US2010042384A1PendingUtilityA1
System program of a wireless coverage prediction
Est. expiryOct 16, 2026(~0.2 yrs left)· nominal 20-yr term from priority
H04W 16/22H04W 16/18H04W 24/06
49
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Claims
Abstract
This invention uses multi-tier indexing methods to organize the wireless communication industry standard Radio Resource Management (RRM) parameters, compression techniques to compress the indexed RRM parameters, model the RRM parameters to identify the relationships between the parameters, simulate the model by eliminating predefined non-influential parameters, to conclude the signal-noise-ratio values in order to determine signal coverage. This invention is used to replace the Road Tests currently implemented by the service carriers for determining actual service coverage.
Claims
exact text as granted — not AI-modified1 . A computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications comprising:
instructing a definition module to define radio resource management parameters; instructing a modeling module to create models by first mathematical expressions in terms of the resource management parameters; instructing a simulation module to perform simulations by using radio resource management parameters and a baseline signal-to-noise ratio (SNR) value; and instructing a characterizing module to define characterizations of the radio resource management parameters by second mathematical expressions,
V={RRM0, RRM1, RRM2, . . . RRMq, BSNR}
where
BSNR: baseline SNR
RRMq: q th number of RRM parameters
F
i
=
[
Vi
^
0
Vi
^
1
Vi
^
2
…
Vi
^
j
Vi
⋆
sin
(
R
)
Vi
⋆
sin
(
2
R
)
…
Vi
⋆
sin
(
mR
)
]
where
V i ̂j: V i to the j th power; An array of RRM parameters and a baseline SNR
F i : characterizing array for the i th member in array V
M i =(V i ,t0 V i ,t1 V i ,t2 . . . V i ,tk)
where
tk: timepoint of k
M i : Array of sampling for RRM i by K samples at different timepoints
P i =(F i ,t0 F i ,t1 F i ,t2 . . . F i ,tk)
where P i : characterizing array for RRM i at k timepoints
2 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 1 comprising:
instructing an index module to perform multiple-tier indexing on the radio resource management parameters.
3 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 2 comprising:
the multiple-tier indexing includes Replica-tree indexing method and Move-To-Front (MTF) indexing method and Run-length Indexing method and Huffman Indexing methods.
4 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 1 comprising:
the first mathematical expressions are,
M
i
=
W
i
⋆
{
[
Pa
0
Pa
1
Pa
2
…
Pan
]
+
Ri
}
where
M i : relationships array representing the relationships between the
RRM i and all other RRM parameters
W i : an intermediate factor
P an : characterizing array for RRM an for all k timepoints
R i : probability array for each Pan.
0≦a0 . . . an ≦q, and a0 . . . an≠i
a0≠a1≠a2≠ . . . ≠an
5 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 1 comprising:
instructing the simulations being performed in accordance with third mathematical expressions,
C
=
U
⋆
[
Fb
0
Fb
1
Fb
2
…
Fbu
Fc
0
⋆
Fd
0
Fc
1
⋆
Fd
1
…
Fcy
⋆
Fdy
Fe
0
/
Ff
0
Fe
1
/
Ff
1
…
Fev
/
Ffv
]
where
C: a constant (any number)
0≦b0 . . . bn ≦q, and b0 . . . bu≠i
c0≠c1≠ . . . ≠cy
d0≠d1≠ . . . ≠dy
e0≠e1≠ . . . ev
f0≠f1≠ . . . ≠fv
U: Balancing array to balance the influential RRMs in the communication environment
6 . A computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications comprising:
instructing a definition module to define radio resource management parameters; and instructing an index module to perform multiple-tier indexing on the radio resource management parameters, wherein the multiple-tier indexing include Replica-tree indexing method and Move-To-Front (MTF) indexing method and Run-length Indexing method and Huffman Indexing methods.
7 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 6 comprising:
instructing a modeling module to create models by first mathematical expressions in terms of the resource management parameters.
