Mobile network operators face significant challenges when it comes to providing network quality and capacity in areas of high demand. To solve this, operators have a number of options at their disposal, including carrier aggregation, installation of additional sites, or deploying new spectrum. While 5G is a potential solution to adding capacity, in many countries 5G auctions have been delayed due to Covid-19 (among other issues); where spectrum is available, it has been deployed only for early adopters in cities and for marketing claims. Moreover, the commercial benefits of 5G are still unclear and this has led to much slower deployment in some countries than anticipated.
In recent years another option has come to the fore: spectrum refarming. In this approach, currently utilized spectrum is repurposed for a new technology. Frequencies associated with 2G and 3G can be reused for LTE, providing extra capacity and potentially other benefits such as better propagation. While it might be easy to assume 2G is the first victim in this process, it is largely protected (at least for the time being) by the requirements set by many regulators to ensure minimum voice call coverage across a country. As a result, many operators are considering reusing 3G spectrum, allowing them to use 3G spectrum in 4G deployments.
However, it’s not as simple as flicking a switch – refarming takes time, and operators need to be strategic in how they approach high priority areas, as well as understanding the impact that removing the 3G network may have. One way to look at this is to examine areas where a 4G network exists, but devices still spend significant portions of time on 3G. This could indicate that 4G radios are currently unable to provide good indoor performance, or there may be significant noise, which operators will need to mitigate in the refarm process to upgrade the quality of experience in these areas.
To help operators do just this, Tutela has analyzed its vast crowdsourced dataset using a unique approach to highlight areas where 3G usage is particularly high in markets where 4G is present. In this example, we will look at an operator in Paris, France.
At a city-wide level, the algorithm visually highlights clusters of high-3G usage areas – continuous areas where devices spend a high proportion of time on 3G, which likely warrant further investigation.
From here, we can zoom into a target area to explore this further. In this instance, we’ve focused on one of the highlighted clusters in the 10th Arrondissement. This turns out to be a hospital, which is a common location for this type of network problem. The platform also tells us that, despite there being a 4G signal in the area, users are spending about 67% of their time on 3G.
We can also look at the amount of time high 3G usage has been occurring for. In this case, we see that in the majority of highlighted areas, the problem has persisted for over six months, making it all the more important to fix sooner rather than later.
Evidently, operators seeking to refarm spectrum in the long run will need to tackle these problems before turning off equipment that is actively serving users with no other recourse for coverage. Combining crowdsourced insights from actual user equipment with state-of-the-art analysis tools can help engineering teams to address these problems efficiently and tactically, paving the way for strategic improvements in the long run.