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Fig. 4.1 An illustration of database assisted spectrum access
Although the database-assisted approach obviates the need of spectrum sensing by
individual users, it remains challenging to achieve reliable distributed spectrum ac-
cess, because many different white-space users may choose to access the same vacant
channel and thus incur severe interference to each other [ 2 , 3 ].
To stimulate effective cooperation among users for interference mitigation, we
leverage the social ties among users and apply the SGUM approach. To capture the
physical coupling, we construct the interference graph
p
p
based on the
interference relationships among users. Here the set of white-space users
G
={ N
,
E
}
N
is the
( n , m ): e nm =
is the edge set where e nm =
E
p
≡{
N }
vertex set, and
1
if and only if users n and m can generate significant interference and affect the data
transmissions of each other. For example, we can construct the interference graph
1,
n , m
p
based on spatial relationships of the users [ 4 ]. Let ʴ denote the transmission range
of each user. We then have e nm =
G
1 if and only if the distance d nm between user n
and m is not greater than the threshold ʴ , i.e., d nm ʴ .
Let a
n = 1 M n be the channel selection profile of all users.
Given the channel selection profile a , the interference received by user n can be
computed as
=
( a 1 , ... , a N )
P m d ʱ
ˉ a n .
ʳ n ( a )
=
mn I { a n = a m } +
(4.1)
p
n
m N
Here ʱ is the path loss factor and I { A }
is an indicator function with I { A } =
1ifthe
0 otherwise. Furthermore, ˉ a n denotes the noisy power
including the interference from primary TV users on the channel a n . We then define
the individual utility function u n ( a )as
event A is true and I { A } =
P m d ʱ
ˉ a n .
=−
=−
mn I { a n = a m }
u n ( a )
ʳ n ( a )
(4.2)
n
m N
Here the negative sign comes from the convention that utility functions are typically
the ones to be maximized. The individual utility of user n reflects the fact that each
user n has interest to reduce its own received interference. To capture the social
coupling in the social graph
s , we further introduce the social group utility of each
white-space user n according to (2.1) as
G
f n ( a )
=
u n ( a )
+
s nm u m ( a ) .
(4.3)
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