1
Simulation of Power Line Communication using
ATP-EMTP and MATLAB
S. Robson, Student Member, IET, A. Haddad, Member, IET and H. Griffiths, Member, IET
Abstract—In this paper, a simulation test bed for narrowband
Power Line Communications (PLC) is demonstrated. The
method is able to quickly assess the performance of modulation
schemes for an arbitrary network constructed in the ATP-EMTP
software, both for point to point and for multi-point to point
communication. Demodulation is carried out in MATLAB. The
test setup is used to implement Orthogonal Division Multiplexing
(OFDM) on a number of ‘typical’ medium voltage (MV)
distribution networks. The simulation results show that with a
considered choice of OFDM parameter values, robust, real time
communication over the narrowband PLC channel is possible.
Index
Terms—multipath,
Communication, OFDM.
Narrowband
Power
Line
I. INTRODUCTION
T
HE recent movement toward smart grids and the
continued pressure on utility companies to provide a more
reliable service to customers has amplified the importance of
robust, real time communication between remote points of the
network and the control room. One way to achieve this is the
use of the existing power line infrastructure as the
communications medium, a process generally known as PLC.
Though PLC is not a new concept [1], advancements in
modulation performance and the ever-decreasing cost of
implementing modems in hardware now means that a network
wide multi-point to point network without the need for
expensive line traps is possible [2].
The usual first step toward assessing the performances of
modulation schemes for PLC is to develop a model that
attempts to accurately describe the power line channel. One of
the first channel models to gain widespread acceptance was
made by Zimmerman and Dostert [3]. In this model, the
multipath effects are resolved by attributing a weighting
factor, attenuation portion and delay portion to each path. The
model is verified for simple networks but loses accuracy as the
number of paths increases. For the 10-kV MV network, an
attempt has been made to form a generalized model based on
empirical measurements [4], however, a general model may
not be suitable for testing multi-point to point modulation
because the multipath components will differ depending on
This work is funded by the Power Networks Research Academy (PNRA) and
in collaboration with EDF energy.
The authors are with the High Voltage Energy Systems (HIVES) group,
Cardiff University. Contact details:
S. Robson, (e-mail: robsons1@cardiff.ac.uk).
A. Haddad (e-mail: haddad@cardiff.ac.uk).
H. Griffiths (e-mail: griffithsh@cardiff.ac.uk)
the location of the modem within the network. If a base node
is defined as the ‘entry point’ to the network, and therefore the
node sustaining an individual link with each separate remote
node, then a proper assessment of the performance of
modulation schemes should separately consider the channel
response between each remote node and the base node, plus
the channel response between each remote node,
simultaneously. The large delay spread and complexity of a
branched distribution network suggests that large differences
in channel response will exist depending on which two points
are chosen [5].
To resolve this problem, the modulation scheme is directly
implemented within the ATP-EMTP software environment
using the native FORTRAN based models language. The
modulated signal can be injected into the network at any point
using any coupling scheme. A model of an inductive coupler
is used in this study. The extracted signal is exported to
MATLAB and demodulated. Synchronisation algorithms
allow the simulation to be ‘free running’ in the sense that a
frame sent from any node can be demodulated by any other
node without additional user intervention.
The organization of the paper is as follows. Section 2
introduces the simulation setup and highlights the important
aspects of each part. In section 3, the network model is
introduced and magnitude and phase responses are obtained.
Examples of how the simulation setup can be used are
presented in section 4, with emphasis on assessing the
performance of multipoint to point OFDM modulation
schemes operating on the rural overhead 11-kV distribution
network in the CENELEC range of frequencies. Special
attention is given to the choice of cyclic prefix length, the
potential advantages of using adaptive techniques and the
performance of the synchronization algorithm.
II. SIMULATION SETUP
A. Simulation Setup Overview
The simulation setup is split into three domains:
1) ATP-EMTP domain, where the network model and the
inductive coupler is constructed and simulated. The
line model used is explained further in section 4.
2) ATP Models domain, where the modulator is
simulated in FORTRAN code. A model is also used to
resolve the phase voltages and currents into modal
values.
3) MATLAB domain, where demodulation and postprocessing takes place.
