Mobile Networks Saturation
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Innovation Reports - 04/05/2010
Solutions for MNOs
At a time where network congestion leads to dropped calls and interruptions in Internet access, this study presents the mobile traffic projections and capacity evaluation of IDATE experts based on several case studies. The aim of our in-depth analysis is, to determine the realities and to provide different scenarios for network saturation up to 2015.
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What are the lessons to be drawn from the sharp growth in mobile data traffic?
What are the bottlenecks explaining the different forms of network saturation?
- congestion in the radio access network and spectrum issues,
- congestion in the backhauling network,
- congestion in the core network.
What are the technical, marketing and strategic options available for mobile operators?
How can 4G/LTE serve congestion issues?
> Traffic Model & Scenarios
Conclusions are based on the results of an in-house model |
1. Executive Summary
Mobile data traffic is pushed by several technological and marketing enablers
The long awaited take-off of mobile data traffic is leading to congestion
Congestion is a threat to profitability
There are 4 main bottlenecks
Many options are available
2. Methodology
3. The Sharp Growth in Mobile Data Traffic
3.1. Key drivers
3.1.1. Improved network infrastructures
3.1.2. Improved mobile data-hungry devices
3.1.3. Strong mobile broadband subscribers' growth
3.1.4. Strong data demand
3.1.5. Mobile data plans
3.2. Mobile data traffic is to turn into congestion
3.2.1. Data-consumption driven by smartphones and portables
3.2.2. Data-consumption driven by video
3.3. Consequences of network congestion for MNOs
Higher churn rates
Higher direct loss of revenues
Higher reacquisition costs and the need to increase CRM efforts
Mobile data traffic is increasing faster than related revenues
Network costs become a threat to MNOs' profitability
4. Where Does Saturation Occur in a Mobile Network?
4.1. Various types of network saturation: identified bottlenecks
4.2. Congestion at the radio interface
4.3. Congestion in the backhauling network
4.4. Congestion in the RNC
4.5. Congestion in the core network
5. What Options Available to MNOs?
5.1. Adapt the backhauling network
5.1.1. Mobile operators invest in backhauling upgrades
5.1.2. Backhauling technical solutions
5.2. Improve the radio access network
5.2.1. Add new cell sites
5.2.2. Add small cells and picocells
5.2.3. Add urban femtocells
5.2.4. Cell splitting and sectorisation
5.2.5. Antennas enhancements
5.2.6. Switch to HSPA+
5.2.7. Accelerate LTE deployment
5.2.8. Buy additional spectrum / use refarming
5.2.9. Use emerging technologies
5.3. Offload mobile data traffic
5.3.1. Wi-Fi offload
5.3.2. Use femtocell capabilities for offloading
5.3.3. Consider the use of broadcast/multicast networks and capabilities
5.4. Improve the data traffic management
5.4.1. Adapt the core network
5.4.2. Manage the type of data traffic in the network
5.4.3. Optimise the applications running on smartphones
6. Traffic Model and Scenarios
6.1. Presentation
6.2. Main hypothesis
6.2.1. Frequency bands, data rates & capacity
6.2.2. Worldwide mobile traffic
6.3. Conservative scenario
6.4. Strong growth scenario
6.5. Large city
6.6. Conclusions on modeling
7. Conclusions for MNOs
7.1. Conclusions on traffic and capacity model
Wireless mobile data traffic is expected to increase sharply over the 2010-2015 period
No theoretical congestion problems
Dense urban areas are the biggest area of concern
7.2. Conclusions from options for MNOs
Carrier strategies will depend on their particular situation on the market place
Rising data demand can be met without exponential increase in CAPEX
What alternatives are favoured?
7.3. Conclusions MNOs global strategies
7.3.1. Speed up 4G deployment
7.3.2. Improve Wi-Fi coverage
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Traffic Model & Scenarios
Conclusions of the study are based on the results of an in-house model
In this study, mobile broadband is considered as a service that provides user access to mobile services, via any mobile device and over any mobile technology at speeds higher than 2.75G.
Segmentation by network speeds
GPRS roughly equates to 114 Kbps
EDGE to 474 Kbps
UMTS to 2 Mbps (stationary)
HSPA to 7.2 Mbps
HSPA+ to 28 Mbps
LTE to 100 Mbps
Modelling methodology
All results below will be based on a simulation of an imaginary mobile operator already running a UMTS/HSPA network and later a LTE network in an imaginary territory.
1 step
We evaluated the capacity of a mobile network based on the following characteristics:
50 million population in a developed country
Area: 400,000 500,000 km²
Mobile operator has 33% market share.
Spectrum availability: frequency band, number of channels, availability date
(see table below for detailed
values)
Spectrum efficiency, maximum data rate for each technology
Evaluation of the capacity of a cell
Total monthly and yearly capacity of the network
2 step
We estimated the mobile traffic (voice and data), first on a worldwide basis and then for a network operator in a medium-sized country. This evaluation takes into account the following assumptions:
Number of mobile subscriber and projections for 2010-2015
% of broadband subscribers
Voice and data traffic per user
Total voice and data traffic
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