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Adjacent channel interference in UMTS systems in

the 2000 MHz and 2500 MHz bands

João Nobre and António Rodrigues

Instituto de Telecomunicações / Instituto Superior Técnico

Technical University of Lisbon

Lisbon, Portugal

E-mail: joaodgnobre@gmail.com,antonio.rodrigues@lx.it.pt

Abstract— The purpose of this paper is to evaluate the impact of

adjacent channel interference in network coverage and capacity,

and find a strategy to minimize it. This strategy consists of

identifying the optimal spacing between adjacent carriers in the

radio spectrum available for use. To define this strategy, first the

issue of dead zones is analyzed. Here, for different spacing

between adjacent carriers, the size of dead zones is calculated. It

s concluded that for a carrier separation of 10 MHz the dead

zones are almost inexistent, and that it can be eliminated by co-

localizing the base stations. To analyse the impact of the adjacent

channel interference in the network capacity, several simulations

are done, using a static simulator, for different types of scenarios.

The simulations are done considering both the 2000 MHz and the

2500 MHz bands. It was noticed that, for both bands, when there

is a high number of BS, the impact of adjacent channel

interference is minimal, due to a more significant interference

coming from BS/MT operating in the same frequency. It was also

concluded that the macro carrier should be placed in the centre

of an operator’s available spectrum and that, when micro and

macro BS operate in adjacent channels, those should be

separated by 10 MHz, in order to minimize the losses in the

capacity of both operators.

Keywords- HSDPA, HSUPA, adjacent channel interference, dead

zones.

I. INTRODUCTION

In a multioperator environment, the way WCDMA mobile communications are distributed in the spectrum, does not contemplate the use of guard bands between different operators, regarding that spectrum is the most scarce and valuable good of a radio system. Therefore, and once one does not have perfect filtering on the base station (BS) side or, more significantly, on the mobile terminal (MT) one, channels will leak and receive power into and from adjacent carriers, respectively. This type of interference is known as adjacent channel interference, and can be minimized through a careful frequency deployment.

The purpose of this paper is to evaluate the impact of adjacent channel interference in network coverage and capacity, and find a strategy to minimize it. This strategy consists of identifying the optimal spacing between adjacent carriers in the radio spectrum available for use, being possible to choose the distance between carriers from the same operator

or from adjacent operators. It is defined by 3GPP a raster of 200 kHz for the spacing between channels, which means that this spacing can vary in increments of 200 kHz around 5 MHz.

The study consists of four main sections. In section 2, an overview of adjacent channel interference in terms of coverage and capacity is presented. In section 3 a brief description of the simulator implemented is outlined. The main results obtained are depicted in section 4, and in section 5 the conclusions of the work are presented, as well as some guidelines for future work.

II. INTERFERENCE IN UMTS NETWORKS

A. Dead Zones

The concept of dead zone is a physical area where it is not possible to keep the necessary QoS of a certain service due to a weak received signal. When a MT enters in one of these zones, the connection is lost and it is not possible to establish a new one.

The existence of adjacent channels is the reason to the existence of dead zones. The smaller the separation between those channels frequencies is, the smaller is the isolation between them, and, consequently, the higher the interference situation and the probability of occurrence of a dead zone is. Thus, it is necessary to do the correct adjustment in the separation of adjacent carriers, within the existent limitations, in order to minimize the problem.

The location of the interfering BSs is also an important factor to the existence or nonexistence of dead zones. If two operators with adjacent carriers have their BS co-localized, the problem of dead zones barely exists. That happens because when BSs are co-localized, the BS that is serving the MT, through power control, will decrease the MT transmission power. Therefore, the interference being caused by the MT to the other operators BS decreases (UL case). In the DL situation, once the MT is at the same distance from both BS, there will be no problem with the signal to noise ratio received resulting from adjacent channel interference. In case of no co-localization, the problem of dead zones might exist. The worst situation of no co-localization is the case when a BS is located in the extreme of the coverage area of the operator using the adjacent channel. Another parameter that influences the

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existence of dead zones is the adjacent channel selectivity (ACS) of the MT.

