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ByFaaDoOEngineers.com 1 INTRODUCTION Broadband Powerline communications are sets of equipment, software and management services that when overlaid on the electric grid provides users with communication means over existing “power lines”. The new technology operates in the 1-30 MHz and can deliver data rates up to 200Mbps. The rationale behind providing high bit-rate data services exploiting the power grid resides in the vast infrastructure in place for power distribution, and the penetration of the service could be much higher than any other wire line alternative. In spite of the renewed interest in Power line communications, this technology still faces several technical challenges and regulatory issues: the power line channel is extremely difficult to model; it is a very noisy transmission medium; Power line cables in the 240V secondary distribution systems are often unshielded, thus becoming both sources and targets of electromagnetic interference (EMI); transformers can introduce severe distortion in the absence of bypass couplers. Since the power-line network is not designed for communications purposes, the channel suffers from multipath fading and frequency selectivity. A transfer characteristic model for the low voltage indoor power line based on the transmission line theory is developed. To model the transfer characteristics of power lines, basically there are two essential factors: the model parameters and the modeling algorithms. These two factors determine the reliability and accuracy of the model. From the ways the model parameters are obtained, the modeling technique can be classified into two approaches: the top-down approach and the bottom-up approach. In the top-down approach, the model parameters are retrieved from measurements. This approach requires little computation and is easy to implement. However, since the parameters depend on the measurement results, the model is prone to measurement errors. On the contrary, the bottom-up approach starts from theoretical derivation of model parameters. Although this approach requires more computational efforts comparing to the top-down approach, it however describes clearly the relationship between the network behavior and the model parameters. Moreover, this modeling approach is more versatile and flexible since all the parameters are formulated, making it easy to predict the changes in the transfer function should there be any change in the system configuration. The model described in this project adopts this bottom-up approach. Depending on the modeling algorithms used, the above approaches can be achieved in the time domain or the frequency domain. First frequency domain modeling, using scattering matrix is used to obtain the transfer function of the channel from which the attenuation in the signal strength and the delay or phase distortion at different frequencies is calculated. Scattering matrix gives the relationship of the incident (a) and reflected (b) waves. Broadband Power Line Communication is only interested in the transfer function in the forward direction, which is the ratio of the incident power into the receiver over the power injected by the transmitter. This can readily be expressed by b 2 / a 1 or S 21 in the scattering matrix. Secondly, IFFT (Inverse fast Fourier transform) is used to calculate the impulse response from the channel transfer function to know the multipath environment of the power line channel in time domain modeling and an echo model is developed in Simulink to represent this physical characteristics.

Broadband Powerline Communication

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ByFaaDoOEngineers.com 1 INTRODUCTION Broadband Powerline communications are sets of equipment, software and management services that when overlaid on the electric grid provides users with communication means over existing power lines. The new technology operates in the 1-30 MHz and can deliver data rates up to 200Mbps. The rationale behind providing high bit-rate data services exploiting the power grid resides in the vast infrastructure in place for power distribution, and the penetration of the service could be much higher than any other wire line alternative. In spite of the renewed interest in Power line communications, this technology still faces several technical challenges and regulatory issues: the power line channel is extremely difficult to model; it is a very noisy transmission medium; Power line cables in the 240V secondary distribution systems are often unshielded, thus becoming both sources and targets of electromagnetic interference (EMI); transformers can introduce severe distortion in the absence of bypass couplers. Since the power-line network is not designed for communications purposes, the channel suffers from multipath fading and frequency selectivity. A transfer characteristic model for the low voltage indoor power line based on the transmission line theory is developed. To model the transfer characteristics of power lines, basically there are two essential factors: the model parameters and the modeling algorithms. These two factors determine the reliability and accuracy of the model. From the ways the model parameters are obtained, the modeling technique can be classified into two approaches: the top-down approach and the bottom-up approach. In the top-down approach, the model parameters are retrieved from measurements. This approach requires little computation and is easy to implement. However, since the parameters depend on the measurement results, the model is prone to measurement errors. On the contrary, the bottom-up approach starts from theoretical derivation of model parameters. Although this approach requires more computational efforts comparing to the