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BER PERFORMANCE OVER FADING CHANNELS DIVERSITY COMBINING AND QAM TECHNIQUES AyushKaushik(student) Mrs.DeeptiSharma(Lecturer) Dimple Tanwar(student) Electronics and Communication Department Ambuj Mani Chaudhary(student) Inderprastha engineering college FarheenBano(student) Ghaziabad, India. Electronics and Communication Department INDERPRASTHA ENGINEERING COLLEGE Abstract-In order to choose the most suitable modulation, several criteria such as power efficiency, bandwidth efficiency, and bit error rate are used for evaluation. This paper focuses on error performance of phase modulation schemesin different channel conditions and on the method to reduce bit error rates with the help of convolutional coding which is extensively used in GSM cellular system's encoder. A brief description of theoretical aspects of phase modulation schemes commonly used in satellite communications such as BPSK is given here along with simulations carried out with the help of Matlab. I.INTRODUCTION In any phase modulation scheme the information is expressed in terms of phase of the carrier. Phase of the carrier signal is shifted according to the input binary data. Two-state phase shift keying (PSK) is called BPSK where the phase of the radio carrier is set to 0 or π according to the value of the incoming bit. Each bit of the digital signal produces a transmit symbol with duration Ts, which is equal to the bit duration Tb. Bit error rate (BER) of a communication system is defined as the ratio of number of error bits and total number of bits transmitted during a specific period. It is the likelihood that a single error bit will occur within received bits, independent of rate of transmission. There are many ways of reducing BER. Here, we focus on channel coding techniques. A channel in mobile communications can be simulated in many different ways. The main considerations include the effect of multipath scattering, fading and Doppler shift that arise from the relative motion between the transmitter and the receiver. In our simulations, we have considered the two most commonly used channels: the Additive White Gaussian Noise (AWGN) channel where the noise gets spread over the whole spectrum of frequencies and the Rayleigh fading channel. Ghaziabad, India. 2.1 Factors affecting BER • channel noise • interference • distortion • bit synchronization problems • attenuation • Wireless multipath fading, etc 2.2 Analysis of BER The BER may be analyzed using stochastic computer simulations. If a simple transmission channel model and data source model is assumed, the BER may also be calculated analytically. An example of such a data source model is the Bernoulli source. Examples of such simple channel models are: analysis of decoding error probability in case of non bursty bit error on the transmission channel) channel without fading. A worst case scenario is a completely random channel, where noise totally dominates over the useful signal. This results in a transmission BER of 50%. In a noisy channel, the BER is often expressed as a function of the normalized carrier-tonoise ratio measure denoted Eb/N0, (energy per bit to noise power spectral density ratio), or Es/N0 (energy per modulation symbol to noise spectral density). For example, in the case of QPSK modulation and AWGN channel, the BER as function of the Eb/N0 is given by: Returning to BER, we have the likelihood of a bit misinterpretation . where is the threshold of decision, set to 0 when We can use the average energy of the signal People usually plot the BER curves to describe the functionality of a digital communication system. In optical communication, BER(dB) vs. Received Power(dBm) is usually used; while in wireless communication, BER(dB) vs. SNR(dB) is used. Measuring the bit error ratio helps people choose the appropriate forward error correction codes. Since most such codes correct only bit-flips, but not bitinsertions or bit-deletions, the Hamming distance metric is the appropriate way to measure the number of bit errors. Many FEC coders also continuously measure the current BER. A more general way of measuring the number of bit errors is the Levenshtein distance. The Levenshtein distance measurement is more appropriate for measuring raw channel performance before frame synchronization, and when using error correction codes designed to correct bit insertions and bit-deletions, such as Marker Codes and Watermark Codes. II.MATHEMATICAL MODEL The BER is the likelihood of a bit misinterpretation due to electrical noise w(t). Considering a x1(t)=A+w(t) to find the final expression : III. FADING Fading is the term used to describe the rapid fluctuations in the amplitude of the received radio signal over a short period of time. Fading is a common phenomenon in Mobile Communication Channels, where it is caused due to the interference between two or more versions of the transmitted signals which arrive at