B. Interference

In the UMTS system it exists interference in the modes TDD, FDD and between both of them (in the 1920 MHz frequency). The focus of this paper is the interference in the FDD mode, and so, all the subsequent aspects related to interference are in respect to the FDD mode. Regarding who is causing the interference it can be divided in two different situations: intra-cell interference and inter-cell interference. The first one is the interference generated in a cell, caused and experienced by both the BS and the MTs inside that cell, and the second one is the interference caused by the BS and MTs of the adjacent cells. Two possible scenarios of interference can occur: MTs causing interference to BSs (uplink) or, BSs causing interference to MTs (downlink). In the case of interference in the uplink, which is strongly related to the load distribution, it is caused by MTs inside the serving cell and MTs served by BSs in the adjacent cells. In the downlink case the MT can experience interference from its own serving BS, due to the loss of orthogonality between codes, and from the BSs operating in adjacent cells.

There are two types of extreme situations caused by the existence of interference: in the uplink the worst case happens when a MT gets too close to a BS operating in an adjacent channel, being the MT capable of blocking the BS (BS receptor saturation); in the downlink, the most problematic situation is when a BS blocks all the MTs operating in an adjacent channel, in a near area (MT receptor saturation).

When characterizing the UMTS system, each radio channel is given a bandwidth of 5 MHz, and the channels allocated are positioned beside each other in uplink and downlink bands separated from each other by 190 MHz [1]. Thus, the strategy to minimize interference consists on finding the optimal spacing between carriers in the spectrum available for use. According to 3GPP, the nominal channel spacing is 5 MHz, but this value can be adjusted in order to obtain a better performance in a particular deployment scenario. Therefore, 3GPP defines a raster of 200 kHz, which means that the spacing between carriers can vary in increments of 200 kHz around 5 MHz.

Considering a chip rate of 3.84 Mcps, the bandwidth used by a transmission in WCDMA, according to 3GPP recommendations, must be inferior to 5 MHz for 99% of the total transmitted power. The out of band emissions are specified in terms of a mask for the emission filter and an adjacent channel power ratio (ACPR). The characterization of the adjacent channel interference is usually made through the use of some parameters.

The Adjacent Channel Leakage Ratio (ACLR) determines how much of the transmitted power is allowed to leak into the first and second adjacent carriers. According to 3GPP recommendations, it is specified a maximum value for the ACLR of 33 dB for the MT and 45 dB for the BS, for an adjacent carrier separation of 5 MHz. For a separation of 10 MHz it is specified a minimum ACLR of 43 dB for the MT and 50 dB for the BS

The Adjacent Channel Selectivity (ACS) is a measure of a

receiver’s ability to receive a W-CDMA signal at its assigned

channel frequency in the presence of an adjacent channel signal

with a certain separation from frequency of the assigned

channel. ACS is the ratio of the receive filter attenuation on the

assigned channel frequency to the receive filter attenuation on

the adjacent channel(s). The minimum required values for

ACS, specified by 3GPP, re of 33 dB both for BSs and MTs.

In order to measure the combined effects of transmission

and reception in the adjacent band, the Adjacent Channel

Interference Ratio (ACIR) is defined as:

(1)

It measures the ratio of the transmission power to the power

measured after a receiver filter in the adjacent channel(s). Both the transmitted and the received power are measured with a filter that has a Root-Raised Cosine filter response with roll-off of 0.22 and a bandwidth equal to the chip rate. Both types of interference occur in downlink and uplink. Once the filter in the MT is poorer than the one in the BS, the MT plays the dominant part both in the downlink (ACSMT<ACLRBS) and uplink situation (ACLRMT<ACSBS). The ACIR values considered in this paper are presented in Table 1.

