Performance Analysis of GSM Networks with Intelligent Underlay-Overlay

  
Khalid Begain , Gergő István Rózsa , András Pfening , Miklós Telek

Dept. of Computing, University of Bradford BD7 1DP, Bradford, West Yorkshire, England, UK, kbegain@bradford.ac.uk

Matáv Hungarian Telecommunications Company Ltd., Budapest, Hungary, Rozsa.Istvan.Gergo@mail.pki.matav.hu

Nokia Telecommunications, Mobile Switching Budapest, Hungary, andras.pfening@ntc.nokia.com

Department of Telecommunications, Technical University of Budapest, H-1521 Budapest, Hungary, telek@hit.bme.hu

Abstract troduce hierarchical structures like micro- and picocells [2],

The paper presents an analytical model for a GSM-based [3]. This approach works well to a certain extent, however
cellular mobile network that applies the Intelligent Under- the denser base station grid results in increased interference
Overlay (IUO) scheme to increase the capacity by increas- that limits the quality and so the capacity in terms of soft
ing the frequency reuse while maintaining the service qual- blocking. Furthermore, the additional network elements
ity. The IUO is a multi-layer cell structure that is based on like base stations and transmission network cost quite a lot.
dividing the frequency band into the super layer and the reg- The most promising way of capacity enhancement requires
ular layer frequency group. The super frequencies (chan- minor investment while allowing more capacity with minor
nels) can be used by mobile stations with good C/I (car- or no degradation of service quality. Two methods shall be
rier/interferer) ratio, while the regular frequencies can be mentioned here, the frequency hopping (FH, [4]) and the
used over the whole cell. The use of IUO is expected to pro- intelligent underlay-overlay proposed by Nokia Telecom-
vide up to 40% gain of capacity [1]. In this paper, we study munications (IUO, [1]). (Recently Nokia proposed the IFH
the effect of various parameters on the performance of the technology, which combines IUO and FH. This is out of the
networks using IUO and provide practical planning support scope of the paper.) Both methods are similar in the sense
based on the analytical results. The considered parameters that they allow more frequencies to be used in the exist-
include network parameters like super area coverage and ing cells, that is increase the reuse factor, introducing minor
mobile user mobility parameters like moving mobile ratio investment cost. As a result of the tighter reuse, the interfer-
and average mobile speed. ence in the network will be higher. The two methods differ
in how they cope with the increased interference. In FH,
Keywords: Cellular mobile networks, GSM, IUO, Per- the established speech connection is hopping on a number
formance analysis. of frequencies. A number of those frequencies are ”clean”,
that is do not suffer from serious interference, while the
other frequencies are interfered. Due to the averaging ef-
1 Introduction fect of the different coding principles, the noise brought by
The demand for wireless communication grows rapidly the interfered frequencies is eliminated. The IUO princi-
nowadays. The capacity of cells in the existing digital cel- ple is to make use of the measurements done by the mobile
lular mobile networks, like GSM, will have to meet the in- station, MS. The MS always measures the strongest neigh-
creased demand. The network operators have to face the bors of the serving cell in order to know when to make a
problem, how to increase the capacity of an existing net- handover to a neighbor cell. This measurement data is used
work without noticable degradation of quality of service. to estimate the C/I conditions of the MS. If the estimated
Different solutions can be foreseen. The most obvious so- C/I is good enough, the MS is assigned a (heavily reused)
lution would extend the GSM band or increase the number so-called super frequency, while if the C/I is bad, a clean
of serving channels or frequencies in an area. However the regular frequency is assigned to the MS. This way the super
overall available GSM spectrum is limited and is usually di- frequencies (channels) can be used by mobiles with good
vided between 2 or 3 network operators leaving a spectrum C/I ratio, while the regular frequencies can be used over the
of not more than 10 MHz for each operator. Another solu- whole cell. The frequency band is divided into two groups,
tion is to deploy more base stations (cell splitting), or to in- a super layer and a regular layer frequencies, and a lower
 frequency reuse factor, thus a smaller area of coverage is
 This work has been partially supported by OTKA T 034972. assigned to the super layer.
Correspondence author

