Thông tin tài liệu
8
Carrier Recovery for
‘Sub-Coherent’ CDMA
8.1 Overview
In this chapter we examine possible methods of carrier recovery for the SE-
CDMA presented in Chapter 6. In particular, we propose, evaluate and compare
two techniques; namely Symbol-Aided Demodulation (SAD) and the Pilot-Aided
Demodulation (PAD). The performance analysis of each scheme (SAD and PAD)
includes both Rician and Rayleigh multipath fading channels, and thus are also
useful (in addition to the satellite) in terrestrial mobile applications. Both schemes
are promising alternatives to differentially coherent demodulation for scenarios
characterized with uncertainties in the carrier phase that make coherent demodulation
unfeasible. The frequency selective fading (multipath), the Doppler phenomenon due
to user mobility and/or to satellite drift motion, and the temperature variation and
ventilation conditions at the sites of the various local oscillators that generate the
transmitted signals cause the carrier phase uncertainty.
Coherent demodulation requires the extraction of a reliable (perfect) phase reference
from the received signal. A traditional alternative is the differentially coherent
demodulation that uses the phase of the previous bit (symbol) as a reference, but
requires almost 3dB (for M-ary PSK modulation in AWGN channels, it is less than
that for BDPSK) of additional signal-to-noise (E
b
/N
0
) in order to achieve the same
bit error rate as coherent demodulation. This problem is more severe in DS/CDMA
systems, which are limited by other-user interference: the additional cost in dBs of
differentially coherent over coherent demodulation increases linearly with the number
of users in the system, so as to render the fully-loaded multi-user system impractical
[1]. Recently, SAD [2] and PAD [3] have been considered a form of ‘sub-coherent’
demodulation. In the proposed SAD and PAD schemes, estimates of the channel
multipath phases and amplitudes are extracted by smoothing and interpolation of
the transmitted known bits in the SAD scheme or the pilot in the PAD scheme. The
SAD (or PAD) performance then consists of evaluating the additional Signal-to-Noise
Ratio (SNR) needed by either scheme to achieve the same Bit Error Rate (BER) as
the coherent demodulation.
In this chapter we first present the system model and the design issues of the SAD
scheme in Section 8.2, and its BER analysis (for the uncoded system) in Section 8.3.
Then in Section 8.4 we present the system model, the design and the BER analysis
CDMA: Access and Switching: For Terrestrial and Satellite Networks
Diakoumis Gerakoulis, Evaggelos Geraniotis
Copyright © 2001 John Wiley & Sons Ltd
ISBNs: 0-471-49184-5 (Hardback); 0-470-84169-9 (Electronic)
188 CDMA: ACCESS AND SWITCHING
(for the uncoded system) of the PAD scheme. The BER analyses of the coded systems
are presented in Section 8.5. The coded system is based on a proposed new iterative
decoding algorithm. The performance of the coded system of both schemes has been
evaluated via simulations. The performance results are presented in Section 8.6.
8.2 Symbol-Aided Demodulation
8.2.1 System Model
In symbol-aided demodulation, known symbols are multiplexed with data bearing
symbols. The known symbols are multiplexed with the data symbols at a constant
ratio, so that one known symbol is followed by J − 1 unknown data symbols. This
ratio implies a loss in the throughput of 1/J. At the receiver the known symbols are
used to estimate the channel for other sampling points.
The system is as shown in Figure 8.1-A. The transmitted signal for the first user is
given by
s
1
(t)=A
∞
k=−∞
b
1
(k)a
1
(t)p(t −kT)
where b
1
(k) is the binary data sequence, a
1
(t) is the spreading code, which is a periodic
sequence of unit amplitude positive and negative rectangular pulses (chips) of duration
T
c
, T = NT
c
is the symbol duration, and N is the processing gain.
The j
th
code pulse has amplitude a
j
i
= a
i
(t)forjT
c
≤ t ≤ (j +1)T
c
,andp(t)isa
unit energy pulse in the interval 0 ≤ t ≤ T . The received signal is
r(t)
L
l=1
c
1l
(t −τ
1l
)s
1l
(t −τ
1l
)+
K
u
m=2
L
l=1
c
ml
(t −τ
ml
)s
ml
(t −τ
ml
)+n(t)
where L is the number of paths, n(t) is the AWGN with power spectral density N
0
in the real and imaginary parts, and K
u
is the number of users. The channel complex
gain c
ml
(t) represents the Rayleigh or Rician fading for the l
th
path of the m
th
user,
with an autocorrelation function [4]
R
c
(τ)=σ
2
g
K
1+K
+
1
1+K
J
0
(2πf
D
τ)
where K is the ratio between the line of sight power and the scattered power, and the
paths are assumed independent and with identical distributions.