Table 1 – Values of the filters used in BS and MT. ACIR (dB) Separation

(MHz) UL DL

4.6 27.470 32.990

4.8 31.059 32.991

5.0 32.999 32.991

5.2 34.339 32.992

10.0 42.991 42.973

The Minimum Coupling Loss (MCL) is the minimum link

loss that is required between the BS and the MT, so the interference caused does not affect either of both. This factor has special importance when a MT is too close to a BS. In this case, the transmission power of the MT is reduced, through power control algorithms, until the minimum limit is reached, but still higher than it would be desired, causing an increase in the interference beyond what would be normal. The MCL depends on several factors and the values recommended by 3GPP are 50-60 dB for micro-cells and 70-80 dB for macro-cells.

III. SIMULATOR DESCRIPTION

The simulator developed for this study was firstly intended to be adapted from the earlier developed NPSW (Network Planning Simulator for WCDMA), which is part of [2]. NPSW is a network planning tool designed for the Release 99, and so, substantial changes were required to make it possible to simulate HSDPA/HSUPA networks. The whole simulator was implemented in MatLab, and can be divided into four major modules: network initialization, users generation, HSDPA, HSUPA.

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In the network initialization all the parameters related to the base stations are defined. This simulator has the capacity to simulate different types of scenarios, with different configurations. Several types of scenarios were chose to be simulated and studied, considering both macro and micro BS. Two of them are more realist scenarios, with a high number of BS, being that in one only macro BS are used, and in the other one, micro BS are introduced in a macro BS environment. The other four scenarios are very specific configurations of the network, using only a few BSs (both macro and micro), with the purpose to create situations where the adjacent channel interference issue is more visible.

The module ‘users generation’ has the purpose to randomly distribute a certain number of users, chosen in the interface menu. The users are generated according to the services’ penetration ratio represented in Table 2, and after that they are distributed, randomly, in the network area.

Table 2 – Profile characterization.

SERVICES

PENETRATION

PERCENTAGE

[%]

QUALITY OF

SERVICE (QOS)

PRIORITY

Web 46.4 1

P2P 42.3 6

Streaming 6.2 2

Chat 3.1 5

E-mail 1.0 3

FTP 1.0 4

The first step in the HSDPA simulation is the calculation of

the link losses between the mobile terminals (MT) and the base stations (BS). In the calculation of the link losses it is already taken into account not only the value of the path loss, which is estimated by using the COST231 Walfisch-Ikegami propagation model, but also the effect of slow and fast fading and the antenna gain. The next step in the simulation is to associate each MT to a BS, and calculate the instantaneous throughput that can be offered to each user. To implement that, it must be first calculated the SINR parameter for every connection, and then, using Figure B.1, it can be estimated the maximum throughput available for each user.

It is in the calculation of the SINR that the effects of a more widely/narrowly carrier separation are taken into account by means of lower/higher interference values. After the SINR is calculated for every MT, it is calculated the maximum throughput that can be offered to each one according to their connections quality (SINR value). Finally, each MT is assigned to only one BS, which is done by connecting each MT to the BS that offers the best SINR.

The number of HS-PDSCH codes is an important parameter for the evaluation of the network performance, once that, due to that fact, the throughput served to the end user varies. One has that the maximum throughput at the physical layer, for a 16QAM modulation, is 0.96 Mbps per HS-PDSCH code, which makes 4.8, 9.6 and 14.4 Mbps for 5, 10 and 15 codes, respectively. Considering that, in real networks only 14

HS-PDSCH codes are used for data, since usually 2 HS-SCCH codes must be reserved for signalling and control, and the reduction due to the overhead of the MAC and RLC layers, the maximum throughput at the Node B is 3.36 Mbps for 5 HS-PDSCH codes, 6.72 Mbps for 10 codes and 9.4 Mbps for 15 codes. It is also needed to take into account the BLER and the overhead reduction of 10%, resulting that way in a maximum throughput at the Node B of 3 Mbps for 5 HS-PDSCH codes, 6 Mbps for 10 codes and 8.46 Mbps for 15 codes. In the implementation of the simulator it was not considered the possibility of having MTs using a different number of codes, i.e., in a simulation all the users are using the same number of codes.