top-down approach, it however describes clearly the relationship between the network behavior and the model parameters. Moreover, this modeling approach is more versatile and flexible since all the parameters are formulated, making it easy to predict the changes in the transfer function should there be any change in the system configuration. The model described in this project adopts this bottom-up approach. Depending on the modeling algorithms used, the above approaches can be achieved in the time domain or the frequency domain. First frequency domain modeling, using scattering matrix is used to obtain the transfer function of the channel from which the attenuation in the signal strength and the delay or phase distortion at different frequencies is calculated. Scattering matrix gives the relationship of the incident (a) and reflected (b) waves. Broadband Power Line Communication is only interested in the transfer function in the forward direction, which is the ratio of the incident power into the receiver over the power injected by the transmitter. This can readily be expressed by b2 / a1 or S21 in the scattering matrix. Secondly, IFFT (Inverse fast Fourier transform) is used to calculate the impulse response from the channel transfer function to know the multipath environment of the power line channel in time domain modeling and an echo model is developed in Simulink to represent this physical characteristics. ByFaaDoOEngineers.com 2 Noise in LV power-line is characterized within two categories: background and impulsive noise. Many electric appliances frequently cause man-made electromagnetic noise on power-line channels. Such man-made noise produces an impulsive distortion on channel causing a burst of noise. A large impulse often causes the entire transmitted symbol to be corrupted and it can be devastating to the overall system performance. The well-known multicarrier technique, orthogonal frequency division multiplexing (OFDM), is considered as the modulation scheme for Broadband Powerline communications. By the application of OFDM, the most distinct property of power-line channel, its frequency selectivity, can be easily coped with. Moreover, OFDM can perform better than single carrier modulation in the presence of impulsive noise, because it spreads the effect of impulsive noise over multiple sub carriers. Like other communications systems, coding can improve the OFDM system performance but because of the nature of this channel, the achieved improvements are usually very restricted. Since power line technology appears to be more mature for the indoor home-networking scenario than for the outside broadband access one, focus here is on the development of channel and noise model for indoor power line network and thus designing of communication system for performance analysis of Broadband PLC using block coding techniques using software simulation in MATLAB / Simulink. In addition, network performance analysis of CORINEX Communication, Inc. Broadband PLC equipments for indoor power line network using measurements of different network characteristics parameters such as throughput and latency is performed. This project is organized as follows. Chapter 2 deals with channel modeling using transmission line analysis of indoor powerline. Noise modeling is mentioned in Chapter 3 while Broadband powerline communication system is designed in Chapter 4. Broadband PLC network performance parameters measurements are discussed in Chapter 5 while conclusion and scope for future work are mentioned at the end. ByFaaDoOEngineers.com 3 CHANNEL MODELING 2.1 TRANSMISSION LINE ANALYSIS OF POWER LINE The electromagnetic theory states that to achieve efficient point-to-point transmission of power and information, the source energy must be guided. When power lines are used to transmit high frequency communication signals, they can be regarded as transmission lines, which guide the transverse electromagnetic (TEM) waves along them. The cable under study in this project is the typical single-phase house wirings commonly found in India. The cables are made up of stranded copper conductors with PVC insulation. The three cables (live, neutral, and earth) are usually laid inside PVC conduits that are embedded inside the concrete wall. Typically, the live and neutral cables are used as the PLC transmission channel, which can be approximated as a close form of the two-wire transmission line. According to Electromagnetic theory, the two-wire transmission line must be a pair of parallel conducting wires separated by a uniform distance. In the actual installation, the power cables are simply pulled through the conduit and the separation between them is not uniform at all. However, the conduit normally has small cross-sectional area and this limits the variation of the separation between the cables. Hence, the assumption of uniform separation is reasonable in this case. Based on the above consideration, the paired power cables are regarded as a distributed parameter network, where voltages and currents can vary in magnitude and phase over its length. Hence, it can be described by circuit parameters that are distributed over its length as shown in Fig.2.1 below. Fig. 2.1 Equivalent circuit of two-wire transmission line The quantities v (z, t) and v (z +Az, t) denote the instantaneous voltages at location z and z + Az, respectively. Similarly, i (z, t) and i (z +Az, t) denote the instantaneous currents at z and z +Az, respectively. R defines the resistance per unit length for both conductors (in O / m), L defines the inductance per unit length for both conductors (in H/m), G is the conductance per unit length (in S/m), and C is the capacitance per unit length (F/m). 