Operators in emerging markets such as India are already facing congestion on their 3G networks in specific areas and at certain times of day, despite less-than-optimal utilisation levels overall. Utilisation is expected to slowly increase as device penetration grows and data usage increases. The congestion creates a sub-optimal user experience, which leads to churn. Mobile network operators need to understand consumer behaviour and consider related solutions to address this issue because spectrum availability is limited.
This article examines options available to operators, including network-related solutions as well as pricing and policy management solutions. However, before defining the solutions, it is essential that operators understand the consumer behaviour-related drivers of network congestion. Figure 1 summarises some of the key questions that operators need to answer.
Figure 1: Key areas of investigation for consumer-related drivers of mobile network congestion [Source: Analysys Mason, 2014]
|
Area |
Key questions |
Consumer-related drivers |
|
User/traffic distribution |
|
To be able to define pricing and policy management rules for different consumer segments (preferred users versus abusers) as well as analyse migration options |
|
Device distribution |
|
To be able to understand LTE migration options and to understand Release 99 issues |
|
User consumption trends |
|
To better define pricing and policy management rules specific to data application as well as to tethering |
Offloading traffic or migrating users to other networks are among the most obvious solutions available to operators
Operators can use two types of traffic offload policy to alleviate congestion on their networks.
- Service-based offload: Low-bandwidth consumption services such as 3G circuit-switched voice can be offloaded to underutilised GSM networks. Operators first need to analyse the contribution of voice in the overall traffic in these sites and establish whether the GSM networks can be used to dynamically offload voice traffic at certain times.
- Network-based offload: Services running on the WCDMA network could be segmented to run either on macro or micro networks. For example, all real-time data services could be handled by macro networks and non-real-time services (such as app updates and email) on small cells.
Migrating heavy traffic users to newly rolled out LTE networks is being actively considered. However, for this option, operators need to:
- understand the traffic distribution by device type – that is, LTE-capable handsets, non-LTE handsets, TD versus FD devices, and USB modems
- provide users of LTE-capable handsets and USB modems with incentives to migrate to LTE networks such as offering competitive prices for 3G at better throughputs.
Pricing and policy management solutions can also help reshape network traffic
Pricing and policy solutions can be broadly classified into four categories.
- User category-based solutions can include segmenting users based on their contribution to revenue and traffic, and setting policies and priority levels by user segment, ensuring good experience for loyal customers while penalising network abusers.
- Service-based policies can also be implemented, whereby certain high-bandwidth applications used by a small number of users, such as P2P downloads, can be throttled during peak hours. Low-priority, non-real-time services that do not impact user experience can also be queued up for non-peak hours. For example, AT&T uses a solution on the handset side that throttles or queues up automatic software upgrades for download at a later time.
- Shared data-based solutions include restricting tethering-based usage by charging a premium for tethering plans, allowing tethering only on premium plans or restricting the number of devices.
- Load- or time-based plans include discounting data tariffs during non-peak hours as well as in specific sites that are usually underutilised. For example, SmarTone in Hong Kong uses policy management software to offer time and cell site utilisation-based data discounts to its customers.
As part of Analysys Mason's commercial strategy expertise, we have helped a number of operators develop innovative pricing strategies to address both network- and consumer-specific issues.
Source: Analysys Mason
