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The expected coupling matrix encodes information regarding traffic density, load distribution, and interference coupling in a UMTS radio network. This information gives hints on quality and performance of the network. Radio network design can thus be viewed as designing a networks coupling matrix. This is the motivation for the optimisation model outlined in this section. The model is described in detail in [57], it works by computing the contributions of the pixels in the area to the coupling matrix. Contributions to the main diagonal and coverage. For each installation configuration, a configuration selection variable xi is used. Again, the server of each point is determined using assignment variables yip . The assignment variables are held exactly: yip is only set to one, if i is the strongest server at p. This depends on the configurations of other sectors, so selection variables are linked in constraints on the assignment variables. As the coupling matrix s main diagonal only depends on the server of each point, it can be calculated from this information. Off-diagonal elements. The off-diagonal elements depend on the relative strength of the signals at each point, so their calculation is more involved. Assignment variables of second order are therefore introduced for each pair of server and potential interferer. Since this can lead to very large models, only the strongest interferers are considered in practical applications. Model usage. The resulting linear mixed integer programming model allows to calculate coverage and the expected average coupling matrix for any given set of candidate installations. A linear objective function formulated in the area coverage and the entries of the coupling matrix can then be optimised with integer programming software. This allows weighted combinations of the different optimisation goals: (a) maximising coverage, (b) balancing load between cells, and (c) reducing interference coupling. asp.net ean 13 EAN - 13 ASP . NET Control - EAN - 13 barcode generator with free ...
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