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ISSN 2394-3777 (Print)
ISSN 2394-3785 (Online)
Available online at www.ijartet.com
International Journal of Advanced Research Trends in Engineering and Technology (IJARTET)
Vol. II, Special Issue XXIII, March 2015 in association with
FRANCIS XAVIER ENGINEERING COLLEGE, TIRUNELVELI
DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING
INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN COMMUNICATION SYSTEMS AND
TECHNOLOGIES
(ICRACST’15)
TH
25 MARCH 2015
TIME-FREQUENCY TRAINING OFDM WITH HIGH
SPECTRAL EFFICIENCY AND RELIABLE
PERFORMANCE IN LONG DELAY CHANNELS
1
R.Ranjitha, 2R.Thirunavukarasu
1
PG Scholar, 2Assist.prof
Department of ECE, Oxford Engineering College, Trichy,tamilnadu, India
Abstract---Orthogonal
Frequency
Division
Multiplexing (OFDM) has recently been applied
widely in wireless communication systems due
to its high data rate transmission capability with
high bandwidth efficiency and its robustness to
multipath delay. TDS-OFDM performance
suffer from fading channels with long delays
andhas
difficulty
supporting
high-order
modulations like 256 QAM. Time-Frequency
Training (TFT) OFDM compressive sensing and
auxiliary information based subspace pursuit
(A-SP) algorithms proposed to estimate the
channel.Theobtainedchannelinformations
are
reduce
the
complexity
of
classical
SPalgorithm.DPN OFDM and TDS OFDM
schemes in both static and mobile environment
Especially when the channel length is close or
even larger than the guard interval length, the
two schemes are can’t work.
Keywords---Channel
estimation
(CE),
compressive sensing(CS), long delays, orthogonal
frequency division multiplexing(OFDM), ultrahigh definition television (UHDTV).
1. Introduction
OFDM is considered an effective
technique for broadband wireless communications
because of its great immunity to fast fading
channels and inter-symbol interference (ISI). It has
been adopted in several wireless standards such as
digital audio broadcasting (DAB), digital video
broadcasting (DVB-T), the wireless local area
network (WLAN) standard; IEEE 802.11a, and the
metropolitan area network (W-MAN) standard;
IEEE 802.16a OFDM partitions the entire
bandwidth into parallel subchannels by dividing the
transmit data bitstreaminto parallel, low bit rate
data streams to modulate thesubcarriers of those
subchannels. As such OFDM hasa symbol duration
longer than single carriersystems(due to the lower
bit rate of subchannels) which makes it very
immune to fast channel fading and impulse
noise.The frequency-selective multipath channel
and the low complexity of the frequency domain
equalizer, and the orthogonal frequency division
multiplexing (OFDM) has been widely recognized
as one of the key techniques for the next generation
broadband wireless communication systems . The
fundamental issue of OFDM is the block
transmission scheme. Basically, three types of
OFDM-based block transmission schemes: cyclic
prefix OFDM (CP-OFDM) , zero padding OFDM
(ZP-OFDM),
and
time
domain
synchronousOFDM(TDS-OFDM). The broadly
used CPOFDM scheme utilizes the CP to eliminate
the inter-block interference (IBI) as well as the
inter-carrier-interference (ICI) . For both the CPOFDM and ZP-OFDM schemes, some allocated
frequency-domainpilots are required for the both
synchronization and channel estimation. The
spectral efficiency is reduced and to solve the
problem, instead of the Cyclic Prefix, the known
training sequence (TS) such as the pseudorandom
noise (PN) sequence, is used in the TDS-OFDM
scheme instead of guard interval. Since the
Training Sequence is known to the receiver, it can
be used for both synchronization as well as channel
estimation .
The main drawback of TDS-OFDM is that
theTS and the OFDM block will cause mutual
inter-blockinterferences (IBI) to each other. Thus,
iterative interference cancellation algorithm with
high complexity has to beadopted for CE and
channel equalization in TDS-OFDM systems.