1
 The origin of IUO principle was reuse-partitioning. It ally used only near the Base Transceiver Station (BTS). The
was presented in some papers [5, 6, 7]. [5] presented the other band contains frequencies that can be used throughout
DCA (dynamic Channel Assignment) with a greedy algo- the whole cell, the regular frequencies.
rithm, and investigated 1 dimensional cellular radio system. Every IUO cell has regular and super Transmitter Re-
Simulation results were reported on IUO in [8, 9, 6]. In [10], ceivers (TRXs). Regular frequencies completely cover the
the performance of GSM network implementing IUO in cell. These frequencies can be reused by conventional crite-
combination with Frequency hopping was studied by sim- ria, using safe hand-over bounds to provide low probabili-
ulation. Some further improvements on the original IUO ties for interference. Mobile stations are assigned to regular
scheme were suggested. The effect of these improvements frequencies at the boundary where C/I rate is under a spe-
was reported in [11]. In this paper, we introduce an analyti- cific level. Figure 1 shows the principle of the layer struc-
cal model of GSM network implementing IUO and provide ture of IUO.
results on the performance of the network taking into ac-
count many parameters like the coverage factor of the super
layer to the whole cell, the ratio of moving mobile stations, Super layer
and the speed at which they are moving. Our paper gives C/I bad
practically useful view on the above mentioned parameters.
C/I good
Network designers can directly apply the provided results to
dimension their network with improved reuse of the spec- Regular layer
trum in cellular radio systems.
With the applied analysis approach we calculate the net-
work performance parameters by considering a large ho- Figure 1. IUO principle
mogeneous network composed by a lot of identical cells, Super frequencies provide services in heavy traffic areas
whose handover traffic to the neighboring cells is symmet- (downtown) of the cell, where C/I rate is good (interference
ric. This assumption on the homogeneous network with free area). Using different C/I ratios, the coverage of the
symmetric handover traffic allows us to calculate the net- super layer (super frequencies) can be controlled. If IUO is
work performance based on the analysis of a single cell. combined with downlink power control, even better inter-
The analysis of inhomogeneous network with asymmetric ference conditions can be maintained resulting in better call
handover traffic of neighboring cells, that would require a quality.
much more complex analysis approach, is out of the scope
of this paper. 2.2 Operation of IUO
In Section 2, we give a description on the operation of
IUO scheme. Section 3 summarizes the main assumption We assume the call admission operation of GSM net-
on the studied systems and defines the main processes that work without IUO is known [12]. The IUO cell operation
affect the performance of the system. The analytical model is described separately for standing (non-moving) and mov-
will be defined in Section 4 with which the performance ing mobile stations (MS). The IUO algorithm does not dis-
analysis of a cell with IUO is carried out in Section 5. Some tinguish moving or not moving MSs, this separation is done
planning issues of the obtained results is summarized in for a modeling assumption: we assume that a non-moving
Section 6 and the paper is concluded in Section 7. mobile’s interference conditions will not change, and that
the mobile will not try any handovers, unlike the moving
mobile station.
2 Intelligent Underlay-Overlay
For both moving and non-moving mobile stations, the call
2.1 Principle request will first be served by a regular frequency, because
the C/I ratio of the call is not yet known. The C/I ratio is
The IUO is a feature designed to allow a tighter fre-
calculated by comparing the downlink signal of the serv-
quency reuse for some of the available radio frequencies and
ing cell with the downlink signal of all neighboring cells,
therefore achieve a higher network capacity. It implements
that use the same super frequencies.
a two-layer network structure with a different reuse factor
for each layer. The underlay adds capacity, the overlay pro- If the C/I value is better than a predefined ”C/I good”
vides coverage. To maintain optimum capacity, the base threshold, then the connection will be served by a super
station assigns mobile traffic to either layer of the network frequency, otherwise it will remain at the regular layer.
according to actual interference levels. The IUO solution If this handover to the super frequency fails, because all
splits the available frequency spectrum into two bands. One super frequencies are occupied, then the connection will
consisting of frequencies that can only be used when a high stay at the regular layer and try to get into the super layer
C/I ratio is ensured, the super frequencies, which are usu- after a specific time.

