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Mobile Data Offloading May 2012 1/13 Mobile Data Offloading: A Tutorial Jianwei Huang Network Communications and Economics Lab (NCEL) Department of Information Engineering The Chinese University of Hong Kong (CUHK) Jianwei Huang (CUHK) Mobile Data Offloading (Tutorial) June 2015 1 / 147 Slides Available Online Google \Jianwei Huang" http://jianwei.ie.cuhk.edu.hk/Files/MDO-Tutorial.pdf Jianwei Huang (CUHK) Mobile Data Offloading (Tutorial) June 2015 2 / 147 Global Mobile Data Traffic, 2013 to 2018 Global Mobile DataOverall mobile Traffic data traffic is expected to grow to 15.9 exabytes per month by 2018, nearly an 11-fold increase over 2013. Mobile data traffic will grow at a CAGR of 61 percent from 2013 to 2018 (Figure 1). Figure 1. Cisco Forecasts 15.9 Exabytes per Month of Mobile Data Traffic by 2018 Global Mobile Data Traffic Growth Projection (source: Cisco VNI Mobile 2014) The Asia Pacific and North America regions will account for almost two-thirds of global mobile traffic by 2018, as shown in Figure 2. Middle East and Africa will experience the highest CAGR of 70 percent, increasing 14-fold over the forecast period. Central and Eastern Europe will have the second highest CAGR of 68 percent, increasing Annual growth rate13-fold over61% the forecast period. The emerging market regions of Asia Pacific and Latin America will have CAGRs of 67∼ percent and 66 percent respectively. I Expected to reach 15.9 exabytes per month by 2018 I A 11-fold increase over 2013 Jianwei Huang (CUHK) Mobile Data Offloading (Tutorial) June 2015 3 / 147 © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public. Page 5 of 40 The Femto Forum: Femtocells — Natural Solution for Offload Cellular MobileFigure Network 3: Historical Increases Capacity in Spectral Efficiency 16 If availableHistorical spectrum Increases is increasing in Spectral at 8% perEfficiency year and the (source:number of Femtoforum)cell sites is increasing at 7% per year and technology performance is improving at 12% per year then operators can expect their network capacities to increase – on average – at 29% Annualper grow year (1.08 rate x 1.07 x 1.12).36% If network capacity is growing at 29% per year and demand is growing currently∼ at 108% per year, then there is a significant gap, which begs for I Available spectrum band growth: 8% per year further innovation. I Cell site increase: 7% per year What other options exist? One possibility is architectural innovation. What if the I Spectrum efficiency growth: < 18% per year (2007 { 2013) definition of a “cell site” were radically changed, in such a way that the number of “sites” dramatically increased and the cost per unit of capacity (after adjusting for the inevitable lower utilisation of smaller108% sites)10 sign7%ificantly118 decreased?% = 1 36Similar% innovation has occurred before in the cellular industry.· Decad·es ago omni-directional sites were sectorised. Operators began adding “down tilt” to their urban site designs. Operators began introducing underlay and overlay sites. Jianwei Huang (CUHK) Mobile Data Offloading (Tutorial) June 2015 4 / 147 The architects of GSM put in place a hierarchical cell structure, allowing macro, micro, and picocells to hand up or down a hierarchical chain of command to one another, so as to best serve the customer and most effectively carry traffic. Technologists and infrastructure manufacturers developed smart antenna solutions that extend coverage and increase capacity. Marty Cooper, developer of the Motorola Dyna-Tac, the first handheld cellular phone, observed that the number of radio conversations that are theoretically possible per square mile in all spectrum has doubled every two and half years for the past 104 years 17 . Femtocells represent the next step in a long history of architectural innovation. Page 10 www.femtoforum.org Background Widening Supply-Demand Gap Network capacity growth vs Data traffic growth 29% vs 66% 36% vs. 61% Slow networkNetwork Capacity capacity growth vs. Fast data trafficData growth Traffic Lin Gao (NCEL, IE@CUHK) Mobile Data Offloading May 2012 1/13 Jianwei Huang (CUHK) Mobile Data Offloading (Tutorial) June 2015 5 / 147 Challenges: need to be cost effective and easy to deploy. How to Narrow the Gap: \Hard" Approaches Expanding the network capacity through technology innovations I Acquiring new spectrum bands I More efficient interference management through cooperations I Developing high-frequency wireless technology I Upgrading access technology (e.g., WCDMA LTE LTE-A) ! ! I Building more pico/micro/macro cell sites I ... Jianwei Huang (CUHK) Mobile Data Offloading (Tutorial) June 2015 6 / 147 How to Narrow the Gap: \Hard" Approaches Expanding the network capacity through technology innovations I Acquiring new spectrum bands I More efficient