Mobile Positioning in CDMA Cellular Networks Erol Hepsaydir University of Technology, Sydney Hutchison Telecoms, Sydney
[email protected] the simulations, real time measurements were performed at eight fixed locations and in a moving vehicle. It was observed that the averaged mobile positioning rms-error was 83 m in a Gaussian-like channel. One of the test locations suffered from a severe multipath propagation which resulted in an averaged rms-error of 504 m. The current CDMA standard, IS95 has limitations to implement the mobile positioning application with a high level of In order to increase the mobile accuracy. positioning accuracy in CDMA networks, the required future developments are also discussed,in this paper.
Abstract: Mobile positioning in cellular networks will provide several services such as, locating stolen mobiles, emergency calls, network self optimisation, different billing tariffs depending on where the call is originated and many more. The IS95, 2"dgeneration digital Code Division Multiple Access (CDMA) cellular standard [l], has potential to accommodate mobile positioning in its architecture. Moreover, on the eve of the 3G wireless network standardization, required steps must be taken for the implementation of mobile positioning. In this paper, mobile positioning in CDMA cellular networks has been discussed, the simulation and the measurement results using standard CDMA mobile phones, are presented. The purpose of this study is to analyse the accuracy of mobile positioning using standard CDMA mobile phones. Positioning calculations were performed in the mobile station using the CDMA forward link channels in order to provide total privacy. This technique can also be incorporated in the 3G, WCDMA networks.
2. MOBILE POSITIONING ALGORITHM
The CDMA forward link consists of four channels i.e. pilot, synch, paging and traffic channels [l]. The MS acquires the pilot channel to synchronize to the short PN code phase. When synchronized to the cell, the MS measures the PILOT-ARRIVAL' time of the pilot channel. The MS measures the PILOT-ARRIVAL' time of a cell when it is promoted to the 'Active Set' which means that the MS is in a soft handoff with the new cell [l]. The MS can communicate with up to three cells when it is in a 3-way soft handoff, so it can 'PILOT-ARRIVAL' times measure three simultaneously. Thus, for the mobile positioning application, it is desirable to have large soft handoff regions. However, this means that extra Channel Elements will be required in the network which will result in a decrease in the available network capacity and an increase in the infrastructure cost. One of the objectives of the optimisation engineers is to reduce soft handoff regions to less than 40% of the overall coverage area. As a result, the CDMA networks should be optimized with the mobile positioning applications in mind.
1. INTRODUCTION
The CDMA Mobile Station (MS) measures the Time Of Arrival (TOA) of each pilot channel arriving at its antenna port. A minimum of three simultaneous TOAs is required to locate the mobile station. The MS synchronizes its system timing to the CDMA system time using the SYS-TIME, value obtained from the received synch channel message [l]. The MS measures the TOA of a pilot channel when the pilot channel is in the Active Set. In this paper, hyperbolic positioning will be used to locate the mobile. The Time Difference Of Arrival (TDOA) between two cells represents a hyperbola. Two hyperbolas may intersect at two points. Therefore a third hyperbola is required to eliminate the ambiguity [2, 31. In this paper, the mobile positioning algorithm was simulated and a rms-error of 74 m was achieved in Gaussian channel at an EJIo value of -13 dB. The rms-error increased significantly from 74 m to 250 m when the multipath channel was introduced. Following
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The CDMA standard IS95 specifies that the MS shall use the strongest multipath component for demodulation. In certain locations the multipath signal may be stronger than the direct path and the
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The mobile’s location (x, y) can be calculated by solving the following equations:
mobile station will report the ‘PILOT-ARRIVAL‘ of the multipath signal instead of the direct path. As a result, significant mobile positioning error will occur depending on the reflected path length. In order to improve the accuracy of self positioning in CDMA cellular networks, the following future developments should be implemented:
- Xi)’
(X
- ~ 3 ) ’ + (Y - y3)’ =L3”(LI
(x - xJ2
The MS should search for the direct path signal and measure the ‘PILOT-ARRIVAL‘ of the direct path instead of the strongest multipath component; The MS should perform ‘PILOT-ARRTVAL’ measurements from a minimum of three base stations when a mobile positioning request is received from either the user or the network; and
(Y - Yi)’ =LI‘=(C Tpd#
(X
+ (Y - yJ2 =Lz’=(LI + 113’=c2 (Tpdl + t13’ + 113) ’=
Cz
(Tpdi + tI.#
where, t,, is the TDOA between cell 1 and cell 2 measured at the mobile terminal; tI3 is the TDOA between cell 1 and cell 3 measured at the mobile terminal; lI2 is the path difference between cell 1 and cell 2; I,, is the path difference between cell 1 and cell 3; (x, y) is the location of the MS; (xi,yJ, (.>, y 3 and (x3, yJ are the locations of the cell 1, cell 2 and cell 3 respectively. 3. SIMULATIONS
The Base Station Controller (BSC) may also force the MS to go into a 3-way soft handoff by adjusting the pilot power levels of the surrounding cells, Todd and Td,op values. The MS then measures the time of arrival of the new cells promoted to the Active Set.
