LTE Network Throughput Estimation

Alexander Babkin, Alexey Pylenok, Alexander Ryzhkov, Andrey Trofimov

The Bonch-Bruevich Saint-Petersburg State University, Saint-Petersburg, Russia {aryjkov@mail.ru}

Abstract. Now LTE is considered to be a prominent radio access standard to meet the needs of the society. LTE networks throughput optimization is one of the main problems under consideration. Two LTE network computer models are worked up to estimate downlink achievable throughput: for macro and femto LTE networks. Considering macro networks four frequency deployment scena-rios are analyzed and their throughputs are compared. In femtocell structure the scenario with two femtocells is under discussion.

Keywords: LTE, eNodeB, frequency deployment, throughput, femtocell

1. Introduction

LTE network allows to construct a flexible service environment due to their two genuine features. The first is an all-IP network. It means that all the network interfac-es are IP-based with the only exception of the radio interface. The second LTE networks are heterogeneous. There is a variety of LTE structures: macro and micro outdoors, pico and femto indoors. Therefore it is required to find different approaches when estimating LTE networks outdoors and indoors effectiveness.

Real throughput values may be obtained after long duration traffic statistical analy-sis. Now, at the beginning of LTE networks deployment we need to have the tools to compare various structures efficiency. With this purpose two LTE network computer models are presented in this report. The models don’t imitate Base Station Node Scheduler in details but come along with its main function: to choose the optimal transmission format in accordance with signal to interference ratio at the receiving point. So the models proposed are to draw signal to interference patterns around Evolved Base Station Nodes (eNodeB) at the first stage of the computer simulation. The next stage of our research is to estimate eNodeB throughput on these patterns basis.

The organization of the paper is as follows. In the first part we compare the efficiency of the different frequency resources al-

location strategies in outdoors network. The main objective is to estimate comparative downlink eNodeB throughput for a number of radio band fraction scenarios. Now there is no common point of view which scenario to held on and the numerical esti-mation will be of great help in a sense. We shall calculate downlink throughput only because it is downlink traffic mainly that comes in collision with channel resources limits.

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In the second part of the paper the structure of two femtocells is being analyzed. LTE femto networks are cost that come to the receiving points in femtocells that allows to use the most effective modulation methods, MIMO space muDownlink throughput in a sole femcussed below.

2. LTE M

When planning LTE networksources in the adjacent is one of the main objectives because higher SINR makes it possible to use more effcient modulation and coding scheme.

The new MATLAB SINR calculation model throughput estimation. Known as ECCsion up to 3.5 GHz was used for pass loss calculations [1]. The new SINR model comprises antenna pattern as well. As a result a number of SINR patterns for different frequency deployment scenarios were obtained. There are 4 scenarioation (Fig.1).

1. Three eNodeB make a cluster; each eNodeB uti2. Fractional frequency reuse: the radio band is divided into 3 parts and each part is

allocated to a certain sector of each eNodeB.3. Every eNodeB utilizes the w4. Soft fractional frequency reuse:

frequency band may be utilized in the interior zone of the eNodeB. In Fig.1 the sectors with the same frequency band

A standard antenna pattern The computer simulation brought a set of the typical trefoil form signal loss pa

terns and SINR patterns for various frequency deployment scenarios (Fig.3).

In the second part of the paper the structure of two femtocells is being analyzed. LTE femto networks are cost effective and easy to develop. There are strong signals that come to the receiving points in femtocells that allows to use the most effective modulation methods, MIMO space multiplexing that results in data rate increasDownlink throughput in a sole femtocell and in two eNodeB femto network is di

Macro Network NodeB Throughput

LTE network, the principle problem is how to allocate channel radjacent eNodeB. The signal to interference ratio (SINR) improvement

is one of the main objectives because higher SINR makes it possible to use more effcient modulation and coding scheme.

The new MATLAB SINR calculation model was worked up for eNodeB throughput estimation. Known as ECC-33 Hata-Okumura propagation model extesion up to 3.5 GHz was used for pass loss calculations [1]. The new SINR model comprises antenna pattern as well. As a result a number of SINR patterns for different frequency deployment scenarios were obtained. There are 4 scenarios under

Three eNodeB make a cluster; each eNodeB utilizes 1/3 of the frequency band.Fractional frequency reuse: the radio band is divided into 3 parts and each part is

allocated to a certain sector of each eNodeB. deB utilizes the whole frequency band.

