International audienceThis paper provides techno-economic analyses on the network deployments to cover 4 key verticals, under 5G-NR. These verticals, namely Automotive, Smart city, Long range connectivity and Disaster and emergency support, were chosen to reflect the ONE5G project objective of investigating environments from densely populated cities ("Megacity") to large underserved areas. The work presented covers the network deployment framework including common centralization strategies and the main cost factors. Initial results presented for long range connectivity and emergency support networks provide the cost trade-offs in different deployment options and cost sensitivity to some of the parameters

Bao, Yu

HAMON, Marie-Hélène

Hunukumbure, Mythri

Jeux, Sebastien

Langouet, Serge

Roblot, Sandrine

Santiago, Elena,

Varsier, Nadège

English

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Techno-economic analyses for vertical use cases in the
5G domain
Sandrine Roblot, Mythri Hunukumbure, Nadège Varsier, Elena Santiago, Yu
Bao, Serge Langouet, Marie-Hélène Hamon, Sebastien Jeux
To cite this version:
Sandrine Roblot, Mythri Hunukumbure, Nadège Varsier, Elena Santiago, Yu Bao, et al.. Techno-
economic analyses for vertical use cases in the 5G domain. EuCNC ONE5G special session, Jun 2019,
Valencia, Spain. ￿hal-02160872￿
Techno-economic analyses for vertical use cases in 
the 5G domain 
Sandrine Destouet Roblot1, Mythri Hunukumbure2, Nadege Varsier1, Elena Serna Santiago3, Yu Bao1, Serge 
Langouet1, Marie-Hélène Hamon1, Sebastien Jeux1 
1 Orange Labs, 4 rue du clos courtel 35512 Cesson-Sévigné, France 
2 Samsung R&D Institute UK, Communications House, Staines-upon-Thames, UK. TW18 4QE 
3 Telefonica I+D, Ronda de la Comunicación, s/n, 28050 Madrid, Spain 
 
Abstract— This paper provides techno-economic analyses on 
the network deployments to cover 4 key verticals, under 5G-NR. 
These verticals, namely Automotive, Smart city, Long range 
connectivity and Disaster and emergency support, were chosen to 
reflect the ONE5G project objective of investigating 
environments from densely populated cities (“Megacity”) to large 
underserved areas. The work presented covers the network 
deployment framework including common centralization 
strategies and the main cost factors. Initial results presented for 
long range connectivity and emergency support networks provide 
the cost trade-offs in different deployment options and cost 
sensitivity to some of the parameters. 
Keywords—5G, cost models, V2X, long range, smart cities, 
underserved areas, TCO Introduction 
I. INTRODUCTION 
The foreseen explosion in new digital services, new vertical 
markets and diverse applications will make 5G networks 
unique in many aspects. The techno-economic analysis of such 
complex networks is of greatest importance, as it assesses the 
economic viability of new services, especially in vertical 
sectors not addressed by cellular networks before. In 5G-PPP 
project ONE5G [1] in particular, the aim of developing a 
flexible air-interface able to be efficient as well as in dense 
urban environments (labeled “Megacities” in ONE5G) as in  
underserved areas scenarios [2], comes with the objective of 
identifying the cost driving elements for the roll-out and 
operation of systems in such scenarios. 
Four use cases (uc) were selected from a total of 9, to be 
studied in ONE5G techno-economic analysis: uc1 on assisted, 
cooperative and tele-operated driving, uc3 on smart cities, uc4 
on long range connectivity in remote areas and uc9 on Ad-hoc 
airborne platforms for disasters and emergencies. This choice 
was realized with the aim of fairly reflecting the Megacities 
and Underserved areas scenarios as well as the 3 service 
categories targeted by 5G (e.g. eMBB, URLLC and mMTC).  
Multiple deployment options were also considered, either 
based on 3GPP 5G New Radio (NR) Rel.15 network and 
accounting for the technical needs of each use case. 
Technology selection (such as Multi-access Edge Computing 
for uc1 or cellular IoT for uc3) was governed by the primary 
requirements of each uc and the cost impacts of different 
methodologies to meet the same requirements were studied. 
 
