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february 19, 2004 chengke sheng ed martinez zf - ble joint detection for td - scdma f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
2 table of contents 1. introduction ................................ ................................ ................................ .......................... 6 1.1. s cope and a udience ................................ ................................ ................................ ............... 6 1.2. e xecutive s ummary ................................ ................................ ................................ ............... 6 1.3. b ackground ................................ ................................ ................................ ........................... 6 2. signal model ................................ ................................ ................................ ........................... 8 2.1. tdd/tdma ................................ ................................ ................................ ............................. 8 2.2. td - scdma f rame h ierarchy ................................ ................................ ............................... 8 2.3. td - scdma s lot s tructure ................................ ................................ ................................ .. 9 3. sys tem model ................................ ................................ ................................ ........................ 10 3.1. c hannel m odel ................................ ................................ ................................ .................... 10 3.2. r eceived s ignal m odel ................................ ................................ ................................ ....... 11 4. ze ro force block joint estimator ................................ ................................ ........... 13 4.1. e stimating the c hannel m atrix a ................................ ................................ ..................... 13 4.2. c omputation of the w hitening m atched f ilter ................................ ............................... 15 4.3. c omputation of the z ero f orce e qualizer ................................ ................................ ....... 16 5. joint detection rece iver implementation ................................ ......................... 18 f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
3 table of fig ures f igure 2 - 1 s ymmetric and a symmetric traffic su pport in td - scdma ................................ ........... 8 f igure 2 - 2 td - scdma f rame s tructure [ 6] ................................ ................................ ....................... 9 f igure 2 - 3 t he td - scdma s lot s tructure [ 5] ................................ ................................ ................... 9 f igure 3 - 1 d iscrete base band mo del of a block trans mission cdma system . ............................ 10 f igure 3 - 2 t he c hannel m atrix a ................................ ................................ ................................ ..... 12 f igure 4 - 1 zf - ble e stimator ................................ ................................ ................................ ............. 13 f igure 4 - 2 e stimation of the s patial c ovariance m atrix ................................ .............................. 15 f igure 4 - 3 z ero f orce e qualizer m atrix ................................ ................................ ......................... 16 f igure 4 - 4 c 0 and c 1 submatrices ................................ ................................ ................................ ....... 17 f igure 5 - 1 j oint d etection b ased r eceiver ................................ ................................ ...................... 18 f igure 5 - 2 mrc6011 b ased td - scdma r eceiver ................................ ................................ ............. 19 f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
4 terms and acronyms tdd time di vision duplex fdd frequency division duplex cdma code division multiple access tdma time - division multiple access fdma frequency - division multiple access bs base station mai multiple access interference rcf reconfigurable computing fabric jd joint detection zf - ble zero - forcing block linear equalizer f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
5 abstract this paper presents the block linear equalizer (zf - ble) joint detection algorithm, which is one of the algorithms used in the implementation of a td - scdma receiver. the paper presents a very brief introduction to td - scdma and the technical aspects relevant to the discussion of the joint detector, including a brief signal and system mode, followed by a detailed description of the zf - ble algorithm and finally a discussion of its implementation. f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
