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Advances in Visual Data Compression and Communication
book

Advances in Visual Data Compression and Communication

by Feng Wu
July 2014
Intermediate to advanced content levelIntermediate to advanced
513 pages
16h 40m
English
Auerbach Publications
Content preview from Advances in Visual Data Compression and Communication
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284 13 Compressive Data Gathering
Substitute Eq. (13.22) into Eq. (13.20), and sum up the interferences from all annu-
luses, we have:
P
f
=
i=1
P
f
(A
i
) <
i=1
2πP
0
(1 + δ)(i + 1)
((1 + δ)ri)
α
=
2πP
0
r
α
(1 + δ)
α1
i=1
1
i
α1
+
1
i
α
=
2πP
0
(ζ (α 1) + ζ (α))
r
α
(1 + δ)
α1
, (13.23)
where ζ (·) is the Riemann Zeta function. When α > 2, ζ (α) <
π
2
6
, and ζ (α 1)
converges to a constant. Denote c
2
= ζ (α) + ζ(α 1). Then, when r = r
0
and δ =
δ
0
>
α1
q
2πβ c
2
1βr
α
N
0
/P
0
1, Eq. (13.23) can be written into:
P
f
<
P
0
r
α
0
β
N
0
. (13.24)
Substitute Eq. (13.19 and Eq. (13.24) into Eq. (13.18), we obtain SINR
j
> β . This
proves that a feasible scheduling under protocol model with r =
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Publisher Resources

ISBN: 9781482234138