AU2020102041A4 - Construction and maintenance of satellite-to-ground and inter-satellite laser communication network based on ants colony algorithm - Google Patents
Construction and maintenance of satellite-to-ground and inter-satellite laser communication network based on ants colony algorithm Download PDFInfo
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- 239000003016 pheromone Substances 0.000 claims abstract description 16
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- H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
- H04B10/11—Arrangements specific to free-space transmission, i.e. transmission through air or vacuum
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- H04B10/112—Line-of-sight transmission over an extended range
- H04B10/1123—Bidirectional transmission
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- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/02—Hierarchically pre-organised networks, e.g. paging networks, cellular networks, WLAN [Wireless Local Area Network] or WLL [Wireless Local Loop]
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Abstract
This invention provides a model building and ant colony solving algorithm for
satellite-to-ground laser communication network link establishment and maintenance.
This invention includes: propose mission, modeling based on the construction and
maintenance of satellite-to-ground laser communication links and construct optimized
ants colony algorithm model. The novel ants colony algorithm model is applied to the
dynamic and large space-time scale characteristics of satellite-ground laser
communication network in order to meet the requirements of satellite-ground and
inter-satellite node visibility, link length, transmission system, link establishment and
maintenance. After the algorithm simulation, we can find that the simulation results
are good enough. From the results of the simulation, this invention innovatively
introduces optimized ants colony algorithm into mission planning of satellite and
ground data in order to improve the efficiency of link construction and maintenance
of space laser communication satellite, which improves the applicability of link
construction and maintenance of satellite laser communication and provides reference
for other relevant researches in the future.
1
Analysis of construction and maintenance
of satellite-to-ground and inter-satellite
laser communication
Problem assumptions and simplification
Modeling based on the construction and
maintenance of satellite-to-ground and
inter-satellite laser communication links
Deduce ants algorithm model
Initialize tasks
Initialize satellite-to-ground and inter
satellite resources' nodes
Transfer or search
Figure 1
1
Obtain the topology of the
satellite network under the
current time slice of the satellite
Initialize the parameters
Set the source node as the
current node of the ant. Add it
into the tabu table. The number
of cycles N=N+1
Select the next node. Add it into
the tabu table.
NN
Current node
is the Fi
destination
< node?>
N
Set(allowed)
uof the current
2node is
empty?
1 i Y
Sort the found paths according Fai
to the goodness. Update
pheromone.
4NNmax?
Y
Output the optimal solution
Figure 2
2
Description
Analysis of construction and maintenance of satellite-to-ground and inter-satellite laser communication
Problem assumptions and simplification
Modeling based on the construction and maintenance of satellite-to-ground and inter-satellite laser communication links
Deduce ants algorithm model
Initialize tasks
Initialize satellite-to-ground and inter satellite resources' nodes
Transfer or search
Figure 1
Obtain the topology of the satellite network under the current time slice of the satellite
Initialize the parameters
Set the source node as the currentnode of the ant. Add it into the tabu table. The number of cycles N=N+1
Select the next node. Add it into the tabu table.
Current node is the Fi destination
NN < node?>
N Set(allowed) uof the current 2node is empty?
1 i Y
Sort the found paths according Fai to the goodness. Update pheromone.
4NNmax?
Output the optimal solution
Figure 2
Construction and maintenance of satellite-to-ground and inter-satellite
laser communication network based on ants colony algorithm
As the intermediate node of satellite-to-ground communication, satellite
network is responsible for the distribution, transmission and acquisition
of information. In satellite optical communication, the establishment of
the satellite-to-ground and inter-satellite laser link is one of the most
noteworthy problems.
Construction and maintenance of satellite-to-ground laser communication
network is one of the main tasks of the space laser communication
satellites operational control system. It aims to determine the scheme of
mission for space laser communication satellites on orbit and to arrange
the implementation of communicated activities.
Space laser communication play a key role in the deep space missions.
On the macro level, the satellite communication mission is a process of on-board sensors continuously receiving and releasing data. New mission of transferring data can only be accepted and executed when the sensor has storage space, and data is written to the sensor during execution.
Therefore, satellite communication construction and maintenance is one
of the most important aspects of inter-satellites laser communication, and
its performance has directly influence to the overall mission.
In the laser communication, construction and maintenance of
satellite-to-ground laser and inter-satellites communication network is a
necessary condition. However, the satellite nodes cyclical movement
characteristics around the earth, which causes the dynamic changes of
network topology, frequent switching of intersatellite links, and the
dynamic changes of link length and on-off relationship with time. They
all have a serious impact on the effectiveness and reliability of space
information transmission.
Besides, the rapid growth of the number mission and the limited ground
resources cause the increasing difficulty of communication. When the
satellites' scale is small, satellites' communication construction strategy
can be carried out by traditional methods, such as manual calculations
and Greedy Algorithm, but when the scale increases, the conflict of
competing for resources intensifies. Therefore, the scheduling scheme cannot be derived by simple rules of algorithm. In this context, it is of significance to develop method of laser-link construction and maintenance of ground-to-satellite and inter-satellites.
