Mobility and Interference analysis of Downlink Long Term Evolution using System Level Simulation

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1 Proceedings of International Conference on Emerging Trends in Electronics & Telecommunications (ICETET) 13th - 14th December -214 Karimnagar, Telangana, India (DSEC32) ISSN (online): ISSN (print): Mobility and Interference analysis of Downlink Long Term Evolution using System Level Simulation 1 Dakuri Chiranjeevi, 2 Mahendar Vengala and 3 Gitty Ramesh Depart of Electronics and Communication, Trinity College of Technology, Karimnagar, Telangana, India chiru.dakuri@gmail.com ABSTRACT LTE (Long Term Evolution) or the E-UTRAN (Evolved Universal Terrestrial Access Network), introduced in 3GPP R8, is the access part of the Evolved Packet System (EPS). The main requirements for the new access network are high spectral efficiency, high peak data rates, short round trip time as well as flexibility in frequency and bandwidth. Performance of LTE depends on several parameters. This paper analyzes the impact of mobility and interference of users on the down link Long Term Evolution using System Level Simulator from [1]. The results obtained concern the sector throughput, BLER (Block Error Rate), the user throughput and the corresponding CQI (Channel Quality Indicator) during all simulation period. The scenarios used considered SISO antenna configuration, Round Robin packet scheduling algorithm and different number of users in the cell. Due to mobility and interference considerable user and sector throughput is observed. Keywords: Block error rate, channel quality indicator, long term evaluation, single input single output. I. INTRODUCTION The Third Generation Partnership Project (3GPP) has standardized Long Term Evolution (LTE) in Release- 8 to build the framework for 3G evolution towards 4G. The motivation for 3G evolution came from the growing demand for network services such as VoIP, web browsing, video telephony, and video streaming, with constraints on delays and bandwidth requirements. LTE aims to support all the applications with better performance at reduced cost, besides maintaining seamless mobility [3]. LTE is an all-ip packet based system with design targets of Supporting high peak data rates of 1Mb/s in the downlink (DL) and 5 Mb/s in the uplink (UL), low latency (1ms round-trip delay), improved system capacity and coverage [3] [4]. To achieve the performance objectives, LTE employs the several enabling technologies which include Orthogonal Frequency Division Multiple Access (OFDMA), Single Carrier Frequency Division Multiple Access (SC-FDMA) [1] and Multiple Input Multiple Output (MIMO). LTE technology uses air interface based on OFDMA for downlink and SC- FDMA for uplink. The LTE operates in both Time Division Duplexing (TDD) and Frequency Division Duplexing (FDD) modes and can be deployed in a range of channel bandwidths up to 2MHz. II. LTE DOWNLINK OVERVIEW The LTE down link is mainly characterized by OFDMA as multiple access scheme and MIMO (Multiple Input Multiple Output) technology. The benefit of deploying OFDMA technology on down link LTE is the ability of allocating capacity on both time and frequency, allowing multiple users to be scheduled at a time. The minimum resource that can be assigned to a user consists of two Physical Resource Blocks (PRBs) and it is known as chunk or ICETET 214 DSEC32 P a g e 22

2 Proceedings of International Conference on Emerging Trends in Electronics & Telecommunications (ICETET-14) simply Resource Block (RB). In downlink LTE one PRB is mapped on 12 subcarriers (18 khz) and 7 OFDM symbols (.5 ms) and this is true for non- MBSFN (Multimedia Broadcast multicast service Single Frequency Network) LTE systems and for normal CP (Cyclic Prefix). Scheduling decisions can be made each TTI (Time Transmission Interval) that in LTE is equal to 1 ms [6]. System performance and individual end user experience depend on the propagation conditions, the mobile device feedback, which is based on measurements, and the scheduling algorithm in the enodeb (Evolved NodeB). Packet Scheduling is one of LTE RRM (Radio Resource Management) functions, three packet scheduling algorithms are used: Round Robin (RR), Proportional Fair (PF) and Best CQI Round Robin (RR):The scheduler assigns resources cyclically to the users without taking channel conditions into account. This is a simple procedure giving the best fairness. But it would offer poor performance in terms of cell throughput. The best CQI scheduler tries to maximize total throughput and completely ignores fairness by just as signing resources to the users with the best channel conditions. The PF strategy is an intermediate strategy, fairer than the Best CQI strategy, but with higher global performances than the RR scheduling. Simulators overview is presented in section II. System Level Simulation of Different scenarios are presented in the section III and Link Level Simulations are discussed in the section IV. Section V concludes the paper. III LTE SIMULATOR OVERVIEW System level simulation focus more on networkrelated issues, such as resource allocation and scheduling [2], multi-user handling, mobility management, admission control, interference management, and network planning optimization [2]. Schematic block diagram of the LTE system level simulator is depicted in Fig.1 [2]. The simulator consists of two parts: (i) a link measurement model, and (ii) a link performance model. The link measurement model reflects the link quality, given by the UE measurement reports, and is required to carry out link adaptation and resource allocation. The chosen link quality measure is evaluated per subcarrier [5]. Based on the Signal to Interference and Noise Ratio (SINR), the UE computes the feedback (PMI, RI, and CQI), which is employed for link adaptation at the enodeb. The scheduling algorithm assigns resources to users to optimize the performance of the system. Based on the link measurement model, the link performance model predicts the BLER of the link based on the receiver SINR and the transmission parameters (e.g., modulation and coding)[5]. Fig. 2 shows LTE BLER for CQIs 1 to 15 based on the receiver SINR. Fig. 1 Schematic block diagram of the LTE system level simulator. TABLE I: Simulation parameters Parametrs Assumptions Carrier Frequency 2.1GHz Transmisssion 5MHz Bandwidthh Thermal Noise Density Inter-site distance Receiver noise figure Simulation length UE speeds of interest UEs position BS antenna gain Scheduler Minimum coupling loss Tx mode 1 ntx x nrx antennas 1x1 enodeb Tx power 43dBm -174 dbm/ Hz 5m 9 db 5 TTI 5km/hr UEs located in target sector Only, 2 UEs/sector 15 dbi RR scheduler 7 db ICETET 214 DSEC32 P a g e 23

