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WHITE PAPER
TPTDSCDMAWP
Re v. 0, 9/ 2004
Chengke Sheng
Ed Martinez
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 2
Table of Contents
1. INTRODUCTION.............................................................................................................. 5
2. TYPES OF CHANNEL IMPULSE RESPONSE ...............................................................12
2.1. NON-DIRECTIONAL CHANNEL IMPULSE RESPONSE. ...........................................................12
2.2. DIRECTIONAL CHANNEL IMPULSE RESPONSE ....................................................................12
3. ESTIMATION OF NON-DIRECTIONAL CHANNEL IMPULSE RESPONSE....................14
4. ESTIMATION OF DIRECTIONAL CHANNEL IMPULSE RESPONSE.............................17
5. ESTIMATION OF TRANSMITTED DATA .......................................................................18
6. SUMMARY .....................................................................................................................21
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 3
Table of Figures
FIGURE 2-1 ANTENNA ARRAY MODEL .............................................................................................13
FIGURE 5-1 STRUCTURE OF THE SPREADING SIGNATURE CODE MATRIX .............................................18
FIGURE 5-2 STRUCTURE OF VECTOR CD........................................................................................19
FIGURE 5-3 THE STRUCTURE OF MATRIX HDA
(K,KD).............................................................................19
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 4
Terms and Acronyms
Term Definition
CDMA Code Division Multiple Access
JD Joint Detection
TD-SCDMA Time Division Synchronous CDMA
UMTS Universal Mobile Telecommunications System
Mcps Mega Chip Per Second
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 5
1. Introduction
1.1. Scope and Audience
This paper presents details of the spatial-temporal processing of a received TD-
SCDMA signal and its channel impulse response.
This document is targeted at systems engineers who are designing TD-SCDMA
systems who are interested in deploying the Motorola MRC6011 in their designs.
It is also targeted to applications engineers and marketing professions who want
to learn more about the broad range of applications of the Motorola RCF
technology.
1.2. Executive Summary
CDMA based systems suffer from Multiple Access Interference (MAI) and it
affects all users equally. FDD based systems attempt to deal with the problem by
using detection schemes such as the rake receiver, however these schemes are
sub-optimal because they only consider one user’s signal information and do not
take into account the interference from all other users in the system.
Joint Detection algorithms on the other hand are designed to process all users in
parallel by including the interference information from the other users. In general
Joint Detection schemes are complex and computationally intensive (complexity
grows exponentially as the number of users increases) because most of the
operations are matrix and vector based operations, as the number of the users
increase, the sizes of the matrices and vectors increases and therefore the
computation power that is required to separate the users.
TD-SCDMA however, solves this problem by limiting the number of users in a
given time slot to 16, this creates a very manageable number of users that need
to be processed in parallel, furthermore these users are also synchronized.
1.3. Background
In the year 1998 the Chinese Wireless Telecommunications Standards (CWTS,
http://www.cwts.org) put forth a proposal to the International Communications
Union (ITU) based on TDD and Synchronous CDMA technology (TD-SCDMA) for
TDD. This proposal was accepted and approved by the ITU and became part of
3GPP in March of 2001.
TD-SCDMA was incorporated as part of the TDD mode of operation in addition to
the existing TDD-CDMA mode of operation. To accommodate both modes,
3GPP now includes a “low chip rate” mode of 1.28 Mcps that corresponds to the
TD-SCDMA specifications. Because of this TD-SCDMA is sometimes referred to
as the low-chip rate mode of UTRA TDD.
Table 1-1 shows where TD-SCDMA fits in relationship to other 3GPP standards
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 6
3GPP
Name Access Mode Chip Rate
WCDMA FDD 3.84 Mcps
TDD-CDMA TDD 3.84 Mcps
TD-SCDMA TDD 1.28 Mcps
Table 1-1 TD-SCDMA in relationship to other 3G standards
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 7
2. Signal Model
2.1. TDD/TDMA
Internet based applications, media (audio and video) enabled applications and
file transfers have very different bandwidth requirements for uplink and downlink
traffic. TD-SCDMA does not dictate a fixed utilization of the frequency band;
rather uplink and downlink resources are assigned according to traffic needs.
