Transcript Example - Jenn Wei Lin

Fundamentals of Wireless
Communications and Its Recent
Developments
鍾偉和
助研究員
中央研究院 資訊科技創新研究中心
http://www.citi.sinica.edu.tw/pages/whc/vita_zh.html
[email protected]
Research Center for Information Technology
Innovation, Academia Sinica-Overview
• Formally Founded in 2007, Started Operation in Sept.
2008
• The 31st youngest research unit in Academia Sinica
• Faculty Member and Research Staff
– Tenure-track appointments(Research fellow): 14
– Research assistants (postdocs): 220+
– Jointly appointed faculty:50+
• Joint advisory with universities
• Collaborations with industries
2
Outline
I. Introduction to communication system
II. MIMO System
III. Wireless Local Area Network(WLAN)
IV. WiMax
3
Wireless Networks are Overloaded
• AT&T reported that mobile data traffic increases
5,000% in the past three years
congested
I. Introduction to communication system
– Mathematical models for channels
– Bandpass signals
– Random process
– Sampling theorem
– Digital modulation
– Types of Codes in communication system
5
Functional diagram of a
communication system
6
Communication channels and their
characteristics
7
• Physical channel media
– magnetic-electrical signaled wire channel
– modulated light beam optical (fiber) channel
– antenna radiated wireless channel
• Noise characteristic
–
–
–
–
thermal noise (additive noise)
signal attenuation
amplitude and phase distortion
multi-path distortion
• Limitation of channel usage
– transmitter power
– receiver sensitivity
– channel capacity (such as bandwidth)
8
Mathematical models for
communication channels
1. Additive noise channel:
where α is the attenuation factor, s(t) is the
transmitted signal, and n(t) is the additive
random noise process. (Note: Additive Gaussian noise
channel: If n(t) is a Gaussian noise process.)
9
2. The linear filter channel with additive noise:
10
3. The linear time-variant filter channel with
additive noise:
c(τ ;t) : τ is the argument for filtering;
t is the argument for time-dependence.
(The time-invariant filter can be viewed as a special
case of the time-variant filter. Cf. the next slide.)
11
Example:
12
• The linear time-variant filter channel with
additive noise:
c(τ ;t) usually has the form
where {ak(t)} represents the possibly time-variant
attenuation factor for the L multipath propagation
paths, and {τk} are the corresponding time
delays. Hence,
13
Example : The linear time-variant filter channel
with additive noise:
14
Band-pass signals and systems
• Representation of band-pass:
– Carrier modulation : carrier =
•
: Amplitude modulation
•
: Frequency modulation
•
: Phase modulation
where m(t ) is the baseband signal.
15
– The transmitted signal (after carrier
modulation)
• is usually a real-valued bandpass signal.
• Mathematical model of a real-valued narrowband
bandpass signal:
16
• For analytical convenience, the real-valued
transmitted bandpass signal is usually analyzed
in terms of its complex-valued equivalent
lowpass signal.
• We need to Develop a mathematical
representation (in time domain) of S+(f) and
S−(f).
17
.
18
19
Previously, we discussed the representations
of deterministic signals.
We now turn to discuss stochastically modeled
signals, i.e., stochastic processes.
20
Random process
• Engineers :
A random process is a collection of random
variables that arise in the same probability experiment.
• Mathematicians :
A random process is a collection of random variables
that are defined on a common probability space.
It is usually denoted by
21
Complex-valued random processes
• Auto-correlation function
22
• Cross-correlation function for two complex-valued
random processes:
23
Sampling theorem
Deterministic signal
• Band-limited
– A deterministic signal (or waveform) s(t) is said to be
(absolutely) band-limited if
• Sampling Theorem
– A band-limited signal can be reconstructed by its samples
if the sampling rate is greater than 2W (Nyquist rate). The
reconstruction formula is
The sinc function sinc(t) is evluated by sin(t)/t.
