digital modulation performance, Study Guides, Projects, Research of Electrical Engineering

Download digital modulation performance and more Study Guides, Projects, Research Electrical Engineering in PDF only on Docsity! ABSTRACT This paper proposed a review on Adaptive Modulation and Coding (AMC) that implemented in Long Term Evaluation (LTE) network in optimizing the Quality of Service (QoS). The main study of this method is on the performance trade-off of the modulation schemes used and understand the used of QPSK, 16QAM, and 64QAM. The modulation schemes is achieved by simulation of NI LabView software and MATLAB for plotting the graph that is related to this review. Simulations are carried out under the changes in Noise Ratio and Bit Error Rate which is very challenging. The superiority of the proposed review over the understanding is confirm 35% increase in understand the AMC. It is envisaged that the review can be very useful in understanding the QPSK, 16QAM and 64QAM. INTRODUCTION QPSK QPSK is another form of modulation and is a very fascinating one because it actually transmits 2 bits per symbol. The QPSK symbol does not mean 0 or 1— it is 00, 01, 10, or 11. This output of two-bit per symbol can be achieved, as carrier variants are not limited to two states. QPSK is an advantage for bandwidth efficiency compared with modulation schemes that transmit one bit per symbol. Picture a BPSK (binary phase shift) device with an analog baseband signal, for example. Instead of using four phase changes, BPSK can only transmit one bit per symbol. The signal of the baseband has a certain frequency and a bit can be transmitted during each bit duration. A QPSK system can use the same frequency band signal, but transmits two bits during each period of the symbol. Thus the efficiency of its bandwidth is (ideally) twofold higher. M-QAM Quadrature Amplitude Modulation, QAM, is a signal for modulating and combining two carriers that moved by 90 degrees in phase (sine and cosine). As a consequence of their disparity in 90 ° process they are four-square and the name comes from this. The first signal is often called the in-phase or "I" and the second signal is the square signal or "Q." There are both amplitude and phase variations on the resulting global signal consisting of the mixture of I and Q carriers. Since amplitude and phase variations also occur, the mixture of amplitude and phase modulation can be considered. The fact that a direct amplitude modulated signal, the double sideband even with a removed carrier, takes up doubles of the bandwidth of the modulated signals is the reason for the use of quadrature amplitude modulation. The usable frequency range is very inefficient. QAM maintains the balance by putting two separate suppressed transmission signals in the same range as a single standard suppressed transmission signal on a double sideband. PROBLEM STATEMENT Given that the symbol rate is 20Mbps and using Root Raised Cosine filter to simulate the bit error probability versus ratio of Energy per bit to the Spectral noise Density and also simulate the average data rate versus ratio of Energy per bit to the Spectral noise Density for QPSK, 16QAM and 64QAM. OBJECTIVES 1. Simulate the modulation of QPSK, 16QAM and 64QAM using LABVIEW. 2. Plot the curves of QPSK, 16QAM and 64QAM using MATLAB simulation. 3. Compare the result obtain from simulation. METHODOLOGY: Throughout the work we have used LABVIEW for getting real time and theoretical data values for QPSK, 16 QAM and 64 QAM. Firstly, we have have taken the BER actual value and theoretical value for QPSK ,16QAM and 64 QAM. As, signal was going through AWGN channel, signal faced some random changes. For theoretical BER we have used the following equations, For QPSK, PE = 2Q( (Eb/No) sin (/4) For M-QAM, PE= 4(1- 1/M) Q(2M/M-1) (EB /No)) PB=PE/K for 1>>PE Here, M is the modulation order, PE is the probability of error for the modulation scheme, PB is the probability of bit error and EB/No is BER of signal. we have plotted graph for visualizing PB Versus SNR(EB/No) in MATLAB Simulink by using the derived data’s from LaBVIEW Simulink . Then again we have taken the actual data rate and average data rate from LABVIEW simulator and plotted it in MATLAB. The theoretical data rate formula is R=kRs (1-PB) , where Rs is the symbol rate. RESULT AND DISCUSSIONS: Data from LabVIEW QPSK Eb/No (dB) BER Data Rate (Mbit/s) ACTUAL THEORETICAL ACTUAL AVERAGE 3 1 1 0 40 4 5.1696e-1 6.5500e-1 17.64 19.32 5 5.0969e-1 5.5900e-1 13.80 19.61 6 5.1615e-1 5.2152e-1 19.14 19.35 7 4.1413e-1 5.0250e-1 20.18 23.43 8 3.8534e-1 4.9950e-1 38.38 24.59 9 3.7981e-1 4.9550e-1 20.02 24.81 10 2.1402e-1 4.0541e-1 19.90 31.44 11 5.3629e-3 8.0000e-3 39.68 39.79 12 1.9241e-3 3.0000e-3 39.88 39.92 13 6.8046e-4 5.0000e-4 39.98 39.97 14 1.0008e-4 3.4127e-4 40 40 15 5.3868e-5 0 40 40 16 0 0 40 40 16QAM Eb/No (dB) BER Data Rate (Mbit/s) ACTUAL THEORETICAL ACTUAL AVERAGE 15 1 1 0 0 16 5.0039e-1 5.1375e-1 39.76 39.97 17 3.9282e-1 5.0300e-1 45.46 48.57 18 3.8009e-1 4.9975e-1 47.2 49.60 19 3.7826e-1 4.8350e-1 50.22 49.74