2.2 MODEL PARAMETERS. Based on the lumped-element circuit of a two wire transmission line as shown above, model parameters per unit length (m) are: 1.) Resistance R = 1/ taooc c cf o t / 1ByFaaDoOEngineers.com 4 Where o= skin depth = and is a function of frequency f . This effect causes an increase in the resistance of the cable and it worsens as the current frequency increases. 2.) Inductance 3.) Conductance 4.) Capacitance Where a = radius of the copper conductor, D = distance between conductors, c = permeability of copper conductor, od =conductivity of the dielectric material, and cd = permittivity of the dielectric material. 2.3 MODELING THE INDOOR POWERLINE Here the indoor power cables are approximated to be a two-wire transmission line with solid core conductor for the ease of implementation using software simulation as shown in Fig.2.2. The dielectric material, between the cable conductors, is inhomogeneous in both space (due to the round shape of the cable conductor) and contents (mixture of insulation and air). But since the cables are of close proximity to each other, the thickness of the insulationt is comparable with that of the air space between the conductors. In this model, the dielectric is assumed to be just a mixed content material and the effects of the inhomogeneous in space are neglected to keep the model tractable. Fig. 2.2 Approximate model of the power line Here, distance between the two conductors (Live and Neutral) D= 2t + 2t + 2a where t = thickness of insulation = 0.7 mm a = radius of copper conductor = 0.63 mm Therefore, D = 4.06 mm Also, Conductivity of copper o C = 5.8 x 107 S/m ) 2 / cosh() 2 / cosh() 2 / cosh(a D aCa D aGa D a Lddctctot===ByFaaDoOEngineers.com 5 Relative permittivity of dielectric [PVC (4) & air (1)] c r = 0.8 Conductivity of dielectric o d = 1 x 10-5 S/m The length of transmission line is taken to be S=5 m with shunt stub terminated in an open circuit as shown in fig.2.3 considering the fact that, indoor power lines are radial N-branched network as shown in fig.2.4 below. Fig. 2.3 Configuration of simulated network Fig. 2.4 A simplified indoor power line channel In the above figure, port 1 is the transmitter from where the signal is sent, and port 2 is the receiver where the signal strength is measured. 2.4 TRANSFER FUNCTION MODELING There are three main types of attenuation for a wave propagating in the forward direction. The first one is the line attenuation, which is caused by the heat loss and radiations along the power line. This line attenuation is always present and it depends on the length of the wave path and the frequency of the wave. The second type of attenuation is caused by reflections arising from the points of impedance discontinuities on the propagation channel. The reflected wave from the unmatched points will interfere with the original incident wave. This kind of interferences may be constructive or destructive, giving rise to attenuation if it is destructive. The last type of attenuation is caused by the delayed version of the forward propagating wave falling out of phase with the main incident forward wave, giving rise to destructive interference and hence overall signal attenuation. Thus, frequency-domain modeling approach using scattering matrix technique is used to account for all these reflected ByFaaDoOEngineers.com 6 and delayed paths in the power network. Scattering matrix gives the relationship of the incident (a) and reflected (b) waves as shown in the fig.2.5 below. Fig. 2.5 Scattering parameters Scattering parameters or S-parameters are properties used to describe the electrical behavior of linear electrical networks when undergoing various steady state stimuli by small signals.They are members of a family of similar parameters used in electronics engineering, other examples being: Y-parameters, Z-parameters, H-parameters, T-parameters or ABCD-parameters.They differ from these, in the sense that S-parameters do not use open or short circuit conditions to characterize a linear electrical network; instead matched and unmatched loads are used. Moreover, the quantities are measured in terms of power. Although applicable at any frequency, S-parameters are mostly used for networks operating at radio frequency (RF) and microwave frequencies. S-parameters change with the measurement frequency so this must be included for any S-parameter measurements stated, in addition to the characteristic impedance or system impedance. S-parameters are readily represented in matrix form and obey the rules of matrix algebra. The S-parameter matrix describing an N-port network will be square of dimension 'N' and will therefore contain N2 elements. At the test frequency each element or S-parameter is represented by a unitless complex number, thus representing magnitude and angle, or amplitude and phase. For all ports the reflected power waves may be defined in terms of the S-parameter matrix and the incident power waves by the following matrix equation: [b] = [S] [a] where S is an N x N matrix the elements of which can be indexed using conventional matrix (mathematics) notation. The phase part of an S-parameter is the spatial phase at the test frequency, not the temporal (time-related) phase. The S-parameter matrix for the 2-port network is probably the most common and it serves as the basic building block for generating the higher order matrices for larger networks. In this case the relationship between the reflected, incident power waves and the S-parameter matrix is given by: ||.|

\|||.|

\|=||.|