24
Random process
• Band-limited random process
– Definition : A (WSS) random process Xt is said to be bandlimited if
– Hence,
• Sampling representation of a random process
– For a band-limited stationary stochastic process Xt
25
Digital modulation
26
Example: M = 8
27
Memoryless modulation methods
• Digital pulse amplitude modulated (PAM) signals
(Amplitude-Shift Keying or ASK)
• Digital phase-modulated (PM) signals (Phase Shift
Keying or PSK)
• Quadrature amplitude modulated (QAM) signals
• Multidimensional modulated signals
– General
– Orthogonal
• Mutidimensional
• Biorthogonal
• Simplex signals
28
• (M-level) pulse amplitude modulated (M-PAM) signals
– Channel symbol :
– Example: M = 4
• The distance between two adjacent signal amplitude = 2d.
• Bit interval = Tb = 1/R, symbol interval = T and k =log2M.
Then symbol rate = symbol / sec = 1 / T = R / k (Note T = k
Tb = k / R).
29
Vectorization of M-PAM signals (Gram Schmidt)
30
• Transmitted energy of M-PAM signals
• Error consideration
– The most possible error is the erroneous selection of an adjacent
amplitude to the transmitted signal amplitude.
– Therefore, the mapping (from bit pattern to channel symbol) is
assigned to result in that the adjacent signal amplitudes differ by
exactly one bit. (Gray encoding)
– In such a way, the most possible bit error pattern caused by the
noise is a single bit error.
– Gray code (Signal space diagram : one dimension)
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• Euclidean distance
For Channel symbol, m = 1~M:
Euclidean distance:
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• Single Side Band (SSB) PAM
– g(t) is real => G(f) is symmetric.
– Consequently, the previous PAM is based on DSB transmission
which requires twice the bandwidth.
– Recall
where
is the Hilbert
transform of g(t).
33
• Transmitted energy of SSB M-PAM signals
• Recall : transmitted energy of DSB M-PAM signals
Under the condition that DSB M-PAM and SSB M-PAM signals require
the same transmitted energy, the latter consumes only half of the
bandwidth of the former by the cost of an additional Hilbert transformer.
34
35
• Applications of PAM
36
• Phase-modulated (PM) signals
– Channel symbol
– Example: M = 4
37
38
• Transmission energy of PM signals
– Advantages of PM signals : equal energy for every channel
symbol.
• Error consideration
– The most possible error is the erroneous selection of an adjacent
phase of the transmitted signal.
– Therefore, we assign the mapping from bit pattern to channel
symbol as the adjacent signal phase differs by one bit. (Gray
encoding).
– In such a way, the most possible bit error pattern caused by the
noise is a single-bit error.
39
• (Two dimensional) signal space diagram for Gray code
• Euclidean distance
40
• SSB for PM ?
– Note that the baseband signal
is not a real
number. (Hence, non - symmetric in spectrum.) So, there
is no SSB version for PM.
– This can be considered as a tradeoff, when being
compared to PAM.
41
Types of Codes
• Channel codes
– data transmission codes (error-correcting codes)
– data translation codes (to meet channel constraints)
• Source codes
– lossless data compression codes
– lossy data compression codes
• Secrecy codes
42
Channel Codes
Concept:
The purpose of channel encoder-decoder pair is to correct
the error introduced by the channel (noise, fading,
interference). The approach is to add redundancy (that is
algebraic related to the information to be transmitted) in the
channel encoder and to use this redundancy (and algebraic
relation) at the decoder to reconstruct the channel
input sequence as accurately as possible.
43
• Shannon’s noisy channel coding theorem
– “With sufficient but finite redundancy properly introduced at the channel
encoder, it is possible for the channel decoder to reconstruct the input
sequence to any degree of accuracy desired, provided that the input
rate to the channel encoder is less than a given value called channel
capacity.”
• General Design Criteria
– For (digital) communication system users, BER is usually the
most important performance measure.
– Spectral efficiency (in bits/sec/Hz) is the ultimate concern from
system engineering’s viewpoint.
