Evaluation of Code Division Multiplexing on Power Line Communication

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1 Evaluation of Code Division Multiplexing on Power Line Communication Adriano Favaro and Eduardo Parente Ribeiro Department of Electrical Engineering, Federal University of Parana CP 90, CEP Curitiba, PR, Brasil Phone: , , Fax: adrianofavaro@pop.com.br, edu@eletrica.ufpr.br Keywords: spread spectrum technique, Synchronous Code Division Modulation, power line communication. Abstract: Data transmission using power line has awaked interest due to many factors: money savings by the use of infrastructure already available; ease of use; possibility to apply new technologies to home appliances and others. Since there is no accepted noise model for power line channel and fewer mathematical formulation to facilitate analytical analysis one way to approach the problem is through Monte Carlo simulation. This present work suggests a simulation scenario to investigate CDM (Code Division Multiplexing) for Power Line Communication. The following kinds of interferences were studied: AWGN, multipath effect, asynchronous impulsive noise and periodic impulsive noise.. INTRODUCTION Communication using the power line is not a new topic but it has became important some years ago []. The most important advantage in using power line as transmission media is that it is widely spread and can be easily accessed through the wall outlet. It is available at homes, offices, buildings, factories and so on. Data transmission using this media is economically attractive because the investments in infrastructure were already done when power line was installed. For this reason, power line communication is called no new wire technology. Also, power line communication can speed up the introduction of new application such as: home automation, online metering, control application, internet access and so on.. Power Line Channel The use of power line as communication media is a challenging task due to innumerous disturbances. Usually loads are randomly switched on and off, equipments like dimmers introduce a lot of noise and non linearity. Many works has been done in order to model the power line channel in terms of noise sources, impedance and attenuation. The difficulties usually found in the power line channel are: frequency response is both time and location dependent; characteristics change quickly; fading and reflection effects; impulsive noises; impedance modulation. The modeling problem is not solved and there is not a universally recognized model as for mobile radio channels or telephone channels [][2]. The characteristics of the power line channel normally rule out the standard modulation scheme used for data communication (ASK, FSK, PSK, QAM) [3]. In order to overcome these challenges some works have suggested the use of spread spectrum techniques..2 Spread Spectrum Spread spectrum was initially developed to avoid intentional noise introduction in military communication and also to guarantee secrecy [4][5]. This is a technique that makes a signal occupies a bandwidth grater than necessary to transmit the information. This technique allows more than one user to transmit at the same frequency and time but each one modulates their information using different special codes. These special codes are random-like so they are called pseudo-random. The most important spread spectrum technique is CDMA (Code Division Multiple Access). It has been studied a lot mostly because it is important application in wireless networks and mobile phones. Recently it has been also studied for power line communication [2][6][7]. There is a variant of CDMA technique called CDM (Code Division Multiplexing) that seems to be under looked in power line communication or in wireless communication. This is the focus of this work..3 CDMA and CDM The CDMA system is based on the users information modulated using the spread spectrum technique called Direct Sequence. In order to modulate information using direct sequence, the information bits are replaced by a pseudorandom code or it complementary code depends on if the information is or 0. Figure shows a signal modulated in direct sequence using eight bits Hadamard-Walsh code.

