The scope of this dissertation is to study the network infrastructure sharing concept
between competing mobile operators. In this particular research, in first approximation
we mainly focus on the total operating cost (OPEX) reduction and energy savings that
can be achieved through a potential multi-operator cooperation during a 24-hour period.
In our study we consider that the operators agree to share their radio access network,
which consists of heterogeneous networks systems such as macro cells and micro cells.
In order to apply the network sharing concept we formulated the power consumption of
base stations as function of served users and we analyzed the parameters that affect this
relationship. Considering a typical daily traffic, the network sharing mechanism can be
applied for periods of low traffic demands. Typically, these off-peak periods correspond
to night hours. Based on energy costs minimization strategies we assign for each operator
an optimal on/off policy and a roaming policy which defines the portion of traffic
that migrates from the switched off operators to active network operators. Thus, considering
a geographical area, under low traffic loads some of the operators set their entire
access network in sleep mode only when the remaining active operators can support
their current traffic and the roaming users without decreasing the quality of service.
In second approximation we analyze how the potential cost reduction gains must be
allocated among the operators which participated in network cooperation. Main concern
of this approach is to distribute the profit gained in a fairly way among the selfinterested
operators. These fairness issues are tackled through a game theoretic approximation.
Namely, in the context of coalition game theory, each operator is considered to
be a rational strategic player who seeks to maximize his payoff (or in other words to
minimize its operating cost). Hence, based on the cooperative game theory and more
particularly on Shapley value axiomatic fairness theorem we define the portion of the
profit (payoff) that each operator must receive depending on its contribution to the total
cost reduction. However, this is not the finalized allocation of the profit since the
switched off operators must pay the corresponding roaming cost to the active operators.
The aforementioned description was optimized for N=3 competing operators. Similarly,
the simulations that we run in Matlab environment were optimized for N=3 and
N=2 operators considering a 24-hour traffic pattern. Setting the network configuration
of each operator the algorithm that we developed defines the on/off and roaming policy
of each operator and calculates the roaming costs.
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