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  1. 1. ISSN: 2277 – 9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 5, July 2012 Performance and Analysis of DS-CDMA Rake Receiver and Analyzing the BER Performance in Presence of Nonlinear Distortion in DS-CDMA System Y Mohan Reddy, K Manjunath, K Yogaprasad uses a set of unique signature sequence or spreading codes toAbstract— In this paper analysis the performance of a CDMA modulate the data bits of deferent users. With the knowledgesystem by varying the system parameters. CDMA is a popular of these spreading codes, the receiver can isolate the datatechnology in cellular system due to its superior capacity and corresponding to each user by the process of Channelperformance. In conventional CDMA, obtained better signal to estimation and detection. This process spreads the bandwidthnoise ratio by using matched filter because of this rake receiver of the underlying data signal; hence CDMA is called a spreadis used in CDMA to obtain desired signal to noise ratio. Rake spectrum technique. Standards such as IS-95 and the proposed W-CDMA are based on CDMA technology [4].receiver is one of the receiver technique, consists of multiplecorrelators, in which the receive signal is multiplied by DS-CDMA signals typically exhibit large dynamic rangetime-shifted versions of a locally generated code sequence. To since they represent the sum of signals of many users.maximize the Signal to Noise Ratio and minimize the Bit Error Unfortunately, when passed through a high power amplifierRate the CDMA Rake receiver is used. A predistorter-high (HPA), this large dynamic range results in distortion forpower amplifier (PD-HPA) pair has become a common practicein wireless communication to compensate for nonlinear components falling in the highly nonlinear regions of thedistortion due to HPA. However, the PD-HPA pair still HPA, which degrades the system bit error rate (BER) [12].produces severe signal distortion when the input signal exceeds A common parameter for characterizing the dynamic rangethe PD-HPA’s saturation level. The effects of such distortion on of a signal is the signal peak-to-average power ratio (PAR).bit error rate (BER) degradation in direct sequence-code PAR is often used as an indicator to how much harm thedivision multiple access signals (DS-CDMA) are analyzed. signal will suffer due to HPA nonlinearity, and also allowsAssuming that the baseband CDMA signal is characterized as a the system designer to determine the required amount ofcomplex Gaussian process, we develop analytic expressions for input back-off (IBO) to reduce nonlinear distortion effects.the BER and the contributing factors to BER. While PAR has its use, a signal’s dynamic range in relation to an HPA only captures only one feature of the signal’s Key Words:-CDMA (code Division Multiplexing), DS-SS(Direct Sequence (DS) Spread Spectrum), FDMA (Frequency interplay with the HPA.Division Multiplexing), PN (Pseudo Noise), SNR (signal to Noise We reformulate which signal characteristics to considerRatio), BER (Bit Error Rate), Nonlinear Distortion, beyond