TCO of DOCSIS® Network XHaul vs. Fiber BackHaul: How DOCSIS Networks Triumph in the Indoor Use Case

TCO of DOCSIS® Network XHaul vs. Fiber BackHaul

Shahed Mazumder
Principal Strategist, Wireless Technologies

Joey Padden
Distinguished Technologist, Wireless Technologies

Jennifer Andreoli-Fang
Distinguished Technologist, Wireless Technologies

Dec 12, 2018

In our recently published blog post, we demonstrated why indoor femtocells have reemerged as an attractive deployment model. In particular, indoor network densification has huge potential for converged cable/wireless operators who can leverage their existing Hybrid Fiber Coax (HFC) footprint to either backhaul from full-stack femtocells or fronthaul from virtual Radio Access Network (vRAN) remote radio units.

In the second blog in our series, we shift the focus from system level benefits to making the business case. As we walk through our TCO model, we will show a 40% to 50% reduction in Total Cost of Ownership (TCO) for an indoor deployment model served by DOCSIS networks compared to a more traditional outdoor deployment served by fiber. Yeah, that is big, so let’s break down how we got there.

Why DOCSIS Networks?

Before jumping into the TCO discussion, let’s revisit the key motivations for using DOCSIS networks as a tool for mobile deployments:

  • Broad-based availability: In a Technical Paper prepared for SCTE-ISBE 2018 Fall Technical Forum, a major Canadian MSO pointed out that there typically is 3~5X more coax cable than fiber in its major metro markets. In the US too, per FCC’s June 2017 statistics, nation-wide cable Household Passed (HHP) stands at 85% (115M units), whereas fiber HHP stands at 29% (39M units)
  • Gigabit footprint: As of June 2018, over 63% of US homes have access to gigabit service over cable. In other markets cable operators are pushing ahead with gigabit buildout as well
  • Ease of site acquisition: No permitting, no make ready, limited installation effort.
  • Evolving mobile-friendly technology: Ranging from latency optimization to timing/synchronization techniques and vRAN support for non-ideal fronthaul links like DOCSIS networks.

Scenarios We Looked At

For TCO comparison, we looked at the following 3 deployment scenarios:

Scenario 1: Outdoor small cell served by leased fiber backhaul

Scenario 1

This is the traditional solution for deploying small cells. For our TCO model, we treated this as the baseline.

Scenario 2: Indoor femtocell/home eNodeB served by residential/SMB DOCSIS network links as backhaul.

Scenario 2

In this scenario, we modeled the deployment of a full-stack femtocell in residential customer homes and small to medium businesses (SMB) served by the converged operator’s DOCSIS network. A converged operator here refers to a cable operator that deploys both DOCSIS network and mobile networks.

Scenario 3: Indoor vRAN Remote Radio Unit (RRU) served by residential/SMB DOCSIS network links as fronthaul

Scenario 3

Scenario 3 is essentially scenario 2 but using vRAN. In this case, the virtual base band unit (vBBU) could be deployed on general purpose processors (GPP) servers in the distribution hub site with low-cost radio units deployed in DOCSIS gateways at the customer premise, or SMB location.

Apples to Apples

To build the TCO model, we start with a representative suburban/urban area we want to model. In our case, we used a 100 sq. km area with a total of 290k households (HH). At 2.4People/HH (the US average), our modeled area covered roughly 700K people.

Next, we considered that this area is already served by 10 outdoor macrocells, but the operator needs to boost capacity through network densification.

Under Scenario 1, the operator deploys 640 outdoor small cells that cut existing macro cells’ traffic load by half and boost the spectral efficiency (and therefore capacity) across the network. To create an apples-to-apples comparison of system capacity under all three scenarios, we applied the concept of normalized spectral efficiency (SE) and kept that consistent across the three scenarios. For SE normalization, we added up weighted SE for different combinations of Radio Location-User Location (e.g. In-In, Out-Out, Out-In) in each scenario.

In the end, we used the normalized SE to find the appropriate scale for each scenario to achieve the same result at the system level, i.e. how many femtocells/vRAN radios will be required in indoor scenarios (2 & 3) so the system capacity gain is comparable to the traditional deployment in scenario 1.

