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Eye Diagrams in Software Draw EAN-13 in Software Eye Diagrams

Eye Diagrams using barcode implementation for software control to generate, create ean-13 image in software applications. Microsoft Office Development. Microsoft Office 2000/2003/2007/2010 The eye diagram gives EAN-13 Supplement 2 for None a qualitative measure of system performance [3]. A wellde ned and open eye usually indicates good performance, while a poorly de ned eye usually indicates poor performance. In addition, the size of the eye relates to the accuracy required of the symbol synchronizer.

While the eye diagram does not provide a quantitative measure of system performance, it is di cult to conceive of a high-performance system having a poorly de ned eye diagram. The generation of an eye diagram is illustrated in Figure 8.4.

Three segments of a waveform, with each segment corresponding to a symbol period, are shown. Segment 1 Segment 2 Segment 3 (a) Three segments (60 samples) of a waveform Segment 1 Segment 3 (b) Three-segment eye diagram Figure 8.4 Generation of an eye diagram. i i i i i TranterBook 2 003/11/18 16:12 page 309 #327. Section 8.2. Estimation in Figure 8.4. The wa Software EAN-13 Supplement 5 veform corresponding to three data symbols is illustrated in Figure 8.

4(a). Assume that this waveform is displayed on an oscilloscope and that the oscilloscope is triggered at the points denoted by the dotted vertical lines. The result will be the three-segment eye diagram illustrated in Figure 8.

4(b). Example 8.1.

In this example, several important signals present in a /2 DPSK system are generated and displayed. The MATLAB program for simulating the system and generating the graphical output is given in Appendix A. Upon entering the program name, c8 pi4demo, at the MATLAB prompt, a menu is presented.

From this menu the user may select one of the following seven options (after a plot is generated, hitting the space bar will display the menu so that another selection can be made): 1. Un ltered /4 DQPSK signal constellation 2. Un ltered 4 DQPSK eye diagram 3.

Filtered /4 DQPSK signal constellation 4. Filtered 4 DQPSK eye diagram 5. Un ltered direct and quadrature signals 6.

Filtered direct and quadrature signals 7. Exit program (return MATLAB prompt) The student should study the material in Appendix A closely, as it illustrates many of the common postprocessing procedures. In addition, the code used for generating the various plots can be used in the postprocessor of other simulation programs.

Here we illustrate three of the more interesting results. Figures 8.5, 8.

6, and 8.7 illustrate the scatter plot (signal constellation), the direct and quadrature channel signals, and the direct and quadrature channel eye diagrams, respectively. [Note that by visualizing the three-dimensional signal in the (D, Q, t) space as previously discussed, the relationship between Figures 8.

5 and 8.7 is easily seen.].

Estimation Many useful estimatio Software EAN13 n routines are based on data generated by a simulation program. Here we consider only a small sampling of the many possibilities..

Histograms When a set of samples EAN-13 Supplement 2 for None of a random process is available, as will be the case in a simulation environment, a histogram formed from that set of samples is frequently used as an estimator of the underlying probability density function (pdf). The histogram is formed by grouping data, consisting of N total samples, into B bins. i i i 1 0.5 0 -0.5 -1.

Quadrature Channel i TranterBook 200 EAN/UCC-13 for None 3/11/18 16:12 page 310 #328. -1.5 -1 -0.5 0 Direc t Channel 0.5 1 1.5 Figure 8.5 Filtered signal constellation. Direc t Quadratute 1.5 1 0.5 0 -0.5 -1 -1.5 0 0.1 0.2 0.3 0.4 0.5 0.6 Norm aliz ed Tim e 0.7 0.8 0.9 1 1.5 1 0.5 0 -0.5 -1 -1.5 0 0.1 0.2 0.3 0.4 0.5 0.6 Norm aliz ed Tim e 0.7 0.8 0.9 1 TranterBook 2003/ 11/18 16:12 page 311 #329. Figure 8.6 Un ltered direct and quadrature signals. 2 1 0 -1 -2 0 5 10 15 20 25 S am ple Index 30 35 40 45 2 1 0 -1 -2 0 5 10 15 20 25 S am ple Index 30 35 40 45. Quadratute Direc t i TranterBook 200 UPC-13 for None 3/11/18 16:12 page 312 #330. Figure 8.7 Filtered eye diagram. i i TranterBook 2 EAN13 for None 003/11/18 16:12 page 313 #331. Section 8.2. Estimation or cells. Each bin is assumed to have equal width W , and the center of each bin is denoted bi . A given sample x[n] falls into the ith bin if bi W W < x[n] bi + 2 2 (8.

4). The quantity of inter Software ean13+2 est is Ni , which denotes the number of samples falling into the ith bin. Clearly. (8.5). We adopt the notation Software European Article Number 13 Count{N : R} to represent the number of samples, in the set of N total samples, falling into the histogram bin de ned by R. Thus Ni = Count N : bi W W < x[n] bi + 2 2 (8.6).

A bar graph is then p lotted in which the height of each bar is proportional to Ni , and each bar is centered at bi . In order to be an estimator of the pdf, the histogram is scaled so that the total area is one. This is accomplished by dividing Ni by N W .

The height of each bar is then Ni /N W . The area of the bar, Ai , representing the ith histogram bin, is found by multiplying the height by the width W . Thus Ai = Ni NW W = Ni N (8.

7).
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