dynamic range that can be linked directly with BER.Predistortion, HPA (High Power Amplifier). In the analysis, we assume that the nonlinear amplifier chain includes a predistorter prior to the HPA, namely PDHPA. I. INTRODUCTION The PD-HPA has a zero AM-PM characteristic∅ 𝑟(𝑡) , and Wireless cellular telephony has been growing at a faster rate an AM-AM characteristic given bythan wired-line telephone networks. The main factor driving 𝐺 𝑟 𝑡 = 𝑟 𝑡 0≤ 𝑟 𝑡 ≤ 𝜁 (1)this tremendous growth in wireless coverage is that it does = 𝜁 𝑟 𝑡 > 𝜁not need the setting up of expensive infrastructure like copper Where𝑟(𝑡) is the input to the PD-HPA and 𝜁 is the PD-HPAor fiber lines and switching equipment. This growth has also saturation (clipping) threshold. Assuming that the basebandbeen fueled by the recent improvements in the capacity ofwireless links due to the use of multiple access techniques CDMA signal is characterized as a band-limited complex(which allow many users to share the same channel for Gaussian process, we establish analytical expressions for thetransmission) in association with advanced signal processing signal characteristics, with respect to the IBO level, that leadalgorithms. Code Division Multiple Access (CDMA) is to BER degradation. Moreover, we develop an analyticbecoming a popular technology for cellular communications expression for the BER performance in presence of the[1]. considered nonlinear amplifier chain. Unlike other multiple access techniques such asFrequency Division Multiple Access (FDMA) and II. RAKE RECEIVERTime-Division Multiple Access (TDMA) [7], which arelimited in frequency band and time duration respectively,CDMA uses all of the available time-frequency space. One In a mobile radio channel reflected waves arrive withform of CDMA called Direct Sequence CDMA (DS-CDMA) small relative time delays, self interference occur. Direct Sequence (DS) Spread Spectrum is often claimed to have Manuscript received June 15, 2012. particular properties that makes it less vulnerable toY Mohan Reddy, student,, dept of ECE, SITAMS, Chittoor, Andhra multipath reception. In particular, the rake receiverPradesh, India,+91-9014157437(mohanreddy.404@gmail.com). architecture allows an optimal combining of energy receivedK Manjunath, Assistant Professor department of ECE, over paths with different [6]. It avoids wave cancellationSITAMS, Chittoor, Andhra Pradesh, India, +91-9052232027 (fades).If delayed paths arrive with phase differences and(manjunathak83@gmail.com). appropriately weighs signals coming in with differentK Yogaprasad, Associate Professor, Dept of ECE, SITAMS,Chittoor, AndhraPradesh India,+919908085522 signal-to-noise ratios [2].(kyogaprasad@gmail.com). 1 All Rights Reserved © 2012 IJARCSEE