In order to solve these problems, in this invention, we use ant colony
algorithm model to build and maintain laser communication network. On
the basis of the original ant colony algorithm, we optimize the link
congestion problems. This invention can be applied to the dynamic and
large space-time scale characteristics of satellite-ground laser
communication network in order to meet the requirements of
satellite-ground and inter-satellite node visibility, link length,
transmission system, link establishment and maintenance.
We establish a model for the construction and maintenance of
satellite-to-ground and inter-satellites laser communication link, which
mainly considers constraints such as path, transmission system and
bandwidth delay.
The ants colony algorithm model was used for rapid optimization solution.
The problem model of construction and maintenance of satellite-ground and inter-satellite laser communication link was transformed into ants colony multi-objective solution algorithm.
This problem and ants colony algorithm model can be applied to the
dynamic and large space-time scale characteristics of satellite-ground and
inter-satellite laser communication network in order to meet the
requirements of satellite-ground and inter-satellite node visibility, link
length, transmission system, link establishment and maintenance, etc.
Figure 1 shows the flow chart of our invention, which describes the
process of construction and maintenance of satellite-to-ground and
inter-satellite laser communication.
Figure 2 shows the process of ants colony algorithm used for construction
and maintenance of satellite-to-ground and inter-satellite laser
communication.
Figure 3 shows the satellite distribution in different orbital types, which
describes the mission's background of the invention.
Example
Propose mission
With the development of the deep space mission, the number of the
satellite clusters in orbit is increasing. The topology network of space
optical communication is getting larger and more complex. Traditional
topology network constructions methods include manual calculation
guidance law and greedy calculation, etc. But these algorithms do not
work effectively when solving large-scale problems. In order to overcome
the low efficiency of traditional topology network constructions methods,
this paper improves the traditional ant colony algorithm with
satellite-ground laser communication network as the background of our
task. In this paper, a novel method of cluster topology network
constructions under multi-satellite missions is proposed, and the
communication efficiency is optimized as much as possible.
Modeling
Establish a planning model
Laser-link construction and maintenance optimization is to make the
optimal choice with various constraints. In order to maximize profit, the
objective function should be the longest working time when the satellite
payload passes through the target area:
F=MAXJ s I 1 x`[t, (1)
The result of the above formula has a quantitative outline. In order to
facilitate the analysis of the results, the objective function need to be
dimensionless normalized, we get the new objective function:
F=MAX s (2) a-TW
a is a constant to avoid the objective function value being too large or too
small.
Constraints
Based on our objectives, the constraints related to this Laser-link
construction and maintenance optimization problem model are
summarized:
[tsi, tei];c[a,,b1](3)
ts; + t,"+ t,, : ts ;(4)
ss11;xl =1, Vs EES(5)
x -(Q +qs): C, VseS,Vi,jE I(6)
Constraint (3) ensures that the task execution interval is within the user's
proposed communication window range. Constraint (4) ensures that
only one mission can be executed per resource at any time. Constraint
(5) limits each mission can executed only once. Constraint (6) limits the
amount of data acquired by satellites when they execute a mission that
must not exceed the capacity of the on-board memory.
d min YDI
min(i, j) E p
RB B(7)
VLink(i,j)v,= v,=1,(i,j)E p(8)
V0< c.jy1 (9)
Constraint (7) ensures that the data packets can be transmitted reliably.
Constraint (8) ensures that adjacent satellites are visible to each other,
which can meet the requirements of data transmission. Constraint (9)
limits each mission can executed only once.
Besides, we know that ants colony algorithm uses pheromones to guide
the ant to choose a path. So, in the model, we should also set the
pheromones as constraints. The constrains include distance, transmission
system, delay jitter, bandwidth, visible window, energy, and space
environment. We need to take these constraints into full consideration in
the design of the algorithm in order to optimize the results.
Algorithm Design
Ants colony algorithm simulates that when ants forage for food, they will
leave pheromones on the path. The shorter the path is, the more times that
ant goes back and forth on the path, the higher pheromone concentration
will be. This will attract more ants to take this path so that they can find the shortest foraging path finally.
The probability that the ant moves from one node to another at a certain
time satisfies formula (8).
S(t77,Y (t). r , je allowed pt ToveI t) (10)
[0, others
After ants have finished one cycle, pheromones on each path need to be
updated according to formulas (9) and (10).
rj (t+1)=(1-p)r(t)+ A rz (11)
Arv=Z Ar(12)
Ar represents the pheromone quantity left by the ant k on the link from
node i to node j in this cycle, which is determined by formula (11).
Arj ~,while ant K goes through the link between I and J Arzi =. Lk (13) 0, others
We define the resource constraint vector of the model as pheromone
concentration, which includes link distance, link transmission system,
link delay jitter, etc.
According to the logic of ants colony algorithm, we can find that the
process of the ant path finding is similar to the path planning process in
satellite network, so we apply the improved ant colony algorithm to the construction of satellite-to-ground and inter-satellite laser communication network. The optimization is aiming to solve the defect that the traditional ant colony algorithm is easy to fall into the local optimal solution.
