International Journal of Engineering Trends and Technology (IJETT) – Volume 13 Number 5 – Jul 2014
A Review Paper on Channel Estimation
Techniques Used in OFDM System
Ajay bahadur Singh1, Vivek kumar gupta2
1
Post Grad. Scholar, 2Associate Professor
1,2
DIT University, Dehradun,
Uttarakhand -248001, India
Abstract-- The main objective of this paper, is to
review the work already done related to channel
estimation technique in OFDM system. Pilot base
channel estimation algorithm i.e. block type, comb
type etc. are discussed and also compared in terms
of their simplicity, computational cost and
suitability conditions. After comparison with
known techniques i.e. decision directed-Kalmanbased estimation, Maximum Likelihood (ML)
method and two pilot-aided OFDM schemes, the
iterative blind channel technique performs better
for regions with mid to high signal to noise (SNR)
ratio. In iterative blind channel estimation,
instead of using pilots to sound channel, a decision
algorithm first makes primary estimates of the
data symbol for each subcarrier based on a
constrained linear minimum mean square error
(MMSE) criterion. Then, these essential estimates
are applied to optimum MMSE channel
estimation.
Index terms: Channel estimation, OFDM, ISI, time
varying channel,
I. INTRODUCTION
OFDM (orthogonal frequency division multiplexing)
has very wide area in wireless communication. In
OFDM, each channel has many sub-channels having
different frequencies which are further used in
parallel transmission at lower rate. Now a days, it is
further used in various wireless application i.e.
Digital Video Broadcasting (DVB), Digital Audio
Broadcasting (DAB), high performance wireless
local area network (HYPERLAN), WiFi and
WiMAX. OFDM is a special case of multi carrier
transmission where a single data stream is transmit
over a number of lower rate subcarrier. It is worth
mentioning here that OFDM can be treated as either a
modulation technique or multiplexing technique. The
basic technique used in OFDM is Frequency Division
Multiplexing (FDM). In FDM there are several
channels, which are separated by a guard band of
frequency to reduce adjacent channel interference.
These channels of FDM are used for the mapping of
information of different streams. While OFDM is
differ from FDM in following ways as follows:
ISSN: 2231-5381
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Multiple carriers are used in former to carry
the information data streams.
All the subcarriers are orthogonal to each
other than later one.
A guard time is added to each symbol to
reduce the time delay spread and inter
symbol interferences.
In OFDM, Orthogonality allows perfect transmission
of signals having multiple-information over a
common channel which are detected without
interference. Orthogonality between two periodic
signals means that the two co-existing signal are
independent to each other in specific time interval
and they should never interact with each other. The
two periodic signals are said to be orthogonal when
their integral product over one period is equal to zero
and they should have integer number of cycles in
fundamental period.In communication system, intersymbol interference (ISI) is a signal distortion in
which one symbol interferes with its subsequent
symbol. This may makes the communication less
reliable. ISI is usually caused due to the multipath
propagation or due to inherent non-linear frequency
response of a channel which cause successive
symbols to blur together. Due to ISI , errors are
occurred at the receiver output of the decision device.
Hence, to combat this problem
transmitter and
receiver filters should be made in such a way that
minimum error rate can be obtained. In OFDM
system, ISI is eliminated by making all the subcarrier
orthogonal to each other.
OFDM signals can be optimized using various
components such as coding[1], adaptive loading[2] ,
and portioning[1]. Due to criticism of modeling and
estimation, all the optimization depends on the
channel. In OFDM, channel estimation is required for
suppressing the interference and ensuing signal
detection.
Due to the accurate channel estimation, OFDM is
able to use the coherent detection for 3-dB signal to
noise ratio(SNR) gain over differential detection.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 13 Number 5 – Jul 2014
Channel estimation can be achieved using two
methods: pilot symbols and Blind manner. In pilot
symbol channel estimation method adding training
sequence pilot or carrier pilot in the time or
frequency domain enables estimate of the channel
response at the pilot position. The channel response
at the other position can be estimate by interpolation.
Pilot scheme is able to increase the complexity of
transmitters and receivers which have prior
knowledge of pilot scheme and both should have
extra processing to implement the pilot scheme
instead of only reduction in the available payload
capacity. Due to the more rapidly variation (time or
frequency) in the channel denser pilot are required.