Under the severely fading channels, it isdifficult for
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the iterative algorithm to perfectly remove theIBI
when the maximum channel delay spread is large,
whichis common in the single frequency network
(SFN) environment . This will cause the
degradation of the whole systemperformance and
the difficulty to support the high-order modulations
like 256 QAM to accommodate the emergingultrahigh definition television (UHDTV) service
requirement(DVB-T2 has claimed to support the
256QAM for UHDTVservices. Some alternative
solutions have been proposed to solve thisproblem
.One exciting solution is the dual-PN addedOFDM
(DPN-OFDM) scheme, whereby the PN sequence
isduplicated twice to make the second PN sequence
immunefrom the IBI caused by the preceding
performance, it is not necessary to remove such
interferencein the proposed scheme since the
received PN sequence isonly used for the coarse
channel path delay estimation. Themain CE task is
transferred to the pilots in the OFDM block,which
could combat the maximum channel delay spread
closeto or even larger than the GI length. With the
use of CSand sparse channel nature, the number of
pilots embedded inthe OFDM block could be
ignificantly reduced (about 1%of the total subcarrier number), and hence high spectral efficiency
can still be maintained. Moreover, the coarse
channelpath delay estimation is used as the
auxiliary information toreduce the complexity of
the classical CS algorithm, makingit applicable for
practical systems.
2.Basic Concept of the TDS and DPN OFDM
System
In time-domain synchronous orthogonal
frequency division multiplexing (TDS-OFDM)
distinguishes the standard cyclic prefix OFDM
(CP-OFDM) by replacing CP with the prior known
pseudo noise (PN) sequence as the guard interval
(GI). The PN sequence can also work as the
training sequence (TS) for both synchronization
and channel estimation (CE) at the receiver side,
which saves a large amount of frequency-domain
pilots commonly used in CP OFDM.TDS-OFDM
usually has higher spectral efficiency under the
same condition. Additionally, faster and reliable
synchronization could be also achieved by TDS
OFDM .However, the main drawback of TDSOFDM is that the TS and the OFDM block will
cause mutual inter-block interferences (IBI) to each
OFDM block . Thus,the second received PN
sequence can be directly used for CE,which avoids
the
iterative
interference
cancellation
algorithmwith high complexity, and improves the
performance overseverely fading channels.
In this paper, consider time-frequency
training OFDM (TFT-OFDM) scheme Which is
modified from TDS-OFDM.The proposed CE
method uses the PN sequence to acquire the coarse
channel path delay estimation, while the exact
channel impulseresponse (CIR) estimation. he
conventional scheme of TDS-OFDMwhere the IBI
caused by the preceding OFDM block tothecurrent
TS has to be cancelled completely to achieve good
other. Thus, iterative interference cancellation
algorithm with high complexity has to be adopted
for CE and channel equalization in TDS-OFDM
systems.
This result is an open problem of TDSOFDM: Under the severely fading channels, it is
difficult for the iterative algorithm to perfectly
remove the IBI when the maximum channel delay
spread is large, which is common in the single
frequency network (SFN) environment. It will
cause the degradation of the whole system
performance and the difficulty to support the high
order modulations like 256 QAM to accommodate
the emerging ultra-high definition television
(UHDTV) service requirement(DVB T2 has
claimed to support the 256QAM for UHDTV
services).Some alternative solutions have been
proposed to solve this problem .
Fig.1: Distinct features of the IBIs in TDS OFDM
As shown in Figure. 1, the IBI from the TS to the
OFDM data block and the IBI caused by the
OFDM block to the TS have distinct features in
TDS-OFDM.
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Fig.4:Proposed signal structure and the corresponding joint
time-frequency channel estimation of the OFDM scheme.
Fig.2:System models for CS-based TDS-OFDM.
In Fig.2: The Compressive Sensing based TDSOFDM scheme utilizes the IBI-free region of size
G within the received PN sequence for CE, but the
maximum estimated channel length is limited to L
= M − G + 1, where M is the length of the PN
sequence .When the channel length L becomes
larger, the size of the required IBI-free region
becomes smaller, which leads to severe
performance deterioration due to the reduced
number of observations in CS.Unlike the
conventional TDS- OFDM or CP-OFDM where the
training information only exists in either the time
or frequency domain.
Fig.3: System model for DPN-OFDM.