The output of the normalizing matched filter, representing the finger of the rake
receiver, for the first path of the first user, with impulse response a
1
(−t)p
∗
(−t)/(
√
N
0
),
and assuming τ
11
= 0, will be given by
r
11
(k)=u
11
(k)b
1
(k)+
L
l=2
u
1l
(k)I
1l
(k)e
jφ
1l
(k)
+
K
u
m=2
L
l=1
u
ml
(k)I
ml
(k)e
jφ
ml
(k)
+ n
11
(k)
CARRIER RECOVERY 189
where the Gaussian noise samples n
11
(k) are white with unit variance, and complex
symbol gain u
ml
(k) has mean
E[u
ml
(k)] =
γ
s
ml
K
K +1
and variance
σ
2
u
ml
= γ
s
ml
1
K +1
where the average SNR for path l of user m is given by
γ
s
ml
=
E
s
ml
N
0
and I
ml
(k) is the interference from path l of user m to path 1 of user 1. For the SAD
scheme
E
s
ml
= E
b
ml
J − 1
J
where E
b
ml
is the energy per bit, and
γ
b
ml
=
E
b
ml
N
0
8.2.2 Design of Modulator and Demodulator
There are several issues that must be taken into consideration for the proper design
of the symbol-aided modulation/demodulation system.
TheRateofAid-Symbols
A proper choice of the value of J is of paramount importance for SAD system design.
Increasing J will result in increasing the throughput, but at the same time it will
increase the processing delay and the carrier-phase estimation error in both the known
symbols and the data symbols.
Guidelines for the choice of J are given below. The value of J is determined from
the bandwidth, rate of fading or of Doppler, or in general, from the rate of change of
the phenomenon that introduces the uncertainty (and change) in the carrier phase.
If we assume that the fading rate (or other rate of change) is R
f
, then the sampling
period T
fs
and sampling rate R
fs
=1/T
fs
of the channel observations must satisfy
the Nyquist condition
R
fs
=
1
T
fs
≥ 2R
f
For notational convenience, define
J
max
=
R
s
2R
f
where R
s
is the symbol rate. J
max
corresponds to the sampling of the fading
phenomenon at exactly the Nyquist rate, presented in a more convenient form
190 CDMA: ACCESS AND SWITCHING
A.
B.
MPSK-Mod
& Symbol or
Pilot Insertion
Pulse
Shaping
Channel
AWGN
&
Fading
Other
User
Interf
.
Rake
Receiver
Decision
Data
Σ
Delay
11
τ
12
τ
L1
τ
T-
Channel
Estimation
Delay
T-
Channel
Estimation
Delay
T-
Channel
Estimation
Decoder
Carrier
Removal
complex
signal
SAD
PAD
SAD
PAD
SAD
PAD
·
·
·
·
·
·
Figure 8.1 A. The SAD/PAD CDMA system B. A rake receiver for SAD (or PAD in
dotted lines).
corresponding to the rate which known symbols are inserted for a given data and fading
rates in order to fully capture the variation in the fading (or other phenomenon). We
expect that
R
f
<< R
s
that is, the rate of change of the carrier phase is much slower than the symbol rate
of the system. For example, we may have R
s
= 64 kbps (kHz) while R
f
= 64 or 128
Hz (or a value in the range of 30 Hz to 200 Hz). Denoting the symbol duration as
T
s
=1/R
s
,wehavethatT
f
>> T
s
, and define J as the ratio T
fs
/T
s
, i.e.
J =[T
fs
/T
s
]=[R
s
/R
fs
] ≤ [R
s
/(2R
f
)] = J
max
Therefore, J
max
corresponds to sampling at exactly the Nyquist rate, and J ≤ J
max
corresponds to oversampling; for example J = J
max
/4 corresponds to sampling at four
times the Nyquist rate, while J = J
max
/8 corresponds to sampling at eight times the
Nyquist rate.
