Singlefrequency networks (SFNs) for broadcasting digital TV is a topic of theoretical and practical interest for future broadcasting systems. Although progress has been made in the characterization of its description, there are still considerable gaps in its deployment with MIMO technique. The contribution of this paper is multifold. First, we investigate the possibility of applying a spacetime (ST) encoder between the antennas of two sites in SFN. Then, we introduce a 3D spacetimespace block code for future terrestrial digital TV in SFN architecture. The proposed 3D code is based on a doublelayer structure designed for intercell and intracell space timecoded transmissions. Eventually, we propose to adapt a technique called effective exponential signaltonoise ratio (SNR) mapping (EESM) to predict the bit error rate (BER) at the output of the channel decoder in the MIMO systems. The EESM technique as well as the simulations results will be used to doubly check the efficiency of our 3D code. This efficiency is obtained for equal and unequal received powers whatever is the location of the receiver by adequately combining ST codes. The 3D code is then a very promising candidate for SFN architecture with MIMO transmission.
Broadcasting digital TV is currently an area of intensive development and standardisation activities. The terrestrial broadcasting is the most challenging transmission system among the existing radio diffusion systems due to the presence of strong echoes.
Technically, singlefrequency
networks (SFNs) [
The optimisation of the MIMOOFDM schemes in the SFN is highly desirable to be led in terms of the bit error rate (BER) after channel decoding. However, the optimisation of the MIMOOFDM systems by simulations is time consuming. Thus, it is very important to accurately abstract the system level BER performance into analytical expression. Moreover, the system level performance abstraction should take into account the different transmission conditions, that is, modulation and coding scheme (MCS), synchronization errors, channel fading, and so forth.
This paper
presents a complete study on the optimisation of the MIMOOFDM schemes for SFN
architectures. The optimisation is double checked analytically and by
simulations. This work has been carried out within the framework of a new
European CELTIC project called
This paper is
structured as follows. Section
In this paper,
we propose to apply a MIMO communication scheme between the antennas located in
the different sites of an SFN architecture. Such a system could be implemented
using
SFN with unequal received powers.
Classically,
in SFN architectures, the different antennas transmit at the same moment the
same signal on the same frequency. For the SFN to work properly, the resulting delay
spread
As a starting
point, let us assume that each site holds one antenna and that the receiver
receives signals from both antennas. In the case of an SFN, the time offset
between the signals received from each site antennas could be seen as a
superposition of the time offset between transmitters’ signals (the signal time
delay between the transmitting antennas) and the signal time offset between each
transmitter and the receiver. The first offset is generally negligible since
the transmitters are synchronized with an ultrastable reference like the global
positioning system (GPS). The second offset could be seen as follows. When the
mobile terminal (MT) moves within one cell, it receives signal from its own
cell antenna but also from the neighbouring cell antenna. Since the MT is not
equidistant to both antennas, the signal received from each one will be delayed
according to the position of the MT. This results into a delay
The delay of
each CIR between the
Without loss
of generality, let us assume that the first transmitter site is the reference
site. Substituting
In the sequel,
we will assume that the power received from the reference antenna is equal to 0 dB and the distance
SFN with unequal received powers.
If we now
consider that the number of Tx in one site is greater than one (i.e.,
We note that
in this paper we consider independent CIRs with the dominant problem of the SFN
architecture, that is, the problem of the CIR delays and the power loss. However,
in real situations, other problems like CIRs correlations should be considered
also. The reader may refer to [
In this section, we describe the transmission model of the doublelayer STBC constructed between the antennas of the different sites. The double layer proposed here has to cope with the equal and unequal received powers. The first layer in our proposed code corresponds to the intercell ST coding while the second corresponds to the intracell ST coding.
Figure
MIMOOFDM transmitter.
The doublelayer
encoding matrix of the proposed code is described by
In order to
simplify the transmission model, the doublelayer encoding matrix given in (
We assume that
the transmitter and the receiver are perfectly synchronised. Moreover, we
assume perfect channel state information (CSI) at the receiver. In this paper,
the transmission is described in frequency domain for simplicity reasons.
However, in real scenario, the signal is transferred to the time domain and
cyclic prefix (CP) insertion operations are achieved at the transmitting side.
Reciprocal operations are done at the receiving side. The signal received on
the subcarrier
Let us now
describe the transmission link with a general model independently of the ST
coding scheme. We separate the real and imaginary parts of the complex symbols input
vector
In the sequel,
we separate the real and imaginary parts of
Since we use
linear ST coding, the vector
The detection
problem is to find the transmitted data
Iterative receiver structure.
At the first
iteration, the demapper takes the estimated symbols
From the
second iteration, we perform PIC operation followed by a simple inverse filtering (instead of MMSE filtering at the
first iteration):
The aim of
this section is to judiciously build the proposed doublelayer 3D STS code so
that the resulting MIMO scheme behaves efficiently in an SFN context. We then
need to choose the adequate ST coding scheme to apply to each layer of our 3D
code. In the sequel, we will consider different coding schemes to apply to the
different layers. First, we will consider the wellknown orthogonal Alamouti ST
coding scheme [
Simulations parameters.
FFT size  8 K 

Sampling frequency 
9.14 MHz 
Guard interval (GI) duration 

Rate 
1/2, 2/3, 3/4 
Polynomial code generator 

Channel estimation  perfect 
Constellation  16QAM, 64QAM, 256QAM 
Spectral Efficiencies 