For OFDM, blind channel estimation methods are
used which are statistical or deterministic. Statistical
blind channel estimation has slow convergence which
makes it unsuitable for mobile radio channels or any
burst transmission. There are several statistical blind
channel estimation: correlation methods [3],
cumulant fitting [4] and iterative blind channel [5]. In
blind deterministic method post discrete Fourier
transform (DFT) received blocks and exploit the
finite alphabet property of information bearing
symbols. For OFDM system blind deterministic
approach is used which is based on maximum
likelihood (ML) principle describe in [6]. This
method is able to producing a channel estimate from
a single OFDM symbol, but high complexity is
needed to execute the maximization in the algorithm,
and there is an ambiguity in recovered phase. To
complete a recovered phase additional pilots are
required. To address this problem of complexity a
modification is applied in ML method described in
[7] in which different modulation schemes on
adjacent subcarriers to resolve the phase ambiguity.
In comparison of both the methods, later one has high
complexity, which may increase as the constellation
order increase. However, as the number of pilots are
increased payload capacity is reduced, hence the pilot
based scheme is only optimized for a given rate of
change of the channel.
Time varying channel models gives in a nutshell and
the important issue of developing wireless system
technology using time varying channels. Excess
coverage of method is that estimating and equalizing
rapidly time varying channels, including a discussion
of training data optimization, which enables
development of wireless systems which have high
performance. Due to the ubiquitous uptake of OFDM
its extensions increased to time varying mobile
channels with widely different rates of change and
higher radio frequencies, its structure and capacity
efficiency should continue to be researched.
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II. LITERATURE REVIEW
A. Optimizing pilot locations using feedback in
OFDM system [8]
Ali Y. Panah, Rodney G. Vaughan, Robert W. Heath,
IEEE. 2009. In this article Pilot-aided OFDM
channel estimation has been optimized only for open
loop systems within the uniform spacing of optimal
pilots. Researchers used vector quantization with
Lloyd algorithm to reduce feedback and extend our
method to MIMO-OFDM based on Alamouti space
time block code. The result shows that how the pilot
symbols may be adapted to the current channel
conditions to improve performance.
B. A New derivation of Least-Squares –Fitting
Principle for OFDM Channel Estimation [9]
Ming-Xian Chang, IEEE. 2006. This paper present
channel estimation and data detection algorithm of
orthogonal frequency division multiplexing system.
Proposed algorithms are based on linear minimum
mean square error estimation. The result shows that
non statistical LSF principle can be derived
alternatively from the statistical LMMSE principle by
Eigen-vector approximation. Further, validates the
constructed link, based on the derived link and MSEE
analysis, and also gives characteristics and discussion
of LSF principle.
C. Detection of OFDM Signals in Fast-varying
Channels With Low-Density Pilot Symbols [10]
Ming-Xian Chang, IEEE. 2007. In this paper,
researchers propose a pseudo pilot algorithm for data
detection in fast varying channels without increasing
the pilot density. This algorithm is based on
regression model based least squares fitting approach.
The result of this paper shows that, the performance
of the proposed algorithms could approach a bit error
probability lower bound that is obtained by letting the
receiver know the true values of the pseudo pilots.
D. Blind Channel Identification Based on HigherOrder Cumulant Fitting Using Genetic Algorithms
[4]
S. Chen, Y. Wu, and S. McLaughlin, IEEE. 1997. In
this paper, scientist proposed a blind identification
scheme which uses genetic algorithms (GAs) to
optimize a HOC cost function. Due to the efficiency
of GAs, the proposed method guarantees to ding a
global optimal channel estimate. The result of this
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International Journal of Engineering Trends and Technology (IJETT) – Volume 13 Number 5 – Jul 2014
article shows that GAs based scheme is robust and
accurate, and has a fast convergence performance.
H. A Subspace Blind Channel Estimation Method for
OFDM System Without Cyclic Prefix [14]
E. Blind OFDM Channel Estimation Through Simple
Linear Pre-coding.[11]
Sumit Roy, IEEE. 2002. In this paper researchers
proposed a subspace based blind channel estimation
method for orthogonal frequency division
multiplexing system over a time dispersive channel.