TheideaistouseasufficientlysmallJ so that oversampling at rate
R
fs
=(J
max
/J) · (2R
f
)
CARRIER RECOVERY 191
captures the change in the phenomenon and reduces the noise in the estimates of
the phase (by a factor of J
max
/J through smoothing, as we will see next) but still
maintains the throughput loss (equal to 1/J) within acceptable values.
A simple analysis of the SAD technique was presented in reference [5]. This
is an approximate analysis assuming perfect filtering, but it provides an intuitive
understanding of the problem and it helps identify the optimum J.Itisdoneby
simply taking into consideration the power loss due to reference insertion, expressed
as
L
r
≈
J +1
J
=1+
1
J
and the amount of increase in the noise due to the noisy reference (assuming perfect
filtering and interpolation) which is given by
L
n
≈ 1+
J
J
max
Thus the total loss compared to coherent system is given by
L
t
(dB)=L
r
(dB)+L
n
(dB)
The optimum choice of J given J
max
can be obtained by calculating the minimum
achievable loss; we can easily get
J
opt
≈
J
max
L
t
(J
opt
) ≈ (1 +
1
√
J
max
)
2
Then the conclusion is that the performance of any SAD system can be no better than
L
t
dBs below (worse than) the performance of a coherent system (which assumes the
perfect knowledge of the fading phase). For example, for J
max
= 50, J
opt
≈ 7, and
L
t
≈ 1.15dB.
For the SAD scheme, the demodulation will delay the data symbols by JM symbols,
where M is half the order of the smoothing filter. Clearly, decreasing J will produce a
shorter delay, but as we mentioned, it will decrease the throughput, and the estimation
error will be increased.
The Smoothing Filter
The bandwidth of the smoothing filter is another important issue. This filter is a
digital filter that estimates u
ml
(k) of the unknown symbol samples. Decreasing J
(which is equivalent to oversampling) will enable the filter to better estimate u
ml
(k)
by removing more noise, and allow easier tracking of the relatively slower fading.
Two approaches are addressed here. The first is to derive the optimal Wiener filter
for every unknown data point within the frame of length J, which means that filtering
and interpolation are done simultaneously (in a sliding window manner). The second
approach is to use a single filter for filtering all the known symbols, which is also a
Wiener filter, and then to linearly interpolate the resulting output in order to obtain
all unknown data symbols. The difference in performance between the two approaches
is evaluated below.
192 CDMA: ACCESS AND SWITCHING
8.3 BER Analysis for SAD
The first step for calculating the performance is to calculate the interference (see
r
11
(k) in Section 8.2.1). The best way to proceed is to calculate I
ml
(k)foragiven
code selection, and hence calculate the mean square power of the interference averaged
over τ
ml
. A very good approximation is to follow references [6] and [1], and to assume
a random signature sequence of length N. This approximation is very accurate if the
system uses long (period) codes like the IS-95 system [3], and has sufficiently large N
and K
u
. Following references [6] or [1], we can calculate
E {I
ml
(k)} =0
E
I
2
ml
(k)
=
2
3N
In this section the analysis of the SAD system will be presented for both the optimum
Wiener filter and linear interpolation case.
8.3.1 Optimum Wiener Filtering
The best performance that can be expected from the SAD technique (for a given filter
length) can be obtained from Wiener filters. We will obtain its performance in this
section for multipath Rician fading channels. Cavers [2] was the first to perform this
analysis for Rayleigh fading channels. The phase reference of the l
th
path of the m
th
user for the unknown symbols is obtained from
v
ml
(k)=h
†
(k)r
ml
=
M
i=−M
h
∗
(i, k)r
ml
(iJ)
where the dagger denotes conjugate transpose, and r
ml
is the vector formed from
r
ml
(iJ), the samples of the output of a matched filter of a finger of the rake receiver,
−M ≤ i ≤ M is the index of the known (SAD) symbols, and 1 ≤ k ≤ J − 1. Note
that there will be J − 1 different filters used.
The Wiener filter equation will be given by
˜
Rh(k)=w(k)
where
˜
R is the autocorrelation matrix of size 2M + 1 defined by
˜
R =
1
2
E[r
ml
r
ml
]
and the J − 1 vectors are
w(k)=
1
2
E[u
∗
ml
(k)r
ml
]
The channel is Rician as described by R
c
(τ) in Section 8.2.1. Perfect power control
is assumed, such that γ
b
ml
is constant for all users and is denoted by γ
bL
. It is assumed
CARRIER RECOVERY 193
that all the paths are identical, and so
γ
bL
=
γ
b
L
where γ
b
= Lγ
b
ml
is the total average SNR for every bit from all the paths.
