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David Goodman - IEEE VTS UKRI - Can cellular networks keep up with the growth of big data?
This document summarizes David Goodman's presentation on addressing the cellular data crisis. The presentation covered: 1) Explosive growth in mobile data usage and the inability of current pricing models to keep up with demand. 2) Technological approaches being taken by the industry to increase network capacity, such as small cell deployment, new spectrum auctions, and video compression. 3) Research at NYU Wireless, including developing techniques for cell selection using opportunistic backhaul, fast handover between small cells, and millimeter wave communications.
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David Goodman - IEEE VTS UKRI - Can cellular networks keep up with the growth of big data?
- 1. CAN CELLULAR NETWORKS KEEPUP WITH THE GROWTH OF BIG DATA? David Goodman NYU WIRELESS Polytechnic Institute of New York University dgoodman@poly.edu IEEE VTS-UKRI CHAPTER MEETING July 26, 2012 David Goodman July 26, 2012
- 2. Cellular Data Crisis2010 January 28, 2010 @ 4G World: Carriers brace for data storm October 20, 21 2010 Like the rest of the world, Japan is forecasting explosive growth in data traffic. Japanese end users are demanding high-definition digital cameras, access to YouTube, e-books and online games. David Goodman July 25, 2012
- 3. Cellular Data Crisis 2012 Update 4G upgrade signals threat and FT: Feb. 25, 2012 opportunity 10-fold surge in global mobile data traffic … by 2016 Non-voice service revenue annual % growth: Italy 1.8, UK 4.9, Germany 7.0 David Goodman July 25, 2012
- 4. Cellular Data Crisis COST $$ REVENUE Time iPhone etc. SMS David Goodman July 25, 2012
- 5. Cellular Data Crisis •Revenue 2005-09 $8.5B →$37B 4x • AT&T Data Usage 2006-09 70x • Japan data usage 2007 – 2017 200x ?? David Goodman July 25, 2012
- 6. Cellular Data Usage •BlackBerry = Cellphone x 2 • iPhone = BlackBerry x 5 • Aircard = iPhone x 5 • iPad, future devices and services = ??? David Goodman July 25, 2012
- 7. Cellular Service Plans •Voice $60 750 minutes $600/GB • SMS $20 1000 texts* $60000/GB • Data $60 5 GB $12/GB • iPhone $30 unlimited →$5/GB?? Pandora=60 MB/hour Live video =300 MB/hour *2011: 8T texts = $127B = $53,000/GB David Goodman July 25, 2012
- 8. What’s wrong withthis picture? Revenue Demand Voice Usage sensitive Limited SMS Data Fixed Unlimited David Goodman July 25, 2012
- 9. Industry response $10-50/GB From June 28, 2012 David Goodman July 25, 2012
- 10. New picture (June2012) Revenue Demand Voice Usage sensitive Limited SMS Fixed Data Fixed Unlimited Usage sensitive David Goodman July 25, 2012
- 11. Increase Network Capacity •Cell splitting • More spectrum • Advanced technology David Goodman July 25, 2012
- 12. Increase Network Capacity 1985-2008 • Total x10,000 • Cell splitting x400 • More spectrum x3.4 • Efficient technology x7 David Goodman July 25, 2012
- 13. FCC Auction 2008 $19,000,000,000 David Goodman July 25, 2012
- 14. 4G Spectrum Auctions France €3.8B Germany €4.4B Italy €3.9B Spain €1.6B UK Late 2012 David Goodman July 25, 2012
- 15. Cellular technology evolution wider transmission bands 1G 2G 3G 4G 25-30 kHz 200 kHz 5 MHz 1.4-20 MHz 100 MHz 1980 1990 2000 2010 20?? AMPS GSM WCDMA LTE LTE-A David Goodman July 25, 2012
- 16. Cellular technology evolution Internet core network 1G 2G, 3G 4G Cellular SS7 - ISDN IP protocols David Goodman July 25, 2012
- 17. Cellular technology evolution multiple access 1G, “4G” 2G 3G FDMA TDMA CDMA 1990 2000 2010 David Goodman July 25, 2012
- 18. Cellular technology evolution system names 1G 2G 3G 1980 – NMT 1990 – GSM 2000 – UMTS NORDIC GLOBAL UNIVERSAL 4G 2010 – ??? LTE David Goodman July 25, 2012
- 19. Addressing the datacrisis Industry trends • LTE – Up to 20 MHz signal band – Up to 300/75 (DL/UL) throughput – Up to 4x4 MIMO – IP core network • Video compression • Smaller cells • Wi-Fi off-loading David Goodman July 25, 2012
- 20. NYU WIRELESS Director: Prof.Ted Rappaport nyuwireless.org David Goodman July 25, 2012
- 21. Addressing the datacrisis Future directions • Network optimization with small cells • mm wave transmission • Cooperative communications • Cognitive radio • Adaptive pricing David Goodman July 25, 2012
- 22. Addressing the datacrisis NYU WIRELESS RESEARCH • Network with small cells – Optimum cell selection Prof. Rangan – Handover for mobile terminals Prof. Panwar • mm wave communication, Prof. Rappaport – Measurements, devices • Cooperative communications Prof. Erkip, Knox, Panwar – Algorithms, signal processing, testbed David Goodman July 25, 2012