6 1 . introduction 1 . 1 . scope and audience this documented is targeted at wireless systems engineers who are interested in obtained detailed knowledge in the mathematical background behind the zero forcing block linear equalizer (zf - ble) joint detection algorithm u sed in td - scdma systems. the paper presents a very brief introduction to td - scdma and the technical aspects relevant to the discussion of the joint detector, including a brief signal and system model, this is followed by a detailed description of the zf - bl e algorithm and finally a discussion of its implementation. 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 enginee rs 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 system s 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 th e 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 gr ows 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 requ ired 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 synchroniz ed. this results in a reasonable complexity joint detector that can be easily implemented in today?s parallel computational architectures. 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 o f 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 f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
7 3gpp name access mode chip rate wcdma fdd 3.84 mcps t dd - cdma tdd 3.84 mcps td - scdma tdd 1.28 mcps table 1 - 1 td - scdma in relationship to other 3g standards f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
8 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 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 signat ures 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 gro ups in order to meet specific traffic requirements. all physical channels require a guard symbol in every time slot [ 6 ]. f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
9 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 m s) subframe #1 subframe 2 figure 2 - 2 td - scdma frame structure [ 6 ] 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 chan nel estimation tasks. data sym bols 352chips midamble 144 chips d a ta sym bols 352 chips gp 16 cp 675 s figure 2 - 3 the td - scdma slot structure [ 5 ] f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
10 3 . system model 3 . 1 . channel model in a td - scdma system, we have k users who access the channel simultaneously. on th e 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 - mat i on m m m m m m e ) ( k b ) ( k b ) 1 ( b c (1) c (k) c (k) h (1) h (k) h (k) n data esti - mat i on m m m m ) 1 ( ? d ) ( ? k d ) ( ? k d ) 1 ( d ) ( k d ) ( k d m m e ) ( k b ) ( k b ) 1 ( b figure 3 - 1 discrete base band model of a block transmission cd ma system. in the system of figure 3 - 1 we assume that there are k a antennas for the receiver . the k th user transmits a data symbol sequence block with n symbols: ( ) t k n k k k d d d ) ( ) ( 2 ) ( 1 ) ( , k = d k = 1,2,?..,k ( 1 ) [ ] t k n n n k k k d d d d d d d d d ) ( ) 2 ( ) 1 ( ) ( 2 ) 2 ( 2 ) 1 ( 2 ) ( 1 ) 2 ( 1 ) 1 ( 1 ) ( , , , , , , , , , k k k k = d ( 2 ) where n is the number of symbols in each data block. ( ) t k q k k k d c c ) ( ) ( 2 ) ( 1 ) ( k = c k = 1, 2 ? k ( 3 ) ) ( k c is the k th 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 th e same spreading factor. each of the k channels in the system is characterized by its impulse response [ ] t k w k k k h h h ) ( ) ( 2 ) ( 1 ) ( k = h k = 1,2 ? k ( 4 ) where w is the number of taps in the channel. similarly, we have the noise vector for antenna k a f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
11 [ ] t ka w nq ka ka ka n n n ) ( 1 ) ( 2 ) ( 1 ) ( - + = k n ( 5 ) and [ ] t ka ) ( ) 2 ( ) 1 ( n n n n k = 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 k a th antenna is: e (ka) = (e 1 (ka) , e 2 (ka) , . . . , e nq+w - 1 (ka) ) t ( 7 ) where q again is the spreading factor of the data symbol and w is t he number of taps in channel. [ ] t ka ) ( ) 2 ( ) 1 ( . , e e e e k = e = vec[ e ] ( 8 ) from figure 3 - 1 we can see that ( ) ) , ( ) , ( 1 ) , ( 2 ) , ( 1 ) , ( * ) ( , , ka k t ka k w q ka k ka k ka k k b b b h c b = = - + k ( 9 ) is the convolution of the channel input response with the corr esponding spreading code. ( ) , ( ka k h is the channel impulse response between the user k and antenna k a , 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 rel ate the user?s signal and the receiver input: n d i a e + ? = ) ( ) ( ka ( 10 ) where, u is the kronecker product . or n ad e + = ( 11 ) the matrix a is called channel matrix and is defined as [ ] t ka ) ( ) 2 ( ) 1 ( a a a a k = ( 12 ) f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
12 k k nq+w b (1,kaa)) b (2,ka) b (k,ka) q+w b (ka) = a (ka) = b (ka) b (ka) b (k a) figure 3 - 2 the channel matrix a f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
