CHANNEL AND CFO FOR OFDM WITH MULTIANTENNA RECEIVER
S.Priyadharshini[1]
Mr.A.Kumar[2]
Abstract:
INTRODUCTION
Orthogonal
frequency
division
multiplexing (OFDM) has drawn substantial
research interests during the past decade and
has been deemed as the key component of
future wireless communication systems.
Although OFDM is immune to frequencyselective fading, its performance is more
sensitive to carrier frequency offset (CFO) that
is caused by oscillator mismatch between the
transceivers. If the CFO is not properly
compensated, the so introduced inter-carrier
interference (ICI) could significantly degrade
the system performance. a new joint blind
CFO and channel estimation method for
OFDM system with multi-antenna receiver.
This method supports fully loaded systems and
is valid when only one OFDM block is
available.
Remarkably,
the
channel
information between the transceivers can be
obtained with only a scaling ambiguity.
Moreover, we derive the CRB of joint CFO
and channel estimation in closed forms. The
CFO can be blindly obtained based on the
kurtosis-type criterion, diagonality criterion
and
oversampling
constant
modulus
constellations or the presence of null
subcarriers. Especially, the methods in are
one-shot estimators which require only a
single received OFDM block, which exhibit
both the spectral efficiency and time
efficiency.
Recent studies in the field is to split a
high data stream into a number of lower rate
streams that are transmitted simultaneously
over a number of subcarriers. Because the
symbol duration increases for the lower rate
parallel subcarriers, the relative amount of
dispersion in time caused by multipath delay
spread is decreased. Inter symbol interference
is eliminated almost completely by introducing
a guard time in every OFDM symbol. In the
guard time the OFDM symbol is cyclically
extended to avoid inter carrier interference
In OFDM system design, a number of
parameters are up for consideration, such as
the numbers of subcarriers, guard time, symbol
duration, subcarrier spacing, modulation type
per subcarrier, and the type of forward error
correction coding. The choice of parameters is
influenced by system requirements such as
available bandwidth, required bit rate,
tolerable delay spread, and Doppler values.
Some requirements are conflicting Orthogonal
Frequency Division Multiplexing (OFDM) is
most commonly employed in wireless
communication systems because of the high
rate of data transmission potential with
efficiency for high bandwidth and its ability to
combat against multi-path delay.
It has been used in wireless standards
particularly for broadband multimedia
wireless services. . This whole process of
1
generating an OFDM signal and the reasoning
behind it are described. The estimation
channel is done by inserting pilot symbols
into all of the subcarriers of an OFDM
symbol or inserting pilot symbols into some
of the sub-carriers of OFDM symbols.Radio
transmission has allowed people to
communicate
without
any
physical
connection for more than hundred years.
When Marconi managed to demonstrate a
technique for wireless telegraphy, more than a
century ago, it was a major breakthrough and
the start of a completely new industry. May
be one could not call it a mobile wireless
system, but there was no wire! Today, the
progress in the semiconductor technology has
made it possible, not to forgot affordable, for
millions of people to communicate on the
move all around the world.
opened a new dimension to future wireless
communications whose ultimate goal is to
provide universal personal and multimedia
communication without regard to mobility or
location with high data rates. To achieve such
an objective, the next generation personal
communication networks will need to be
support a wide range of services which will
include high quality voice, data, facsimile,
and streaming video.
These future services are likely to
include applications which require high
transmission rates of several Mega bits per
seconds (Mbps). In the current and future
mobile communications systems, data
transmission at high bit rates is essential for
many services such as video, high quality
audio and mobile integrated service digital
network. When the data is transmitted at high
bit rates, over mobile radio channels, the
channel impulse response can extend over
many symbol periods, which leads to inter
symbol interference (ISI).
Orthogonal
Frequency
Division
Multiplexing (OFDM) is one of the promising
candidate to mitigate the ISI.In an OFDM
signal the bandwidth is divided into many
narrow sub channels which are transmitted in
parallel. Each sub channel is typically chosen
narrow enough to eliminate the effect of delay
spread. By combining OFDM with Turbo
Coding and antenna diversity, the link budget
and dispersive-fading limitations of the
cellular mobile radio environment can be over
come and the effects of co-channel
interference can be reduced
The Mobile Communication Systems are
often categorized as different generations
depending on the services offered. The first
generation comprises the analog frequency
division multiple access (FDMA) systems
such as the NMT and AMPS (Advanced
Mobile Phone Services). The second
generation consists of the first digital mobile
communication systems such as the time
division multiple access (TDMA) based GSM
(Global System for Mobile Communication),
D-AMPS (Digital AMPS), PDC and code
division multiple access (CDMA) based
systems.