the receiver at slightly different times. The resultant received signal can vary widely in amplitude and phase, depending on various factors such as the intensity, relative propagation time of the waves, bandwidth of the transmitted signal etc. A fading channel is a communication channel in which deviation of the attenuation affecting a signal over certain propagation media. In wireless systems fading may either be due to multipath propagation shadowing from obstacles affecting the wave propagation. bipolar NRZ transmission, we have for a "1" and x0(t)= -A+w(t) for a "0". Each of x1(t) and x0(t) has a period of T. Knowing that the noise has a bilateral spectral density of No/2 , A common example of multipath fading is the experience of stopping at a traffic light and hearing an FM broadcast degenerate into static, while the signal is re-acquired if the vehicle moves only a fraction of a meter. The loss of the broadcast is caused by the vehicle stopping at a point where the signal experienced severe destructive interference. Cellular phones can also exhibit similar momentary fades. SLELCTION DIVERSITY IV. RAYLEIGH FADING Rayleigh fading is a statistical model for the effect of a propagation environment on a radio signal, such as that used by wireless devices. Rayleigh fading models assume that the magnitude of a signal that has passed through such a transmission medium (also called a communications channel) will vary randomly, or fade according to a Rayleigh distribution — the radial component of the sum of two uncorrelated Gaussian random variables. Of the N received signals, the strongest signal is selected. When the N signals are independent and Rayleigh distributed, the expected diversity gain has been shown to be , expressed as a power ratio. Therefore, any additional gain diminishes rapidly with the increasing number of channels. This is a more efficient technique than selection combining. Sometimes more than one combining technique is used – for example, lucky imaging uses selection combining to choose (typically) the best 10% images, followed by equal-gain combining of the selected images. Zk = (Z1k, if |Z1k| > |Z2k| Z2k, if |Z2k| > |Z1k| V.DIVERSITY One of the most efficient and simple techniques to overcome the destructive effects of fading is Diversity. Diversity is an efficient technique to exploit the random nature of radio propagation by finding methods to generate and extract independent signal paths for communication. The concept behind diversity is relatively simple if one signal path undergoes a deep fade at a particular point of time, another independent path may have a strong signal. By having more than one path to select from, both the instantaneous and average SNR can be improved in the receiver by a large amount. There are various types of diversity used in communication systems operating over fading channels. They are:• Space Diversity. • Frequency Diversity. • Time Diversity. • Polarization Diversity. • Multipath Diversity. EQUAL GAIN COMBINING In Equal Gain Combining (EGC), all the received signals are co-phased at the receiver and added together without any weighting. The performance of EGC is only marginally inferior to the optimal maximal ratio combiner. In case of a two-fold diversity scheme, the combining equation is given by: Zk = Z1k + Z2k Whatever be the diversity technique employed, the receiver has to process the diversity signals obtained in a fashion that maximizes the power efficiency of the system. There are several possible diversity reception methods employed in communication receivers. The most common techniques are: •Selection Diversity. •Equal Gain Combining (EGC). •Maximal Ratio Combining (MRC). MAXIMAL RATIO COMBINING In Maximal Ratio Combining (MRC), the signal all the branches are co-phased and individually weighed to provide the optimal SNR at the output.It can be shown that the output SNR is maximized when the signals in each of the diversity branches are weighed by their own envelopes. In case of a twofold diversity scheme, the combining equation is given by: Zk = r1kZ1k + r2kZ2k protection channel for automatic use by any faded channel. Later examples include: • OFDM modulation in combination with subcarrier inter leaving and forward error correction • Spread spectrum, for example frequency hoping Where, r1k and r2k represent the instantaneous envelopes of the signals received at each of the diversity branches. TIME DIVERSITY SPACE DIVERSITY The signal is transmitted over several different propagation paths. In the case of wired transmission, this can be achieved by transmitting via multiple wires. In the case of wireless transmission, it can be achieved by antenna diversity using multiple transmitter antennas (transmit diversity) and/or multiple receiving antennas (reception diversity). In the latter case, a diversity combining technique is applied before further signal processing takes place. If the antennas are far apart, for