Computer and Information Science; Vol. 9, No. 4; 2016 ISSN 1913-8989 E-ISSN 1913-8997 Published by Canadian Center of Science and Education
Simulating the Performance Characteristic of Passband Modulation Techniques in MATLAB Environment Saed Thuneibat1, Abdallah Ijjeh1, Huthaifa Al_Issa1 & Mousa Ababneh2 1
Department of Electrical Engineering, Al-Balqa Applied University, Jordan
2
Department of Finance and Administrative Sciences, Al-Balqa Applied University, Jordan
Correspondence: Saed Thuneibat, Department of Electrical Engineering, Al-Balqa Applied University, Jordan. E-mail:
[email protected] Received: May 19, 2015 doi:10.5539/cis.v9n4p52
Accepted: June 21, 2015
Online Published: October 31, 2016
URL: http://dx.doi.org/10.5539/cis.v9n4p52
Abstract Now days, digital communication systems become complex and sophisticated. Not all vendors, if any, can understand the system and components of system that represent different modulation techniques, line and block coding, multiplexing and multiple access. They need the conclusion about which of modulation techniques is the suitable for transmission and in the same time can save the power and bandwidth. Engineers can study and analyze the modulation techniques and then compare between them to give such conclusion using modeling and simulation. MATLAB is a high level mathematical language for technical computing. In this paper we use MATLAB environment as simulation software to give on display a clear result that used to compare between two digital Passband modulation techniques BPSK and QPSK, and pinpoint the performance of the two techniques over selected parameters. Keywords: simulation, modulation, performance parameters, MATLAB 1. Introduction Nowadays, digital modulation techniques are the most widely used in communication systems. We need to achieve higher data rates in limited bandwidth of spectrum to improve the performance of transmission. A great deal of interest for a digital Passband digital transmission system that is bandwidth efficient with low signaling rate and high data rate and provide low Bit Error Rate (BER) at a relatively low Signal to Noise Ratio (SNR). Various digital modulation schemes are well described in different literatures but cannot fulfill actual requirement in different kind of varying environment until studded and analyzed. Recently, a large number of research papers which study the modulation techniques were published. In (Masud, 2010), authors have investigated the performance analysis of M-ary modulation techniques when the digital communication system is subjected to Additive White Gaussian Noise (AWGN) and multipath Rayleigh fading in the channel. The study has been performed by using MATLAB program for the simulation and evaluation of BER and SNR for W-CDMA system models. It shows that the analysis of quadrature phases shift key and 16-ary quadrature amplitude modulations which are being used in wideband CDMA system, Therefore, the system could go for more suitable modulation technique to satisfy the channel quality, thus can deliver the optimum data rate to mobile user. The paper (Samson, 2013) analyzed the performance of different passband modulation techniques in AWGN channel and multipath fading channel. This study examined the inherent attributes of the digital modulation to overcome the channel impairments and was carried out to understand the contributions of channel characteristics to effective wireless communication and made comparison between the two channels. The BER for simulated modeled channels agreed with the theoretical results. It was found that the performance of 64-QAM is better compared to other passband modulation schemes in AWGN Channel. It was also observed that the BER is higher in frequency selective channel as compared to the AWGN channel and was also observed that multipath fading 52
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channel chharacteristic lim mits the data raate in wireless communicatioon. Authors inn (Hemant, 2014) have preseented the impaact of various m modulation paarameters towaards the modulation and demoddulation proceesses. In additiion, it has beenn proven that M MATLAB sim mulation enviroonment can pla ay an important role towards thhe understandiing of subject matter. mi, 2011), a general theoretical approacch in studding various M--ary modulation schemes using u In (Rashm MATLAB taking the BE ER as the meassure of perform mance when thhe system is aaffected by AW WGN and multipath Rayleigh ffading channell is developed.. Based on theese performancces a desirable modulation sccheme is simu ulated that providdes low BER at low receivved SNR, perrforms well inn multipath annd fading condditions, occupies a minimum of bandwidth and is easy and cost effectivve to implemennt in modern coommunicationn system. Xiaolong, 2008), authors are iimplementing various binary y and In (Virenddrakumar, 20144), (Tharakanaatha, 2013), (X M-ary moddulation schem mes in MATLA AB by using diifferent SIMUL LINK tool boxxes. An efficieent and effective methodoloogy for teaching digital annd analog moddulation typess to undergrad duate students eenrolled in ann Information Technology program whiich does not require a stroong foundatio on in mathematiics as in the caase of engineering program is provided in (Boulmalf, 20010). The implemented apprroach utilizes M MATLAB program, SIMUL LINK, and C Communicatioon Blockset tto simulate ddigital modulation techniquess avoiding the derivation of m mathematics foormulations annd without com mplex coding. Research paper containns introductionn to the subjeect with literaature review. Section 2 intrroduces MATLAB software aand environmeent. 