10-WiMax.ppt

Report
10-IEEE802.16 and WiMax
Applications: various Area Networks
According to the applications, we define three “Area Networks”:
• Personal Area Network (PAN), for communications within a few meters. This is the
typical Bluetooth or Zigbee application between between personal devices such as
your cell phone, desktop, earpiece and so on;
• Local Area Network (LAN), for communications up 300 meters. Access points at
the airport, coffee shops, wireless networking at home. Typical standard is
IEEE802.11 (WiFi) or HyperLan in Europe. It is implemented by access points, but it
does not support mobility;
• Wide Area Network (WAN), for cellular communications, implemented by towers.
Mobility is fully supported, so you can move from one cell to the next without
interruption. Currently it is implemented by Spread Spectrum Technology via CDMA,
CDMA-2000, TD-SCDMA, EDGE and so on. The current technology, 3G, supports
voice and data on separate networks. For current developments, 4G technology will
be supporting both data and voice on the same network and the standard IEEE802.16
(WiMax) and Long Term Evolution (LTE) are the candidates
More Applications
1. WLAN (Wireless Local Area Network) standards and WiFi. In particular:
• IEEE 802.11a in Europe and North America
• HiperLAN /2 (High Performance LAN type 2) in Europe and North America
• MMAC (Mobile Multimedia Access Communication) in Japan
2. WMAN (Wireless Metropolitan Network) and WiMax
• IEEE 802.16
3. Digital Broadcasting
• Digital Audio and Video Broadcasting (DAB, DVB) in Europe
4. Ultra Wide Band (UWB) Modulation
• a very large bandwidth for a very short time.
5. Proposed for IEEE 802.20 (to come) for high mobility communications
(cars, trains …)
IEEE 802.16 Standard
IEEE 802.16 2004 ( http://www.ieee802.org/16/ ):
Part 16: Air Interface for Fixed Broadband Wireless Access
Systems
From the Abstract:
• It specifies air interface for fixed Broadband Wireless Access (BWA) systems
supporting multimedia services;
• MAC supports point to multipoint with optional mesh topology;
• multiple physical layer (PHY) each suited to a particular operational environment:
IEEE 802.16-2004 Standard
Table 1 (Section 1.3.4) Air Interface Nomenclature:
•
WirelessMAN-SC, Single Carrier (SC), Line of Sight (LOS), 10-66GHz, TDD/FDD
•
WirelessMAN-SCa, SC, 2-11GHz licensed bands,TDD/FDD
•
WirelessMAN OFDM, 2-11GHZ licensed bands,TDD/FDD
•
WirelessMAN-OFDMA, 2-11GHz licensed bands,TDD/FDD
•
WirelessHUMAN 2-11GHz, unlicensed,TDD
MAN: Metropolitan Area Network
HUMAN: High Speed Unlicensed MAN
IEEE 802.16e 2005:
Part 16: Air Interface for Fixed and Mobile Broadband
Wireless Access Systems
Amendment 2: Physical and Medium Access Control Layers
for Combined Fixed and Mobile Operation in Licensed
Bands
and
Corrigendum 1
Scope (Section 1.1):
• it enhances IEEE 802.16-2004 to support mobility at vehicular speed, for combined
fixed and mobile Broadband Wireless Access;
• higher level handover between base stations;
• licensed bands below 6GHz.
IEEE 802.16-2004: Reference Model (Section 1.4), Figure 1
External Data
By Layers:
CS-SAP
Service Specific Convergence
Sublayer (CS)
SAP=Service Access Point
Section 5
MAC-SAP
MAC
MAC Common Part Convergence
Sublayer (CS)
Security Sublayer
Section 6
Section 7
PHY-SAP
PHY
Physical Layer
Section 8
Parameters for IEEE 802.16 (OFDM only)
802.16-2004
802.16e-2005
Frequency Band
2GHz-11GHz
2GHz-11GHz fixed
2GHz-6GHz mobile
OFDM carriers
OFDM: 256
OFDMA: 2048
OFDM: 256
OFDMA: 128, 256, 512,1024,
2048
Modulation
QPSK, 16QAM, 64QAM
QPSK, 16QAM, 64QAM
Transmission Rate
1Mbps-75Mbps
1Mbps-75Mbps
Duplexing
TDD or FDD
TDD or FDD
Channel Bandwidth
(1,2,4,8)x1.75MHz
(1,4,8,12)x1.25MHz
8.75MHz
(1,2,4,8)x1.75MHz
(1,4,8,12)x1.25MHz
8.75MHz
IEEE802.16 Structure
data
randomization
data
De-rand.
Error
Correction
Coding
Error
Correction
Decoding
M-QAM
mod
OFDM
mod
M-QAM
dem
OFDM
dem
TX
RX
Choices:
Coding rates
M-QAM
1/2
2
2/3
4
3/4
16
5/6
64
OFDM
carriers
Channel
B/width
256
1.25 MHz
512
5 MHz
1024
10 MHz
2048
…
OFDM and OFDMA (Orthogonal Frequency Division Multiple Access)
• Mobile WiMax is based on OFDMA;
• OFDMA allows for subchannellization of data in both uplink and downlink;
• Subchannels are just subsets of the OFDM carriers: they can use contiguous or
randomly allocated frequencies;
• FUSC: Full Use of Subcarriers. Each subchannel has up to 48 subcarriers evenly
distributed through the entire band;
• PUSC: Partial Use of Subcarriers. Each subchannel has subcarriers randomly
allocated within clusters (14 subcarriers per cluster) .
Section 8.3.2: OFDM Symbol Parameters and Transmitted Signal
OFDM Symbol
Ts
Tg
guard
Tb
data
(CP)
Tg
1 1 1 1
 , ,
,
Tb
4 8 16 32
An OFDM Symbol is made of
• Data Carriers: data
• Pilot Carriers: synchronization and estimation
• Null Carriers: guard frequency bands and DC (at the modulating carrier)
pilots
data
frequency
Guard
channel
Guard
band
band
N guards  to provide frequency guards betw een cha nnels
N nulls  N guards  1 (D C subcarrier is alw ays zero)
N pilots 
pilots for channel tracking and synchronization
N data 
data subcarriers
N used  N pilots  N dat a
OFDM Subcarrier Parameters:
FFT size
256
128
512
1024
2048
N_used
200
108
426
850
1702
N_nulls
56
20
86
174
346
N_pilots
8
12
42
82
166
N_data
192
96
384
768
1536
            
