Preparing for mobile data growth and network congestion
By Joseph Zeto
As part of supporting the massive global growth in mobile data 
subscribers and traffic, today’s mobile broadband networks must carry multiplay services that share radio access and core network resources, as well as support delay-sensitive, real-time services. Making it even more challenging is that all services have their own unique Quality of Service (QoS) specifications in terms of packet delay tolerance, acceptable packet loss rates, and required minimum bit rates. So as mobile networks continue to cross over to high-speed, IP-based infrastructure, the wireless industry is actively creating and implementing QoS and policy management to provide these high-quality services that consumers demand, while simultaneously adding network capacity.
In order to do so, policies are being created to establish application quality, giving operators the ability to present individualized services to users and manage network congestion. These “rules” also help to compensate operators who have invested significant funds toward building out new networks. Policy management is defined as the process of applying operator-defined rules for resource allocation and network use and plays a crucial role in QoS implementation of mobile broadband. And as this area continues to grow and develop, policy management is critical to three closely-related areas – limiting and managing network congestion, monetizing services and enhancing service quality.
Strengthening Service Quality and Limiting Network Congestion
It is a well-known fact that mobile operators are limited by a finite amount of resources and capital. As network congestion becomes increasingly problematic and expectations for premium QoS and Quality of Experience (QoE) rise, operators need to find innovative solutions to address these issues.
Adding transmission lines, fatter pipes and improving efficiency are accepted and reliable counteractions to network congestion. Unfortunately, these options are better suited for wired networks than for wireless networks. While increasing capacity with additional spectrum and improving spectrum efficiency are important, capacity improvements alone will not solve this complex challenge.
Policy rules could be used to curb traffic rates on the network in order to control network abusers and provide fair use – impeding one user from having a detrimental impact on the quality of another service. For example, Peer-to-Peer (P2P) file sharing is a bandwidth-intensive, non-real-time service. If left without any type of management, P2P services have the potential to consume an excessive amount of network resources and adversely impact the network’s ability to establish and maintain real-time service quality.
Providing high service quality by over-provisioning network capacity is the most obvious answer to the QoS predicament, but unfortunately, it is the least likely to work in the long run. Over time, this option will leave an operator at a competitive disadvantage to providers who offer the same or better QoS at a lower cost. A better option is to have policy management that characterizes and discerns services (applications) and subscriber types, and then controls the Quality of Experience (QoE) of each type. A combination of judicious management policies along with other strategies such as cellular offload with Wi-Fi, implementation of small cells, and demand calibration can better satisfy consumers’ demand for multiplay services.
With strong policy management, operators will be given the reigns to manage the availability and QoE of different services. These policies will be used to dynamically allocate network resources – for example, a particular bandwidth can be reserved in the radio base station and core network to support a live video conversation. Policy rules can also control the priority, packet delay and the acceptable loss of video packets in order for the network to treat the video call in a particular manner.
Building An Adaptive Business Model for the Monetization of New Services
The development of smart devices has created a new obstacle for wireless operators – how to monetize the new services they provide. When voice-only services functioned as end-to-end services, operators were able to acquire the majority of the customers’ mindshare and service revenue. Now that content/application providers are becoming more popular (and taking away profit), wireless operators are filling the role of bit transporters which means that there is an uncertainty over who provides value to the subscriber and who the subscribers pays.
