4.2 C HANNEL M ODEL
4.2.2 Mobile channel model
In DVB-T standard, it only provides two static channel models which is described in section 4.2.1. However, the applications in DVB-T/H systems are not only fir fix reception, but also for mobile reception. Therefore, we refer to the channel models Typical Urban 6 (TU6) and Rural Area 6 (RA6) in GSM COST 207 project [23]. The two single-transmitter
profiles come from the set defined by the COST 207 project (GSM transmission). The technical specification of COST207 describes the equipment and techniques used to measure the channel characteristics over typical bandwidths of 10~20 MHz at near 900MHz. Therefore, the COST207 profiles are applicable to the DVB-T transmission situations. The detailed value of these parameters is listed in table 4-1 and table 4-2. The Fig4.6 shows the TU6 model, the Doppler spectrum filter will introduce in next section.
Fig. 4.6 TU6 model
Table 4-1 Typical Urban Reception (TU6) channel model
Tap number Delay(us) Power(dB) Doppler spectrum
1 0 -3 Rayleigh 2 0.2 0 Rayleigh 3 0.5 -2 Rayleigh 4 1.6 -6 Rayleigh 5 2.3 -8 Rayleigh 6 5.0 -10 Rayleigh
Table 4-2 Rural Area Reception (RA6) channel model
Tap number Delay(us) Power(dB) Doppler spectrum
1 0 0 Rice
oppler spec types
Doppler
In DVB-T/H system, the reception ability in mobile environment is necessary. Hence a mobile radio channel including Doppler spread must be constructed. A simplified Doppler spread model is shown in Fig. 4.7 [24]. In the beginning, we assume a channel with a known and fixed number of paths P such as Rayleigh or Ricean with a Doppler frequency d( )k
Fig. 4.7 Doppler spread model
f ,
attenuation ρ(k)ejθ( )k , and time delay τ( )k . All the parameters are fixed as described in section 4.2.1 except the Doppler frequency. Since each path has its own Doppler frequency, the decision of the statistic distribution of f is very important. There are two commonly d sed Doppler frequency PDFs, uniform and classical, where the former exploits uniform d, and the later uses Jake’s Doppler spectrum [25],
respectively e Jak s essed as
u
distribution to model Doppler sprea
. The PDF of th e’s Doppler pread can be expr
2
After transformation of random variable, each f can be obtained by the following equation d cos(2 (1)) max
d d
f = π⋅rand ⋅f (4-5) The type of Doppler spread (uniform or Jake’s) affects the system performance enormously.
Because each path gets different f in each simulation case with different d fdmax, the value of fdmax should be fixed for each simulation and comparison.
B. Rayleigh fading
In wireless communication, the multi path effect will cause the frequency selective fading problems. If the transmitting environment is without the main direct path, according to central limit theory the amplitude will be Rayleigh distribution and the phase will be uniform distribution. So here we based on the Jake’s model to simulate the Doppler effects, in concept,
in-phase) and imaginary components of each fader are zero-mean independent Gaussian the Jake’s model will produce the complex signal with the same statistic character s [25-27].
Simulating a multipath fading channel often requires the generation of multiple independent Rayleigh faders which can be odeled as complex-valued random processes.
Ideally the Rayleigh faders should conform to the following criteria. First, the real (or istic
m
processes with identical power spectra or auto-correlation functions. As a result, the envelope is Rayleigh distributed and the phase is uniformly distributed. Second, the cross-correlation
yleigh fading waveform
deterministically or statistically. The Rayleigh Doppler spectrum generator is shown in Fig.
4.8. The Rayleigh fading Doppler spectrum is generating by Jake’s model which Doppler between any pair of faders should be zero. Ra s can be generated
frequency is 100Hz is shown in Fig. 4.9.