  2. 2. ISSN: 2277 – 9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 5, July 2012 The rake receiver [3, 6] consists of multiple correlators, According to the maximum ratio combining principle, thein which the receive signal is multiplied by time-shifted SNR at the output is the sum of the SNRs in the individualversions of a locally generated code sequence. The intention branches, provided that,is to separate signals such that each finger only sees signals 1. We assume that only AWGN is present (no interference).coming in over a single (resolvable) path. The spreading code 2. Codes with a time offset are truly orthogonal.is chosen to have a very small autocorrelation value for any Signals arriving with the same excess propagation delay asnonzero time offset. This avoids crosstalk between fingers. In the time offset in the receiver are retrieved accurately,practice, the situation is less ideal. It is not the full periodic becauseautocorrelation that determines the crosstalk between signalsin different fingers, but rather two partial correlations with 𝑁 𝑁 2contributions from two consecutive bits or symbols. It has 𝑐1 𝑛𝑇 𝑐 + 𝑡 𝑑 = 𝑐1 2 𝑛𝑇 𝑐 = 𝑁 (2)been attempted to find sequences that have satisfactory 𝑛=1 𝑛=1partial correlation values, but the crosstalk due to partial This reception concept is repeated for every delayed path that(non-periodic) correlations remains substantially more is received with relevant power. Considering a singledifficult to reduce than the effects of periodic correlations the correlator branch, multipath self-interference from otherrake receiver is designed to optimally detect a DS-CDMA paths is attenuated here, because one can choose codes suchsignal transmitted over a dispersive multipath channel. It is that [4].an extension of the concept of the matched filter [2, 9]. 𝑁 𝑐1 𝑛𝑇 𝑐 𝑐1 𝑛𝑇 𝑐 + 𝑡 𝑑 ≅ 0 (3) 𝑛=1 III. MULTIPATH AND RAKE RECEIVER One of the main advantages of CDMA systems is the capability of using signals that arrive in the receivers with different time delays. This phenomenon is called multipath. Fig 1: Matched Filter Receiver for AWGN Channel FDMA and TDMA, which are narrow band systems, cannot discriminate between the multipath arrivals, and resort to In the matched filter receiver, the signal is correlated equalization to mitigate the negative effects of multipath [5,with a locally generated copy of the signal waveform. If, 10]. Due to its wide bandwidth and rake receivers, CDMAhowever, the signal is distorted by the channel, the receiver uses the multipath signals and combines them to make anshould correlate the incoming signal by a copy of the even stronger signal at the receivers. CDMA subscriber unitsexpected received signal, rather than by a copy of transmitted use rake receivers. This is essentially a set of severalwaveform. Thus the receiver should estimate the delay receivers. One of the receivers (fingers) constantly searchesprofile of channel, and adapt its locally generated copy for different multipath and feeds the information to the otheraccording to this estimate [2, 7]. three fingers. Each finger then demodulates the signal In a multipath channel, delayed reflections interfere corresponding to a strong multipath. The results are thenwith the direct signal. However, a DS-CDMA signal combined together to make the signal stronger [2].suffering from multipath dispersion can be detected by a rakereceiver. This receiver optimally combines signals received Multipath Receptionover multiple