2 Information 0 PN Code Walsh W Direct Sequence Signal Figure Signal modulated in direct sequence Each user of CDMA system has a different code assigned and uses it to modulate the information to be transmitted. All the users signals modulated in direct sequence are transmitted at the same frequency and time. So, the users information is mixed both in time and frequency domain. Only the code each information was modulated is different [8]. Figure 2 shows this principle in wireless environment. As the figure suggest, the original information bandwidth of each user is spread out by the process gain at the direct sequence modulator. The direct sequence modulator can be implemented using over sampled digital filter FIR with coefficient equal the pseudo-random code [7]. If orthogonal pseudo-random code and narrowband synchronous CDMA (Tc >> max) are used, than to demodulate the information a matched filter followed by a symbol rate sampler can be used [8]. Code Division Multiplexing is a particular case of CDMA. Instead allocate pseudo-random codes to each user as CDMA does, CDM allocate them to each bit of information and transmit them simultaneously (in parallel). So, CDM is actually a multiplexing scheme and not multiple accesses. 2. SYSTEM CONCEPT Figure 3 shows the block diagram for the system proposed with CDM technique. First, the information is converted from serial to parallel format. Each bit is modulated in direct sequence using one of the eight bit Hadamard-Walsh codes. At DSP level the signals modulated in direct sequence are digitally added to form the CDM signal. The CDM signal is transmitted using a QAM stage. The QAM stage maps the baseband CDM signal to passband signal using eight point constellations. The QAM stage receives 256k symbol/s and transmits using 500 khz sinusoidal carrier sampled with ksample/s. The passband signal plus the channel noise is received and remapped to baseband CDM signal. The CDM signals are demodulated using digital filters FIR whose coefficients are Hadamard-Wash codes in reversal order [7]. Finally the bits can be converted to serial format again. Information BER Calc. CDM Modulator CDM DeMod. SNR Meter QAM 8 Modulator QAM 8 DeMod. Channel Figure 3 CDM functional blocks IN IN 2 IN 3 DS MOD DS MOD2 DS MOD3 Figure 2 CDMA Principle f 2. Simulation Scenario Simulink is a graphic user interface of MatLab [mathworks] that allows insertion of blocks like noise source, channel model, modulator scheme or spectrum analyzer. For example, it is easy to change the spread spectrum codes from Hadamard-Walsh to Gold codes or m-sequence and study the system performance. Also, it is easy replaces the QAM-8 Modem by PSK-8 or generic constellation QAM-8 Modem. Different kind of noise can be inserted to study the system performance. MatLab version 6.0 was used to evaluate the system. A computer equipped with K6-II-500MHz CPU and 28M RAM memory was enough to run the simulations. The Figure 4 shows in detail the CDM modulator. Each bit is up sampled and fed to FIR filter. The signals

3 modulated in direct sequence are added and converted to CDM binary format. The most important parameters for each block are described in details below. Information block: A Random Integer Generator block is used to provide seven bits information data. The information is converted to parallel format using Integer to bit Converter and Demux blocks. Three parameters can be set at Integer Generator block: M-ary number, initial seed and sample time. To get 224kbps data rate the sample time must be set to / As the CDM modulator needs information in bipolar format for implement direct sequence modulator with filter FIR, the bits are converted to bipolar format before leave this block. This is can be implemented with two mathematic operations: multiplying by two and subtracting by one. Figure 4 CDM modulator Figure 5 shows the CDM demodulator as it was implemented at Simulink. First the CDM signal is converted to bipolar format. The eight sample delay block is necessary to force synchronization of the CDM signal. Synchronization mechanisms were not addressed in this work. The FIR decimation blocks demodulate the CDM signal and output value whose signal represents the information bits in bipolar format. CDM Modulator: To build the direct sequence modulator, Upsampler and FIR decimation block is used. On Upsampler the upsampler factor is set to eight. On FIR decimation block, the decimation factor is set to one and the FIR filter coefficients are vectors choose from eight bits Hadamard-Walsh codes in bipolar format. Each Hadamard-Wash code is associate to each FIR filter to implement the modulator, that means: bit is modulated with W [ ], bit2 is modulated with W 2 [ ] and so on. The system was designed to transmit seven bits in parallel. So, the Hadamard-Walsh code W 0 was not used. The direct sequence signals are added using the sum block to form CDM signal. As bipolar format was used in the previous stage, the CDM signals ranges between -8 to 8 in steps of 2 (CDM bipolar format ). The QAM block accepts only non-negative inputs. So, the CDM signal is converted in order to stay in the range 0 till 8 in steps of (CDM binary format ). QAM Modulator: The passband signal is generated using Rectangular QAM modulator Passband from communication blockset. On it, the M-ary is set to eight, input type is integer, minimum distance is one, symbol period is /256k, baseband samples per symbol is one, carrier frequency is 500kHz, carrier initial phase is zero and output sample time is /2.048k. The QAM block has some constrains between symbol frequency, carrier frequency and sample frequency that must be respected QAM demodulator: At the receptor side, Rectangular QAM demodulator passband is used to recover the baseband CDM signal. The same parameters used for the QAM modulator must be used for the demodulator. Figure 5 CDM demodulator CDM demodulator: The CDM signals are converted again to CDM bipolar format before getting into the direct sequence demodulator. The direct sequence demodulators are built with FIR decimation block. The decimation factor is