2
 For the connections of non-moving MS, the call will be
served at the same layer chosen according to the value of REGULAR
C/I until its normal termination. Super to Regular

SUPER
For the connections of the moving MS, the value of C/I ra- Super to Super Intercell hand-over
Incoming intercell
tio may change after the setup of the connection. This im- hand-over
plies a number of hand-over possibilities as follows:

1. For a connection going on a super frequency, the fol- Regular to Super

lowing hand-overs exist due to the movement of the Regular to Regular

MS:
If the value of C/I ratio falls below the ”C/I good” Figure 2. Possible handovers in the system
threshold, but there is another free super frequency
where the C/I ratio is appropriate, hand-over will be
done, and the call will be kept on the super layer. Only one cell is considered in the analysis. All the inter-
actions from the neighboring cells to the studied cell are
If there is no free super frequency, or none of these has taken into account as an aggregate incoming hand-over
an appropriate C/I ratio, the call gets back to regular request process, which will first be served by regular fre-
layer, or if all the regular frequencies are occupied, the quencies.
call will be lost.
2. For a connection going on a regular frequency, the The studied cell implements IUO scheme with the super
following handovers exist due to the movement of the layer coverage factor
 of the cell area. Only one super
MS: frequency group is assumed, i.e., the same coverage factor
is assumed for all super frequencies.
If the C/I value improves and reaches the ”C/I good”
and there is a free super frequency, the connection will 
The Base Transceiver Station of the cell manages reg-
be moved to the super layer. 
ular and super frequencies. Thus, the total number of
 
An intra-cell hand-over to regular frequency of an- frequencies (channels) in the cell is
 .
other TRX in the same cell.
An inter-cell hand-over to regular frequency of an- The cell contains moving and non-moving mobile sta-
other neighboring cell. tions. The ratio of the moving MSs is  .

3. The case of direct inter-cell hand-over from a super fre- The moving MSs are assumed to move in a uniformly dis-
quency to a neighboring cell is not considered in the tributed random direction and with a constant speed  .
model, because we assume that the C/I ratio is deter-
mined by the distance of the MS from the (closest) BTS. Super and regular frequencies of the same cell are not dis-
Hence, in our model, a super-regular hand-over always tinguished. The hand-over between regular frequencies or
preceeds the inter-cell hand-over if the coverage factor between super frequencies in the same cell are not taken
of super layer is less than 100%. In the applied frame- into account, since it does not modify the number of busy
work it would also be possible to model direct inter-cell frequencies of the layers.
hand-over from super layer based on a probabilistic rule
that describes the probability of direct inter-cell hand- The different processes that control the events in the sys-
over from super layer to a neighboring cell as a function tem are:
of the coverage factor of super layer, but it is not con-
sidered in this paper. 1. the new call arrival process is assumed to be a Poisson
process with rate  . We assume that the arrivals are uni-
Figure 2 summarizes all possible handovers in the IUO formly distributed on the area of the cell and, therefore,
cell.
 of the calls will have C/I value better than the ”C/I
good” threshold.
3 Performance analysis 2. the aggregate incoming hand-over is assumed to be a
Poisson process with rate  .
3.1 Modeling assumptions
3. the time needed for the calculation of the C/I parameter
For the sake of building an analytical model of the sys- for a new connection is assumed to have an exponential
tem, we make the following assumptions: distribution with mean of !#" .

