2.4 S AMPLING C LOCK O FFSET S YNCHRONIZATION
2.4.4 Proposed Tracking Loop
The principle of proposed SCO tracking architecture is to add a feedback forward path in the SCO estimation loop. It is shown as Fig 2.27. The feedback forward architecture is to extract the previous two SCO estimation values after loop filter and then through some simple
transformation execution, the estimation values would change to become the phase information. Finally, do the phase compensation to the phase difference between continual pilots of two f-domain symbols that were not resample-modified at t-domain. As we compensate the phase forward, we would not wait for the FFT process latency, and we will improve the throughput of SCO tracking outcome. The timing diagram is shown in Fig. 2.28.
Like the conventional design, the same color means the same resample-modified symbol, in other words, the same color means the same effect of SCO. We can obviously see the f-domain symbol is modified. The throughput becomes one symbol. The phase compensated equation is:
( ) 2 (1k Ng/ )N k
ϕ = π + × (2-25) ζ where d means the estimated outcome of SCO after loop filter, ϕ( )k means the phase compensation, and k means continual pilot index.
1 2 1π⎛⎜⎝ +N Ng/ ⎞⎟⎠
2 1 g/ ki⋅ π⎛⎜⎝ +N N⎞⎟⎠
Fig 2.27 the architecture of proposed SCO tracking loop
1 2 3
Fig 2.28 timing diagram of proposed SCO tracking loop architecture
Now, we choose proposed SCO estimation algorithm, scatter pilot method, to replace the conventional algorithm. The architecture is shown in Fig 2.29, and the timing diagram is shown in Fig 2.30. The phase compensation equation is:
( ) 2 (1k Ng/ ) 4N k
ϕ = π + ⋅ × (2-30) ζ Where d means the estimated outcome of SCO after loop filter, ϕ( )k means the phase compensation, and k means scatter pilot index. In section 2.4.1, we mentioned about the problem of the throughput of SP method. The throughput of the estimation outcome is high to six symbols, and five symbols for waiting for the scatter pilot location and one symbol for FFT process. In this section we will no longer see the problem because of the feedback forward path. The feedback forward path can add in any kind of algorithm and also can solve some problem like low throughput. Hence, this proposed architecture can combine with all other estimation algorithms.
1 4 2 1× π⎛⎜⎝ +N Ng/ ⎞⎟⎠
4 2 1 g/ ki⋅ × π⎛⎜⎝ +N N⎞⎟⎠
Fig 2.29 the architecture of proposed SCO tracking loop with SP method
1 2 3
FFT_in FFT_process
4 5 6 7 8 9
1 2 3 4 5 6 7 8
ζ15 Phase compensated
current 1 2 3 4 5 6 7 8
1 2 3 4
Phase compensated Previous 4
ζ37 ζ26
Fig 2.30 timing diagram of proposed SCO tracking loop architecture with SP method
In the comparison and results, first, we will show the estimation accuracy of proposed estimation algorithm and then we will show the improving throughput in proposed tracking loop architecture.
Chapter 3 .
Simulation and Performance Analysis
3.1 Simulation Platform
In order to verify the performance of proposed algorithm, a complete DVB-T baseband simulation platform is developed in Matlab. The block diagram of DVB-T simulation platform is depicted in Fig 3.1.
De-Inner
Fig 3.1 Block diagram of simulation platform
The platform consists of transmitter, channel and receiver. A typical transmitter receiving video data from MPEG2 encoder is fully established. Besides FEC blocks, constellation mapping, pilot insertion, IFFT modulation and GI insertion are built in order.
The 2K and 8K with all other transmission modes are able to being selected as simulation parameters. In order to simulate discrete signal as far as continuously, upsampling and pulse shaping filter are adopted prior to entering channel. The upsampling rate is flexible and depends on the required simulation accuracy. The roll-off factor of pulse-shaping filter is not defined in ETSI DVB-T/H standard so that a normal value of α=0.15 is used. In the channel model, various channel distortions are introduced for simulating real mobile wireless environment, which contains multipath fading, Doppler frequency spread, AWGN, CFO and SCO. In fact, there are some other distortions such as co-channel interference, adjacent-channel interference and common phase error due to defective front-end receiving.
However, these distortions are relatively small compared to effective time-variant channel response caused by Doppler spread, CFO and SCO, so that we can neglect those channel effects.