II. METHODOLOGY 
The starting point of the techno-economic study is to 
consider an already existing NR 5G Rel.15 network as defined 
in 3GPP Rel.15 [3]. It follows a hybrid model where the gNB 
can be either aggregated in a single node or disaggregated into 
three logical nodes comprising the Remote Radio Head (RRH), 
the distributed unit (DU) and the centralized unit (CU).  These 
centralization themes are a key common factor in uc1, uc4 and 
uc9 analysis, where the 3GPP centralization options 2 (PDCP 
layer) and 7 (upper PHY layer) are considered. 
The related backhaul and fronthaul (last part of the 
transport network that reaches the base station or Radio Unit - 
plus the metro segment between the Baseband Unit (BBU) and 
the RRH) cost models are developed in line with the work 
performed in mmMAGIC project [4]. Different possibilities 
can be envisioned for the backhaul and fronthaul deployments, 
based on owned microwave, leased or owned fiber. In all cases 
the cost is dependent of the fronthaul or backhaul capacity. For 
the last drop, either leased lines or owned lines are envisioned: 
in leased lines, there is no need to consider a particular cost 
model as such cost would be subsumed within the overall 
connection cost charged by the third party that provides the 
connectivity; in owned lines case this cost is calculated 
separately including civil work costs, average last drop length, 
and related equipment. 
III. TECHNO-ECONOMIC ANALYSIS 
A. Use case 1: assisted, cooperative and tele-operated driving 
The assisted, cooperative and tele-operated driving uc is 
one of the multiple services that are comprised within V2X 
category that can pose stringent requirements over networks 
due to the sensitivity of its actions.  
These requirements (low latency, high availability and very 
high reliability) are quite difficult to fulfill by traditional 
networks, requiring in most cases the need to deploy additional 
network nodes to satisfy the ultra-low communications that are 
needed. These nodes are known as Multi-access Edge 
Computing (MEC) nodes. 
The techno-economic analysis carried out in uc1 considers 
precisely this approach where one or several MEC nodes are 
included under different RAN topologies (Centralized (C-
RAN) and Distributed (D-RAN)) [5] with the aim to reduce the 
E2E service latency and improve reliability. Megacities and 
underserved areas were considered in the study as both 
scenarios can seamlessly provide V2X services regardless their 
characteristics and main differences. The study was conducted 
in a two-step analysis. 
Firstly, we analyzed the impact of a MEC node over the 
existing infrastructure in a D-RAN/C-RAN topology such as 
the power and fronthaul/backhaul requirements and how they 
should scale up/down with the MEC introduction. Lastly, the 
cost impact of deploying V2X with the aid of MEC nodes for 
such different scenarios configurations was quantified.  
The initial outcomes of the quantitative analysis show in 
terms of Total Cost of Ownership (TCO) that C-RAN split 7 
(Phy layer) is the most cost-effective solution to provide V2X 
services regardless the characteristics of the scenario, i.e. 
number of sectors, MIMO order, modulation scheme and 
bandwidth, in both megacities (Figure 1) and rural areas 
(Figure 2). D-RAN remains as the most expensive option due 
to the high dependency on dedicated hardware, whereas C-
RAN split 2 (PDCP layer) architecture slightly reduces the total 
cost as it starts avoiding this dependency by introducing 
Commercial Of The Shelf (COTS) equipment. 
 
Figure 1: TCO per sector for Megacity scenario 
 
Figure 2: TCO per sector for Underserved area scenario 
 
B. Use case 3: smartcities  
 The smart cities uc deals with non-time-critical processes 
and logistics for dense urban and suburban area management. 
The objective is to provide mMTC services for applications 
such as traffic management, waste collection and 
management, parking detection and information, air 
monitoring, etc. where data has small payloads and no high 
constraints on latency. 
 3GPP announced that such Low-Power Wide-Area 
(LPWA) deployments requirements would finally be 
supported by Narrowband-IoT (NB-IoT) and LTE-M whose 
evolution would be part of 5G NR, meaning that NB-IoT and 
LTE-M are on the path to 5G [6]. That’s why the techno-
economic analysis for use case 3 was considered with, on one 
side, the in-band deployment of LTE-M and of NB-IoT on the 
other side. The study was carried out by firstly evaluating the 
number of additional Physical Resource Blocks (PRBs) that 
would be necessary in Rel. 16 to satisfy the number of devices 
envisioned for the Smart cities applications; and secondly by 
assessing the impact on cost deployment. For that purpose, 
performance studies carried out for 3GPP by Ericsson were 
considered [7]. In order to see if LTE-M and NB-IoT would 
meet the 5G requirements in term of density of connections (1 
million devices/km2) Ericsson carried out non-full buffer 
system simulations considering two different inter-site 
distances (ISDs) and two different channel models. For the 
traffic model, devices were considered to emit 32 bytes 
messages every 2 hours. For NB-IoT (LTE-M respectively) 
the results have shown that 1 to 15 PRBs (1 to 3 narrowbands 
respectively) would be necessary to fulfil the 5G mMTC 
requirements, depending on the considered ISD and channel 
model. Then to evaluate the number of devices envisioned for 
the smart cities applications at the time of Rel.15 and Rel.16 
deployments, a study was carried out extrapolating these 
numbers for a typical dense urban city (Paris) in 2020 
(corresponding to Rel. 15) and 2030 (corresponding to Rel. 
16):250 000 devices were extrapolated for Rel. 15 and 
650 000 for Rel. 16. 
The analysis has shown that, depending on the deployment 
settings and the traffic model, up to 6 additional PRBs (one 
additional narrowband respectively) would be necessary for 
NB-IoT (LTE-M respectively) between Rel. 15 and Rel. 16 to 
satisfy the number of devices envisioned for Smart cities 
applications as illustrated on Figure 3. 
 