3
 \[] O@NG^ REGULAR (
C >@? A ) =IL
4. the call holding time, i.e., the time for normal call
termination, is assumed to be exponentially distributed A VX Y =OHPRQ
= C EGH> FJ? BKA[>@Z ? ZW >H? A ) =IL
with average duration of 
. S SUPER (

S C CEHFa C >H? A Z LOSS

Zcb IFX3Y
IF

= >H? ABDCC EGF

5. The hand-over rate from super to regular frequencies \ S`\ _ B O@NG^ Y CEGF ) I= CEGFJBK>@? A
M
REGULAR (
IF S
H> ? AUTWVX3Y
and vice versa resulting from the movement of the mov-
=MN ? L I
= L
ing MS are calculated taking into account: the speed of
the MS   , the radius of the cell, the coverage factor
=>@? ABDCEGF
of the super layer, and the probability that the move-
ment of the MS will lead to increase or decrease the Figure 3. Queuing model of IUO cell
value of C/I ratio. According to this, we assume that dfe  g
the time needed for a moving MS to move from super 0h[i "0
  , where the matrix Q denotes the infinitesimal
to regular area or from regular to super area is an expo- generator of the Markov chain.
nentially distributed random variable with mean value The transition rates, the elements of matrix Q, can be
 
 or 

 , respectively. obtained from the analysis of the driving process in the sys-
6. Similarly, we assume the channel dwell time to be an tem. We follow the style used in the rule definition syntax
exponentially distributed random variable with mean of the model specification language, MOSEL [13], which
value    , which is calculated with similar consid- is based on a ”Which state follows  
    "! if...”
erations to the previous point. logic. MOSEL is a model specification and evaluation lan-
guage developed at the Department of Computer Science
IV, University of Erlangen, Germany. Figure 3 shows the
3.2 The model
considered queuing model of the cell and Table 1 provides
With the above listed modeling assumptions the consid- the rules that determine the transition rates following this
ered system (a cell) behaves as a Continuous Time Markov style The Mosel description of the model is directly read-
Chain. At any time instant the state of the cell is determined able from this set of rules.
by the number of active calls of each class of frequencies,
Event Condition Successor State Rate
tJkuGvw x
Ix tJyz{
Ixx||}}~~
H € ‚
so we define it as the vector:
New Call in reg. j3kl`monqp"rUs
 New Call in sup. j k l`monqp"rUs t kuGv t
Iyx z{ w x|}~ € l  ‚ ƒR… n„ƒJ…
 
     "! Incoming HO j k l`monqp"rUs t kuGv w t yz{ …D†
good C/I calls
|R}~ p‡„s t kuGv x t
Iyx z{ 
Ixx||}}~~ w

t|Ry}zI~ {‰ˆDŠG‹IŒ
where Super to regular j3kl`monqp"rUs tJkuGvw tJyz{ ˆ yzI{@ kuGv
j kl`monqp"rUs tJkuGvw x
Ix tJyzx|{ } ~
I xG|R
}~ tJ|Ry}zI~ { ˆKyzI{@ kuGv

 is the number of connections served by regular fre- Soft blocking j|R}k ~ l`monŽ
rUs t kuGv  t
Iyx z{ x|}~
ˆ yzI{@ kuGv
quencies and have C/I # ”C/I good”, Regular to super
|}~ Ž
p"‡1‡„ss t kuGv 
Ix t yz{
IxG|Rw }~
tJkuGv tJyz{Rw
t kRuHvUˆ kuGvyz{
tJkRuHv ˆ kuGvyz{
  is the number of connections with C/I $ ”C/I good” Call termination t kuGv  x
Ix tJy z{
Ixx||}}~~ tJkRuHv ˆK‘
t kuGv x t yz{ x|}~
t|Ry}zI~ {‰ˆ ‘
that are served by regular frequencies, (there are two rea- t kuGv t yz{ ˆ ‘
sons for this situation: new calls with C/I $ ”C/I good” are Outgoing HO t kuGv 
Ix t yz{ x|}~ t kRuHvUˆ †’ z ‘
served by regular frequencies for the period of C/I calcula-
tion; and calls with C/I $ ”C/I good” are served by regular Table 1. Transition rules and rates
frequencies if all the super frequencies are occupied.)
Parameter Value
  is the number of connections served by super fre- Number of regular frequencies, r‰s 28 (4 TRX)
Number of super frequencies, ‡1s
quencies. € ‚ 16 (2 TRX)
 