• Other general design criteria include:
–
–
–
–
–
Complexity (delay)
Cost
Weight
Heat dissipation
Fault tolerance
44
• Spectral Efficiency
– Definition:
η = data rate/required bandwidth (bits/s/Hz)
• The Shannon-Hartley capacity of a band-limited AWGN
channel of bandwidth W is given by
C = W log2(1+S/N)
where S/N=(EbR)/(N0W).
• Hence the maximum spectral (bandwidth) efficiency ηmax
is equal to
ηmax = log2(1+S/N) =C/W≤R/W (bits/s/Hz)
45
Examples of simple channel codes
• Single-parity-check codes
– add a single parity-check bit to a k-bit
message word
– code rate k/n = k/(k+1) = (n-1)/n
• Repetition codes
– repeat the information bit n times
– code rate = 1/n
46
• Example: (3,2) parity check code
m {00,01,10,11}, C {000;011;101;110}
001,010,10 0,111  C
• Definition: Hamming weight of a binary codeword is
defined as the number of 1 in the codeword.
• Definition: Hamming distance between two binary
codeword is the number of places where they differ.
• For the above example, w(000)=0, w(011)=2, w(101)=2,
w(110)=2, d(011,101) = 2.
47
• Example: (3,1) Repetition code
m {0,1},
C  {000,111}
– Repetition decoding :To determine the value of a particular bit,
we look at the received copies of the bit in the bitstream and
choose the value that occurs more frequently.
– Received bitstream c’ = 110, estimated m = 1.
48
• A good code is one whose minimum distance is large.
For the previous example, the (3,2) parity check code
has dmin = 2.
49
Convolutional Codes
• Encoding of information stream rather than
information blocks
• Easy implementation using shift register
• Decoding is mostly performed by the
Viterbi Algorithm
– Errors in Viterbi decoding algorithms for
convolutional codes tend to occur in bursts
because they result from taking a wrong path
in a trellis.
50
Convolutional Codes: (n=2, k=1, M=2)
Encoder
51
State diagram
52
Trellis
53
Interleaver
• Interleaving is a technique commonly used
in communication systems to overcome
correlated channel noise such as burst
error or fading.
• The interleaver rearranges input data such
that consecutive data are spaced apart. At
the receiver end, the interleaved data is
arranged back into the original sequence
by the de-interleaver.
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Example: Block interleaver
55
56
Information Capacity Theorem
• The information capacity (or channel capacity) C of a
continuous channel with bandwidth B Hertz can be
perturbed by additive Gaussian white noise of power
spectral density N0/2, provided bandwidth B satisfies
– P is the average transmitted power P =EbRb (for an ideal system,
Rb = C).
– Eb is the transmitted energy per bit.
– Rb is transmission rate.
57
Turbo Codes
• The turbo code concept was first
introduced by C. Berrou in 1993. Today,
Turbo Codes are considered as the most
efficient coding schemes for forward error
correcting (FEC).
• Scheme with components (simple
convolutional or block codes, interleaver,
soft-decision decoder, etc.)
58
Turbo encoder
59
Turbo decoder
60
Shannon Limit
61
II. Typical MIMO System
– System and signal model
– ML Detector
– Linear Detector
1. ZF detector
2. MMSE detector
62
System and signal model
• Signal model : y = Hx + v where x ∈ Cm, y ∈ Cn, H ∈ Cn×m
is a known channel matrix, and n ≥ m.
• The elements of x belong to a finite alphabet S of size |S|.
• Example:
BPSK: S = {1,−1}, and |S| = 2.
4-PSK: S = {1 + j, 1 − j,−1 + j,−1 − j}, and |S| = 4
63
Typical MIMO System
• Maximum Likelihood (ML) Detection
• QR-decomposition of H: H = QR, where Q ∈ Cn×m:
orthogonal (QHQ = I), and R ∈ Cm×m: upper triangular.
• Equivalent problem:
where y′ = Qhy.
64
ML Detection
• Tree Representation
• Calculation of ||y′ − Rx|| can be broken down into layers
and successively examined:
Note that xi  S
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• The problem can be written as
66
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Linear Detectors
• Suboptimal but very low complexity
• Signal model: y = Hx + v
• After Linear Detector: x  Wy  W( Hx  v )
where W  C mn .