Inner Receiver De-mappingDe-mapping FECFEC Outer Receiver
Tuner VGAVGA ADCADC
DVB-T Digital Baseband Receiver Analog
RF
AGCAGC DACDAC
Fig 3.2 Overview of receiver design
In the receiver design, we focus on the baseband demodulation part between ADC and MPEG-2 decoder. The receiver can be divided into two portions, inner and outer receiver as
depicted in Fig 3.2. Inner receiver copes with pre-FFT synchronization, FFT, post-FFT frequency synchronization, channel estimation and pilot removal. Then TPS check, de-mapping, inner de-interleaver, Viterbi decoder, outer de-interleaver, RS decoder and de-scrambler are done in outer receiver. The transmission parameters computed by TPS decoder such as constellation mapping and code rate of Viterbi send to downstream blocks in outer receiver. Afterwards, the bitwise output of FEC blocks enters to source decoding block, MPEG-2 decoder. Note the TPS check should operate all the time to prevent transmission interruption. If TPS check error occurs, the inner receiver ought to reset and hence all blocks in acquisition mode restart. As for BER measurement, the quasi error-free condition is defined in ETSI standard [3] which means less than one uncorrected error event per hour, corresponding 10-11 after Reed-Solomon decoder and 2×10-4 after Viterbi decoder. Therefore, the BER should be measured both in the outputs of Viterbi and RS. In particular, the SER (symbol error rate) is usually applied as another performance measurement in several papers.
As a result, we should exploit hard-decision demapping to measure SER in addition.
^
Fig 3.3 Structure of inner receiver
In Fig 3.3, it shows the detail structure of inner receiver. As mentioned in Chapter 2, synchronization task consists of symbol synchronization, frequency synchronization and sampling clock synchronization. Acquisition blocks operate in the initial synchronization period and turn off in tracking mode, and tracking blocks act all the while. Our frequency synchronization design consults reference [1]. Like coarse symbol synchronization, pre-FFT frequency acquisition is based on guard interval correlation. Disregarding ISI and sampling timing error, the tail received sample and its cyclic prefix show the same property except for a phase rotation between guard and tail segments being proportional to the fractional carrier frequency offset. Guard interval correlation samples thus become
* j2 f
n n n N
x = ×r r− ∝e πΔ +noise (3-1) Given the coarse estimated symbol window ˆn, the ML frequency estimate [11] becomes
ˆ * where x denote the forsaken samples distorted by ISI in multipath channel. Since the perfect coarse symbol window is impossible, we have to consider the ISI samples. In severe multipath fading channel as Rayleigh channel in DVB-T standard, long time delay profile raises the ISI effect which is illustrated in Fig 3.4. As a result, we must give up several beginning samples to reduce the ISI distortion. However, discarding too many samples will also degrade the averaging performance. The optimal value of x can be decided by simulation result.
Fig 3.4 ISI effect on CFO acquisition
Post-FFT integer carrier frequency acquisition refers to [1]. Because of pre-FFT acquisition, the residual fractional offset Δf is small so that the ICI noise in this stage is also small. We assume the integer carrier frequency offset nI (subcarrier spacing), which causes spectrum shift in frequency domain. The integer CFO must now be detected using continual pilots which are all boosted in power. Correlating FFT output samples of two consecutive OFDM symbols l-1, l and a particular set k C m∈ + are accumulated. The maximum absolute value of accumulation result then yields the estimated integer carrier frequency offset
*
, 1,
ˆI arg max l k l k
m I k C m
n z z −
∈ ∈ +
=
∑
⋅ (3-3) where C denotes the positions of continual pilots and I represents the search range which is typical given by [-nI,max, nI,max ]. Considering small offset Δf and ζ, the probability of false detection ( ˆnI ≠ ) is very small. The channel estimation unit must estimate both the channel nI response and any residual phase errors caused by imperfect synchronization. In the channel estimation design of DVB-T system, it is common to use two-dimensional interpolation method such as [1] in order to estimate the mobile time-variant channel. The channel response is generated by interpolation in time and frequency dimension respectively. In time direction, channel gain estimates at scattered pilot are first interpolated so that channel gain estimates are available at every third subcarrier in every OFDM symbol as depicted in Fig 3.5.Subsequently, channel response estimates at all other subcarriers are obtained by interpolating
the resulting time-interpolated channel gain in frequency direction. In time-dimension interpolation, four complete OFDM symbols have to be stored for each noncausal tap.
Considering the memory requirement, interpolation in time dimension exploits linear interpolation so that only the storage of three additional OFDM symbols is needed. As for frequency-dimension interpolation, it is general to adopt Wiener filter approach. In general, the high-complexity frequency direction interpolation deserves since the system performance is usually dominated in channel estimation unit.