2
by mapping the parallelised input biit stream using some form
of modulation. In this study, differeential modulation schemes
are examined. In this case, the inform
mation is modulated in the
phase difference between adjacent sub-carriers, either in the
time or frequency domain, though
h, only frequency domain
differential modulation is considered
d in these simulations. The
code is designed to be flexible, allo
owing the implementation
of several Phase Shift Keying (PSK
K) schemes. In the analysis
that follows, Differential Binary PS
SK (DBPSK), Differential
Quadrature QSK (DQPSK) and Diffferential 8 PSK (D8PSK)
are to be used. Each modulation scheme is implemented in the
FORTRAN code through the use of a simple truth table.
TABLE 1
TRUTH TABLE FOR SYMBOL MAPPING: IN PHASE COMPONENTS (I) AND
QUADRATURE COMPON
NENTS (Q)
DBPSK
Fig. 1. Block diagram of the simulation setup
The overall simulation scheme (see Fig. 1) facilitates the
simulation of OFDM modulation on any ATP-EMTP network
model. Within ATP-EMTP, one may replicatte network events
such as fault transients or switching surges tto study the effect
on the communication link. Furthermore, thhe scheme allows
the noise inherent to the power line (bothh background and
impulse) to be incorporated in the modeel. A number of
modulators can be considered simultaneouslyy, giving the user
an indication on how time domain multiiplexing schemes
operate on the power line channel. The mainn disadvantage of
the presented simulation scheme is the unncertainty in the
accuracy of the line model at high frequencies.
B. OFDM Modulator
OFDM is regarded as a suitable modulatioon scheme for the
PLC channel [6], [7]. The most important advvantage of OFDM
over single carrier modulation schemes iis the ability to
mitigate the multipath environment inherent in PLC channels.
OFDM divides the available spectrum innto many narrow
bands. The data to be transmitted are sserial to parallel
converted, symbol mapped, and inputtedd to an Inverse
Discrete Fourier Transform (IDFT). The ouutput of the IDFT
can then be reconstructed into a time ddomain baseband
representation of its input. The OFDM ssymbol period is
approximately N times longer than an equuivalent data-rate
single carrier modulation scheme. If the lenggth of the symbol
is long compared to the RMS delay spreadd of the channel,
Inter Symbol Interference (ISI) is signifficantly reduced.
Furthermore, if a cyclic prefix is appended too the beginning of
each OFDM symbol, ISI can be effectively elliminated, even in
aggressive multipath channels [8]. One OFD
DM symbol can be
defined as the sum of N sub-carriers:
/
,0
1
where T is the symbol duration and Xk are tthe data symbols,
i.e. the IDFT output values. The input to thee IDFT is formed
DQPSK
Bits
0
I/Q
1
1
-1
00
01
10
1/1
1/-1
-1/1
11
-1/-1
D8
8PSK
Bits
000
001
010
011
100
101
110
111
I/Q
1.404/0
1/1
0/1.404
-1/0
-1.404/0
-1/-1
0/-1.404
1/-1
The code can be easily modified to implement higher order
constellation schemes. The serial to parallel conversion is not
necessary in the model because thee use of a simple random
function can determine which poin
nt on the constellation is
transmitted on each sub-carrier and
d performance calculations
(e.g., Bit Error Rate (BER)) can stilll be achieved provided the
transmitted constellation points are known
k
at the demodulator.
The output of the complex IDFT is a series of time domain
values. The FORTRAN code allowss the possibility to append
a cyclic prefix of arbitrary length to
t the start of the OFDM
symbol. This is done by copying a number of samples from
the end of the symbol and appendin
ng them to the start. Thus,
(1) becomes:
/
,
2
where Tc denotes the length of the cy
yclic prefix.
A Digital-to-Analog Converter (DAC) is required to
d signal from the discrete
construct a time domain baseband
output values of the IDFT. This is achieved by a simple
r
filter. To
sample and hold followed by a reconstruction
implement the sample and hold, the simulation directive
he output of the modulator
‘TIMESTEP MAX’ is applied to th
model. The effect is to define a local maximum to the
simulation time-step of the model,, allowing the conversion
rate of the DAC to be specified. Carre must be taken to ensure
that the Nyquist criterion is met by
y making the ATP-EMTP
sampling frequency at least twice as
a large as the conversion
rate of the DAC. A number of examp
ples are listed in Table 2.