\|2122 2112 1121aaS SS Sbb Expanding the matrices into equations gives: and 2 22 1 21 22 12 1 11 1a S a S ba S a S b+ = + = ByFaaDoOEngineers.com 7 Each equation gives the relationship between the reflected and incident power waves at each of the network ports, 1 and 2, in terms of the network's individual S-parameters, S11 , S12, S21 and S22 . If one considers an incident power wave at port 1 (a1) there may result from it waves exiting from either port 1 itself (b1) or port 2 (b2). However if, according to the definition of S-parameters, port 2 is terminated in a load identical to the system impedance (Z0) then, by the maximum power transfer theorem, b2 will be totally absorbed making a2 equal to zero. Therefore += =111111VVabS and += =121221VVabS Similarly, if port 1 is terminated in the system impedance then a1 becomes zero,giving += =212112VVabS and += =222222VVabS Each 2-port S-parameter has the following generic descriptions: S11 is the input port voltage reflection coefficient S12 is the reverse voltage gain S21 is the forward voltage gain S22 is the output port voltage reflection coefficient. Here, S21 gives the Network Transfer Function. 2.5 DETERMINATION OF TRANSFER FUNCTION In order to find out the degree of signal degradation in the power line channel between two access point, software simulation is done using MATLAB programming to obtain the transfer function whose magnitude (dB) Vs frequency plot gives the attenuation in the signal strength and angle (radian) Vs frequency plot gives the phase distortion or delay. The MATLAB program is as given below. %Attenuation and Phase measurement h=rfckt.twowire('EpsilonR',0.8,'Linelength',5,'Radius',0.63e-003,'separation',4.06e-003,'sigmaCond',5.8e07,'sigmaDiel',1e-05,'stubmode','Shunt','termination','open'); freq=[1e6:1e6:3e7]; analyze(h,freq); figure plot(h,'s21','dB'); legend show figure plot(h,'s21','Angle (radians)'); legend show Fig.2.6 obtained after running the program shows the presence of deep notches at certain frequencies in the transfer function. These deep notches are resulted from signal reflections and multipath propagations through the power line channel. For communication to establish between two access points, the carrier frequency chosen ByFaaDoOEngineers.com 8 must not fall at deep notches. For instance, the carrier frequency between 15 MHz and 20 MHz in the cable length of 5 m will not be chosen for transmission. 0 5 10 15 20 25 30-14-12-10-8-6-4-20Attenuation (decibels)Freq [MHz]S21 Fig. 2.6 Attenuation measurement Also, Fig.2.7 shows that when there is deep notch at certain frequency in the transfer function, there is a discontinuity in the phase characteristics leading to phase distortion or delay. 0 5 10 15 20 25 30-1-0.8-0.6-0.4-0.200.20.40.60.8Angle (radians)Freq [MHz]S21 Fig. 2.7 Phase Characteristics 2.6 DETERMINATION OF IMPULSE RESPONSE In addition to the frequency dependent attenuation that characterizes the powerline channel, deep narrowband notches occur in the transfer function, which may be ByFaaDoOEngineers.com 9 spread over the whole frequency range. These notches are caused by multiple reflections at impedance discontinuities. The length of the impulse response and the number of the occurred peaks can vary considerably depending on the environment. This behaviour can be described by an echo model of the channel as illustrated in fig.2.8 below. Fig. 2.8 Echo model representing the multipath Broadband PLC channel model Complying with the echo model, each transmitted signal reaches the receiver over N different paths. Each path i is defined by a certain delay ti and a certain attenuation Ci. The Broadband PLC channel can be described by means of a discrete-time impulse response h (t) as in equation given below: if jNii iNii e C f H t C t h t tt o21 1. ) ( ) ( . ) ( = = = = Here the impulse response is calculated from the transfer function i.e. the frequency response by using Inverse Discrete Fast Fourier Transform (IFFT). %Impulse response of powerline channel G =[0.9981-0i 0.9978-0.0095i 0.9974-0.0191i 0.9969-0.0291i 0.9960-0.0397i 0.9948-0.0509i 0.9932-0.0633i 0.9909-0.0771i 0.9877-0.0929i 0.9831-0.1115i 0.9764-0.1341i 0.9660-0.1623i 0.9489-0.1992i 0.9182-0.2492i 0.8562-0.3189i 0.7118-0.4053i 0.3687-0.3819i 0.1671+0.1607i 0.5660+0.4316i 0.7984+0.3643i 0.8927+0.2830i 0.9361+0.2234i 0.9589+0.1803i 0.9722+0.1480i 0.9805+0.1227i 0.9860+0.1022i 0.9898+0.0851i 0.9925+0.0703i 0.9944+0.0572i 0.9958+0.0454i 0.9968+0.0345i]; w =[0:1e6:3e7]; Ts=pi/3e7; datafr =idfrd(G,w,Ts); datf =iddata (datafr); dat =ifft (datf); plot(dat) Impulse response plot after running the program is as obtained below. In the impulse response, the multiple propagation paths can be seen. ByFaaDoOEngineers.com 10 0 1 2 3 4 5 6 7x 10-6-101234567Time (microseconds)output 'y(t)'0 1 2 3 4 5 6 7x 10-602468Time (microseconds)input 'u(t)' Fig. 2.9 Impulse response plot at output and input, the multiple propagations paths can be seen The dominant paths of the impulse response are sufficiently covered by the simple N=6 path model from which the attenuations and delays are calculated to develop a six path echo model in SIMULINK as shown below. Impulsive noise is added in the echo channel model which is explained in the later chapters. Path Number Attenuation Cn Delay tn 1 0.875 0 2 0.1775 0.315e-6 3 0.07 0.579e-6 4 0.0525 1e-6 5 0.0375 1.3e-6 6 0.0375 1.8e-6 ByFaaDoOEngineers.com 11 Fig. 2.10 Echo model representing the multi-path channel model of Broadband PLC developed in Simulink 1Out1i mpSi gnal FromWorkspaceProduct5Product4Product3Product2Product1Productz-NDel ay5z-NDel ay4z-NDel ay3z-NDel ay2z-NDel ay1z-NDel ay0.037Constant50.037Constant40.052Constant30.07Constant20.177Constant10.875ConstantAdd1In1ByFaaDoOEngineers.com 12 NOISE MODELING 3.1 NOISE DESCRIPTION Since the power-line network is not designed for communications purposes, the channel exhibits an unfavorable frequency selective transfer function. Furthermore, this channel is distorted by impulsive noise and by severe narrowband interference. Unlike many other communication channels, power-line channel does not represent an additive white Gaussian noise (AWGN) environment. Noise in LV power-line is characterized within two categories: background and impulsive noise. Many electric appliances frequently cause man-made electromagnetic noise on power-line channels. Such man-made noise produces an impulsive distortion on channel causing a burst of noise. A large impulse often causes the entire transmitted symbol to be corrupted and it can be devastating to the overall system performance. Background noise usually consists of coloured background noise and narrowband noise. Here only coloured background noise in residential environment is considered. 