3 y pos [m] BLER y pos [m] Proceedings of International Conference on Emerging Trends in Electronics & Telecommunications (ICETET-14) SINR Algorithm Averaging EESM, Uplink delay 3 Macroscopic path loss log1(R) LTE BLER for CQIs 1 to SNR [db] CQI 1 CQI 2 CQI 3 CQI 4 CQI 5 CQI 6 CQI 7 CQI 8 CQI 9 CQI 1 CQI 11 CQI 12 CQI 13 CQI 14 CQI 15 Fig. 2. LTE BLER for CQIs 1 to 15. IV. SIMULATION SCENARIOS AND RESULTS For the first scenario simulated it was selected 2.1GHz as carrier frequency, 5 MHz system bandwidth, SISO antenna technology, RR scheduler, 1 UE per enodeb sector, meaning 7 UEs, UEs speed 5 km/h, Typical Urban as channel model, inter enodeb distance 5 m. The UEs are randomly positioned in the cells. The sector throughput and BLER for each enodeb are shown in Fig. 3. The throughput values vary from.1 Mbps to 18.5 Mbps due to the user position in the sector, the interference experimented from other users etc. The second scenario was built in order to see the user speed influence on the throughput. Two things change from the previous scenario: UE speed (1 km/h). The sector throughput for this second scenario is illustrated in Fig. 4. Comparing Fig. 4 with Fig. 3 Moreover, the network BLER increases when the user speed is higher. 6 4 Network BLER and throughput using 5 MHz bandwidth, 24. Mbps maximum S1,.1, 1.52 Mbps S2,.3, 9.62 Mbps S3,.6, 3.2 Mbps S1,.1, 8.93 Mbps S2,.2, Mbps S3,.8, 4.54 Mbps S1,., 15.5 Mbps S2,.1, 14.4 Mbps S3,., 18.5 Mbps S1,.1, Mbps S2,.2, Mbps S3,.9, 3.19 Mbps S1,.2, 16.4 Mbps S2,.2, 7.89 Mbps S3,.97,.1 Mbps S1,.3, Mbps S2,.3, Mbps S3,.1, 14.7 Mbps S1,.1, 3.1 Mbps S2,.3,.84 Mbps S3,.1, 1.9 Mbps Fig. 3. Network BLER and throughput using 5 MHz transmission bandwidth and UEs speed 5 km/h. 6 4 Network BLER and throughput using 5 MHz bandwidth, 24. Mbps maximum S1,.75, 4.65 Mbps S2,.2, 1.42 Mbps S3, NaN,. Mbps S1,.5, Mbps S2,.5, 7.73 Mbps S3,.5, 18.7 Mbps S1,.4, 1.56 Mbps S2,.8, 4.34 Mbps S3,.7,.66 Mbps S1,.2, 7.31 Mbps S2,.2, 13.1 Mbps S3,.4, Mbps S1,.2, 6.11 Mbps S2,.2, 1.59 Mbps S3,.1, 3.33 Mbps S1,.2, 5.54 Mbps S2,.2, 1.25 Mbps S3,.6, 1.33 Mbps S1,.2, Mbps S2,.4, 1.26 Mbps S3,.2, 13.8 Mbps Fig. 4. Network BLER and throughput using 5 MHz transmission bandwidth and UEs speed 1 km/h. Fig. 5 represents the throughput and BLER report for UE 67 (the one from, sector 2). There are two curves for BLER. The green line represents the BLER as measured by the ACK/NACK ratio and the black line the values applied by the link quality model [1] and the CQI s values for UE 67. The blue line is the sent CQI report for the selected RB, the mean CQI for the whole frequency bandwidth is red and the CQI of the Transport Block sent to the UE is marked with black [1]. ICETET 214 DSEC32 P a g e 24