3
In code and hardware implementations, this is most
conveniently implemented using the iterative formula:
TABLE 2
EXAMPLES OF SIMULATION PARAMETERS
Timestep
Max
Simulation
Sampling
Frequency
OFDM System
Sampling Frequency
Sample Rate in
MATLAB
6 μs
10 MHz
333.33 kHz
Every 30
samples
60 μs
1 MHz
333.33 kHz
Every 30
samples
333.33 MHz
Every 3
samples
0.6 µs
10 MHz
4
1
where d is the time index corresponding to a window of 2L
samples. The energy received in the second half symbol is:
|
|
5
Finally, the actual timing metric is defined as:
A reconstruction filter is implemented in a separate model
within the ATP-EMTP environment. The input to the
reconstruction filter model is taken from the output of the
modulation model. The Z transfer function built in to the
models language is used to implement a low pass filter with a
cut-off frequency of approximately 1/2T, where T is the
OFDM symbol period.
It is noted that the simulation setup is able to assess the
trade-off between filter requirements and oversampling. For
example, zero-padding the IDFT eases the roll-off
requirements of the reconstruction filter at the cost of
sacrificing data rate.
The up-conversion is carried out immediately after the
reconstruction filter. In code, this is quadrature mixing the
baseband signal by a carrier frequency signal. The signal is
now ready to be transmitted onto the channel.
C. OFDM Dedodulator
Once injected into the network, the OFDM signal is free to
propagate. The signal can be recovered from any node in the
network and exported to MATLAB for demodulation. The
first step in the demodulation process is down-conversion to
an intermediate frequency (IF) and quadrature demodulation.
A low pass filter is required to filter out the IF and leave the
baseband signal. After low pass filtering, a synchronization
algorithm is implemented in order to provide an estimate for
the starting time of the symbol. In this study, the Schmidl and
Cox algorithm [9] is implemented directly in the MATLAB
code. The algorithm is chosen due to its robustness and ease of
implementation, though any synchronization algorithm can be
easily implemented in the simulation setup. The Schmidl and
Cox algorithm searches for a time domain signal with two
identical halves, where each half can be made equal in length
to half the FFT sampling period. The construction of such a
training symbol is conveniently carried out in the modulator
by transmitting a constellation point on only the even
frequencies of the IFFT and keeping the odd frequencies set to
zero. The search for the start of the symbol is made by a
sliding window autocorrelation function.
|
|
6
The timing metric leads to a characteristic plateau with
length equal to the length of the cyclic prefix minus the
duration of the channel impulse response. This leads to a
degree of uncertainty in the exact start time of the symbol,
however, the addition of the cyclic prefix and the use of
differential modulation eases the requirements on necessary
accuracy. Note that in the full implementation of the Schmidl
and Cox algorithm, a second training symbol is used to gain
an estimate of the frequency offset. In this study, the
frequency offset is assumed to be zero hence the second
training symbol is not required.
After synchronization, the timing offset estimate is used to
dictate when the FFT sampling period begins. The FFT
sampling period begins at every S+F samples, where S is the
number of samples making up the FFT symbol duration plus
the cyclic prefix length and F is the offset estimate from the
timing metric. In this implementation, one training symbol is
used per frame and the frame consists of any number of data
symbols. The demodulator assumes that the received symbols
have been differentially encoded. Though differential
modulation has not actually occurred at the modulator, the
performance of the scheme can still be determined by
demodulating the randomly generated sent symbols to reveal
the bit-stream that would have created these symbols. This is
then compared to the demodulated received symbols to give a
value for the BER.
D. Noise
The aim of the noise part of the simulation scheme is to
provide a means of replicating the noise levels on an MV
power line. For convenience, background noise is added after
signal extraction in the MATLAB part of the simulation
scheme. The noise power is set by changing the variance of a
random variable. For an extracted signal, S, and a noise
source, N, the signal-to-noise ratio is defined as:
7
3
where
is the standard deviation of the noise.
4
TABLE 3
DIMENSIONS AND MODAL PARAMETERS OF OVERHEAD LINE USED
III. NETWORK MODEL
A. Line Model
The line model is required to satisfactorily model the
response of the distribution line over the frequencies of
interest. For this study, the frequencies of interest are
restricted to below 1 MHz, however, the difficulty resides in
modeling a wide range of frequencies with the same line
model. The usual starting point in line model development is
and the propagation
to define the characteristic impedance,
constant, :
8
Wood Pole Overhead Line
Height
9m
Height at mid-span
7.5m
Conductor separation
1.5m
Conductor name
Dingo
Conductor resistivity
0.1814 Ω/km DC
Mode 1 propagation constant
0.09 Nepers/km at 500 kHz
Mode 2 propagation constant
0.008 Nepers/km at 500 kHz
Mode 3 propagation constant
0.007 Nepers/km at 500 kHz
0.603
0.707
0.409
0.523
0
0.816
0.603 0.707
0.409
Transformation matrix
9
where R is the resistance, L the inductance, C the capacitance
and G the conductance of the mode of propagation. It is noted
and
are frequency dependent. R and L are
that both
themselves frequency dependent and complicate the
calculation of and over wide frequency ranges.
