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burst via an alternate satellite (say) every fth burst. By noting the strengths of the regular and alternate bursts, the subscriber terminal could determine which satellite presently affords the best path to the gateway Earth station and could adjust its own burst time and frequency to select that satellite. For more coverage on other existing land satellite PCS, the reader is referred to the original papers [34 36].
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14.7. MEGA-CELL GLOBAL NETWORKS DESIGN Prediction of radio and cellular maps for full coverage of the Earth s surface, using determined constellations of satellites, CEO, MEO, or LEO, is based on most strict statistical and physical-statistical propagation models. The models take into account the average path loss along all three sub-links : land, atmospheric, and ionospheric. These effects can be postulated as worst (or bad) or convenient (or good) with intermediate variants good-bad and bad-good, obtained from numerous measurements carried out in these three sub-links. In s 6 and 7, we showed how to take into account fading phenomena for a link budget design and how to predict radio coverage for the atmospheric and ionospheric links. It was also shown that for the frequencies of interest operated in land satellite links, the effects of these two subchannels on total path loss and fading are not so signi cant. More essential fading effects are observed in the land communication sub-channel. To show the reader how to predict the land-link total path loss and to obtain a mega-cell radio coverage using speci c satellite constellations, we developed a mathematical tool. This planning tool is based on results obtained in References [29 33] and is able to show the ef ciency of the general approach proposed in previous sections to resolve the problem of link budget design and outage probability of path loss prediction within any LSC link. Thus, in our calculations we combine two models, Loo s model and the three-state Markov model, that account for the effects of overlay pro le of the buildings. For this purpose, we introduced the PDFs, Pa r , Pb r , and Pc r , for LOS, multipath and shadow effects description, respectively. Here, each status, a, b, and c, corresponds to a transaction from bad to good situations within a wireless link, depending on environment phenomena. Then, for each situation within the channel, we took the corresponding PDF, P a , P b , and P c , (the lognormal, Rayleigh, and Rician, respectively). Next, the following cumulative formula for determining the probability of fading phenomena within the satellite link is found as Ptotal r P a Pa r P b Pb r P c Pc r 14:53
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Below, we present the different coverage maps based on the planning tools developed in References [29 33] in order to understand the differences between satellite networks and their effect on the network s foot print. Thus, in Figure 14.31, the cellular map of Iridium network [29,30] with uniform radio coverage of the Earth s surface is presented.
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FIGURE 14.31. Computed foot print patterns of the Iridium network. (Source [29]: Reprinted with permission # 1991 IEEE)
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Figure 14.32 illustrates the cellular map for GlobalStar network [31,32]. The corresponding constellation covers most of the populated area of the Earth. But the polar areas of the Earth cannot be covered by this system. It is seen that a medium orbit satellite (MEO) constellation covers the Earth with only 12 satellites with great overlapping, which is caused by their relatively high altitude.
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FIGURE 14.32. Computed foot print patterns of the Globalstar network. (Reprinted with permission from Globalstar)
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FIGURE 14.33. Simulation output of probability to obtain a smaller acceptable path loss for varying satellite elevation angles.
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Now we present some outputs derived from our calculation of the general physical-statistical model described by the cumulative formula (14.53) to demonstrate the actions of our own simulation tool and its ability to be adapted to different cellular network and various environments: urban, suburban, rural, and open. The output parameters computed by the proposed tool are probability of fading, path loss, link budget, radio and cell coverage, LCR, AFD, and BER. First, we varied the satellite elevation angle; Figure 14.33(a) (d) shows the increase of the probability to obtain a smaller path loss with an increase in the number of satellites or with a decrease in the elevation angle. Second, we investigated the same probability versus the maximum accepted path loss for different satellite networks. Results are presented in Figure 14.34(a) (d), where one network is virtually created by us. The difference between the networks is seen in the x-axis. It is clear that the differences in results are due to the varying satellite altitudes and the downlink operational frequency. Finally, we showed how the terrain, as the land channel environment, affects the probability to obtain a smaller acceptable path loss. Figure 14.35(a) (d) shows a difference between obtained results for different land environments. Results were obtained for a low elevation satellite. As expected, the main difference is noticeable in the urban environment, due to its special propagation features such as multiple diffraction, scattering, and re ection.
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FIGURE 14.34. Simulation output of probability to obtain a smaller acceptable path loss for varying global networks.
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FIGURE 14.35. Simulation output of probability to obtain smaller acceptable path loss for varying land environments. 601
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