Fig.2: The DPN-OFDM scheme uses the
second received PN sequence immune from IBI for
CE.Thus, the iterative IBI removal can be avoided,
but significant loss in spectral efficiency will be
introduced.
3.PROPOSSED TFT- OFDM SYSTEM MODEL
Unlike TDS-OFDM or CP-OFDM where the
training information only exists in the time or
frequency domain, Fig. 4 shows that TFT-OFDM
has training information in both time and frequency
domains for every TFT-OFDM symbol, i.e., the
time-domain TS and the frequency-domains are
grouped pilots scattered over the signal bandwidth
are used in TFT-OFDM. The signal structure of the
TFT-OFDM scheme in both the time and frequency
domain.
In the time domain, the ith TFT-OFDM symbol si
=[si,−M··· si,−1 si,0si,1 ··· si,N−1] T is composed of
the known time-domain TS ci=[ci,0 ci,1 ···
ci,M−1]T and the OFDM data block xi=[xi,0 xi,1 ···
xi,N−1]T as below
Where M is the length of the TS, Nis the
length of the OFDM data block, P=M+N presents
the length of the TFT-OFDM symbol,
Xi=[Xi,0Xi,1 ··· Xi,N−1]T Denotes the frequencydomain OFDM symbol, and xi =FNH Xi Being
different from the time-domain PN sequence used
inTDS-OFDM, the TS in TFT-OFDM could be any
kind ofsequences with desirable specific features
defined in the above two domain. Normally, the
sequences with idealor good autocorrelation
property are preferred for channelestimation.e.gThe
constant
amplitude
with
zero
autocorrelation(CAZAC) sequence with constant
envelop in both time andfrequency domains , or the
PN sequences are used in TDS-OFDM.
The TS having constant envelopein the
frequency domain, i.e., ci =FHMCi, where
Ci=[Ci,0Ci,1 ··· Ci,M−1]T with the entry |Ci,k| =c,
and c is an arbitrary real number. For simplicity ,Ci
,k =±1is used throughout this paper. It can be
proved that such TS with any length has perfect
circular autocorrelation property, since the circular
correlation theorem allows
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defined by
In the frequency domain, different from
TDS-OFDM where all subcarriers are used to carry
the useful data , TFTOFDM has Nd data subcarriers
and Ngroup groups of binary phase-shift keying
(BPSK) modulated pilots scattered over the signal
bandwidth. Each pilot group has 2d+1pilots. The
index set of the central pilots in the Ngroup pilot
groups can be denoted by η={η0η1 ··· ηNgroup−1},
and the index set of all pilots is consequently
presented by the Ψ={η0−dη0−d+1···η0+d···z
ηNgroup−1−d···ηNgroup−1+d}. The pilot number is
Np=Ngroup(2d+1), and N=Nd+Np. Although the
frequency-domain pilots are very common in CPOFDM systems, the grouped pilots in TFT-OFDM
are different from the block-type pilots or the
comb-type pilots used in most CP-OFDM systems,
e.g., the second generation digital terrestrial
television broadcasting system (DVB-T2) and the
next generation mobile wireless system called the
long term evolution (LTE), TFT-OFDM requires
much less pilots than CPOFDM.
The discrete multipath channel during the ith TFTOFDM symbol at the time instant n(−M≤n≤N−1)
can be modeled as hi,n =[hi,n,0hi,n,1 ··· hi,n,L−1] T
of the maximum length L, where hi, n ,l denotes the
coefficient of the l th path with the delay nl. Behind
the cyclic prefix reconstruction of the received
OFDM block has been accomplished (the hybrid
domain cyclic prefix reconstruction method based
on the well-known overlap and add (OLA) scheme
in ZP-OFDM systems can be straightlyused.since
TFT-OFDM is essentially equivalent to ZP-OFDM
after removing the known TS at the receiver side),
the received time domain OFDM block
yi=[yi,0yi,1 ··· yi,N−1]T is
(3)
Where wiis the additive white Gaussian noise
(AWGN) vector with zero mean and covariance of
σ2IN, and the time-domain system matrix Hi is
Using FFT to the above signal (3), we have the
frequency domain OFDM block Yi=[Yi,0 Yi,1 ···
Yi,N−1]T as
(5)
Where Yi =FN yi, Wi =FNwi, and Gi is the N×N
channel frequency response (CFR) matrix with the
(p+1,q+1) th entry Gi,p,q being
If the channel is time-invariant within each TFTOFDM symbol, the ICI coefficient Gi,p,q (p not =
q) equals to zero, and Gi becomes a diagonal
matrix.