The most popular frequency dependent model within the
ATP-EMTP is known as the J.MARTI frequency dependent
from DC
model [10]. The model requires the calculation of
up to a frequency where it is constant and up to a frequency
where it becomes negligibly small. An obvious source of error
is in the ATP-EMTP treatment of the frequency dependence of
R and L. For R, the skin depth will have an ever-increasing
influence as frequency increases. To calculate the skin depth,
the ATP-EMTP assumes a tubular conductor and the forced
approximation that a stranded conductor is equivalent to a
tubular conductor of the same cross sectional area. For
stranded aluminum or copper conductors, for instance those
commonly used in MV overhead lines, the actual skin depth
calculation is less trivial and non negligible errors are to be
expected if the ATP-EMTP tubular approximation is used at
frequencies exceeding 5-10 kHz [11]. For frequencies
exceeding 5 kHz, the ATP-EMTP uses the Galloway formula
[12] which provides a more accurate model of the skin effect
at higher frequencies. With the current state of knowledge, it
is difficult to confidently assess the error associated with the
ATP-EMTP treatment of stranded conductors so caution must
be used in interpreting the results of the presented simulation
scheme in simulations where attenuation is an important
factor.
The actual geometry of the overhead line is based on
standard wood pole designs commonly deployed in the UK.
The dimensions of the overhead line model and the ATPEMTP computations of the transformation matrix and modal
propagation constants are shown in Table 3.
B. Developed Network Models
To demonstrate the simulation scheme, a network model
based on representative 11 kV overhead networks is
constructed in ATP-EMTP. The actual network is based on a
series of ‘typical’ networks known as the UK Generic
Distribution Network (UKGDS) [13]. The UKGDS is a suite
of reference networks designed to embody the main features
of distribution networks in the UK. The emphasis in this study
is on rural overhead networks because this represents a part of
the power system network operators have least real time
knowledge of and is particularly vulnerable to outages. For the
‘large rural’ network of the UKGDS is chosen. This is a large
overhead network with branches. It is noted that some branch
lengths in the reference network are identical, leading to the
possibility of unrealistic multipath conditions. To make the
network more realistic, all branch lengths are randomised to
±10% of their original length. The test network is shown in
Fig. 2.
0.815 km
C
0.390 km
0.745 km
0.515 km
0.510 km
0.445 km
0.790 km
1.515 km
0.410 km
A
0.525 km
0.634 km
0.593 km
0.419 km
0.521 km
0.434 km
B
0.811 km
0.404 km
0.578 km
0.760 km
0.815 km
0.552 km
0.790 km
0.535 km
0.815 km
0.634 km
0.760 km
0.795 km
0.773 km
0.815 km
0.807 km
D
0.770 km
0.876 km
0.800 km
Fig. 2. Line network model representative of a large, rural overhead
distribution network
5
C. Magnitude and Phase Response of Test Network
A method is developed to determine the magnitude and
phase responses between point A and points B, C and D
respectively. An impulse is injected into the network at point
A and the measured signal at point B, C and D is recorded.
Phase to phase coupling is used resulting in a signal that
contains only mode 2. An FFT is applied to the received
signals at B, C and D. The magnitude and phase of the FFT
operation can be regarded as the magnitude and phase
response of the channel.
The impulse responses used to derive Fig. 3 can also be
used to calculate the root mean squared (RMS) delay spread.
