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Cellular Networks and Mobile Computing COMS 6998-10, Spring 2013

Cellular Networks and Mobile Computing COMS 6998-10, Spring 2013. Instructor: Li Erran Li ( lierranli@cs.columbia.edu ) http://www.cs.columbia.edu/ ~lierranli/coms6998-10Spring2013/ 3 / 5 /2013: Radio Resource U sage P rofiling and Optimization. Announcements. Course evaluation due!

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Cellular Networks and Mobile Computing COMS 6998-10, Spring 2013

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  1. Cellular Networks and Mobile ComputingCOMS 6998-10, Spring 2013 Instructor: Li Erran Li (lierranli@cs.columbia.edu) http://www.cs.columbia.edu/~lierranli/coms6998-10Spring2013/ 3/5/2013: Radio Resource Usage Profiling and Optimization

  2. Announcements • Course evaluation due! • Project description due on March 25

  3. Review of Previous Lecture • What are the physical layer technologies in 3G and LTE?

  4. UMTS Physical Layer Code Division Multiple Access (CDMA) • Use of orthogonal codes to separate different transmissions • Each symbol or bit is transmitted as a larger number of bits using the user specific code – Spreading • Spread spectrum technology • The bandwidth occupied by the signal is much larger than the information transmission rate • Example: 9.6 Kbps voice is transmitted over 1.25 MHz of bandwidth, a bandwidth expansion of ~100 Courtesy: Harish Vishwanath

  5. One resource block 12 subcarriers during one slot (180 kHz × 0.5 ms) One resource element 12 subcarriers One OFDM symbol One slot LTE Physical Layer • The key improvement in LTE radio is the use of OFDM • Orthogonal Frequency Division Multiplexing • 2D frame: frequency and time • Narrowband channels: equal fading in a channel • Allows simpler signal processing implementations • Sub-carriers remain orthogonal under multipath propagation frequency Time domain structure Frame (10 ms) time Slot (0.5 ms) Subframe (1 ms)

  6. Review of Previous Lecture (Cont’d) • What are the mobility protocols used in cellular networks?

  7. Mobility Protocol: GTP SGi HSS PDN GW GTP S5 Gn GTP SGW MME SGSN MSC S11 IuCS IuPS RNC S1-U S1-CP GTP Iub eNodeB NodeB UE Courtesy: Zoltán Turányi

  8. Mobility Protocol: Proxy Mobile IP (PMIP) SGi HSS PDN GW S5 PMIP S2 SGW MME PMIP S11 Non-3GPP Access (cdma2000, WiMax, WiFi) S1-U S1-CP GTP eNodeB UE EPC – Evolved Packet Core Courtesy: Zoltán Turányi

  9. Review of Previous Lecture (Cont’d) • Is carrier sensing multiple access (CSMA) used in cellular networks?

  10. Random Access Why not carrier sensing like WiFi? • Base station coverage is much larger than WiFi AP • UEs most likely cannot hear each other • How come base station can hear UEs’ transmissions? • Base station receivers are much more sensitive and expensive Base station UE 2 UE 1

  11. Review of Previous Lecture (Cont’d) • What are the problems of current LTE network architecture?

  12. LTE Data Plane is too Centralized • Data plane is too centralized • UE: user equipment • eNodeB: base station • S-GW: serving gateway • P-GW: packet data network gateway eNodeB 1 Cellular Core Network Scalability challenges at P-GW on charging and policy enforcement! eNodeB 2 S-GW 1 UE 1 P-GW Internet and Other IP Networks eNodeB 3 S-GW 2 UE 2 GTP Tunnels

  13. LTE Control Plane is too Distributed • No clear separation of control plane and data plane Home Subscriber Server (HSS) • Problem with Inter-technology (e.g. 3G to LTE) handoff • Problem of inefficient radio resource allocation Control Plane Data Plane Mobility Management Entity (MME) Policy Control and Charging Rules Function (PCRF) Packet Data Network Gateway (P-GW) Serving Station (eNodeB) Base Gateway (S-GW) User Equipment (UE)

  14. Review of Previous Lecture (Cont’d) • What can we do to design a better cellular network for the future?

  15. CellSDNArchitecture Mobility Manager Subscriber Information Base Policy and Charging Rule Function Infra-structure Routing Radio Resource Manager Translates policies on subscriber attributes to rules on packet header SCTP instead of TCP to avoid head of line blocking Network Operating System: CellOS Offloading controller actions, e.g. change priority if counter exceed threshold Cell Agent Cell Agent Cell Agent Central control of radio resource allocation DPI to packet classification based on application Packet Forwarding Hardware Packet Forwarding Hardware Radio Hardware