4 y pos [m] Proceedings of International Conference on Emerging Trends in Electronics & Telecommunications (ICETET-14) Fig. 5. Throughput and BLER, CQI report for UE 67 using 5MHz and RR scheduler with 1 users per enodeb. A third scenario was simulated to analyze the influence of interference as the number of users increases in the system and a considerable decrease in the throughput is observed for network as well as for all the users in the network and shown in Fig 6 and Fig. 7. Fig 8 shows Network BLER and throughput using 5 MHz transmission bandwidth and 3 UEs per enodeb and keeping all the parameters from scenario 1. The maximum sector throughput obtained in Fig. 6 is approximately quarter of the highest throughput value illustrated in Fig. 4. And user 1 throughput and BLER, CQI report is depicted in Fig 7. V. CONCLUSIONS This paper evaluates the mobility and interference of downlink LTE using System Level Simulator. First, it was analyzed the impact of the users speed, for that several simulations has been done with different user speeds and is presented in Fig. 3 and Fig. 4 with 5km/h and 1km/h, on comparing both figures, it is observed there was a strong decrease in user and sector throughput because the feedback cannot follow the fast fading. Second, it was analyzed the impact of interference on the users throughput and the network throughput when users are increased from 1 users per enodeb to 3 users per enodeb with Round Robin scheduling, and it is presented in Fig.3 and Fig. 6, considerable decrease in throughput to both users and network is observed because of multi cell interference. Individual user throughput is shown in Fig. 5 and Fig.7. LTE performance depends on lots of parameters and configuration chosen, but through these simulations, several LTE expectations have been achieved. Network BLER and throughput using 5 MHz bandwidth, 24. Mbps maximum 6 4 S1,.4, 1.15 Mbps S2,.5, 1.46 Mbps S3,.3, 3.57 Mbps S1,.1, 2.13 Mbps S2,.14, 3.1 Mbps S3,.2, 2.56 Mbps S1,.3, 2.32 Mbps S2,.4, 2.56 Mbps S3,.4, 3.15 Mbps S1,.2, 1.44 Mbps S2,.2, 3. Mbps S3,.2, 1.54 Mbps S1,.6,.57 Mbps S2,.4, 1.88 Mbps S3,.2, 1.4 Mbps S1,.2, 1.38 Mbps S2,.23, 2.62 Mbps S3,.3, 2.99 Mbps S1,.85,.49 Mbps S2,.3, 1.25 Mbps S3,.1, 1.16 Mbps Fig. 6. Network BLER and throughput using 5 MHz transmission bandwidth and RR scheduler with 3 users per enodeb. Fig. 7. Throughput and BLER, CQI report for UE 6 using 5MHz and RR scheduler with 3 users per enodeb. REFERENCES [1] J.C. Ikuno, M. Wrulich, M. Rupp, System level simulation of LTE networks, in Proc. 21 IEEE 71 st Vehicular Technology Conference, Taipi, Tiawan, may 21. Available at htt://public.tuwien.ac.at/files/pubdat_18498.pdf ICETET 214 DSEC32 P a g e 25

5 Proceedings of International Conference on Emerging Trends in Electronics & Telecommunications (ICETET-14) [2] Christian Mehlführer *, Josep Colom Ikuno, Michal Šimko, Stefan Schwarz, Martin Wrulich and Markus Rupp, The Vienna LTE simulators Enabling reproducibility in wireless communications research, EURASIP Journal on Advances in Signal Processing 211, 211:29 [3] 3GPP TR v8.. Release 8, Requirements for evolved UTRA (E-UTRA) and evolved UTRAN (E-UTRAN). [4] Technical Specification Group RAN, E-UTRA; LTE RF system scenarios, 3GPP, Tech. Rep. TS , 89. [5] Christian Mehlführer *, Josep Colom Ikuno, Michal Šimko, Stefan Schwarz, Martin Wrulich and Markus Rupp Mehlführer et al. EURASIP Journal on Advances in Signal Processing 211, 211:29 [6] Onna IOSIF, Ion BANICA, U.P.B. Sci. Bull., Series C, Vol. 75, Iss. 1, 213. ICETET 214 DSEC32 P a g e 26