A Novel Device-Free Counting Method Based on Channel Status Information

. 2018 Nov 15;18(11):3981. doi: 10.3390/s18113981

Algorithm 1 Crowd Counting based on Channel State Information

Require: Sample Data

([H_{1}, H_{2}, \dots, H_{k}], k \in (1, 30))

, Matrix Resolution

(R)

, Dilatation Coefficient

(D)

, Number of Subcarrier

(S)

, Number of Packets

(P)

, Covariance Matrix

(C (i, j))

, Maximum
Value of Covariance

(C_{m a x})

, Minimum Value of Covariance

(C_{m i n})

, Expansion Matrix

(M)

Ensure: Percentage of Element

(q)

1:
the covariance matrix is extracted from wavelet transformed data
2:
for $i = 1$ to S do
3:
the integet k is calculated
4:
the matrix M is dilated // the element in row k and column j is set to be “1”
5:
for u = $- D$ to D do
6:
for v = $- D$ to D do
7:
the matrix M is dilated // the element in a radius of D is set to be “1”
8:
end for
9:
end for
10:
end for
11:
for $l = 1$ to P do
12:
for $h = 1$ to S do
13:
M = M $(1, h)$ // the percentage of the matrix M of each subcarrier
14:
q = q/ $(P \times S)$ // the percentage is calculated
15:
end for
16:
end for