Fig. 4.8 Rayleigh Doppler spectrum generator
-400 -300 -200 -100 0 100 200 300 400
0 20
-20 -40 -60 -80 -100 -120
Frequency (Hz)
eensity (dPowr Spectrum D
Fig. 4.9 Rayleigh fading Doppler spectrum by jake’s model
B)
Rayleigh Fading Spectrum Doppler Frequency : 100Hz
C. Rice fading
The Rice fading spectrum is similar to Rayleigh fading spectrum, but there are one direct fects is like path between the transmitter and the receiver. This direct path with Doppler ef
pure Doppler spectrum, but the other path is similar to Rayleigh fading spectrum.
The Rice fading Doppler spectrum is generating by Jake’s model which Doppler frequency is 100Hz is shown in Fig. 4.10.
-400 -300 -200 -100 0 100 200 300 400 Doppler Frequency : 100Hz
4.2.4
The additive requency
domain is defined by :
Fig. 4.10 Rice fading Doppler spectrum by jake’s model
Additive White Gaussian Noise (AWGN)
white noise is added after multipath fading channel. The SNR in f
2
the variance of AWGN. Therefore, the signal in real part and in imaginary part should be
added AWGN which variance is : 2 2 1
discussed t of sinc
ediate value that the samp
Carrier Frequency Offset and Sampling Clock Offset model
The detailed signal model of CFO is already described in section 2.1.1 and will not be repeatedly in this section. The model of SCO is built based on the concep
interpolation. The input digital signals can be exploited to interpolate the interm between two successive samples by using the shifted value of sic function. Assume
ling period is T and SCO is s ζ . Then the sampling phase can be represented as
The performa the proposed channel estimation scheme is illustrated in this
ation algorithm in chapter 2. The 3. First, we do the channel estimator for pilot signal, cond, we do the transform domain processing finally do the interpolation process. First we ke the overall respec
nalysis
nce analysis of
section. Except the verification of the proposed algorithms, some performance or computational complexity comparison between different methods and proposed scheme will be made too. We introduced the proposed channel estim
proposed scheme is depicted in Fig. 2.
se
discuss the interpolation process result, then discuss each block finally ma
syste
4.3.1 Interpolati
After interpolation in tim ts, we can get estimated CFR every three subcarriers. lation results to verify the algorithm
ic channel (Gaussian, Ricean , Rayleigh) which cified in DVB-T standard [3] to compare the MSE results. Here we use the MSE
he frequency interpolators.
m performance. The simulation environment is 2k mode, GI=1/4, 64-Qam, code rate=2/3.
A good compromise between bandwidth efficiency and robustness is 64-QAM with code rate 2/3 (mode used in UK). Furthermore, the performance of the overall system is based on the quasi-error free. The quasi-error free (QEF) condition which is corresponds to 2x10-4 BER after Viterbi decoder will be the system erformance target. p
on in frequency domain
e domain between scattered pilo Here we will make simu
mentioned in section 2.5.2.
Fig.4.11~Fig.4.13 are the simulation results of the different interpolation methods under different channel condition. First we use stat
are spe
criterion to discuss the performance of t
0 10 20 30 40 50
100 Gaussian channel awgn only
SNR(dB)
Fig. 4.11 MSE of different frequency interpolator in Gaussian channel
0 10 20 30 40 50 10-6
10-5 10-4 10-3 10-2 10-1
100 Ricean channel awgn only
SNR(dB)
MSE
Cubic interpolator Linear interpolator Parabolic interpolator Average interpolator Second-order interpolator
44 45 46 47 48 49 50
10-5
Ricean channel awgn only
SNR(dB)
MSE
Cubic interpolator Linear interpolator Parabolic interpolator Average interpolator Second-order interpolator
Crossover point
Fig. 4.12 MSE of different frequency interpolator in Ricean channel
0 10 20 30 40 50 10-6
10-5 10-4 10-3 10-2 10-1 100
101 Rayleigh channel awgn only
SNR(dB)
MSE
Cubic interpolator Linear interpolator Parabolic interpolator Average interpolator Second-order interpolator
37 38 39 40 41 42 43 44 45
10-4
Rayleigh channel awgn only
SNR(dB)
MSE
Cubic interpolator Linear interpolator Parabolic interpolator Average interpolator Second-order interpolator
Crossover point
Fig. 4.13 MSE of different frequency interpolator in Rayleigh channel
Here, we define the MSE is the sum of MSE expectation at all subcarriers which is expressed
where N is the total number of subcarriers. Here we use 2k mode for explanation, in 2k mode we can get estimated CFR every three subcarriers after time interpolation. So there are on 1705 subcarriers and 569 (1705/3) subcarrier is estimated by time interpolation. Here they are the same in every interpolation methods which MSE is the _
k p
In Gaussian channel, the CFR is only effect by AWGN noise. Furthermore, the CFR is the same at every subcarrier (Hk = ), so we can use this AWGN to verify the noise term effects 1 in different interpolation method. From equation (2-21), the MSE can be reduced to (4-9).