Paths. Experiments with mobile communication were done at VHF frequencies, near 50 MHz, already in the 1920s. Results of these tests revealed a very hostile propagation environment, particularly in urban centers. The signal quality varied from "excellent" to "no signal". Moving the vehicle over a few meters resulted in dramatic changes of the received field strength [11]. Fig 2: Rake Receiver with 5 FingersLike a garden rake, the rake receiver gathers the energyreceived over the various delayed propagation paths. 2 All Rights Reserved © 2012 IJARCSEE
  3. 3. ISSN: 2277 – 9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 5, July 2012 𝜁 ∞ −𝜁 2 Fig 3: Bit Error in Multipath Fading = 𝑟 2 𝑓𝑟 𝑟 𝑑𝑟 + 𝜁 2 𝑓𝑟 𝑟 𝑑𝑟 = 2𝜍 2 1 − 2 (10) 𝑥 0 𝜁 𝑒 2𝜍 𝑥 IV. CDMA SYSTEM PERFORMANCE Evaluating the BER in the case of an optimum receiver is difficult and tedious; hence, the BER for a suboptimum The system under investigation is a downlink CDMA receiver is used as an upper bound [13]. We adopt thesystem in which the users’ signals are synchronized and have decorrelating receiver, where multi-user interference isequal power. The complex envelope of the CDMA signal for eliminated [13], [15] at the expense of noise enhancing. ForK active users is defined as [12], [13] the decorrelating receiver, the 𝐾 𝑡ℎ user BER is given by 𝐾 ∞ 𝐿−1 𝐵𝐸𝑅 𝐾 = 𝑄 𝑆𝑁𝑅 𝑘 (11) 𝑠 𝑡 = 𝐸𝑘 𝑎 𝑛 𝑘 𝑐 𝑡 𝑘 ℎ 𝑡 − 𝑙𝑇𝑐 − 𝑛𝑇 Where𝑆𝑁𝑅 𝑘 is the signal-to-noise ratio at the 𝐾 𝑡ℎ receiver −𝑢 2 𝑘=1 𝑛=−∞ 𝑙=0 ∞ 𝑒 2 = 𝑥 𝑡 + 𝑗∗ 𝑦 𝑡 = 𝑟 (4) and 𝑄 𝑘 = 𝑥 √2𝜋 𝑑𝑢 .Including Additive White Gaussian Where 𝐸 𝐾 is the 𝐾 𝑡ℎ user’s signal energy per bit, T is the Noise (AWGN), 𝑆𝑁𝑅 𝑘 is given by [13, eq. (15.3-65, 67)]symbol duration, L is the spreading factor,𝑇𝑐 = 𝑇 𝐿 is the 𝜍2 𝑠,𝑘 𝐸𝑘 (𝑘) 𝑆𝑁𝑅 𝑘 = 𝑆𝑁𝑅 𝐴𝑊𝐺𝑁 ,𝑘 = 2 = (12)chip duration, 𝐶 𝑙 is the 𝑙 𝑡ℎ chip in the spreading code 𝜍 𝑛,𝑘 𝜀 𝑘 𝜍2𝑛 𝑇 𝐶 𝑘 = 𝐶0 𝑘 … … … … . . 𝐶 𝐿−1 , h(t) is the impulse response 𝑘 Where 𝑆𝑁𝑅 𝐴𝑊𝐺𝑁 is the SNR due to AWGN only, 𝜍 2 is the 𝑛 (𝑘) variance of the AWGN and 𝜀 𝑘 = 𝑅−1 𝑘,𝑘 is the noise 𝑠of the transmit pulse shaping filter, and 𝑎 𝑛 = (±1 ± 𝑗)/√2 enhancement factor introduced by the decorrelating receiveris the𝐾 𝑡ℎ user’s symbol data for QPSK modulation in the 𝑛 𝑡ℎ [13], where Rs is the correlation matrix with elements𝜌 𝑗𝑘 0symbol duration. Moreover, the symbols 𝑎 𝑛 𝑘 are assumed to 𝑇 (𝑘) 2 defined as𝜌 𝑗𝑘 0 = 𝑐 𝑗 𝑐 𝑘 .be independent with zero mean and variance of 𝐸 𝑎𝑛 In the presence of a nonlinear amplifier, the SNR measured at[12]. the 𝐾 𝑡ℎ receiver input is the ratio of the transmitted distorted For a large number of users and assuming the pulse signal power 𝜍 2 = 𝑎0 2 𝜍 2 + 𝜍 2 to the noise power 𝜍 2 𝑑 𝑠 𝑛𝑙 𝑛,𝑘shaping filter corresponds to a square-root raised cosine filter −𝜁 2(SRRC) with small roll-off factor, x (𝑡) and 𝑦(𝑡) can be 𝜍2𝑑,𝑘 𝜍 2 (1 𝑠,𝑘 − 2 𝑒 2𝜍 𝑥 )regarded as two uncorrelated zero-mean Gaussian processes 𝑆𝑁𝑅 𝑘 = = 𝜀 𝑘 𝜍2𝑛 𝜀 𝑘 𝜍2 𝑛with equal variances, that is 𝜍 2 =𝜍 2 [14]. Hence, 𝑠(𝑡)can be 𝑥 𝑦 −𝜁 2regarded as a complex zero-mean Gaussian process with a = 𝑆𝑁𝑅 𝐴𝑊𝐺𝑁 ,𝑘 1 − 𝑒 2𝜍 2 𝑥 (13)variance of 𝐾 Actually, once the PD-HPA is designed, its saturation 2 𝜍2 𝑠 = 