Symmetric
Traffic
Asymmetric
Traffic
UL
UL DL
DL
Figure 2-1 Symmetric and Asymmetric traffic support in TD-SCDMA
The variable allocation of the time slots for uplink or downlink traffic is what
allows TD-SCDMA to efficiently support asymmetric traffic requirements and a
variety of users. Figure 2-1 illustrates this principle where for symmetric traffic,
the time slots are equally split and for asymmetric traffic the DL can use more
time slots.
2.2. TD-SCDMA Frame Hierarchy
TD-SCDMA uses both unique codes and time signatures to separate the users in
a given cell. The standard defines a very specific frame structure as shown in
Figure 2-2. There are three different layers: the radio frame, the sub-frame and
the individual time slots. Depending on the resource allocation, the configuration
of the radio frames becomes different. The radio frame is 10ms; the sub-frame is
5 ms in length and is divided into 7 slots. The standard also specifies various
ratios for the number of slots between these two groups in order to meet specific
traffic requirements. All physical channels require a guard symbol in every time
slot.
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 8
Time Slot
(
0.675 ms
)
Time Slot (0.675 ms)
Radio Frame (10 ms)
TS0 TS1 TS2
TS3
TS4 TS5 TS6
Data Data Midamble G
Frame #i Frame i+1
Subframe (5 ms)
Subframe #1 Subframe 2
Figure 2-2 TD-SCDMA Frame Structure
2.3. TD-SCDMA Slot Structure
A TD-SCDMA time slot has been designed to fit into exactly one burst. The time
slot (Figure 2-3) consists of four parts, a midamble with 144 chips duration, and
two identical data fields with 352 chips duration at each side of the midamble and
followed by a 16 chips guard period. The midamble is used by the receiver to
carry out channel estimation tasks.
Da ta symb ol s
352chips
Midamble
144 chips
Da ta symb ol s
352 chips
GP
16
CP
675 µs
Figure 2-3 The TD-SCDMA Slot Structure
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 9
3. System Model
3.1. Channel Model
In a TD-SCDMA system, we have K users who access the channel
simultaneously. On the same frequency and in the same time slot. Figure 3-1
shows a general model of a TD-SCDMA System.
C(1
)
C(k
)
C(K
h
(1)
h
(k)
h
(K)
n
Data
Esti
-
mation
e
)
(
K
b
)
(
k
b
)
1
(
b
C(1
)
C(k
)
C(K
h
(1)
h
(k)
h
(K)
n
Data
Esti
-
mation
)
1
(
ˆ
d
)
(
ˆk
d
)
(
ˆ
K
d
)
1
(
d
)
(
k
d
)
(
K
d
e
)
(
K
b
)
(
k
b
)
1
(
b
Figure 3-1 Discrete base band model of a TD-SCDMA system.
In the system of Figure 3-1 we assume that there are Ka antennas for the
receiver .
The kth user transmits a data symbol sequence block with N symbols:
()
T
k
N
kk
kddd )()(
2
)(
1
)( ,
=d k = 1,2,…..,K (1)
[]
T
k
NNN
kk
kddddddddd )()2()1()(
2
)2(
2
)1(
2
)(
1
)2(
1
)1(
1
)( ,,,,,,,,,
=d (2)
Where N is the number of symbols in each data block.
(
)
T
k
Q
kk
kdcc )()(
2
)(
1
)(
=c k = 1, 2 … K (3)
)(k
c is the kth user signature, N is the number of symbols in each data block and
Q is the spreading factor. All users are assumed to be at the same spreading
factor.
Each of the K channels in the system is characterized by its impulse response
[]
T
k
W
kk
khhh )()(
2
)(
1
)(
=h k = 1,2 … K (4)
Where W is the number of taps in the channel.
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 10
Similarly, we have the noise vector for antenna ka
[
]
T
ka
WNQ
kaka
ka nnn )(
1
)(
2
)(
1
)(
−+
=
n (5)
and
[]
T
Ka)()2()1( nnnN
= n = vec [N] (6)
The transmission of the block on N symbols can be modeled by a system of
linear equations that relates the spreading codes, the channel’s input response
and the impact of noise in the signal.