Now we can obtain
˜
R and w(k)from
R
ij
=
γ
bL
K +1
J − 1
J
K + J
0
π
(i −j)J
J
max
+
γ
bL
J − 1
J
2(K
u
∗ L − 1)
3N
+1
δ
i,j
w
i
(k)=
γ
bL
K +1
J − 1
J
K + J
0
π
(iJ − k)
J
max
where δ
i,j
is the Kronecker delta. The Rake receiver is shown in Figure 8.1-B, which is
the maximal ratio combiner with noisy reference. From reference [7] we can calculate
the probability of error using
Pe = Q
1
(a, b) −I
0
(ab)e
[−
1
2
(a
2
+b
2
)]
+
I
0
(ab)e
[−
1
2
(a
2
+b
2
)]
[2/(1 − µ)]
2L−1
L−1
k=0
2L −1
k
1+µ
1 −µ
k
+
e
[−
1
2
(a
2
+b
2
)]
[2/(1 − µ)]
2L−1
×
L−1
n=1
I
n
(ab)
L−1−n
k=1
2L −1
k
·
b
a
n
1+µ
1 −µ
k
−
a
b
n
1+µ
1 −µ
2L−1−k
where
a
2
=
L
2
E{r}
σ
r
−
E{v}
σ
v
2
and b
2
=
L
2
E{r}
σ
r
+
E{v}
σ
v
2
Q
1
(a, b)=
∞
b
xe
[−
1
2
(a
2
+x
2
)]
I
0
(ax)dx and µ =
σ
2
rv
σ
v
σ
r
where for the SAD scheme,
σ
2
rv
= w
†
(k)h(k) −
K
K +1
J − 1
J
γ
bL
S
h
(k)
σ
2
v
= w
†
(k)h(k) − (E{v})
2
σ
2
r
= γ
bL
J − 1
J
1
K +1
+1+γ
bL
J − 1
J
2[K
u
∗ L − 1]
3N
E{v} =
K
K +1
J − 1
J
γ
bL
S
2
h
(k)
E{r} =
K
K +1
J − 1
J
γ
bL
194 CDMA: ACCESS AND SWITCHING
where S
h
(k)=
M
i=−M
h(i, k), while for coherent demodulation we have v
ml
(k)=
u
ml
(k)
σ
2
rv
=
1
K +1
γ
bL
σ
2
v
=
1
K +1
γ
bL
σ
2
r
= γ
bL
1
K +1
+1+γ
bL
2[K
u
∗ L − 1]
3N
E{v} =
K
K +1
γ
bL
E{r} =
K
K +1
γ
bL
and for differential modulation we have v
ml
(k)=r
ml
(k − 1)
σ
2
rv
=
1
K +1
γ
bL
J
0
π
J
max
σ
2
v
= γ
bL
1
K +1
+1+γ
bL
2[K
u
∗ L − 1]
3N
σ
2
r
= γ
bL
1
K +1
+1+γ
bL
2[K
u
∗ L − 1]
3N
E{v} =
K
K +1
γ
bL
E{r} =
K
K +1
γ
bL
Filtering Followed by Interpolation
The second approach is to design a single filter to filter the known samples and then
linearly interpolate the output to estimate the channel at the unknown samples. A
Wiener filter can still be used to maximize the effective SNR at k = iJ. Following
the same Wiener optimization approach as before, we can obtain h for k =0and
use it.