• Each estimated symbol xˆk is determined by
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Zero-Forcing (ZF) Detector
– ZF Criterion: WH = I
– Since m ≥ n, there is in general no such solution.
– Least square solution: WZF = (HHH)−1HH
• ZF detection:
H
-1 H
~
xZF  WZF y  x  (H H) H v
• Apply the principle of the linear detector, we can find
each estimated symbol xˆZF ,k
69
Minimum Mean Square Error (MMSE) Detector
• Assume E[x] = ,E[xxH] = σx2I; E[v] = 0 and E[vvH] = σv2I
• MMSE criterion: J  minW E[|| ~
x  x ||2 ]. Note~
x  Wy
• Optimal W :
x  x ||2 ]
1. Compute E[|| ~
2. Let J  0
W
3. Apply two formulas


tr{AXB }  A H B H and
tr{XBX H }  XB H  XB
X
X
Fine the optimal W
WMMSE   x2 ( x2HH H   v2I)1 HH
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• The solution is Wiener solution.
• MMSE detection
• Common use since simple and analytic.
71
III. Wireless Local Area Network (WLAN)
– 802.11 Physical Layer
1. 802.11b (1999)
2. 802.11a (1999)
3. 802.11g (2003)
72
Wireless Local Area
Network(WLAN)
• IEEE 802.11 is a set of standards for
implementing WLAN computer
communication in the 2.4, 3.6 and 5 GHz
frequency bands.
• They are created and maintained by the
IEEE LAN/MAN Standards Committee
(IEEE 802).
73
802.11 Physical Layer
• (1999) 802.11b (HR/DSSS at 2.4GHz)
– 5.5 Mbps and 11 Mbps
• (1999) 802.11a (OFDM at 5GHz)
– 6 Mbps to 54 Mbps
• (2003) 802.11g (OFDM at 2.4 GHz)
– Maximal rate: 54 Mbps
– Maximal rate: get up to 108 Mbps (Atheros’ Super G)
74
802.11b
• 802.11b - Data Transmission
– Transmit 300 to 500 feet
– Frequency-hopping spread-spectrum (FHSS)
• 1 or 2 Mbps
– Direct-sequence spread-spectrum (DSSS)
• 1, 2, 5.5, or 11 Mbps
• 802.11b - Frequencies and Bandwidth
– 2.4000 to 2.4835 GHz frequency
– 22 MHz bandwidth per channel
– 3 MHz guard bands
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• Transmission
– 1 and 2 Mbps speeds
• Use 11-bit Barker sequence
• A Barker sequence is a string of digits of length
such that
l k
|  ai ai k | 1,
i 1
for all 1  k  l.
– Higher data rate, 5.5 and 11 Mbps speeds
• Use complementary code keying (CCK)
• The CCK is a variation and improvement on M-ary
Orthogonal Keying Modulation.
76
CCK
• CCK is a “single carrier” system, meaning
that all data is transmitted by modulating a
single radio frequency or carrier.
Signal bandwidth
Single carrier
frequency
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傳輸速率
展頻碼長度
（Data
Rate）
（Code Length
）
1Mbps
2 Mbps
5.5 Mbps
11 Mbps
調變方式
（Modulation）
符元率
符元內之
位元數
（Symbo （Bits/
l Rate） Symbol
）
直接序列展頻/差分
二相位移鍵調變
（DSSS/DBPSF）
1Msps
1
直接序列展頻/差分
四相位移鍵調變
（DSSS/DQPSF）
1Msps
2
8（CCK）
互補碼調變/差分四
相位移鍵調變
（CCK/DQPSF）
1.375Msps
4
8（CCK）
互補碼調變/差分四
相位移鍵調變
（CCK/DQPSF）
1.375Msps
8
11（Barker
sequence）
11（Barker
sequence）
表 IEEE 802.11b資料率特性
78
79
802.11a
• 802.11a - Data Transmission
– Transmit 100 to 150 feet
– Orthogonal Frequency-Division Multiplexing (OFDM)
• 6 to 54 Mbps
• OFDM is a “multi-carrier” modulation scheme.
