Transcript Overview of the Third Generation Mobile Communications In

Overview of the Third
Generation Mobile
Communications
Overview of the Third
Generation Mobile
Communications
Contents
• Progress of the Mobile Communication
• Standards: WCDMA, CDMA-2000 phase
II, TD-SCDMA and TD-CDMA
• Introduction to the Mobile Communication:
Basic Concepts, Key Technologies
• Wireless Channel Estimation
Progress of the Mobile
Communication
• The first generation cellular mobile
communications: (1980 )
– Technology: FDMA and Analog Technology.
– Systems: AMPS(USA), NMT-900(Sweden),
HCMTS(Japan)
– Shortages: Only lower Frequency available,
same Frequency band Inference, poor Security.
– Advantages:convenience for communication
Progress of the Mobile
Communication
• The second generation cellular mobile
communications: (1992)
– Technology: TDMA, TDMA hybrid FDMA
– Systems:
DAMPS(USA, IS-54), GSM
– Advantages: Higher Frequency available, good
Security, higher Capacity, good speech QoS
Progress of the Mobile
Communication
– Technology: CDMA(Qualcomm)
– Systems:
CDMA(IS-95)
– Advantages: Higher Frequency available, good
Security, Soft Capacity, Higher Capacity, Speech
Activity Technology, Diversity Technology.
– Shortages:Focusing on Speech Service, lower rate
Service, the Capacity does still not satisfy the evergrowing demand, no Multimedia Service and no higher
rate Service
Progress of the Mobile
Communication
• The third generation 3G: (1996-2005)
– High mobile velocity(300-500km/hour); less than
100km/hour(GSM)
– To carry out the global wandering tour; District and
Country(GSM)
– Support Multimedia Service, especially Internet
Service, 144kb/s(Outdoor and higher velocity ),
384kb/s(from Outdoor to indoor, lower velocity),
2Mb/s(indoor); Speech of QoS and other services 4100-200kbs/s(GSM, lower velocity)
Progress of the Mobile
Communication
– Convenience for transition and evolvement or
innovation, compatibility with networks
– Highest spectrum availability, higher QoS, Speech
Recognition Technology, lower Cost, higher Security
– Advantage technologies such as Adversity transmitting
and receiving, Multipath Combining, Turbo Code,
Channel Estimation, SIR measurement and TPC,
Space-time technology, Multiuser Detection and
Interference Cancellation, Beamforming and Smart
Antennas, Soft handoff
– The 3G’s aim is to implement truly anybody at any
place to communicate with anyone at any time
Standards: WCDMA, CDMA2000, TD-SCDMA,TD-CDMA
• FPLMTS in 1986. IMT-2000 in 1996
• Japan: WCDMA to be central technology
in 1997.
• Europe:WCDMA (FDD model) and TDCDMA(TDD).
• America: CDMA-2000 Phase II
• China: TD-SCDMA(1998)
• The Standards of 3G
WCDMA
•
Ompany:
NTT, NEC, Nokia, Ericsson;
Smallest bandwidth:
5Mhz
Technology: DS-DCDMA
Working type: FDD/TDD
Chip rate:
4.096Mcps
Length of frame: 10/20/30ms
Synchronous : Synchronous and asynchronous
Modulation:
QPSK/BPSK
Channel structure of the inverse link:
Pilot/TPC/Dedicated
Channel code: Convolutional coding+Turbo coding
Enhanced technique:
Multiuser detection(O)/Smart Antennas(O)
Handoff:
Soft handoff(complicated)
TPC: Fast TPC(1600)
Forward and inverse Detection:
Pilot assistant
Speech code: Variant rate
CDMA-2000 Phase II
•
Company:
Qualcomm, Motorola, Lucent, Nortel
Smallest bandwidth:
3*1.25Mhz
Technology: DS-CDMA and multicarrier
Working type: FDD
Chip rate:
1.2288/3.686Mcps
Length of frame: 10/20/30ms
Synchronous : Synchronous and asynchronous
Modulation:
QPSK/BPSK
Channel structure of the inverse link:
Pilot/Control
Channel code: Convolutional coding+Turbo coding
Enhanced technique:
Multiuser detection(O)/Smart Antennas(O)
Handoff:
Soft handoff(IS-95)
TPC: TPC(1800)
Forward and inverse Detection:
Pilot assistant
Speech code: Variant rate
TD-SCDMA, TD-CDMA
•
Company:
DATANG, HUAWEI, ZHONGXIN,( Nortel)
Smallest bandwidth:
1.25Mhz
Technology: TDMA and multicarrier
Working type: TDD
Chip rate:
*Mcps
Length of frame: 10/20/30ms
Synchronous : Synchronous and synchronous
Modulation:
QPSK/BPSK
Channel structure of the inverse link:
Dedicated/Pilot/Dedicated
Channel code: Convolutional coding+Turbo coding(O)
Key technology: Joint detection, Smart Antennas
Handoff:
Soft handoff(?)
TPC:
*
Forward and inverse Detection:
Pilot assistant
Speech code: Variant rate
Key Technologies
• 1, Auto Frequency Control(AFC), Acquisition
or Cell Searching, Chip Tracking, Auto Gain
Control(AGC), Multipath Searching, Root
Cosine Filters Design, Transmit Diversity,
Mobile Location, Speech coding. Linear Power
Amplifier(LPA), Adaptive Echo Cancellation.
• 2, Channel Model Simulation
• 3, Channel Estimation
• 4, Channel Code, especially Turbo Code
Key Technologies
• 5, Diversity receiver and RAKE combiner
6, Multiuser Detection and Interference
Cancellation
7, Joint Detection
8, Smart antennas
9, SIR measurement and TPC
10, Soft handoffs in CDMA Mobile systems
*11, Multimedia Communications in 3G
*12, Speech recognition technology in 3G
*13, Security algorithms
*14, Route technology and Packet access
Basic Concepts
• Gaussian channel and multiuser receiver
– A baseband digital direct sequence(DS)CDMA network of K users. The received
signal can be modeled as
r (t )  S (t )  n(t )
K
S (t )   Ak
k 1
M
b
i  M
k
(i ) sk (t  iT   k )
• where 2M+1 is the number of data symbols per user per frame, T is the
symbol interval, {bk (i)}is a collection of independent equiprobable random
variables,and the user signaling waveforms are of the form
N 1
sk (t )    kj (t  jTc )
•
j 0
( 0k , 1k ,..., Nk 1 ) is a signature sequence of  1 ’s assigned the kth user; and  is a
normorlized chip waveform of duration , where NT
c
T
.
• Rayleigh channel and a single user receiver
In the case of the time-multiplexed pilot channel, the QPSK symbol sequence
is mapped over a sequence of slots, each containing N
data symbols
preceded by N pilot symbols placed at the beginning of each slot. The
resultant symbol sequence is spread over much wider bandwidth by a
spreading sequence. The slot length T  (N  N )T , where T is the QPSK symbol
duration. In the case of the parallel pilot channel, on the other hand, data and
pilot channel are spread by orthogonal spreading sequence. Assuming that the
multiple channel has
resolvable, frequency-nonselective path, the spread
signal received over a multipath channel can be represented as
d
p
slot
L( 1)
L 1
L 1
l 0
l 0
p
d
r (t )   rl (t )  2S  l (t )s(t   l )   (t )
 l (t )
and are the complex-valued channel gain and time delay of the l-th
path(l=0,1,…,L-1), respectively, and s(t) is the transmitted spread signal
waveform. We assume
l
 L1

