Performance Improvement of DS-CDMA Wireless Communication Network with Convolutionally Encoded OQPSK Modulation Scheme



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International Journal of Advances in Engineering & Technology, Mar 0. IJAET ISSN: 3-963 Performance Improvement of DS-CDMA Wireless Communication Networ with Convolutionally Encoded OQPSK Modulation Scheme Manish Rai Inderpreet Kaur Deptt. of Elect. & Comm. Engg., M.J.P.Rohilh University, Bareilly, India manishrai968@yahoo.co.in,amitoj.eas@gmail.com Astract: This paper considers the it error proaility analysis of Direct-Sequence Code-Division Multiple Access (DS-CDMA) system. A statistical characteriation of the decision variale at transmitter receiver is otained. System is simulated with OQPSK modulation scheme which when compared with conventional Binary Phase Shift Keying (BPSK) gives improved performance in terms of Proaility of Error (Pe). Convolution coding is further incorporated with oth of the modulations schemes results show that this coding further improves the system when compared without coding. However, mathematical analysis includes exact it error calculation as well as various approximation methods ased on Gaussian modeling of the Multiple-Access Interference (MAI) terms. Keywords: Direct-sequence code-division multiple access, multiple-access interference, Offset QPSK, BPSK, convolution encoder etc.. INTRODUCTION CDMA technique for wireless communication networs always gives etter performance as far as Proaility of Error (Pe) is concerned, when compared to either FDMA or TDMA. CDMA is now a days are widely eing used particularly in wireless cellular networs. Several modulation techniques namely it error efficient techniques, OQPSK, MSK (Minimum Shift eying) etc. can further enhance the performance. Here, it error proaility analysis of DS-CDMA system using offset quadrature phase-shift eying (OQPSK) modulation is done. Offset QPSK is essentially the same as QPSK except that the I- Q-channel pulse trains are staggered. The modulator the demodulator of OQPSK differ from the QPSK y an extra delay of half of the it time T / with T as it duration in the Q-channel. QPSK is also excellent modulation method, when necessary to maximie transmitter output power []. For spectrum conservation, occupancy of the chosen modulation scheme must e small, so that as many channels as possile can e accommodated in a given. Of all the constant envelope digital modulation schemes considered for radio transmission, OQPSK (offset quadrature phase shift eying) is considered to have good spectral properties. Here, effect of the Multiple-Access Interference (MAI) on the it error performance of the single user correlation receiver is considered. The prolem is examined in the context of OQPSK spreading, which is more applicale to the recently introduced third-generation CDMA stards. Accurate evaluation of error performance for DS-CDMA with offset quadrature modulation schemes can e simply achieved y applying the Stard Gaussian Approximation (SGA).. SYSTEM MODEL.. Transmitter 8 Vol.,Issue,pp.8-33

International Journal of Advances in Engineering & Technology, Mar 0. IJAET ISSN: 3-963 Analysis of DS-CDMA systems with mixed-data rates is considered for analysis. The data its for the th user are transmitted after spreading OQPSK modulation. [,]. For each of inphase quadrature component, BPSK spreading is used. Data its are romly generated assumed independent identically distriuted(iid). If s denotes the transmitted signal of th user then transmitted stream can e mathematically represented y [6] where P F s (t) Re[( p (t) a (t) j p t - T 3 a (t)) e -t t + H G I K J () P is the normalied power of th user φ is the phase of carrier signal for th user. After serial to parallel conversion of the data stream, (t) l (t) l are the data signals of in-phase ranch quadrature ranch respectively,expressed as (i) l (t) tp (t it ) i l () (i) Q (t) tp (t it ) i Q (3) l±q are the i th it of the th user for the in-phase quadrature ranches where (i) l (i) Q respectively. The signal pulse P T (t) is a unit rectangular pulse defined y p T if 0 t T n 0 elsewhere s with T as duration of one it. Bit stream a (t) is a spreading waveform, written as [6] where a (f) ± a (t) a pc(t jt ) j (j) c l q is the j th chip of the th user s spreading sequence {a.. Multipath Channel (f) }. Impulse response of the multi path fading channel can e represented as [6] h(t, ) Re{h(t, )e j c ω t } where is a multipath delay ω c is a carrier angle frequency. The signal h(t,) is the complex ase impulse response, expressed for th user as L jφl h (t, ) α e (t ) l,l δ l (6) with L as numer of multi path components; a l :amplitude fading of l th path (Rayleigh distriuted rom variale); l : delay of l th path; φ l :phase shift of l th path (uniform distriuted rom variale); δ(.) : Dirac delta function..3. RECEIVER Received signal is a sum of user signals, their multi path delayed signals, AWGN can expressed as [6]. L jf,l ra ( t) n(t) + S (t )e l,l α,l (7) Aove equation may e roen in to several individual parts as (4) (5) 9 Vol.,Issue,pp.8-33