4. Soft fractional frequency reuse: it differs from scenario 2. In this case frequency band may be utilized in the interior zone of the eNodeB.

1 the sectors with the same frequency band are of the same colour.

Fig.1. Frequency Deployment Scenarios

A standard antenna pattern is used in the SINR model is shown in Fig.2. The computer simulation brought a set of the typical trefoil form signal loss pa

patterns for various frequency deployment scenarios (Fig.3).

In the second part of the paper the structure of two femtocells is being analyzed. effective and easy to develop. There are strong signals

that come to the receiving points in femtocells that allows to use the most effective data rate increase.

in two eNodeB femto network is dis-

principle problem is how to allocate channel re-improvement

is one of the main objectives because higher SINR makes it possible to use more effi-

downlink propagation model exten-

sion up to 3.5 GHz was used for pass loss calculations [1]. The new SINR model comprises antenna pattern as well. As a result a number of SINR patterns for different

under consider-

lizes 1/3 of the frequency band. Fractional frequency reuse: the radio band is divided into 3 parts and each part is

In this case the whole

ame colour. .

The computer simulation brought a set of the typical trefoil form signal loss pat-patterns for various frequency deployment scenarios (Fig.3).

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Fig.2. Antenna Pattern (k80010691, Kathrein)

Fig.3. eNodeB Signal Loss Pattern (dB)

As a result, the cell area around the eNodeB is divided into a number of zones with

different SINR inside. The next step was to match a certain SINR with a correspond-ing CQI (Channel Quality Indicator). CQI is a specified parameter but it is a vendor problem to establish the correlation between CQI and SINR. Considering some ven-dor materials we used for the computer simulation the approximation curve CQI as the function of SINR at a user receiver input that is shown in Fig.4.

Fig.4. CQI as a function of SINR

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Each CQI determines the most efficient downlink transmission format that can be assigned. In Table 1 the correlation between CQI, modulation type, code rate and the expected maximum downlink data rate is presented for LTE FDD network with the 2×10 MHz bandwidth.

Table 1. CQI and Modulation&Coding Schemes

CQI Modulation Code Rate Bit Rate, Mbit/s

1 QPSK 0.08 0.95

2 QPSK 0.12 1.46

3 QPSK 0.19 2.35

4 QPSK 0.30 3.75

5 QPSK 0.44 5.47

6 QPSK 0.59 7.34

7 16-QAM 0.37 9.21

8 16-QAM 0.48 11.94

9 16-QAM 0.60 15.02

10 64-QAM 0.46 17.04

11 64-QAM 0.55 20.73

12 64-QAM 0.65 24.35

13 64-QAM 0.75 28.23

14 64-QAM 0.85 31.92

15 64-QAM 0.93 34.66

The average eNodeB downlink throughput is calculated at the assumption that the

user density is constant inside the sell. In this case the zone partial throughput with a fixed CQI is proportional to the zone area. Area histograms for each frequency dep-loyment scenario in Fig.1 (percents of the cell area for various CQI) are presented in Fig.5.

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Fig.5. CQI Area Distribution in a Cell The histograms in Fig.5 and the bit rate values in Table 1 make it possible to esti-

mate the average eNodeB downlink throughput and to compare the different scenarios for frequency resource allocation. The results are presented in Table 2.

Table 2. Average eNodeB Downlink Throughput

Frequency deployment scenario Downlink Throughput, Mbit/s

1 4.4

2 12.6

3 5.5

4 11.9

As it follows from Table 2, scenarios 2 and 4 bring almost the same downlink

throughput. However scenario 4 is more preferable, as it can provide more opportuni-ties for subtle subband allocation in the sectors of a cell in depend of the sector loads. There is dynamic frequency resource control in LTE networks and the soft fractional frequency reuse is optimal for eNodeB load balancing purposes.

3. Femtocell LTE Network Throughput Estimation Femtocell is a small cell with a low power eNodeB (transmitter power less than 13

dBm), so femto base station is called Home eNodeB (HeNB). First and foremost LOS signals are to be received in a femtocell that provides high SINR at the receiver point.

