z Average trend : 40 dB / decade z Slow fading : Caused by shadowing. Typically log-normal distribution ( σ = 8 dB ) z Fast fading : Caused by local scatterers near mobile. Typically Rayleigh distribution (σ = 5.57 dB)
8
Comm. Sys. Lab. / AJOU Univ.
Doppler, Delay and Angle Spreads
z Local and remote scattering, and mobile motion spread the signal
� Delay spread� Angle spread� Doppler spread
: 0.5 to 20 µs: 2 to 60±( ~ 360±for indoor or micro-, pico-cells ): 5 to 200 Hz
Comm. Sys. Lab. / AJOU Univ.
Multipath Propagation in Macrocells
z High base station antenna elevation, multipath scatterers arise
from three sources
Ö Local to mobile
: Cause Doppler spread (time selective fading along with mobile motion),
and small delay and angle spreads
Ö Local to base
: No additional Doppler spread, small delay spread, large angle spread
(space selective fading)
Ö Remote dominant
: Independent fading on paths, no additional Doppler spread,
large delay spread (frequency selective fading),
large angle spread (space selective fading)
9
Comm. Sys. Lab. / AJOU Univ.
Multipath Propagation in Microcells
z Base station antenna at a low elevation below the rooftop level Ö Difficult to identify distinct classes of scatterers Ö Usually characterized by high angle spreads and small delay spreads
Comm. Sys. Lab. / AJOU Univ.
Macrocells vs. Microcells - Impulse Response
z Macrocell impulse response - Dominant path exists
z Microcell impulse response - No dominant impulse at the origin - High angle spread and low delay spread
10
Comm. Sys. Lab. / AJOU Univ.
Mobile Vector Channel with Base Station Arrays
zz Channel impulse response
),,2,1(),()()()()(1 1
)()( MmttathL
ll
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Comm. Sys. Lab. / AJOU Univ.
Mobile Vector Channel (cont.)
z Vector channel impulse response
∑=
−=L
lll ttt
1
)()()( τδAh
)cosexp()exp()(
)()()()(
],,)([)(
])(,,)([)(
1
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l
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=
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�
A
h
m : antenna index
: array response of m-th antenna
: angle of arrival of path
: amplitude, phase of path
: signal distribution
: phase constant
: speed of mobile
: angle between scatterer
and the MS
)(θma
nlθ
nlnlg θ,
)(θω
βv
nlϕ
11
Comm. Sys. Lab. / AJOU Univ.
3. Smart Antenna Systems3. Smart Antenna Systems
Comm. Sys. Lab. / AJOU Univ.
Antenna Systems
• Adaptive Array Antennas
• Sectored Antenna • Diversity Antennas
• Switched Beam Antennas
12
Comm. Sys. Lab. / AJOU Univ.
Antenna Diversity
∑U SER
AN TEN NA 1
AN TEN NA 2
AN TEN NA M
OU TPU T
SIGN AL
z Antenna diversity
- Weighting and combining of signals from multiple antenna elements
- Space, Angle, Time, Polarization, etc.
z Diversity gain with multipath
- Require independent fading
Ö Directions-of-arrival
Ö Polarization
Comm. Sys. Lab. / AJOU Univ.
Antenna and Diversity Gain
z Antenna gain : Increased average signal power
- Power gain M with M antennas
z Diversity gain : Decreased required signal power for a given BER
averaged over fading
- Dependent on BER ( M=2 )
Ö 5.2 dB at 10-2 BER
Ö 14.7 dB at 10-4 BER
- Gain increase with M ( BER =10-2 )
Ö 5.2 dB for M=2
Ö 7.6 dB for M=4
Ö 9.5 dB for M=∞ - Dependent on fading correlation
13
Comm. Sys. Lab. / AJOU Univ.
Diversity Types
z Spatial : Horizontal separation
- Correlation depends on angular spread
z Polarization : Vertical and horizontal polarizations
- Low correlation
- 6-10 dB lower horizontal than vertical with vertical transmit and LOS
z Angle : Adjacent narrow beams
- Low correlation typical
Comm. Sys. Lab. / AJOU Univ.
Combining Techniques
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z Selection combining - Select antenna with the highest received signal power - z Maximal ratio combining - Weight and combine signals to maximize signal-to-noise ratio - Optimum technique with noise only - BERM ≈ BERM (M-fold diversity gain)z Optimum combining (Adaptive antennas) - Weight and combine signals to maximize signal-to-interference-plus-noise ratio (SINR) - Utilize correlation of interferences at the antennas - Same as MRC in the case of no interference
MooM
PP =
14
Comm. Sys. Lab. / AJOU Univ.