The mobile positioning algorithms have been simulated in various environments as modeled in figure 2. The Gaussian and Rayleigh random variables were generated using the Box-Muller and the Jakes methods respectively [4].
Each TDOA represents a hyperbolic locus (figure 1). The TDOA between two cells can be calculated as:
TDOA
(PILOT-ARRIVAL,-PILOT-ARRIVAL3
PN Code Generator I
I
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64 x (PN-OFFSET, - PN-OFFSET3 where, PN-OFFSET, and PN-OFFSET, are unique short PN code phases for celll and cellz respectively. There are 512 PN-OFFSETS in a CDMA network. Each PN-OFFSET represents 64 chips which corresponds to a 52 usec phase shift.
PN-o:FSET 1
Rayleigh Channel1
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Rayleigh Channel2
Rayleigh Channel3
Hyperbola 1
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Estimator
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Figure 2: Simulation block diagram
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The model in figure 2, consists of three cells. The Rayleigh channel for each cell was made up of two reflective paths. The Rayleigh coefficients were independent for each path. The configuration of the
Figure 1: Hyperbolic positioning
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TOA 2
Estimator
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multipath channel simulator for a slow moving MS is specified by the IS98, CDMA MS standard [5] as follows: Number of paths is 2; Path 2 power relative to path 1, is 0 dB; and Delay from path 2 to path 1 is 2 chips.
A positioning rms-error of 74 m was achieved in a Gaussian channel at an E,& value of -13 dB. The simulation was run for 300 samples. Each estimated sample in two dimensions is shown in figure 5 before the samples were averaged.
A sample correlator output is shown in figure 3 in the presence of a multipath signal.
I x-axis
Figure 5: The estimated mobile positions (E&o=-13 dB)
Time
Figure 3: Correlator output of multipath simulator The accuracy of the mobile positioning is specified as follows:
rms-error=,/E{(X-x)2 + ( Y - y ) 2 } where:
m
In order to increase the accuracy, the estimator output was filtered by using the following algorithm: Samples that have a large variation from the mean estimated value were removed; and They were then averaged over 25 samples.
(X,Y) is the mobile's true location; and (x,y) is the mobile's estimated location.
The rms-error is defined above as the radius of the circle, produced from the square root of the sum of the square of the error components centred at the mobile's true location (X, Y).
The estimated mobile positions following the filter were shown in figure 6. After the filtering, the standard deviation of rms-error reduced from 41 m to 9 m. The averaged rms-error also reduced from 74 m to 16 m.
Gaussian Channel Simulations: The accuracy of estimated mobile positions was obtained at different E& values in a Gaussian channel. 300 samples were recorded and the averaged rms-error was calculated for each E& value (figure 4). 160,
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Figure 4: Mobile positioning accuracy in Gaussian Channel.