3d section presents the siimulation of m modulation andd demodulationn process in BPSK B and QPSK K using MATL LAB environm ment. Sections 4-7 devoted for the perforrmance parameeters, data rate e, bit error rate, capacity, PSD D respectively. Finally, concluusion and literaature referencees are includedd. 2. MATLA AB Software and a Environm ment MATLAB is a mathemaatical computinng environmennt with 4th genneration prograamming languuage and intera active environmeent that enablees engineers to perform intensive calculaations based taasks very sim mply. Develope ed by Math workks (http://www w.mathworks.ccom), MATLA AB allows matrrix manipulatioon, plotting off functions and d data in tables aand curves, impplementation oof algorithms, creation of usser interfaces, and interfacingg with program ms in other languuages. MATLA AB has been w widely adoptedd in the academic communitty, industry annd research cen nters. It was origginally writtenn to provide eeasy access to LINPACK annd EISPACK ssoftware packkages (Gilat, 2004), (www.matthworks.com/pproducts/simulink), (Quarterroni, 2006), (F Ferreira, 2009)), (Leon, (20001). The MATLAB software pprovides the reesearchers withh a large colleection of toolbooxes and moddules for a variiety of applica ations in many fields of interest. Figure 1 ddemonstrates thhe basic MATL LAB work envvironment and commands.
Figgure 1. The MA ATLAB work eenvironment
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3. Simulattion of Modullation and Demodulation Here, to ddemonstrate thhe simulation using MATL LAB environm ment we comppare two willl-known and basic passband modulation techniques t BP PSK and QP PSK. These m methods are still used in different mo odern communiccation systems.. 3.1 BPSK Technology BPSK moodulation is a basic techniquue used in vaarious wirelesss standards suuch as CDMA A, Imax (16d, 16e), WLAN 111a, 11b, 11g, 11n, Satellite, D DVB and cablee modem. BPS SK consideredd to be more roobust among all the modulationn schemes duee to the 180° ddifference betw ween two constellation pointts. Hence it cann with stand se evere amount off channel connditions or channel fading. It is used inn OFDM and OFDMA to m modulate the pilot subcarrierss used for channnel control. Different cchannels are used u for speciific data transmission in cellular systemss. The channells used to tran nsmit system related information which are vvery essential aare modulatedd using BPSK m modulation. ate is BPSK is lless susceptiblle to error thaan ASK, also is more efficcient to use off bandwidth (higher data ra possible). BPSK modullation and dem modulation coode was writtten in MATLA AB environm ment. The resu ult of running thhis program is shown s in figurre 2.
Figure 2. 2 Simulation oof Modulation and demodulaation using BP PSK in MATLA AB 3.2 QPSK Technology QPSK useed widely in applications a inncluding CDM MA cellular phoone, wireless llocal loop, Iridium (a voice e/data satellite syystem) and DV VB-S (Digital V Video Broadcaasting — Satellite). QPSK is used for satellite transmissio on of MPEG-2 vvideo also usedd in video confferencing. With four phases, QPSK K can encode ttwo bit per symbol, to minim mize the requiired bandwidthh, twice the ra ate of BPSK in thhe same bandw width. This maay be used eithher to double th the data rate coompared to a B BPSK system while w the maintaaining the banddwidth of the ssignal or to maaintain the dataa rate of BPSK K but half banddwidth needed. As with B BPSK, there arre phase ambiiguity problem ms at the receiiver and differrentially encodded QPSK is more normally uused in practicce. Another advvantage of QP PSK is the use of differentiall DQPSK. Herre the phase sh hift is not relativve to a referencce phase of a signal but relaative to the phhase of previouus two bit. Thee receiver does not need the reeference signal but only com mpares two signnals to reconsttruct the originnal data. The phasee shift can alw ways be relative to reference signal. If thiss scheme usedd, phase shift oof 0 means tha at the 54
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signal is inn phase with reference r signaal. QPSK signal will then exxhibit a phase shift of 45o foor the data 11, 135o o 0 for 10, 2255 for 00 and 315 3 for 01, wiith all phase shhifts being relaative of the refeerence signal. Inter channnel interferencce (ICI) is signnificantly largee in QPSK. Too avoid ICI QP PSK requires filtering which h can change am mplitude and phase of QPSK K waveform. Q QPSK requiress a round 8 tim mes its bandwiidth to transmiit the same poweer. The disadvvantage of QP PSK relative tto BPSK is thhat it is more sensitive to pphase variation. Transmitterr and receiver haave to be syncchronized veryy often, example by using sppecial synchronnization patterrns before userr data arrives or vvia pilot frequuency as referennce. QPSK moodulation and demodulation code was wrritten in MATL LAB environm ment. The resuult of running g this program iss shown in figuure 3. We enter [[0 0 0 1 1 1 0] as an original sequence to thhe simulation pprogram and taaking in to account the Gray code we got thee result as show wn in figure 3.