2𝜍 2 𝑥 = 𝐸 𝑘 𝐸{ 𝑎 𝑛 𝑘 } = 𝐾𝐸 𝑘 (5) threshold is fixed. However, the clipping threshold with 𝑘=1 respect to the input signal to the PD-HPA depends on theSince 𝐶 𝑙 𝑘 = 1. The envelope 𝑟 𝑡 = 𝑥 2 𝑡) + +𝑦 2 (𝑡 signal average power. Therefore, it is more convenient tohas a quasi- Rayleigh distribution [14], with probability relate the threshold 𝜁 to IBO, where the IBO is the ratio of thedensity function [13]. input power at the PD-HPA saturation threshold to the signal 𝑟 𝑟2 average power. This relation allows the system operator to 𝑓𝑟 𝑟 = 2 𝑒 − 2 𝑟≥0 (6) determine the optimum IBO required, according to the design 𝜍𝑥 2𝜍 𝑥 demands. Hence, the threshold level can be defined thru theFinally, the output from the PD-HPA can be expressed as IBO,𝛾, multiplied by the signal average power𝑃𝑎𝑣 , that is 𝑠 𝑑 𝑡 = 𝑟 𝑑 𝑡 𝑒 𝑗 𝜃 𝑑 𝑡 = 𝐺 𝑟 𝑡 𝑒 𝑗𝜃 𝑡 (7) 𝜁 = 𝑃𝑎𝑣 ∗ 𝛾 = 𝜍 2 ∗ 𝛾 𝑛 (14) −𝜁 2 V. BER PERFORMANCE ANALYSIS The term 𝑒 2𝜍 2 𝑥 in (13) represents the probability that the Using the Bussgang theorem extension for a complex signal envelope exceeds the threshold 𝜁 , equivalently theGaussian input to a memory less nonlinear device, the output threshold exceeding rate RE, which using (14) is written asof the PD-HPA can be represented as the sum of two −𝜁 2 2uncorrelated components: a scaled linear component and a 𝑅𝐸 = = 𝑒 −𝛾 𝑒 2𝜍 𝑥 (15)nonlinear component,𝑠 𝑛𝑙 𝑡 , [12], [14], [15], that is Substituting (15) in (13) and then in (11), the BER in 𝑠 𝑑 𝑡 =∝ 𝑜 𝑠 𝑡 + 𝑠 𝑛𝑙 𝑡 (8) presence of the PD-HPA as a function of the IBO level hasWhere 𝐸 𝑠 𝑡 𝑠 ∗ 𝑡 = 0and ∝ 𝑜 is the linear gain given by 𝑛𝑙 the form 𝐸 𝑠 𝑡 𝑠∗ 𝑡 𝑛𝑙 𝐸 𝐺 𝑟 𝑟 ∝ 𝑜= = (9) 𝐵𝐸𝑅 𝑘 = 𝑄 𝑆𝑁𝑅 𝐴𝑊𝐺𝑁 ,𝑘 1 − 𝑅 𝐸 (16) 𝐸 𝑠 𝑡 2 2𝜍 2 𝑥 Consequently, the variance of the distorted signal 𝑆 𝑑 𝑡 is From (16), it is clear that the threshold exceeding rate𝑅 𝐸 isgiven by 𝜍 2 = 𝑎0 2 𝜍 2 + 𝜍 2 where 𝜍 2 is the variance of the 𝑑 𝑠 𝑛𝑙 𝑛𝑙 the main contributor to BER degradation; by minimizing𝑅 𝐸 ,nonlinear component𝑆 𝑛𝑙 𝑡 . As far as 𝑠(𝑡)is considered as a 𝑆𝑁𝑅 𝑘 𝑖s maximized resulting in BER improvement, and vicezero-mean complex Gaussian process, 𝜍 2 can be calculated 𝑑 versa. This result can be understood from the PD-HPAas transfer function. When the input signal exceeds the ∞ saturation threshold 𝜁 , an output signal value has a𝜍 2 = 𝐸 𝑠 𝑑 (𝑡) 𝑑 2 = 𝐸 𝑟 2 (𝑡) = 𝑑 𝑟 2 𝑓𝑟 (𝑟)𝑑𝑟 𝑑 many-to-one mapping to the input values, where, 0 discriminating between these input values at the receiver to recover the original transmitted data would be challenging, 3 All Rights Reserved © 2012 IJARCSEE
  4. 4. ISSN: 2277 – 9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 5, July 2012resulting in expected BER degradation. Effectively, errorsare introduced in advance at the transmitter. Actually,𝑅 𝐸 is not the only contributor to BER degradationsince the BER in (16) is based on the SNR in (12). Such SNRis the apparent SNR since an increase in the nonlinearcomponent variance 𝜍 2 ,𝑘 as part of 𝜍 2 in (11) increases the 𝑛𝑙 𝑑,𝑘 Fig.4. (b) Output envelope 𝑟 𝑑 𝑡 from PD-HPA.SNR, although effectively deteriorates the BER [15], [16].While the effective SNR, where the non-linear signal 𝑠 𝑛𝑙 𝑡in (8) is assumed Gaussian distributed [12], is defined as [15] 𝛼0 2 𝜍2 𝑠,𝑘 𝛼0 2 𝜍 2 𝑠,𝑘 𝑆𝑁𝑅 𝑒𝑓𝑓 ,𝑘 = = 2 𝜍2 𝑛,𝑘 + 𝜍 2 ,𝑘 𝑛𝑙 𝜍 𝑛,𝑘 + 𝜍 2 − 𝛼0 𝑑,𝑘 2 𝜍2 𝑠,𝑘 Fig.4. (c) clipped envelope portion𝑟𝑐 𝑡 . 