Following the filter, the interpolator linearly interpolates the estimates of the carrier
(or fading) inphase and quadrature components of the data symbols between each two
successive known symbols (0 and J). We consider the case of 1 ≤ k ≤ J −1 without
any loss of generality. We have
v(k)=
k
J
v(J)+
J − k
J
v(0)
The expression for the probability of error P
e
(given above) will be used again to
calculate the performance, where now
CARRIER RECOVERY 195
σ
2
rv
=
M
i=−M
h(i)γ
bL
J − 1
J
1
K +1
K +
J − k
J
· J
0
π
iJ − k
J
max
+
k
J
J
0
π
(i +1)J − k
J
max
−
K
K +1
J − 1
J
γ
bL
S
h
(k)
σ
2
v
=
M
i=−M
M
j=−M
h(i)h(j)γ
bL
J − 1
J
1
K +1
J − k
J
2
+
k
J
2
K + J
0
π
(i −j)J
J
max
+ h(i)h(j)γ
bL
J − 1
J
1
K +1
J − k
J
k
J
2K
+ J
0
π
(i −j − 1)J
J
max
+ J
0
π
(i −j +1)J
J
max
+ h(i)h(j)
J − k
J
2
+
k
J
2
1
+ γ
bL
J − 1
J
2(K
u
∗ L − 1)
3N
δ
i,j
+ h(i)h(j)
J − k
J
k
J
·
1+γ
bL
J − 1
J
2(K
u
∗ L − 1)
3N
(δ
i,j−1
+ δ
i,j+1
)
− (E{v})
2
The other parameters (E{v},σ
2
r
,E{r},S
h
(k)) are like those given in the previous
section for the optimum Wiener filter case.
8.4 Pilot-Aided Demodulation
8.4.1 System Model
The transmitted signal for user 1 is given by
s
1
(t)=A
∞
k=−∞
((A
p
a
p
1
(t)+b
1
(k)a
1
(t))p(t −kT)
where A
p
is the pilot amplitude, a
p
1
(t) is the pilot spreading code, and all the other
parameters are as described for the SAD scheme. a
p
1
(t)anda
1
(t) could easily be
made orthogonal through the use of code concatenation. The orthogonality will be
maintained for every path because both codes will pass through the same channel.
196 CDMA: ACCESS AND SWITCHING
The received signal will be given by
r(t)=
L
l=1
c
1l
(t −τ
1l
)s
1l
(t −τ
1l
)+
K
u
m=2
L
l=1
c
ml
(t −τ
ml
)s
ml
(t −τ
ml
)+n(t)
The output of the normalizing matched filter, representing the finger of the rake
receiver, for the first path of the first user, with impulse response a
1
(−t)p
∗
(−t)/(
√
N
0
)
assuming equal energy pulses and BPSK modulation, will be given by
r
11
(k)=u
11
(k)(b
1
(k)+I
11
p
(k)) +
L
l=2
u
1l
(k)I
1l
(k)e
jφ
1l
(k)
+
K
u
m=2
L
l=1
u
ml
l(k)I
ml
(k)e
jφ
m
l
+ n
11
(k)
where the Gaussian noise samples n
11
(k) are white with unit variance. I
11
p
(k)isthe
interference from the pilot signal to the data signal from the same path. As mentioned
above, each user’s data and pilot codes are assumed orthogonal, and so I
11
p
(k)=0.
For the pilot-aided scheme, for fair comparison, the energy per bit E
b
will be the
sum of the pilot energy E
p
and data energy E
d
,whichmeansE
b
= E
p
+ E
d
.Inthe
following, we will denote the power in the pilot as a fraction of the power of the data
signal, and so we can write E
p
= PE
b
.
The complex symbol gain u
ml
(k) has mean
E[u
ml
(k)] =
γ
d
ml
K
K +1
and variance
σ
2
u
ml
= γ
d
ml
1
K +1
where
γ
d
ml
=
E
d
ml
N
0
and I
ml
(k) is the interference from path l of user m to path 1 of user 1, including
the interference from both the data and pilot signals. The same expression can be
obtained for the pilot fingers of the rake, but with E
p
replacing E
d
. The output of the
first finger of the first user pilot Rake will be denoted by r
11p
(k).
8.4.2 Design of Modulator and Demodulator
There are several issues that must be taken into consideration in the proper design of
a pilot-aided modulation/demodulation system.
