
(PTS)
Yes
No
Yes
Interleavin
g
Yes
No
Yes
Tone
Reservation
(TR)
Tone
Injection
(TI)
Yes
Yes
Yes
Yes
Yes
No
Clipping
and
Filtering
Selective
Mapping
(SLM)
Figure 19. Average OFDM signal at CT=5 for 64-QAM mod scheme
TX: Clipping
RX: None
TX:M times
IFFTs
operation
RX: Side
information
extraction,
inverse SLM
TX: Coding
or table
searching
RX: Decoding
or table
searching
TX: V times
IFFTs
operation
RX: Side
information
extraction,
inverse PTS
TX: D times
IFFTs
operation, D1 times
interleaving
RX: Side
information
extraction,
deinterleaving
CONCLUSIONS
Though, there is a major drawback for using OFDM, which
is the high PAPR, recently OFDM became a compulsory in all
LTE systems for higher data rates. This problem can be
Figure 20. BER for clipped and unclipped signal [15]
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reduced by using channel coding and clipping as a power
reduction technique. We proposed and implemented a
reconfigurable SDR platform by combing USRP N210 and
GNU Radio. The selected technique allows for us with a
good range in performance to reduce PAPR problem. The
paper concludes that as SNR increases, BER will decreases.
And higher order PSK requires a larger SNR to minimize BER.
QAM constitutes of amplitude as well as phase, but QPSK
only have phase, so QAM is widely used instead QPSK .
The obtained results prove that PAPR reduces more at lower
CR and there is a tradeoff between the clipping threshold
value (CT) and out-of-band radiation. This out-of-band
radiation can be controlled by frequency domain filtering.
The results show how clipping and filtering affect the BER of
an OFDM signal and it is clear that the BER is increased after
this process. Filter is used to decrease the distortion that
result from clipping. This research will extend in directions
Firstly, PAPR reduction concepts will be expanded for
distortion less transmission and identifying the best
alternatives in terms of performance increase Secondly,
PAPR reduction technique will be develop for low data
rate loss and efficient use of channel.
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“Clipping and Filtering Technique for reducing PAPR in
OFDM”, IOSR Journal of Engineering (IOSRJEN), vol2, pp
91-97, 2012.
[6] Li, Xiaodong and Cimini Jr, Leonard J, “Effects of clipping
and filtering on the performance of OFDM,” Communications
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[7] GNU Radio Trac, http://gnuradio.org/trac/wiki.
[8] Matt Ettus, Universal software radio peripheral. http://
www.ettus.com.
[9] J.Mitola, “Analysis and comparison of clipping techniques for
OFDM Peak-to-Average Power Ratio reduction,” Digital Signal
Processing, 2009 16th International Conference on, pages 1—
6, 2009.
[10] Reddy, B Siva Kumar and Lakshmi, B,” Adaptive Modulation
and Coding in COFDM for WiMAX Using LMS Channel
Estimator,”2013.
[11] Sekar, Venkatesh and Palanisamy, V and Baskaran, K,”
Performance Analysis of IEEE 802.16 d using Forward Error
Correction,” Journal of Computer Science,vol 7, num 3, pp
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[12] Kaiser, Stefan,” OFDM code-division multiplexing in fading
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© 2013 ACEEE
DOI: 01.IJRTET.9.1.526
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