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White Paper 
RAN Congestion Management: 
Meet the Challenges of Mobile 
Broadband with Cisco Quantum 
Policy
© 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 2 of 10 
Contents 
Introduction .............................................................................................................................................................. 4 
Customer Challenges .............................................................................................................................................. 4 
Resolving RAN Congestion .................................................................................................................................... 5 
Business Case Study .............................................................................................................................................. 7 
RAN Congestion-Aware Solution with Cisco Quantum Policy ............................................................................ 7 
Advantages of Cisco Quantum Policy RAN Congestion Management ............................................................... 9 
Summary ................................................................................................................................................................ 10 
For More Information ............................................................................................................................................. 10
© 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 3 of 10 
THE SPECIFICATIONS AND INFORMATION REGARDING THE PRODUCTS IN THIS MANUAL ARE SUBJECT TO CHANGE WITHOUT NOTICE. ALL STATEMENTS, INFORMATION, AND RECOMMENDATIONS IN THIS MANUAL ARE BELIEVED TO BE ACCURATE BUT ARE PRESENTED WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED. USERS MUST TAKE FULL RESPONSIBILITY FOR THEIR APPLICATION OF ANY PRODUCTS. 
THE SOFTWARE LICENSE AND LIMITED WARRANTY FOR THE ACCOMPANYING PRODUCT ARE SET FORTH IN THE INFORMATION PACKET THAT SHIPPED WITH THE PRODUCT AND ARE INCORPORATED HEREIN BY THIS REFERENCE. IF YOU ARE UNABLE TO LOCATE THE SOFTWARE LICENSE OR LIMITED WARRANTY, CONTACT YOUR CISCO REPRESENTATIVE FOR A COPY. 
The Cisco implementation of TCP header compression is an adaptation of a program developed by the University of California, Berkeley (UCB) as part of UCB’s public domain version of the UNIX operating system. All rights reserved. Copyright © 1981, Regents of the University of California. 
NOTWITHSTANDING ANY OTHER WARRANTY HEREIN, ALL DOCUMENT FILES AND SOFTWARE OF THESE SUPPLIERS ARE PROVIDED “AS IS” WITH ALL FAULTS. CISCO AND THE ABOVE-NAMED SUPPLIERS DISCLAIM ALL WARRANTIES, EXPRESSED OR IMPLIED, INCLUDING, WITHOUT LIMITATION, THOSE OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OR ARISING FROM A COURSE OF DEALING, USAGE, OR TRADE PRACTICE. 
IN NO EVENT SHALL CISCO OR ITS SUPPLIERS BE LIABLE FOR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, OR INCIDENTAL DAMAGES, INCLUDING, WITHOUT LIMITATION, LOST PROFITS OR LOSS OR DAMAGE TO DATA ARISING OUT OF THE USE OR INABILITY TO USE THIS MANUAL, EVEN IF CISCO OR ITS SUPPLIERS HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. 
Cisco and the Cisco logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. To view a list of Cisco trademarks, go to this URL: http://www.cisco.com/go/trademarks. Third- party trademarks mentioned are the property of their respective owners. The use of the word partner does not imply a partnership relationship between Cisco and any other company. (1110R). 
Any Internet Protocol (IP) addresses and phone numbers used in this document are not intended to be actual addresses and phone numbers. Any examples, command display output, network topology diagrams, and other figures included in the document are shown for illustrative purposes only. Any use of actual IP addresses or phone numbers in illustrative content is unintentional and coincidental. 
© 2014 Cisco Systems, Inc. All rights reserved.
© 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 4 of 10 
Introduction 
Rapid growth in mobile data traffic is pushing networks to their limits, resulting in increased operator concerns about RAN congestion management in their networks - how to avoid it, and how to deal with it once it occurs. This ever-growing demand is driven by the popularity of multimedia handsets, smartphones, and mobile data card- enabled laptops. The popularity of tablets, such as the Apple iPad and Android-based devices, is expected to accelerate traffic growth further, especially mobile video. 