To perform the analysis of the network capacity, each Node B is evaluated individually. The instantaneous throughput from all the users connect to a specific Node B are summed and then if the result is lower then the maximum allowed throughput for the Node B, all the users connected to that Node B are served without being reduced. After the reduction strategy is finalized and all the resources are distributed among the users, the interference calculation is made.

For the HSUPA module implementation, most of the decisions made were the same as the ones taken in the HSDPA implementation.

The SNR in HSUPA is the Ec/N0. For the first estimation it

was assumed the value of 6 dB for the interference margin, once at the beginning the network is substantially overloaded, which leads to a particularly high interference margin value. Using this value would make the results of the Ec/N0 very unrealistic. So the approach made to this problem was to first evaluate the network considering a normally high interference margin (6dB) and calculate the load factor per BS in that conditions. Then, at the BS where the load factor is higher than 0.9, a first reduction strategy is applied. This strategy consists of delaying the users that are causing more interference,(i.e., the MTs transmitting at a higher level), until an acceptable value for the load factor is reached. That way, it is possible to obtain a first approximation of what will be the final situation, and achieve values for the interference margin that are reasonable.

As in the HSDPA module, after the network has a stable

situation, the interference calculation is performed.

IV. RESULTS ANALYSIS

A. Dead Zones

The worst case of adjacent channel interference happens when, a MT in UL and a BS in DL, are transmitting at maximum power, and the MT is close to a BS that is transmitting in the adjacent frequency. Considering this case, it is analyzed which side of the connection, DL or UL, would be more damaged. It is assumed that the BS is transmitting with a maximum power of 44.7 dBm, and the MT with 24 dBm. For a typical macro BS the MCL (Minimum Coupling Loss) is 70 dB. It is also considered a carrier separation of 5 MHz, which corresponds to an ACIR of 33 dB. The sensitivity analysis for

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the DL and UL is presented in Table 3. Regarding the results obtained, one can notice that DL is the first side of the connection being affected, once the sensitivity loss of this one is 40.7 dB while for UL is only 24 dB. That means that before the MT in UL cause interference in the BS operating in the adjacent channel, its DL connection will be lost, due to the interference caused by that BS.

Table 3 – Desensitization comparison between DL and UL.

DOWNLINK UPLINK

INTERFERER POWER 44.7 dBm 24 dBm

MCL (MT -

INTERFERING BS) 70 dB 70 dB

ADJACENT CHANNEL

ATENUATION 33 dB 33 dB

ADJACENT CHANNEL

INTERFERECE

44.7 dBm – 70 dB

– 33 dB

= –58.3 dBm

24 dBm – 70 dB –

33 dB

= –79 dBm

TERMAL NOISE LEVEL

KTB –108 dBm –108 dBm

RECEIVER NOISE

FIGURE 9 dB 5 dB

RECEIVER NOISE

LEVEL

–108 dBm + 9 dB

= –99 dBm

–108 dBm + 5 dB

= –103 dBm

WORST-CASE

DESENSITISATION

–58.3 dBm – (–99

dBm)

= 40.7 dB

–79 dBm – (–103

dBm)

= 24 dB

In Figure 1 it is shown, for the several minimum data rates that are needed to assure a specific service, the size of the dead zone in function of the distance between the MT and the BS, to which is connected, for a carrier separation of 5 MHz and 10 MHz. It is considered that the MT is connected to a micro BS and is getting closer to a macro BS.

Figure 1 – Dead zone size (urban scenario – micro-macro).

Here, the size of the dead zone is significant. In this case, assuming a cell radius of 250-300 m, the dead zone can reach almost 80 m (with a carrier separation of 5 MHz). Thus, the dead zone radius corresponds to around 25% of the cell radius,

causing a loss of coverage area of 7%. This result associated to a micro BS may cause some problems in the network performance, once, near this type of BS, usually exists a higher concentration of users.