These systems mainly offer speech
communication, but also data communication
limited to rather low transmission rates. The
third generation started operations on 1st
October 2002 in Japan.This growth has
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System Model
EXISTING SYSTEM
Wireless Systems are operating in an
environment which has some specific
properties compared to fixed wire line systems
and these call for special design
considerations. In a wired network, there are
no fast movements of terminals or reflection
points and the channel parameters are
changing very slowly. In addition, time
dispersion is less severe in a wired system,
though it might still be a hard problem due to
high data rates. In a mobile system the
terminals are moving around, the received
signal strength as well as the phase of the
received signal, are changing rapidly.
restriction of is that at least two
OFDM blocks should be received, during
which time the channel between the
transceivers should stay constant. Hence, the
estimator should be more vulnerable to the
channel variations than the existing one-shot
estimators Moreover, does not considered the
channel length information, which is usually
bounded by the length of cyclic prefix (CP) in
practical OFDM systems. On the other side,
few of above CFO estimation methods could
obtain the channel estimate in theme an time.
Further, the signal transmitted over the
radio channel is reflected by buildings and
other means of transportation on the ground,
leading to different paths to the receiver, as
shown.If the length of the paths differ, the
received signal will contain several delayed
versions of the transmitted signal according to
the channel impulse response defined in
Equation.The delays make it necessary to use
complex receiver structures. In a mobile
wireless system, the terminals are of course
intended to be portable.
Fig.4.1 Architecture of an OFDM system
Though can further obtain the
frequency domain channel responses after
CFO estimation, it requires a number of pilot
symbols to remove the channel estimation
ambiguity. Nevertheless, there are many blind
channel estimation algorithms for OFDM
without CFO estimation, for example, the
subspace-based channel estimation method.
However, most existing subspace-based
methods require sufficient number of received
blocks in order to build reliable sample
covariance matrix.
This means that power consumption is
important since batteries sometimes will power
the equipment.Therefore, low complexity and
low power consumption are properties that are
even more desirable in wireless systems than
in a wired system. Consider a sequence of T+1
data symbols X0 ;X1;…… ;XT , each of length
N, to be transmitted in an OFDM system.
Every symbol Xi, undergoes an IFFT operation
to produce the time domain symbol
𝑥i= √𝑁 Q*𝑥I
(1.1.2)
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PROPOSED SYSTEM:
OFDM TRANSMISSION
Orthogonal
frequency
division
multiplexing (OFDM) is inherently resistant to
multipath fading and has been adopted by
many standards because it offers high datarates and low decoding complexity In this
Proposed method it supports fully loaded
systems and block receiving by a wireless
communication device, a wireless signal
transmitted from a stream of two or more
blocks of symbols, wherein each of the two or
more blocks of symbols includes one or more
information-bearing symbols and one or more
training symbols, and at least one null
subcarrier at a different position within each of
the two or more blocks of symbols.
Block diagram for OFDM
Channel Estimation
Since the number of pilots must be
greater than the number of channel taps, the
use of cyclic pre- fix (CP) and pilot symbols
entails a significant bandwidth loss, motivating
blind methods. Several works have attempted
to perform blind channel estimation in OFDM.
The authors in explored transmitter
redundancy for blind channel estimation while
in, a blind identification exploiting receiver
diversity which can get CSI during one OFDM
symbol was investigated.
The simulation results showed
that the proposed method not only outperforms
the existing estimators, but also attains CRB in
relatively high SNR range. All these advantages
makes the proposed algorithm a good ranking
for future wireless communication systems.As
mentioned in the introduction, our aim is to
design an algorithm for channel estimation in
OFDM. In this section, we will take a look at
the literature relating to channel estimation in
OFDM systems.