Mobile network service providers have traditionally addressed congestion by deploying additional capacity. However, it takes time to bring additional capacity online. With subscriber demand for new data applications and video traffic accelerating, simply adding bandwidth is not viable over the long term. Nor can service providers just slow traffic indiscriminately across the network without affecting users’ quality of experience, which is likely to increase churn. 
Adding to the challenges, network congestion often occurs in predictable busy hour times and locations. But it also flares up at unpredictable times and locations across the network. 
Service providers need more sophisticated solutions that can specifically target congested zones and intelligently take into account the subscribers and applications contributing most to the congestion. 
Customer Challenges 
RAN technologies, delivery architectures, and economics haven’t kept pace with customers’ increasing appetite for mobile broadband services. Techniques used by device manufacturers to optimize the customer experience, such as saving battery life, are severely affecting the signalling load and resources in the RAN. As more and more subscribers turn to data-intensive devices and applications, demands on the network increase. As a result, there is a growing gap between rising data traffic and revenue. And, as more subscribers connect from their desktop computers, mobile network congestion is increasing. This congestion strains network resources and bandwidth, negatively affecting subscribers’ quality of experience (QoE) and creating churn, because subscribers don’t remain loyal if service quality doesn’t meet their expectations. 
The dramatic rise in signalling congestion is largely attributable to increasing use of smartphones and tablets. A single smartphone can generate eight times the network signalling load of a laptop USB modem. Even in idle mode, the devices generate substantial signalling traffic, sending messages to keep in sync with the network, maintain status and location, and connect and reconnect. In addition, the increased resource usage of, mobile data services, devices, and applications are also largely responsible for congestion of these services: 
● Streaming video 
● Streaming audio 
● Downloads and file sharing (peer to peer) 
● Peer-to-peer video 
High-definition (HD) and 3D video busy-hour periods are also a significant contributor to congestion, because they vary from operator to operator and are now expanding in scope. Many operators are increasing network capacity or moving to Long Term Evolution (LTE) technology, with its increased bandwidth, to handle swelling traffic loads. However, these approaches need to be supplemented by other techniques that help address traffic growth, concentration, and signalling congestion in ways that are cost efficient and improve the customer experience. 
The Policy and Charging Control (PCC) architecture, as defined in 3GPP TS 23.203, provides features supporting traffic flow and network utilisation policy management and online and off-line charging.
© 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 5 of 10 
Resolving RAN Congestion 
Adding capacity to the network to prevent peak-usage congestion, essentially over-provisioning the network, is not a cost-effective or practical answer, because RAN bandwidth is still very expensive compared to core network bandwidth. However, finding a solution to RAN congestion is critical to long-term success, because RAN congestion has a direct and immediate effect on QoE and ultimately on subscriber loyalty. A number of techniques can combat RAN congestion, including: 
● Scheduled congestion zones 
● Real-time congestion notification 
Scheduled Congestion Zones 
The Standard 3GPP PCC model provides an architectural approach which supports dynamic real-time monitoring, charging, and control of user sessions. However, more is needed to fully monetize the mobile network. 
Scheduled congestion zones refer to a preconfigured congestion schedule (by day of week, time of day, congestion times, location, and levels) to relieve the predictable congestion that occurs during busy hours. In addition, one-time events, such as festivals and sporting events can be scheduled as congestion events that occur outside of normal traffic patterns. Scheduling congestion events is a highly proactive approach. 
While this scheduling technique is more proactive, it cannot adapt in real-time situations to rapidly changing and dynamic conditions within the RAN network. Unexpected changes in traffic patterns, for example, due to a cancelled event, can have unintended consequences. It may lead to poor QoE and low usage as the policies stay in effect. Similarly, unexpected emergencies may lead to a traffic surge and make the behavior of the network quite unpredictable. 
Real-Time Congestion Notification 
To address congestion events that occur outside of typical traffic patterns, a RAN monitoring platform or some other OSS feed can be integrated with the policy and charging rules function (PCRF) platform. This system notifies the PCRF when congestion occurs in the specific cells that are congested and when the specific subscriber is idle and using the congested cells. 