13 4 . zero force blo ck joint estimator we want to find the estimate of the transmitted data vector d from the received signal e. n d i a e + ? = ) ( ) ( ka ( 13 ) if we treat the data vector d as an unknown nonrandom vector, we want to find an estimate of the n data symbols transmitted by the k th user during the sub frame based on the principle of maximum likelihood estimation, we can obtain this estimate by e r a a r a d 1 n h 1 1 n h ) ( ? - - - = ( 14 ) where { } h n e nn r = is the noise covariance matrix. since we need r n - 1 we assume that r n is non - singular. we will use the cholesky decomposition: r n - 1 = l h l to arrive at r n - 1 the estimation of the data block the data block d ? can be broken to a whitening filter a h r n - 1 followed by a zero - force equalizer ( a h r n - 1 a ) - 1 (see figure 4 - 1 ) . channel a e = ad + n whitening filter l matched filter a h l h= ( la ) h zero - force equal i zer ( a h r n - 1 a ) - 1 ^ d n figure 4 - 1 zf - ble estimator to estimate the data vector d, we need to know both noise covariance matrix r n and the channel matrix a. 4 . 1 . estimating the channel matrix a estimation of the channel matr ix a is based on the midamble chips in each slot. suppose e m (ka) = (e 1 (ka) , e 2 (ka) ,. . . , e l (ka) ) t is the received midamble chip vector from antenna k a and the received midamble chips are not contaminated by its previous data symbol. (thus, we pick u p the midamble chips from 17 to 144 for a total of 128 chips, i.e. l = 128 and we assume that the multi - path dispersion is within 16 chips). we stack all ka such vectors together to form the received matrix. e r a a r a d 1 n h 1 1 n h ) ( ? - - - = ( 15 ) e m = [ e m (1) , e m (2) , ? , e m (ka) ] ( 16 ) similarly, the received noise vector for antenna k a is f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
14 n m (ka) = (n 1 (ka) , n 2 (ka) , . . . , n l (ka) ) t and stacked noise matrix is ( 17 ) n m = [ n m (1) , n m (2) , ? , n m (ka) ] ( 18 ) we define h (k,ka) as the w - tap channel impulse response between the user k and antenna k a h (k,ka) = (h 1 (k,ka) , h 2 (k,ka) , . . . , h w (k,ka) ) t ( 19 ) then the channel impulse response matrix for u ser k is stacked matrix from all ka antennas: h (k) = [ h (k,1) , h (k,2) , ? , h (k,ka) ] ( 20 ) h = [ h (1)t , h (2)t , ? , k (k)t ] t the key to estimate the channel matrix a is to estimate the channel?s impulse response based on the given midamble training code sequence. thus we build up the midamble matrix: g (k) is a l x w toeplitz matrix of the midamble training code sequence for kth user. and g = [ g (1) , g (2) , ? , g (k) ] stacked midamble training code matrix for all users ( 21 ) . then, we have e m = gh + n m ( 22 ) e m = vec{ e m } = vec{ gh + n m } = vec{ gh } + vec{ n m } = ( i (ka) u g )vec{ h } + n m ( 23 ) = ( i (ka) u g ) h + n m where i (ka) is a k a x k a identity matrix. then the ml estimator of vector h is m 1 t h 1 1 t h (ka) } ) ( { ? e r g g r g i h - - - ? = ( 24 ) where r m = e{ n m n m h }= r d u r t then, we have (ka) m 1 t h 1 1 t h (ka) ) ( ? e r g g r g h - - - = ( 25 ) since r t is the temporal covariance, we will assume that r t = i , then (ka) m (ka) m h 1 h (ka) ) ( ? me e g g g h = = - ( 26 ) where m = ( g h g ) ? 1 g h f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
15 if g is a square matrix, then m = g - 1 is a square right circulant matrix, then [ 4 ] h (ka) = d * l m d e m (ka) = ifft( l m fft( e m (ka) )) ( 27 ) = ifft(fft( e m (ka) )/.diag( l m ) ) ( 28 ) 4 . 2 . computation of the whitening matched filter from the previous analysis, it is known that the estimated data vector can be written as e r a a r a d 1 n h 1 1 n h ) ( ? - - - = = ( a h r n - 1 a ) - 1 d mf ( 29 ) w here r n = r d u r t = r d u i and d mf = a h r n - 1 e is the whitening matched filter output. the key to compute the whitening match filter output is to estimate the spatial covariance matrix r d [ r d ] i,j = s p=1 m ( n p (i) n p (i)* )/m = ( n (i) n (j)h )/m i,j = 1,2,?., ka; m=nq+w - 1. ( 30 ) we estimate the spatial covariance matrix based on the noise detected from the data field of the slot. there are total nq+w - 1 noise samples in each data field. suppose that: r n - 1 = r d - 1 u r t - 1 = r d - 1 u i= a 11 , a 12 ,??. a 1ka a 21 , a 22 ,??. a 2ka a ka,1 , a ka,2 ,??. a ka,ka u i ka ka nq+w - 1 nq+w - 1 figure 4 - 2 estimation of the spatial covariance matrix we have ] ' ,...., ' , ' [ ] ,....., [ (ka)h (2)h (1)h 1 d (ka)h (2)h (1)h 1 n h a a a i r a a a r a = ? = - - ( 31 ) where a ? (ka)h = s i=1 ka a i,ka a (ka)h then : a h r n - 1 e = s ka=1 ka a ? (ka)h e (ka) ( 32 ) maximum ratio combining f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