interference management through cooperations I Developing high-frequency wireless technology I Upgrading access technology (e.g., WCDMA LTE LTE-A) ! ! I Building more pico/micro/macro cell sites I ... Challenges: need to be cost effective and easy to deploy. Jianwei Huang (CUHK) Mobile Data Offloading (Tutorial) June 2015 6 / 147 Challenges: need to be user-friendly and network neutral. How to Narrow the Gap: \Soft" Approaches Reshaping the demand through economics and software I Tired data pricing I Capped or throttling (e.g., 128kbps if monthly usage >5GB) I Time/Location/Congestion dependent pricing (e.g., delay coupons) I Application specific optimization (e.g., network-friendly implem.) I On device software client (e.g., \fuel gauge" meters) I Content specific control (e.g., two-sided 1-800 pricing) I ... Jianwei Huang (CUHK) Mobile Data Offloading (Tutorial) June 2015 7 / 147 How to Narrow the Gap: \Soft" Approaches Reshaping the demand through economics and software I Tired data pricing I Capped or throttling (e.g., 128kbps if monthly usage >5GB) I Time/Location/Congestion dependent pricing (e.g., delay coupons) I Application specific optimization (e.g., network-friendly implem.) I On device software client (e.g., \fuel gauge" meters) I Content specific control (e.g., two-sided 1-800 pricing) I ... Challenges: need to be user-friendly and network neutral. Jianwei Huang (CUHK) Mobile Data Offloading (Tutorial) June 2015 7 / 147 Today's Focus: Mobile Data Offloading Basic idea: deliver cellular traffic over Wi-Fi or Femtocell. MU13 BS2 BS1 AP1 MU11 MU21 AP2 MU24 AP4 MU14 MU32 AP3 BS3 MU33 MU31 MU11 & MU21 AP1, MU24 AP2, MU31 & MU33 AP3, MU14 & MU32 AP4. ! ! ! ! Jianwei Huang (CUHK) Mobile Data Offloading (Tutorial) June 2015 8 / 147 A Reality Check Jianwei Huang (CUHK) Mobile Data Offloading (Tutorial) June 2015 9 / 147 As a percentage of total mobile data traffic from all mobile-connected devices, mobile offload increases from 45 percent (1.2 exabytes/month) in 2013 to 52 percent (17.3 exabytes/month) by 2018 (Figure 14). Without offload, Global mobile data traffic would grow at a CAGR of 65 percent instead of 61 percent. Offload volume is determined by smartphone penetration, dual-mode share of handsets, percentage of home-based mobile Internet use, and Global Mobilepercentage of dual Data-mode smartphone Offloading owners with Wi-Fi fixed Internet access at home. Figure 14. 52 Percent of Total Mobile Data Traffic Will Be Offloaded by 2018 Mobile Traffic Offloading Prediction (source: Cisco VNI Mobile 2014) The amount of traffic offloaded from smartphones will be 51 percent by 2018, and the amount of traffic offloaded from tablets will be 69 percent by 2018. Mobile offloading will increase from 45% in 2013 to 52% in 2018 A supporting trend is the growth of cellular connectivity for devices such as tablets which in their earlier generation were limited to Wi-Fi connectivity only. With increased desire for mobility and mobile carriers offer of data plans catering to multi-device owners, we find that the cellular connectivity is on a rise albeit cautiously as the end users are testing the waters. As a point in case, we estimate that by 2018, 42 percent of all tablets will have a cellular Jianwei Huangconnection (CUHK) up from 34 percentMobile in 2013 Data (Figure Offloading 15). (Tutorial) June 2015 10 / 147 © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public. Page 18 of 40 OffloadingFigure Increases16. Mobile Data Traffic and withOffload Traffic, Technology2018 Mobile and Offloaded Traffic from Mobile-Connected Devices (source: Cisco VNI Mobile 2014) Trend 6: Comparing Mobile Network Speeds Globally, the average mobile network connection speed in 2013 was 1,387 Kbps. The average speed will grow at 4G networksa compound will annual attract growth rate of high-usage 13 percent, and will devices.exceed 2.5 Mbps by 2018. Smartphone speeds, generally third-generation (3G) and higher, are currently almost three times higher than the overall average. Smartphone The offloadingspeeds will nearly ratio double onby 2018, 4G reaching will 7 beMbps. the highest. There is anecdotal evidence to support the idea that usage increases when speed increases, although there is often a delay between the increase in speed and the increased usage, which can range from a few months to several years. The Cisco VNI Forecast relates application bit rates to the average speeds in each country. Many Jianwei Huangof the (CUHK) trends in the resulting trafficMobile forecast Data can Offloading be seen (Tutorial)in the speed forecast, such as the highJune growth 2015 rates for 11 / 147 developing countries and regions relative to more developed areas (Table 5). © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public. Page 20 of 40 Complementary
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