The first moment of the power delay profile (PDP) is defined
as:
∑
∑
10
where
is alternatively called the mean excess delay. The
square root of the second central moment of the PDP is given
by:
Magnitude Response (Position A to Position B)
Attenuation (dB)
50
∑
0
-100
11
∑
-50
0
1
2
3
4
5
6
7
8
9
10
x 10
5
Another measure of multipath delay spread is the coherence
bandwidth:
Phase Response (Position A to Position B)
Phase (Radians)
4
1
5
2
0
-2
-4
0
1
2
3
4
5
Frequency(Hz)
6
7
8
9
10
x 10
5
(a)
Magnitude Response (Position A to Position C)
Attenuation (dB)
50
0
is simply a dual representation of the RMS delay spread. It
specifies the range of frequencies over which the channel
affects the signal in a similar way. More specifically, it is the
range over which the attenuation can be thought of as ‘flat’
and the phase change can be thought of as linear. The
calculated RMS delay spread and coherence bandwidth are
listed in Table 4.
-50
-100
0
1
2
3
4
5
6
7
8
9
TABLE 4
10
RMS DELAY SPREAD AND COHERENCE BANDWIDTH
5
x 10
Phase Response (Position A to Position C)
Phase (Radians)
4
B
2
MODE 1
0
MODE 2
-2
MODE 3
-4
0
1
2
3
4
5
Frequency(Hz)
6
7
8
9
-50
0
1
2
3
4
5
6
7
8
9
10
5
Phase (Radians)
x 10
Phase Response (Position A to Position D)
2
0
-2
-4
0
1
2
3
4
5
Frequency(Hz)
D
860
350
220
257
184
363
780
1080
550
IV. SIMULATION RESULTS
-100
4
232
578
912
x 10
0
-150
C
710
750
500
5
Magnitude Response (Position A to Position D)
50
278
267
398
10
(b)
Attenuation (dB)
12
6
7
8
9
10
x 10
5
(c)
Fig. 3. (a) Magnitude and phase response between positions A and B. (b)
Between position A and C. (c) Between positions A and D.
A. Performance of the synchronization algorithm
The Schmidl and Cox synchronization algorithm is tested
under various conditions. For AWGN channels (no multipath),
the length of the characteristic plateau is equal to the cyclic
prefix length. This is clearly shown in Fig. 4. A weakness of
the Schmidl and Cox method is the inherent uncertainty in the
starting time caused by the plateau. It was observed that the
start time can be chosen anywhere within the cyclic prefix
without a significant loss in performance. For multipath
channels, the plateau is shortened due to the delay spread of
the channel. This is demonstrated in Fig. 5. Problems were
encountered when using the Schmidl and Cox algorithm in
noisy channels and channels with large delay spreads, even
when the condition that the cyclic prefix is greater in length
than the RMS delay spread of the channel. False peaks falling
outside of the characteristic plateau led to inaccuracies. A
possible solution to this follows from a suggestion published
in [14]. A moving average filter can be used to smooth the
timing metric, improving the accuracy of the algorithm. In
6
Schmidl and Cox: No multipath and noiseless
Unchanged Schmidl and Cox metric
Moving Average Filter
1
0.9
0.8
Timing Metric
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
400
500
600
700
800
900
1000
Sample Number
1100
1200
1300
1400
Fig. 4. Schmidl and Cox timing metric in AWGN noise channel and the
response of the modified metric using a moving average filter.
C. Effect of position on network
The effect of positioning of the remote node is examined.
The BER is obtained for communication between the base
node, A and the remote positions B, C and D. A carrier
frequency of 275 kHz is chosen, with a sampling frequency of
333 kHz, FFT size of 512 and 320 used subcarriers with
DBPSK modulation. These parameters lead to a useful symbol
duration of 1.5 ms, a sub-carrier spacing of 650 Hz and a data
bandwidth of approximately 200 kHz. Fig. 7, Fig. 8 and Fig. 9
show the results of the simulation. It is observed that the BER
climbs to 0.5 at particular frequencies, even in channels with
an extremely high SNR. This is true at all three positions,
though position A shows a better performance.
Schmidl and Cox: Multipath channel and noiseless
0.7
Moving Average Filter
Unchanged Schmidl and Cox metric
1
0.9
0.6
0.8
0.5
0.6
0.5
Bit Error Rate
Timing Metric
0.7
0.4
0.3
0.2
0.4
0.3
0.1
0.2
0
500
600
700
800
900
Sample Number
1000
1100
1200
1300
0.1
Fig. 5. Schmidl and Cox timing metric in multipath channel and the modified
moving average metric.
practice, a ‘back-off’ time was required due to the delay of the
filter and the tendency of the peak of the filtered metric to fall
at the very latest part of the plateau.
