Cost analysis of rural roll-out using a long-reach passive optical network: trading off the upfront cost under uncertainty of the user take-up rate

Cezary Żukowski; Cezary Żukowski; Cezary Żukowski; Atri Mukhopadhyay; David B. Payne; Marco Ruffini; Marco Ruffini

doi:10.1364/JOCN.415806

Journal of Optical Communications and Networking
Vol. 13,
Issue 5,
pp. 69-84
(2021)
•https://doi.org/10.1364/JOCN.415806

Cost analysis of rural roll-out using a long-reach passive optical network: trading off the upfront cost under uncertainty of the user take-up rate

Cezary Żukowski, Atri Mukhopadhyay, David B. Payne, and Marco Ruffini

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Cezary Żukowski, Atri Mukhopadhyay, David B. Payne, and Marco Ruffini, "Cost analysis of rural roll-out using a long-reach passive optical network: trading off the upfront cost under uncertainty of the user take-up rate," J. Opt. Commun. Netw. 13, 69-84 (2021)

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Abstract

High deployment cost with respect to expected revenue is the main barrier to fiber-to-the-home (FTTH) roll-out in rural areas. This problem, as shown in this paper, is exacerbated by the uncertainty associated with the end-user take-up rate. The randomness associated with subscribers’ service take-up yields considerable fluctuation and escalation in the total cost of deployment. This adverse and varying environment makes it difficult to produce firm business cases and can increase the reluctance of potential investors and incumbent operators to deploy FTTH access networks. In this paper, we develop a holistic framework for examining real-world FTTH deployment scenarios, taking as a case study one of the most rural counties in Ireland. Further, we carry out an in-depth techno-economic analysis identifying the methods more applicable in the rural scenario. We analyze the cost effectiveness of FTTH deployment, also proposing solutions that provide different levels of upfront investment risk, relating it to uncertainty in customers’ take-up rates. For example, we show how a lower take-up rate can be made profitable by adopting a strategy that favors lower upfront costs at the expense of higher connectivity costs.

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Last Splitter Size	Homogeneous Splitter Configurations
64	$64 \times 2$
32	$32 \times 2 \times 2$ , $32 \times 4$
16	$16 \times 4 \times 2$ , $16 \times 8$
8	$8 \times 4 \times 4$ , $8 \times 8 \times 2$ , $8 \times 8 \times 2 +$
4	$4 \times 8 \times 4$ , $4 \times 4 \times 4 \times 2$ , $4 \times 2 \times 8 \times 2$ , $4 \times 16 \times 2$ , $4 \times 16 \times 2 +$
2	$2 \times 16 \times 4$ , $2 \times 16 \times 4 +$

	Capacity or Rate	Costs	Planning Details
Ducting (C1)	$T_{1}$ set contains 1-BFT, 2-BFT, 4-BFT, 7-BFT, 9-BFT, 12-BFT, 19-BFT	$C_{t}^{1}$ set contains 180, 310, 520, 800, 970, 1200, 1750 (EUR/km), where $t \in T_{1}$	$C_{t}^{1}$ includes the cost of materials. The planning is fully automated by the heuristic (in Section 4), which dimensions the size of duct links planned along the streets according to the required fiber capacity and particular deployment scenario (Fig. 3). So, it is known in advance what variant of BFT to install in both stages in Fig. 3.
Splitter and splice nodes (C2)	$T_{2}$ set contains 2, 4, 8, 16, 32	$C_{t}^{2}$ set contains 290, 340, 440, 620, 990 (EUR/node), where $t \in T_{2}$	Splitter/splice nodes must be installed on the poles (the positions where to install the nodes are provided by the heuristic in Section 4) to interconnect the ducts. $C_{t}^{2}$ contains both material and labor costs and the bill of materials (BoM) is illustrated in Fig. 9. The total cost of a node also includes the labor cost required to install a node on a pole, which is set to 1 h for two workers.
Blown fiber cabling (C3)	$T_{3}$ set contains 4-BFU, 8-BFU, 12-BFU	$C_{t}^{3}$ set contains 130, 240, 330 (EUR/km), where $t \in T_{3}$	$C_{t}^{3}$ contains both material and labor costs. The labor is required to blow fiber into the infrastructure of ducts.
Duct installation (C4)	$T_{4}$ set contains 1 h/km, 4 h/km	$C_{t}^{4}$ set contains 210, 840 (EUR/km), where $t \in T_{4}$	$C_{t}^{4}$ includes the labor cost required to install a kilometer of duct over poles with rate $t \in T_{4}$ . The planning is fully automated by the heuristic (in Section 4), which creates a duct installation schedule. It is known in advance when a particular duct (in row C1) should be installed. The schedule differs between the methods in Fig. 3.

	All Component Costs of Total Deployment Cost ( $t_{c}$ ) in Eq. (1)
	Blown Fiber Cabling (C3)	Splitter and Splice Nodes (C2)	Ducting (C1)	Duct Installation (C4)
CM2: $16 \times 4 \times 2$	1.19%	0.50%	1.52%	6.78%
CM2: $8 \times 4 \times 4$	1.24%	1.01%	1.54%	6.22%
CM2: $4 \times 16 \times 2 +$	1.29%	1.75%	1.53%	5.42%
CM3: $16 \times 4 \times 2$	1.97%	0.83%	2.12%	5.08%
CM3: $8 \times 4 \times 4$	1.55%	1.27%	1.82%	5.37%
CM3: $4 \times 16 \times 2 +$	1.37%	1.85%	1.59%	5.19%
CM1: $16 \times 4 \times 2$	2.37%	1.00%	2.39%	4.23%
CM1: $8 \times 4 \times 4$	1.94%	1.58%	2.10%	4.38%
CM1: $4 \times 16 \times 2 +$	1.66%	2.24%	1.82%	4.28%

$N$	$P$ (EUR)	$F$ (EUR)	Payback Period (Years) (NPV Value Becomes Positive after That Period)
$N_{t} \cdot 5 %$	10	0	Never within 40-year period
		500	Never within 40-year period
		1500	Never within 40-year period
	20	0	33
		500	28
		1500	19
$N_{t} \cdot 25 %$	10	0	Never within 40-year period
		500	31
		1500	15
	20	0	16
		500	12
		1500	7
$N_{t} \cdot 75 %$	10	0	32
		500	23
		1500	10
	20	0	13
		500	10
		1500	5

			Payback Period (Years) (NPV Value Becomes Positive after That Period)
	$P$ (EUR)	$F$ (EUR)	$S_{a v g} = 1000 (E U R)$	$S_{a v g} = 4000 (E U R)$
	10	0	90	$x$
		500	56	$x$
		1500	29	$x$
	20	0	23	63
		500	19	52
		1500	12	37
	40	0	10	20
		500	9	18
		1500	7	15
	70	0	6	11
		500	6	10
		1500	4	8
Minimum	10	0	90	$x$
profit ( $P$ ) to	9	500	76	$x$
obtain viable	6	1500	86	$x$
payback time

Abstract

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Equations (2)

Journal of Optical Communications and Networking