It is proposed that TDD would be on usage in femtocell networks. LTE specifica-tions support 7 different frame configurations for TDD transmission. In the example presented below configuration 1 is applied, where downlink/uplink transmission time ratio is 3:2 [2], [3].

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The special MATLAB femtocell model was worked up for signal strength and SINR calculation indoors. The model calculates the total signal generated by the nu-merous rays (1000) from HeNB taking into account the losses when rays reflecting and passing through walls. It comprises COST231 Indoor multiwall model for signal losses estimation as well [4].

We introduce femtocell structure on the office building floor (Fig.6). The floor size is 8m wide and 24m long. All the rooms are of the same size separated by thin walls. The HeNB maximum output power is 13 dBm and it uses a stub antenna. We didn’t take into account other floor femtocell interferences due to significant signal inter-floor losses.

Fig.6. Plan of the Floor Within the limits of the paper 4 femtocell network scenarios were considered: 1 – HeNB 1 in the room 1, 2 – HeNB 1 in the room1and HeNB 2 in the room 4, 3 – HeNB 1 in the room1and HeNB 2 in the room 3, 4 – HeNB 1 in the room1and HeNB 2 in the room 2. As the result of the computer simulation the field, SINR and CQI patterns were ob-

tained. In the case of the CQI patterns the curve in Fig.4 was used. For obtaining downlink bit rate in TDD LTE networks the table analogous with Table 1 for band-width 10 MHz was calculated.

CQI pattern on the floor for scenario 1 is shown in Fig.7 and the corresponding bit rate histogram in Fig.8. CQI scale is indicated on the right side of Fig.7 (Fig. 9, 11 below). The deep black means the lack of communications. In Fig.7, 9, 11 on the horizontal and vertical axes are distances (m) in accordance with the plan of the floor (Fig.6).

In Fig.8, 10, 12 on the horizontal axis is the maximum bit rate (Mbit/s) and on the vertical axis is the percentage of the floor area where this bit rate can be achieved. In addition thick horizontal lines in Fig.8, 10, 12 mark the average throughput AT (Mbit/s) of the HeNB.

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In scenario 2, when two

both HeNB are quite the same as in (Fig.9, Fig.10) and 4 (Fig.1

Fig.7. CQI Pattern – Scenario 1

Fig.8. Bit Rate Distribution – Scenario 1

In scenario 2, when two femtocells are set with maximum diversity the patterns for both HeNB are quite the same as in scenario 1. They start to change in scenar

and 4 (Fig.11, Fig.12).

femtocells are set with maximum diversity the patterns for start to change in scenarios 3

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Fig.9. CQI Patterns – Scenario 3

Fig.10. Bit Rate Distribution – Scenario 3

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Fig.11. CQI Patterns – Scenario 4

Fig.12. Bit Rate Distribution – Scenario 4

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The computer simulation results are presented in Table 3, that contains the distance between two HeNB, downlink throughput in each femtocell and the total network throughput. Thus this model gives the opportunities for various femtocell structures analysis and effectiveness estimation.

Table 3. Femtocells downlink throughput

Scenario 1 2 3 4

Distance between HeNB, m 21 13 6

HeNB 1 average throughput, Mbit/s 15.1 14.2 11 10

HeNB 2 average throughput, Mbit/s 14.1 12.3 9.9

Network average throughput, Mbit/s 15.1 28.3 23.3 19.9

Discussed in the report eNodeB throughput calculation models and the calculation results will be used in LTE network planning and optimization.

4. References

1. Comparative Study of Path Loss Models in Different Environments/Manju Kumari, Ti-lotma Yadav, Pooja Yadav, Purnima K Sharma, Dinesh Sharma// International Journal of Engineering Science and Technology 2011. Vol.3, №14. Р. 2945–2949.

2. 4G LTE/LTE Advanced for Mobile Broadcast/ Eric Dohlman, Stefan Parkvall, Johan Sköld – Elsevier Ltd, 2011, ISBN 978-0-12-385489-6 – 431p.

3. 3GPP TS 36.211; Physical Channels and Modulation. 4. 3GPP TR 101 112; Selection procedures for the choice of radio transmission technolo-

gies of the UMTS.

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