The Impact of Carrier Frequency at 800 MHz and3.5 GHz in Urban and Rural Environments Using

Large Antenna ArraysBlanca Ramos Elbal†, Fjolla Ademaj†, Stefan Schwarz† and Markus Rupp

† Christian Doppler Laboratory for Dependable Wireless Connectivity for the Society in MotionTU Wien, Institute of Telecommunications

Gusshausstrasse 25/389, A-1040 Vienna, AustriaEmail: {brelbal, fademaj, sschwarz, mrupp}@nt.tuwien.ac.at

Abstract—The widespread use of wireless mobile communica-tions in past years has resulted in a mass use of the 2GHz band.As a consequence, the 3.5GHz and 800MHz bands have emergedas an excellent alternative for mobile operators. In this paper,we investigate such alternatives using the 3GPP 3-dimensional(3D) channel model. We show the impact of both 800MHz and3.5GHz carrier frequencies not only in an urban but also in arural environment. We consider indoor and outdoor users, aswell as LOS and NLOS users. We evaluate and compare theperformance of each scenario in terms of SINR, throughput,RSRP, RSSI and RSRQ.

Index Terms—3GPP 3D channel model, system level simula-tion, rural environment, urban environment, antenna array.

I. INTRODUCTION

Spectrum scarcity in the 2GHz band has led to the emer-gence of new bands as a potential alternative for the future5th generation of mobile communications. Among such alter-natives, mmWave wireless systems have erupted on the scenewith considerable force and are foreseeably a key aspect ofdata rate enhancement. [1]. One of its main benefits is theunderutilization of the spectrum in the [6 − 100]GHz range.Further positive aspects concomitant with high frequencies area higher spatial resolution achieved by packing hundreds ofantenna elements into an antenna array. But there are alsosome important drawbacks associated to this frequency rangesuch as the high sensitivity to shadowing and blockage effects,large attenuation in long distances and high penetration losses.Furthermore, some challenges remain still open [2, 3].

Moreover a good candidate to complement the congested2GHz band is the 3.5GHz band, commonly known asCitizens Broadband Radio Service. Already simulations andmeasurements have been carried out in this band [4, 5].However, a new carrier frequency would force operators toreplace or duplicate the actual antennas at the base stations(BSs). Dealing with that issue, the authors in [6] study theimpact of re-using the antennas matched to 2GHz to conveyat 3.5GHz. In [7], the authors develop a dual band printeddipole antenna to transmit at both 3.5GHz and 2GHz.

Another possibility that offers more coverage but less ca-pacity is the 800MHz band. It is also used for short-rangeapplications, including Radio Frequency IDentification [8] or

wereables devices [9], as well as for long-range applications,such the television broadcasting [10]. In LTE it was usuallyemployed to cover rural areas. Nevertheless, this carrier fre-quency has started to be used also for urban environments.

In this paper we compare the performance in terms ofmacroscopic Signal-to-Interference-plus-Noise Ratio (SINR),Reference Signal Received Power (RSRP), Received SignalStrength Indicator (RSSI), Reference Signal Received Quality(RSRQ) and average user throughput by means of system levelsimulations. We consider both Rural Macro cell (RMa) andUrban Macro cell (UMa) cells at both 3.5GHz and 800MHz,for outdoor as well as for indoors users.

II. SYSTEM MODEL

Our scenario comprises a three-sectorized BS surroundedby six interfering three-sectorized BSs as depicted in Figure 1.We consider a dense scenario with users deployed accordingto a uniform distribution.

LOS/NLOS

NLOS

NLOS

NLOSNLOS

NLOS

NLOS

NLOS

NLOS

NLOS

NLOS

NLOS

NLOSNLOS

NLOS

NLOS

NLOS

NLOS

NLOSNLOS

NLOS

Fig. 1: System model comprising the observed sector and sixinterfering three-sectorized BSs. We consider that the users from ourcell are always NLOS regarding to the interferings BSs.