Filter Length
The filter length is of great importance for the performance of the PAD scheme. If
the fading is very slow relative to the data rate, an averaging filter could be used; this
[...]... Geraniotis ‘Iterative Decoding and Channel Estimation of DS /CDMA over Slow Rayleigh Fading Channels’ PIMRC 98, Boston, MA, 1998 [11] M Khairy and E Geraniotis ‘Asymmetric Modulation and Multistage Coding for Multicasting with Multi-Level Reception over Fading Channels’ MILCOM 99, Atlantic City, NJ, 1999 [12] M Khairy and E Geraniotis ‘BER of DS /CDMA Using Symbol-Aided Coherent Demodulation over Rician... available Le (k), which is the extrinsic information for both the data and code bits Following the first iteration, the probability of the bits is calculated according to p(x(k) = 1) = eL(k) /(1 + eL(k) ) 200 CDMA: ACCESS AND SWITCHING and the channel estimate is adapted after every iteration according to M h(l)r1l (l + m)[2p(l + m) − 1] cl (m) = ˆ l=−M,l=0 where p(k) = 1 for known symbols The new Lcl (k)’s... different numbers CARRIER RECOVERY 201 Figure 8.2 BER in (A) Rician (K = 10), (B) Rayleigh fading and for one and six users J = 7, Jmax = 50, P = 1, N = 31, L = 1 Filter length = 31 for both schemes 202 CDMA: ACCESS AND SWITCHING of users Ku = 1, 6, and the processing gain (number of chips per symbol) is N = 31 The filters for the SAD and PAD schemes are of length 29 J = 7, P = 1/7 and Jmax = 50 It was... also shows that CARRIER RECOVERY 203 Figure 8.3 BER versus the number of users, for (A) Rician (K = 10), (B) Rayleigh fading J = 7, Jmax = 50, P = 1/7, L = 1, 4 and SNR very large Filter order = 11 204 CDMA: ACCESS AND SWITCHING Figure 8.4 BER versus the position of the unknown symbol, for different SAD filtering schemes (A) Rayleigh fading, Rs = 10 kb/s, Rf = 200 Hz, J = 20, Jmax = 25, Ku = 3, N = 31,... order = 11 CARRIER RECOVERY 205 Figure 8.5 BER versus Eb /N0 for coded signal in Rayleigh fading (A) L = 1, Ku = 6, J = 7, Jmax = 50, P = 1/7, N = 31 (B) L = 4, Ku = 1, Jmax = 50, P = 1/7, N = 31 206 CDMA: ACCESS AND SWITCHING Figure 8.6 BER versus Eb /N0 for coded signal, in Rician fading (K = 10), L = 1 (A) Ku = 1, J = 7, Jmax = 50, P = 1/7, N = 31 (B) Ku = 6, J = 7, Jmax = 50, P = 1/7, N = 31 CARRIER... RECOVERY 207 Figure 8.7 The effect of J and P on the BER for (A) Rayleigh fading, L = 1, Jmax = 50, Ku = 6, N = 31, Eb /N0 = 11 dB; (B) Rician fading, L = 1, Jmax = 50, Ku = 6, N = 31, Eb /N0 = 6 dB 208 CDMA: ACCESS AND SWITCHING the filter design is very important for fast fading Rayleigh channels, while averaging could be used for very slow Rician fading channels Figures 8.5-A, -B and 8.6-A, -B indicate... SAC-3, September 1985, pp 687–694 [2] J Cavers ‘An Analysis of Pilot Symbol Assisted Modulation for Rayleigh Fading Channels’ IEEE Trans on Vehicular Technology, Vol 40, No 4, November 1991 [3] A J Viterbi CDMA, Principles of Spread Spectrum Communications Addison-Wesley, 1995 [4] W Lee Mobile Communications Engineering, McGraw-Hill, 1982 [5] F Ling ‘Method and Apparatus for Coherent Communication in a SpreadSpectrum... system is given by Lt (dB) = Lr (dB) + Ln (dB) The optimum choice of P given Jmax can be obtained by calculating the minimum achievable loss; we can easily get Popt ≈ Lt (Jopt ) ≈ 1 Jmax 1 1+ √ Jmax 2 198 CDMA: ACCESS AND SWITCHING Note the similarity of this result to the one given for the SAD scheme Ideally, the two schemes will have the same performance The question is, in practical situations where . Recovery for
‘Sub-Coherent’ CDMA
8.1 Overview
In this chapter we examine possible methods of carrier recovery for the SE-
CDMA presented in Chapter 6 same
bit error rate as coherent demodulation. This problem is more severe in DS /CDMA
systems, which are limited by other-user interference: the additional cost
Ngày đăng: 26/01/2014, 14:20
Xem thêm: Tài liệu CDMA truy cập và chuyển mạch P8 pptx, Tài liệu CDMA truy cập và chuyển mạch P8 pptx