Work Smarter, Not Harder

Crucially, converged operators know who their heavy cellular data users are and among them, who consistently use the network during non-business hours, i.e., most likely from their residences. As an example, a CableLabs member shared empirical data showing that the top 5% of their users consume between 25%~40% of overall cellular network capacity on a monthly basis.

So as a converged operator, if you want to prevent at least 25% of network traffic from traversing through walls, you can proactively distribute home femtocells or RRUs to only the top 5% of your users (assuming their entire consumption happens indoor).

In our model, we used the following approach to get the scale of indoor deployment for scenarios 2 and 3:

Figure-A: Determining Scale of Deployment for Indoor Use Cases

Figure-A: Determining Scale of Deployment for Indoor Use Cases

Therefore, theoretically, if only 2.5% of subscribers start using indoor cellular resources, we can achieve the same SE improvement in scenarios 2 and 3, as observed under scenario 1’s fiber outdoor deployment.

However, we know assuming 100% of heavy users traffic is consumed at home or indoors is unrealistic. To account for a combination of real-world factors including that indoor doesn’t mean only at your residences, that some of those heavy user locations may not be serviceable by a DOCSIS network, and/or some users may opt out from using a home femtocell/RRU we boosted that percentage of the subscriber base we modeled using femtocell/RRU deployments to 12.5% (or roughly 35K units) to make sure that we can definitely capture at least 12.5% of cellular traffic in scenario 2 and 3.

Our Analysis and Key Takeaways

For the TCO model assumptions, we gathered a wide range of input from a number of CableLabs operators and vendors. In addition, we validated our key assumptions with quite a few Telecom Infra Project (TIP) vRAN fronthaul project group’s members.

Though configurable in our model, our default TCO term is 7 years. Also, we calculated the TCO per user passed and focused on the relative difference among scenarios to de-emphasis the overall cost (in dollars), which will differ by markets, the scale of deployment and supplier dynamics among other things.

Figure-B: Summary of 7-Yr. TCOs across 3 Deployment Scenarios

Figure-B: Summary of 7-Yr. TCOs across 3 Deployment Scenarios

According to our base case assumptions, we see the following:

  • TCO in scenarios 2 and 3 can be around 40%~50% cheaper than the TCO in scenario 1.
  • For scenario 1, Opex stands out as it involves large fees associated with outdoor small cell site lease and fiber backhaul lease.
  • Scenario 2 commands a higher Capex than scenario 3, largely because of higher (~2X) unit price per full-stack home femtocell (vs. home RRU) and the need for security gateway, which is not required in scenario 3.
  • Scenario 3’s Opex is nearly double (vs. scenario 2 Opex), as it requires a significantly higher DOCSIS network capacity for the upstream link. Yet, notably, despite the increased DOCSIS network capacity used by a vRAN deployment, the TCO is still the most favorable.
  • We allocated 20% of DOCSIS network upgrade (from low split to mid split) cost to DOCSIS network-based use cases (scenarios 2 and 3). If we take those out (since DOCSIS network upgrades will happen anyway for residential broadband services) the TCO of these indoor use cases get even better compared to the fiber outdoor case (scenario 1).
  • Other key sensitivities include monthly cost/allocated cost of the XHaul, number of small cell sites within a small cell cluster, radio equipment cost, and estimated number/price of threads required for vBBU HW to serve a cluster in the vRAN scenario.

In an upcoming strategy brief (CableLabs member operators only), we intend to share more details on our methodology, assumptions and breakdown of observed results (both Capex and Opex) along with a sensitivity analysis.

What Do These Results Mean?

To us, it was always a no-brainer that a DOCSIS network-based deployment would have favorable economics compared to a fiber-based model. The TCO model introduced here confirms and quantifies that perceived benefit and points out that for network densification, there is a business case to pursue the indoor femtocell use case where market conditions are favorable.

Subscribe to our blog because our exploration of DOCSIS networks for mobile deployments isn’t over. Coming up next we explore a similar TCO model focused on outdoor deployments served by DOCSIS backhual. Later we will shift back to technology as we look at the DOCSIS networks ability to support advanced features such as CoMP.