For each user position, the macroscopic SINR, throughput,RSRP, RSSI and RSRQ are computed. The RSRP expressionthat we use follows the definition for the RSRPp given by (1),where p represents the antenna port at the transmitter. For eachport, the expression contains a component for line-of-sight(LOS) and non line-of-sight (NLOS) propagation conditions,

α0,u,p and αn,m,u,p respectively. In the 3rd Generation Part-nership Project (3GPP) 3-dimensional (3D) channel model,N clusters act as scattering objects and M rays depart fromeach cluster. Therefore, the component in LOS depends onthe antenna port at the transmitter p and the antenna elementat the receiver u, and the component in NLOS depends alsoon the cluster n and the ray m. Additionally, the RSRPpexpression includes the pathloss PL and the shadow fadingSF at the user position. The expression of α0,u,p and αn,m,u,pare specified in [11] and it takes into account variables such asthe cross polarization power ratios for each ray of each cluster,the cluster power or the receive and transmit antenna elementfield patterns.

RSRPp = PL · SFU∑

u=1

(| α0,u,p |2 +

N∑n=1

M∑m=1

| αn,m,u,p |2)TXpower

U(1)

After computing the RSRPp values, the computation of theRSRP given by [12] follows (2). Furthermore, the RSSI isdefined as the total received power from both attached BS andinterferers I and the noise Z, as expressed in the equation (3).The RSRQ expression is given by (4), where NNrb

is the totalnumber of resource blocks and scales up the RSRQ value tothe entire bandwidth.

RSRP = max{RSRP1, RSRP2, ....RSRPNTX} (2)

RSSI = RSRP +

I∑i

RSRP i + Z (3)

RSRQ = NrbRSRP

RSSI(4)

In our scenario, each sector is endowed with a 2D antennaarray as illustrated in Figure 2, where A equidistantly spacedantenna elements are mapped to port p. The total number ofantenna ports is given by NTX . Therefore, NTX different val-ues of RSRPp are computed and following (2) the maximumvalue is chosen to be the RSRP.

From the two polarization modes defined in [11], we con-sider cross-polarized antennas. In this mode the first columnof antenna elements is mapped to the first port with a slantangle of +45◦, the second column of antenna elements ismapped to the second port with a slant angle of −45◦, andso forth. We consider that the BS is neither electrically normechanically tilted and consequently the BS beam pointstowards the horizon and no beamforming is performed. On theother hand, at the user side we consider two cross-polarizeddipoles.

III. SIMULATIONS

This section presents simulation results obtained with theVienna LTE-Advanced (LTE-A) system level simulator [13–15]. In each realization, the macroscopic SINR is computedfor each user as well as the throughput and RSRP values.

...

ω1(θ

s)

ω2(θ

s)

ωM(θ

s)

m=

{1, 2

, ...,

10

}

p={1, 2, 3 ,4}

...

λ/2

Fig. 2: Antenna array structure at BS consisting of NTX antennaports and A antenna elements in elevation mapped to a single antennaport.

The RSSI and RSRQ parameters are computed according to(3) and (4). We consider a dense scenario with 50 users percell in order to observe the average performance of the entirecell. We evaluate both RMa and UMa scenarios at 3.5GHzand 800MHz. The scenario parameters for each environmentare specified in Table I. The inter site distance (ISI) and BSheight are larger for the RMa environment, while the averagebuilding height h is smaller. The channel parameters employedare frequency dependent and are specified in [16, Table 7.5-6].

TABLE I: Reference scenario parameters

3D-UMa 3D-RMaFrequency {800MHz, 3.5GHz}

ISD 500m 2000mdcell 333m 1333mhBS 25m 35 m

h 20m 5 m

We perform 300 simulation realizations with the parameterssummarized in Table II. We do not include any feedback delay.