The proposed CS-based CE method firstly
utilizes the PN-based correlation in the time
domain to acquire the auxiliary channel
information, and then the frequency-domain pilots
are used for the final exact CIR estimation based on
CS.
4.Exact CIR Estimation Using A-SP:
The pilots can be extracted from the
OFDM block after cyclicity reconstruction for the
final accurate CE. Based on the basic idea of
classical SP algorithm .The propose the A-SP
algorithm, whereby the auxiliary channel
information obtained.The areexploited to improve
the CE performance and lower the computational
complexity. The proposed A-SP algorithm is
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described by pseudo code.Compared to the
classical SP algorithm, the proposed A-SP
algorithm has quite similar procedure, but differs
from SP inthe following three aspects:
1) Initial Configuration: In the proposed A-SP
scheme, by exploiting the obtained partial path
delays T0, the initial approximation can be directly
configured as T0 ← T0.
2) Significant Entry Identification:The S0 most
significant entries unchanged, and identify the next
S − S0 most significant ones instead.
3) Iteration Number: The required number of
iterations is reduced from S − S0 in A-SP, so the
computational complexity can be reduced.
5.Cyclicity Reconstruction of the OFDM Block:
The cyclicity reconstruction of the OFDM
block is achievedby firstly subtracting the IBI
caused by the PN sequencefrom the received
OFDM block, then adding the received
PNsequence and finally subtracting the first part of
linear convolution outputs between the PN
sequence and channel . Thisprocess is based on the
idea of OLA algorithm .The IBI caused by the PN
sequence is obtained by computing the linear
convolution between the local PN sequence and the
estimated CIR obtained in the preceding symbol.
Under the slow time-varying channels, which can
be assumed in many wireless broadcasting systems
, the estimated CIR obtained in the preceding
symbol can be used for the IBI removal in the
current symbol. In fact, the received PN sequence
contains not only the useful part which is the IBI
caused by the OFDM block, but also the useless
part that is the linear convolution between the PN
sequence and channel.Hence, the useless part
should be removed after the receivedPN sequence
is added to achieve the cyclicity reconstruction.
6.PerformanceAnalysis
OFDM:
Of
Cs-Based
TFT-
embedded in TFT-OFDM is J = 36. The
conventional TDS-OFDM scheme has the highest
spectral efficiency, but the iterative interference
cancellation isrequired, which results in high
complexity and performanceloss. In the DPNOFDM scheme, the PN sequence is duplicated to
avoid the interference from the preceding
OFDMblock to the second PN sequence, but the
spectral efficiency issignificantly reduced. In the
proposed scheme, the embeddedpilots would some
how reduce the spectral efficiency, but thepenalty
is very small, since the proposed A-SP signal
recovery algorithm only requires a very small
number of observationsO Slog2 L S . In fact, for
the most common broadcasting channels with six
active paths, the number J = 36 ofthe embedded
pilots is enough for good channel recovery
performance.In the typical system configuration of
M = 256 and N =4096 ,the spectral efficiency of the
proposed CS-basedTFT-OFDM scheme is 93.29%,
which is only 0.83% less thanthat of the
conventional TDS-OFDM system.Theconstant 36symbol transmission parameter signaling (TPS)
used in the practical DTMB systemscan be
regarded as the pilots once after being
successfullydetected , which indicates that even the
negligible spectralefficiency loss can be avoided.
B)CRLB of the Channel Estimator:
Compared with the channel estimator in
DPN-OFDM systems, where the best mean square
error (MSE) performanceis σ 2 , the channel
estimator based on A-SP can achieve muchbetter
MSE performance, since S is much smaller than J,
andthe boosted power A is usually larger than 1.