The RAN Congestion solution with Cisco Quantum™ Policy uses a real-time feedback loop that allows operators to continually examine and adjust network resources to deliver a consistent and tailored customer experience. This flow of real-time information and analysis allows operators to quickly adapt to the unpredictable demands of the data network. The continuous feedback loop is described in Figure 1:
© 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 6 of 10 
Figure 1. RAN Congestion Call Flow 
For subscribers located in or originating calls in congested cells, the PCRF pushes specific packages to the deep packet inspection (DPI) or Gateway GPRS Support Node (GGSN) to affect the subscriber’s session at the overall session level, at service-specific levels, or both if needed. For instance, taking into account criteria such as the subscriber’s plan, value, and churn risk, the PCRF may do a push to downgrade a subscriber’s speeds - or to block or squeeze video, peer-to-peer (P2P), and VoIP protocols. 
In an effort to prevent thrashing of cell sites into and out of congestion, PCRF applies congestion policies for an operator-configured time box, which should be greater than the reporting interval. The operator may elect to notify affected subscribers, through SMS, of the congestion levels or policies applied, to help up-sell subscribers to more high-value plans or to support customer care. This step allows amortization of existing services. 
The challenge is that no single-approach solution fits every network due to the fact that QoE can be subjective. QoE depends on several factors, including the number of subscribers attached to a cell site, subscriber usage, and network architecture and functionality. RAN Congestion solutions with Cisco Quantum Policy address all these considerations.
© 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 7 of 10 
Business Case Study 
Table 1 shows a business model of how a Tier 1 operator is affected by RAN congestion. The model estimates revenue loss in detail. It considers factors like maximum revenue generated by base transceiver station (BTS) per cell, network utilization percentage during normal and congested hours, and the number of congested sites and hours affected. The assumptions taken are near real world and have been seen at several deployment sites worldwide. However, all these parameters may vary from one operator to another. 
Table 1. Effects of RAN Congestion on a Tier 1 Operator Tier 1 - Use Case (in US$) Monthly revenue from 1 BTS with congestion $73,600 Monthly revenue from 1 BTS without congestion $76,000 Number of BTSs full coverage 100,000 Estimated number of congested BTSs 6,000 Estimated number of congested hours per month 75 Revenue loss saving per month $1,500,000 Revenue loss per year due to RAN congestion $18,000,000 
This example makes clear that RAN congestion is a significant issue for an operator. Failing to arrest congestion would directly affect subscriber QoE, which can create a ripple effect on the credibility of the operator, generate bad press, and reduce customer goodwill and retention. 
The economic effect of applying policy control to manage RAN congestion, rather than building more radio stations and adding backhaul links, can be significant. Managing revenue leakage from subscribers who are not able to access resources can also be substantial. Using the approach just discussed, it takes only a fraction of the capital expenditures (CapEx) to manage RAN congestion by policy management. Varying QoS for subscribers based on high and low packages is a more pragmatic approach to managing congestion in a cell, rather than imposing the same bandwidth and performance across all subscribers. 
RAN Congestion-Aware Solution with Cisco Quantum Policy 
The RAN congestion solution with Cisco Quantum Policy provides comprehensive static and dynamic data, which is used to inform and execute policy and configuration changes and to prioritize network resource allocation. Its real-time detection mechanism provides valuable insights about congested cells, including cells where the policy server had to take actions, as well as the effectiveness of the policy server actions. Flexible deployment options allow operators to implement the approach best suited to their particular network requirements. The platform can be deployed as a fully integrated, automated system that includes the following product IDs: 
● Policy Control Module 
● Quota Feature Pack 
● Unified Subscriber MGMT Module 
● Congestion Management Feature Pack
© 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 8 of 10 
Figure 2. Cisco Quantum Policy Architecture 
Figure 2 reflects the overall RAN congestion solution with Cisco Quantum Policy and shows how the Policy Control Module interfaces with the congestion probes and controllers in the RAN, as well as the DPI and DMI monitoring in the core IP network. This solution can also be deployed in conjunction with existing OSSs and performance management systems to manage congestion-time behavior. 