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Figure 6: Estimated mobile positions following the filter A posteriori probability densities of the estimated x and y-axis are shown in figure 7. It can be seen that the estimated x and y-axis have Gaussian-like probability densities as expected.
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Test Point 8 4
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-
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Figure 9: Test locations
Figure 7: A posteriori probability densities of mobile's estimated x and y-axis.
As shown in figure 9, the test locations were amongst four base stations. This configuration provided a minimum of three simultaneous TOA values in the field. Following fixed location measurements, the rms-error was 182.6 m. When the filter was applied to the estimated mobile positions, the rms-error reduced to 138.8 m. The standard deviation of rms-error also reduced significantly from 107.2 m to 51.2 m following the filtering (Table I).
Rayleigh Channel Simulations: Once the multipath was introduced in the simulations the averaged rms-error increased from 74 m to 250 m. The estimated mobile positions in the presence of multipath are shown in figure 8.
x-axis
Figure 8: Estimated mobile positions in multipath channel at E& = -13 de. The output of simulator was filtered as discussed above and the averaged rms-error reduced from 250 m to 156 m. The standard deviation of the rms-error also reduced from 127 m to 44 m. Table 1: Fixed location measurement results
4. MEASUREMENTS Real time measurements were performed in an operational CDMA network. The test locations were carefully selected to record three simultaneous PILOT-ARRIVAL' times from a minimum of three base stations (figure 9). Measurements were performed at eight fixed locations and in a moving vehicle [6]. The test configuration was a standard CDMA mobile terminal connected to a laptop. Data was logged into a file and consequently the mobile's location was estimated using the data collected in the field.
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As shown in table 1, at the test location 6, the averaged rms-error is significantly higher than the other test locations. The filtering would not provide a substantial improvement under these channel conditions where the direct path's E& value is lower than reflected signals. Thus it is essential to estimate the direct path's TOA in order to improve the accuracy in multipath channels. The estimated mobile positions in two dimensions are shown in figure 10.
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1100
2 900
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x axis Figure 13: GPS data collected during the drive test
x-axis (m)
Figure 10: Estimated mobile positions at location 6
On the other hand, the estimated x and y-axis of the mobile locations at the test location 4 show Gaussian-like distribution. The estimated mobile positions and the probability densities of x and yaxis are shown in figure 11 and 12 respectively -
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x axis Figure 14: Estimated Mobile positions in a vehicle 5. CONCLUSION In this paper, mobile positioning application in CDMA networks has been investigated through simulations and measurements. The current CDMA architectural limitations in order to implement mobile positioning have been discussed. It is important to note that, the MS should search for the direct path signal for the CDMA mobile positioning in order to improve the accuracy, especially in multipath channels. It was also shown that the rms-error could be improved significantly by averaging the estimated samples.
Figure 11: Estimated mobile positions at location 4 40
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1
.. .A.. .y a ~ s
30
6 . REFERENCES [l]IS-95-A, "MS-BS Compatibility Standard for Dual Mode Wideband S S Cellular system" [2]J. Caffery, G.L. Stuber "Subscriber Location in CDMA Cellular Networks", May 1998, IEEE Trans on Vehicular Technology, Vo1.47, No 2. [3] C.R.Drane "Positioning Systems, A Unified Approach", 1992, Springer-Verlag [4]William C. Jakes "Microwave Mobile Communications", 1993, IEEE Press. [5]TWEIA-98-B, Recommended Minimum Performance Requirements for Dual Mode Spread Spectrum Cellular Mobile Station", 1998 [6]E.Hepsaydir "Analysis of Mobile Positioning Measurements in CDMA Network", Accepted to be presented in IEEE RAWCON'99, Denver
rms-error (m)
Figure 12: Distribution of estimated x and y-axis Measurements were also performed in a moving vehicle at a speed of 40 km/hr. The averaged rms-error reduced from 184 m to 121 m when the output was averaged over 50 samples [6]. Figure 13 and 14 show the GPS data collected during the drive showing the drive test route and the estimated mobile positions respectively.
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