International Journal of Engineering Trends and Technology (IJETT)
Performance Estimation of Pre-distortion Technique
for Modern Communication System
Sangeeta Bawa#1, Rajat Gupta#2, Jyoti Gupta#3
#
Department of Electronics & Communication Engineering
Maharishi Markandeshwar University, Mullana (Ambala), INDIA.
Abstract— In modern communication system, high power
amplifiers are the central component as their function is to
amplify the signal and generate the required power for
transmission of signals. For this purpose the communication
system needs highly linear amplifiers. However with the use of
multi carrier and complex modulated signals the response of the
amplifier is nonlinear. To make the response of high power
amplifiers linear; various linearization techniques are used. In
this paper an adaptive pre-distortion technique is used for
reducing the distortion and makes the response almost linear.
Keywords— High power amplifiers, Linearization, Pre-distortion
and adaptive linearization.
I. INTRODUCTION
This The rapid growth in technology created a huge
demand for highly linear amplifiers [1-2]. Practically, the
response of high power amplifiers is nonlinear. Now-a-days
modern communication systems make use of multi carrier and
complex modulated signals [3]. In both cases, any amplitude
or phase distortion of the signal will generate additional
undesired signals called intermodulation distortion products
(IMD) [4]. Because of IMD’s beat products are produced in
the vicinity of input signals as shown in figure 1.
very small then the output signal but still may cause
interference. Therefore, to compensate these nonlinearities
many linearization techniques are used like feed forward,
feedback, pre-distortion [5]. It is to be noted that among all
the linearization techniques pre-distortion technique is the
historically one approach for reducing the distortion and make
the response almost linear.
II. PRE-DISTORTION
Pre-distortion technique is the most important technique to
linearize the power amplifiers. It has a strong potential to use
wideband signals. Basically; in this technique it creates a
previous distortion curve complementary to the power
amplifier distortion. So, if these two curves are situated in
cascade, the final result will be completely linear [6]. The
block diagram for the pre-distortion is given in figure 2:
Fig. 2: Pre-distortion linearization technique [6].
The pre-distortion techniques have comparatively simple
circuitry; it may be classified into two categories; 1) adaptive
pre-distortion and 2) non adaptive pre-distortion. The
difference between the two categories is very simple. The
adaptive pre-distortion estimate the predistorter functions
again and again whereas the non-adaptive pre-distortion
estimates the pre-distortion function only at one time [7]. That
is why adaptive pre-distortion gives the better result. In this
paper an adaptive pre-distortion technique is used for IMD
suppression and estimating the performance of wideband
signal. Digital adaptive pre-distortion is a famous predistortion scheme as its ability to accurately update the
predistorter transfer function to varying PA characteristics.
The flow chart for the pre-distortion technique is given in
Figure 3.
Fig. 1: IMD’s produced due to non-linear response.
Figure 1shows IMD’s produced due to non-linear response;
when sine wave with multiple frequencies is used as an input
signal. Although many times these distortion products are
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International Journal of Engineering Trends and Technology (IJETT)
Fig. 3: Flowchart for adaptive linearization technique.
The output of non-linear amplifier is fed back; the error,
due to non-linearity of amplifier, is calculated by taking the
difference of the attenuated output of the non-linear amplifier
and input signal. This error is fed to the adaptive linearizer
such that error can be minimized. In this adaptive linearization
technique, the coefficients of polynomials are adjusted in such
a way that the error approaches to zero and the output of an
overall system (amplifier and linearizer) becomes closely to
linear [8].
The proposed technique checks the error at any instant with
both the previous error and the initial error; and the
coefficients are changed only if for any change in the value of
the coefficient the error is both less than the previous error
and the initial error. The distortions, produced in signal being
amplified by high power amplifiers occur due to the non-
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linear behavior of power amplifier. The characteristics of the
non-linear amplifier are represented by a polynomial. This
polynomial contains the higher order odd terms but for
simplicity polynomial up to fifth order is considered. The
proposed technique shows better performance and the shape
of the output signal better matches the input signal. It can also
be observed that the proposed algorithm better suppresses the
IMDs as shown in figure 4.
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International Journal of Engineering Trends and Technology (IJETT)
Fig. 4: IMD’s produced due to non-linear response and the same
suppressed by the proposed adaptive linearization technique.
Fig. 6: The input 64 PSK signal a nd the scaled non-linear amplifier
output showing the effect of gain compression on outer symbols
III. RESULTS AND DISCUSSION
To determine the performance of above adaptive
linearization technique extensive simulation is done in Matlab.
For this purpose many wideband signal can be used like QAM,
PSK, and QPSK. In this paper for evaluating the performance
of linearizer for wideband signal PSK signal constellation is
used [9].
Figures 5 to 8 shows the effects of PA nonlinearity on the
PSK modulated signal constellation. It can be observed from
these figures that the non-linear response causes many signals
to go from out-of-phase. The non-linear response of the
amplifier and linearizer shifts the signals in opposite
directions, so that the combined system produces a linear
response. In particularly, the linearizer has transfer
characteristics in anti-phase to those of amplifier, so these
nonlinear characteristics displaced the signals towards center
of constellation. When this signal is fed to the amplifier, the
already shifted signal by linearizer nullify the shift due to the
non-linearity of the amplifier transfer characteristics, which
finally results in a better linearized output. It can be seen from
these figures that not all the signals matches the original PSK
constellation. This can be improved by increasing the number
of cycles.
Fig 7:The input 64 PSK signal and the scaled non-linear lineariser
output affecting the outer symbols
Fig 8: The input 64PSK signal and the scaled pre-distortion based
lineariser and amplifier output.
Fig. 5: The input 64 PSK signal
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Consider another example in Figures 9 to 12, in which
noise is added to the above simulated PSK signal. The signals
at various stages (amplifier, linearizer and overall output) are
shown with and without pre-distortion. It can be evident from
Figures 9 to 12 that the proposed algorithm works well even
in the presence of a high level of noise.
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International Journal of Engineering Trends and Technology (IJETT)
Fig. 9: The input 64 PSK signal with noise.
Fig. 10: The input 64 PSK signal and the scaled non-linear
amplifier output showing the effect of gain compression on
outer symbols.
Fig. 11: The input 64 PSK signal and the scaled nonlinear linearizer output showing the effect on outer
symbols.
Fig. 12: The input 64 PSK signal and the scaled pre-distortion
based lineariser a nd a mplifier output.
IV. CONCLUSIONS
The Linearization of amplifiers is very necessary as it is the
main component of communication system. Linearizer
increases the power capacity and efficiency of high power
amplifiers for multi carrier and complex digital signals. In this
paper adaptive linearization technique is used to suppress the
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IMD and to determine the performance of wideband signals
PSK is used. Thus from the results, it can be concluded that
the proposed pre-distortion approach has potential in
improving the performance of amplifiers and is able to
linearize the amplifier up to points close to saturation .
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