The platform’s main function include: 
● Tracking subscriber usage against fair-use policies and taking targeted actions against subscribers abusing fair-use policies 
● Reducing backhaul expansion as much as 10 to 20 percent, depending on various factors such as time and duration of congestion and type of policy applied 
● Allowing planners to model network changes and predict results, for proactive correction of trouble spots in the network through policy configuration 
● Promoting QoE during busy periods by helping to ensure that valuable activities and valued customers are treated well
© 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 9 of 10 
● Deferring CapEx through smarter policies 
● Managing congestion proactively, before problems occur 
● Tracking subscriber and network state for affected areas only (for example network or cell nodes) 
● Targeting cells for active management 
● Identifying subscribers and services likely to cause the congestion 
● Managing a balance between growth and investment 
Figure 3. RAN Congestion 
Advantages of Cisco Quantum Policy RAN Congestion Management 
Most-Deployed Policy Solution: With more than 70 installations, Cisco Quantum Policy Suite is a global leader with deployments in 3G/4G mobile, fixed broadband, and Wi-Fi offload. 
Fully Virtualized Platform: This design supports an order of magnitude more active sessions. 
Open Development Architecture: Policy and service creation can be up to ten times faster based on past customer deployments and optimized for third-party development and application integration. 
Integrated Policy, Online Charging, and Subscriber Profile Management: These capabilities enhance control, monetization, and personalization of new services.
© 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 10 of 10 
Summary 
Operators need solutions that help them solve today’s problems and still retain the flexibility to adapt as their businesses evolve. Cisco Quantum Policy Suite offers one of the industry’s most flexible policy platforms and, with the addition of our powerful congestion control, now delivers a full-featured RAN congestion management solution as well. 
Cisco Quantum Policy Suite is a leader in providing rapid, scalable, multiplatform innovation. It is our fifth- generation policy management platform and is designed to excel in the dynamic, high-performance, highly competitive world of mobile and broadband policy 2.0. 
For More Information 
The Cisco Quantum Policy Suite is comprised of five offerings including our Policy Control Module, Quota Feature Pack, Unified Subscriber MGMT Module, Congestion Management Feature Pack and additional modules - for unparalleled control, monetization, and personalization. 
Printed in USA C11-732919-00 10/14

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RAN Congestion Management: Meet the Challenges of Mobile Broadband with Cisco Quantum Policy

  • 1. White Paper RAN Congestion Management: Meet the Challenges of Mobile Broadband with Cisco Quantum Policy
  • 2. © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 2 of 10 Contents Introduction .............................................................................................................................................................. 4 Customer Challenges .............................................................................................................................................. 4 Resolving RAN Congestion .................................................................................................................................... 5 Business Case Study .............................................................................................................................................. 7 RAN Congestion-Aware Solution with Cisco Quantum Policy ............................................................................ 7 Advantages of Cisco Quantum Policy RAN Congestion Management ............................................................... 9 Summary ................................................................................................................................................................ 10 For More Information ............................................................................................................................................. 10
  • 3. © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 3 of 10 THE SPECIFICATIONS AND INFORMATION REGARDING THE PRODUCTS IN THIS MANUAL ARE SUBJECT TO CHANGE WITHOUT NOTICE. ALL STATEMENTS, INFORMATION, AND RECOMMENDATIONS IN THIS MANUAL ARE BELIEVED TO BE ACCURATE BUT ARE PRESENTED WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED. USERS MUST TAKE FULL RESPONSIBILITY FOR THEIR APPLICATION OF ANY PRODUCTS. THE SOFTWARE LICENSE AND LIMITED WARRANTY FOR THE ACCOMPANYING PRODUCT ARE SET FORTH IN THE INFORMATION PACKET THAT SHIPPED WITH THE PRODUCT AND ARE INCORPORATED HEREIN BY THIS REFERENCE. IF YOU ARE UNABLE TO LOCATE THE SOFTWARE LICENSE OR LIMITED WARRANTY, CONTACT YOUR CISCO REPRESENTATIVE FOR A COPY. The Cisco implementation of TCP header compression is an adaptation of a program developed by the University of California, Berkeley (UCB) as part of UCB’s public domain version of the UNIX operating system. All rights