Blog | Optimizing telco networks through intelligent automation

Share on facebook
Share on twitter
Share on linkedin
Share on email

By Jim Lim Amdocs_Jim Lim Telco providers face multiple challenges in today?s hyper-connected world such as enhancing the use of radio resources, simplifying network management, and reducing the total cost of ownership. To address these challenges, self-optimizing network (SON) is one of the most valuable and promising technologies. Large leap in wireless data usage Mobile devices such as smartphones or tablets are fostering the explosive growth in wireless data usage, this has led mobile data traffic to grow exponentially in the past few years. By 2019, it is expected that in Asia Pacific, mobile data traffic will reach 9.5 exabytes per month up from 977.4 petabytes per month in 2014. This resonates with the internet growth in the Philippines. In a short span of a year and a half (June 2013 and December 2014), over six million Filipino mobile Internet users were activated. Intense competition among device manufacturers, proliferation of local smartphone vendors, as well as promotion bundles and free offerings from mobile carriers will only further propel this growth. Telco providers, therefore, must efficiently optimize their radio access networks (RANs) to support a growing number of higher-bandwidth data applications and provide advanced services, while simultaneously ensuring they?re delivering the optimal user experience. Using SON to maximize network resources While LTE wireless access technology was welcomed as a means to address a growing data capacity crunch, it also contributes to the problem. An always available and speedier access to mobile applications means more people are increasingly going wireless. At the same time, data throughput per user is growing, revenue per megabyte is dropping so rapidly that these gains are unable to help operators compensate for the lost revenue. Consequently, mobile operators are increasing their focus on operational cost reduction through the capabilities of SON, as well as to help them manage the surge of network traffic. The prevalence of multi-technology architectures ? with 2G, 3G, LTE, and Wi-Fi technologies operating in parallel ? also pose significant operational and network complexity. Heterogeneous Networks (HetNets) place increasing demands on service providers? networks and their operational staff because they are required to manage the complexity of overlaid and inter-related networks ? a task that is virtually impossible to do manually. To ensure quality of experience (QoE), more complex quality of service (QoS) and policy implementations are required, while at the same time increasing network throughput in response to the rapid growth in wireless data usage. Rather than spending millions extending their network with new sites and carriers, telcos can save money and time by maximizing the capacity they already have. Mobility load balancing (MLB) is the self-optimization feature of SON that shifts loads from capacity-restricted resource to cells with free capacity. MLB provides automatic modification of admission and congestion control parameters. This functionality allows telcos to effectively grow and improve the reliability and capacity of their radio resources, while minimizing further infrastructure investments until it?s more cost effective or unavoidable. By automating coverage and capacity allocation, the RAN becomes much more dynamic and efficient, helping to contain operational expenditures (OPEX) by increasing network efficiency and contributing to revenue growth. SON is able to offer a more consistent, high-quality user experience through monitoring and automatically addressing the causes of network degradation. By identifying recurring network congestion and automatically applying solutions in a proactive manner, MNOs are able to limit performance degradation, prevent recurring network issues and enhance QoE through dynamic capacity allocation. Zero-touch approach to network optimization In traditional mobile infrastructures, network elements and associated parameters are manually configured. Planning, commissioning, configuration, integration, and management of these parameters are essential for efficient and reliable network operation. However, the operational costs are significant and the manual process is both time consuming and prone to human error. The result is sub-optimal network performance. SON minimizes the need for human intervention and delivers cost efficiency in network management. Automatic neighbor relation (ANR) — one of the primary drivers of SON deployments will relieve operators of the burden of manually managing neighbor cell relations. By removing the need for engineers to be deployed to a site to provision and configure cells, it is possible to achieve the supplementary OPEX savings that operators want and eliminate any opportunity for human error. Automation is not a new concept in network management. Service provider networks already depend on the extensive use of automated processes. For instance, the area of radio resource management (scheduling, power and rate control, etc.), demonstrates that automated features perform well. The introduction of SON represents a continuation of the natural evolution of wireless networks, where automated processes are simply extending their scope deeper into the network. There are other varying drivers compelling operators to reach a truly zero-touch network but the common denominator is the benefits offered by SON capabilities. These include increased network performance, a better end-user experience and an increase in network capacity and network quality. For the bottomline, it also means reduced operational expenditures and preventable investments in network upgrades. The author is the client business executive for Amdocs Philippines ]]>

Latest Posts