Fig 3.5 2-D interpolation in channel estimation unit design
3.2 Channel Model
⊕
⊗
2 j ft
e
πΔ (1+ζ)fsFig 3.6 Channel model of DVB-T/H system
Fig 3.6 shows the typical baseband equivalent channel model of DVB-T system. The transmitted data passes through multipath fading, Doppler spread, AWGN, RF lowpass filter,
carrier frequency offset and sampling clock offset. The effects of inter-channel interference (co- and adjacent-channel interference) and common phase error are neglected in our simulation. In fact, the overall system performance represented as “BER versus SNR” shows nearly no difference. The detail illustration of each channel distortions will be shown in the following sections.
3.2.1 Multipath Fading Channel Model
In the wireless transmission, transmitted data is received through several paths with different time delay and power decay. This is so-called multipath fading. Two types of channel are specified by ETSI DVB-T standard. Fixed reception condition is modeled by Ricean channel (Ricean factor = 10db) while portable reception is modeled by Rayleigh channel. The full 20-tap Ricean and Rayleigh channel was used with floating point tap magnitude and phase values and with tap delay accuracies rounded to within 1/2 of duration (7/64 μs/2) for practical discrete simulation.
The major difference between Rayleigh and Ricean channel is the main path (The line of sight ray). In a Rayleigh fading channel, the received signals consist of several reflected signals with similar powers because there is no main path in Rayleigh channel. The rms delay of Rayleigh channel is about 12 sample time. This characteristic will cause serious synchronization error. A time delay and subcarrier distortion of frequency domain both occur in a Rayleigh fading channel. The frequency response and impulse response for each subcarrier are shown in Fig 3.7. The frequency response is not flat over the entire frequency region and some parts are severely distorted. The Ricean channel model defines Ricean factor K (the ration of the power of the direct path to the reflected paths) is given as
2
where ρι is the attenuation of the i’th path. The channel models can be generated from the
following equation where x(t) and y(t) are input and output signals respectively
where N is the number of echoes equals to 20, θi is the phase shift from scattering of the i’th path and τι is the relative delay of the i-th path. The detail value of above parameters is listed in table B.1 of [1]. The rms delay of Ricean channel (k=10db) and Rayleigh channel is respectively 0.4491 μs (about 4 samples) and 1.4426 μs (about 13 samples). The channel impulse response and channel frequency response of Ricean channel (K=10db) and Rayleigh channel are shown in Fig 3.7 respectively.
0 10 20 30 40 50
0 200 400 600 800 1000 1200 1400 1600 1800 0
(a) Impulse response of Rayleigh channel (b) Frequency response of Rayleigh channel
0 10 20 30 40 50
0 200 400 600 800 1000 1200 1400 1600 1800
0.3
(c) Impulse response of Ricean channel (d) Frequency response of Ricean channel Fig 3.7 Channel response of Rayleigh and Ricean (K=10dB) channel
In addition to Rayleigh and Ricean channel, a statistical channel model WSSUS (Wide Sense Stationary Uncorrelated Scattering) [12] is adopted in our simulation. The power delay profile is measured in two different areas in Germany (Berlin and Darmstadt) with a system bandwidth of 8 MHz and at carrier frequencies of 714 and 920 MHz. We can regard this channel model as a real case of transmission environment. WSSUS channel model provides several type of channel model which contains Non Line Of Sight (NLOS) –models and Type K (TypK)-models. NLOS models have a very small Rice factor ( K ≤ -20 db ) and TypK models have a Rice factor around the 50% of its model category. The detail descriptions of each channel model have been discussed in [12].
3.2.2 Doppler Spread Model
Delay Attenuation CFO SCO AWGN
Fig 3.8 Doppler frequency spread model
It’s well known that Doppler spread causes the loss of orthogonality in OFDM system. In DVB-T system, a mobile radio channel including Doppler spread must be considered. A simplified Doppler frequency spread model [13] is depicted in Fig 3.8. First, we initially assume a channel with a known and fixed number of paths P such as Ricean, Rayleigh or WSSUS with a
Doppler frequency fd( )k , attenuation ρ( )k ejθ( )k , and time delay τ(k) . Every path has different amplitude, Doppler frequency, and time delay. Since each path has its own Doppler frequency, how to decide the statistical distribution for fd is important. There are two commonly used Doppler frequency PDFs, uniform and classical. Obviously uniform case uses uniform distribution to model Doppler spread, and classical case uses Jakes’ Doppler spectrum.
