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Current procedures for network design estimate the radio network performance on the basis of empirical propagation models, whose accuracy is largely dependent on the precision with which the actual environment has been modelled in the tool Adjustments of planning parameters, such as base locations, antenna tilt and orientation, BTS output power or frequency plans, are normally carried out during the design phase following a trial-and-error approach During the subsequent deployment phase, some limited further eld-based tuning of the previously mentioned parameters is performed on the basis of the feedback data obtained from drive tests or key performance statistics Finally, during the operational phase, operators x parameters in radio resource algorithms to common sets of default values shared between cells, even if not optimum performance in terms of quality/capacity is achieved, as the large set of parameters makes the detailed parameter planning process on a cell-by-cell basis a time-consuming task.

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In the meantime, ATM was available, ATM was the international standard for cell relay, and ATM was for everything There are actually two ways to employ ATM to link frame relay switches The first makes the frame relay switches look like ATM premises devices on the ATM network The frame relay switches have only an ATM interface, however The second way, which is becoming very common, is to make the frame relay switch into an ATM switch at heart Now the ATM (frame relay) switch UNIs are still frame relay UNIs, but the links between the ATM switches with frame relay UNIs are now ATM network-node interfaces (NNIs) This sounds complex, so a few more words might be needed to straighten it all out..

Unfortunately, this homogeneity hypothesis may be far from reality, as propagation, interference and traf c distribution vary both in space and time throughout the network As a consequence, degradation of system performance is observed In cases where existing speci c features are extremely sensitive to network peculiarities (eg traf c management in complex urban scenarios), tailoring of parameters is sometimes performed by means of eld trials carried out on isolated areas, which de ne the default values to be applied across the network To account for non-homogeneity in the space domain, few advanced operators extend parameter optimisation to different scenarios (eg rural, urban, tunnel, indoors) or layer/band (eg Macro900/1800, Micro900/1800, Pico1800, Motorway900).

Nonetheless, cell-by-cell parameterisation is rarely considered because of time and cost constraints, so parameter retuning is normally carried out only on those cells where performance problems exist, so the potential of parameters that can be adjusted on a cell-by-cell (or even adjacency-by-adjacency) basis is not fully exploited Even if optimum parameter values were reached to deal with spatial peculiarities, network behaviour is still changing with time Temporal variation results from a combination of both long-term trends (ie user growth) and periodical changes (ie season, day and hour periods) Whilst slow trend variation can be easily coped with by means of network re-planning, no automatic instantaneously reactive process is currently in use, still remaining as a challenging optimisation task.

When you are working with an element, you might simply want to check to see whether it has child elements before doing anything else with it. You can test to see whether an element has child nodes by invoking the hasChildNodes() method from the element. It returns true if child nodes exist, and false if there are no child nodes:

The outer div, shadow, includes shadow.gif as a background image based in the lowerright corner. It also uses the Important Hack to send different margin values to Internet Explorer on Windows. You ll remember that most modern browsers (with the exception of Internet Explorer on Windows) will use any declaration with the !important property in place of a later declaration.

From this analysis, it can be concluded that the exibility emerging from the existing large set of parameters included in various network algorithms cannot be currently fully utilised because of the complexity in current networks and a lack of tools to fully support this activity Obviously, a great potential gain can be obtained from automatic parameter tuning and optimising processes that take advantage of cell and adjacency parameters Such strategy would help operators during the deployment and operational stages, providing bene t from cost savings and improved performance despite changes of the environment both in space and time Automatic optimisation has clear and direct bene ts for the operators, since it aims at maximising radio performance for a given network infrastructure through a minimum manual effort Keeping the network in an optimum point continuously, operators can minimise traditional overdimensioning factors, thus reducing the infrastructure costs to.