Overview of 3rd Generation Mobile Communications

Overview of the Third Generation Mobile Communications

Xiaobo Zhou

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


• 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


– 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 ever-growing demand, no Multimedia Service and no higher rate Service


• 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 4-100-200kbs/s(GSM, lower velocity)


– 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, CDMA-2000, TD-SCDMA,TD-CDMA• FPLMTS in 1986. IMT-2000 in 1996

• Japan: WCDMA to be central technology in 1997.

• Europe:WCDMA (FDD model) and TD-CDMA(TDD).

• America: CDMA-2000 Phase II

• China: TD-SCDMA(1998)

• The Standards of 3G

WCDMA

• Ompany: NTT, NEC, Nokia, Ericsson;Smallest bandwidth: 5MhzTechnology: DS-DCDMAWorking type: FDD/TDDChip rate:4.096McpsLength of frame: 10/20/30msSynchronous : Synchronous and asynchronousModulation: QPSK/BPSKChannel structure of the inverse link: Pilot/TPC/DedicatedChannel code: Convolutional coding+Turbo codingEnhanced technique: Multiuser detection(O)/Smart Antennas(O)Handoff: Soft handoff(complicated)TPC: Fast TPC(1600)Forward and inverse Detection: Pilot assistantSpeech code: Variant rate

CDMA-2000 Phase II

• Company: Qualcomm, Motorola, Lucent, NortelSmallest bandwidth: 3*1.25MhzTechnology: DS-CDMA and multicarrierWorking type: FDDChip rate:1.2288/3.686McpsLength of frame: 10/20/30msSynchronous : Synchronous and asynchronousModulation: QPSK/BPSKChannel structure of the inverse link: Pilot/ControlChannel code: Convolutional coding+Turbo codingEnhanced technique: Multiuser detection(O)/Smart Antennas(O)Handoff: Soft handoff(IS-95)TPC: TPC(1800)Forward and inverse Detection: Pilot assistantSpeech code: Variant rate

TD-SCDMA, TD-CDMA

• Company: DATANG, HUAWEI, ZHONGXIN,( Nortel)Smallest bandwidth: 1.25MhzTechnology: TDMA and multicarrierWorking type: TDDChip rate:*McpsLength of frame: 10/20/30msSynchronous : Synchronous and synchronousModulation: QPSK/BPSKChannel structure of the inverse link: Dedicated/Pilot/Dedicated Channel code: Convolutional coding+Turbo coding(O)Key technology: Joint detection, Smart AntennasHandoff: Soft handoff(?)TPC: *Forward and inverse Detection: Pilot assistantSpeech 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 Cancellation7, Joint Detection8, Smart antennas9, 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

• Gaussian channel and multiuser receiver– A baseband digital direct sequence(DS)CDMA network of K users. The received

signal can be modeled as

• where 2M+1 is the number of data symbols per user per frame, T is the symbol interval, is a collection of independent equiprobable random variables,and the user signaling waveforms are of the form

• is a signature sequence of ’s assigned the kth user; and is a

normorlized chip waveform of duration , where .

Basic Concepts

)()()( tntStr

M

Mikkk

K

kk iTtsibAtS )()()(

1

)}({ ibk

1

0

)()(N

jc

kjk jTtts

),...,,( 110kN

kk 1

TNTc

• Rayleigh channel and a single user receiverIn the case of the time-multiplexed pilot channel, the QPSK symbol sequence is mapped over a sequence of slots, each containing data symbols preceded by 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 , 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

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

dN

pN

TNNT dpslot )(

)1(L

1

0

1

0

)()()(2)()(L

lll

L

ll ttstStrtr

)(tl l

1|)(|1

1

2

L

ll tE

PPCSfortPtgtdtg

TPMCSfortdtgts

pppppd

tmtm

)()()()(

)()()(

• 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

• 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.

N

iiiz VtjaE

1

)]cos(exp[

• Channel Model Simulation• There are mainly two methods of channel model simulation. The first method

is filters design. The Classical Doppler spectrum is

• 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)

Now, we use a series of the form

can be find, approximating arbitrarily close, in the mean square sense, provided we take small enough. The are uncorrelated complex random variables with zero mean and variance

else

ffff

A

fS m

m

0

||)/1()( 2

)(tgn

]2

,2

[,lim)( 02 TTtectx

N

Nk

tfjkNn

)(tgn

0f kc

0

0

)2/1(

)2/1( 002 )(

2)(

2

1}|{|

wk

wk nnk kwSw

dffScE

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: , Complex channel gain c(t) is time-variable, which auto correlation is . In the receiver, the received signal pass through a bank of matched filters. The matched filters output is

In generality, we assume b(0) to be a pilot symbol. Now, we want to detect symbols , Then, the linear estimator is

According to Wienner filter, we can obtain the optimal h(k).

)()()()( tntstctr )2()2exp()( 00

2 Dc fJtfjR

)()()()( knkbkukr

]2/[]2/[),( MkMkb

]2/[

]2/[

* )(),()(K

Ki

iMrkihkv

)()(. kwkhR

WMSA• simple Coherent RAKE receiver

• The channel estimation filter is to estimate the value of using the pilot channel and its estimate is denoted by 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

2000

),,(),(2

),,(),(exp),(2

),(),(exp),(2

)()(1

),()1(

CDMAfor

channelpilotnmnmS

channeldatanmnmjnmS

WCDMAfor

nmnmjnmS

dttgtrT

nmr

ll

lpl

ltml

nTTm

nTmT lll

lslot

lslot

),( nml

,

),(~

nml

),(~

nml

Finally, the RAKE combiner output is de-interleaved and soft-decision Viterbi decoded to recover the transmitted data.

• We assume the channel estimator 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 to further increasing SNR Therefore, the instantaneous channel estimates need to be smoothed by a smoothing filter. The smoothing filter is expressed as

• where is the pilot channel estimator at the n-th slot. is the coefficients of the filter

1

0

* ),(~

),(),(L

lll nmnmrnmd

),(ˆ nml

),(ˆ nml

K

Kjljml jnnm

1, )(ˆ),(ˆ

)(ˆ nl jm,

• As

• AS

• The RAKE combiner (Max-ratio Combing(MRC) output at the m-th symbol position of n-th slot is therefore, represented as

2/6.0

2/2.08.0

0.12/

2.08.0

2,

1,

0,

1,

Dm

Dm

m

Dm

N

mN

m

N

m

2/DNm

2/DNm

2/

2/2.06.0

0.12/

2/2.00.1

2/

2/6.06.0

2,

1,

0,

1,

D

Dm

m

D

Dm

D

Dm

N

Nm

N

NmN

Nm

1

0

),(~

),(),(L

lll nmnmrnmd

Kalmann Filter based on AR model

• the state process and observation process of Kalman filter.

• The traditional transition matrix

• 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.

)()()()(

)()(),1()1(

2

1

nvnxnCny

nvnxnnFnx

),1( nnF

01...000

..................

0...0010

0...0001

0...0000

),1( nnF