Fixed
WiMax
Fixed and
Mobile
WiMax
IEEE 802.16, with N=256
Data (192)
Pilots (8)
Nulls (56)
X [k ]
k
n


0
12
x[ n  L ]
0
13

24
38
24
24
12
63
88
100
101

12
24

IFFT
155
156
168
193
24
218
24
12

243
255
255
IEEE802.16 Implementation
In addition to OFDM Modulator/Demodulator and Coding we need
• Time Synchronization: to detect when the packet begins
• Channel Estimation: needed in OFDM demodulator
• Channel Tracking: to track the time varying channel (for mobile only)
In addition we need
• Frequency Offset Estimation: to compensate for phase errors and noise in the
oscillators
• Offset tracking: to track synchronization errors
Basic Structure of the Receiver
Channel Estimation:
estimate the frequency
response of the channel
Time Synchronization:
detect the beginning of
the packet and OFDM
symbol
Received
Signal
Demodulated
Data
WiMax Demodulator
Time Synchronization
In IEEE802.16 (256 carriers, 64 CP) Time and Frequency Synchronization are
performed by the Preamble.
Long Preamble: composed of 2 OFDM Symbols
Short Preamble: only the Second OFDM Symbol
First OFDM Symbol
Second OFDM Symbol
320 samples
320 samples
2 repetitions of a long
pulse + CP
4 repetitions of a short
pulse+CP
64
Tg
64
64
Td
64
64
64
Tg
128
128
Td