0
0
0
100
150
200
Subcarrier Number
250
300
350
Fig. 7. BER for the channel between positions A and B. Cyclic prefix >>
RMS delay spread
0.8
B. Performance in the AWGN channel
The simulation is first tested under AWGN conditions and
no multipath. This is achieved by using a long line model such
that no reflections are possible. Signal injection takes place at
the centre of the line and extraction at some arbitrary point
away from the injection point. The OFDM scheme uses
DBPSK, DQPSK or D8PSK with all subcarriers used to aid
comparison with theoretical BER curves. The results are
shown in Fig. 6.
10
50
0.7
Bit Error Rate
0.6
0.5
0.4
0.3
0.2
0.1
0
0
50
100
150
200
Subcarrier Number
250
300
350
Fig. 8. BER for the channel between positions A and C. Cyclic prefix >>
RMS delay spread
-1
10
0.7
0.6
0.5
Bit Error Rate
Bit Error Rate
-2
10
-3
10
-4
10
0
0.3
0.2
DQPSK
D8PSK
DBPSK
0.1
0
0
-5
10
0.4
2
4
6
Eb/N0 (dB)
8
10
12
Fig. 6. BER curves obtained from the simulation setup using DBPSK,
DQPSK and D8PSK on an AWGN channel (no multipath). Averaged over
2000 symbols.
50
100
150
200
Subcarrier Number
250
300
35
Fig. 9. BER for the channel between positions A and D. Cyclic prefix >>
RMS delay spread
7
,
,
,
,
,
,
,
,
13
,
where the phase of is the received phase difference between
the current and previous subcarrier,
is the FFT output for
the
conjugate
of the FFT
the current subcarrier and
,
output of the previous subcarrier. The received phase is made
up of the desired phase, φij, and an unwanted component,
caused by the phase shift between adjacent
,
subcarriers in the frequency domain. The tendency of the
network to do this is not constant across the frequency range.
For instance, it is observed that there are regions in the
spectrum exhibiting a zero BER for high SNR channels. It is
also found that the regions below approximately 250 kHz is
more frequency selective and gives larger and more sudden
phase shifts than higher up in the frequency range. This is
reflected by higher BERs.
D. Cyclic Prefix Length
The choice of cyclic prefix length is a crucial factor in the
design of OFDM systems. It has been suggested that a sensible
design choice is to set the cyclic prefix at least twice as large
as the RMS delay spread of the channel [15]. In the simulation
setup, the BER for various cyclic prefix lengths are obtained
and shown for three carrier frequencies in Fig. 10. It is
observed that the BER minimises at a certain cyclic prefix
length. For the simulated system, this occurs at around 200
samples (1.2 ms). This is around twice the RMS delay spread
for the channel (see Table 4).
E. Effect of modulation scheme
The phase shift between adjacent subcarriers will affect
different modulation schemes in different ways. It is expected
that larger constellation schemes will be less robust to phase
shifts because the decision boundary is smaller than for lower
order constellation schemes. This is tested by simulating
DBPSK, DQPSK and D8PSK on the same channel. The
results are shown in Fig. 11 and Fig. 12. The simulation
results show a marked difference between BER depending on
the modulation scheme. As expected, D8PSK is the worst
performer; however, at certain subcarriers zero BER is
obtained. Given that D8PSK is able to transmit 3 bits per
subcarrier (compared to 2 bits per subcarrier for DQPSK and 1
bit per subcarrier for DBPSK), there may be a significant gain
in performance if adaptive schemes are used, for instance
algorithms able to dynamically allocate subcarrier modulation
schemes depending on channel SNR could be used. The
comparison between Fig. 11 and Fig. 12 shows that the BER is
generally less in schemes using the 440 kHz carrier frequency
(i.e. for a 200 kHz bandwidth, this would mean the frequency
range between 340 kHz and 540 kHz would be occupied).
0.7
Bit Error Rate Comparison:SNR=50 dB, Carrier Frequency=275 kHz
D8PSK
DQPSK
DBPSK
0.6
0.5
Bit Error Rate
There is an intimate relationship between the phase
response of the network and the expected error when
transmitting differentially encoded information over the
network. Referring again to Fig. 3, it is clear that the phase
response is non-linear for large parts of the frequency
spectrum. This translates into phase rotations that have the
potential to move the phase difference between one subcarrier
and the previous subcarrier away from the correct decision
making boundary. From [15], differential phase detection in
the frequency domain can be described as:
0.4
0.3
0.2
0.1
0
50
100
150
200
Subcarrier Number
300
Fig. 11. BER comparison of DBPSK, DQPSK and D8PSK for a carrier
frequency of 275 kHz, occupied bandwidth of ~200 kHz (175 kHz-375 kHz),
sampling frequency of 333 kHz, FFT size of 512 and between position A and
B.