3.2. Received Signal Model
The received sequence received at chip rate from the ka
th antenna is:
e(ka) = (e1
(ka) , e2
(ka), . . . , eNQ+W-1
(ka))T (7)
where Q again is the spreading factor of the data symbol and W is the number
of taps in channel.
[]
T
Ka)()2()1( ., eeeE
= e = vec[E] (8)
From Figure 3-1 we can see that
()
),(
),(
1
),(
2
),(
1
),( *)(,, kak
T
kak
WQ
kakkak
kak kbbb hcb == −+
(9)
Is the convolution of the channel input response with the corresponding spreading code.
(),( kak
his the channel impulse response between the user k and antenna ka, c(k) is the
spreading code of the user k.)
Then the we can see that the signal arriving at the receiver can be described by
a linear system of equations that relate the user’s signal and the receiver input:
NdIAE +⊗= )( )( Ka (10)
Where,
8
is the Kronecker product .
Or
nAde +=
(11)
The matrix A is called channel matrix and is defined as
[]
T
Ka)()2()1( AAAA
= (12)
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 11
K
K
NQ+W
b
(1
,
k
aa
))
b(2,ka)
b
(K
,
k
a
)
Q
+W
b
(k
a
)
=
A
(ka) =
b
b
(k
a
)
b
(k
a
)
Figure 3-2 The Channel Matrix A
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 12
4. Types of Channel Impulse Response
When dealing with spatial-temporal signal processing in the TD-SCDMA, we need to identify two
types of channel impulse responses – non-directional channel impulse response and directional
channel impulse response.
4.1. Non-Directional Channel Impulse Response.
Let’s first discuss the non-directional channel impulse response. The impulse
response is defined between each individual user and its antenna. A non-
directional channel response between user k and antenna ka can be modeled as
a FIR filter with W taps:
h(k,ka) = [h1
(k,kd),h2
(k,kd), … , hW
(k,kd) ]T (13)
We can stack all of the channel impulse responses of the k users together to
form the non-directional channel impulse response matrix:
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎣
⎡
=
),(
W
)2,(
W
)1,(
W
),(
2
)2,(
2
)1,(
2
),(
1
)2,(
1
)1,(
1
)(
hh h
hh h
hh h
Kakkk
Kakkk
Kakkk
k
H (14)
Then we stack all users’ matrixes together to form the system non-directional
channel impulse response matrix:
H = [ H(1)T, H(2)T,……, H(K)T ]
4.2. Directional Channel Impulse Response
The second type of channel impulse response is the directional channel impulse
response. The directional channel impulse response is directly related to each
signal path with a DoA and it is defined to be the channel impulse response
between user k and a reference point:
hd
(k,kd) = [hd1
(k,kd),hd2
(k,kd), … , hdW
(k,kd) ]T
Similarly as with the non-directional channel impulse response matrix, we have:
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎣
⎡
=
))(,(
dW
)2,(
dW
)1,(
dW
))(,(
d2
)2,(
d2
)1,(
d2
))(,(
d1
)2,(
d1
)1,(
d1
)(
hh h
hh h
hh h
kKdkkk
kKdkkk
kKdkkk
k
d
H (15)
Where Kd(k) is the number of DoA paths of the kth user.
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 13
Hd = [ Hd (1), Hd (2),……, Hd (K)] (16)
(Note that there is no transpose operation)
There is a close link between the non-directional channel impulse response and
the directional channel impulse response. The non-directional channel impulse
response for a given user k and given antenna ka is the summation of all
directional channel impulse responses of the user k on the antenna ka:
∑
=
=
)(
1
),(
),,(ka)(k,
kKd
kd
kdk
d
kdkakj
ehh
φ
(17)
where
φ
(k,ka,kd) = {2πL(ka)cos(β(k,kd) - α(ka) )}/λ k=1…K ka = 1…Ka and kd =
1…Kd
(k) ;
Reference point Signal k, DoA k
d
Antenna k
a
L
(k
a
)
Interference ki
β
(k,kd)
γ
(ki)
α
(ka)
Figure 4-1 Antenna array model
For a given user k and DoA kd , e j
φ
(k,ka,kd) ( ka = 1….Ka) forms its steering vector.