The standard specifies the Down Link preamble as QPSK for subcarriers between -100
and +100:
 1  j,
PALL [ k ]  
0,
k   100 ,...,  1,  1,...,  100
otherwise
Using the periodicity of the FFT:
PALL [ k ], k  1,..., 100
1
PALL [ k ]  PALL [ 256  k ], k   100 ,...,  1
100
156
255
• Short Preamble, to obtain the 4 repetitions, choose only subcarriers multiple of 4:
*
 2 PALL
[ k ], if k mod 4  0
P4 [ k ]  
otherwise
0,
P4 [ k ]
p4[n]
FFT

0
4
8
64
252
64
64
255
0
255
p4[n]
Add Cyclic Prefix:
64
0
64
64
64
64
64
255
319
• Long Preamble: to obtain the 2 repetitions, choose only subcarriers multiple of 2 :
 2 PALL [ k ], if k mod 2  0
P2 [ k ]  
otherwise
0,
P2 [ k ]
p2[n]
FFT

0
2
4
6
8
128
252
255
0
255
254
128
p2[n]
Add Cyclic Prefix:
64
128
128



0
CP
319
Several combinations for Up Link, Down Link and Multiple Antennas.
We can generate a number of preambles as follows:
With 2 Transmitting Antennas:
 2 PALL [ k ], if k mod 2  0
P [k ]  
otherwise
0,
0
2
 2 PALL [ k ], if k mod 2  1
P [k ]  
otherwise
0,
1
2
With 4 Transmitting Antennas:
m  0
m  1, 2 ,3
*

2
P
[ k ], if k mod 4  0
0
ALL
P4 [ k ]  
otherwise
0,
*

P
[ k  2  m ], if k mod 4  m
m
ALL
P4 [ k ]  
otherwise
0,
Time Synchronization from Long Preamble
1. Coarse Time Synchronization using Signal Autocorrelation
Received signal:
preamble
64
128
OFDM Symbols

128
n0
Compute Crosscorrelation Coefficient:
2
127

ry [ n ] 
2
y [n ]
xcorr
z
 128
y [ n   ] y [ n  128   ]
*
0
 127
 127
2 
2 
  y [ n   ]     y [ n  128   ] 
 0
  0

Effect of Periodicity on Autocorrelation (no Multi Path). Let L=64.
Max starts at n  n 0  64
….
Same signal
y [n ]
64
128
data
128
n
n0
y [ n  128 ]
64
128
data
128
n
2
ry [ n ]
MAX when
y [ n ]  y [ n  128 ]
1
n 0  64
n0
n
Effect of Periodicity on Autocorrelation (no Multi Path):
… and ends at n  n 0
Same signal
y [n ]
64
128
data
128
n
n0
y [ n  128 ]
64
128
data
128
n
2
ry [ n ]
MAX when
y [ n ]  y [ n  128 ]
1
n
n 0  64
n0
Effect of Periodicity on Autocorrelation (with Multi Path of max length LC  L  64 ):
Max starts at n  n 0  64  LC
LC  L
Same signal
y [n ]
64
….
128
data
128
n
n0
y [ n  128 ]
64
128
data
128
n
2
ry [ n ]
MAX when
y [ n ]  y [ n  128 ]
1
n 0  64  LC
n0
n
Effect of Periodicity on Autocorrelation (with Multi Path of max length L C  L ):
and ends at n  n 0
LC  L
Same signal
y [n ]
64
128
data
128
n
n0
y [ n  128 ]
64
128
data
128
n
2
ry [ n ]
MAX when
y [ n ]  y [ n  128 ]
1
n
n 0  64  LC
n0
With Noise: y [ n ]  y R [ n ]  w [ n ]
Then, at the maximum:
2
127

ry [ n 0 ] 
y [ n 0  ] y [ n 0  128  ]
*
0
2
 127
 127
2 
2 
]

128

n
[
y

]

n
[
y
0
0

 


  0
 0
2
127

y R [ n0  ]
2
0

2
127

2
y R [ n 0  ]  w[ n 0  ]
0




1

R
SN


SN R
2
2
Information from Crosscorrelation coefficient:
Estimate of SNR
SN R 
rM AX
1  rM AX
r y [n ]
Estimate of Beginning
of Data n 0