𝛼0 2 𝜍 2 𝑠,𝑘 Rearranging (22) and substituting into (19), 𝛼 𝑜 is given by = (17) 1 1 1 1 𝜍 2 + 𝜍 2 (1 − 𝑅 𝐸 − 𝛼0 2 ) 𝑛,𝑘 𝑠,𝑘 𝛼 𝑜 = 1 − −𝛾 − 2 𝜍 2 = 1 − − 2 𝜍2 (23) 𝑐Substituting (17) in (11), the BER in presence of the 2𝑒 4𝜍 𝑥 2𝑅 𝐸 4𝜍 𝑥 𝑐PD-HPA, according to𝑆𝑁𝑅 𝑒𝑓𝑓 ,𝑘 , has the form From (23) as part of (16), it is clear that 𝑅 𝐸 and 𝜍 2 are the 𝑐 main contributors to the BER performance; decreasing𝑅 𝐸 𝛼0 2 and𝜍 2 , increases𝛼0 , increases𝑆𝑁𝑅 𝑘 , and in turn improves 𝑐 𝐵𝐸𝑅 𝑘 = 𝑄 2 (18) 1 − 𝑅 𝐸 − 𝛼0 + (𝑆𝑁𝑅 𝐴𝑊𝐺𝑁 ,𝑘 )−1 BER.Looking to the linear gain 𝛼0 , it can be expanded as VI. ALGORITHM AND IMPLEMENTATION ∞ 1 𝛼0 = 2 𝑟 𝑟 𝑓 𝑟 𝑑𝑟 2𝜍 𝑥 0 𝑑 𝑟 𝜁 ∞ In this section, discussing about the MATLAB algorithm 1 = 2 𝑟 2 𝑓𝑟 𝑟 𝑑𝑟 + 𝜁 𝑟𝑓𝑟 𝑟 𝑑𝑟 and implementation techniques 2𝜍 𝑥 0 𝜁 i. Generate a fifteen bit user data for each user to simulate 𝜁2 with Rake or without Rake on MATLAB. − 2 2𝜍 𝑥 1 𝜋𝜁 2 𝜁 =1− 𝑒 + 𝑒𝑟𝑓𝑐 ii. Generate a PN sequence data for every user. 2 2𝜍 2 𝑥 2𝜍 2 𝑥 iii. Generate code data by multiplication of user data and PN √ 𝜋𝛾 sequence. = 1− 𝑅𝐸 + 𝑒𝑟𝑓𝑐 𝛾 (19) iv. Add AWGN noise with the code and we create multiple 2The output of the PD-HPA can be written as path with different attenuation, every multipath add 𝑆 𝑑 𝑡 = 𝑟 𝑑 𝑡 𝑒 𝑗𝜃 𝑡 = 𝑟 𝑡 − 𝑟𝑐 𝑡 𝑒 𝑗𝜃 𝑡 random noise to code so at the end of path we will get = 𝑠 𝑡 − 𝑠𝑐 𝑡 (20) multiple code with different noise. v. Comparing the BER performance of WITH andWhere𝑆 𝑐 𝑡 = 𝑟𝑐 𝑡 𝑒 𝑗𝜃 𝑡 is the signal portion that is clipped WITHOUT Rake receiver for different attenuation factors.from𝑆(𝑡),𝐸 𝑆 𝑐 (𝑡) = 0, and its envelope𝑟𝑐 (𝑡) has the form 𝑟𝑐 𝑡 = 𝑟 𝑡 − 𝑟 𝑑 𝑡 VII. SIMULATION RESULTS = 0, 𝑟 𝑡 ≤ 𝜁 = 𝑟 𝑡 − 𝜁, 𝑟 𝑡 > 𝜁 (21) Here we are observing the performance of CDMA systemExamples of 𝑟 𝑡 ,𝑟 𝑑 𝑡 , and 𝑟𝑐 𝑡 are shown in Fig. 4(a), Fig. with and without rake receiver. Figure 5 shows that the4(b), and Fig. 4(c), respectively. performance of CDMA system with and without rake The variance 𝜍 2 of 𝑆 𝑐 𝑡 can be derived using the 𝑐 receiver for different attenuation factors to minimize the Bitdefinition of the envelope of the clipped signal portion in (21) Error Rate. performance analysis of with and without rake receiveras 0 10 ∞ with rake 𝜍2 = 𝐸 𝑐 𝑆𝑐 𝑡 2 = 𝐸 𝑟𝑐2 𝑡 = 𝑟− 𝜎 2 𝑓𝑟 𝑟 𝑑𝑟 without rake -1 𝜎 10 𝜁2 2 − 2 𝜁 = 2𝜍 𝑥 𝑒 2𝜍 𝑥 − 2𝜋𝜍 2 𝜎𝑒𝑟𝑓𝑐 𝑥 ...................BER -2 2𝜍 2 10 𝑥 = 2𝜍 2 (𝑒 −𝑦 − 𝑥 𝜋𝛾 𝑒𝑟𝑓𝑐 𝛾 (22) -3 10 -4 10 -5 10 0 5 10 15 20 25 30 35 ..................EbNo Fig 5: Performance of CDMA system with and without rake receiver. Fig.4. (a) Input envelope 𝑟 𝑡 to PD-HPA. Figure 6 shows that performance of multipath using rake receiver in CDMA system and figure 7 shows that BER performance for conventional CDMA and proposed RAKE Receiver. 4 All Rights Reserved © 2012 IJARCSEE