Figure 3. 3 Simulation oof Modulation and demodulaation using QP PSK in MATLA AB 4. Nyquistt Data Rate Data rate is a parametter associated with the ratee of data trannsferred betweeen two or m more computin ng or telecommuunicating devices. Bit rate describes how m much binary ddigits or bits caan be transferrred in a given time, normally iin one secondd. Mostly data rate is measuured in Mbps. Data rate is pproportional too the bandwid dth of communiccation channel not to informaation signal baandwidth. If thee bandwidth iss high, data ratte will be also high. In our situuation we assuume that the bbandwidth is tthe same for BPSK and QP PSK channels. According to o the formula Rb = 2B × log 2 L , where L is thhe number of levels. In QPSK L is largerr than the in B BPSK, this leads to make the bbit rate of QPS SK larger than BPSK. The Data R Rate code of QPSK Q and BP PSK was writteen in MATLA AB environmennt, a part of w which shown be elow. The result of running thiis program connfirms the abovve idea and shoown in figure 4.
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BW=11:30 Rb_B= =log2(2)/2.*BW W*10^6 Rb_Q= =log2(4)/2.*BW W*10^6 plot(BW,Rb_B,'-rs') hold onn plot(BW,Rb_Q,'-b*')) grid onn legendd('BPSK','QPSK K') xlabel(('BW (MHz)') ylabel(('Rb (bps)') title('B Bandwidth Vs. Data rate') From figurre 4, we can seee that at the ssame bandwidtth for examplee at 10 MHZ, Q QPSK shows tw wice superiority on BPSK in ddata rate
Figure 4. Data rate for BPSK and QP PSK in MATLA AB 5. Bit Error Rate In digital ttransmission, the t number off bit errors is thhe number of rreceived bits oof over a comm munication cha annel that have bbeen altered duue to noise, intterference, disttortion or bit syynchronizationn errors. BER is thee number of biit errors divideed by the total nnumber of trannsferred bits duuring a studiedd time interval. Also the ddefinition of bit b error rate ccan be presentted in a simplle formula; thhe equation beelow is the ratio of energy coonsumed in bit b BER = 0.5 erfc e ? Eb N 0
E b to thhe signal speectral noise N 0 and reprresent bit errror rate in BPSK B
. Foor QPSK usinng Q parameterr BER = Q
E b N 0 . Based on thesse BER formullas, a
code was w written in MAT TLAB environnment. The result of running this program iis shown in figgure 5.
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Figure 5. B Bit error rate foor BPSK and Q QPSK in MAT TLAB To achievee the same BER R, for examplee 10-4, BPSK nneeds less enerrgy as 8.5 dB, while QPSK nneeds 11.4 dB. 6. Capacitty and Signal to noise ratioo Signal to noise ratio is expressed as SNR = P . T The SNR for B BPSK is very low means th hat it P signaal noise provides hhigh immunityy to noise ass compare to the signal flooating throughh the medium m. The capaciity is calculated as
c = B × log l 2 ( SNR + 1) . Figure 6 represents SN NR of BPSK and QPSK ass result of run nning
MATLAB B code.
