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Smartphones impact in 3G and Future LTE Networks. Student : Adnan Basir (84906S) Supervisor : Jyri Hämäläinen Instructor : Timo Halonen (Nokia Siemens Networks ) Work carried out at Nokia Siemens Networks, Espoo. 17-March-2011. Aalto University, School of Electrical Engineering .
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Smartphones impact in 3G and Future LTE Networks Student : AdnanBasir (84906S) Supervisor : JyriHämäläinen Instructor : TimoHalonen (Nokia Siemens Networks ) Work carried out at Nokia Siemens Networks, Espoo 17-March-2011 Aalto University, School of Electrical Engineering
Table of Contents • Introduction /Background • Reason for Smartphone Signaling Congestion • Problem statement • Layer 3 Radio Resource Control (RRC) Cell states. • Method Used • Important Results • Signaling Congestion in LTE • Conclusion and Future Work
Introduction • What is smartphone ? • A device that has ability to browse internet, send/receive email, edit office tasks etc, in addition to make regular phone calls. • What is Smartphone Signaling Challenge ? • Huge Influx of smartphones to the market • Congestion in cellular networks • Failed call attempts • High congestion report in newyork (AT&T case) and london • Is increase in data usage the real problem ? • High data usage is only among small group of subscribers but congestion is in entire network.
Why Congestion then ! • Signaling Traffic is the culprit . • 30 – 50 % higher now as compared to data traffic. • Applications in smartphones connect to internet even when users are no using them (i.e. facebook updates, tweets etc). • Keep-alive messages • 3G networks were designed to handle huge data traffic but not signaling traffic ! • With influx of tablet devices the problem is going to get worse
RRC Cell states • What is signaling message ? • Each time a mobile make state transition it generates signaling messages. • 30 messages to go between idle and dch • 7 messages between dch and pch • 2 messages between pch and fach • Some mobile vendors implement Fast dormancy which is transition from DCH to IDLE state when there is no data.
Thesis objective • Observe impact of various smartphones applications on network in terms of resource management. • Best network parameters for optimized services • T1, T2, T3 timers etc • To study How LTE cope with signaling congestion problem.
Method Used • 3G Test Network • 3G RRC logs with EMIL Tool (NSN propriety) • Wireshark for traces from 3G Gn Interface • NSN NETACT to configure network parameters • Nemo Handy (Used in case of outdoor map studies)
Important Results • Online Gaming • 30 minutes game play • A single voice call would result in estimated 50 signaling messages. • Android uses “Fast dormancy” which results in high number of signaling messages TOTAL STATE TRANSITIONS TOTAL SIGNALING MESSAGES(Respective to state transitions) 3201 1996 345 97 G Android IPhone 4.1
3201 Total Signaling Messages = 3201 ! Android uses fast dormancy and forces the UE to idle state when there is no data ! STATE TRANSITIONS SIGNALING MESSAGES(Respective to state transitions) 97 RABS DCH>FACH FACH>PCH PCH>FACH FACH>DCH SIGNALING IMPACT (TEXAS HOLDEM ON GOOGLE ANDROID) Total Signaling Messages = 1996 ! 936 930 STATE TRANSITIONS SIGNALING MESSAGES(Respective to state transitions) 155 156 36 28 66 18 14 2 RABS DCH>FACH FACH>PCH PCH>FACH FACH>DCH SIGNALING IMPACT (LIVE POKER ON IPHONE 4.1) Important Results 30 minutes game play !
24 Hour user profiling with N97 • In 24 Hour resources utilization estimate, idle, shoulder and busy cases have been divided as following • User remain idle for 14 hours in 24 hours • User perform shoulder activity for 7 hours in 24 hours. • User perform busy activity for 3 hours in 24 hours • For N97 mini, the results from 24 hour profile is given in the table
Signaling Congestion in LTE • Simplified RRC Architecture • RRC Idle • Cell selection • Monitoring • RRC Connected • DRX in connected state • Only one reconfiguration message • No RNC • Simple RRC connection procedure. • No NBAP and ALCAP signaling • Only PS Domain • No signaling connection release procedure • MME Handling most of the load now • So there can more signaling congestion on core network side
Other important studies • Impact of CELL_PCH • Laptop (with utms dongle) Vs Mobile signaling Load • Maps Studies (Google maps, Ovi maps) • Angry bird (Online Game) • MiFi study
Conclusion / Future Work • Implement HSPA Release 7 Cell-Fach • HS-DSCH instead of FACH • High efficiency • Implement Cell-Pch • Avoid fast-dormancy • Femtocells • Load sharing (signaling/data) • Intelligent network monitoring • Application using more signaling resources • Charge users on application bases
QUESTIONS ? THANK YOU !