Combining Performance
z Selective combining
- Outage voltage probability,
)( where
),,(
0
1
si
MosMoM
prob P
PprobP
Γ≤==Γ≤=
γγγ �
z Maximal ratio combining
- Mean signal-to-noise ratio,
oMP
sMΓ
where 0
0
γγMsM =Γ
: Mean signal-to-noise ratio of a path
MM
MMM ee
e
)BER(BER -
)(BER -
BER -00
0
∝=∝
∝−−
−
γγ
γ
Comm. Sys. Lab. / AJOU Univ.
Smart Antenna Systems
z Switched beam systems
- A finite number of fixed, pre-defined patterns
- Detect signal strength
Ö Choose one of several predetermined beams
Ö Switch from one beam to another
z Adaptive array systems
- An infinite number of patterns that are adjusted in real time
- A variety of new signal-processing algorithms
- Provide optimal gain and minimize interfering signals
15
Comm. Sys. Lab. / AJOU Univ.
Switched Beam Systems
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z Major focus within industry todayz Advantages of narrow beams : Improves coverage, reduces interference, and can improve capacity
Comm. Sys. Lab. / AJOU Univ.
Switched Beam Systems (cont.)
z Many narrow beams : Improve coverage, capacity and reduce interference
z Performance depends on a number of factors : Angle- Doppler- Delay spread,
relative angles of arrival of signal and interference, array topology
z Performance gains from array gain, space diversity gain, interference reduction
and trunking efficiency
z Performance losses from cusping loss, mismatch loss, beam selection loss,
path diversity loss
16
Comm. Sys. Lab. / AJOU Univ.
Switched Beam Systems - Rx Performance
z Beam selection in angle spread environments is a major problem and involves many compromises - how do you select strongest beam before identifying channelz Beam qualification using training signals needs framing, STR and carrier recovery
B /F S elec t
S n if fer
G a insA rr ay G a inD iv ers it y G ainIn ter fe re nce R ed uct ion G ain
L o ssesM ism atch L ossC usp ing L os sB eam Selec tion L ossP ath D ive rsi ty L os s
Comm. Sys. Lab. / AJOU Univ.
Switched Beam Systems - Tx Performance
z Again similar to Rx processing, but constraints in angle spread environmentsz EIRP limits mean no coverage gainz Beam selection losses can translate to coverage losses
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17
Comm. Sys. Lab. / AJOU Univ.
System Comparison - Coverage Pattern
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S w itc h ed B ea m
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Comm. Sys. Lab. / AJOU Univ.
4. Adaptive Arrays4. Adaptive Arrays
18
Comm. Sys. Lab. / AJOU Univ.
Adaptive Arrays - System Design Considerations
z Array geometry
z Number of elements
z Beamforming algorithms
z Propagation conditions
z Radiation patterns of elements
z Transmitter/Receiver nonlinearity
Comm. Sys. Lab. / AJOU Univ.
Array Geometry - Uniform Linear Array
Uniform linear array Beam pattern of an eight-element linear array
19
Comm. Sys. Lab. / AJOU Univ.
Array Geometry - Uniform Circular Array
θ
φ
φK RK
rk
r
Uniform Circular array with M elements Three-dimensional beam pattern of an 8-element circular array with R=0.8710
Comm. Sys. Lab. / AJOU Univ.
Number of Elements
z Beamwidth
Ö With high M (No. of elements), higher resolution (narrower beam)
z Performance improvement
Ö With high M, improve the signal quality, capacity and coverage
z Hardware/Software complexity
Ö With high M, higher H/W and S/W complexity
20
Comm. Sys. Lab. / AJOU Univ.
Radiation Patterns
z Isotropic radiation pattern
Ö Simple to analyze and to control
Ö Practically, difficult to produce
z Sectored pattern
Ö Widely used in the current cellular base stations
z Arbitrary radiation pattern
Ö Difficult to control and analyze
Ö All elements may have minor arbitrary factors
Comm. Sys. Lab. / AJOU Univ.
Propagation Conditions
z Macro cells (Rural)
Ö Low angular spread (Easy to estimate DOA)
Ö Large delay spread
Ö Spatial techniques
z Pico cells
Ö High angular spread
Ö Small delay spread
Ö Temporal techniques
z Micro cells
Ö Medium angular spread (Urban, Suburban)
Ö Medium delay spread
Ö Spatial and temporal techniques
21
Comm. Sys. Lab. / AJOU Univ.
