5.4 Outer loop based on power distribution
5.4.1 Power distribution analysis
The transmitted powers in both uplink and downlink between mobile stations and base stations are limited with a maximum and a minimum effect. From the maximum effect pmax there are steps of 2 dBm down to the minimum effect pmin. The maximum and minimum powers are pmin= 16 dBm, pmax= 30 dBm. The transmitted power are described in equation 3.3 in section 3.2.
If link quality is low, transmitted powers with higher effect are used and lower effects are used when link quality is high. However, a simple method that estimates the amount of users not limited by the power range could be described as,
regulating f raction = number of pbetween max and min
total number of p . (5.6) In equation 5.6 regulating f raction is defined as the number of users transmitting with power level between the minimum and maximum value, divided with the total amount of transmitted powers. Only looking at the regulating fraction does not give any information about how to change qdes.
Another estimate that takes this into consideration is the difference between the number of users transmitting with maximum respectively minimum ef-fects,
P Cdif f = number of pmax− number of pmin
total number of p . (5.7)
This value will be positive if many mobiles are transmitting with high power and negative if many mobiles are transmitting with low power.
The idea is that if a high number of mobiles transmit with a power in between the minimum and maximum value, then good system quality should be achieved because there is high usage of power control. This holds only if high usage of power control implies good system quality, in other words if usage of power control correlates with the number of satisfied users. To examine this some simulations on the existing system with fixed qdes has been done.
In Figure 5.7, the power distribution are displayed in histograms. The histograms are from two different occasions, one with a relatively low traffic load and the other with a relatively high traffic load. As we see in the figure, for the same qdes, when there are higher traffic load, a lot of mobiles are transmitting on maximum effect. If the method could regulate the algorithm to decrease the powers for some of those mobiles a higher regulating fraction would be accomplished. This is the idea of how this method should work.
16 18 20 22 24 26 28 30
Figure 5.7: Histograms for two different occasions. In the left plot the system has experienced a relatively low traffic load and in the right a relatively high traffic load.
The correlation between the regulating fraction and the number of satis-fied users gives a hint of whether there is a relation between the transmitted power distribution and quality. As mentioned before, regulating fraction is defined as the amount of powers that is not transmitting on minimum or maximum effect. The number of satisfied users is defined as the amount of mobiles with the average FER, during the lifetime of a connection, lower than one percent, as defined in section 5.3.1.
In Figure 5.8 the amount of satisfied users are plotted against qdes for a specific traffic load. The figure below shows how the amount of satisfied users changes by an adjustment of qdes. This plot is for a situation with fixed environment conditions. The qdes value that implies the highest amount of satisfied users may however, vary with the environment conditions.
0 10 20 30 40 50 60 70 70
75 80 85 90 95 100
qdes
Number of satisfied users [%]
Satisfied users for different qdes
Figure 5.8: Number of satisfied users for a specific condition for different qdes.
The correlation between the regulating fraction and the number of sat-isfied users gives a hint of whether this method could be useful or not. . In Figure 5.9 these two parameters are plotted against qdes for a fixed low traffic load.
0 10 20 30 40 50 60 70 70
75 80 85 90 95
Amount of users for different qdes, low load
qdes
Satisfied users [%]
0 10 20 30 40 50 60 700
50 100
Regulating fraction [%]
Satisfied users Regulating fraction
Figure 5.9: The usage of power control and the amount of satisfied users plotted for different qdes. The traffic load is fixed and low.
The figure above shows that the maximum value for the both lines ap-pear at approximately the same value of qdes, and the curves have similar appearence. This high correlation indicates a relation between the regulating fraction of the transmitted powers and the number of satisfied users. This means that information of the power distribution could be used to increase the amount of satisfied users. If the system strives to find the value of qdes that gives the highest regulating fraction, this will also imply that the sys-tem achieves the highest number of satisfied users. The same situation as above is plotted in Figure 5.10, but with a higher load. In this plot the both maximum values appear approximately at the same value of qdes. Obvious from these two figures is that an increase in traffic load decreases both the number of satisfied users and the regulating fraction.
0 10 20 30 40 50 60 70 70
75 80 85 90 95
Amount of users for different qdes, medium load
qdes
Satisfied users [%]
0 10 20 30 40 50 60 700
50 100
Regulating fraction [%]
Satisfied users Regulating fraction
Figure 5.10: The plot shows the regulating fraction of the transmitted powers and the number of satisfied users for a high traffic load.
The same situation as above is plotted in Figure 5.11, but with a even higher traffic load. In this plot the both maximum values do not appear at the same value of qdes. However, the results points to a relation between the number of satisfied users and the regulating fraction of the transmitted powers.
0 10 20 30 40 50 60 70 70
75 80 85 90 95
Amount of users for different qdes, high load
qdes
Satisfied users [%]
0 10 20 30 40 50 60 700
50 100
Regulating fraction [%]
Satisfied users Regulating fraction
Figure 5.11: The plot shows the regulating fraction of the transmitted powers and the number of satisfied users for a high traffic load.
Figure 5.12 below shows plots of the difference, P Cdif f , for some differ-ent traffic loads. A high value, in other words a high difference, means that many mobiles transmit with maximum effect, which imply that a change in qdes is desirable. Achieving the value zero correspond to finding the optimal value of qdes for this situation.
0 10 20 30 40 50 60 70
Difference between no. of max and no. of min powers
qdes
PCdiff [%]
Low load Medium load High load
Figure 5.12: The difference between number of mobiles transmitting on max-imum effect and the number of mobiles transmitting on minmax-imum effect for some different traffic loads.
From the figure above it is visible that the lines for the different traffic load are almost linear and have the same slopes. Assuming that they in fact are linear with the same slope means that it is simple to adjust qdes according to the difference. A change in P Cdif f implies a change in qdes. If the optimal values for the difference is zero this plots could be compared to the plots showing the regulating fraction in Figure 5.9 to 5.11. The maximum values of the regulating fraction appears at higher values when the traffic load is increased. The same behaviour could be seen in Figure 5.12. Where the lines crosses zero appears not exactly at the same qdes as where the regulating fraction has the maximum value, for the same traffic load.