Bit Error Rate Comparison: SNR=50 dB, Carrier Frequency=440 kHz
0.7
D8PSK
DQPSK
DBPSK
0.6
0.5
0.14
Bit Error Rate
0.16
400 kHz
300 kHz
500 kHz
0.12
Bit Error Rate
250
0.4
0.3
0.2
0.1
0.1
0.08
0
50
100
150
Subcarrier Number
200
250
300
0.06
Fig. 12. BER comparison of DBPSK, DQPSK and D8PSK for a carrier
frequency of 440 kHz, occupied bandwidth of ~200 kHz (340 kHz – 540
kHz), sampling frequency of 333 kHz, FFT size of 512 and between position
A and B.
0.04
0.02
0
0
50
100
150
200
250
300
Cyclic Prefix Length (samples)
350
400
450
Fig. 10. Cyclic prefix length versus BER for the channel between A and B
and at carrier frequencies of 300 kHz, 400 kHz and500 kHz. The sampling
frequency is 333 kHz
8
F. Number of Subcarriers
It is generally recognised that the sub-carriier spacing should
be less than the coherence bandwidth of the channel. For
narrowband PLC, this condition may be challenged. For
instance, for a system using a 512 FFT and a sampling
frequency of 333 kHz, the sub-carrrier spacing is
approximately 650 Hz. This is close too the calculated
coherence bandwidth of the channel. One waay to decrease the
sub-carrier spacing is to use a longer FFT pperiod. For every
doubling of the FFT period, the sub-carrier spacing halves.
Simulations are run to examine the efffect on BER of
increasing the FFT period from 512 to 10244, 1536 and 2048.
Fig. 13 shows the simulation result.
[5]
[6]
[7]
[8]
[9]
BER Versus Number of Subcarriers (500 kHz Carrier)
0.25
DQPSK
DBPSK
D8PSK
[10]
0.2
[11]
BER
0.15
[12]
0.1
0.05
0
400
[13]
600
800
1000
1200
1400
1600
Number of Subcarriers
1800
0
2000
2200
Fig. 12. Effect on BER of increasing the FFT period for DBPSK, DQPSK
and D8PSK. The channel from A to B is used and the sampling frequency is
333 kHz.
V. CONCLUSION
FDM modulation
A simulation scheme able to simulate OF
on an ATP-EMTP network has been demonsstrated. For the 11
kV rural overhead network, it has been foundd that the channel
is extremely frequency selective. For frrequency domain
differential PSK, the BER varies dependinng on the phase
rotation between the adjacent subcarriers. IIt has been found
that the degree to which the multipath channnel degrades BER
is frequency dependent. Positioning on tthe network was
observed to affect BER less than frequenncy, provided the
cyclic prefix exceeded the RMS delay spreadd of the channel.
The presented simulation scheme is ablee to assess OFDM
modulation on an arbitrary network. The m
main caveat when
using the simulation scheme is the uncertaintty in the accuracy
of the line models at high frequencies. Further work is
required to test the model against empiriical results. It is
proposed that this study be extended to includde channel coding
techniques, adaptive modulation schemes and a sensitivity
analysis for different network types incorpporating differing
conductor resistances and the inclusion of undderground cables.
VI. REFERENCES
[1]
[2]
[3]
[4]
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A. Treytl, T. Sauter, and G. Bumiller, "Real timee energy management
over power-lines and internet," in Proc. 8th Int. Symp. on Powerline
Communications and its Applications, Zaragosa, Spain, 2004, pp. 306311.
M. Zimmerman and K. Dostert, "A multi-path signal model for the
power line," IEEE Trans. Commun., vol. 50, pp. 5553-559, Apr. 2002.
I.S. Xiaoxian, Z. Tao, Z. Baohui, H. Zonghong, C. Jian and G. Zhiqiang,
“Channel model and measurement methods for 100-kV medium-voltage
[14]
[15]
power lines,” IEEE Trans. Pow. Del., vol. 22, no.1, pp. 129-134, Jan.
