S IMULATION P LATFORM

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.

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 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

Inner Receiver ^De-mapping_De-mapping ^FEC_FEC Outer Receiver

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 [1] which means less than one uncorrected error event per hour, corresponding 10^-11 after Reed-Solomon decoder and 2x10^-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

Fig 3.3 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 [3]. 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 ^π∆ +noise (3.1)

Given the coarse estimated symbol window n , the ML frequency estimate [16] becomes ^{^}

^

^

^ *

1

1 arg ( ) ( )

2

g n

i n N x

f r i r i N

π _{= − − +}

∆ = ⋅ ⋅ − (3.2)

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 [3]. Because of pre-FFT acquisition, the residual fractional offset f∆ is small so that the ICI noise in this stage is also small. We assume the integer carrier frequency offset n_I (subcarrier spacings), 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,

arg max

I m I k C m l k l k

n z z ₋

∈ ∈ +

= ⋅ (3.3)

where C denotes the positions of continual pilots and I represents the search range which is typical given by [−n_I,max,n_I,max]. Considering small offset f∆ and ζ , the probability of

false detection (n^{^}_I ≠n_I) is very small.

The channel estimation unit must estimate both the channel 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 [3] 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 2D interpolation in channel estimation unit design