2 2
∑ ∑ ∑
are zero in each interpolation methodswhich are listed in Table 2-3. So the MSE of each subcarrier becomes to (4-10).
2 2 2
{| k | } ( ) [ ]
j
MSE E H H= − =
∑
Cj E Nj (4-10) So the MSE of Linear interpolation is expressed by2 2 2
_ _ ( )
569 ( ) 1136 0.5555 ( ) 1200 ( )
k k
k p k p
MSE linear VAR sample E H H
E N E N E N
The MSE of cubic interpolation is expressed by
2 2 2
and cubic interpolation is 0.52dB. (4-13) So the gap between linear interpolation
10
find there are only AWGN noise effects, so there is no cro igh SNR
t
NR
almost the same in each frequency interpolator. In Ricean, Rayleigh, TU6 channel model, we 1200
1200 1355.2
(4-13)
In Fig. 4.11, we can find the simulation results can be proven the noise effects will enhanced by different interpolation methods, which is mentioned in section 2.5.2. In Fig. 4.11 we will
region. The performance is AVG > Linear > Cubic > Second-order > Parabolic.
ssover point, even at h
In the other channel types we can still use the MSE criteria to calculate the cross poin between linear and cubic interpolation methods. From simulation results, we can find the crossover point is at about SNR=46.5dB in Ricean channel (Fig. 4.12), and at about SNR=38.5 dB in Rayleigh channel (Fig. 4.13). The crossover points are all in the high S region, but the system requirement QEF are about less than 30dB [3]. Fig. 4.14 is the simulation results under dynamic channel environments. We can find the uncoded BER are
can find the linear interpolator is the best.
So the Linear ection is the proper choice than the other interpolation methods which mentioned in section 2.5.2.
interpolation in frequency dir
14 16 18 20 22 24 26 28 30 10-1
10-2
Different Frequency Interpolator
E R
Linear interpolator Cubic interpolator
r Second-order interpolato Parabolic interpolator
unc oded B
SNR(dB) TU6 model
Code rate 1/2
els. In Fig.4.15 we use 2k mode, 64Qam, GI=1/4 and D
er TU6 channel. The solid line is the linear interpolation method, and the dashed line is the 1st-order extrapolation methods which are mentioned in section 2.5.1. Furthermore, the BER performance achievement is based on the uncoded BER equal to 10-2.
From the simulation results we can find the 1st order extrapolation is much worse than linear interpolation method, although 1st order extrapolation can save large memory for three OFDM symbols. Cost is trade off to the performance. Table 4-3 and Table 4-4 show that the
Doppler freq. 60Hz Constellation 16Qam Guard interval ratio 1/4
Fig. 4.14 Comparison different frequency interpolator in dynamic channel
4.3.2 Interpolation in time domain
Fig. 4.15 ~ Fig. 4.16 are the simulation results of different time interpolators under different Doppler effects and channel mod
oppler frequency are 0, 50, 70 Hz under Rayleigh channel. In Fig.4.16 we use 2k mode, 16Qam, GI=1/4 and Doppler frequency are 60, 90 Hz und
1st order extrapolation equalizers can tolerant Doppler frequency 60Hz under dynamic channel. Though 2.5dB to 5dB SNR losses compared with linear interpolators, but 78%
storage can be saved by using 1st-order extrapolation.
We can find the performance is much sensitive to the interpolation in time directions.