Beamforming Techniques
z Beamforming(or Spatial filtering) ? Ö Focussing the energy radiated by an aperture antenna along a specific direction Ö To receive/to transmit preferentially a signal from/to that directionz Examples 1) Parabolic antenna system - Energy aligned with the preferred direction is summed coherently - Sources unaligned may be added incoherently 2) Antenna arrays - Sampled aperture - Subject to various signal processing functions Ö Phase and amplitude weightings Ö Concurrent angular information for signals arriving in several different directionsz Beamforming network - Phasing network Ö Arranged to add coherently the outputs of all the elements for a given direction Ö Must implement another phasing network for a different direction
Comm. Sys. Lab. / AJOU Univ.
Beamforming - Basic Principle
wave f ron t
a r ray ax issensor 1sensor 2
a r ray no rma l
s(t)
dsin
θ
θ
d
z Array response vector ( No. of antennas = M)
=
−−
−
θω
θω
θ
sin)1(
sin
0
0
1
)(
c
dMj
c
dj
e
e
�a
22
Comm. Sys. Lab. / AJOU Univ.
Digital Beamforming
z Advantages
- Greater flexibility
Ö Different types of beams, such as scanned beams, multiple beams,
arbitrarily-shaped beams, or beams with steered nulls
Ö Can be easily integrated with other receiver functions, such as
demodulation, equalization and so on.
- Well suited to adaptive techniques
- Greater accuracy in amplitude and phase control
- Self-calibration capability
Comm. Sys. Lab. / AJOU Univ.
Beamforming Constraints
z Spatial references - Direction-of-arrivals (DOAs) of the target signals Ö Must be estimated prior to beamforming - Spatial signatures - ML method - Subspace-based method
zz Temporal references - Training sequences, pilot signals or color codes - Finite alphabet - Constant modulus - Higher order statistics - Cyclostationarity
23
Comm. Sys. Lab. / AJOU Univ.
Spatial Reference Beamforming (SRB)
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Comm. Sys. Lab. / AJOU Univ.
Temporal Reference Beamforming (TRB)
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24
Comm. Sys. Lab. / AJOU Univ.
SRB vs TRB
z SRB - Low angle spread multipath channel - Work for any modulation schemes - Not require unique user signature signals - Easy to derive downlink weight vectors - Require good calibrationz TRB - High angle spread channel - Optimum combining Ö Can obtain the optimum spatial signature of the specific user - Require unique user signature signals Ö e.g., training sequences or color codes - Difficult to derive downlink weight vectors from uplink weight vectors
Comm. Sys. Lab. / AJOU Univ.
DOA Estimation Algorithms for SRB
z Arbitrary array geometry
- MVDR, MUSIC, WSF, MEM, Min-Norm, ML
z Uniform linear array
- Root-MUSIC, ESPRIT, IQML, Root-WSF
25
Comm. Sys. Lab. / AJOU Univ.
Subspace-Based Method
z Based on the eigenvector decomposition of the covariance matrix
z Use singular value decomposition(SVD)
- Partition into noise subspace eigenvectors and signal subspace eigenvectors
- The covariance matrix can be written as
z The projection operator separates signal subspace from input signal
- Use the signal characteristics of orthogonality to noise
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)( HHnnn
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Comm. Sys. Lab. / AJOU Univ.
Blind Temporal Finite Alphabet (FA) Methods
z In this method we exploit the finite alphabet (FA) property of digital signals to construct the beamformer. The approach uses both the digital modulation and channel coding structure. The adaptive beamformer attempts to fit the underlying FA model to the array data.
z We exploit the temporal structure such as Constant Modulus or Self-Coherence to construct the beamformer. The waveform property is damaged by the presence of interference. The adaptive beamformer attempts to restore signal property at its output and thus automatically reduces interference. Many variants of CM have been studied
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Comm. Sys. Lab. / AJOU Univ.
5. Adaptive Beamforming5. Adaptive Beamforming
27
Comm. Sys. Lab. / AJOU Univ.
Adaptive Beamforming
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z Spatial processing dynamically creates a different sector for each user
z Because it transmits an infinite number of combinations, its narrower focus
creates less interference to neighboring users than a switched-beam approach
Comm. Sys. Lab. / AJOU Univ.
Signal Model for Adaptive Beamforming
z Received signal vector at base station antenna array
z Array covariance matrix
z Undesired signal vector covariance
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)()()( ttt niu +=
28
Comm. Sys. Lab. / AJOU Univ.