 
(a) 
 
(b) 
 
Figure 3: Needed resources for NB-IoT (respectively LTE-M) to satisfy to 
the number of devices envisioned for Smart cities applications in Rel. 15 
and 16 
 
C. Use case 4: long range connectivity in remote areas  
 The long range connectivity in remote areas uc is dedicated 
to underserved areas, for the provision of minimal voice and 
data services over long distances in low user density areas. The 
applications targeted are minimal services including voice over 
long distances plus best effort data services for smartphones, 
tablets, etc. The priority of this service is to provide a 
maximum coverage (up to 50 km in rural and 100 km or more 
for ultra-rural) without strict requirements on throughput. 
 Such wide radio coverage has some implications on the 
backhaul technology (fiber, microwave, satellite) and its 
configuration (architecture, topology). In both rural and 
extreme rural environments, different solutions are being 
analyzed to check which configuration guarantees the targeted 
coverage. This is performed by using specific link budget tools, 
long distance propagation model and 3GPP radio interface 
physical channels link budget data.  
 Multiple configurations were studied in order to determine 
the best alternative to meet the requirements of extreme rural 
and rural deployments: three antenna heights (60m, 75m, 
108m), three options of vertical diversity (2, 3 or 4 floors), two 
MIMO orders (2x2 or 4x2), two possibilities of sectorization (3 
or 6 sectors). 
 For extreme rural, the objective was to reach a 100km 
coverage with throughputs of 2 Mbps downlink and 0.256 
Kbps uplink. The best option found was to consider the 700 
MHz frequency band, a mast elevation of 108m, four floors of 
antennas, six sectors and MIMO4x2. With such configuration, 
the maximum coverage we obtained is 80km.  
 The extreme rural TCO per km² of such configuration is 
pictured in Figure 4. For this extreme rural case, the backhaul 
is supported by microwaves only. The satellite option was 
envisioned as well but is much more expensive and thus not 
considered as a possible solution, especially since we have 
wonders on its ability to maintain the latency requirements.  
  
 
 Figure 4: TCO per km² evolution with three different antenna heights, 6 
sectors, MIMO4x2, 4 floors of antennas in extreme rural deployment 
 
 A similar analysis was performed for the rural areas case 
where the targeted objective was to reach 50km while 
maintaining throughputs of 50 Mbps downlink and 25 Mbps 
uplink. Massive MIMO at 3.5GHz was considered to fulfill the 
need for capacity: MIMO64x2 for downlink and SIMO1x64 
for uplink. The best coverage we obtained was 15km.  
 Different options of backhaul were envisioned for the rural 
case, comparing the costs induced by C-RAN splits 2 and 7, 
mixing both microwave and dark fibers. 
D. Use case 9: Ad-hoc airborne platforms for disasters and 
emergencies  
 This uc is customized to provide on demand, 5G eMBB 
services to emergency crews, wherever the need arises, within 
their service area. The 5G provision is through drones, which 
use multiple drone links to relay the signal (Fronthaul) back to 
a ground relay anchor station (existing 4G or 5G small cell 
upgraded to support this), then to the BBU and the core 
network as per the centralized (C-RAN) network architecture. 
The analysis considers 3 main deployment cost factors: the 
costs of acquiring and running a fleet of high precision drones 
and their radio kit, the costs of upgrading ground small cells 
and the incrementing costs of providing the additional 
fronthaul and backhaul capacity. For the fronthaul and 
backhaul, the leased line cost model is assumed, where the 
incremental costs are directly linked to the additional 
capacities. For the C-RAN split 2 (PDCP layer), the fronthaul 
capacity needed is lower than for the C-RAN split 7 (Phy 
layer). The capacity increment factors are taken from [4]. 
 The overall TCO for this solution was estimated with the 
above 3 cost factors, for the two split points. The TCO – 1 year 
results are shown in Figure 5 below, where the split 2 costs are 
lower than for the split 7. The trade-off between higher drone 
costs and the lower fronthaul costs for the PDCP split 
outperforms the opposite trade-off for these factors in the upper 
PHY layer split. Similar results are also seen for the 5 year 
TCO. 
 