In some papers, a worst case of two-side Doppler spectrum is exploited, which shifts in frequency each even-indexed channel tap by +fd, and each odd-indexed channel tap by -fd. When we compare the performance with other papers, we should pay attention to the definition of Doppler Spectrum. The PDF of Jakes’ Doppler spectrum [18] is derived as below.
2
cos(2 (1)) max
d d
f = π⋅rand ⋅f (3-8) The type of Doppler spread (uniform or Jakes’) affects the performance very much. Because each path gets different fd in each simulation case, the amount of the lost orthogonality will be not the same. Therefore, we should fix each fd in each simulation and comparison.
3.2.3 Carrier Frequency Offset and Sampling Clock Offset model
The detailed signal model of CFO is already described in chapter 2 and will not be discussed repeatedly in this section. The model of SCO is built based on the concept of sinc interpolation. The input digital signals can be exploited to interpolate the intermediate value between two successive samples by using the shifted value of sic function. Assume that the sampling period is T and SCO is s ζ . Then the sampling phase can be represented as
3.3 Performance Analysis
3.3.1 Carrier Phase Alignment
In the analysis of carrier phase alignment, we divide into three parts: BER after Viterbi versus SNR in different frequencies of fine symbol synchronization, BER after Viterbi versus the tolerance of different SCO in the same channel model and BER after Viterbi versus different Doppler frequency with other channel parameter fixed.
In the first analysis, BER after Viterbi versus SNR in different frequencies of fine symbol synchronization is discussed. First, we introduce the simulation environment. The transmission mode is 2k mode, GI 1/4, 64-QAM mapping, code rate 2/3, sampling rate 2, alpha 1 and hierarchical false. The channel model is AWGN, Rayleigh multi-path, Doppler 70Hz and SCO 20ppm. Transmission mode and channel model are reference from [3], the ETSI-DVB-T/H standard. In the receiver, we choose channel equalizer in 2-D linear interpolation [8], fine symbol synchronization in IFFT based method [2], SCO tracking in LLS algorithm [9] with loop filter [14] and resampler [15]. In Fig 3.9 and Fig 3.10, it shows the BER after Viterbi versus SNR between with and without proposed architecture. It shows one fine tune in every 8 symbols and 64 symbols in Fig 3.9 and Fig 3.10, respectively.
Fig 3.9 BER vs SNR after Viterbi decoder with one fine tune every 8 symbol
Fig 3.10 BER vs SNR after Viterbi decoder with one fine tune every 64 symbol
In Fig 3.9 and Fig 3.10, we can observe that with proposed design, the performance is much better than without proposed design. And no matter how many symbol cycles with the fine symbol synchronization. In Fig.11, BER after Viterbi versus the tolerance of different SCO in the same channel model is shown. The channel model is 2k mode, GI 1/4, 64-QAM mapping, code rate 2/3, sampling rate 2, alpha 1 and hierarchical false. The channel model is AWGN, Rayleigh multi-path, Doppler 70Hz and SNR 34dB.
Fig 3.11 Tolerance range of SCO @ Rayleigh, SNR=34dB, and Doppler 70Hz
In Fig 3.11 it shows the tolerance of SCO. The required performance, Quasi Error Free (QEF) criterion, is BER = 2×10-4 after Viterbi decoder. And we can observe only our proposed design can reach QEF in worst channel.
BER after Viterbi versus different Doppler frequency with other channel parameter fixed is shown in Fig 3.12. The transmission is 2k mode, GI 1/4, 64-QAM mapping, code rate 2/3, sampling rate 2, alpha 1 and hierarchical false. The channel model is AWGN, Rayleigh multi-path, SNR 34dB and SCO 20ppm. Transmission mode and channel model are reference from [3], the ETSI-DVB-T/H standard. In the receiver, we choose channel equalizer in 2-D linear interpolation [8], fine symbol synchronization in IFFT based method [2], SCO tracking in LLS algorithm [9] with loop filter [14] and resampler [15].
Fig 3.12 BER after Viterbi vs Doppler frequency
3.3.2 Fast Synchronization
The proposed method would not improve the accuracy of synchronization but the synchronization time could definitely be reduced. TPS decoder costs from 135 to 85 symbols time for synchronization. RS packet synchronization time is from 272/136/68 symbols to 5/3/2 symbols in 2k/4k/8k mode. One solution of the synchronization time is (acquisition time + TPS decoded time +RS packet synchronization time). The total results of this proposed system design reduce the synchronization time from 417/281/213 symbols to 100/98/97 symbols. Table 3-1, Table 3-2, Table 3-3 and Table 3-4 shows the synchronization time (ms) in 8MHz, 7MHz, 6MHz and 5MHz channel respectively.