In this researcher use resemblance of the
multichannel signal model of the received OFDM
signal to that in conventional single carrier system.
The result of this paper shows that the proposed
algorithm is attractive for its potential in sense of
increase the system’ s channel utilization by
eliminating CP. Comparison of algorithm results that
proposed one is able for estimate accuracy and the
speed of convergence.
Athinn a Peropulu, Ruifeng Zhang, IEEE. 2004. In
this paper, a new blind system is proposed by the
researchers which comprises simple linear
transformation applied to blocks of symbols before
they enter the OFDM. The transformation imposes a
correlation structure on the transmitted blocks, which
is used at the receiver to recover the channel through
simple cross correlation operations. The result of the
this paper shows that, this technique compares
favorably to the training-based scheme used in the
IEEE 802.11a wireless standard.
F. Channel Estimation for OFDM with Fast Fading
Channels by Modified Kalman Filter [12]
Ki- Young Han, Sang –Wook Lee, Jun Seok Lim,
IEEE. 2004. In this paper, researchers describe time
varying channels destroy the orthogonality between
sub channels and cause inter channel interference
(ICI) in conventional frequency domain estimation
approaches. To combat the ICI researchers propose a
new channel estimator for OFDM systems in a fast
and frequency selective Rayleigh fading channel. The
result shows that, proposed filter does not require
pilots especially in slow fading environments and
also able to compensate for ICI.
G. Data Efficient Blind OFDM Channel Estimation
Using Receiver Diversity [13]
Hao Wang, IEEE. 2003. In this paper, researchers
investigate non data aided channel estimation for
cyclically prefixed orthogonal frequency division
multiplexing (OFDM) system. They also proposed a
blind deterministic algorithm by exploiting channel
diversity using only two receive antennas. The
proposed method has desired property of being data
efficient only a single OFDM block is need to
achieve good estimation performance for a wide
range of SNR values in presence of noise. The result
of this paper shows that, this new approach is its data
efficiency can be implemented using a single data
block to achieve reasonable accurate estimate, and
this property is independent of the input signal
constellation.
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I. Channel Estimation Techniques Based on Pilot
Arrangement in OFDM System.[15]
Sinem Coleri, Mustafa Ergen, Anuj Puri and Ahmad
Bahal, IEEE. 2002. In this paper researchers
proposed a channel estimation technique for OFDM
system based on pilot arrangement. They use
different algorithms for both estimating of channel at
pilot frequencies is based on LS and LMS while
channel interpolation is done using linear
interpolation. The result of this paper shows that
comb type pilot based channel estimation with low
pass interpolation performs the best among all
channel estimation algorithms.
J. OFDM With Iterative Blind Channel Estimation
[5]
Seyed Alireza Banani, IEEE. 2010. In this article
researcher proposed a new blind channel estimation
technique for un-coded OFDM. He use a decision
algorithm which makes primary estimation of data
symbol for each subcarrier based on a constrained
linear minimum mean square error. The technique
used only require one value from the time frequency
correlation of the channel transfer function. The
result shows that, the performance of blind system is
very promising and data detection is employed for
high Doppler.
III. CONCLUSION
In this paper, the various channel estimation
techniques for OFDM are studied. By comparing
various techniques we come to an conclusion that the
blind channel estimation is more efficient than pilot
aided system for simulated channels and is more
robust in sense of time variation of the channel than
pilot aided system. The blind technique has more
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International Journal of Engineering Trends and Technology (IJETT) – Volume 13 Number 5 – Jul 2014
optimum than pilot, while the sensitivity of former is
less than later one but they also operate from worse
error performance data. For high correlations
between all taps the comb pilot system. The blind
system outperforms the comb type pilot system for
lower correlations and always performs better than
the block type system and decision directed Kalmanbased tracking technique under this error measure.
REFERNCES
AUTHOR
Ajay bahadur singh presently lives in Dehradun
and completed his Graduation as a B. Tech.
graduate in the field of Electronics and
communication from Uttar Pradesh Technical
University, Lucknow, UP,India in 2010. He is a
post-graduate scholar in the field of Wireless &
Mobile Communications from Dehradun Institute
of Technology, Dehradun, Uttarakhand, India in
2013. Presently he is working on “Channel
Estimation for OFDM system”.
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