E |  l (t ) |2   1
 l 1

g tm (t )d tm (t )

s(t )  
 g pd (t )d p (t )  g pp (t ) Pp (t )
for TPMCS
for
PPCS
• Diversity receiver and RAKE combiner
•
•
A diversity scheme is a method that is used to develop information from
several signals transmitted over independently fading paths. The objective
is to combine the multiple signals and reduce the effect of excessively deep
fades. Diversity schemes can minimize the effects of fading, since deep
fades seldom occur simultaneosly during the same time intervals on two
or more paths.
Since the chance of having two deep fades from two uncorrelated signals
at any instant is rare, the effect of the fades can be reduced by combining
them. There are two general types of diversity schemes. One is called the
“macroscopic diversity scheme”. The macroscopic diversity scheme is
used for combining two or more long-term lognormal signals, which are
obtained via independently fading paths received from two or more
different antennas at different base-station sites. The microscopic
diversity schemes is used for combining two or more short-term Rayleigh
signals, which are obtained via independently fading paths received from
two or more different antennas but only one receiving cosite.
•
The macroscopic diversity scheme—applied on different-Sited Antennas.
•
The microscopic diversity schemes. At the base station and at the mobile
unit, there are space diversity, Polarization diversity, Angle diversity,
frequency diversity, time diversity.
• Rayleigh channel model(ITU-M R.1225)
A central factor of mobile radio propagation environments is
multipath propagation causing fading and channel time
dispersion. The fading characteristics vary with propagation
environment and its impact on the communication quality is
highly dependent on the speed of the mobile relative to the serving
base station. The purpose of the test environment is to challenge
the RTTs.
The key parameters to describe each propagation model would
include:
--time delay-spread, its structure, and probability distribution of
time delay spread.;
--geometrical path loss rule(e.g. and excess path loss;
--shadow fading;
--multipath fading characteristics(Doppler spectrum) for the
envelop of channels;
--operating radio frequency
•
1, Long-term Fading
Long-term fading components, which contribute only on to propagation-path
loss must be removed. We must estimate the local mean. in general, the local
mean can be obtained by measurement.
•
2, Short-term Fading
N
E z   ai exp[ jVt cos(i   )]
i 1
•
3, Frequency-flat fading and Frequency-selective fading
Frequency-flat fading channel is composed of long-term fading and short-term
fading. Frequency-selective fading channel is composed multipath channels
with different time delay spread, which each channel is Frequency-flat fading
channel.
• Channel Model Simulation
•
There are mainly two methods of channel model simulation. The first method
is filters design. The Classical Doppler spectrum is