Table 3-1 Synchronization time (ms) in 8 MHz channel
2k mode 4k mode 8k mode
GI 1/4 1/8 1/16 1/32 1/4 1/8 1/16 1/32 1/4 1/8 1/16 1/32 Conventional 116.8 105.1 99.2 96.3 157.4 141.6 133.8 129.8 238.6 214.7 202.8 196.8 Proposed 28 25.2 23.8 23.1 54.9 49.4 46.7 45.3 108.8 99.8 92.3 89.6
Table 3-2 Synchronization time (ms) in 7 MHz channel
2k mode 4k mode 8k mode
GI 1/4 1/8 1/16 1/32 1/4 1/8 1/16 1/32 1/4 1/8 1/16 1/32 Conventional 133.4 120.1 113.4 110.1 179.8 161.9 152.9 148.4 272.6 245.4 231.7 224.9 Proposed 32 28.8 27.2 26.4 62.7 56.5 53.3 51.7 124.2 111.7 105.5 102.4
Table 3-3 Synchronization time (ms) in 6 MHz channel
2k mode 4k mode 8k mode
GI 1/4 1/8 1/16 1/32 1/4 1/8 1/16 1/32 1/4 1/8 1/16 1/32 Conventional 155.7 140.1 132.3 128.4 209.8 188.8 178.3 173.1 318.1 286.3 270.3 262.4 Proposed 37.3 33.6 31.7 30.8 73.2 65.7 62.2 60.4 144.8 130.4 123.1 119.5
Table 3-4 Synchronization time (ms) in 5 MHz channel
2k mode 4k mode 8k mode
GI 1/4 1/8 1/16 1/32 1/4 1/8 1/16 1/32 1/4 1/8 1/16 1/32 Conventional 186.8 168.1 158.8 154.1 251.8 226.6 214 207.7 381.7 343.5 324.4 314.9 Proposed 44.8 40.3 38.1 36.9 87.8 79 74.7 72.4 173.8 156.4 147.8 143.4
We can see the different synchronization times in different transmission modes, and then we can choose one couple of them to calculate the saving of power consumption from (1-6).
We can obtain different power savings in different modes. For instance, in 5MHz channel, 4k mode and GI 1/4, the conventional method costs 251.8ms and proposed method costs 87.8ms.
According to chapter 1, let Burst Duration be 200ms, Delta-t Jitter be 10ms Constant Bandwidth be 512kbps and Burst Size be 1024kbits. Thus, we can obtain the conventional saving of power consumption is 78%, and the proposed method obtains 86% power saving. In this example, the saving power is up to 8%. The proposed method of fast synchronization in DVB- H system saves 65% to 95% power consumption than in DVB-T system. And the proposed design averagely reduces 10% power consumption than conventional design.
3.3.3 Sampling Clock Synchronization
In this section, we will show two kinds of simulation result. One is the SCO estimation algorithm, and the other is SCO tracking loop architecture. These two topics show different results respectively. SCO estimation shows the estimation accuracy and the SCO tracking loop architecture shows the tracking throughput.
(1) SCO estimation
We show the comparisons between different estimation algorithms. As mentioned in chapter 2, reference [2] proposed a “CP-LLS algorithm” to use the linear least square method between continual pilots of consecutive symbols. Reference [16] mentioned “CP-CFD/SFD algorithm” to joint CFO and SCO tracking, and “CP” means continual pilots too. Table 3-5 lists the estimation accuracy of the above two algorithm and proposed “SP-LLS algorithm”
mentioned in chapter 2. And the channel model is listed in table 3-6.
Table 3-5 the estimation accuracy of the SCO in ppm CP-CFD/SFD [5] 0.0694 5.9905 1.3678 7.2908 -2.0967 8.2107 CP-LLS [3] -0.1567 5.4948 -0.0450 6.3277 -4.0990 8.6082 Proposed SP-LLS 0.0475 1.0645 0.1032 1.3617 -3.5122 4.8212
Table 3-6 channel model of the simulation in SCO estimation algorithm Mode 2k
GI 1/4 Mapping 64QAM Initial SCO 20ppm AWGN 15dB
GI 1/4 Mapping 64QAM Initial SCO 20ppm AWGN 15dB