  16. CellSDN Virtualization Network OS (Slice 1) Network OS (Slice 2) Network OS (Slice N) Slicing Layer: CellVisor Slice semantic space, e.g. all roaming subscribers, all iPhone users Cell Agent Cell Agent Cell Agent Packet Forwarding Hardware Packet Forwarding Hardware Radio Hardware

  17. Outline • Introduction • Network Characteristics • RRC State Inference • Radio Resource Usage Profiling & Optimization • Biayo Su and AshwinRamachandran on radio resource profiling (15min) • Network RRC Parameters Optimization • Xin Ye and Nan Yan on RadioJockey (15min) • Conclusion

  18. Introduction • Typical testing and optimization in cellular data network • Little focus has been put on their cross-layer interactions Many mobile applications are not cellular-friendly. • The key coupling factor: the RRC State Machine • Application traffic patterns trigger state transitions • State transitions control radio resource utilization, end-user experience and device energy consumption (battery life) ? RRC State Machine Courtesy: FengQian et al.

  19. Network characteristics • 4GTeston Android • http://mobiperf.com/4g.html • Measures network performance with the help of 46 M-Lab nodes across the world • 3,300users and 14,000 runs in 2 months 10/15/2011 ~ 12/15/2011 4GTest user coverage in the U.S. Courtesy: Junxian Huang et al.

  20. Downlink throughput • LTE median is 13Mbps, up to 30Mbps • The LTE network is relatively unloaded • WiFi, WiMAX < 5Mbps median

  21. Uplink throughput • LTE median is 5.6Mbps, up to 20Mbps • WiFi, WiMAX < 2Mbps median

  22. RTT • LTE median 70ms • WiFi similar to LTE • WiMAX higher

  23. The RRC State Machine for UMTS Network • State promotions have promotion delay • State demotions incur tail times Tail Time Delay: 1.5s Delay: 2s Tail Time Courtesy: FengQian et al.

  24. Example: RRC State Machinefor a Large Commercial 3G Network DCH Tail: 5 sec FACH Tail: 12 sec Tail Time: waiting inactivity timers to expire DCH: High Power State (high throughput and power consumption) FACH: Low Power State (low throughput and power consumption) IDLE: No radio resource allocated Promo Delay: 2 Sec Courtesy: FengQian et al.

  25. Why State Promotion Slow? + RRC connection setup: ~ 1sec Radio Bearer Setup: ~ 1 sec Figure source: HSDPA/HSUPA for UMTS: High Speed Radio Access for Mobile Communications. John Wiley and Sons, Inc., 2006. Tens of control messages are exchanged during a state promotion.

  26. Example of the State Machine Impact:Inefficient Resource Utilization State transitions impact end user experience and generate signaling load. A significant amount of channel occupation time and battery life is wasted by scattered bursts. Analysis powered by the ARO tool Courtesy: FengQian et al.

  27. RRC state transitions in LTE Courtesy: Junxian Huang et al.

  28. RRC state transitions in LTE • RRC_IDLE • No radio resource allocated • Low power state: 11.36mW average power • Promotion delay from RRC_IDLE to RRC_CONNECTED: 260ms Courtesy: Junxian Huang et al.

  29. RRC state transitions in LTE • RRC_CONNECTED • Radio resource allocated • Power state is a function of data rate: • 1060mW is the base power consumption • Up to 3300mW transmitting at full speed Courtesy: Junxian Huang et al.

  30. RRC state transitions in LTE Continuous Reception Send/receive a packet Promote to RRC_CONNECTED Reset Ttail Courtesy: Junxian Huang et al.

  31. RRC state transitions in LTE DRX Ttail expires Ttail stops Demote to RRC_IDLE Courtesy: Junxian Huang et al.

  32. Tradeoffs of Ttail settings Courtesy: Junxian Huang et al.

  33. RRC state transitions in LTE • DRX: Discontinuous Reception • Listens to downlink channel periodically for a short duration and sleeps for the rest time to save energy at the cost of responsiveness Courtesy: Junxian Huang et al.