Thus we define:
A(k) = [ a(k,1), a(k,2),….., a(k,Kd(k))] k=1…,K (18)
as the user kth user’s steering matrix. Then the relation between the directional
channel impulse response and non-directional channel impulse response is given
by
Tk
k
d
Tkdk
kdk
kKd
kd
k)(
)(
),(
),(
d
)(
1
)( AHahH == ∑
=
(19)
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 14
5. Non-directional channel impulse response
We will estimate the non-directional channel impulse response first. The estimated response can
be used to estimate the DoA for each user and each path. Then based on the estimated DoA and
non-directional channel impulse response, the directional channel impulse response can be
derived. The estimation will be based on the midamble training sequence with length of W+L.,
where W is the maximum number of channel delay taps.
Suppose we have x = Ad + n, where n is a Nx1 Gaussian noise vector (it is not necessary to be
white), A is an Nxp known matrix, d is px1 signal vector and x is Nx1 observed signal, then a ML
estimator of d can be derived as
x
nn
1
H
1
H)(
ˆ−−
=RAARAd (20)
Actually, the estimator d
ˆ is an efficient MVU (Minimum Variance Unbiased estimator reaching
the Cramer-Rao Lower Bound) if the vector n is a complex Gaussian noise vector.
Now, we define Ka Lx1 column vectors: em(ka) for ka=1…Ka. em(ka) is the received signal
for the antenna ka based on the last L midamble training sequence. Stack Ka vectors together to
form the received L x Ka matrix
Em = [em
(1) , em
(2) ,…, em
(Ka) ]
Similarly, we define received noise vectors and LxKa matrix
Nm = [nm
(1) , nm
(2) ,…, nm
(Ka) ]
Then we have
Em= GH + Nm
where the matrix G is an L x KW observing matrix.
Moreover we have
em= vec{ Em }= vec{ GH } + vec{Nm} = vec{ GHI(Ka) } + nm (21)
= (I(Ka) ⊗ G)vec{H}+ nm = (I(Ka) ⊗ G)h+ nm
where I(Ka) is a Ka-by-Ka identity matrix, and ⊗ is the Kronecker product operator.
Thus, from (8), we have
mm
Hkaka
m
Hka eRGIGIRGIh 1
)(1)(
1
)( )()}(){(
ˆ−
−
−⊗⊗⊗= (22)
Now we have to work out the matrix G and the noise covariance matrix Rm before the non-
directional channel impulse response vector h can be obtained.
We define the matrix G to be
G = [G(1), G(2),…, G(K)] (23)
where G(k) k=1…K is the LxW Toeplitz matrix of the midamble training sequence for the kth
user. It is clear that the matrix G is pre-defined since it is composed from the given midamble
training code for all K users.
For the noise covariance matrix Rm, we have
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 15
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎣
⎡
=
),()2,()1,(
),2()2,2()1,2(
),1()2,1()1,1(
KaKa
m
Ka
m
Ka
m
Ka
mmm
Ka
mmm
m
RRR
RRR
RRR
R
(24)
In (24), we have Rm
(i,j) = E{ nm
(i)nm
(j)H }
}{ )(
),(
1
)(
1
),( Hkj
d
jkjj
Ki
kj
ki
d
Ki
ki
ikij
Enene
φ
φ
−
== ∑∑
=
}{ )()(
1
)],(),([ Hki
d
ki
d
Ki
ki
jkiikij
Enne
∑
=
−
=
φφ
2)(
)(
1
)],(),([ ~ki
ki
m
Ki
ki
jkiikij
σ
φφ
Re
∑
=
−
=
where 2)(
)()()( /}{
~ki
Hki
d
ki
d
ki
mE
σ
nnR =. Notice that )(
~ki
m
Ris the same for all Ki, Then let
)(
~~ ki
mm RR = for all ki=1….Ki and )],(),([
1
2)(
*
,, )( jkiikij
Ki
ki
ki
jiji rr
φφ
σ
−
=
∑
== e
we have
mji
ji
mrRR ~
,
),( = for i,j = 1…..Ka and
mdm RRR ~
⊗= (25)
where [Rd ]i,j = ri,j
The matrix m
R
~is a temporal covariance matrix and Rd is spatial covariance matrix.