In the authors present a fast
converging blind channel estimator for
OFDM-systems based on the Maximum
Likelihood principle. A non redundant
precoding along with cyclic prefix was
explored on. In, second-order cyclostationary
statistics and antenna precoding are used
while employs infinite alphabet constraint for
blind channel estimation. The authors in
suggest an approach which relies on the
4
Sl.NO
BER
-0.5
1.
10
2.
10
-0.7
Step 6: Take variance of noise and add data to
the noise.
Step 7: The channel is estimated by evaluating
the mean square error (MSE) and Bit Error
Rate(BER) using LS, LS-Modified, MMSE
algorithms
Table 5.5 BER values verses SNR values
SNR at dB
2 dB
4 dB
The channel estimation and BER performance
output is shown in following Figure 5.5
-0.9
3.
10
4.
10
-1.2
-1.8
5.
10
8 dB
10 dB
12 dB
assumption of the data sequence and uses the
cyclic prefix redundancy present in OFDM
systems and
developed a posteriori
probability based two dimensional channel
estimation algorithm.
Fig 5.5 BER vs SNR
STEPS TO
CHANNEL
CALCULATE
Wireless communication is the transfer
of information between two or more points
that are not connected by an electrical
conductor while wireless operations permit
services, such as long-range communications,
that are impossible or impractical to
implement with the use of wires.Here, three
channel models namely AWGN, Rayleigh and
Rician are estimated. It is implemented by
using three algorithms namely Least Square
(LS), Minimum Mean Square Error (MMSE),
Least Square Modified (LS Mod).The system
is simulated in MATLAB and analysed in
terms of Bit Error Rate (BER) with Signal to
Noise Ratio (SNR).In LS algorithm, estimation
procedure is simple but it has high mean
BER FOR
The following steps are followed to
calculate the BER for channel
Step 1: Initialize the various parameters such
as number of subcarriers, number of
pilots, guard interval and SNR.
Step 2: Generate G matrix by using formula.
Step 3: Generate OFDM symbols for random
input data and encode it by using trellis
algorithm.
Step 4: Modulate the encoded data by BPSK
modulation technique.
Step 5: For AWGN channel, add the complex
Gaussian noise to the data.
5
square error (MSE). WMAN and WiMax used
under wireless network category.
in Wireless Communications, SPAWC'03,
Rome, Italy,.
[2] Cui .T and Tellambura .C(2010), “Joint
frequency offset and channel estimation For
OFDM systems using pilot symbols and
virtual carriers,” IEEE Trans. Wireless
Commun., vol. 6, no. 4, pp. 1193–1202,.
[3] Cai .K, Li .X, J. Du, Y. Wu .C, and
Gao .K(2007), “CFO estimation in OFDM
systems under timing and channel length
uncertainties with model averaging,”IEEE
Trans. Wireless Commun., vol. 9, pp. 970–
974,.
[4] Cimini .L,(19985) “Analysis and
Simulation of a digital mobile channel using
OFDM,”IEEE Trans. on Commun., vol.
33,pp. 665-675, July.
[5]
Fazel, K. and Fettis, G.,(1967)
“Performance of an Efficient Parallel Data
Transmission System.” IEEE Transaction
Communication Technology. pp. 805-813.
CONCLUSION
The new joint blind CFO and channel
estimation method is designed for OFDM
system with multi-antenna receiver. Then its
supports fully loaded systems and is valid
when only one OFDM block is available.
Moreover, we derive the CRB of joint CFO
and channel estimation in closed forms. The
simulation results showed that the proposed
method not only outperforms the existing
estimators, but also attains CRB in relatively
high SNR range. All these advantages makes
the proposed algorithm a good candidate for
future wireless communication systems.The
future enhancements with a new joint blind
CFO and channel estimation method for
OFDM
system
with
multi-antenna
receiver.several interesting directions for
future work exist. First, it is possible to
employ the algorithm both in time and
frequency domains. Second, the crisp logic
controller may be replaced by a fuzzy logic
controller in which case a tradeoff between
reliability and transmitter complexity should
be evaluated. All these advantages make the
proposed algorithm a good candidate for
future wireless communication systems
REFERENCES
[1] Bradaric .I and PetropuluA.P(2003),
“Blind Estimation of the Carrier Frequency
Offset in OFDM Systems,” 4th IEEE
Workshop on Signal Processing Advances
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