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Overview of the Third Generation Mobile Communications

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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

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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

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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

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

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

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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 3Gs aim is to implement truly anybody at any place to communicate with anyone at any time

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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

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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

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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

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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

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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

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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

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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

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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 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

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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 schemeapplied 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.

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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

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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.

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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

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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

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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).

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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,

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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

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

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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.

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