J“
Super area coverage factor, 50% (var. of study)
Let %
 !  
   and %& ! denote the number Call holding time, ˆ ‘

J“ 80s (exponential)
of occupied regular and total frequencies in the cell, respec- Time for C/I calculation, ˆ ŠH‹IŒ 5s (exponential)
Cell radius, r 3km
Ratio of moving MS, t ”–•
tively. It is clear that a permissible state must satisfy the
    ‚—™˜ 50% (var. of study)
conditions %& !('
and %
 !(' . Let ) denote Speed of moving MS, 50km/h (var. of study)
the number of feasible states. Then, we can define * to
denote the state space of the system given that the states Table 2. Default value of parameters
are conveniently ordered from + ,,, ).-  . The result-
ing model is thus homogeneous and irreducible on the finite
state space * and therefore the steady state distribution p 4 Performance analysis of a cell with IUO
= / 1032 , 4 5+ ,,, )6-  , exists, unique and can be com- In this section, we present some numerical results using
puted through the linear system of equations 798: <;  and the defined model. Table 2 summarizes the default values

4
 Loss probability Utilization Loss probability

1.0 1.0 1.0

0.9 0.1

0.1 0.8 1e−2

0.7
1e−3

Ratio of moving mobile

1e−2 Super coverage factor 0.6 Super coverage factor 0% moving
1e−4
0.25 0.25 25% moving
0.5 0.5 50% moving
0.75 0.5 0.75 75% moving
0.9 0.9 1e−5

1e−3 0.4
0 20 40 60 80 100 120 140 0 20 40 60 80 100 120 140 1e−6
0 20 40 60 80 100 120 140
Offered Traffic [Erlang] Offered Traffic [Erlang]
Offered Traffic [Erlang]

Figure 4. Loss probabilities Figure 5. Utilization for differ- Figure 6. Loss probabilities
versus super area coverage ent super area coverage versus moving MS ratio

for the parameters used in the study. The use of different in Figure 7. When the load is low then the movement helps
values will be explicitly mentioned. We present results on in reaching better utilization in the cell, while in higher load
the call loss probability and the average utilization of chan- conditions the increased movement has a negative effect on
nels (i.e., the carried traffic per channels) versus the offered the utilization of the super frequencies which results in a
traffic. Different results are provided by varying different reduced overall utilization of the cell. This is the reason
parameters: the super area coverage factor, the number of for the crossing of the utilization curves between 20 and 60
  
and (but keep their sum constant,
), the ratio of Erlang offered traffic.
moving MS, and the speed of moving MS. In all cases, the
call loss probability is computed by summing the blocking
probability of new calls and incoming handovers and the
Figures 8 and 9 examine the effect of the speed of the
moving MS given that    . Three values were
chosen to reflect the movement in the downtown area of


