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Fig. 2.1 Illustration of the social group utility maximization (SGUM) framework
2.2
Physical Network Graph Model
We consider a set of wireless users
where N is the total number
of users. We denote the set of feasible strategies for each user n
N ={
1, 2, ... , N }
N
as
X n .For
instance, a strategy x
X n can be choosing either a channel or a power level for
wireless transmission. Subject to heterogeneous physical constraints, the strategy
set
X n can be a set of feasible
relay users that are in vicinity of user n for cooperative communication.
To capture the diverse physical coupling among the users in the physical domain,
we introduce a physical graph
X n can be user-specific. For example, the strategy set
p
p
G
={ N
,
E
}
(see Fig. 2.1 for an example). Here
( n , m ): e nm =
p
the set of users
N
is the vertex set, and
E
≡{
1,
n , m
N }
is the
edge set where e nm
1 if and only if users n and m have physical coupling (e.g.,
cause interference to each other). We also denote the set of users that have physical
coupling with user n as
=
n
: e nm =
N
≡{
m
N
1
}
.
n = 1 X n be the strategy profile of all users. Given the
strategy profile x , the individual utility function of user n is denoted as u n ( x ), which
represents the payoff of user n , accounting for the physical coupling among users. For
example, u n ( x ) can be the achieved data rate or the satisfaction of quality of service
(QoS) requirement of user n under the strategy profile x . Note that in general the
underlying physical graph plays a critical role in determining the individual utility
u n ( x ). For example, users' achieved data rates are determined by the interference
graph and channel quality.
Let x
=
( x 1 , ... , x N )
2.3
Social Network Graph Model
To capture the diverse social coupling among the users in the social domain, we
introduce a social graph
s
s
G
={ N
,
E
}
to model their social ties. Here the edge set
s
( n , m ): e nm =
where e nm =
is given by
E
={
1,
n , m
N }
1 if and only if users
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