Different MIMO schemes and efficiencies.
Spectral efficiency  ST scheme  ST rate 
Constellation 



Alamouti  1  64QAM  2/3 
SM  2  16QAM  1/2  
Golden  2  16QAM  1/2  
3D code  2  16QAM  1/2  

Alamouti  1  256QAM  3/4 
SM  2  64QAM  1/2  
Golden  2  64QAM  1/2  
3D code  2  64QAM  1/2 
In the simulations results given hereafter, we separate the singlelayer
case and the doublelayer case. For NO schemes, we show in [
In the case of
singlelayer reception, we have one antenna by site. Then, the secondlayer
matrix
Alamouti scheme in SFN environment.
Figure
Required
Considering
the whole doublelayer space domain construction, one ST coding scheme has to
be assigned to each layer of the proposed system. The resulting 3D STS code
should be efficient for both environments in SFN architectures. In this paper,
we restrict our study to
Since the
distance
3D STS scheme in SFN environment.
Figure
Required
Figure
Required
As we have shown, the 3D code outperforms the other MIMO schemes in
different reception scenarios. Let us now compare the different MIMO schemes in
terms of complexity implementation. At this stage, different complexity points
could be evaluated. First, at the transmission side, the implementation of the Alamouti
and the Golden code schemes between different sites in SFN architecture does
not increase the complexity when it is compared to that of the SISO case.
Indeed, we just need to synchronize the transmission from both sites as it
should be already done with SFN in the SISO case. This task can be ensured by
an ultrastable reference like the GPS. However, for the 3D code, an additional
frontend RF should be used at each site. At the receiving side, the iterative receiver
used for NO schemes like the SM scheme or the Golden code is the same of that
used for the 3D code. Moreover, when compared to the ML detection, we had
showed in [
In the previous section, we have proposed a new 3D STSBC for MIMOOFDM systems in SFN architecture. Using the system level simulations, we have showed that this new ST code is very efficient to cope with equal and unequal received powers. However, explicit bit level simulation of each MT in every cell of the SFN would be forbidding time consuming. The problem becomes more noticeable when MIMOOFDM techniques are used in SFN architectures. As a consequence, it is desirable to evaluate the system level performance in terms of BER without achieving system simulation. Thus, the practical need of an accurate abstraction of the system level simulation into analytical evaluation highly motivates our work to achieve an analytical BER expression of the MIMOOFDM systems using iterative receiver.
In
some studies, it has been shown that the BER at the output of the channel
decoder is directly related to the SINR at the output of the detector [
In
this paper, we propose to adapt the EESM technique to the MIMOOFDM systems
using the iterative receiver. The first step in our work consists in computing
the SINRs expressions at the output of the detector. The
second step is to establish an accurate relationship between the different
SINRs and the coded BER through the adapted EESM technique. We note that the
SINR expressions and the predicted BER given hereafter are not specified for a
given antenna, that is, we do not separate between the different antennas like
in [
Without loss
of generality, we assume in the sequel that we are interested by the
The complex
transmitted data symbols are assumed i.i.d. having zero mean and unit variance
(the variance of the real and imaginary parts is equal to
Based on the
structure of the iterative receiver, we already know that the outputs of the
soft Gray mapper are complex symbols which belong to the set of constellation
points. Let
(I) If the estimated
symbol
(II) If the
estimated symbol
In order to evaluate the BER at the output of the channel decoder, we propose in this section to adapt the EESM technique to the MIMOOFDM context. At the first step, we will develop analytically the EESM technique. At the second step, we will present its application in the OFDM system. Then, we will adapt it to the MIMOOFDM context using the SINR expressions computed at the previous subsection.
Let
In an OFDM
system, it was concluded that the key issue to accurately determine the
appropriate BER after channel decoding is to use the effective SINR in
combination with AWGN curves. The work in [
BER prediction through EESM.
In our study,
the EESM technique must be adapted to the MIMOOFDM system. Indeed, the
estimated received symbol at each subcarrier is a superposition of different
symbols transmitted by the different antennas on that subcarrier. Therefore,
the EESM technique will be applied on the set of Q symbols transmitted on the
In this
section, we validate through the EESM technique and the SINR analysis the
efficiency of the proposed 3D STS code. The considered simulation parameters
are the same of those given in Table
The results
given in this section are obtained with the COST 207 TU6 channel model. The AWGN
results used to estimate the parameter
Figure
Validation
of EESM technique, Alamouti scheme,
Figure
Validation of EESM technique,
Golden code scheme,
In Figure
Validation of EESM technique,
In this paper, a new 3D STSBC has been presented for MIMO transmission in SFN architecture including two transmitting sites. The proposed 3D STSBC is based on a doublelayer structure defined for intercell and intracell situations by adequately combining the Alamouti code and the Golden code schemes. We showed that our proposed 3D STS scheme is very efficient to cope with equal and unequal received powers in SFN scenarios whatever the receiver position is.
Moreover, we have proposed an analytical SINR evaluation of MIMOOFDM systems using an iterative receiver as well as an adaptation of the EESM technique to efficiently evaluate the BER at the output of the channel decoder. Using the EESM technique and the analytical evaluation, we have showed again the superiority of the proposed 3D code. It is then a very promising candidate for the broadcasting of the future terrestrial digital TV in SFN architectures.
The authors would like to thank the European CELTIC Project “B21C” for its support to this work.