probability that a connection going on a super frequency city; walking speed (3km/h), vehicle speed in residential
will fail to be served due to the lack regular frequency area (30km/h), and vehicle speed in in-city main streets
when it’s C/I value drops bellow ”C/I good” threshold. In (50km/h). The results show that the increase of the speed
the model quality problems can only be due to interference implies very slight increment on the overall call loss proba-
problems indicated by leaving the super coverage area. This bility. It is because the loss probability is composed by two
interference problem can lead to call drop, referring to soft main factors: the probability of rejecting new or incoming
blocking. handover calls (referred to as blocking) and the soft block-
First, we study the effect of the super area coverage on ing. Figure 8 depicts these factors separately. The over-
the performance of the studied cell. Figure 4 shows the loss all loss probability practically coincides with the blocking
probability versus the offered traffic. The different curves probability. According to the expectations the soft blocking
refer to different super area coverage factor,
 . It can be probability is significantly affected by the speed of moving
seen that the higher
 results in lower loss probability. On MSs, but it has negligible effect on the overall loss since the
the other hand, Fig. 5 shows that decreasing the area cov- blocking probability is at least an order of magnitude higher
ered by the super layer has a negative impact on the utiliza- than the soft blocking probability. The decrease of the soft
tion of the cell. This is in consistence with the conclusions blocking probabilities from 80 Erlang offered load is due to
obtained in [10]. This means that a trade-off or optimization the high blocking probability.
should be done in the design phase of the network between The results shows that the usage of IUO has a negative
the reduced utilization and increased loss probability versus effect on the performance of one cell and, therefore, there
the capacity increased by the higher reuse factor. It can be should be an optimization for the gain of tighter reuse in
seen that the soft blocking has minor effect on the overall the multiple cell network and the loss in the performance
blocking rate even in case of high load situations. of each cell. The other conclusion is regarding the effect of
the mobility of the performance of the IUO scheme. The
In the rest of the results, we study the effect of move- results show that the IUO performs worse as mobility of the
ment on the performance of the IUO cell. Figures 6 and mobile stations increase.
7 show curves on the call loss probability and utilization.
The different curves refer to different value of the ratio of
moving MSs,   . The results show that the higher ratio
5 Planning issues
of movement results in higher loss probability which can To assist traffic dimensioning considerations additional
be explained with the higher number of handovers resulting computations were performed to evaluate the offered traffic
from the movement. The utilization point of view is shown with associated 2% loss. The input and output parameters

5
 Utilization Loss probability Utilization
1.0 1.0 1.0
Blocking

0.9 0.1 0.9

0.8 1e−2 0.8

0.7 1e−3 Soft blocking 0.7

Ratio of moving mobile
0% moving Speed of moving mobile
0.6 25% moving 1e−4 0.6 3 km/h
50% moving Speed of moving mobile 30 km/h
75% moving 50 km/h
3 km/h
0.5 1e−5 0.5
30 km/h
50 km/h

0.4 1e−6 0.4

0 20 40 60 80 100 120 140 0 20 40 60 80 100 120 140 0 20 40 60 80 100 120 140
Offered Traffic [Erlang] Offered Traffic [Erlang] Offered Traffic [Erlang]

Figure 7. Utilization versus Figure 8. Loss probabilities Figure 9. Utilization versus

moving MS ratio versus moving MS speed moving MS speed

of the described numerical analysis are the offered traffic configuration, does not mean immediate capacity degrada-
and the associated loss, respectively. Hence, to evaluate the tion. For instance, for configuration 3+2, the super cover-
offered traffic with associated 2% loss a numerical approx- age factor can be decreased down to 60% without degrading
imation is applied. We have evaluated the loss at 8, 16, 24, loosing capacity in the cell.
32, and 40 Erlang offered traffic and fit the obtained loss The same system is evaluated with 50% moving MSs.
values by a 4th order polynome (through the Fit function of From Figure 11 it can be seen that the movement of MS
Mathematica [14]). The offered traffic with associated 2% decreases the performance of the cell. The main reason of
loss is calculated as the point where the polynomial equals this performance degradation is the increased need of the
to 0.02. This approximation was found to be the best among moving MSs for regular channels. Due to the high mov-
those we tried (e.g. the fitting of the inverse of the loss func- ing MSs ratio the regular channels become the bottleneck
tion). The approximation was verified against the Erlang of the system and their availability characterize the sys-
formulae. The error falls in the range of 0.5-1.2 Erlang. tem performance. The curve of the 4+1 TRX cell con-
In Figure 10 the capacity of various cell configurations figuration is slightly decreasing above 0.6 coverage fac-
deploying IUO with non-moving MSs is compared. The tor. We think that this feature is not an evident property
figure shows the offered traffic value (in Erlangs) versus the of cellular systems with IUO, but it results from the applied
 
super coverage factor where the overall blocking probabil-  "
      
  ! , 

1       
  !
ity is 2%. The super coverage factor is ranging from 100% functions:
(the C/I conditions are good throughout the coverage area
of the cell) to 0% (only regular frequencies are used, this  
  
   
  