To further analyze the dead zones, it is performed an analysis to a more realist scenario. It is simulated a scenario with a network with several BS, from two different operators, operating in adjacent channels (5 MHz separation).

Figure 2 - Dead zones for operator 1 (BS height = 1.5m).

Analyzing the results in Figure 2 it is clear that the dead zones for operator 1 (blue) are localized in the neighborhood of operator’s 2 BS (red). Those zones are the ones where the MT cannot reach data rates over 0.512 Mbps (which corresponds to a SINR higher than 3.95 dB. However, one should bear in mind that results obtained are acquired assuming the most adverse conditions, in order to analyze the worst case.

One way of minimizing the effects of interference, and thus, avoid the existence of dead zones is the co-localization of BS using adjacent carriers. The results of the simulation regarding this solution are shown in Figure 3. It can be observed that in this case all the dead zones vanished.

B. Interference in the 2000 MHz band

This scenario is composed by a layer of macro-cells (carrier 1) and some micro-cells (carrier 2). The aim of this scenario is to create a dense urban environment where some micro-cells are introduced with the purpose to cover network hotspots (with a higher density of users), and analyze the impact of those micro-cells in the macro-cell network capacity.

The results regarding the loss of capacity, due do the use of different carrier separations, are present in Figure 4 for the downlink and in Figure 5 for the uplink. It is possible to observe that in the downlink it is the micro-cell network that is more affected, being the losses in capacity for the operator using the macro-cell network hardly perceptible. This is due to the fact that the transmitted power by a macro BS is considerably higher than the one of a micro BS (around 10 dB), and thus, the interference caused by a macro BS on a micro-

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cell is much higher then in the opposite case. In the reverse side of the connection, the uplink, it is noticed that there is a higher impact of a narrower carrier separation on the macro network, instead of the micro one, as seen before. In this case, those results are a consequence of having a higher concentration of users in a restricted area, which causes an increase in the interference experienced by the operator using the adjacent channel.

Figure 3 – Dead zones for operator 1 with co-sited BS (BS

height = 25m).

Figure 4 – Capacity loss (DL-2000 MHz).

Figure 5 – Capacity loss (UL-2000 MHz).

In this way, the impact of introducing micro BSs in a macro network cannot be neglected, especially for the smaller adjacent channel separations. When a separation of 4.6 MHz is applied, there is a loss in capacity in the macro network of about 9.25%, and for the micro network, which is less affected, around 5.7%. In contrast, when the channels are 10 MHz separated from each other, the losses in capacity diminish to less significant values.

So, regarding the results, the macro network should be placed in the spectrum the farthest away from the micro one. Thus, the best way to plan the network, is to put the carrier used for the macro network in the middle of an operator’s spectrum, being that way assured that any adjacent carrier of another operator is at least 10 MHz away, suffering less the impact of adjacent channel interference.

C. Interference in the 2500 MHz band

The scenario analyzed in the 2500 MHz band is the same as for the 2000 MHz band, in order to have a comparison basis.

It can be noticed that the capacity loss registered in both operators is in accordance with the values for the 2000 MHz band, being the exception for values for operator 2, in downlink, where the losses are higher for the smallest separations. However, if it is considered a separation of 10 MHz those losses diminish and become insignificant. The results of the capacity loss are presented in Figure 6, for downlink, and Figure 7, for uplink.

Figure 6– Capacity loss (DL-2500 MHz).

Figure 7– Capacity loss (UL-2500 MHz).

The conclusions that come out of this analysis are the same

as for the previous section. When using only macro or micro

BSs alone, the interference problems generated are no very

significant, and its impact on the network capacity can be

neglected. However, when both macro an micro BS are put

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together, the impact of having a adjacent channel operating in

a wider or narrower spectral separation is different, and

therefore, both carriers should be separated by the most

possible, which is 10 MHz.

Regarding the results obtained for the band of 2500 MHz,

one should bear in mind that for the link losses calculation it was used the COST231 Walfisch-Ikegami propagation model which is only valid until 2000 MHz, and thus, there might be associated to the results a small error percentage, but yet not significant.