  5. 5. ISSN: 2277 – 9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 5, July 2012 To assess the validity of the derived expressions for thefactors contributing to BER degradation, 𝑅 𝐸 and 𝜍 2 , and the 𝑐linear gain 𝛼0 , a 64-user CDMA signal filtered using anSRRC filter with Walsh codes of length L = 64 is simulated. 𝑅 𝐸 ,𝜍 2 , and 𝛼0 are measured for the simulated signal and 𝑐compared against the analytic expressions in (15), (22), and(23), respectively. The relations of such factors versus IBOare shown in Fig. 8, where the agreement between theanalytic curves and simulated points confirms the analyticderivations. Finally, the analytically derived BER is computed from(16) and compared against the BER measured fromsimulation. Fig. 9 shows the BER curves, where it is evident Fig.9 Analytic and simulated plots of BER at different IBO levels.that good agreement exists between the analytic curves andthe measured points for all IBO levels. 0 Multiple paths of rake receiver CONCLUSION 10 1-path 2-path 3-path In this paper, Rake receiver is used for CDMA 4-path technique rather than using conventional CDMA with -1 10 matched filter. Rake receiver is used to minimize the bit error rate and obtain maximum signal to noise ratio. -------BER In this how nonlinear distortion due to PD-HPA affects BER degradation for transmitted DS-CDMA signals. We -2 10 established analytically how the threshold exceeding rate 𝑅 𝐸 and the variance of the clipped portion of the signal 𝜍 2 . 𝑐 contribute to BER degradation. The motivation of this work -3 is to provide system designers/operators with efficient tools 10 2 3 4 5 6 7 8 --------Ebno(dB) 9 10 11 12 that provide potential insight into the interactions between CDMA signals and the nonlinear PD-HPA, leading to better Fig 6: performance of multipath using rake receiver in CDMA system. understanding of the impact of the PD-HPA on system BER. Moreover, establishing these characteristics for the input Performance analysis of the with and without rake receivers 10 0 signal in relation to the PD-HPA characteristics opens new Coventional Proposed avenues for research to minimize the effect of nonlinear distortion before the signal even hits the amplifier. For -1 10 instance, in search and optimization techniques such as the selected mapping technique, where many representations of the same signal are generated and the one that achieves the ------BER -2 10 minimum of these characteristics is selected for transmission. 10 -3 REFERENCES [1] Peter Flanagan, ―Personal Communications Services: The Long -4 Road Ahead,‖ Telecommunications, February 1996. 10 2 4 6 8 10 12 14 16 18 20 [2].http://wireless.per.nl/reference/chaptr05/cdma/rake.htm. ------Ebno (dB) [3] W. C. Y. Lee, ―Overview of Cellular CDMA,‖IEEE Trans. On Fig 7: BER graph for conventional and proposed systems Vehicular Technology, Vol. 40, no. 2, pp. 291-302, May 1991. [4] R. A. Cameron and B. D. Woerner, ―An Analysis of CDMA with Imperfect Power Control,‖ Proceedings of 42nd IEEE Vehicular Technology Conference, Denver, CO, pp. 977-980, 1992. [5] R. Lupas and S. Verdu, ―Linear Multiuser Detectors for Synchronous Code Division-Multiple-Access Channels,‖ IEEE Trans. Info. Theory, vol. 35, no.1, pp. 123-136, Jan. 1989. [6]. K.Murali.Krishna, Abhijit Mitra and Cemal Ardil‖ A