  3


 !  
is practically the non-IUO configuration). The cell config-
      
g   
 
urations differ in the number of regular and super TRXs,
as shown in the legend. All the configurations are shown  


[1     
 

! 
    -    ! , 
where 1 to 5 TRXs are used in the cell. For instance, with
configuration 2+3 at super coverage factor 50% maximum These functions were found to be the best (regarding the

15 Erlangs can be accepted with 2% blocking rate. overall model behaviour) to approximate the assumption
Several interesting conclusions can made reading the fig- that the MSs are uniformly distributed over the cell as well
ure. As it is expected, the curve belonging to the configu- as their moving direction.
ration A+B approximates the curve of configuration A+0 The practical use of the depicted results is as follows.
(which is of course a horizontal line) as the super cover- Assumed the network planner has N TRXs in the given cell,
age factor approaches 0. In the other end, A+B’s curve ap- he can easily compare the capacity of the different configu-
proaches the curve of configuration (A+B)+0 as the cover- rations of N+0 (no IUO), (N-1)+1 (1 super frequency), (N-
age factor approaches 100%. The difference between the 2)+2 (2 super frequency), etc. and he can immediately read
various configurations’ result stems from the assumptions the allowable super coverage factor, which is a key factor
that regular frequencies consist of 7 TCHs while super fre- for planning the reuse of the frequencies of the super fre-
quencies consist of 8 TCHs each, this also can be seen very quency plane. Thus the planner can see the possible benefits
well in the figure. For example, at 90% coverage factor the of defining some of the TRXs as super frequencies. On the
3+2 configuration (37 channels) outperforms the 4+1 con- other hand if capacity extension is needed in the cell with
figuration (36 channels). N TRXs, the network planner can compare the solutions
One the most useful outcomes of the paper is that de- (N+1)+0, N+1 or maybe N+2, where the last two cases al-
creasing the super coverage factor assuming a given cell low the planner to keep the original frequencies in the regu-

6
 30
25

25
1+2 # 7+16 20
1+3 # 7+24
1+4 # 7+32
1+2 # 7+16
1+1 # 7+8 1+3 # 7+24
20 1 # 7+0 1+4 # 7+32
2+2 # 14+16 1+1 # 7+8
2+3 # 14+32 15
1 # 7+0
2+1 # 14+ 8 2+2 # 14+16
2 # 14+ 0 2+3 # 14+32
15 3+2 # 21+16

Traffic [Erlang]
2+1 # 14+ 8
Traffic [Erlang]

3+1 # 21+ 8 2 # 14+ 0

3 # 21+ 0 10 3+2 # 21+16
4+1 # 28+ 8 3+1 # 21+ 8
10 4 # 28+ 0 3 # 21+ 0
5 # 35+ 0 4+1 # 28+ 8
4 # 28+ 0
5 # 35+ 0
5
5

0
0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
0 0.2 0.4 0.6 0.8 1 Super coverage factor (lines at 0.02 loss probabilities)
Super coverage factor (lines at 0.02 loss probabilities)

Figure 10. Performance of different cell config- Figure 11. Performance of different cell config-
urations with non-moving MSs urations with moving MSs

lar TRXs and finding new frequencies for the super TRXs, [5] M. Frodigh, Reuse partioning combined with traffic
which frequencies may suffer interference, handled by IUO. adaptive channel assignment for highway microcellu-
lar systems Globecom ’92

6 Conclusions [6] S. Papavassiliou, L. Tassiulas, P. Tandon, Meeting

QoS requirements in cellular network with reuse par-
The paper presented an analytical model for GSM-based titioning IEEE Journal of selected areas in Communi-
cations, 1994
cellular mobile network that implements the Intelligent
Underlay-Overlay scheme to increase the frequency reuse [7] J. Zander, Generalized reuse partitioning in cellular
and, therefore, the capacity of the network. The Markov mobile radio, Proc. Veh Tech Conf, 1993
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using this scheme on the one-cell performance taking into Intelligent Underlay and Overlay Network, Proc. of
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