Modeling and Performance Analysis of Opportunistic Link Selection for UAV Communication

View full-text article in PMC

. 2021 Jan 13;21(2):534. doi: 10.3390/s21020534

Algorithm 2 Pseudo-code of RA-OLA Scheme for Random PU Traffic Patterns.

1:
Initialization of parameters
2:
while $m \in {M}$ do // Create PU traffic patterns.
3:
Generate random ON model with $λ_{a}$ exponential distribution for $m_{t h}$ link within $T_{o}$ .
4:
Generate random OFF model with $λ_{v}$ exponential distribution for $m_{t h}$ link within $T_{o}$ .
5:
end while
6:
Calculate probability of false alarm ${\hat{P}}_{F} (m)$ following Equation (13) given determined ${\hat{P}}_{D}$ .
7:
Generate LHS $T$ for each UAV following the allocation Algorithm 1.
8:
Create a two-stage Markov machine presented in Figure 5.
9:
while $k \in {K}$ do
10:
Calculate $n_{e}$ with $n_{o}$ , F and $T$ .
11:
while $n \in {n_{e}}$ do
12:
Add Rice propagation model to the upload data.
13:
Identify the Markov machine state.
14:
Identify whether the upload data is received (power is within the threshold). The flag $f l a g_{t}$ sets to 0 when the data is lost.
15:
Update the Markov machine state.
16:
while the received LHSs have not been fully processed do
17:
while Time of re-sensing is smaller than R do
18:
Generate AWGN noises with $N_{d}$ length for $N_{n}$ channels.
19:
Calculate the sub-channel number whose power is over the threshold.
20:
if More than $N_{k}$ sub-channels detect the busy state. then
21:
$T_{s e n s e c o u n t} = T_{s e n s e c o u n t} + 1$ .
22:
if The re-sensing time reaches R then
23:
$f l a g_{s} = 0$ .
24:
end if
25:
end if
26:
end while
27:
if current opportunity length $L > (T_{s e n s e c o u n t} \cdot T_{s e n} + δ_{T})$ then $f l a g_{f} = 0$ .
28:
end if
29:
if $f l a g_{t}$ , $f l a g_{s}$ , and $f l a g_{f}$ equal 1 then
30:
Summarize throughput for this opportunity.
31:
end if
32:
end while
33:
end while
34:
end while
35:
Calculate the simulation throughput value $T h_{U A V}$ .