• Data is split up among several closely spaced
“subcarriers”, increasing reliability and speed
• 802.11a - Frequencies and Bandwidth
– 12 channels
– 20 MHz bandwidth per channel
– Broken into 52 separate channels
80
• 48 transmit, 4 used for control
Orthogonal Frequency Division Multiplexing
– was first implemented in 802.11a.
– OFDM is a “multi-carrier” modulation scheme.
– Data is split up among several closely spaced
“subcarriers” or frequencies, increasing
reliability and speed
81
• Transmission
– 6 and 9 Mbps speeds
• Use 24-bit Barker sequence
• Lowest rate: 6 Mbps
– BPSK - 48 bits per symbol, Rate 1/2 coding
» 24 data bits per symbol
» 24 x 250 ksps = 6 Mbps
– 12, 24 and 28 Mbps speeds
• Use binary phase shift keying (BPSK)
82
83
Comparison
• Physical Layer
802.11b
DSSS
• 3 - 22 MHz channels
• Data Rates: up to 11
Mbps (5.5 is norm)
• Frequency Range up to
300 Feet
802.11a
OFDM
• 12 – 20 MHz channels
• Data rates: up to 54
Mbps (12-24 is norm)
• Frequency Range up to
300 Feet
84
Range Comparison
85
802.11g (Atheros’ Super G)
How does Atheros’ Super G make 802.11g faster?
1. Compression
– Link-level hardware compression utilizes the
connection more efficiently and maximizes
bandwidth.
– In hardware compression, the compression
computations are offloaded to a secondary
hardware module. This frees the central CPU
from the computationally intensive task of
compression calculations.
86
Push Toward High Data-Rate
Systems
Why
Congested
?
Multiple Antenna
Systems
Data rate
1 Gbps
LTE (8 x 8 MIMO)
300 Mbps
802.11n (4x4 MIMO)
WiMax (8 x 8 MIMO)
56-128 Mbps
11-54 Mbps
56-114 kbps
30-40 kbps
802.11 a/b/g
GPRS
GSM
199X 2000
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Far below
theoretical bound
2003
2009
2007
2012
year
全球無線寬頻通訊標準之演進
88
IV. WiMAX
• WiMAX Network Architecture
• Recent Technologies in WiMAX
– 802.16j
– 802.16m
• Overview of IEEE 802.16m
• Advanced Features & Challenges of IEEE 802.16m
89
WiMax
• WiMAX Forum
– WiMAX: Worldwide Interoperability for Microwave
Access
– Formed in Apr 2001, by Intel, Proxim, Airspan,
Fujitsu, etc.
– 500+ members including Intel, R&S, Alvarion,
Wavesat, PicoChip, Sony, Samsung, Nokia, TI, ADI,
III, ITRI, etc.
– Support IEEE 802.16 standards
• IEEE 802.16 Standards
– 802.16 d/e define data and control plane functions in
wireless PHY/MAC
– 802.16 f/g/i define management plane functions
90
WiMAX Network Architecture
Inter-ASN Mobility: R3, R4
Intra-ASN Mobility: R6, R8
R3
ASN GW
R3
ASN GW
R4
R6 R6
R6
R8
R8
WiMAX
BS
R1
R1
MS: Mobile Station
WiMAX MS
SS: Stationary Station
Rx: Reference point x
ASN GW: Access Service Network Gateway
R6
R1
R1
WiMAX MS
R1
WiMAX
BS
WiMAX SS
91
Recent Technologies in WiMAX
• 802.16j Multi-hop Relay
– Aiming at developing relay based on IEEE802.16e, to gain:
• Coverage extension
• Throughput enhancement
– Scope
• To specify OFDMA PHY and MAC enhancement to IEEE Std.