reserved. Copyright © 1981, Regents of the University of California. NOTWITHSTANDING ANY OTHER WARRANTY HEREIN, ALL DOCUMENT FILES AND SOFTWARE OF THESE SUPPLIERS ARE PROVIDED “AS IS” WITH ALL FAULTS. CISCO AND THE ABOVE-NAMED SUPPLIERS DISCLAIM ALL WARRANTIES, EXPRESSED OR IMPLIED, INCLUDING, WITHOUT LIMITATION, THOSE OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OR ARISING FROM A COURSE OF DEALING, USAGE, OR TRADE PRACTICE. IN NO EVENT SHALL CISCO OR ITS SUPPLIERS BE LIABLE FOR ANY INDIRECT, SPECIAL, CONSEQUENTIAL, OR INCIDENTAL DAMAGES, INCLUDING, WITHOUT LIMITATION, LOST PROFITS OR LOSS OR DAMAGE TO DATA ARISING OUT OF THE USE OR INABILITY TO USE THIS MANUAL, EVEN IF CISCO OR ITS SUPPLIERS HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. Cisco and the Cisco logo are trademarks or registered trademarks of Cisco and/or its affiliates in the U.S. and other countries. To view a list of Cisco trademarks, go to this URL: http://www.cisco.com/go/trademarks. Third- party trademarks mentioned are the property of their respective owners. The use of the word partner does not imply a partnership relationship between Cisco and any other company. (1110R). Any Internet Protocol (IP) addresses and phone numbers used in this document are not intended to be actual addresses and phone numbers. Any examples, command display output, network topology diagrams, and other figures included in the document are shown for illustrative purposes only. Any use of actual IP addresses or phone numbers in illustrative content is unintentional and coincidental. © 2014 Cisco Systems, Inc. All rights reserved.
  • 4. © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 4 of 10 Introduction Rapid growth in mobile data traffic is pushing networks to their limits, resulting in increased operator concerns about RAN congestion management in their networks - how to avoid it, and how to deal with it once it occurs. This ever-growing demand is driven by the popularity of multimedia handsets, smartphones, and mobile data card- enabled laptops. The popularity of tablets, such as the Apple iPad and Android-based devices, is expected to accelerate traffic growth further, especially mobile video. Mobile network service providers have traditionally addressed congestion by deploying additional capacity. However, it takes time to bring additional capacity online. With subscriber demand for new data applications and video traffic accelerating, simply adding bandwidth is not viable over the long term. Nor can service providers just slow traffic indiscriminately across the network without affecting users’ quality of experience, which is likely to increase churn. Adding to the challenges, network congestion often occurs in predictable busy hour times and locations. But it also flares up at unpredictable times and locations across the network. Service providers need more sophisticated solutions that can specifically target congested zones and intelligently take into account the subscribers and applications contributing most to the congestion. Customer Challenges RAN technologies, delivery architectures, and economics haven’t kept pace with customers’ increasing appetite for mobile broadband services. Techniques used by device manufacturers to optimize the customer experience, such as saving battery life, are severely affecting the signalling load and resources in the RAN. As more and more subscribers turn to data-intensive devices and applications, demands on the network increase. As a result, there is a growing gap between rising data traffic and revenue. And, as more subscribers connect from their desktop computers, mobile network congestion is increasing. This congestion strains network resources and bandwidth, negatively affecting subscribers’ quality of experience (QoE) and creating churn, because subscribers don’t remain loyal if service quality doesn’t meet their expectations. The dramatic rise in signalling congestion is largely attributable to increasing use of smartphones and tablets. A single smartphone can generate eight times the network signalling load of a laptop USB modem. Even in idle mode, the devices generate substantial signalling traffic, sending messages to keep in sync with the network, maintain status and location, and connect and reconnect. In addition, the increased resource usage of, mobile data services, devices, and applications are also largely responsible for congestion of these services: ● Streaming video ● Streaming audio ● Downloads and file sharing (peer to peer) ● Peer-to-peer video High-definition (HD) and 3D video busy-hour periods are also a significant contributor to congestion, because they vary from operator to operator and are now expanding in scope. Many operators are increasing network capacity or moving to Long Term Evolution (LTE) technology, with its increased bandwidth, to handle swelling traffic loads. However, these approaches need to be supplemented by other techniques that help address traffic growth, concentration, and signalling congestion in ways that are cost efficient and improve the customer experience. The Policy and Charging Control (PCC) architecture, as defined in 3GPP TS 23.203, provides features supporting traffic flow and network utilisation policy management and online and off-line charging.