Estimate of Channel Length L C  L  
2. Fine Time Synchronization using Cross Correlation with Preamble
y [n ]
127
ryp [ n ] 
xcorr

y[ n  ] p [ ]
*
l0
p[ n ]
Since the preamble is random (almost like white noise), it has a short autocorrelation:
y [n ]
64
128

128
ryp [ n ]
n
n0
p[ n ]
128
0
127
n
n 0  256
n 0  128
… with dispersive channel
y [n ]
127
ryp [ n ] 
xcorr

y[ n  ] p [ ]
*
l0
p[ n ]
Since the preamble is random, almost white, recall that the crosscorrelation yields the
impulse response of the channel
 | h[ n ] |
y [n ]
64
128

128
ryp [ n ]
n
n0
p[ n ]
128
0
127
n
n 0  256
n 0  128
However this expression is non causal.
It can be written as (change index   127   ):
127
ryp [ n ] 

y[ n  ] p [ ]
*
l0
127


y [ n  127  ] p [127  ]
*
l0
 ryp [ n  127 ]
Which van be computed as the output of an FIR Filter with impulse response:
*
*
~
p [ n ]  p [127  n ],
y [n ]
*
p [n]
n  0 ,..., 127
*
r yp [ n ]  y [ n ] * ~
p [n]
Taking the time delay into account we obtain:
*
ryp [ n ]
p [n]
y [n ]
Since the preamble is random, almost white, recall that the crosscorrelation yields the
impulse response of the channel
 | h[ n ] |
y [n ]
64
128

128
ryp [ n ]
n
n0
p[ n ]
128
0
127
n
n 0  129
n0  1
Compare the two (non dispersive channel):
Autocorrelation of
received data
ry
Crosscorrelation with
preamble
r yp
n 0  128
n0
n 0  64
Synchronization with Dispersive Channel
Autocorrelation of
received data
ry
Crosscorrelation with
preamble
r yp
Channel impulse
response
n0
Start of Data
Synchronization with Dispersive Channel
Let LC  L be the length of the channel impulse response
64  LC
Channel impulse
response
In order to determine the starting point, compute the energy on a sliding window and
choose the point of maximum energy
y [n ]

xcorr
p[ n ]
c [n ]
r yp [ n ]
c [n ]
r yp [ n ] 1
n  L 1
n
L=max length of
channel = length of CP
L 1
c[ n ] 
r
k 0
yp
[n  k ]
Maximum
energy
Example
y [n ]

xcorr
p[ n ]
r yp [ n ]
Impulse response
of channel
c [n ]
Auto
correlation
y [n ]
max
Cross
correlation
p[ n ]

c [n ]
Channel Estimation
Recall that, at the receiver, we need the frequency response of the channel:
 X m [0]



m-th data block  X m [k ]


 X m [ N  1]

w[ n ]
Ym [ 0 ]
OFDM
TX
h[n ]

OFDM
RX
Y m [k ]

Y m [ N  1]
Transmitted:
Received:
Ym [ k ]  H [ k ] X m [ k ]  W [ k ]
X m [k ]
H [k ]
channel freq.
response
W [k ]
From the Preamble: at the beginning of the received packet. The transmitted signal in
the preamble is known at the receiver: after time synchronization, we take the FFT of
the received preamble
Estimated initial time
n0
Received Preamble:
64
128
128
256 samples