However, for mobile reception, we still propose the linear interpolation in time direction.
22 24 26 28 30 32 34
10-3 10-1
10-2
Time domain interpolator
unc oded B E R
Linear without doppler 1st-order without doppler Linear with doppler=50Hz 1st-order with doppler=50Hz Linear with doppler=70Hz 1st-order with doppler=70Hz
SNR(dB) Rayleigh channel
Doppler frequency: 0, 50, 70 Hz m
code rate = 2/3
Time interpolator Doppler range SNR loss * Storage requirements(2K)
Constellation : 64 Qa Guard interval: 1/4
Fig. 4.15 Different time interpolator under Rayleigh channel
Table 4-3 Comparison on performance and cost under Rayleigh channel model
1 -order st 60 2.5 dB@55Hz 1138 carriers
Linear >80 0dB 5115 carriers
(* compared with linear interpolator)
10 15 20 25 30 35
Doppler frequency: 60, 90 Hz Constellation : 16 Qam code rate = 1/2 Guard interval: 1/4
Fig. 4.16 Different time interpolator under TU6 channel
Table 4-4 Comparison on performance and cost under TU6 channel model
Time interpolator Doppler range SNR loss * Storage requirements(2K)
1st-order 60 6 dB@60Hz 1138 carriers
Linear >90 0dB 5115 carriers
(* compared with linear interpolator)
4 do ing
In section 2.4 we use transform domain processing to implement lter [11].
The tra domain proce is depicted in Fig. 2.11. There are an M-point FFT, and
c. In fact, we can do the transform domain processing .3.3 Transform main process
the low pass fi
nsform ssing
need to decide the cutoff frequency p
after interpolation in time direction, so we can get better accuracy. In 2K mode, there are only 142 (1705/12) CFR for scatter pilots, and we can get 568 (1705/3) after interpolation in time direction. So the resolution is increasing, but more point FFT we need.
Furthermore, the cutoff frequency pc of the transform domain low-pass filter is an important parameter that affects the accuracy of the channel estimation. Therefore the pc can be determined from (2-13). The energy ratio R is suggested by [11],R∈
[
0.9,0.95]
.Fig. 4.17 shows the simulation results of differentR∈
[
0.8,0.85,0.9,0.95]
under static channel, and Fig. 4.18 shows the simulation results under dynamic channel. Here we can find the best performance is R=0.9 and it can get 0.25 dB in static channel and 0.2dB in dynamic channel. However, it needs a 568 point FFT and IFFT in 2K mode, but the hardware cost is very high. So this method is not efficient in DVB-T/H systems.24 25 26 27 28 29 30
10-2
Different R to decide Pc
unc oded B
R=0.95 R=0.9
=0.85 0.8 without R R=
E R
0
SNR(dB)
.25dB
Constellation: 64Qam Code rate: 2/3
Guard interval: 1/4 Rayleigh channel
Fig. 4.17 Performance between different R under Rayleigh channel
18 20 22 24 26 28 30 32 10-2
SNR(dB)
unc oded B E R
Different R to decide the Pc
R=0.95
Fig. 4.18 Performance between different R under TU6 channel
4.3.4 Channel estimator for pilot signal
We proposed an adaptive channel estimator for pilot signal in section 2.3. The adaptive weights for estimator in (2-8) are based on MSE criterion in (2-9). Here, we based on the low hardware cost issue, so we assume the weights β∈{0,0.25,0.5,0.75} four kinds. In equation (2-9), we rewrite it again in (4-14). There are two parameters E(D2) and E(N2/X2) are estimated roughly by a simple algorithm, and the implementation methods are described in next Chapter 5.2.
In this section, we show the simulation results between fixed weights [14-16] and
proposed estimator with adaptive 4 kinds of weightsβ∈{0,0.25,0.5,0.75}. We list the simulation results of static channel and dynamic channel under different frequency effects on table 4-5. Furthermore, Fig. 4.19.~Fig.4.21. show the performance between different β. We can find the β=0.75 is the best choice in static channel without Doppler effects. As Doppler increasing, the time dependency of channel is less, so the performance will be better with lower β. However, the channel can’t be static, so if we fix β to some value, we can find that, when channel with high Doppler frequency effects, the performance will degrade seriously.