  • 5. © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 5 of 10 Resolving RAN Congestion Adding capacity to the network to prevent peak-usage congestion, essentially over-provisioning the network, is not a cost-effective or practical answer, because RAN bandwidth is still very expensive compared to core network bandwidth. However, finding a solution to RAN congestion is critical to long-term success, because RAN congestion has a direct and immediate effect on QoE and ultimately on subscriber loyalty. A number of techniques can combat RAN congestion, including: ● Scheduled congestion zones ● Real-time congestion notification Scheduled Congestion Zones The Standard 3GPP PCC model provides an architectural approach which supports dynamic real-time monitoring, charging, and control of user sessions. However, more is needed to fully monetize the mobile network. Scheduled congestion zones refer to a preconfigured congestion schedule (by day of week, time of day, congestion times, location, and levels) to relieve the predictable congestion that occurs during busy hours. In addition, one-time events, such as festivals and sporting events can be scheduled as congestion events that occur outside of normal traffic patterns. Scheduling congestion events is a highly proactive approach. While this scheduling technique is more proactive, it cannot adapt in real-time situations to rapidly changing and dynamic conditions within the RAN network. Unexpected changes in traffic patterns, for example, due to a cancelled event, can have unintended consequences. It may lead to poor QoE and low usage as the policies stay in effect. Similarly, unexpected emergencies may lead to a traffic surge and make the behavior of the network quite unpredictable. Real-Time Congestion Notification To address congestion events that occur outside of typical traffic patterns, a RAN monitoring platform or some other OSS feed can be integrated with the policy and charging rules function (PCRF) platform. This system notifies the PCRF when congestion occurs in the specific cells that are congested and when the specific subscriber is idle and using the congested cells. The RAN Congestion solution with Cisco Quantum™ Policy uses a real-time feedback loop that allows operators to continually examine and adjust network resources to deliver a consistent and tailored customer experience. This flow of real-time information and analysis allows operators to quickly adapt to the unpredictable demands of the data network. The continuous feedback loop is described in Figure 1:
  • 6. © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 6 of 10 Figure 1. RAN Congestion Call Flow For subscribers located in or originating calls in congested cells, the PCRF pushes specific packages to the deep packet inspection (DPI) or Gateway GPRS Support Node (GGSN) to affect the subscriber’s session at the overall session level, at service-specific levels, or both if needed. For instance, taking into account criteria such as the subscriber’s plan, value, and churn risk, the PCRF may do a push to downgrade a subscriber’s speeds - or to block or squeeze video, peer-to-peer (P2P), and VoIP protocols. In an effort to prevent thrashing of cell sites into and out of congestion, PCRF applies congestion policies for an operator-configured time box, which should be greater than the reporting interval. The operator may elect to notify affected subscribers, through SMS, of the congestion levels or policies applied, to help up-sell subscribers to more high-value plans or to support customer care. This step allows amortization of existing services. The challenge is that no single-approach solution fits every network due to the fact that QoE can be subjective. QoE depends on several factors, including the number of subscribers attached to a cell site, subscriber usage, and network architecture and functionality. RAN Congestion solutions with Cisco Quantum Policy address all these considerations.
