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GPRS and 3G Wireless application - Anderson C.

Anderson C. GPRS and 3G Wireless application - Wiley publishing , 2001. - 356 p.
ISBN: 0-471-41405 -0
Download (direct link): gprsand3gwirelessapplica2001.pdf
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LMU
Figure 13.4 UL-TOA architecture.
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Figure 2.6 I-Mode growth.
directly transferable to the rest of the world. Some argue that the low Internet penetration in Japan has made the Japanese turn to their mobile devices for those services that many others can access from their home computer. Others claim that the enterprise market and business-to-business (B2B) is much more pervasive in, for instance, the United States— implying that entertainment will not necessarily be the most popular application everywhere. It is however important to see I-Mode as more than just a technology and a mark-up language. Rather, it is a concept and a way of doing business by giving the users what they want. In the process, the application developer can easily charge for the services, and this open approach from NTT DoCoMo has been a significant success factor.
As of late 2000, more than a million new I-mode subscribers were added every month. Many wireless evangelists have used this success as an example of the incredible potential of the mobile Internet.
What Makes the Mobile Internet Take Off?
Looking at the examples of I-Mode of Palm.net, we can see some common denominators that created a massive increase in takeup. The three major factors are as follows:
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with all handsets—even with those that never were designed with position features in mind.
You can expect the accuracy of UL-TOA to be between 50m in urban areas where base stations are densely deployed and 150m or more in rural areas.
CGI-TA
UL-TOA requires additional equipment to be installed on the operator’s network, which some operators might be reluctant to do. An even simpler method of positioning by using the network is to look at the cell in which the user currently exists. This information is already available on the network; therefore, you do not need any network add-ons. We commonly call this method Cell Global Identity (CGI). The granularity of CGI, of course, depends on the cell size but usually is sufficient for proximity services (where is the closest restaurant, for example). Depending on which configuration you use, the resulting positioning area (the area where the user is located) is either a circle (an omnisector antenna configuration) or an approximate circle sector (when three sectors and directional antennas are used, as seen in Figure 13.5).
In order to take even more information into account that is already available on the network, you can use the Timing Advance (TA). TA is a measure of how far away from the base station the mobile user is (and therefore, you can shrink the uncertainty area of the positioning). The same configurations as in Figure 13.5 with CGI-TA appear in Figure 13.6.
The accuracy for CGI-TA is in the range of 100 to 200m, which is a very good result for such a simple method that works with legacy handsets.
Which Solutions Will We Use, and What Are the Consequences?
We will implement all of these solutions many times—in some instances, applying more than one solution to the same system—because of their complementary features. An excellent example is a network where we use A-GPS for those handsets that support it (when we are outdoors; line of sight to the satellites) and then use CGI-TA as an indoor method to fall back on and for users who do not have GPS receivers. A-GPS seems to stand out from the rest by providing excellent accuracy even in rural areas, but on the down side, it adds the most to the cost of the handset. Those systems that can position low-end and legacy handsets are always appealing, because they enable instant mass-market access.
Team-Fly®
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Figure 13.5 CGI positioning areas.
Because the positioning functionality is abstracted from the developers and (most of the time) from the user, the available technology does not make much of a difference to developers. Of course, some applications will rely on the highest level of accuracy for fully featured operations, but even then a solution that we can fall back on must be acceptable. The main aspect apart from that is the time that it takes to achieve the position. This time consists of two parts: the delay to get to the positioning center, and the time that it takes for the center to determine the desired position.
Because the positioning server is likely to be part of the service network, the developer needs to ensure that the application server that hosts a location-based application is located in such a way that it can communicate with the positioning center as quickly as possible. If you use HTTP over TCP/IP in order to achieve the position, the famous handshakes will make enough delays themselves so that the link (at least) will be fast. If an application server has a ping rate of 500ms just to get to the positioning center, this delay will be noticeable to the user.
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configuration
Omnisector configuration
Figure 13.6 CGI-TA positioning areas.
In addition to the communications delay, some positioning methods take time to deliver the result. For E-OTD, for example, location processing times (the delay before achieving the requested position) have been measured at three to five seconds, and those figures are reported by the most convinced evangelists of the technology. A GPS system without network assistance can need as much as 45 seconds of processing time, while A-GPS shortens that time to one to eight seconds. For UL-TOA, the delays should be in the same range as E-OTD (a couple of seconds). Keeping this factor in mind when designing applications leads us to minimize the calls to the positioning center (and possibly designing it concurrently with other tasks).
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