Page 145 - ITU Journal Future and evolving technologies – Volume 2 (2021), Issue 2

ITU Journal on Future and Evolving Technologies, Volume 2 (2021), Issue 2

low‑cost RRH, only provide low‑complexity transmission contribution of sharing techniques. [14], different sce‑
and reception. Due to its low complexity functionality, its narios of infrastructure sharing models are explored to
size is smaller than that of conventional base stations and build a mathematical model to analyze the bene its and
can be easily installed [16]. The BBU pool is deployed on costs of infrastructure sharing in China. Vanessa Vascon‑
hardware, i.e. multi‑core servers, and the baseband func‑ cellos et al. also proposed a mathematical model to cal‑
tions are software‑de ined and run as applications on the culate the bene its of infrastructure sharing between op‑
servers [17]. erators and neutral hosts in 5G based on cost evaluation
The capacity of the cloud is de ined by the number of [8]. This study aims to set up a framework based on the
BBUshostedontheservers. TheBBUpoolscanbestacked comparison with other sharing strategies, suggesting the
without a direct link or interconnected in such a way best alternative from a cost point of view. Using urban
as to share resources and functionality according to de‑ environments with very high population density as a case
mand from the RRH. Therefore, if n is the number of BBUs study in which several actors share passive infrastructure,
hosted in the cloud, it is possible to perform baseband preliminary results have shown that sharing with a neu‑
processing of m RRH. In the case of rural areas, it can be tral host can increase savings compared to other passive
seen that when a network is traditionally deployed, the sharing strategies. Based on game theory, Adrian Kliks
traf ic is low; the network is under exploited because of [21] found that operators can achieve substantial inan‑
the low population density. As a result, m can become cial savings by avoiding new site construction costs at
very large compared to n. The cloud‑RAN also allows overlapping sites, consolidating existing sites, and reduc‑
the coexistence of several technologies. This will be very ing lease, maintenance and transmission costs.
important to offer voice telephony services with 2G in‑ In Joseph [3] an extensive analysis of infrastructure shar‑
frastructure, for example, and broadband with 4G to sev‑ ing and a model to be developed to analyze the cost and
eral cells simultaneously. Thus, pooling the resources de‑ bene its of tower sharing in Ghana. The results obtained
ployed and sharing these resources in the cloud can ben‑ from data sources support the propositions of the liter‑
e it the operators and enable the ef icient and optimal ature review that infrastructure sharing provides opera‑
use of the deployed resources. In [18], it was shown that tors with a wide range of bene its and savings. On aver‑
the more cells or base stations that use a cloud‑RAN, the age, about 44.61% of capital can be saved if the eight tele‑
lower the overall CAPEX deployment cost and TCO per com operators in the country share a tower. In [9], the
site. And the faster the return on investment in the par‑ authors propose a model for infrastructure sharing and
ticular case of rural areas. Thus, by opting for joint con‑ found that sharing can save between 30 and 40 percent
struction of a cloud‑RAN in which several operators share of CAPEX and OPEX expenses. Also, [22] has developed a
the infrastructure, it accelerated the reduction of the dig‑ model for backhaul sharing using different technologies.
ital bill. However, to better appreciate the bene its of sharing, a
On the other hand, a new paradigm brought about by 5G complete model that considers all the modules for net‑
now makes it possible to consider sharing in the network work extension is required. Also, in the various stud‑
according to several services: network slicing. The net‑ ies, the modelling is done for passive sharing in the RAN.
work slicing consists of using virtualization, i.e. Software The study cases are generally for densely populated ar‑
De ined Network(SDN) and Network Function Virtualiza‑ eas where the network capacity implemented on the sites
tion (NFV), to partition and optimize resource manage‑ is fully utilized. Although we have a signi icant amount
ment by creating slices. The network slice is a logical net‑ of modelling, the authors do not consider infrastructure
work that can be technically deployed in all ixed and mo‑ sharing an application framework for universal ICT ac‑
bile networks [19]. cess or removing the digital bill. Therefore, in this study,
Network slicing allows for different performances asso‑ we model passive and active infrastructure sharing and
ciated with each slice and allocates dedicated resources network resource sharing to eliminate the rural digital di‑
per type of usage. Each network slice, therefore, corre‑ vide.
sponds to a speci ic use different from the other slices.
The network slice can be considered as a real catalyst for 3. INFRASTRUCTURE SHARING MODEL
services. It can be created, modi ied and deleted using
network management functions [20]. In particular, net‑ This section presents a modelling approach for infras‑
work slicing as a form of resource sharing in the RAN is tructure sharing solutions in mobile network extension
a mechanism that allows the sharing of a single network in rural areas. This modelling calculates the total in‑
infrastructure between several operators, where each op‑ vestment cost resulting from infrastructure deployment
erator provides its functionality and services. according to the sharing approach. For this purpose, we
Different sharing techniques can lead to signi icant sav‑ use the OPEX and CAPEX cuts to determine the TCO.
ings. However, the most important thing is to ind an The irst step of our framework consists of a total net‑
optimal model for sharing, especially in a context where work deployment cost model in the standard case as
the return on investment is not obvious, such as in ru‑ presented in Fig.1.
ral, poor and remote areas. In the literature, different ap‑
proaches and models have been proposed to assess the

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