From (10)
mm
Hkaka
m
Hka eRGIGIRGIh 1
)(1)(
1
)( )()}(){(
ˆ−
−
−⊗⊗⊗=
since
(I(ka) ⊗G )HRm
-1 = (I(ka) ⊗G )H(Rd
-1 ⊗ m
R
~-1 )
= Rd
-1 ⊗ GH 1
~−
m
R
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 16
h
ˆ= { Rd
-1 ⊗ GH1
~−
m
RG }-1 (Rd
-1 ⊗GH1
~−
m
R )em
= { Rd ⊗ ( GH1
~−
m
RG )-1 }(Rd
-1 ⊗ GH 1
~−
m
R)em
= {I(ka) ⊗ ( GH1
~−
m
RG )-1 GH1
~−
m
R}em
= {I(ka) ⊗ Mm}em
Where
1
~
1
1
~
)( −
−
−
=m
H
m
H
mGM RGGR
If m
~
R= 1 then
()
HH
mGGGM 1−
=
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 17
6. Directional channel impulse response
The directional channel impulse response is based on each directional signal path. It is the
impulse response between a given directional signal path and reference point. Based on (7)
Tk
k
d
Tkdk
kdk
kKd
kd
k)(
)(
),(
),(
d
)(
1
)( AHahH == ∑
=
if H(k) and A(k)T can be obtained or estimated, then Hd
(k) can be derived.
From
em = vec{G H } + nm = Gdhd + nm
we have the ML estimator of hd
mmd
H
ddmd
H
dd eRRGGRRGh 111 )
~
())
~
((
ˆ−−− ⊗⊗=
where 11
1))
~
(( −−
−⊗= dmd
H
dm GRRGX is the decorrelator filter and 1
)
~
@( −
md
H
dRRG is the
spatial-temporal whitening matched filter and
()
()
()
()
()
()
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎣
⎡
⊗
⊗
=
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎣
⎡
⊗⊗⊗
⊗⊗⊗
=⊗
−−
−−
−−
−−
−
1
)1(
1
)1(
1
)1(
1
)1(
11
)()(
11
)1()1(
1
~
~
~
~
)(
m
H
d
m
H
d
md
KK
md
md
H
d
RGRA
RGRA
RRGA
RRGA
RRG
H
H
HH
HH
Then we have
~
~
~
Vec{G(1)HRm-1 Em (Rd -1)*A(1)* }
Vec{G(2)HRm-1 Em (Rd -1)*A(2)* }
Vec{G(K)HRm-1 Em (Rd -1)*A(K)* }
GdH(Rd ⊗ Rm) -1 vec{Em}=
Where G(k)HRm
-1 is the temporal whitening matched filter and (Rd
-1)*A(k)* is the spatial whitening
matched filter of the user k.
We define the spatial whitening matched filter
W(k) =(Rd
-1)*A(k)* = [ w(k,1), w(k,2),….., w(k,Kd(k))], thus w(k,kd) is beanformed for the kd’s DoA.
~
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 18
7. Estimation of transmitted data
Based on the directional channel impulse response, we will estimate the transmitted data. As we
will see, beam-forming will be generated for each DoA path and all the DoA paths of the same
user will be coherently combined to enhance the system’s performance.