16 from above equati on, the output of the whitening matched filter is the coherent maximum ratio combining of all k a antennas. thus k a elements of the antenna array work as a diversity array and no beam is formed. 4 . 3 . computation of the zero force equalizer we now turn our atten tion to the computation of the zero force equalizer ( figure 4 - 1 ). we define the zero force equalizer matrixes as c - 1 = ( a h r n - 1 a ) - 1 and c = a h r n - 1 a ( 33 ) c = [ a? (1)h a? (2)h ?.. a? (ka)h ] [ a (1)t a (2)t ?.. a (ka)t ] t = s ka=1 ka a? (ka)h a (ka) ( 34 ) = s ka=1 ka c (ka) the matrix c is the summation of the matrix c (ka) .which indicate that ka antenna elements are coherently combined. c (ka) = b (ka) b (ka) b (ka) ka=1 ~ ~ ~ a (ka) h ~ a (ka ) = c 0 q+w - 1 c 0 c 0 c 0 c 1 c 1 c 1 h c 1 h c 1 h c 1 h c 1 c 2 c 1 b (ka) b (ka) b (ka) figure 4 - 3 zero force equalizer matrix from figure 4 - 3 the sub - matrixes c 0 and c 1 can be computed from: f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
17 c 0 = k b (1, ka ) b (2,ka ) b (k,ka ) q+w - 1 b (1,ka) h b (2,ka) h b (k,ka) h ~ ~ ~ q+w - 1 c 1 = b (1,ka ) b (2,ka ) b (k,ka ) first w - 1 rows b (1,ka) h b (2,ka) h ~ 0 q+w - 1 q k b (1,ka ) b (2,ka ) b (k,ka ) q+w - 1 b (1,ka) h b (2,ka) h b (k,ka) h ~ ~ ~ q+w - 1 c 0 = figure 4 - 4 c 0 and c 1 submatrices f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
18 5 . joint detection receiver implementation figure 5 - 1 gives the logical block diagram of the joint detector that has been discussed in this paper. joint detection algorithms are complex and computationally intensive (complexity grows exponentially as the number of codes increases) and as such are not suitable for use in other cdma systems because of the high number of codes used in those systems. in the joint detection block diagram, most of the operations are matrix and vector operations. as the size of the matrices and vectors increases, so does the complexity of the system and the computational power that is required to separate the users. antenna d ata da ta e xtract e (a) w hitening ma tched filter a (a)h r n (a) - 1 max ra tio antenna comb ining noise va rian ce e stimation ma trix a (a) g e ne r a t or d ecorrelator (a h r n - 1 a (a) ) - 1 max ra tio antenna comb ining calculate (a (a) h r n (a) - 1 a (a) ) - 1 spreading code g e nerator midamble e x tr ac tion e (a) channel e st imation u ser?s data figure 5 - 1 joint detection based receiver the analysis of the joint detection algorithm presented in this work shows very clearly that a very large of matri x computations are involved. because of this, traditional dsps are not suited to this task. one could argue that a matrix - coprocessor could be used in the computations, however the variety in the dimensions of the matrices involved would make such a coproc essor very inefficient and therefore very expensive to use. an approach with a structure that can reconfigure and adapt would be the ideal solution to the problem. the inherent parallelism in the implementation of the various blocks in the joint detector makes it an ideal fit for the motorola mrc6011 reconfigurable compute fabric. the multicore architecture provides a very high degree of flexibility and scalability and facilitates the integration of the joint detection operation with the other receiver blo cks such as the channel estimation processor. when coupled with motorola?s advanced dsps, the mrc6011 provides the ideal solution for the implementation of a td - scdma receiver. for more complete details on the implementation of the receiver with the mrc60 11, the reader is referred to other publications in this series or contact your local motorola field applications engineer. f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
19 figure 5 - 2 mrc6011 based td - scdma receiver user 1 user 2 user n channel estimation joint detector symbol rate processor analog front end a/d burst split mrc6011 msc8102/msc81 26 f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .
20 references 1 . rappaport, t. s., wireless communications, upper saddle river, nj: prentice hall, 1996. 2 . viterbi, a.j., cddma: principles of spread spectrum communications. reading. ma: addisson - wesley, 1995. 3 . m. haardt, a. klein, r. koehn, s. oestreich, m. purat, v. sommer. ?the td - cdma based utra t dd mode? ieee journal on selected areas in communications, vol 18, no. 8, august 2000. 4 . bernd steiner, peter jung: optimum and suboptimum channel estimation for the uplink of cdma mobile radio system with joint detection. 5 . 3gpp tr 25.928 v4.01 ? 1.28 funct ionality for utra tdd physical layer (release 4). 2001 6 . 3gpp ts 25.221 v5.5.0 (2003 - 6). physical channels and mapping of transport channels onto physical channels (tdd) ? release 5. f r e e s c a l e s e m i c o n d u c t o r , i freescale semiconductor, inc. f o r m o r e i n f o r m a t i o n o n t h i s p r o d u c t , g o t o : w w w . f r e e s c a l e . c o m n c . . .

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