Traditional ant colony algorithm uses the reciprocal of the distance
between nodes as the heuristic function to find the shortest path. This will
possibly cause a large number of services are concentrated in the shortest
path resulting in link congestion. So, we define the concept of link
goodness: r = d(). d(ij) is the quality of service distance between
the actual attribute information and the ideal attribute information on the
link from node i to node j: d(ij) = VZk w1 Wk [(i,j) - Xk (i, j)]2
We use rule of link goodness to change the traditional rule of distance. So,
the formula (10) is changed into the following formula:
ra (t)rj~t , je allowed, p r (t ' (14) se allowedA
[0, others
Then, in order to solve the problem of the behavior of path congestion in
the traditional ants colony algorithm, we define the new state transition
rule, which is a better rule for ants to choose the next node. The principle
is shown in formula (15).
arg maxr?(t)<f (t,q:q; q5 j e- iallowed, (15) Jq>qo
The above is the principle of optimized ants colony algorithm. The
specific process of the algorithm is shown in Figure 2.
Result
This invention sets the number of ants as two thirds of the number of
nodes, and initializes Q, -mi, r(0), qO, a, #,and p. Finally, In the simulation time, this invention gets the good result of maximum network
delay, average network packet loss rate, average network delay jitter and
the laser-link construction success rate of 100%.
Table shows the parameters explanation, which are shown in the
formulas of optimized ants colony algorithm.
Table 1
Parameter Explanation
S Satellite resource set
s Mission set allocated to satellite
I Station set
i andj Number of stations
Boolean variable, is 1 if satellite is available to execute XS
missions, otherwise it is 0
ti The time taken by the satellite s to execute task i
The longest working time when the satellite payload F passes through the target area
TW The mission planning time period
tsi The start time of executing mission i by satellite s
te The end time of executing mission i by satellite s
[ai,b] Time window of executing mission i required by user
The time taken by the satellite s to switch to mission j
ti from i
s Boolean variable, is 1 if satellite is available to execute
missions, otherwise it is 0
Satellites on-board memory occupancy after completing
task i
Satellite s on-board memory capacity required to
completing task j
CS Total memory capacity of satellite s
d Number of the destination node
A path in a satellite network from a source node to a P destination node
v Settelite
c Link capacity
Cost per link
The minimum bandwidth required by the link to transmit B packets
Residual bandwidth on any 2 satellites and
intercommunication links
allowedk The node set that ant k can choose in the next step
The pheromone concentration on the link from node i to r, (t) node j at time t
qj (t) Illumination on the link from node i to node j at time t
The probability that ant k moves from node i to node j at p (t )
time t
The relative importance of pheromone in pathfinding in a ants
The relative importance of heuristic functions in
pathfinding in ants
The quantity of pheromones left by the kth ant on the link
from node ij to node j in this cycle
The total quantity of pheromones on the link from node i H to node j in this cycle
p The volatilization coefficient of pheromones
Q Pheromone strength
Lk The sum of the link lengths contained in the path
r(t) goodness of the link
Xk (iJ) The kth actual Quantity of Service attribute information of the link after normalization
The kth ideal Quantity of Service attribute information on Xk (i,j) the normalized node i to node j link
Wk The weight of the kth Quantity of Service
A random number uniformly distributed between [0,1]
The constant between [0,1]
Selected satellite node
Claims (2)
1. A method of construction and maintenance of satellite-to-ground and
inter-satellite laser communication network based on ants colony algorithm,
characterized in that, in order to overcome the disadvantages of low efficiency
and difficulty of traditional mission planning methods, after reading abundant
relevant documents, introduce ants colony algorithm, which improves the
efficiency and accuracy of construction and maintenance of satellite-to-ground
laser communication network.
2. According to method of claim 1, wherein through establishing a mathematical
model of construction and maintenance of satellite-to-ground laser
communication network, we optimize the traditional ants colony algorithm in
order to avoid the situations that the algorithm falls into local optimal solution
and satellite communication path congests; the algorithm model can be applied
to the dynamic and large space-time scale characteristics of satellite-ground
and inter-satellite laser communication network, the flexibility and
applicability of planning results increase.
Analysis of construction and maintenance of satellite-to-ground and inter-satellite laser communication
Problem assumptions and simplification 2020102041
Modeling based on the construction and maintenance of satellite-to-ground and inter-satellite laser communication links
Deduce ants algorithm model
Initialize tasks
Initialize satellite-to-ground and inter- satellite resources nodes
Transfer or search
Figure 1
Obtain the topology of the satellite network under the current time slice of the satellite
Initialize the parameters
Set the source node as the current node of the ant. Add it into the tabu table. The number 2020102041
of cycles N=N+1
Select the next node. Add it into the tabu table.
N
Current node is the N destination node?
N Set(allowed) of the current Y node is empty?
Y
Sort the found paths according Fail to the goodness. Update pheromone.
N=Nmax?
Y
Output the optimal solution
Figure 2
GEO
Figure 3 LEO
Earth
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