Information Technology Reference
In-Depth Information
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)