3.1.1 COLOURED BACKGROUND NOISE Coloured background noise power spectral density (psd) is relatively lower and decrease with frequency. This type of noise is mainly caused by a superposition of noise sources of lower intensity. Contrary to the white noise, which is a random noise having a continuous and uniform spectral density that is substantially independent of the frequency over the specified frequency range; the coloured background noise shows strong dependency on the considered frequency. The parameters of this noise vary over time in terms of minutes and hours. For the model of the coloured background noise psd, the measurements have shown that a first-order exponential function is more adequate, as formulated by equation given below; 1/1. f fO CBN e N N N + = with No the constant noise density, N1 and f 1 are the parameters of the exponential function, and the unit of psd is dBV/Hz1/2. The psd of coloured background noise in residential environment according to [2] is given by following equation: 6 , 3 / ] [. 35 35 ) ( MHz fBN e f N + = for residential environments Matlab program for plot of coloured background noise is as given below: %Equation for coloured background noise for resi. environment function y = cbnpsd(f) y = -35 + 35*exp (-(f/6)); %coloured background noise power spectral density ByFaaDoOEngineers.com 13 f=[1:1:30]; a=cbnpsd(f); plot(f,cbnpsd(f)) title('power spectral density'); Fig. 3.1 Power Spectral density of coloured background noise in residential environment 3.1.2 IMPULSIVE NOISE The impulsive noise class is composed of the periodic impulses that are synchronous with the main frequency and the asynchronous impulsive noise. The measurements taken in [2] show that this class is largely dominated by asynchronous impulsive noise, whose impulses are mainly caused by switching transients in the networks. These impulses have durations of some microseconds up to a few milliseconds with an arbitrary interarrival time. Their power spectral density can reach value of more than 50 dB above the level of the background noise, making them the principal cause of error occurrences in the digital communication over PLC networks. One approach to model these impulses is a pulse train with pulse width tw, pulse width A, interarrival time ta and a generalized pulse function p (t / tw) with unit amplitude and impulse width tw as given by equation below: ) ( . ) (,,i wi aii imptt tp A t n = = 0 5 10 15 20 25 303530252015105 power spectral densityFrequency (MHz)dBmicrovolt / Hz 1/ 2ByFaaDoOEngineers.com 14 Fig. 3.2 The impulse model used for impulsive noise class modeling The parameters tw,i, Ai and ta,i of impulse i are random variables, whose statistical properties are measured and investigated in []. The measured impulses have shown that 90% of their amplitudes are between 100 and 200mV. Only less than 1% exceeds maximum amplitude of 2V. The measurements of the impulse width tw have also shown that only about 1% of the measured impulses have a width exceeding 500s and only 0.2% of them exceeded 1 ms. Finally, the interarrival time that separates two successive impulses is below 200ms for more than 90% of the recorded impulses. Based on the above formulation an impulsive noise is simulated using MATLAB program which is then converted to a Simulink block and then added in the channel model as shown in fig 2.10. Here, only impulsive noise is added to the channel model since they are the principal cause for burst error, and the effect of coloured background noise is neglected for the ease of software simulation Matlab program for generation of impulsive noise is as given below: % Impulsive noise plot imp=rand(1,470); n=1; while n4. ByFaaDoOEngineers.com 23 The Rectangular QAM Modulator Baseband block modulates using M-ary quadrature amplitude modulation with a constellation on a rectangular lattice. The output is a baseband representation of the modulated signal. The signal constellation has M points, where M is the M-ary number parameter. M must have the form 2K for some positive integer K. The block scales the signal constellation based on the setting of the Normalization method parameter. Possible scaling conditions for value of Normalization method parameter are: Min. distance between symbols: The nearest pair of points in the constellation is separated by the value of the Minimum distance parameter. Average Power: The average power of the symbols in the constellation is the Average power parameter. Peak Power: The maximum power of the symbols in the constellation is the Peak power parameter. The input and output for this block are discrete-time signals. The Input type parameter determines whether the block accepts integers between 0 and M-1, or binary representations of integers. If Input type is set to Integer, then the block accepts integers. The input can be either a scalar or a frame-based column vector, and can accept the data types int8, uint8, int16, uint16, int32, uint32, single, and double. If Input type is set to Bit, then the block accepts groups of K bits, called binary words. The input can be either a vector of length K or a frame-based column vector whose length is an integer multiple of