8 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 7 comprising:
instructing a simulation module to perform simulations by using radio resource management parameters and a baseline signal-to-noise ratio (SNR) value; and instructing a characterizing module to define characterizations of the radio resource management parameters by second mathematical expressions,
V={RRM1, RRM1, RRM2, . . . RRMq, BSNR}
where
BSNR: baseline SNR
RRMq: q th number of RRM parameters
F
i
=
[
Vi
^
0
Vi
^
1
Vi
^
2
…
Vi
^
j
Vi
⋆
sin
(
R
)
Vi
⋆
sin
(
2
R
)
…
Vi
⋆
sin
(
mR
)
]
where
V i ̂j: V i to the j th power; An array of RRM parameters and a baseline SNR
F i : characterizing array for the i th member in array V
M i =(V i ,t0 V i ,t1 V i ,t2 . . . V i ,tk)
where
tk: timepoint of k
M i : Array of sampling for RRM i by K samples at different timepoints
P i =(F i ,t0 F i ,t1 F i ,t2 . . . F i ,tk)
where P i : characterizing array for RRM i at k timepoints
9 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 8 comprising:
instructing the simulations being performed in accordance with third mathematical expressions
C
=
U
⋆
[
Fb
0
Fb
1
Fb
2
…
Fbu
Fc
0
⋆
Fd
0
Fc
1
⋆
Fd
1
…
Fcy
⋆
Fdy
Fe
0
/
Ff
0
Fe
1
/
Ff
1
…
Fev
/
Ffv
]
where
C: a constant (any number)
0≦b0 . . . bn ≦q, and b0 . . . bu≠i
c0≠c1≠ . . . ≠cy
d0≠d1 . . . ≠dy
e0≠e1≠ . . . ≠ev
f0≠f1≠ . . . ≠fv
U: Balancing array to balance the influential RRMs in the communication environment
10 . A computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications comprising:
instructing a definition module to define radio resource management parameters; and instructing a characterizing module to define characterizations of the radio resource management parameters by second mathematical expressions,
V={RRM0, RRM1, RRM2, . . . RRMq, BSNR}
where
BSNR: baseline SNR
RRMq: q th number of RRM parameters
F
i
=
[
Vi
^
0
Vi
^
1
Vi
^
2
…
Vi
^
j
Vi
⋆
sin
(
R
)
Vi
⋆
sin
(
2
R
)
…
Vi
⋆
sin
(
mR
)
]
where
V i ̂j: V i to the jth power; An array of RRM parameters and a baseline SNR
F i : characterizing array for the i th member in array V
M i =(V i ,t0 V i ,t1, t2 . . . V i ,tk)
where
tk: timepoint of k
M i : Array of sampling for RRM i by K samples at different timepoints
P i =(F i ,t0 F i ,t1 F i ,t2 . . . F i ,tk)
where P i : characterizing array for RRM i at k timepoints
11 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 10 comprising:
instructing a modeling module to create models by first mathematical expressions in terms of the resource management parameters; and instructing an index module to perform multiple-tier indexing on the radio resource management parameters.
12 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 11 comprising:
the multiple-tier indexing includes Replica-tree indexing method and Move-To-Front (MTF) indexing method and Run-length Indexing method and Huffman Indexing methods.
13 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 11 comprising:
the first mathematical expressions are,
M
i
=
W
i
⋆
{
[
Pa
0
Pa
1
Pa
2
…
Pan
]
+
Ri
}
where
M i : relationships array representing the relationships between the RRM i and all other RRM parameters
W i : an intermediate factor
P an : characterizing array for RRM an for all k timepoints
R i : probability array for each Pan.
0≦a0 . . . an ≦q, and a0 . . . an≠i
a0≠a1≠a2≠ . . . ≠an
14 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 11 comprising:
instructing a simulation module to perform simulations by using radio resource management parameters and a baseline signal-to-noise ratio (SNR) value.
15 . The computer-readable medium having computer-executable instructions of automatic coverage preditions for wireless communications of claim 14 comprising:
instructing the simulations being performed in accordance with third mathematical expressions,
C
=
U
⋆
[
Fb
0
Fb
1
Fb
2
…
Fbu
Fc
0
⋆
Fd
0
Fc
1
⋆
Fd
1
…
Fcy
⋆
Fdy
Fe
0
/
Ff
0
Fe
1
/
Ff
1
…
Fev
/
Ffv
]
where
C: a constant (any number)
0≦b0 . . . bn ≦q, and b0 . . . bu≠i
c0≠c1≠ . . . ≠cy
d0≠d1≠ . . . ≠dy
e0≠e1≠ . . . ≠ev
f0≠f1≠ . . . ≠fv
U: Balancing array to balance the influential RRMs in the communication environmentJoin the waitlist — get patent alerts
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