802.16 for licensed bands to enable the operation of relay stations
• Subscriber station specifications are not changed
• 802.16m
– Advanced Air Interface for BWA in the future
• Moving towards 4G
– Scope:
• To amend the IEEE 802.16 WirelessMAN-OFDMA to provide an
advanced air interface for operation in licensed bands
• To meet the cellular layer requirements of IMT-Advanced next
generation mobile networks
• To provide continuing support for legacy WirelessMAN-OFDMA
equipment
92
Overview of IEEE 802.16m
• IEEE 802.16m provides the performance improvements necessary
to support future advanced services and applications for 4G
communications.
• Major worldwide governmental and industrial organizations,
including ARIB, TTA, and the WiMAX Forum, are adopting this
standard.
• IEEE 802.16m Support
–
–
–
–
low to high mobility applications
a wide range of data rates in multiple user environments
high-quality multimedia applications
significant improvements in performance and quality of service
93
MIMO architecture for the downlink of 802.16m systems.
94
Features of 802.16m
• Aggregate Data Rate:
– 100 Mbps for mobile stations,
– 1 Gbps for fixed
• Operating Radio Frequency: < 6 GHz
• MIMO support: 4 or 8 streams, no limit on antennas
• Coverage: 3 km, 5-30 km and 30-100 km
95
Advanced Features & Challenges of 16m
1. Unified single-user/multi-user MIMO Architecture
– support various advanced multi-antenna processing techniques
including open-loop and closed single-user/multi-user MIMO
schemes (single stream and multi-stream)
– Support multi-cell MIMO techniques
2. Multi-carrier support
– The RF carriers may be of different bandwidths and can be noncontiguous or belong to different frequency bands
– The channels may be of different duplexing modes, e.g. FDD, TDD
– Support wider band (up to 100MHz) by BW aggregation across
contiguous or non-contiguous channels
96
3. Multi-hop relay-enabled architecture
– Improve the SINR in the cell for coverage extension and
throughput enhancement
4. Support of femto-cells and self-organization
– Femto-cells are low power BS at homes achieving FMC
– Self-configuration by allowing real plug and play installation of
network nodes and cells
– Self-optimization by allowing automated or autonomous
optimization of network performance with respect to service
availability, QoS, network efficiency and throughput
97
5. Enhanced multicast and broadcast service
– Multi-carriers with dedicated broadcast only carriers
– Single/multi-BS MBS
6. Multi-rate operation and handover
– Support interworking with IEEE 802.11, GSM/EDGE, 3GPP,
3GPP2, CDMA2000etc.
7. Multi-radio coexistence
– MS reports its co-located radio activities to BS
– Accordingly, BS can operates properly via scheduling to support
multi-radio coexistence
98
References
1.
2.
3.
4.
5.
6.
7.
8.
9.
WiMAX無線寬頻技術與垂直 智慧網通系統研究所 財團法人資訊工業策進會
Digital Signal Processing (4th Edition): John G. Proakis
Ioannis Papapanagiotou, Dimitris Toumpakaris, Jungwon Lee, Michael
Devetsikiotis, “A Survey of Mobile WiMAX IEEE 802.16m Standard” IEEE
COMMUNICATIONS SURVEYS & TUTORIALS, VOL. 11, NO. 4,
FOURTH QUARTER 2009
IEEE 802.11: Wireless LAN Medium Access Control (MAC) and Physical
Layer (PHY) Specifications
"802.11a-1999 High-speed Physical Layer in the 5 GHz band“
"802.11b-1999 Higher Speed Physical Layer Extension in the 2.4 GHz
band“
"IEEE 802.11g-2003: Further Higher Data Rate Extension in the 2.4 GHz
Band“
http://zh.wikipedia.org/wiki/IEEE_802.11
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and Applications”
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Algorithms and Applications
12. Lung-Sheng Tsai, Wei-Ho Chung*, and Da-Shan Shiu, "Lower Bounds on
the Correlation Property for OFDM Sequences with Spectral-Null
Constraints," IEEE Transactions on Wireless Communications, Volume 10,
Issue 8, pp. 2652-2659, August 2011.
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Autocorrelation and Low PAPR OFDM Sequences Under Spectral
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Transactions on Signal Processing, Volume 59, Issue 5, pp. 2234-2243,
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Communications, 2012.
Thank you
[email protected]
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