Cellular systems by nature have finite resources. Radio spectrum and transport, or backhaul resources are limited, expensive and shared between many users and services. Today’s mobile broadband networks must support multiplay applications of voice, video and data on a single IP-based infrastructure. However, these converged services each have unique traffic handling and quality of experience (QoE) requirements. Such issues cannot be economically solved through over-provisioning but through efficient partitioning of the available wireless network resources.
Granularly controlling service quality is critical to establishing new business models and monetizing services. The 3rd Generation Partnership Project (3GPP)policy and charging control (PCC) is the heart of the Evolved Packet Core (EPC), and ensures user QoE for a particular subscription and service type. As networks continue to evolve, policy management will play a fundamental role in implementing QoS in mobile broadband. By applying operator-defined rules for resource allocation and network usage, policy management will be critical in two closely related areas:
* Enhancing service quality by limiting network congestion
* Monetizing services.
Using Policy Management and QoS to Manage Congestion and Control Service QualityEven if mobile operators significantly increase capacity, certain applications such as peer-to-peer (P2P) services and video will eventually consume any excess bandwidth. Providing high service quality by over-provisioning network capacity can also eventually leave an operator at a competitive disadvantage to other operators that provide the same or better quality service at a lower cost.
By implementing a solid policy strategy, network performance is maintained during peak traffic times and spikes in user demand – saving the operator from carrying any excess capacity. In addition, policy management allows operators to granularly control the availability and QoE of different services. Policy is primarily used to dynamically allocate network resources. For example, policy rules control the priority, packet delay and acceptable loss of video packets in order for the network to treat the video call in a particular manner.
In other cases, policy rules are used to limit traffic rates on the network in order to curb network abusers and provide fair use – preventing one user from negatively impacting the quality of another service. For example,P2P services can consume a disproportional amount of network resources and negatively impact the network’s ability to establish and maintain real-time service quality.
Policy Management’s Role in New Business Models for Service MonetizationWith the emergence of smart devices, such as smartphones and tablets, the line between who provides value to the subscriber and who the subscriber pays has blurred. Operators are at greater risk of becoming bit transporters, while content and application providers as well as device manufacturers capture more revenue from mobile subscribers. Policy management is one method operators can implement to form new business models and maximize service monetization.
Policy management can also be taken a step further by offering tiered service levels which can guarantee higher performance and quality to higher paying subscribers; for instance, corporate accounts. Dynamic policy management allows providers to “put a coin slot in front of the customer.” By improving the content delivery quality for fixed periods, policy control supports subscribers’ impulse buying of premium services. For example, a subscriber can upgrade their service for a fixed period of time to watch a video in high definition.
Service Quality Validation for Mobile BroadbandService quality validation allows operators to evaluate networking devices, and proactively measure their QoS and policy management functions. The fundamental strategy is to test the mobile data network with the traffic types and traffic mixes that closely resemble the real services operators will deploy. Service quality and policy/QoS schemes are only stressed when a network encounters congestion. The test approach should involve fully loading the device or network under test. After a network is fully loaded with a broad mix of real traffic services, detailed QoE measurements are made to quantify network performance.
Key Performance Indicators for QoE in Multiplay Wireless NetworksQuantitatively measuring QoE requires an understanding of the key performance indicators (KPI) that impact users’ perception of quality. KPIs are unique by service type so each service type such as conversational video, voice, and internet browsing, have unique performance indicators that must be independently measured.
To fully understand QoE, KPIs must be evaluated over time at varying load rates and application mixes. Policy and QoS mechanisms must be judged when a network is fully loaded, and there are competing demands for network resources. Only under these conditions can the effectiveness of rate limiting/policing, packet shaping, resource scheduling, and packet delay budgets be thoroughly analyzed.
Summing It UpMobile subscriber modeling and multiplay service emulation are a fundamental part of measuring QoS, policy mechanisms and QoE. Policy testing is a mission critical technique that allows equipment vendors and mobile operators to measure today’s network and device performance, as well as adapt to new services and capabilities in evolving mobile data networks.
Joe Zeto serves as a technical marketing evangelist within Ixia’s marketing organization. He has over 17 years of experience in wireless and IP networking, both from the engineering and marketing sides. Joe has extensive knowledge and a global prospective of the networking market and the test and measurement industry. Prior to joining Ixia, Joe was Director of Product Marketing at Spirent Communications running Enterprise Switching, Storage Networking, and Wireless Infrastructure product lines. Joe has a Juris Doctorate from Loyola Law School, Los Angeles, Calif.