International Journal of Advances in Engineering & Technology, Mar 0. IJAET ISSN: 3-963 o K Z r g (t) n(t) + P (t ) α,l,l,l a (t ) j p (t ),l +,Q,l jθ.l a (t,l ) q e (8) However, decision statistic K,M from the m th correlator ranch can e written as [4, 5, 7],l (m) + Τs ~,m, Re ra ( t) { cos ω ct + θ (m) a t -,l (m) ge,lj},l (m) dt (9) + Τ ~ r t) -sin ω t + θ a t - m, lm,l (m) + Ts/ { } ( g a c,l g e j,l l (m) x s/ (m) (m) dt (0) where Z`,m,Re Z`,m,Im are the real imaginary parts of Z`,m. These parts are further exped as L K L,m,Re x l + A l + i L L ll m), l, Re g + ll, l, Re () L K L m m, l, l m,m,l x Q + A Q + i L L ll m), l, l g + ll () Terms A l A Q represent the in-phase quadrature contriution of the desired component to the overall decision statistic which can e simplified as A 4 P a i Ts l (m),l l (3) A 4 P a i Ts (m) Q,l Q (4) ξ l ξ Q are the in-phase quadrature phase variances due to the noise respectively. Third fourth terms are interferences due to single multi paths. 3. BER ANALYSIS Stard Gaussian Approximation is the most common technique for the evaluation of the it error proaility of DS-CDMA systems. Here central limit theorem to model the MAI as a Gaussian rom variale added to the thermal noise is used. Variance due to interference without incorporation of convolution coding is given y [4, 6] VAR[l] NT 3 which is further simplified as P (5) 30 Vol.,Issue,pp.8-33

International Journal of Advances in Engineering & Technology, Mar 0. IJAET ISSN: 3-963 σ MAL ( κ ) E T 3 (6) with T NT c where T T c as it spreading chip durations respectively, N as spreading factor. Variance due to noise is given y NT varg η 4 (7) Average SNR can e calculated as SNR A l Var(l) + Var( η ) (8) which is further simplified as SNR Or 6 P,m T α,l l c NT + ( )E T 4 3 (9) N0 4( κ ) SNR + (m) (m) E α 3Να,l,l,l,l (0) Now, convolution coding is applied with OQPSK modulation scheme, giving average SNR as [4, 0] SNR 6 P,m T α,l l NT 4 () 4 (m) E α,l l, / NC () or Finally, BER is calculated as BER Q SNR (3) Where Q(.) as stard Gaussian error function, given y t Q(x) (/ p) e dt x (5) For simulation purpose, different values taen are as follows: 3 Vol.,Issue,pp.8-33

International Journal of Advances in Engineering & Technology, Mar 0. IJAET ISSN: 3-963 N 63 E 50d N 0 (6) 4. RESULTS AND DISCUSSIONS Now, system is simulated for OQPSK BPSK modulation schemes with without incorporation of convolution coding as shown in Fig () fig () respectively. From oth of the diagrams, it is clear that OQPSK modulation scheme outperformed the BPSK technique in terms of proaility of error. Hence, system performance can e improved using this particular modulation over conventional BPSK scheme. However, incorporation of convolution coding can further improve the performance as can e oserved from oth of the figures. Taing numerical value of SNR e.g. 0, it is OQPSK gives Pe of 0-9 with coding whereas it gives Pe of 0-7 without applying coding, hence an improvement of almost 90% is achieved in this case which is clear from the respective figures. Similar conclusions can e drawn for BPSK modulation scheme which gives Pe of 0-7 with coding Pe of 0-6 without coding almost 80% improvement as can e oserved from simulated Fig () Fig () respectively. 0 0 0-5 Proaility of error with coding ps with coding oqps 0-0 Pe0-5 -0-5 -30-0 4 6 8 SNR, Fig.(). Comparison etween Proailities of error P versus Signal to Noise ratio E/N 0 in the case of OQPSK modulation in DS-CDMA networ with convolution coding. 0 0 0-5 Proaility of error without coding OQPSK without coding BPSK 0-0,Pe 0-5 0-0 0-5 0-30 0 4 6 8 0 4 6 8 0 SNR, Fig(). Comparison etween Proailities of error P versus Signal to Noise ratio E/N 0 in the case of OQPSK modulation in DS-CDMA networ without convolution coding. REFERENCES 3 Vol.,Issue,pp.8-33

International Journal of Advances in Engineering & Technology, Mar 0. IJAET ISSN: 3-963 [] Theodore S. Rappaport, Wireless Communications principles Practice, 996, Prentice Hall PTR. [] Hyrid Channel Coding for Error-Sensitive Class on DS-CDMA Air Interface y Byungwan Yu. [3] Yingo Li Y.L. Guan, Modified Jaes Model for Simulating Multiple Uncorrelated Fading Waveforms, IEEE Vehicular Technology Conference Proceedings, VTC 000 Toyo, IEEE 5st, Vol. 3, pp. 89-8, Spring 000. [4] Mohamed A. Lolsi Wayne E. Star, On the accuracy of Gaussian Approximations in the error analysis of DS-CDMA with OQPSK modulation IEEE Trans. Commun Vol. 50, No., Dec 00. [5] Douglas H. Morais Kamilo Feher, Bwidth efficiency proaility of error performance of MSK QPSK system IEEE Trans. Commun, Vol. COM-7, No., Dec 979. [6] Ria Esmailadeh Masao Naagawa, TDD-CDMA for wireless communication Artech House pulication. [7] Fuqin Xiong, Digital Modulation Techniques Artech House Pulication. [8] George Aliftiras, Receiver implementation for a CDMA cellular system. [9] Andrew J. Viteri, CDMA Principles of Spread Spectrum Communication,995 Addison-Wesley. [0] Performance of Convolutionally Coded Multicode Spread Spectrum CDMA System Oechuwu C. Ugweje Sami Khorotly Department of Electrical Computer Engineering The University of Aron Aron, OH 4435-3904 Christian Maduata Department of Electrical Engineering Tusegee University Tusegee, AL 36088,GLOBECOM 003 33 Vol.,Issue,pp.8-33