- 23. Femto and pico Femto- and Picocells: cells Small is Beautiful Smaller, easily deployable, lower cost Traditional Nokia MetroSite Huawei femtocell macrocell tower UMTS base “personal base station station” 5 Wireless Research Lab David Goodman July 25, 2012
- 24. Femtocell Use customer broadband for backhaul Offload traffic from Macro cells David Goodman July 25, 2012
- 25. Femtocell challenges • Uncontrolledinterference environment – Unplanned deployments. – Large power disparities between macro and femto. – Restricted association & closed subscriber groups • Need for self-configuration & “plug & play”. – Must synchronize for macro-femto handover & to enable advanced interference mitigation techniques. • Mixed backhaul: operator and subscriber’s ISP. David Goodman July 25, 2012
- 26. Small cells arecoming Today's Top News (June 25, 2012) Rumor mill: AT&T gears up to order 100,000 small cells (283,000 cells total in USA at end of 2011) Small cells=femto < pico < metro < micro www.smallcellforum.org David Goodman July 25, 2012
- 27. Backhaul becoming adominant cost • Backhaul represents significant cost to operators: – 30 to 50% of OPEX costs by various estimates • Cost and management of airlink is decreasing – Lower power / smaller cells – Self-organization • With greater bandwidth and larger numbers of cell sites, backhaul will become dominant expense • Is there a cheaper way to deliver backhaul? David Goodman July 25, 2012
- 28. Cell selection withopportunistic backhaul: Prof S. Rangan • Cell selection now based on signal strength • Add backhaul as selection criterion • Provision for average (not maximum) traffic • Opportunistic backhaul challenges – Variable traffic loads – Distributed management – Heterogenous cell sizes – Load balancing – Small numbers of users per cell David Goodman July 25, 2012
- 29. Cellular Handover, Prof.Panwar • Handover between macrocells takes less than 100ms. • Handover to indoor Femtocells – Near stationary user – Slow handover: Many messages going over the public internet. • Handover among outdoor picocells – More Frequent: Users quickly passing through small cells. David Goodman July 25, 2012
- 30. Faster Handover • Prefetchuser data to picocells in proximity. • Add a fast over-the-air interface connecting picocells. • Decouple control messages from actual handoff. Handover Durations for Femtocells • Legacy Handover ~ 1500ms. (applied as it is) • Prefetch-based Fast Handover ~ 800ms. (with all control messaging via backhaul) • Near-Instantaneous Handover ~ 30ms. (with OTA interface) David Goodman July 25, 2012
- 31. Background Spectrum Allocationfor 60GHz – key mmWave frequency • Spectrum allocation similar worldwide • 5 GHz common bandwidth among several countries •Park, C., Rappaport, T.S. , “Short Range Wireless Communications for Next Generation Networks: UWB, 60 GHz Millimeter-Wave PAN, and ZigBee,” Vol.14, No. 4, IEEE Wireless Communications Magazine, Aug. 2007, pp 70-78. •G. L. Baldwin, “Background on Development of 60 GHz for Commercial Use,” SiBEAM, inc. white paper, May 2007, http://sibeam.com/whtpapers/Background_on_Dev_of_60GHz_for_Commercial%20Use.pdf David Goodman July 25, 2012
- 32. mm Wave devices mmWave/sub-THz on-chip antennas Probe de-embedding and calibration RFICs for 60 GHz, 77 GHz, sub-THz Wireless propagation measurements and modeling for mmWave/sub-THz On-chip channel sounding system “PN Generator” “Antenna” Dec. 2009 Oct. 2010 3 1,4 “Bevo 1” June 2009 1,4,5 “Bevo 4” July 2010 2 David Goodman July 25, 2012
- 33. Cooperative communications research at NYU WIRELESS •Antenna diversity (virtual MIMO) •Cooperative coding •Coop MAC – IEEE802 •Relay •Video multicast •P-to-P content sharing David Goodman July 25, 2012
- 34. Cooperative communications Portable devicescommunicate with each other S1 Base Station S2 Bandwidth consumers → suppliers David Goodman July 25, 2012
- 35. Adaptive Pricing Research QuickTime™ and a decompressor are needed to see this picture. David Goodman July 25, 2012
- 36. Beyond the datacrisis • Align theory, experiments, and systems • Challenges become opportunities – Mobile (distribute information) – Portable (human energy source) – Free space (broadcasting, cooperation) • Application specific networks – Health – Transportation – Environment – Entertainment David Goodman July 25, 2012