K. For bit inputs, the block can accept int8, uint8, int16, uint16, int32, uint32, boolean, single, and double. The Constellation ordering parameter indicates how the block assigns binary words to points of the signal constellation. Such assignments apply independently to the in-phase and quadrature components of the input: If Constellation ordering is set to Binary, then the block uses a natural binary-coded constellation. If Constellation ordering is set to Gray and K is even, then the block uses a Gray-coded constellation. If Constellation ordering is set to Gray and K is odd, then the block codes the constellation so that pairs of nearest points differ in one or two bits. The Rectangular QAM Demodulator Baseband block demodulates a signal that was modulated using quadrature amplitude modulation with a constellation on a rectangular lattice. The settings used are shown in the fig.4.8 and fig.4.9 below: ByFaaDoOEngineers.com 24 Fig. 4.8 Rectangular QAM Modulator Baseband ByFaaDoOEngineers.com 25 Fig. 4.9 Rectangular QAM Demodulator Baseband 4.6 OFDM (Orthogonal Frequency Division Multiplexing) 4.6.1 Modulation Principles MultiCarrier Modulation (MCM) is the principle of transmitting data by dividing the stream into several parallel bit streams, each of which has a much lower bit rate, and by using several carriers, called also subcarriers, to modulate these substreams. Orthogonal Frequency Division Multiplexing is a special form of MCM with densely spaced subcarriers and overlapping spectra. To allow an error-free reception of OFDM signals, the subcarriers waveforms are chosen to be orthogonal to each other. In spite of its robustness against frequency selectivity, which is seen as an advantage of OFDM, any time-varying character of the channel is known to pose limits to the system performance. Time variations are known to deteriorate the orthogonality of the subcarriers. ByFaaDoOEngineers.com 26 4.6.2 Generation of OFDM Signals The generation of the OFDM symbols is based on two principles. First, the data stream is subdivided into a given number of substreams, where each one has to be modulated over a separate carrier signal, called subcarrier. The resulting modulated signals have to be then multiplexed before their transmission. Second, by allowing the modulating subcarriers to be separated by the inverse of the signaling symbol duration, independent separation of the frequency multiplexed subcarriers is possible. This ensures that the spectra of individual subcarriers are zeros at other subcarrier frequencies, consisting of the fundamental concept of orthogonality and the OFDM realization. Fig. 4.10 shows the basic OFDM system. The data stream is subdivided into N parallel data elements and are spaced by At = 1/fs, where fs is the desired symbol rate. N serial elements modulate N subcarrier frequencies which are then frequency division multiplexed. The symbol interval has now been increased to N At which provides robustness to the delay spread caused by the channel. Each one of two adjacent subcarrier frequencies is then spaced by the interval formulated by equation: t N f A = A . / 1 This ensures that the subcarrier frequencies are separated by multiples of 1/T where T in this phase is the OFDM symbol duration, so that the sub carriers are orthogonal over symbol duration in the absence of distortions. Fig. 4.10 Basic OFDM Transmitter According to the basic OFDM realization, the transmitted signal s(t) can be expressed by ( ) lT t k b t sNk lk l == =10] [ ) ( with the pulse having the function p(t) and fk = k/T, each subcarrier can be formulated by ByFaaDoOEngineers.com 27 ( ) ( ) t f jkke t p t t2. = The basis {1 1 0, , N } is orthogonal, therefore ( ) ( ) k i ifk i ifdt t t iTK= = =}, 0, 1{*0 Then the transmitted signal can be expressed as | | ( ) t f jNk llke lT t p k b t s t 210. ) ( == = By sampling at a rate Ts= T/N | | | | ( )S S NT knT jNS SNk ll e lNT nT k b n x/ 210. ] [ t[ = = = | | | | N kn jNk l Nl e lN n k b n x/ 210. ] [ t [= = = with | | ( )otherwiseN l n lN forlN nN + s < = [, 0) 1 ( , 1{ the signal can be presented in the form | | | | N kn jNKll Ne k b lN n n x/ 210. ] [ t [ = = = | | ) , ( . ] [ n b IDFT lN n n x ll N[ = = where IDFT is Inverse Discrete Fourier Transform. From the above derivation, it can be deduced that for the generation of the OFDM signals x[n] an IDFT block processing is required. The OFDM signal generation can be further optimized by calculating the IDFT of the original signals by the mean of the Inverse Fast Fourier Transform (IFFT). The blocks used in Simulink for OFDM Transmitter and OFDM Receiver are shown in fig.4.11 and fig.4.12 respectively. ByFaaDoOEngineers.com 28 1OutZero padfor OFDMZero pad for OFDMUni pol ar toBi pol arConverterPN SequenceGeneratorPN SequenceGeneratorSel ectRowsMul ti portSel ectorVert CatMatri xConcatenati on IFFTIFFT-10+0i U U(E)Add Cycl i cPrefi x1In Fig. 4.11 OFDM Transmitter 2PIl ots1DataU U(E)Remove Cycl i cPrefi xSel ectRowsRemovePi l otsU U(E)Remove zero-paddi ngandreorderToFrameFrame StatusConversi on FFT FFT1Recei ved si gnalDataPilots Fig. 4.12 OFDM Receiver 4.7 DATA SOURCE 4.7.1 Bernoulli Binary Random Generator The Bernoulli Binary Generator block generates random binary numbers using a Bernoulli distribution. The Bernoulli distribution with parameter p produces zero with probability p and one with probability 1-p. The Bernoulli distribution has mean value 1-p and variance p(1-p). The Probability of a zero parameter specifies p, and can be any real number between zero and one. The number of elements in the Initial seed and Probability of a zero parameters becomes the number of columns in a frame-based output or the number of elements in a sample-based vector output. The settings used for simulation are shown in fig.4.13 below: ByFaaDoOEngineers.com 29 Fig. 4.13 Bernoulli Random Binary Generator 4.8 DATA SINK 4.8.1 Error Rate Calculation The Error Rate Calculation block compares input data from a transmitter with input data from a receiver. It calculates the error rate as a running statistic, by dividing the total number of unequal pairs of data elements by the total number of input data elements from one source. This block can be used to compute either symbol or bit error rate, because it does not consider the magnitude of the difference between input data elements. If the inputs are bits, then the block computes the bit error rate. If the inputs are symbols, then it computes the symbol error rate. This block inherits the sample time of its inputs. This block produces a vector of length three, whose entries correspond to: - The error rate. - The total number of errors, that is, comparisons between unequal elements. - The total number of comparisons that the block made. The Receive delay and Computation delay parameters implement two different types of delays for this block. One is useful when part of the model causes a lag in the received data, and the other is useful when one want to ignore the transient behavior of both input signals: - The Receive delay parameter is the number of samples by which the received data lags behind the transmitted data. This parameter tells the block which ByFaaDoOEngineers.com 30 samples "correspond" to each other and should be compared. The receive delay persists throughout the simulation. - The Computation delay parameter tells the block to ignore the specified number of samples at the beginning of the comparison. The settings used in the simulation are as shown in fig. 4.14 below. Fig. 4.14 Error Rate Calculation settings 4.8.2 DISPLAY The Display block shows the value of its input on its icon. The amount of data displayed and the time steps at which the data is displayed are determined by block parameters: - The Decimation parameter enables to display data at every nth sample, where n is the decimation factor. The default decimation, 1, displays data at every time step. - The Sample time parameter enables to specify a sampling interval at which to display points. This parameter is useful when using a variable-step solver ByFaaDoOEngineers.com 31 where the interval between time steps might not be the same. The default value of -1 causes the block to ignore the sampling interval when determining the points to display. The settings used are: Fig. 4.15 Display block settings. 4.9 SIMULATION AND RESULTS Communication system is designed in Simulink with each block simulated as a different subprogram as shown in fig.4.16 below. Uni pol ar toBi pol arConverterUni pol ar toBi pol arConverterTermi natorRectangul arQAMRectangul ar QAMModul atorBasebandRectangul arQAMRectangul ar QAMDemodul atorBasebandRandomInterl eaverRandomInterl eaverRandomDei nterl eaverRandomDei nterl eaverIn1Out1PLC ChannelPunctureP2 PunctureOFDMTransmi tterOFDMRecei verpi l otsInsert ZeroInsert ZeroHammi ng enHammi ng EncoderHammi ng deHammi ng DecodersRefsDeldelayFi ndDel ayFi nd Del ay Error Rate Cal cul ati onTxRx0Di spl ay10Bernoul l iBi naryBernoul l i RandomBi nary GeneratorBRBR Fig.4.16 Simulink model of the Broadband powerline communication system. ByFaaDoOEngineers.com 32 The display block showed the following bit error rate as shown in fig.4.17 below obtained after running the model i.e. when both channel multipath effect and the effect of impulsive noise is considered. Fig.4.17 Bit Error Rate when the effect of both multipath and impulsive noise is considered. Now, when the effect of impulsive noise is neglected from the model than the bit error rate obtained is as shown in fig.4.18 below: Fig.4.18 Bit Error Rate when effect of only multipath effect is considered. From the above figures it is seen that both impulsive noise and multipath effect have a very adverse effect on the BER. Moreover it is also seen that BER caused by multipath effect almost does not change even when the effect of application of impulsive noise is neglected. Thus, it can be concluded that the main obstacle to achieve the good BER performance of the OFDM system is the multipath effect. The plot of BER versus SNR is drawn using bertool in MATLAB under the effect of both multipath effect and impulsive noise as shown below in fig.4.19. An almost constant BER is obtained up to SNR of 10 dB. ByFaaDoOEngineers.com 33 Fig.4.19 BER under the effect of both impulsive noise and multipath effect ByFaaDoOEngineers.com 34 BROADBAND PLC NETWORK PERFORMANCE PARAMETERS MEASUREMENT 5.1 BROADBAND PLC EQUIPMENTS Head End (HE): Communication infrastructure module for injection of PLC signal over Low voltage electrical network. Customer Premises Equipment (CPE): Ethernet Bridge switch 10/100 Mbps by PLC, designed for connection of end-user multimedia devices through any power outlets. The Broadband PLC equipments used for performance analysis network are of CORINEX Communications, Inc. The Corinex AV200 Powerline Adapter can be configured both as a Head End as well as a Customer Premises Equipment by changing settings in its configuration files in the firmware. It enables users to connect individual PCs or other devices with Ethernet communications links into a local area network through existing electric power lines (Powerline). After successful installation, the AV Powerline network behaves like a traditional LAN for computers. The Corinex AV200 Powerline Adapter supports up to 200 Mbps network speed. Front Panel Description Fig 5.1: Corinex AV200 Powerline Adapter front view LED Definitions (LEDs from left to right) 1. POWER Green On: Power on Off: Power off 2. PLC Green On: Powerline activity Off: No Powerline activity Blinking: Receiving/Transmitting data 3. ETHERNET