First, we consider our attached BS and interfering links to bein NLOS. Figure 3 shows the empirical cumulative distribution

TABLE II: Simulation parameters

Parameter ValueCarrier frequency 3.5GHz, 800MHz

LTE bandwidth 10MHzBS transmit power 46 dBm

NTx ×NRx 4× 2BS antenna polarization XPOL

User antenna gain pattern omni-directionalAntenna element gain 8 dBi

Receiver type zero forcingNoise power density −174 dBm/Hz

Noise Figure 9 dBLTE transmission mode 4

Number users per cell 50User speed 5 km/h

Scheduler Round robinSimulation length 10 TTI

Number of realizations 450

function (ECDF) of the macroscopic SINR evaluated in alluser positions considering indoor as well as outdoor users,and Figure 4 illustrates the RSRP of the attached BS as wellas the RSRP obtained from the interferers. The plotted resultsin Figure 4a for outdoor users shows that the signal comingfrom our attached BS is stronger at 800MHz in both RMa andUMa environments. However, the results in Figure 3 show aswell a minor difference in the SINR. This is due to the factthat the interference is also higher at 800MHz, as depictedin Figure 4b. Regarding indoor users, the worst performanceis obtained for the users in a RMa environment at 3.5GHz.This is caused by the higher attenuation at 3.5GHz, and alsobecause in a RMa cell the average building height is smallerthan in a UMa environment. Therefore, the maximum 3Ddistance from the BS to the user location is in average higherin a RMa scenario.

Figure 5 provides performance results in terms of RSSIand RSRQ and Figure 6 shows the ECDF of the averagethroughput. Though the results in macroscopic SINR do notshow huge differences between scenarios as we explainedabove, to compute the throughput the channel is taken intoaccount. Hence, there are differences in average throughput foroutdoor users though there are not in the SINR. As the SINR,the RSRQ take into account both desired and interfering linksand as a consequence no difference are appreciated betweenscenarios. The highest throughput is achieved with the RMaenvironment.

We perform further simulations considering the desired linkin LOS for all users in the cell, and all interfering links inNLOS as depicted in Figure 1. Figure 8 shows the SINRfor both indoor and outdoor users. In this case we can seedifferences in macroscopic SINR for the UMa cell. Thatis due to the pathloss model employed [16]. In LOS thepathloss model for a UMa environment is a two slope modelwhich results into a slightly higher value at 3.5GHz, butthe difference with the value at 800MHz is not very large.However, in NLOS the pathloss obtained at 3.5GHz is quitelarge in comparison to the value at 800MHz. In this way, thesignal coming from the attached BS and the interferers is notproportional as in Figure 3, causing the differences in SINR.Though the best RSRP is the one obtained for outdoor usersin a UMa environment at 800MHz as Figure 8a illustrates,Figure 8b shows that the interference is also large, resultingthe best SINR for users at 3.5GHz.

Figure 9 illustrates the ECDF of the RSSI and RSRQ.In this scenario, the largest total received power is achievedin a UMa environment at 800MHz since the contributionof both attached BS and interferers is the largest one, asshown in Figure 8. Figure 10 shows the average throughputwhen we consider our attached BS to be in LOS and theinterfering BSs in NLOS. In a UMa environment the SINRis very high, and consequently the Channel Quality Indicator(CQI) achieved is the best. Since we consider a Round Robinscheduler, the resources are equally assigned to all users, andpractically all users achieve the maximum throughput, which

-60 -40 -20 0 20 40 60

UE SINR (dB)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

Fig. 3: ECDF of the SINR (dB) at each user position in a UMaand RMa cell at 3.5GHz and 800MHz when the desired link inin NLOS. Outdoor users results are plotted in solid line, while thedashed lines are related to indoor users.

-140 -120 -100 -80 -60 -40 -20

RSRP (dBm)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

(a)

-200 -180 -160 -140 -120 -100 -80 -60 -40 -20 0

RSRPinterferers

(dBm)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

(b)

Fig. 4: ECDF of the RSRP (dBm) of the desired link (a) andinterfering links (b) in a UMa and RMa cell at 3.5GHz and 800MHzfor both indoor and outdoor users when the attached BS is consideredto be in NLOS.

