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Reducing Wireless Network CAPEX through Streamlined Planning

By: Bernard Breton, Cyril Doussau

Perhaps the two greatest challenges that today’s mobile network operators (MNOs) face are the drastic increase in over-the-top (OTT) service usage and the constant changes in subscribers’ behaviors. We also live in a hyperconnected world in which mobile applications and services are expected to be constantly available and perform seamlessly, making it critical for MNOs to optimize network resources and streamline the buildout of additional capacity.

Additional capacity is available in the form of several network-technology migrations, including that of TDM to Ethernet in MNOs’ backhaul, 2G and 3G to LTE and LTE Advanced in their radio access networks (RANs), and the deployment of small cells and Wi-Fi offload to release traffic pressure on their wireless networks. While these new technologies are lowering the cost of transporting voice and data, it also means networks are becoming more complex, leaving MNOs with yet another challenge, namely keeping operating expenditures (OPEX) down while managing multiple technology evolutions in parallel.

So, what we have are two challenges inextricably linked to one another: MNOs need to optimize the planning and management of additional capacity buildouts, and the new technology deployments have to be handled in a way that doesn’t cause OPEX to skyrocket. The first step in accomplishing both of these goals is to address the issue of stranded capacity—that is, existing network capacity that goes unused, albeit unintentionally. While network self-optimization techniques can be employed to lower OPEX to a certain degree, streamlining the planning process to begin with is the key to reducing stranded capacity and realizing the true benefits and cost savings of new technology deployments.

Market saturation is preventing most MNOs from growing their subscriber bases. Because the quality of network coverage is the primary criteria by which subscribers choose service providers, MNOs are in fierce competition to launch new services, and are actively looking to combat churn by improving network coverage and performance. When you combine the investments needed to retain customers and the capital expenditures (CAPEX) required to roll out the latest technology upgrades while factoring in dwindling ARPU numbers (average revenue per user)—an anticipated annual decline of 5 to 15 percent through 2017—it’s abundantly clear that MNOs need to embrace new strategies to protect their margins.

In its May 2013 white paper “Optimization Automation: Immediate Gains for Today, SON Enabler for the Future,” the research firm Analysys Mason indicates that as much as 5 percent of any given MNO’s network capacity is stranded, demonstrating that opportunities do exist for MNOs to rightsize capacity by improving their planning process, thereby increasing their margins.

But how can an MNO improve the accuracy of its network planning if it has to depend on outdated information? Planning and optimization teams often rely on network-usage information that can take weeks to be produced by transport or service-quality departments; by the time it’s made available, traffic patterns are likely to have already changed. What good is spending money to add more capacity if it’s being deployed in the wrong part of the network?

What’s more, rolling out new network technologies can take several years to complete, meaning MNOs find themselves having to manage and optimize several networks in parallel while relying on that outdated usage information. Such complexity makes network management more costly than ever, and automated network-optimization techniques represent the best bet for recovering stranded capacity and reducing both CAPEX and OPEX. According to Analysys Mason, automated network optimization and advanced network planning can recover between 20 and 40 percent of that stranded capacity, providing much-needed relief to those aforementioned margins.



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