Figure 66. Capacity verrsus SNR for B BPSK and QPS SK 57
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The capacity of QPSK iss twice of BPS SK at the samee SNR. 7. Power S Spectral Denssity Power speectral density function (PSD D) shows thee power as a function of ffrequency. PSD D shows at which w frequenciees variations arre strong and aat which variaations are weakk. Computation of PSD is doone by fast Fo ourier transform. The formuula of PSD foor BPSK moddulation is
S B (f
S B (f
) = 2E b Sinc 2 (T b f )
and for QP PSK modulatio on is
) = 4E b Sinc 2 (T b f ) .
Figure 7 reepresents PSD D for BPSK andd QPSK as result of MATLA AB code.
Figure 7. PSD D for BPSK annd QPSK 8. Conclussion In this papper, we had prresented two kkinds of digitall modulation ttechniques BPSK and QPSK K which are widely used in wireless communnication system m. MATLAB for the simulation and comparrison between BPSK and Q QPSK over a sset of perform mance We used M parameterss. We can concclude that:
Banddwidth and dataa rate of QPSK K is better thann BPSK.
Bit errror rate is lesss occurred in B BPSK unlike Q QPSK.
Signaal to noise ratioo of QPSK is bbetter than BPSK.
Poweer spectral dennsity of BPSK aand QPSK aree the same.
All of thesse expected annd theoretical results prove the suggestedd idea of usingg MATLAB ennvironment fo or the simulationn of passband modulation m tecchniques. Referencees Boulmalf, M., Semmarr, Y., Lakas, A A., & Shuaibb, K. (2010). Teaching Diggital and Anallog Modulatio on to Undeergraduate Infformation Tecchnology Studdents Using M Matlab and SSimulink, IEEE E EDUCON 2010 Confe ference, thee future of globbal learning engineerring educaation, 685-691. http:///dx.doi.org/100.1109/EDUCO ON.2010.5492513 Ferreira, A A. J. M. (2009)). MATLAB Coodes for Finite Element Analy lysis, Springer. ISBN 978-1-44020-9199-5. Gilat, A. ((2004). MATL LAB: An Introoduction with A Applications 22nd Edition, JJohn Wiley & Sons. ISBN 97858
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0-471-69420-5. Hemant, D., & Ravindra, P. (2014). Performance Analysis of Digital Modulation Techniques under Simulation Environment, Journal of Emerging Technologies and Innovative Research (JETIR), Volume 1 Issue 5 JETIR (ISSN-2349-5162) JETIR1405013 Retrieved from http://www.mathworks.com/access/helpdesk_r13/help/ toolbox/commblks/ref/simref-7.html#611864 Leon, W. C. (2001). Digital and Analog Communication Systems. Prentice Hall, New Jersey, sixth edition. Li, X. L. (2008). Simulink-based Simulation of Quadrature Amplitude Modulation (QAM) System. Proceedings of The 2008 IAJC-IJME International Conference ISBN 978-1-60643-379-9. Masud, M. A., Samsuzzaman, M., & Rahman, M. A. (2010). Bit Error Rate Performance Analysis on Modulation Techniques of Wideband Code Division Multiple Access. Journal of Telecommunications, 1(2), Retrieved from http://sites.google.com/site/journaloftelecommunications/ Quarteroni, A., & Fausto S., (2006). Scientific Computing with MATLAB and Octave, Springer. ISBN 978-3-540-32612-0. Rashmi, S., Sunil, J., & Navneet, A. (2011). Performance Analysis of Different M-ARY Modulation Techniques in Cellular Mobile Communication, IP Multimedia Communications A Special Issue from IJCA – Retrieved from http:// www.ijcaonline.org Samson, A., Oyetunji, A., & Akinninranye, A. (2013). Comparing Performances of Bandpass Modulation in Wireless Communication Channels. Journal of Environmental Engineering and Technology, 2(2). ISSN: 2165-8315 (Print) http://www.researchpub.org/journal/jeet/jeet.html Tharakanatha, G. S. K., Mahaboob, K. B., & Vijay, B. C. (2013). Implementation and Bit Error Rate analysis of BPSK Modulation and Demodulation Technique using MATLAB, International Journal of Engineering Trends and Technology (IJETT), 4(9). ISSN: 2231-5381. http://www.ijettjournal.org Virendrakumar, V., & Raut, J. (2014). IMPLEMENTATION OF DIGITAL MODULATION TECHNIQUES IN MATLAB. International Journal of Advanced Technology in Engineering and Science, 2(7). http://www.ijates.com Copyrights Copyright for this article is retained by the author(s), with first publication rights granted to the journal. This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
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