-100 -90 -80 -70 -60 -50 -40 -30 -20 -10 0

RSSI (dBm)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

(a)

-70 -60 -50 -40 -30 -20 -10

RSRQ(dB)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

(b)

Fig. 5: ECDF of the RSSI (dBm) (a) and RSRQ (dB) (b) in a UMaand RMa cell at 3.5GHz and 800MHz for both indoor and outdoorusers when the attached BS is considered to be in NLOS.

0 0.2 0.4 0.6 0.8 1 1.2 1.4

avg. UE throughput (Mbps)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

Fig. 6: ECDF of the throughput (Mbit/s) of each user in a UMaand RMa cell at 3.5GHz and 800MHz when the desired link is inNLOS for both indoor and outdoor users.

-60 -40 -20 0 20 40 60 80 100 120

UE SINR (dB)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

Fig. 7: ECDF of the SINR (dB) at each user position in a UMa andRMa cell at 3.5GHz and 800MHz when the desired link is in LOS.Outdoor users results are plotted in solid line, while the dashed linesare related to indoor users.

-140 -120 -100 -80 -60 -40 -20 0 20 40

RSRP (dBm)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

(a)

-200 -180 -160 -140 -120 -100 -80 -60 -40 -20 0

RSRPinterferers

(dBm)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

(b)

Fig. 8: ECDF of the RSRP (dBm) of the desired link (a) andinterfering links (b) in a UMa and RMa cell at 3.5GHz and 800MHzfor both indoor and outdoor users when the attached BS is consideredto be in LOS.

-100 -80 -60 -40 -20 0 20 40

RSSI (dBm)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

(a)

-90 -80 -70 -60 -50 -40 -30 -20 -10

RSRQ(dB)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

(b)

Fig. 9: ECDF of the RSSI (dBm) (a) and RSRQ (dB) (b) in a UMaand RMa cell at 3.5GHz and 800MHz for both indoor and outdoorusers when the attached BS is in LOS.

0 0.2 0.4 0.6 0.8 1 1.2 1.4

avg. UE throughput (Mbit/s)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

UMa-3.5 GHz

UMa-800 MHz

RMa-3.5 GHz

RMa-800 MHz

outdoor user

indoor user

Fig. 10: ECDF of the throughput (Mbit/s) of each user in a UMaand RMa cell at 3.5GHz and 800MHz when the desired link is inLOS for both indoor and outdoor users.

with the parameters selected for the simulation is 1.4 Mbit/s.Due to the lower SINR of the outdoor users in the RMaenvironment indoor users shown in Figure 7, not all usersreach the maximum throughput.

IV. CONCLUSION

In this paper we investigate the macroscopic SINR, RSRP,RSSI, RSRQ and throughput performance at 3.5GHz and800MHz for outdoors and indoors users. We evaluate a BSsector surrounded by six three-sectorized BSs in a hexago-nal grid, in a UMa and RMa environments. We simulate adense scenario to observe the entire cell performance. First,we consider the desired as well as the interfering links tobe in NLOS, and we observe that the best performance isachieved for outdoor users in a RMa environment at 800MHz.Furthermore, we isolate the interference by considering theinterfering links to be in NLOS but assuming that the desiredlink is in LOS. In this scenario the highest performance isobtained for outdoor users in a UMa environment. In terms ofSINR, the users at 3.5GHz outperforms the users at 800MHz,however in terms of throughput in a UMa cell there areno differences since at both carrier frequencies the highestthroughput is achieved.

ACKNOWLEDGEMENTS

The financial support by the Austrian Federal Ministry forDigital and Economic Affairs and the National Foundation forResearch, Technology and Development is gratefully acknowl-edged.

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