S( f )  


•
A
(1  f / f m )
0
| f | f m
2
else
The second method is harmonic decomposition technique. The simplest
nondegenerate class of process which exhibits uncorrelated dispersiveness in
time delay and Doppler shifts is known as the Wide Sense Stationary
Uncorrelated Scattering(WSSUS) g (t )
T T
Now, we use a series of the form x (t )  lim  c e  , t [ 2 , 2 ]
can be find, approximating g (t ) arbitrarily close, in the mean square sense,
provided we take f small enough. The c are uncorrelated complex random
variables with zero mean and variance
n
N
n
N 
j 2 f 0t
k  N
k
n
0
E{| ck |2 } 
k
1
2

( k 1 / 2 ) w0
( k 1 / 2 ) w0
S n ( f )df 
w0
S n (kw 0 )
2
Wireless Channel Estimation
•
•
•
•
•
•
•
•
•
Wienner filter
Gaussian Interpolation
WMSA(Weighted multi-slot averaging)
Polynomial Interpolation
Adaptive Lattice Weighted Algorithm
Kalmann Filter based on AR model
Joint Data Message to Estimate Channel
Channel Estimation based on Fuzzy systems
Blind Channel Estimation
Wienner filter
Fading Channel output: r (t )  c(t )s(t )  n(t ) , Complex channel gain c(t) is timevariable, which auto correlation is Rc ( )   2 exp(j 2f 0t ) J 0 (2f D ) . In the
receiver, the received signal pass through a bank of matched filters. The
matched filters output is
r (k )  u(k )b(k )  n(k )
In generality, we assume b(0) to be a pilot symbol. Now, we want to detect
symbols b(k ),[M / 2]  k  [M / 2] , Then, the linear estimator is
v( k ) 
[ K / 2]
h
*
(i, k )r (iM )
i  [ K / 2 ]
According to Wienner filter, we can obtain the optimal h(k).
R.h(k )  w(k )
WMSA
• simple Coherent RAKE receiver
1 ( m1)T  nTslot  l
rl (m, n)  
rl (t ) g (t   l )dt
mT

nT


slot
l
T
 2S l (m, n) exp jtm (m, n)   l (m, n)
for WCDMA
,
 2S l (m, n) exp j p (m, n)   l (m, n), data channel

2S l (m, n)   l (m, n),
pilot channel

for CDMA2000
•
~
l (m, n)
The channel estimation filter is to estimate the value of  (m, n) using the
pilot channel and its estimate is denoted by ~l (m, n) L despread and
resolved signal components are multiplied by the complex conjugates of
s before combined(maximal-ratio combing(MRC)). The RAKE combiner
output at the m-th symbol position of n-th slot is therefore, represented as
l
L 1
~
d (m, n)   rl (m, n) l * (m, n)
l 0
•
Finally, the RAKE combiner output is de-interleaved and soft-decision Viterbi
decoded to recover the transmitted data.
We assume the channel estimator ˆl (m, n) to be which denotes the channel
estimator at the m-th symbol position of n-th slot associated with the l-th path .
In the case of fading, we can extend the observation interval to several slots
and coherently add several consecutive instantaneous channel estimatesˆl (m, n)to
further increasing SNR Therefore, the instantaneous channel estimates need to
be smoothed by a smoothing filter. The smoothing filter is expressed as
ˆl (m, n) 
•
K

j   K 1
m, j
ˆl (n  j )
where ˆl (n) is the pilot channel estimator at the n-th slot.
of the filter
 m, j
is the coefficients
• As m  N D / 2
m

 m, 1  0.8  0.2  N / 2
D



1
.
0
m,0

   0.8  0.2  m
 m,1
ND / 2

m
  m, 2  0.6 

ND / 2
• AS m  N D / 2
m  ND / 2

 m, 1  0.6  0.6  N / 2
D

m

N
D /2
   1.0  0.2 
m,0
ND / 2


 m,1  1.0

m  ND / 2
  m, 2  0.6  0.2 

ND / 2
• The RAKE combiner (Max-ratio Combing(MRC) output at the m-th
symbol position of n-th slot is therefore, represented as
L 1
~
d (m, n)   rl (m, n) l (m, n)
l 0
Kalmann Filter based on AR model
•
the state process and observation process of Kalman filter.
x(n  1)  F (n  1, n) x(n)  v1 (n)
•
y(n)  C (n) x(n)  v2 (n)
The traditional transition matrix F (n  1, n)
0
1

F (n  1, n)  0

...
0
•
0 0 0 ... 0 
0 0 0 ... 0 
1 0 0 ... 0 

... ... ... ... ... 
0 0 ... 1 0 
The traditional Kalman filter can only be used for the estimate of slow fading
channel, which channel gain remains almost same in one slot. The kernel of
this paper demonstrates how to get this transfer probability matrix. We get this
matrix through two methods. AR model is used in the state process of Kalman
question. To get AR model's coefficients, we apply two methods, one of which
is adaptive LMS algorithm, and the other of which is Durbin retrieve method.