4 set to eight because eight bit Hadamard-Walsh codes were used. The FIR filter coefficients are the eight bits from Hadamard-Walsh codes in bipolar format and in reverse order. For example the coefficients for W are [ ]. To have the information in bipolar format, signals pass through Sign function block before leave the CDM demodulator stage. Error rate calculation: to evaluate bit error rate (BER) seven Error Rate Calculation blocks are used. Due to internal delays the parameters receive delay and computation delay must be set to two. The outputs of error rate calculation blocks are added to have total rate error instead of per bit error rate. The total BER must be recalculated because it can t be obtained by summing individual BER. The Demux block is used to separate the three vector elements (BER, error number and number of bits). The second and third elements are connected to product block to calculate the total BER (error number divide by number of bits). A Mux block is used to recover the error vector with three elements that will be shown at Display block. SNR Meter block: In order to know the signal to noise rate the block showed in Figure 6 was implemented. The following blocks are used: Math function, Mean, db Conversion, Frequency Down Converter, Product. SNR is determined by the mean signal power divide by mean noise power at receiver input. The Frequency Down Converter is used to convert signals to baseband. To determine the noise, signal plus noise and signal basebands are subtracted. To determine the mean power, the signal or noise passes through the Math function that computes the square value for each input. After that, the signal or noise passes through the Mean block that computes the mean value overtime ( Running mean must be selected at Mean block). The mean signal and noise powers are connect to the product block to determine SNR. The parameter number of input of Product block must be set to /* if the noise is connected at the first port and signal at second. Finally, the SNR is converted to db using the db Conversion block with parameter input signal set to power. 2.2 Interference Models Since there is no universally recognized model for PLC [][2] some interference models were proposed to study CDM performance. AWGN Channel: the Figure 7 show the scheme used to simulate the AWGN noise channel. A Gaussian Noise Generator was used. Its mean value was set to zero; variance was set according to SNR investigated; initial seed was 2345 and sample time was /2.048k. The output of Gaussian Noise Generator is added to the output of Rectangular QAM Modulator Passband to add noise to the passband signal. In Gaussian Gaussian Noise Generator Out Figure 7 AWGN interference Multipath Interference: In order to simulate the reflective effect a filter FIR was used. It was used eight order FIR filter to simulate the main path and seven reflected paths. The delayed version of the signal causes inter-symbol interferences. The coefficient for the main path was changed from 0,55 till 0,82 to produce different SNR values. The coefficients for each path were set decreasing with the path number. In x[n] Multipath Model Out Figure 8 Multipath Model Periodic Impulsive Noise: to simulate noise like that produced by switched power supplies, the scheme showed by Figure 9 was used. Figure 6 SNR Meter

5 is well-know. The Figure shows the calibration results for our simulation. In Out -K- Gain BER - QAM 6 QAM 6 Theoretical QAM6 Simulink Band-Limited White Noise Zero-Order Hold,00E+00,00E Ground Discrete Pulse Generator Rst N-Sample Switch,00E-02,00E-03 Figure 9 Periodic Impulsive noise source One random noise sample is take each / s and add to the signal to produce the periodic interference. Asynchronous Impulsive Noise: to simulate the noise produced by turn equipments on and off the scheme showed by Figure 0 was used. A periodic impulsive noise is randomly delayed to produce an asynchronous impulsive noise. The maximal delayed used at delay block was a hundred and the M-ary of Random Integer Generator was set to 00 with sample time / ,00E-04 Eb/No Figure Calibration using QAM6 The BER curve for the system with CDM was compared with pure QAM-8. The BER curves were gotten changing the variance of Gaussian Noise Generator Block from 0, till 2,5 and the simulation ran till at least 00 errors be reached. To get around 0-5 bit error rate the simulation ran more than 0 hours using K6-II-500MHz CPU. The Eb/No is obtained using the relation SNR=Eb/No*R/W and the SNR metered by the system. R is the data rate and W is the baseband bandwidth at receptor input. For the system without CDM R=768kbps and W=256kHz while for the system with CDM R=224kbps and W=256kHz. Figure 2 shows the result simulation for CDM/QAM-8 under AWGN noise. BER for AWGN Noise QAM 8 CDM8,00E ,00E-0,00E-02,00E-03 Figure 0 Asynchronous Impulse Noise source 3. SIMULATION RESULTS In order to assure that the SNR measure block and the QAM blocks was working as expected, it was simulated a single data transmission (without CDM stage) using QAM-6 Modulation- Demodulation. The QAM-6 modulation was chosen because its theoretical bit error rate curve,00e-04,00e-05,00e-06 Eb/No (db) Figure 2 BER curve for AWGN noise The BER curve for AWGN shows that for bit error rate of 0-3 the scheme using CDM8 is around 0,25dB worst than QAM8.