Optimum Beamforming Weights
z Maximum SINR beamformer - Output SINR
00
2
0020
20
200
0
)(
]|)(|[E
]|)()(~|[E0
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1 θζ vRw uu−=SINR
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)]()(~)([)]()(~)([ 01
01
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Comm. Sys. Lab. / AJOU Univ.
Optimum Beamforming Weights (cont.)
z MMSE beamformer - Error between the beamformer output and the desired signal
)()(~)( 0ttste H xw−=
- Mean squared error{ } 00~0
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20 2Re]|)(|[E)( wRwrww xxx
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z Beamforming based on training signals
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−
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29
Comm. Sys. Lab. / AJOU Univ.
Adaptive Algorithms
z LMS (Least mean square) algorithm
)()()(ˆ)1(ˆ * nnnn εµxww +=+
)(ˆ)()()(with ntndn H wx−=ε
z DMI (Direct matrix inversion) algorithm
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∑∑==
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1
2
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N
Ni
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)(~ * nndnnnnnn H xrrxxRR +−=+−= γγ
)]()1(ˆ)()[()1(ˆ)(~)(~
)(ˆ *1 nnndnnnnn H rwqwrRw −−+−== −
)()1()(1
)()1()(with
11
11
nnn
nnn
H xRxxR
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−= −−
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γγ
Comm. Sys. Lab. / AJOU Univ.
Digital Beamforming with Multiple Access
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Uplink configuration for FDMA system Downlink configuration for FDMA system
30
Comm. Sys. Lab. / AJOU Univ.
Digital Beamforming with Multiple Access (cont.)
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Uplink configuration for TDMA system Downlink configuration for TDMA system
Comm. Sys. Lab. / AJOU Univ.
Digital Beamforming with Multiple Access (cont.)
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z DBF with CDMA
Uplink configuration for CDMA system Downlink configuration for CDMA system
31
Comm. Sys. Lab. / AJOU Univ.
Digital Beamforming with Multiple Access (cont.)
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(a) Uplink (b) Downlink
Comm. Sys. Lab. / AJOU Univ.
Beamformer-RAKE Receiver Structure
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32
Comm. Sys. Lab. / AJOU Univ.
Downlink Beamforming
z FDD Downlink beamforming techniques
- Direct channel sounding and feedback techniques, Probing techniques
- DOA-based methods
- Subspace mapping methods
- Switched-beam systems
- Spatial signature translation methods
z TDD
- In most, uplink and the downlink channels can be considered reciprocal
- Use the uplink channel information
Comm. Sys. Lab. / AJOU Univ.
6. Performance6. Performance
33
Comm. Sys. Lab. / AJOU Univ.
Range Increase
z M-element adaptive array and a switched beam provide a M-fold increase in antenna gain
- Increase the range by , where is the propagation loss exponent - Reduces the number of base stations required to cover a given area by
γ1Mγ
γ2M
Comm. Sys. Lab. / AJOU Univ.
Capacity and Data Rate Increase
z Capacity - In CDMA systems, switched beam with M beams reduces the number of interferers per beam by a factor of M, and increases the capacity M-fold - In TDMA systems, adaptive array with an M-element array having the potential to permit greater than an M-fold increase
z Data rate (example of IS-136) - 48.6Kb/s in a single 30KHz channel - Using M antennas at the mobile and base station Ö M spatially separate channels are permitting M • 48.6Kb/s in a single 30KHz channel
34
Comm. Sys. Lab. / AJOU Univ.
BER Performance with Fading
z Average BER vs average SINR for optimum combining
A single interferers A pair of interferers
Comm. Sys. Lab. / AJOU Univ.
Co-Channel Interference Reduction
z Outage probability and relative spectral efficiency
Outage prob. with six cochannel cells Relative spectral efficiency
35
Comm. Sys. Lab. / AJOU Univ.
Improvement in CDMA Systems
z Outage probability for uplink
Comm. Sys. Lab. / AJOU Univ.
7. Research Trends7. Research Trends
36
Comm. Sys. Lab. / AJOU Univ.
Space-Time Processing
z Space-time optimum receiver
z Space-time optimum multi-user receiver
z Space-time joint equalization multi-user transmitter-receiver system
z Space-time coding
Comm. Sys. Lab. / AJOU Univ.
Space-Time Optimum Receiver
z VD(Viterbi Detector) connected to an ST-WMF(Spatially and Temporally Whitened
Matched Filter) which is constructed by a TDL(Tapped Delay Line) antenna array
37
Comm. Sys. Lab. / AJOU Univ.
Space-Time Optimum Receiver (cont.)
