Space-air-ground integrated UAV-assisted IOT data collectioncollection method based on AOI

Patent metadata

Field	Value
Publication number	US-12184389-B2
Application number	US-202217882619-A
Country	US
Kind code	B2
Filing date	Aug 8, 2022
Priority date	Jan 24, 2022
Publication date	Dec 31, 2024
Grant date	Dec 31, 2024

Abstract

A space-air-ground integrated UAV-assisted IoT data collection method based on AoI comprises: constructing a UAV-assisted space-air-ground integrated IoT system, constructing a UAV channel model and an AoI model, establishing an AoI-based UAV-assisted space-air-ground integrated IoT data collection model, transforming a problem into a Markov problem, introducing a neural network to solve a high-dimensional state problem, introducing a deep reinforcement learning algorithm to train UAVs to find optimal collection points, and introducing a matching theory to match the UAVs and IoT devices. To meet the requirement for the timeliness of information collection, the invention finds the optimal configuration of flight parameters of UAVs and deduces the restrictive relation between performance indicators such as AoI, system capacity and energy utilization rate, thus effectively improving the timeliness of information collection, reducing the management and control complexity of the system, and improving the application level of AI in the IoT field.

First claim

What is claimed is:

1. A space-air-ground integrated UAV-assisted IoT data collection method based on AoI, comprising the following steps:
Step 1: constructing a UAV-assisted space-air-ground integrated IoT system;
Step 2: constructing a UAV channel model and an AoI model;
Step 3: establishing an AoI-based UAV-assisted space-air-ground integrated IoT data collection model;
Step 4: transforming a problem into a Markov problem;
Step 5: introducing a neural network to solve a high-dimensional state problem;
Step 6: introducing a deep reinforcement learning algorithm to train UAVs to find optimal collection points; and
Step 7: introducing a matching theory to match the UAVs and IoT devices.

2. The space-air-ground integrated UAV-assisted IoT data collection method based on AoI according to claim 1 , wherein in Step 1, the UAV-assisted space-air-ground integrated IoT system is constructed, the UAV-assisted space-air-ground integrated IoT system comprises a low earth orbit satellite, the low earth orbit satellite is connected to multiple UAVs, the multiple UAVs are connected to multiple IoT devices, data generated by the IoT devices is randomly distributed by time, the size of the data follows Poisson distribution, each UAV flies from an initial location to a preset location to collect data and transmits the collected data to the satellite, and the UAVs are configured in a hovering mode during data collection.

3. The space-air-ground integrated UAV-assisted IoT data collection method based on AoI according to claim 1 , wherein in Step 2,
data transmission between the UAVs and the IoT devices is based on line-of-sight, and a path loss between the UAV n and the IoT device m is:

P
⁢

L

m
,
n

=

2
⁢
0
⁢

log
⁡
(

d

m
,
n

)

+

2
⁢
0
⁢

log
⁡
(
f
)

+

2
⁢
0
⁢

log
⁡
(

4
⁢
π

c

)

+

η

L
⁢
o
⁢
S

wherein, d m,n indicates a distance from the UAV n to the IoT device m, f represents a center frequency, c represents a speed of light, and η LoS represents an additive loss due to shadowing and scattering caused by man-made structures;
a signal plus noise ratio from the IoT device m to the UAV n is expressed as:

Γ

m
,
n

=

p
m

⁢
P
⁢

L

m
,
n

2

σ
2

,

wherein, p m represents power from the IoT device m to the UAV n, and σ 2 represents Gaussian white noise power;
a transmission rate from the IoT device m to the UAV n is calculated by:
R m,n =B log 2 (1+Γ m,n )

wherein, B represents a bandwidth;
AoI is introduced to describe the freshness of sensing data received by the UAVs;
assume when a first matching IoT device generates data, the UAVs start to fly towards a final location; other matching IoT devices generate data randomly in a UAV flight time; when arriving at a target location, the UAVs start to send data; so, the AoI is composed of the UAV flight time and a transmission time from the IoT devices to the UAVs;
the AoI of data received from the IoT device m in a time t is expressed as A m (t):
A m ( t )= t−u m ( t )

u m (t) represents a time when the IoT device m generates data.

4. The space-air-ground integrated UAV-assisted IoT data collection method based on AoI according to claim 1 , wherein in Step 3,
a system AoI minimization problem to be solved is summarized as an optimization problem:

min

b

m
,
n

t

,

x
t
U

,

y
t
U

∑

m
=
1

M

A
m

⁢

(
t
)

s
.
t
.

C
⁢
1
:

b

m
,

Assignees

• Univ Dongguan Technology

Inventors

• Zhang Guobin
• Wei Xin
• Zhao Tiezhu

Classifications

• H04W28/20

  Negotiating bandwidth · CPC title

• H04B7/2041

  Spot beam multiple access · CPC title

• H04B7/18504 Primary

  Aircraft used as relay or high altitude atmospheric platform · CPC title

• Y02T10/40

  Engine management systems · CPC title

• H04B7/18508 Primary

  with satellite system used as relay, i.e. aeronautical mobile satellite service · CPC title