But in proposed adaptive β estimator, it will let β equal to zero which only use the current symbol information without the previous symbol information. Therefore, it will not to degrade the performance when channel with high Doppler effects.
From simulation results, we can find the proposed estimator could select the proper β at each subcarrier. Here, we will show the performance of the overall system. We list the required SNR for QEF condition which corresponds to 2x10-4 BER after Viterbi decoder. We
can find in the proposed estim d
d = 150 Hz under TU6 channel.
method can gain 0.3dB in Ricean channel under Doppler frequency 30 Hz, 0.2 dB in Ra
frequency effects environm
ator method we can achieve f = 70 Hz under Rayleigh channel and f
From table 4-5, we can find the proposed
yleigh channel under Doppler frequency 10 Hz, and 0.2dB in TU6 under Doppler frequency 60 Hz. So the proposed adaptive estimator can get a little improvement under middle Doppler ent, it can’t degrade the performance in high Doppler frequency effects.
14 15 16 17 18 19 20
Fig. 4.19(a) Performance under static Ricean channel
16 17 18 19 20 21 22
0 Ricean with Doppler 70Hz
10 b=0
Fig. 4.19(b) Performance under Ricean channel with 70Hz Doppler
22 23 24 25 26 27 28
Fig. 4.20(a) Performance under static Rayleigh channel
22 24 26 28 30 32
Rayleigh with Doppler 70Hz
Rayleigh channel Doppler frequency: 70 Hz Constellation : 64 Qam code rate = 2/3 Guard interval: 1/4
Fig. 4.20(b) Performance under Rayleigh channel with 70Hz Doppler
11 12 13 14 15 16 17
Fig. 4.21(a) Performance under TU6 channel with 10Hz Doppler
14 14.5 15 15.5 16 16.5 17 17.5 18
Fig. 4.21(b) Performance under TU6 channel with 30Hz Doppler
14 16 18 20 22 24 10-5
10-4 10-3 10-2 10-1
100 Dynamic channel
SNR(dB)
BER
b=0 b=0.25 b=0.5 b=0.75 adaptive b
TU6 channel model Doppler frequency: 150 Hz Constellation : 16 Qam code rate = 1/2 Guard interval: 1/4
Fig. 4.21(c) Performance under TU6 channel with 150Hz Doppler
Table 4-5(a) Comparison on performance between different β
Ricean channel with different Doppler effects: 2K mode, 64Qam, code rate=2/3, GI=1/4 required SNR (dB) for BER=2x10-4 after Viterbi
Doppler(Hz) β=0 β=0.25 Β=0.5 β=0.75 Adaptive β Gain (*)
0 18.5 18.35 18.15 18.05 18.1 0.4
10 19.15 18.8 18.75 18.85 18.75 0.4
30 19.62 19.38 19.45 22.2 19.32 0.3
50 20.14 21.5 NA NA 20.14 0
70 20.5 20.9 NA NA 20.5 0
(* compared to β=0 , NA : can’t achieve BER=2x10-4)
Table 4-5(b) Comparison on performance between different β
Rayleigh channel with different Doppler effects: 2K mode, 64Qam, code rate=2/3, GI required SNR (dB) for BER=2x10-4 after Viterbi
=1/4
Doppler(Hz) β=0 β=0.25 β=0.5 β=0.75 Adaptive β Gain (*)
0 25.95 25.5 25.3 25.2 25.25 0.7
10 28.2 28 NA NA 28 0.2
30 29 40 NA NA 29 0
50 29.65 NA NA NA 29.65 0
70 31.5 NA NA NA 31.5 0
(* compared to β=0 , NA : can’t achieve BER=2x10-4)
Table 4-5(c) Comparison on performance between different β
Dynamic channel (TU6) with different Doppler effects: 2K mode, 16Qam, code rate=1/2, GI=1/4 required SNR (dB) for BER=2x10-4 after Viterbi
Doppler(Hz) β=0 β=0.25 β=0.5 β=0.75 Adaptive β Gain (*)
10 16.2 15.7 15.8 15.95 15.7 0.5
30 16.55 16.45 16. 3 16.4 16.3 0.25
60 18.2 18 NA NA 18 0.2
90 18.5 19.4 NA NA 18.5 0
150 21 NA NA NA 21 0
(* compared to β=0 , NA : can’t achieve BER=2x10-4)
Chapter 5 .
