Smart city is a new paradigm indicating a well performing city in terms of a eficiency and sustainability perceived in diferent sectors (e.g. mobility, environment, health, space living) by citizens. New cellular technologies as Long Term Evolution (LTE) are crucial for this new approach due to possibility to enable pervasive reception of digital services by users. In order to be able to use all LTE innovative features, Mobile Network Operators (MNO) need to also guarantee acceptable QoS perceived by end user. End-to-end approach for QoS is strongly recommended, especially for IP delay sensitive services like VoIP over LTE (VoLTE). This work presents analysis of delay impact on VoLTE end-to-end performances in multi-user and multi-service (VoLTE and HTTP web browsing) environment. Diferent LTE network scenarios are simulated using OPNET modeler 17.5. A final comparison of simulation results is provided in order to evaluate delay impact on VoLTE end-to-end performance.
UTRAN (E-UTRAN) and a Core Network called Evolved
Packet Core (EPC). LTE system also introduces a direct
Today our cities need to be smarter, especially in terms management of QoS policies based on bearers and QoS
of eficiency and sustainability perceived by citizen in Class Identifier (QCI) in order to guarantee acceptable
diferent sectors of city, e.g. mobility, environment, servie reception by end user. QoS policies in LTE are
health, space living [
Among them cellular technologies, especially Long Term Actual scenario of ICT technologies is characterized
Evolution (LTE) which indicates 4th Generation (4G) by a strong convergence of diferent ICT networks
(wirestandard for wireless systems, gives to citizens the op- less, wireline, cable). LTE is part of this important
portunity to make smarter their living conditions due multi-network, multi-client and multi-service [
This is surely possible also thanks to the incredi- are operating.
ble capabilities in terms of computing of modern digi- In order to guarantee acceptable QoS to end user
ustal systems that allow the eficient implementation of ing IP transport protocol and best efort type of service
communication systems [
In the first quarter of 2014 number of mobile broad- grate LTE native QoS features with other enhanced
band subscribers was characterized by a very strong techniques based on a QoS end-to-end approach.
Esgrowth. As mentioned in [
LTE is the first 3GPP cellular standard full IP-based. Since LTE is full IP-based wireless standard it only
enIt is able to ofer to end users a download data rate up ables entire wireless transmission over Packet
Switchto 100 Mbps and an upload data rate up to 50 Mbps [
LTE is also characterized by several innovative fea- ization entities already treated issue of QoS in LTE
ustures. Architecture is more flexible and interoperable. ing end-to-end approach. In [
In real scenarios many network impairments can with higher priority. Strategies of priority service
allooccur (e.g. excessive delay caused by network conges- cating are left to operators [20]. This is also confirmed
tion or faults) and can bring a negative efect for ac- by Medbo et al. in [21]. In case of LTE mixed
trafceptable service transmission/reception [
Network management techniques have also a cru- Since an eficient end-to-end approach to quality of cial role for QoS guaranteeing procedures. Horvath service needs to analyze both quality of content delivin [17] presents a new LTE QoS Signaling (LQSIG) pro- ered (voice quality in case of VoLTE) and network pertocol able to guarantee a resource reservation for data formances, a QoS assessment based on the most impath transmission compliant with LTE QCI target val- portant Key Performance Indicators (KPIs) is needed [22]. ues. S. Shen et al. in [18] propose a new LTE per- In this work following KPIs are considered in case of formance management framework based on CoS/QoS VoLTE [23]: mapping table: main scope is to identify relationship among QoS informations in LTE and operator trans- • Mean Opinion Score (MOS) port network. In particular LTE service QCIs are compared with QoS information in case of IP protocol (DSCP • End-to-end delay value), carrier Ethernet (802.1p value) and MPLS (EXP • Packet loss value). Margoc et al. in [19] analyze QoS in LTE systems that confirms better performances for services • Jitter
MOS is a scalar term included in range 1-5. It indicates quality of a voice, VoIP and VoLTE call. Packet loss gives a percentage indication of number of packets lost during transmission. Jitter is variance of packet inter-arrival time. End-to-end delay can be summarized by following formula:
where 1 = 2 = 3 = 2 −
= 1 + 2 + 3 _ + + _ +
+ + + + (1) Table 2
simulated scenarios configuration. _2 are performing a VoLTE call using a direct link interrupted by IP cloud, _3 is performing HTTP web session.
