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in a commercial environment. For example a cost
minimization value of 3.21 was achieved in 45
minutes for the Siemens 1 scenario utilizing ten
predators, alpha = 0.95 and beta = 0.99. Best results
were found when using less than twenty predators,
0.9≤alpha≤0.99 and 0.9≤beta≤0.999 in all the COST
259 scenarios.
Table 1: COST 259 Siemens scenarios.
Siemens 1: GSM 900 network with 179 active sites, 506 cells, and an average of
1.84 TRXs per cell. The available spectrum consists of two blocks containing 20
and 23 frequencies, respectively
TRX pairs exceeding App Cost Co Adj TRX
.01 .02 .03 .04
K-THIN 2.20 0.03 0.03 0.05 33 4 1 0
TUHH 2.78 0.04 0.04 0.08 60 14 6 0
RWTH 2.53 0.03 0.03 0.06 48 11 3 0
TA 2.30 0.03 0.03 0.05 43 7 2 0
U 3.36 0.05 0.04 0.12 78 25 10 3
SEMA 2.35 0.03 0.03 0.06 44 9 2 0
Siemens 2: GSM 900 network with 86 active sites, 254 cells, and an average of
3.85 TRXs per cell. The available spectrum consists of two blocks containing 4
and 72 frequencies, respectively
TRX pairs exceeding App Cost Co Adj TRX
.01 .02 .03 .04
DTS 14.28 0.11 0.02 0.20 343 89 24 18
K-THIN 14.27 0.07 0.02 0.16 359 71 27 17
TUHH 15.46 0.07 0.02 0.18 404 109 42 20
RWTH 14.75 0.06 0.02 0.17 268 91 34 13
TA 15.05 0.11 0.02 0.20 381 92 37 15
U 17.33 0.08 0.02 0.20 462 148 47 18
SEMA 14.86 0.08 0.02 0.17 364 87 41 14
Siemens 3: GSM 900 network with 366 active sites, 894 cells, and an average of
1.82 TRXs per cell. The available spectrum comprises 55 contiguous frequencies.
TRX pairs exceeding App Cost Co Adj TRX
.01 .02 .03 .04
DTS 5.19 0.04 0.03 0.07 88 14 3 0
K-THIN 4.73 0.03 0.02 0.08 80 6 0 0
TUHH 6.75 0.05 0.03 0.11 137 31 9 2
RWTH 5.63 0.03 0.03 0.07 103 15 3 0
TA 5.26 0.04 0.03 0.07 87 10 3 0
U 8.42 0.05 0.04 0.12 188 47 18 6
SEMA 5.76 0.03 0.03 0.08 101 28 3 0
Siemens 4: GSM 900 network with 276 active sites, 760 cells, and an average of
3.66 TRXs per cell. The available spectrum comprises 39 contiguous frequencies
TRX pairs exceeding App Cost Co Adj TRX
.01 .02 .03 .04
DTS 81.88 0.20 0.05 0.43 2161 971 547 344
K-THIN 77.25 0.19 0.05 0.36 2053 871 445 282
TUHH 89.15 0.24 0.03 0.53 2350 1056 591 368
RWTH 83.57 0.18 0.04 0.35 2251 1006 540 343
TA 80.97 0.17 0.03 0.36 2143 933 502 328
U 105.82 0.27 0.04 0.53 2644 1286 798 562
SEMA 81.96 0.21 0.05 0.48 2181 991 549 353
5 RESULTS OF
IMPLEMENTATION
The SEMA was tested on a commercial mobile
telecommunications network in South Africa,
namely MTN. The SEMA was applied to one
operational base station controller (BSC). There
were 349 cells with an average of 3 transmitters per
cell in the BSC. The available spectrum consisted of
two blocks containing 24 and 31 frequencies,
respectively. The frequency plan produced by the
SEMA took on average several days to produce. The
frequency plan produced by the SEMA was also
implemented into the mobile telephone network. The
%DROP (percent drop) parameter represents the
percentage of abnormal disconnections (drop calls)
on the BSC in a mobile cellular network. From
figure 1 it is clear that there was a decrease in the
%DROP on the BSC after the SEMA frequency plan
was implemented. This can be seen by studying the
%DROP before and after the vertical yellow broken
line. The vertical yellow broken line depicts the
point at which the SEMA was implemented into the
BSC (see the label “Swarm AFP run in”). Swarm
AFP stands for the Swarm automatic frequency
planner that implements SEMA. The measurement
before this mark depicts the initial network
measurements while all measurements after the
mark depict the network after the SEMA frequency
plan was implemented. The decrease in the %DROP
was a substantial 0.4 on the %DROP scale. This may
not seem significant, but in terms of the %DROP on
a cellular network that prides itself on its low
%DROP, a decrease of 0.4 is amazing. An
improvement of 0.4 on the %DROP scale on a BSC
carrying a large amount of traffic can equate to a
large addition in revenue. To substantiate the actual
decrease of a 0.4% on the %DROP scale, the traffic
(erlang rate) would have to have remained constant,
since a decrease in the erlang rate would also cause a
decrease in the %DROP. However, by studying
figure 1 it can be seen that the erlang rate remained
constant (see the horizontal black broken line which
represents the erlang gradient), while there was a
distinct decrease in the %DROP after the SEMA
was implemented. Usually when a frequency plan is
implemented an increase in the %CFAIL is
experienced. The %CFAIL (percent channel failure)
parameter represents the percentage failure rate in
the ability to seize a traffic channel. The reason for
this is that most frequency plans relax the adjacent
channel rule for the traffic channels, as the major
concern is to minimize co-channel interference on
the TCHs and to ensure that there is absolutely no
co-channel or adjacent channel interference between
the BCCH and TCHs. Again, an encouraging feature
noted in figure 1 is that the BSC did not suffer from
an increase in the %CFAIL. The %CFAIL remained
fairly constant after the SEMA implementation. This
indicates that the actual frequency planning that was
taking place by the SEMA was of good quality.
Overall the SEMA frequency plan performed fairly
well by decreasing the %DROP by 0.4% on the
%DROP scale and did not cause the %CFAIL to
fluctuate in an increasing way after the frequency
plan was implemented.
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