tu and lem ati
In this chapter, the platform based design m dology w e introdu first. Then the archi re of the i emented DVB-T/H receiver will be illustrated. The architecture of the propo channel er desig rdware esis info on and chip summary will be shown in the following sections.
.1 Design Methodology
The trend . System-level
si
system simulation First, the system
hann dals s estab ccor e s ic
MATLAB languag ich ensu e desig he prac ndition rithm research and architecture development o unctio should rified i ystem p m to en the whol tem perf ance. Fix int simu n is applied before hardware imple tation to the tr f between system performance and hardware cost. In hardware impleme on, the og HDL dules ar ified with the test benches re the correctness. Finally, once the erification between HDL modules and fixed-point MATLAB platform is finished, the HDL ased platform will be synthesized and translated to circuit level by place and route (P&R)
ols.
Architec re Imp ent on
etho ill b ced
tectu mpl
sed equaliz n, ha synth rmati
5
of IC technology is towards to System-on-Chip (SoC)
mulation becomes very important in today’s design flow. Our design methodology from to hardware implementation can be shown in Fig. 5.1.
platform and c el mo hould be lished a ding to th ystem specif ation with
e, wh res th n in t tical co . Algo
f each f n block be ve n the s latfor
sure e sys orm ed-po latio
men make ade-of
ntati Veril mo e ver
dumped from the equivalent Matlab blocks to ensu v
b to
Fig. 5.1 Platform-based design methodology
5.2 Architecture of the DVB-T/H Baseband Receiver[28]
Based on the 2x1D linear interpolation channel estimation scheme and other low power designs such as high speed FEC decoder and dynamic scheduling FFT processor [29], a DVB-T/H baseband receiver is implemented and tapped out in Jun. 2005. The detailed structure in OFDM demodulator is shown in Fig.5.2. In the initial phase, the timing synchronizer estimates Operation Mode (2K/4K/8K), Guard Interval length, and symbol boundary with auto-correlation and power detection. Then the received signal is sent to FFT and the CFO integer is estimated with a monitor of frequency-domain signal drift. The FFT is realized with radix-8 butterfly units, a dynamic wordlength-scaling (DWC) method, and a cache-based architecture to provide 2K/4K/8K modes with less memory power. After FFT
operation, both tim a 2D linear EQ. The
sym
QAM soft-dem
of DVB-T/ es of the
original da erent channel
bandwidths will co
e that the implem
result is se
μm CMOS
table 5-1. A ing clocks with the
frequency division method. In
es 250mW power for the highest data rate 31.67Mb/s with 70Hz Doppler frequency tolerance.
e-variant CFR and CFO are estimated and tracked by
equalized signal is sent to symbol deinterleaver. Different from the general approaches, the bol interleaving is done before QAM demapping. That is because the developed 64-level apping is designed with a 24-bit input and a 36-bit output to achieve low BER H. After the de-QAM constellation, the clock rate is raised up to six tim
ta rate to satisfy the bit-level calculation. In DVB-T/H system, diff
rrespond to different clock rates. The highest clock rate of the received data is about 9MHz when the 8MHz channel bandwidth is utilized. In order to assur
ented chip can work in such condition properly, the basic clock rate of the synthesis t at 11MHz.
Power profiling and die photo of the proposal implemented in standard 0.18
process is shown in Fig.5.3 and Fig.5.4 respectively. Furthermore, chip summary is listed in 109.71MHz system clock is referenced to provide the work
tegrating OFDM demodulator and FEC designs, the proposed
tegrating OFDM demodulator and FEC designs, the proposed