Green On: Link on LAN Off: No link on LAN Blinking: receiving/transmitting data ByFaaDoOEngineers.com 35 Rear Panel Description Fig 5.2: Corinex AV200 Powerline Adapter rear view Connector Definitions (Connectors from left to right) 1. LAN: 1x RJ-45 LAN10/100 Ethernet port 2. Power cord: Power supply & Powerline connector Specifications: Standards Compliance: IEEE 802.3u Speed: Up to 200 Mbps on physical layer AC Plug Type: US, EU, UK and AUS LED Status Lights: Power, PLC Link/Activity, Ethernet Link Interface: 10/100BaseT Fast Ethernet, Powerline Frequency Range used: 2 34 MHz Power Input: 85 to 265 V AC, 50/60 Hz Dimensions: 148 mm L x 106 mm W x 47 mm H Transmitted Power spectral density: -56 dBm/Hz Power Consumption: 5W Safety & EMI:UL/EN 60950, FCC Part 15, EN 55022 EMC limits 5.2 BROADBAND PLC NETWORK Network performance analysis of CORINEX Communication, Inc. Broadband PLC equipments for indoor power line network using measurements of different network characteristics parameters such as throughput and latency is conducted for the network as shown in fig.5.3 below: ByFaaDoOEngineers.com 36 Fig.5.3 SCADA Lab Broadband PLC network. The throughput is a measure of how fast the data can be sent through the network. It is different from the bandwidth in the sense that a link may have bandwidth of B bps, but only T bps can be sent through this link with T always less than B. Bandwidth is a potential measurement of a link. The measurements obtained for different CPEs (Customer Premises Equipment) both in uplink (i.e. from the CPE to the Head End) and the downlink (i.e. from the Head End to the CPE) direction is as measured below. ByFaaDoOEngineers.com 37 Fig.5.4 Telnet screen showing throughput. The latency or delay defines how long it takes for an entire message to completely arrive at the destination from the time the first bit is sent out from the source. It is made up of four components: propagation time (time required for a bit to travel from the source to the destination equal to the distance divided by the propagation speed), transmission time (depends upon the message size divided by the bandwidth), queuing time (time needed for each intermediate or end device to hold the message before it can be processed, it is not a fixed factor, it changes with the load imposed on the network) and processing delay. It is calculated by using the ping program. ByFaaDoOEngineers.com 38 Measurement of throughput and latency for different CPEs is shown in Table 5.1 in tabular form as shown below: TABLE 5.1: Measurement of Throughput and Latency Customer premises Equipment (CPE) no. Transfer speed [ Mbps ] Latency [ ms ] Distance with respect to Head End (HE) DL UL A 50 55 7 ~ 14 < 15 m B 65 66 -do- < 15 m C 101 63 -do- > 15 m It is seen that broadband plc promises high bit rate in terms of throughput. Latency measured using ping program almost remains same with distance. However, throughput for CPE C almost doubles due to straight wire connection with respect to other CPEs which belong to a branched network of the SCADA Lab. ByFaaDoOEngineers.com 39 CONCLUSION AND FUTURE WORK Bit Error Rate (BER) of the OFDM system under both impulsive noise and multipath effect is calculated & it is seen that they have a very adverse effect on the BER. Moreover it is also seen that BER caused by multipath effect almost does not change with the application of impulsive noise. Thus, it can be concluded that the main obstacle to achieve the good BER performance of the OFDM system is the multipath effect. It is seen that broadband plc promises high bit rate with measurements taken on a real Broadband PLC network. Latency measured using ping program almost remains same with distance. However, throughput for CPE C almost doubles due to straight wire connection with respect to other CPEs which belong to a branched network. The main purpose of this work was the designing of the Broadband powerline communication system using software simulation and to do performance analysis in terms of bit error rate and as well as to test the real system in terms of their network performance parameters. However, for future work performance enhancement of the system can be done in terms of the bit error rate and the real system can be used for different utility applications like automatic meter reading (AMR), transformer monitoring, etc. ByFaaDoOEngineers.com 40 REFERENCES [1] C W Gellings and K George, Broadband over power lines 2004: Technology and Prospects", Electric Power Research Institute (EPRI),USA, Oct 2004. [2] H. Hrasnica, A. Haidine, and R.Lehnert, Broadband Powerline Communications. London, U.K.: Wiley, 2004. [3] H. Meng, S. Chen, Y. L. Guan, C. L. Law, P. L. So, E. Gunawan, and T.T. Lie, "Modeling of transfer characteristics for the broadband power line communication channel, IEEE Trans. Power Del., vol. 19, no.3, Jul. 2004, pp. 10571064. [4] Ludwig, Reinhold and Pavel Bretchko, RF Circuit Design: Theory and Applications, Prentice-Hall, 2000. [5] P Amirshahi, S M Navidpour and M Kavehrad, Performance Analysis of uncoded & coded OFDM Broadband transmission over low voltage power line channels with impulsive noise, IEEE Trans. Power Del., vol. 21, no.4, Oct. 2006, pp. 1927-1934. [6] S. Galli and T. Banwell, A novel approach to the modeling of the indoor power line channel-part II: Transfer function and its properties, IEEE Trans. Power Del., vol. 20, no. 3, Jul. 2005, pp. 18691878. [7] V C Gungor and F C Lambert, A survey on communication networks for Electric system automation, ELSEVIER Journal of computer networks 50(2006), pp 877-897. [8] Y H Ma, P L So and E Gunawan, Performance analysis of OFDM systems for Broadband power line communications under impulsive noise and multipath effects, IEEE Trans. Power Del., vol. 20, no. 2, Apr. 2005, pp. 674-682.