example at different cellular base station sites or WLAN access points, this is called macro diversity or site diversity. If the antennas are at a distance in the order of one wavelength, this is called micro diversity (STC). FREQUENCY DIVERSITY The signal is transmitted using several frequency channels or spread over a wide spectrum that is affected by frequency-selective fading. Middle-late 20th century microwave radio delay lines often used several regular wide bands radio channels, and one Multiple versions of the same signal are transmitted at different time instants. Alternatively, a redundant forward error correction code is added and the message is spread in time by means of bitinterleaving before it is transmitted. Thus error bits are avoided, which simplifies the error correction. POLARIZATION DIVERSITY Multiple versions of a signal are transmitted and received via antennas with different polarization. A diversity combining technique is applied on the receiver side. MULTIPATH DIVERSITY Multiuser diversity is obtained by opportunistic user scheduling at either the transmitter or the receiver. Opportunistic user scheduling is as follows: at any given time, the transmitter selects the best user among candidate receivers according to the qualities of each channel between the transmitter and each receiver. A receiver must feed back the channel quality information to the transmitter using limited levels of resolution, in order for the transmitter to implement Multiuser diversity. VI.QUADRATURE AMPLITUDE MODULATION Quadrature amplitude modulation (QAM) is both an analog and a digital modulation scheme. It conveys two analog message signals, or two digital bit streams, by changing (modulating) the amplitudes of two carrier waves, using the amplitude-shift keying (ASK) digital modulation scheme or amplitude modulation (AM) analog modulation scheme. The two carrier waves, usually sinusoids, are out of phase with each other by 90° and are thus called quadrature carriers or quadrature components. The modulated waves are summed, and the resulting waveform is a combination of both phase-shift keying (PSK) and amplitude-shift keying (ASK), or (in the analog case) of phase modulation (PM) and amplitude modulation. QAM Transmitter Output using BPSK Modulation First the flow of bits to be transmitted is split into two equal parts: this process generates two independent signals to be transmitted. They are encoded separately just like they were in an amplitude shift keying (ASK) modulator. The sent signal can be expressed in the form: where and are the voltages applied in response to the symbol to the cosine and sine waves respectively. Output using Diversity in BPSK Modulation QAM Receiver The receiver simply performs the inverse process of the transmitter. Its ideal structure is shown in the picture below with the receive filter's frequency response : Multiplying by a cosine (or a sine) and by a lowpass filter it is possible to extract the component in phase (or in quadrature). Then there is only an ASK demodulator and the two flows of data are merged back. Output using QAM Modulation Output using 64 QAM Output using 128 QAM Comparing Outputs of BPSK and QAM CONCLUSION Output using 16 QAM We have studied the effect of fading amplitude and diversity combining techniques on the BPSK over flat Rayleigh fading channels. The results areobtained by averaging the conditional BER over the jointdistribution of the fading and its estimate. The exact BERexpressions are given by finite-range integrals. Thus by diversity technique we can improve our signal to noise ratio by three techniques which one is suited the best. We find that for 16-QAM and 64-QAM, amplitude estimation error yields degradation in average SNR, and combined amplitudephaseestimation error yields a greater degradation for the systemparameters. Our results allow the designers ofM-QAM to easily choose system parameters tomeet their performance requirements under reasonable channel conditions. We have also found out various future aspects to find out new techniques and device ways for better communication.These techniques has shown us the path for a lot more better communication methods with an excellent accuracy and better efficiency. Thus it has opened new ways for finding more efficient techniques that will change the course of future. VII. REFERENCES [1] D. Brennan, "Linear diversity combining techniques", Proc. IRE, vol. 47, no. 6, pp.1075 1102 1959 . [2] R.Price and P. E. Green, "A communication technique for multipath channels", Proc. IEEE, vol. 46. [3] G. L. Stu¨,ber, Principles of Mobile Communications, 1996 :Kluwer . [4] J. W. Craig, "A new, simple, and exact result for calculating the probability of error for twodimensional signal constellations", Proc. IEEE Milit. Commun. Conf. MILCOM',91, pp.571 -575 1991. [5] G. L. Turin, "Communication through noisy, random-multipath channels", IRE Nat. Conv. Rec., pp.154 -166 1956 .