BER of optimum receiver (single user) BER of optimum CDMA multi-user receiver (multi-user)
Comm. Sys. Lab. / AJOU Univ.
Space-Time Joint Equalizer in the Tx and Rx
z ST joint transceiver system which consists of an ST transmission filter(ST-TF) based on a transmitting TDL array, an ST-WMF based on a receiving TDL array, and a VD for MLSE
a space-time joint transmitter-receiver system
ST-TFW t(t,Φ)
Mu ltipathchannel
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38
Comm. Sys. Lab. / AJOU Univ.
Space-Time Joint Equalizer in the Tx and Rx (cont.)
BER according to the number of users Transmission rate according to the number of users
Comm. Sys. Lab. / AJOU Univ.
Space-Time Coding
z Transmit diversity : Significant improvements in data rates or BER performance
z Transmitter functions - N-element antenna arrays - Space-time encoding is splitting into N streams using N-element antenna arrays - Periodic orthogonal pilot sequences to obtain channel estimates
z Receiver functions - M-element antenna arrays - Using orthogonal pilot sequences to estimate fading channel - Using interpolation filter to obtain accurate channel state information - Block symbol-to-symbol deinterleaver Æ vector ML sequence decoder Æ RS decoder
39
Comm. Sys. Lab. / AJOU Univ.
Space-Time Coding (cont.)
Im fo rm ationSo ur ce
Space-T im e E ncoder
B lock E ncoder(R eed Solo m on )
C oncatenated S pace-T im e E n co der
In ter leav ingBurst
Build ing
P ulseShaper
Burst 2
In ter leav ingBurst
Build ing
P ulseShaper
Burst 1
R eed So lom o nD ecod er
D e in te r leav ing
C h ann e l E stim a t io nand
In te rpo la tionM atchedF il te r
D e in te r leav ingC h ann e l E stim a t io n
andIn te rpo la tion
M atchedF il te r
Space-T im eV ec tor V i te r b i
D ecod er
C onca ten ated Space-T im e D ecod er
< Base station transmitter with STCM and 2 transmit antennas >
< Mobile receiver with STCM and 2 receiver antennas >
Comm. Sys. Lab. / AJOU Univ.
Smart Antenna Systems for IMT2000
z Difference Between IS-95 & cdma2000
z 2-D Space-Frequency Rake in UTRA FDD
- SIEMENS scheme
z Adaptive Antenna Array Combined with Rake Receiver
- NTT DoCoMo scheme
z Transmit Diversity for WCDMA
- NOKIA scheme
40
Comm. Sys. Lab. / AJOU Univ.
Difference Between IS-95 & cdma2000
z Issues affecting the performance of adaptive antenna arrays:
� IS-95 - Uniform (in rate and space) voice user population
- No pilot channel for the uplink â Blind training required
- Interference rejection capabilities of adaptive antenna arrays are
diffused due to uniform spatial distribution of voice users
� cdma2000 - Multi-rate traffic processing gain range
Ö PG = 3.56 ( high speed data ) ~ 768 ( voice )
- Pilot channel available in the uplink
- High data rate users introduce non-uniformity in the spatial
distribution of interfering sources
Comm. Sys. Lab. / AJOU Univ.
UMTS Terrestrial Radio Access (UTRA)
z UTRA FDD uplink � Uplink data and control channels I/Q-multiplexed � 2-D space-frequency rake smart antenna system
z UTRA FDD downlink � Downlink data and control channels time multiplexed � Connection-dedicated pilot bits enable downlink beamforming � Support the use of space-selective beamforming
z UTRA TDD � Efficient support of asymmetrical services � Joint space-time processing smart antenna system on the uplink � Connection-dedicated midamble sequences are also transmitted � Spatial beamforming on the downlink
- SIEMENS scheme -
41
Comm. Sys. Lab. / AJOU Univ.
2-D Space-Frequency Rake in UTRA FDD
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- SIEMENS scheme -
Comm. Sys. Lab. / AJOU Univ.
Raw BER Performance in UTRA FDD
No. of rake fingers / antenna (space-time rake) = 3
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- SIEMENS scheme -
42
Comm. Sys. Lab. / AJOU Univ.
Adaptive Antenna Array Combined with Rake Receiver
z Frame structure
- Reverse link : time-multiplexed pilot
- Forward link : I/Q-multiplexed
z Algorithm & Receiver Structure - Antenna beamforming criteria
Ö Decision directed MMSE criteria using data symbols as well as pilot
Ö Implemented by the normalized least mean square (N-LMS)