The observation matrix T does not have orthogonal
columns, the CRLB cannot be achieved by the
practical channel estimator. However, due to the
random positions of the pilots used in TFT-OFDM
and the random locations of active paths of
wireless channels, the matrix T has imperfect but
approximate orthogonal columns.
A). Spectral Efficiency:
C).Computational Complexity:
The spectral efficiency of different TDSOFDM schemes with the ideal OFDM system
without anyoverhead . The length of the PN
sequence is M = 256and the pilot number
In the CS-based CE method, the M-point
circular correlation
could be efficiently
implemented by M-point FFT, so the
corresponding complexity is O Mlog2 (M) /2 . It
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requires the complexity of O Mlog2 (M) /4 + 3M
for the cyclicity reconstruction operation. In fact,
the main computational burden of the proposed
method is the A-SP algorithm used to acquire the
actual path delays .
Each iteration has the complexity of O J L
+ S2 , and the overall complexity of SP comprising
S iterations is O JS L + S2 and S − S0 iterations are
required by A-SP, since some of the locations of
the significant taps have been detected already, the
complexity of the proposed A-SP is reduced to O J
(S − S0 ) L + S2 . So the complexity of A-SP is
lower than that of SP.
simulations.The typical six-tap ITU-VB channel
model(S = 6, L = 152) is adopted for performance
evaluation.Furthermore, the State Administration
of Radio, Film, andTelevision 8 (SARFT-8)
channel model (S = 6, L = 241) witha very strong
echo path close to the GI length and the modified
ITU-VB channel (S = 7, L = 303) with an
extremelylong path delay exceeding the GI length
are also adoptedto evaluate the system
performance.
7.Simulation results
This section investigates the performance
of the CS-basedCE for TFT-OFDM under typical
roadcasting channels. Thesignal bandwidth is 7.56
MHz locating at a central frequency of 760 MHz.
The OFDM block length N is 4096,and the GI
length M is 256. The low-density paritycheck(LDPC) code with code rate of 0.6 and code
length of7488 in DTMB is adopted.The wellknown iterativedecoding algorithm called belief
propagation (BP) is usedwith the maximum
iteration number of 30.The modulation schemes
256 QAM for the static channel and 16QAM with a
receiver velocity of 60 km/h are both considered to
evaluate the support for UHDTV and mobile
services,respectively.
Fig.6:MSE performance comparison under the modified
SARFT-8 channelwith the channel length larger than the GI
length
Fig: 5and 6 present the MSE performance
comparison of theproposed scheme with the
onventional DPN-OFDM and CS-based TDSOFDM schemes under three different channelswith
different channel lengths. It can be seen from Fig. 5
thatunder the ITU-VB channel, the MSE
performance of the proposed scheme enjoys a
significant SNR gain of 4 dB and 10 Dbcompared
to those of CS-based TDS-OFDM and DPNOFDM,respectively, when the target MSE of 10−3
is considered. Ifthe channel length L is fairly close
to the GI length M, seethe SARFT-8 channel
considered in Fig. 6, the MSE performance of the
proposed scheme is 7.5 dB better than that ofDPNOFDM, while the recent CS-based TDS-OFDM
cannotwork due to the reduced size of the IBI-free
region.
Fig.5: MSE performance comparison under the ITU-VB channel
with thechannel length smaller than the GI length.
The multipath channel parameters used for
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Conclusion
Fig.7 BER performance comparison under the ITU-VB channel
.
under the ITU-VB channel, the BER performance
of the proposed scheme enjoys a significant Eb /N0
gain of about 1 dB and 2.5 dB compared with CSbased TDS-OFDM and DPN-OFDM, respectively,
when the target BER of 10−4 is considered.
This paper proposes a CS-based CE
method for OFDM transmission scheme called
TFT-OFDM, whereby the training information
exists in both time and frequency domains. The
corresponding joint time-frequency channel
estimation utilizes the time domain TS without
interference cancellation to estimate the channel
path delays, while the channel path coefficients are
acquired by using the pilot groups scattered within
the OFDM symbol. The MSE performance of this
method outperforms the conventional schemes and
is close to the CRLB bysimultaneously exploiting
the time-domain PN sequence andfrequencydomain pilots. Simulation results show that the
proposed scheme has a good BER performance in
both static andmobile scenarios and can well
support the 256 QAM, especially when the
maximum channel delay spread is fairly closeto or
even larger than the GI length. Besides, by using
the auxiliary channel information, the proposed ASP algorithm haslower complexity than the
conventional SP algorithm. Thus,this scheme is
expected to extend TDS-OFDM in the emerging
UHDTV applications under SFN with long channel
delayspread. Furthermore, for CP-OFDM system
with time-domainpreamble or TS, this scheme can
also be applied.