6 Figure 3 shows the BER curve for multipath effect. It was defined Jo as the value of power spectral density of an equivalent wideband interference and it is defined as the rate of average noise power by the receptor bandwidth (W=256kHz). The curve for AWGN was included at the same graphic just for comparing the performance. The graphic shows that for BER of 0-3 the Modem with CDM8 is around 3dB better than a pure CDM8 Modem.,0E-0,0E-02,0E-03,0E-04,0E-05,0E-06,0E-07 CDM8 x QAM8 for MultiPath Effect ,0E+00 Eb/Jo (db) QAM8 with AWGN CDM8 with AWGN QAM 8 - Multipath CDM8 - Multipath Figure 3 Performance for Multipath effect The Figure 4 shows the simulate results for periodic and asynchronous Impulsive Noise.,0E-0,0E-02,0E-03,0E-04,0E-05,0E-06 CDM8 x QAM8 for Impulsive Noise ,0E+00 Eb/Jo (db) Figure 4 Performance for Impulsive Noise QAM8 with Periodic CDM8 with Periodic QAM8 with Asynchronous CDM8 with Asynchronous The graphic shows that for QAM8 Modem there is no difference if the impulsive noise is periodic or asynchronous. Also it shows that asynchronous impulse noise is worst for CDM8 than periodic impulsive noise. For periodic impulsive noise and bit error rate of 0-3 the CDM8 is around 5dB better than QAM8. While for asynchronous impulsive noise and the same BER CDM8 is only 2dB better than QAM8. 4. CONCLUSION We developed a simulation environment using Simulink to evaluate the use of Code Division Multiplexing for Power Line Communication. It was tested for AWGN channel, multipath effect, periodic impulsive noise and asynchronous impulsive noise. The investigation for AWGN noise shows that CDM is 0,25dB worst than QAM modulation for BER of 0-3. But for the others kind of interference usually found in PLC channel we saw CDM can be 5dB better than QAM for BER of 0-3. The simulation environment proposed allow easy testing for other spread spectrum modulation configurations under different types of noise where there is no available mathematical formulation to evaluate BER. REFERENCES [] CHEN Y., Chiueh T., Baseband Transceiver Design of a 28-kbps Power-Line Modem for Household Applications, IEEE transactions on Power Delivery, Vol. 7,p , April [2] BIGLIERI E., Coding and Modulation for a Horrible Channel, IEEE Communication Magazine, May, [3] SLISKOVIC M., Robust Digital Receiver for Frequency Redundant Digital Communications over Power Lines, IEEE, 999. [4] VITERBI A. J., CDMA Principles of Spread Spectrum Communication, Addison Wesley Longman, Massachusetts, 995 [5] MEEL J., Spread Spectrum (SS), Hogeschool Voor Wetenschap [De Nayer Instituut], Belgium, V2 dec 999. [6] MARABAYASHI G., Tachikawa S., Spread Spectrum Transmission on Residential Power Line, IEEE 4th International Symposium on Spread Spectrum Techniques and Applications Proceedings, Vol. 3, p , September 996. [7] OUVRY L., Hachem W., Lattard D., Laugeois M., Piaget B., Implementing DSSS-CDMA in Powerline Communication, WTC 02, Paris, September [8] LIU H., Signal Processing Applications in CDMA Communications, Artech House Publishers, Boston London, 2000.

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