We define vector d as the transmitted data column vector of length KN for all K users;
d = [d(1)T, d(2)T,……, d(K)T]T where d(k)T is user k’s transmitted data vector of length N
Define matrix E the received signal matrix with dimension (NQ+W-1) x Ka:
E = [ e(1), e(2),….., e
(Ka)], where e(ka) is the received signal vector of length NQ+W-1 from
antenna ka. And we also define e = vec{E} and the combined noise vector
n = [n(1)T, n(2)T,……, n(K)T]T of length (NQ+W-1)Ka:
The data d has to been spreaded by the special signature code before it can be transmitted, thus
we define the spreading signature code matrix for user k:
N blocks = NQ rows
Q
N
C(k) = I(N) ⊗ c(k) =
Figure 7-1 Structure of the Spreading signature code matrix
Where c(k) is the special signature code for user k, k=1…K. Stack all C(k) k=1…K together to form
the combined signature code matrix
C = blockdiag[ C(1) , C(2) ,….., C(K) ]
The spreaded data can be written as:
C d = blockdiag[ C(1) , C(2) ,….., C(K) ] [d(1)T, d(2)T,……, d(K)T]T
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 19
k=2
k=K
KN
Q
k=1
NQ
=
Figure 7-2 Structure of Vector Cd
The received signal vector e is the transmitted spreaded data pass the directional channel plus
the noise:
e = Ad Hda C d + n
Where Ad= A⊗ I(NQ+W -1) , A=[A(1), A(2),……, A(K)] and
Hda= blockdiag[ Hda
(1) , Hda
(2) ,….., Hda
(K) ]
⎥
⎥
⎥
⎥
⎥
⎦
⎤
⎢
⎢
⎢
⎢
⎢
⎣
⎡
=
))(,(
)2,(
)1,(
)(
kKdk
da
k
da
k
da
k
da
H
H
H
H
Had(k,kd) =
W
N
N
Q
+W =
All vectors are
hd1(k,kd)
hd2(k,kd)
hdW
(k
,
kd
)
Figure 7-3 The structure of matrix Hda
(k,kd)
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 20
Then based on the ML rule, we can estimate transmitted data:
d
ˆ= ( CHHda
HAd
H(Rd
-1 ⊗1
~−
n
R)AdHdaC)-1 CHHda
HAd
H(Rd
-1 ⊗1
~−
n
R) e
= X CHHda
HAd
H(Rd
-1 ⊗1
~−
n
R)e
where X = ( CHHda
HAd
H(Rd
-1 ⊗1
~−
n
R)AdHdaC)-1 is a zero force equalizer.
Since Ad
H(Rd
-1 ⊗1
~−
n
R) =( AH⊗ I(NQ+W-1) ) (Rd
-1 ⊗1
~−
n
R)= AH Rd
-1 ⊗1
~−
n
R
d
ˆ = X CHHda
H (AH Rd
-1 ⊗1
~−
n
R)vec{E} = X CHHda
H vec{ 1
~−
n
RE (Rd
-1)TA*}
We define
Kd(k)
K
w(k,1) w(k,2) w
(k,Kd(k))
W(k) = (Rd
-1)TA (k)* =
As the weight matrix for the user k and
W = (Rd
-1)TA* = [ w(1,1), …, w(1,Kd(1)),……, w(K,1),…, w(K,Kd(K))] is the combined antenna weight matrix
for all K users. Then the combined beam output is
Z = EW = [y(1,1), …, y(1,Kd(1)),……, y(K,1),…, y(K,Kd(K))], where y(k,kd)= Ew(k,kd)
d
ˆ= X CHHda
H (AH Rd
-1 ⊗1
~−
n
R)vec{E} = X CHHda
H vec{ 1
~−
n
RE W }
= X CHHda
H vec{ 1
~−
n
RZ }
Since vec{ 1
~−
n
RZ }= vec{ 1
~−
n
RZ I(Kd) } =( I(Kd) ⊗ 1
~−
n
R)vec{Z}, then
d
ˆ= X CHHda
H( I(Kd) ⊗ 1
~−
n
R)vec{Z}
is the estimate of the transmitted data.
= X CHHda
H( I(Kd) ⊗ 1
~−
n
R) [y(1,1)T, …, y(1,Kd(1))T,……, y(K,1)T,…, y(K,Kd(K))T]
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 21
8. Summary
In this paper, the spatial-temporal processing of a received TD-SCDMA signal is presented. The
directional channel impulse response is estimated based on the non-directional response. It is
shown in this paper that the ML estimator of the transmitted data utilizes both the temporal and
spatial information of the signal and that the estimator consists of a bean former followed by a
zero-force equalizer.
Spatial Temporal Processing in TD-SCDMA
Error! Reference source not found. 22
References
1. http:// www.3gpp.org
2. http://www.tdscma.org.
3. Josef Johannes Blanz, Apostolos Papathanassiou, Martin Haardt, Ignasi Furio and Paul
Walter Baier, “Smart Antennas for Combined DoA and Joint Channel Estimation in Time-
Slotted CDMA Mobile Radio Systems with Joint Detection” IEEE Tran. On vehicular tech.
Vol.49, No.2, March 2000.
AN2904
Rev. 0
11/2004
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