Operators of 4G-LTE cellular data networks face an uphill battle against rapidly increasing data usage and declining ARPU. Increased sales of iPhones, Android smartphones, tablets, and notebooks with embedded 3G/4G capabilities are all taxing the macro networks for scarce capacity resources. This exponential growth of data traffic is forcing operators to evaluate mid to long term migration strategies to LTE while in need of short term strategies to relieve their congested macro networks. On top of these clear and present dangers to the day-to-day operations of the network, operators are faced with increased scrutiny from shareholders to prove that a pure LTE overlay deployment will provide a positive ROI as well as an improved customer experience.
One method that is getting the most attention for managing the mobile data tsunami is Wi-Fi Offloading. Recent market research indicates that even though very few dedicated carrier Wi-Fi offload networks exist, a lot of data traffic is already being offloaded to existing private and public Wi-Fi networks in homes, at work, and public hotspots. Research companies Comscore and Heavy Reading estimate that between 20%-80% of smartphone mobile data traffic traverses these private/public Wi-Fi networks. Several network equipment vendors are rushing to develop carrier-grade Wi-Fi infrastructure solutions, while MNOs are analyzing how to integrate Wi-Fi capabilities into their networks in order to offload data traffic from their primary 3G/4G network. But there has been a lack of analysis to examine where, when, and if using Wi-Fi offload helps an operator’s business case.
Wireless 20|20 conducted an analysis of two 4G-LTE deployments and examined the impact of Wi-Fi offloading, one in the dense urban market of New York City and the second case in San Diego with less population density. This analysis highlights the difference in the impact of a Wi-Fi offload network on the business case in a large dense urban market versus a midsized urban market. Although both markets would benefit from implementing a carrier Wi-Fi offload network, the economic impact on the business case, and the optimum configuration for the Wi-Fi network varied dramatically. Using the WiROI™ Tool, operators can pinpoint the combination of coverage and density of access points (APs) that will provide the maximum ROI.
The key findings from these analyses show that OpEx related costs, such as the monthly site rental and backhaul expenses, determine the viability of a Wi-Fi offload network. The New York and San Diego analyses conclude that a Wi-Fi offload network with OpEx less than $40 per month per access point is highly attractive, but if monthly OpEx per AP exceeds $100, the business case becomes challenging. The case studies have shown that the most critical parameters of the business case are the assumptions around OpEx for the Wi-Fi offload network. Therefore, it is important to achieve the right balance of the Wi-Fi coverage area and the density of APs in order to offload the optimum amount of traffic while maintaining or improving the user experience. Implementing too few access points could result in not capturing enough data traffic. On the other hand, implementing too many access points per square kilometer could increase OpEx significantly and drive the business case into negative ROI.
In a dense urban environment with a high traffic profile, such as New York City, Wi-Fi Offload is optimal at 100% coverage with a density of 42 APs per square kilometer, but a significant TCO reduction and positive ROI can be realized with as little as 20% coverage and a density of 24 APs per square kilometer.
By deploying a Wi-Fi offload network at this optimal balance between coverage and density, the operator would reduce the number of macro LTE capacity sites from 1,879 to 432, a saving of 1,447 LTE sites. In financial terms, this translates into a cumulative TCO savings of over $250M, a significant 7.2% reduction in the TCO over ten years. Cumulative cash flow is improved by 4.3% or $287 million over a 10-year period.
Analyzing the numbers further, the cumulative CapEx is reduced by 44.7%, or $230 million, while the cumulative OpEx reduction is a moderate 0.9%, or $23 million over the ten year period. It should be noted that in the New York case, a very dense urban area, an operator would start to see significant TCO improvement at 20% Wi-Fi coverage, leaving the operator great flexibility in its Wi-Fi offload network implementation.