FFT

Y [0]
Y [ k ]  H [ k ] X p [ k ]  W [ k ], k  0 ,..., 255
Y [k ]
Y [ 255 ]
Y [ k ]  H [ k ] X p [ k ]  W [ k ], k  0 ,..., 255
Solve for H [k ] using a Wiener Filter (due to noise):
*
Hˆ [ k ] 
Y [k ] X P [k ]
| X p [ k ] |  w
2
2
noise covariance
Problem: when
X p [k ]  0
we cannot compute the corresponding
frequency response H [k ]
X p [k ]  1  j
Fact: by definition,
X p [k ]  0
if
k  2 , 4 ,..., 100
k  156 ,158 ,..., 254
otherwise (ie DC, odd values,
frequency guards)
Two solutions:
1. Compute the channel estimate
Hˆ [ k ] 
Y [k ] X
*
preamble
[k ]
| X p [ k ] |  w
2
2
only for the frequencies k such that
X p [k ]  0
and interpolate for the other frequencies. This might not yield good results and the
channel estimate might be unreliable;
known


interpolate
k
2. Recall the FFT and use the fact that we know the maximum length L of the
channel impulse response
Y [k ]  H [k ] X p [k ]  W [k ]
Since the preamble is such that either
for the indices where | X p [ k ] |
*
Y [k ]
X p [k ]
2
2
 jk
n
 L 1
N
   h [ n ]e
 n0
| X p [ k ] | 0
or | X p [ k ] |
2
2 we can write:
X p [k ]

  W [k ]
2

*
so that we have 100 equations and L=64 unknowns.
for
k  2 , 4 ,..., 100
k  156 ,158 ,..., 254
This can be written in matrix form:
*
Y [k ]
X p [k ]
2
*
 vk h  W [k ]
X p [k ]
2
,
k  2 , 4 ,..., 100
k  156 ,158 ,..., 254
where

v k  1

 jk
e
2
256
 jk
e
2
256
( L  1)

,

 h[ 0 ] 


h [1]

h 





h
[
L

1
]


Write it in matrix form:
 12 Y [2] X *p [2]    v 2    h[0]   12 W [2] X *p [2] 

 


 





 
 1 Y [200] X * [200]    v    h[63]   1 W [200] X * [200] 
p
200
p

 2
2
 

100  1
100  64
64  1
z  Vh  e
100  1
*T
ˆ
h  V V
Least Squares solution

1
V
*T
z
this is ill conditioned.
eigenvalues
5
10
128
0
10
-5
10
-10
10
-15
10
0
10
1
20
*T
ˆ
h  V V   I  V z ,
*T
30
40
  10
50
3
60
70
Channel Frequency Response Estimation:
1
1. Generate matrix M   V *T V   I  V *T
kF=[2,4,6,…,100, 156, …, 254]’;
n=[0,…,63];
non-null frequencies (data and pilots)
time index for channel impulse response
V=exp(-j*(2*pi/256)*kF*n);
M=inv(V’*V+0.001*eye(64))*V’;
2. Generate vector z from received data y[n]:
Let n0 be the estimated beginning of the data, from time synchronization.
Then
y0=y(n0-256:n0-1);
received preamble
Y0=fft(y0);
decoded preamble
z=Y0(kF+1).*conj(Xp256(kF+1))/2;
h=M*z;
multiply by transmitted preamble
channel impulse response
3. Channel Frequency Response: H=fft(h, 256);
Simulink Implementation
Trigger when preamble is detected
Y [k ]
h[n ]
Channel
Estimate out
Data in
y [n ]
H [k ]
*
X p [k ]
Example:
Spectrum of
Received Signal
NOT TO
SCALE
As expected, it
does not match in
the Frequency
Guards
Estimated
Frequency
Response of
Channel
Start after processing
preamble
WiMax-2004 Demodulator
WiMax256.mdl
Standard OFDM
Demod (256 carriers)
data
Error Correction
Decoding
Ch.
Channel Tracking
In mobile applications, the channel changes and we need to track it.
IEEE802.16-2005 tracks the channel by embedding pilots within the data.
In the FUSC (Full Use of Sub Carriers) scheme, the pilots subcarriers are chosen
within the non-null subcarriers as
9 k  3m  1
with
m  symbol_ind
ex  mod 3  0 ,1, 2
 0 ,..., 191 for N FFT  2048

 0 ,..., 95 for N FFT  1024
k 
 0 ,..., 47 for N FFT  512
 0 ,..., 11 for N
 128
FFT

subcarrier
0 1 4 7 
OFDM
Symbol
m
k
nulls
DC
(null)
pilots
data
nulls

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