  • 7. © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 7 of 10 Business Case Study Table 1 shows a business model of how a Tier 1 operator is affected by RAN congestion. The model estimates revenue loss in detail. It considers factors like maximum revenue generated by base transceiver station (BTS) per cell, network utilization percentage during normal and congested hours, and the number of congested sites and hours affected. The assumptions taken are near real world and have been seen at several deployment sites worldwide. However, all these parameters may vary from one operator to another. Table 1. Effects of RAN Congestion on a Tier 1 Operator Tier 1 - Use Case (in US$) Monthly revenue from 1 BTS with congestion $73,600 Monthly revenue from 1 BTS without congestion $76,000 Number of BTSs full coverage 100,000 Estimated number of congested BTSs 6,000 Estimated number of congested hours per month 75 Revenue loss saving per month $1,500,000 Revenue loss per year due to RAN congestion $18,000,000 This example makes clear that RAN congestion is a significant issue for an operator. Failing to arrest congestion would directly affect subscriber QoE, which can create a ripple effect on the credibility of the operator, generate bad press, and reduce customer goodwill and retention. The economic effect of applying policy control to manage RAN congestion, rather than building more radio stations and adding backhaul links, can be significant. Managing revenue leakage from subscribers who are not able to access resources can also be substantial. Using the approach just discussed, it takes only a fraction of the capital expenditures (CapEx) to manage RAN congestion by policy management. Varying QoS for subscribers based on high and low packages is a more pragmatic approach to managing congestion in a cell, rather than imposing the same bandwidth and performance across all subscribers. RAN Congestion-Aware Solution with Cisco Quantum Policy The RAN congestion solution with Cisco Quantum Policy provides comprehensive static and dynamic data, which is used to inform and execute policy and configuration changes and to prioritize network resource allocation. Its real-time detection mechanism provides valuable insights about congested cells, including cells where the policy server had to take actions, as well as the effectiveness of the policy server actions. Flexible deployment options allow operators to implement the approach best suited to their particular network requirements. The platform can be deployed as a fully integrated, automated system that includes the following product IDs: ● Policy Control Module ● Quota Feature Pack ● Unified Subscriber MGMT Module ● Congestion Management Feature Pack
  • 8. © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 8 of 10 Figure 2. Cisco Quantum Policy Architecture Figure 2 reflects the overall RAN congestion solution with Cisco Quantum Policy and shows how the Policy Control Module interfaces with the congestion probes and controllers in the RAN, as well as the DPI and DMI monitoring in the core IP network. This solution can also be deployed in conjunction with existing OSSs and performance management systems to manage congestion-time behavior. The platform’s main function include: ● Tracking subscriber usage against fair-use policies and taking targeted actions against subscribers abusing fair-use policies ● Reducing backhaul expansion as much as 10 to 20 percent, depending on various factors such as time and duration of congestion and type of policy applied ● Allowing planners to model network changes and predict results, for proactive correction of trouble spots in the network through policy configuration ● Promoting QoE during busy periods by helping to ensure that valuable activities and valued customers are treated well
  • 9. © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 9 of 10 ● Deferring CapEx through smarter policies ● Managing congestion proactively, before problems occur ● Tracking subscriber and network state for affected areas only (for example network or cell nodes) ● Targeting cells for active management ● Identifying subscribers and services likely to cause the congestion ● Managing a balance between growth and investment Figure 3. RAN Congestion Advantages of Cisco Quantum Policy RAN Congestion Management Most-Deployed Policy Solution: With more than 70 installations, Cisco Quantum Policy Suite is a global leader with deployments in 3G/4G mobile, fixed broadband, and Wi-Fi offload. Fully Virtualized Platform: This design supports an order of magnitude more active sessions. Open Development Architecture: Policy and service creation can be up to ten times faster based on past customer deployments and optimized for third-party development and application integration. Integrated Policy, Online Charging, and Subscriber Profile Management: These capabilities enhance control, monetization, and personalization of new services.
  • 10. © 2014 Cisco and/or its affiliates. All rights reserved. This document is Cisco Public Information. Page 10 of 10 Summary Operators need solutions that help them solve today’s problems and still retain the flexibility to adapt as their businesses evolve. Cisco Quantum Policy Suite offers one of the industry’s most flexible policy platforms and, with the addition of our powerful congestion control, now delivers a full-featured RAN congestion management solution as well. Cisco Quantum Policy Suite is a leader in providing rapid, scalable, multiplatform innovation. It is our fifth- generation policy management platform and is designed to excel in the dynamic, high-performance, highly competitive world of mobile and broadband policy 2.0. For More Information The Cisco Quantum Policy Suite is comprised of five offerings including our Policy Control Module, Quota Feature Pack, Unified Subscriber MGMT Module, Congestion Management Feature Pack and additional modules - for unparalleled control, monetization, and personalization. Printed in USA C11-732919-00 10/14