Simplified Single Correlator Rake, Receiver for DMA Communications‖ International Journal of Information Technology Volume 2 Number 4 2005. [7] P. Jung, P. W. Baier, and A. Steil, ―Advantages of CDMA and Spread Spectrum Over FDMA and TDMA in Cellular Mobile Radio Applications,‖ IEEE Transactions Vehicular Technology, Vol. 42, no. 3, pp. 357- 364, August 1993 [8] Electronic Industries Association, ―Cellular System Dual-Mode Mobile Station Base Station Compatibility Standard,‖ IS-54, May 1990.Fig.8. Analytic and simulated plots of𝑅 𝐸 , 𝜍 2 , and 𝛼 𝑜 over a range of IBOs. 𝑐 5 All Rights Reserved © 2012 IJARCSEE
  6. 6. ISSN: 2277 – 9043 International Journal of Advanced Research in Computer Science and Electronics Engineering Volume 1, Issue 5, July 2012[9] K. S. Gilhousen, ―On the Capacity of a Cellular CDMA System,‖IEEE Transactions on Vehicular Technology, Vol. 40, no. 2, pp. 303-311,May 1991.[10] Electronic Industries Association, ―Wideband Spread Spectrum Digital Cellular System Dual Mode Mobile Station - Base Station Compatibility Standard,‖ IS-95, April, 1992.[11] J. C. Liberti and T. S. Rappaport, ―Analytical Results for Capacity Improvements in CDMA,‖ IEEE Transactions on Vehicular Technology, Vol.43, No. 3, pp. 680-690, August 1994. [12] A. Conti, D. Dardari, and V. Tralli, ―An analytical framework for CDMA systems with a nonlinear amplifier and AWGN,‖ IEEE Trans. Commun.vol. 50, no. 7, pp. 1110–1120, July 2002.[13] J. Proakis, Digital Communications, 4th ed. McGraw-Hill,2000.[14] R. Dinis and A. Palhau, ―A class of signal-processing schemes for reducing the envelope fluctuations of CDMA signals,‖ IEEE Trans. Commun., vol. 53, no. 5, pp. 882–889, May 2005.[15] L. Rugini, P. Banelli, and S. Cacopardi, ―Theoretical analysis and performance of the decorrelating detector for DS-CDMA signals in nonlinear channels,‖ IEEE Trans. Wireless Commun., vol. 3, no. 2, pp. 367–372, Mar. 2004.[16]P. Banelli and S. Cacopardi, ―Theoretical analysis andperformance of OFDM signals in nonlinear AWGN channels,‖IEEE Trans. Commun., vol. 48, no. 3, pp. 430–441, Mar. 2000 ABOUT THE AUTHORS Mr. Y MOHAN REDDY received B.Tech degree from JNT University, Anantapur and is pursuing his M.Tech degree from JNT University, Anantapur. He presented 2 technical papers in various national level conferences. His area of interest is wireless communication. Mr.K.MANJUNATH working as Assistant Professor in the department of ECE in SITAMS, chittoor. He received B.Tech degree from Anna University, Chennai and M.Tech degree from VIT University, Vellore. He presented 2 technical papers in various national level conferences. His areas of interest is digital image processing and wireless networks. Mr.K.YOGAPRASAD working as Associate Professor in the department of EIE in SITAMS, chittoor. He received B.Tech degree from madras university, Chennai, M.Tech degree from vishweswaraiah university, Belgaum. and pursuing Ph.D from JNT university, Anantapur. He presented 3 technical papers in various national level conferences . His areas of interest is wireless communication networks. 6 All Rights Reserved © 2012 IJARCSEE