V. CONCLUSIONS AND FUTURE WORK

The aim of this paper is to analyze the impact of the adjacent

channel interference in the network capacity and coverage

and, as a result, be able to identify an optimal frequency

deployment that minimizes that type of interference. To

perform that study a static simulator was implemented in

MatLab, and for different scenarios, and different carrier

separations, several simulations were done. From these

simulations, for each combination of a scenario and a carrier

separation, it was obtained data relatively to the network

capacity, interference ratio and intra and inter-cell

interference.

The work in this paper is divide in two different parts: the first

one is the study of dead zones, and how the existence of those

is dependent on the existence of adjacent channel interference;

the second part, is also about the impact of adjacent channel

interference, but now, regarding its effects on the network

capacity. In this last one, the analysis is performed for two

different bands: 2000 MHz and 2500 MHz.

Starting on the dead zones analysis, the downlink was found

out to be the most critical side of a connection for the

existence of dead zones, which means that, before the MT in

UL cause interference in the BS operating in the adjacent

channel, its DL connection will be lost, due to the interference

caused by that BS. Therefore, a more detailed analysis of the

downlink was carried out, being calculated the sizes of dead

zones for a specific configuration, the case where a MT is

connected to a micro BS and gets closer to a macro one. In

this case, there is a loss in the coverage area of around 7%,

which, regarding that it is related to a micro BS, can cause

problems in the network performance, once near those type of

BSs there is a higher concentration of users. However, those

results can be different if one considers a wider separation

between adjacent carriers. For a separation of 10 MHz, which

can correspond to place the carrier in the centre of the

operators’ frequency band, the losses in capacity diminish

significantly. To finish the dead zones study, a more realist

scenario, with several BSs from different operators, was

analysed for 5 MHz. One way of minimizing, or even

eliminate, the dead zones problem is the co-localization of the

BSs.

The next study was the analysis of capacity for different

network configurations, first for the 2000 MHz band and later

for the 2500 MHz band. In the scenario where micro BSs are

introduced in the middle of an already existent macro network,

the effect of the interference that results from adjacent channel

cannot be neglected, when smaller separations between

carriers are considered (there are losses in capacity of almost

10% in the macro network). Therefore, the carrier used for the

micro network should not be placed right aside to the carrier

of the macro network. For the simulations in the 2500 MHz band, the results

obtained, for the impact of adjacent channel interference, are in accordance with the previous ones for 2000 MHz. The differences between both, are mostly in a decreased number of users served, which is due to the higher link losses registered. So the same conclusions as before can be taken: when using only macro or micro BSs alone, the interference problems generated are no very significant, and its impact on the network capacity can be neglected; in networks with both macro and micro BSs, the carriers on which each of the BSs are operating must be separated by 10 MHz.

As future guidelines for a continuous development of the scope of this paper, several suggestions can be made. Regarding the simulator, and its limitations, it could be further developed, in order to include more carriers (3 or 4) and to become a dynamic simulator, to evaluate interference in a temporal basis. It could also be considered the use of real scenarios, based on real maps and BS/MT distribution. One other direction would be the analysis of the adjacent channel interference in the 900 MHz band, where UMTS would be co-operating with GSM 900.

REFERENCES

[1] 3GPP, Technical Specification Group Radio Access Network, Base Station (BS) radio transmission and reception (FDD) (Release 6), Report TS 25.104, V6.17.0, March 2008.

[2] Laiho, J.,Wacker, A.,Novosad, T., Radio Network Planning and Optimisation for UMTS, John Wiley & Sons, Sussex, England, 2002

[3] Chen,Y., Soft Handover Issues In Radio Resource Management for 3G WCDMA Networks, Ph.D. Thesis, Queen Mary College, University of London, London, UK, Sep. 2003.

[4] Holma,H. and Toskala,A., WCDMA for UMTS – Radio Access for Third Generation Mobile Communications, John Wiley & Sons, Sussex, England, 2004.