REFERENCES
Fig.8 BER performance comparison under the SARFT-8
channel
Fig. 8 that under the SARFT-8 channel, the BER
performance of the proposed scheme is about 2 dB
better than that of the DPN-OFDM scheme, while
the CS-based TDS-OFDM scheme cannot work
due to the IBI-free region is severely ontaminated
by the long channel
1.
J. Wang, Z. Yang, C. Pan, and J. Song, “Iterative padding
subtraction of the PN sequence for the TDS-OFDM over
broadcast channels,” IEEE Trans. Consum. Electron., vol.
51, no. 11, pp. 1148–1152, Nov. 2005.
2.
Z. Tang, R. Cannizzaro, G. Leus, and P. Banelli, “Pilotassisted time varying channel estimation for OFDM
systems,” IEEE Trans. Signal Process, vol. 55, no.5,
pp.2226–2238, May 2007.
3.
J. Fu, J. Wang, J. Song, C. Pan, and Z. Yang, “A
simplified equalization method for dual PN-sequence
padding TDS-OFDM systems,” IEEE Trans. Broadcast.,
vol. 54, no. 4, pp. 825–830, Dec. 2008.
4.
W. Dai and O. Milenkovic, “Subspace pursuit for
compressive sensing signal reconstruction,” IEEE Trans.
Inf. Theory, vol. 55, no. 5, pp. 2230–2249, May 2009.
5.
L. He, F. Yang, C. Zhang, and Z. Wang, “Synchronization
for TDSOFDM over multipath fading channels,” IEEE
75
TECHNOLOGIES
(ICRACST’15)
TH
25 MARCH 2015
Trans. Consum. Electron.,vol. 56, no. 4, pp. 2141–2147,
Nov.2010.
6.
L. Dai, Z. Wang, and S. Chen, “A novel uplink multiple
access scheme based on TDS-FDMA,” IEEE Trans.
Wireless Commun., vol. 10, no. 3, pp. 757–761, Mar.
2011.
7.
L. Dai, Z. Wang, and Z. Yang, “Compressive sensing
based time domain synchronous OFDM transmission for
vehicular communications,” IEEE J. Sel. Areas Commun.,
vol. 31, no. 9, pp. 460–469, Sep. 2013.
8.
Linglong Dai, Jintao Wang and ZhaochengWangTsinghua
National Laboratory for Information Science and
Technology, Tsinghua University, China “Time Domain
Synchronous OFDM Based onSimultaneous MultiChannel Reconstruction’’.
9.
J. Xiong, L. Gui, H. Liu, and P. Cheng, “On channel
estimation andequalization in 2x1 MISO TDS-OFDM
based terrestrial DTVsystems”IEEE Trans. Broadcast.,
vol. 58, no. 1, pp. 130–138, Mar. 2012.
10. K. Yan, F. Yang, C. Pan, and J. Song, “Reception quality
predictionin a single frequency network for the DTMB
standard,” IEEE Trans.Broadcast., vol. 58, no. 4, pp. 629–
636, Dec. 2012.
11. S. Li, J. Xiong, L. Gui, and Y. Xu, “A generalized
analytical solution to channel estimation with intersymbol
interference cancelation and cochannelinterference
cancelation for single input single output/multiple input
single output digital terrestrial multimedia broadcasting
systems,”IEEE Trans. Broadcast., vol. 59, no. 1, pp. 116–
128, Mar. 2013.
12. B. Ai, J. Ge, and Y. Wang, “Symbol synchronization
technique in COFDM systems,” IEEE Trans. Broadcast.,
vol. 50, no. 1, pp. 56–62, Mar. 2004.
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