2007.
M. Gotz, M. Rapp and K. Dostert, "Po
ower line channel characteristics
and their effect on communication systeem design," IEEE Commun. Mag.
vol. 50, no. 4 pp. 78-86, Apr. 2004.
Y.H. Ma, P.L. So and E. Gunawen, "Performance analysis of OFDM
ommunications under impulsive
systems for broadband power line co
noise and multipath effects," IEEE Tra
ans. Pow. Delivery., vol. 20, pp.
674-682, Apr. 2005.
K
"Performance analysis
P. Amirshahi, S.M. Navidpour and M Kavehrad,
of uncoded and coded OFDM broadban
nd transmission over low voltage
power-line channels with impulsive noise," IEEE Trans. Pow. Delivery.,
vol. 21, pp. 1927-1934, Apr. 2006.
J. H. Manton, "Dissecting OFDM: thee independent roles of the cyclic
prefix and the IDFT operations," IEEE
E Commun.. Letters, vol. 5, pp.
474-476, Dec. 2001.
T.M. Schmidl and D.C. Cox, “R
Robust frequency and timing
synchronization for OFDM,” IEEE Tra
ans. Commun., vol. 45, no.12, pp.
1613-1621, 1997.
J.R. Marti, “Accurate modeling of freequency dependent transmission
lines in electromagnetic transient sim
mulations,” IEEE Trans. Pow,
App.and Sys., vol. PAS-101, Issue 1, Jan
n. 1982.
P. de Arizon and H.W Dommel, “Co
omputation of cable impedances
based on subdivision of conductors,” IE
EEE Trans. Power Delivery., vol.
PWRD-2, no. 1, Jan. 1987.
R.H. Galloway, W.B. Shorrocks, L.M
M. Wedopohl, “Calculation of
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United Kingdom Generic Distribution
Available: http://monaco.eee.strath.ac.uk/ukgds/.
H. Minn, M. Zeng, V.K. Bhargava, "On timing offset estimation for
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FDM for wireless multimedia
R. Van Nee and R. Prasad, OF
communications, 1st ed., Artech house, Inc,.
I
Norwood, MA, 2000.
d the MEng degree in Electrical
S. Robson obtained
and Electronic engiineering from Cardiff University
in 2007 and is curreently pursuing the Ph.D degree as
a PNRA scholar at the same University. His current
interests include applications of Power Line
n distribution networks, network
Communications on
modeling and modu
ulation. Mr. Robson is a student
member of the IET.
A. Haddad obtained the degree of Ingénieurr d’Etat in Electrical Engineering
in 1985 and then a Ph.D., degree in High
h Voltage Engineering in 1990.
Following graduation, he took up a Research
h Associate position. In 1995, he
was appointed a Lecturer, and, in 2006, Proffessor in electrical engineering at
Cardiff University, with responsibility for th
he High Voltage Energy Systems
Group (HIVES). His research interests are in overvoltage protection,
a earthing of electrical energy
insulation systems, insulation coordination and
systems. He has co-authored over 100 publiccations, with three paper awards.
He has recently published an IET-Power Serries Book on “Advances in High
Voltage Engineering”. He is a member of IET
T and CIGRE. He is chairman of
the IET South Wales Power Specialist, and member of the British Standard
Institution committees on overvoltage proteection of low and high voltage
systems BSI PEL1 and PEL2, the Internatio
onal Electrotechnical committees
IEC TC37 MT4 and MT10, and a member of
o the Steering Committee of the
International Universities Power Engineering
g Conference (IUPEC). He is also
a founding member and current chairman
n of the UK Universities High
Voltage network (UHVnet).
ustry in 1978 as an engineering
H. Griffiths joined the UK electricity indu
apprentice and obtained a B.Sc. degree fro
om the Polytechnic of Wales in
1982. Between 1983 and 1990, he worked
d at the South Wales Electricity
Board and the Central Electricity Generating Board (CEGB) as an engineer in
distribution and transmission system design. In 1990, he was appointed to the
lecturing staff at Cardiff University, where hee obtained the Ph.D. degree. He is
currently a Senior Lecturer in the HIVES
S Group. His research interests
include earthing systems and transients. Hee is currently a member of BSI
PEL/99 and chair of BSI GEL/600. He is a chartered
c
engineer and a member
of IET.