 
Figure 5: TCO comparison for PHY and PDCP layer splits 
 
 The cost sensitivity of the proposed solution to increments 
of the number of maximum drones per link is also studied. 
Incrementing the drone numbers increases the drone related 
costs, but reduces the number of ground small cells needing 
upgrades and the additional fronthaul capacities. Figure 6 
shows that the TCO reduces exponentially with the drone 
numbers up to 6 and then increases again. The drone radio kit 
costs are taken here as to be comparable to ground small cells, 
but full results taking this also as a variable will be presented. 
 
Figure 6 TCO variation with the number of drones per link 
IV. CONCLUSIONS 
    The presented work analyses the techno-economic 
aspects of 5G network deployment to support 4 key vertical 
areas. While the individual studies are quite distinct, common 
aspects such as 3GPP C-RAN options are utilized as a means 
of comparing the cost trends. Some of the cost models 
developed in the previous mmMAGIC project have been 
utilized to develop the studies. Some assumptions had to be 
made on the costs of certain network elements, as these 
envisaged 5G systems are still far from being deployed. So the 
trends we have highlighted are more accurate and the absolute 
cost values reported should be taken only as indicative 
 
 
 
In the uc1 (Automotive) analysis, the TCO for the C-RAN 
split 7 returns the lower costs than for the split 2 or the D-RAN 
options. This can be attributed to the hardware costs of the 
distributed units having more impact than the fronthaul 
capacity provision costs in uc1. In the uc 9 (NTN emergency 
support) we see the reverse trend, where the distributed unit 
(drone) costs are lower than the Fronthaul and anchor BS 
upgrade costs.  
 For uc3 we have shown that additional resources might be 
needed between Rel. 15 and Rel. 16 if we want to satisfy to the 
number of devices envisioned for Smart cities applications. 
This need will depend on the deployment settings and the 
considered traffic models.  
In the uc4 (long range), multiple deployment options were 
evaluated. Some parameters permit an improvement of the 
coverage while providing a more interesting TCO per km²; 
this is the case for the number of floors (vertical diversity) or 
the MIMO order. Sectorization increases the capacity while 
reducing the TCO per km² as well. On the other side, 
increasing the mast elevation of antennas enhances the 
coverage but does not reduce the TCO. The same way, 
increasing the power at the base station does not improve the 
coverage because the limiting factor is always on the uplink 
but has some negative impact on the TCO per km². 
 
ACKNOWLEDGMENT  
Part of this work has been performed in the framework of the 
Horizon 2020 project ONE5G (ICT-760809) receiving funds 
from the European Union. The authors would like to 
acknowledge the contributions of their colleagues in the 
project, although the views expressed in this contribution are 
those of the authors and do not necessarily represent the 
project. 
REFERENCES 
[1] ONE5G project website, https://one5g.eu/ 
[2] ONE5G deliverable, D2.1 - “Scenarios, KPIs, use cases and baseline 
system evaluation”, Nov. 2018 
[3] 3GPP TR 21.915, Release description, Release 15, available at 
https://www.3gpp.org/DynaReport/21-series.htm 
[4] mmMAGIC, Deliverable 1.4, “Use case description, spectrum 
considerations and feasibility analysis”, June 2017. 
[5] 3GPP Technical Report TR38.801, “Study on New Radio Access 
Technology; Radio Access Architecture and Interfaces (Release 14)”, 
available at:  https://www.3gpp.org/ftp/Specs/archive/38_series/38.801/ 
[6] GSMA publication, “Mobile IoT in the 5G Future – NB-IoT and LTE-M 
in the context of 5G”, April 2018 
[7] 3GPP R1-1809780, “IMT-2020 self evaluation: mMTC non-full buffer 
connection density for LTE-MTC and NB-IoT”, source Ericsson, RAN1 
meeting #94 
 


Techno-economic analyses for vertical use cases in the 5G domain

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Techno-economic analyses for vertical use cases in the 5G domain

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