  34. Discontinuous Reception (DRX): micro-sleeps for energy saving • In LTE 4G, DRX makes UE micro-sleep periodicallyin the RRC_CONNECTED state • Short DRX • Long DRX • DRX incurs tradeoffs between energy usage and latency • Short DRX – sleep less and respond faster • Long DRX – sleep more and respond slower • In contrast, in UMTS 3G, UE is always listening to the downlink control channel in the data transmission states Courtesy: Junxian Huang et al.

  35. DRX in LTE • A DRX cycle consists of • ‘On Duration’ - UE monitors the downlink control channel (PDCCH) • ‘Off Duration’ - skip reception of downlink channel • Ti: Continuous reception inactivity timer • When to start Short DRX • Tis: Short DRX inactivity timer • When to start Long DRX Courtesy: Junxian Huang et al.

  36. LTE power model • Measured with a LTE phone and Monsoon power meter, averaged with repeated samples

  37. LTE power model • Measured with a LTE phone and Monsoon power meter, averaged with repeated samples

  38. LTE power model • Measured with a LTE phone and Monsoon power meter, averaged with repeated samples

  39. LTE power model • Measured with a LTE phone and Monsoon power meter, averaged with repeated samples

  40. LTE power model • Measured with a LTE phone and Monsoon power meter, averaged with repeated samples • P(on) – P(off) = 620mW, DRX saves 36% energy in RRC_CONNECTED • High power levels in both On and Off durations in the DRX cycle of RRC_CONNECTED

  41. LTE consumes more instant power than 3G/WiFi in the high-power tail • Average power for WiFi tail • 120mW • Average power for 3G tail • 800mW • Average power for LTE tail • 1080mW Courtesy: Junxian Huang et al.

  42. Power model for data transfer • A linear model is used to quantify instant power level: • Downlink throughput td Mbps • Uplink throughput tuMbps < 6% error rate in evaluations with real applications Courtesy: Junxian Huang et al.

  43. Energyper bit comparison • LTE’s high throughput compensates for the promotion energy and tail energy Total energy per bit for downlink bulk data transfer Courtesy: Junxian Huang et al.

  44. Energyper bit comparison • LTE’s high throughput compensates for the promotion energy and tail energy Small data transfer, LTE wastes energy Large data transfer, LTE is energy efficient Total energy per bit for downlink bulk data transfer Courtesy: Junxian Huang et al.

  45. Example of the State Machine Impact:DNS timeout in UMTS networks Start from CELL_DCH STATE (1 request / response) – Keep in DCH Start from CELL_FACH STATE (1 request / response) – Keep in FACH Start from IDLE STATE (2~3 requests / responses) – IDLE  DCH Starting from IDLE triggers at least one DNS timeout (default is 1 sec in WinXP) 2 second promotion delay because of the wireless state machine (see previous slide), but DNS timeout is 1 second! => Triple the volume of DNS requests… Courtesy: FengQian et al.

  46. State Machine Inference P1: IDLEFACH, P2:IDLEDCH P1: FACHDCH, P2:Keep on DCH Normal RTT < 300msRTT w/ Promo > 1500ms A packet of min bytes never triggers FACHDCH promotion (we use 28B) A packet of max bytes always triggers FACHDCH promotion (we use 1KB) • State Promotion Inference • Determine one of the two promotion procedures • P1: IDLEFACHDCH; P2:IDLEDCH • State demotion and inactivity timer inference • See paper for details Courtesy: FengQian et al.

  47. RRC State Machines of Two Commercial UMTS Carriers PromotionInference Reports P2 IDLEDCH PromotionInference Reports P1 IDLEFACHDCH Carrier 1 Carrier 2 What are the optimal inactivity timer values? Courtesy: FengQian et al.

  48. State Machine Inference DCH Tail: 5 sec FACH Tail: 12 sec Carrier 1 Promo Delay: 2 Sec Validation using a power meter

  49. Outline • Introduction • RRC State Inference • Radio Resource Usage Profiling & Optimization • Network RRC Parameters Optimization • Conclusion

  50. ARO: Mobile Application Resource Optimizer • Motivations: • Are developers aware of the RRC state machine and its implications on radio resource / energy? NO. • Do they need a tool for automatically profiling their prototype applications? YES. • If we provide that visibility, would developers optimize their applications and reduce the network impact? Hopefully YES. • ARO: Mobile Application Resource Optimizer • Provide visibility of radio resource and energy utilization. • Benchmark efficiencies of cellular radio resource and battery life for a specific application Courtesy: FengQian et al.

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