Table 2 lists the most important features of each simulated scenario.
• LTE_wkstn: LTE workstation or UE. • UE_1: VoLTE source (or caller) • UE_2: VoLTE destination (callee) • UE_3: requesting HTTP web session • lte_enodeb_3sector_slip4_adv_1_upgvrade: LTE e-NodeB with 3 sectors. Two diferent eNodeBs are considered: eNB_1 serving UE_1 and UE_3, eNB_2 serving UE_2 • lte_epc_atm8_ethernet8_slip8_adv: LTE EPC node • Ethernet_server: HTTP server • PPP_DS3: link model for LTE nodes • 100baseT: link model for HTTP web server OPNET modeler management nodes are: • app_config: application configuration node • profile_config: profile configuration node • lte_attr_definer_adv: LTE attribute definer node
For all simulated scenarios entire LTE network is modeled using parameters listed in Table 3.
In this paper voice and HTTP applications are selected among those available in OPNET modeler. New voice application created is named VoLTE. It is launched with a start ofset of 20 seconds till the end of simulation period. As requested by 3GPP LTE standard, the same VoLTE application is carried out over EPS bearer with QCI 1 (GBR) and ARP 1.
Table 4 lists the main characteristics of VoLTE application.
New HTTP application is named HTTP. It is launched with a start ofset of 40 seconds and it is characterized by: • N. 1 web page with dimension: 1000 Bytes (constant distribution) • N. 5 medium images with dimension: uniformly variable from 500 to 2000 bytes • N. 2 short videos with dimension: uniformly variable from 10000 to 350000 bytes
In order to simulate VoLTE and HTTP services, two diferent OPNET profiles are created: VoLTE Profile and HTTP profile. Main settings of profiles are listed in Table 6 and Table 7.
VoLTE Profile uses a unique application, VoLTE application. Since Voice Profile uses also a start ofset of 20 seconds, there are two diferent start ofset of 20 seconds: the first one is related to configuration of VoLTE application, the second one is related to configuration of VoLTE profile.
It means that VoLTE packets are going to be sent after 40 seconds from simulation starting. HTTP profile uses a start ofset of 40 seconds. Since HTTP application has also a start ofset of 40 seconds, IP packets of HTTP session are going to be delivered after 80 seconds after simulation start. Simulation period is 3 minutes for all scenarios.
In this paragraph main simulation results based on KPIs listed in Table 1 are presented. Figure 4-Figure 8 show graphic representation of each scenario in terms of MOS mean value, end-to-end packet delay, VoLTE trafic sent, VoLTE trafic received, HTTP Page response Time.
Table 8 shows comparison of final simulation results for each scenario.
A general comparison among all scenarios underlines better KPIs performance in scenarios 1, 2 (without IP cloud) than ones measured in scenarios 3, 4 (with IP cloud). Simulation results of scenarios 1 and 2 indicate a general behavior of KPIs quite near LTE QoS target values fixed by QCIs. However MOS mean value is far from target value (see table IV) typical of GSM EFR voice codec. Scenarios 3 and 4 are afected by higher value of end-to-end delay and packet loss than previous scenarios. Worst performance of scenario n. 4 is also evidenced. Combination of mixed trafic together with impairments caused by IP Cloud (1% packet discard ratio and 0.1 second delay) determines KPI endto-end values around 1.7 in terms of MOS, around 31% in terms of packet loss ratio and 01 seconds in terms of packet delay. These negative performances justify adoption of strong network management techniques by MNO in order to reach maximum value fixed by LTE QCI (10%) using end-to-end QoS approach.
VoLTE is a crucial service for LTE networks. Purpose of this work is to evaluate end-to-end performance of
VoLTE in a multi-user and multi-service environment. Four diferent scenarios are simulated using OPNET Modeler software tool. Simulation results show a general worsening of all measured KPIs either when HTTP web browsing is added to VoLTE either network impairments due to IP cloud are introduced. Scenario characterized by both of them has the worst performance.
Network impairments due to IP cloud are the heavier factors for a general decrease of VoLTE end-to-end performance. Improvements in LTE network transmission are necessary both in user and control plane in order to improve end-to-service quality perceived by end user and to reach KPI values compliant with requirements fixed by QCIs. Future works are going to investigate network improvements in entire LTE transmission chain and additional techniques able to enhance QoS management (e.g. queue management, user priority).