Is it possible to estimate broadband coverage potential for new technologies? I’ve blogged many times about the effect of “demand density” (roughly, a measure of how many opportunity dollars a mile of infrastructure would pass) on the economics of broadband. Where demand density is high, it’s possible to deliver broadband using things like FTTH because cost/opportunity ratios are favorable. Where it’s low, cost has to be ruthlessly constrained to get coverage, or subsidies are needed.
We know from experience that, using my metrics for demand density, an average density of about 4.0 will permit quality broadband under “natural market” conditions for at least 90% of households. Where demand density falls to about 2.0, “thin” areas, meaning low populations and economic power, will be difficult to support profitably, so penetration of broadband is likely to fall below 80%, and at densities approaching 1.0, penetration will fall to 70% or less without special measures.
The characteristics of wireline infrastructure are usually the limiting factor here. If broadband deployment costs were very low, then a low economic value passed per mile of infrastructure would still create a reasonable ROI. Obviously, running any form of physical media to homes and businesses, even with a hierarchy of aggregation points, is going to be more costly where prospective customers are widely distributed. Almost all urban areas could be served with wireline broadband, where most deep-rural areas (household densities of less than 5 households per square mile) would be difficult to serve unless the service value per household was quite high.
Public policy is almost certainly not going to permit operators to cherry-pick these low-density areas based on potential revenue, but that would be difficult in any case because the revenue that could be earned per household depends on the services the household would likely consume.
What is the service value of a household? Here we have to be careful, because an increasing percentage of the total online service dollars spent per household don’t go to the provider of broadband access. An example is that many households who used to spend around $150 per month on TV, phone, and Internet, have dropped everything but Internet and now spend less than $70 per month. Sure, they may get Hulu and even a live TV streaming service, and spend another $70 or even more, but the broadband operator doesn’t get that.
Generally, the preferred relationship for broadband in US markets seems to be a household revenue stream (all services monthly bill) that’s roughly equal to one third of the combination of pass cost (per-household neighborhood wiring) plus connect cost. Today, average pass costs run roughly $250 and average connect costs roughly $200, for a total of $450. That would mean a household revenue stream of $150 is needed, on the average.
In US urban and suburban areas, it’s getting more difficult to hit that monthly revenue target, but it’s still largely possible. Household densities even in the suburbs tend to run between 300 and 600 households per square mile, which is usually ample to support profitable broadband. As you move into rural areas, though, household densities fall to an average of less than 100 per square mile, down to (as previously noted) as little as 5 or less.
Wireline infrastructure is rarely able to deliver suitable ROI below densities of 150 households per square mile. Even in higher household densities, as many as 500 or more, it’s often necessary today for developers to either share costs or promise exclusivity to induce broadband providers to offer quality infrastructure for new subdivisions.
5G millimeter wave, just beginning to deploy, is typically based on a combination of short-haul 5G and fiber-to-the-node (FTTN). The overall cost will depend in large part on whether there are suitable node points where there’s either already fiber available or where fiber can be introduced at reasonable costs. Operators tell me that they believe that, on the average, it should be possible to serve household densities of between 100 and 200 per square mile with monthly revenues of $120 or more per household, since self-installation is a practical option here. This would cover a slightly broader swath of low-density suburbs to high-density rural.
The problem here is that 5G/FTTN tends to support demand densities of somewhere in the 2.5-3.5 range, which is better than the 4.0 lower limit for traditional technologies but still far too high to address many countries and most rural areas. For that, the only solution is to rely on cellular technologies with greater range.
Studies worldwide suggest that 5G in traditional cellular form (macrocells in low-density areas, moving to smaller cells in suburbs and cities) could deliver 25 Mbps to 35 Mbps per household at acceptable ROIs, and many operators and vendors say that these numbers could probably be doubled through careful site placement and RF engineering. My models suggest that using traditional 5G, it would be possible to support demand densities down to as low as 0.8, without any special government support.
The “would be possible” qualifier is important here, and so is the 0.8 demand density floor. The “possible” issue relates to the fact that while it’s possible to hit minimal ROI targets on demand densities below 1.0, it’s not clear whether minimal ROI could actually get anyone interested in deployment. With every operator chasing revenue, many leaving their traditional territories to seek opportunities half a world away, would they flock to rural areas? Maybe not.
With respect to the 0.8 limit, the problem is that there are a lot of areas that fall well below that. In the US, there are 18 states with demand densities below that limit, and that’s entire states. Within well over 80% of states there are areas with demand densities below 0.8. Does this mean that even in the US, widespread issues with broadband quality are inevitable without government support? Yes. Does it mean the support has to be direct subsidization? Perhaps not.
You can swing the ROI upward by lowering the cost of infrastructure. The biggest cost factors in the use of 5G (in either form) as a means of improving broadband service to low-demand-density areas are the spectrum costs and cost of providing fiber connections to cell towers and nodes. Both these costs could be reduced by government programs. For example, governments could provide 5G spectrum at low/no cost to those who would offer wireline-substitute broadband at 40 Mbps or more, and they could trench fiber along all public routes, when any construction is underway, then offer fiber capacity under the same terms.
This could be an alternative to direct subsidies. I’ve not been able to model the impact of the approach, because there are so many country-specific variables and low-level data on population and economic density isn’t always available, but it would appear from my efforts that it could pull over 90% of the US into a zone where ROIs on even rural broadband could be reasonable, enough to make it possible for existing wireless operators at least to serve rural areas profitably.