CN114661063B - Unmanned aerial vehicle emergency communication flight control method - Google Patents
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- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
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Abstract
The invention discloses an unmanned aerial vehicle emergency communication flight control method, and belongs to the technical field of wireless communication. The flight control method comprises the following steps: s1, establishing a total energy consumption function based on unmanned aerial vehicle flight energy consumption and communication transmission energy consumption, establishing a cost energy consumption function based on a minimum successful transmission rate threshold, S2, establishing a global energy consumption function based on the total energy consumption function and the cost energy consumption function, S3, calculating the three-dimensional space distance between the unmanned aerial vehicle and a user when the minimum successful transmission rate is calculated based on the minimum successful transmission rate threshold, defining the distance as a target distance, and calculating an optimal three-dimensional flight control strategy by using the target distance and the global cost function. According to the method, the shortest path from the initial distance of the unmanned aerial vehicle to the target distance of the user is calculated by using the minimum successful transmission rate threshold as the connection reference, so that the problem that in the prior art, the unmanned aerial vehicle only moves in the height direction and has high energy consumption is solved.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to an unmanned aerial vehicle emergency communication flight control method.
Background
The unmanned aerial vehicle can be deployed as a wireless relay or an air base station to enhance a ground wireless communication system in various scenes, such as emergency communication and network access in remote areas, and in the case of emergencies such as tsunamis, earthquakes and the like, the cellular infrastructure cannot support communication services due to equipment damage, the mobile unmanned aerial vehicle can establish a communication link to send data packets to ground users, but when the number of unmanned aerial vehicle and users is large, the problem of serious communication interference exists, so that the improvement of the connection success rate of the communication link and the consideration of the energy consumption of the unmanned aerial vehicle are serious challenges.
Although the prior art solves the problem of unmanned aerial vehicle communication, the displacement of the unmanned aerial vehicle is only the displacement in the height direction, and the optimal solution of the communication transmission rate and the displacement energy consumption of the unmanned aerial vehicle cannot be achieved, so that the problem that the energy consumption of the unmanned aerial vehicle cannot meet the long-time communication service greatly exists in the prior art, and therefore, a flight control method capable of reducing the space three-dimensional movement energy consumption of the unmanned aerial vehicle is needed.
Disclosure of Invention
Aiming at the problem that the unmanned aerial vehicle in the prior art has large energy consumption and cannot meet the long-time communication service, the invention provides a method for controlling the unmanned aerial vehicle to realize the long-time communication service
In order to solve the technical problems, the invention provides the following technical scheme: the unmanned aerial vehicle emergency communication flight control method comprises the following steps: s1, establishing a total energy consumption function based on unmanned aerial vehicle flight energy consumption and communication transmission energy consumption.
A cost energy consumption function is established based on the minimum successful transmission rate threshold.
S2, establishing a global energy consumption function based on the total energy consumption function and the cost energy consumption function.
S3, calculating the three-dimensional space distance between the unmanned aerial vehicle and the user when the minimum successful transmission rate is calculated based on the minimum successful transmission rate threshold, defining the distance as a target distance, and calculating an optimal three-dimensional flight control strategy by using the target distance and the global cost function.
In a further embodiment, in S1, the total energy consumption function E i (t) is:
em,i(t)＝amfi(t)
ew,i(t)＝Pu+ae
Wherein e m,i (t) is flight energy consumption of unmanned aerial vehicle i, e w,i (t) is communication transmission energy consumption of unmanned aerial vehicle i, R i (t) is data transmission rate of unmanned aerial vehicle i at time t, a m is quality of unmanned aerial vehicle, f i (t) is flight distance of unmanned aerial vehicle i, P u is transmission power of unmanned aerial vehicle i, and a e is fixed energy consumption independent of P u.
The cost energy consumption function T i (T) for successful communication is:
Wherein, |h i,k(t)|2 is the channel gain of unmanned plane i and user k at time t, P u is the transmission power of unmanned plane i, R th is the minimum successful transmission rate threshold, B is the transmission bandwidth, σ 2 is the noise power.
In S2, the global energy consumption function J i (t) is:
Ji(t)＝ω1Ei(t)+ω2Ti(t)
Where ω 1 is the weight of E i (T) and ω 2 is the weight of T i (T).
In a further embodiment, in the cost energy consumption function,
Wherein d i,k represents the total distance between unmanned aerial vehicle i and user k, alpha is the path loss index and alpha is more than or equal to 2, g i,k (t) represents the channel fading coefficient of unmanned aerial vehicle i and user k at time t, deltax (t) is the transverse coordinate distance of unmanned aerial vehicle i and user k at time t, deltay (t) is the longitudinal coordinate distance of unmanned aerial vehicle i and user k at time t, deltaz (t) is the vertical coordinate distance of unmanned aerial vehicle i and user k at time t, and the degree of coincidence of actual energy consumption and theoretical energy consumption is further improved by introducing the three-dimensional space distance of user and unmanned aerial vehicle and the channel fading coefficient.
In a further embodiment, in S3, the calculation function of the target distance D i (t) is as follows:
The flight distance f i (t) of the unmanned aerial vehicle is:
In a further embodiment, the channel fading coefficients are processed using a smooth gaussian process of mean regression:
Wherein, Mu g and C are positive real numbers, mu g is the long-term average of a smooth Gaussian process,/>Is the long-term mean velocity of the stationary gaussian process, W 1 (t) is the standard brownian motion.
The beneficial effects are that: compared with the prior art, the invention has at least the following beneficial effects: the method comprises the steps of calculating the optimal three-dimensional flight control strategy by using a global cost function on the basis of calculating the three-dimensional space distance between the unmanned aerial vehicle and the user by using a minimum successful transmission rate threshold as a connection reference, calculating the shortest path from the initial distance between the unmanned aerial vehicle and the user to the target distance, and controlling the three-dimensional space position of the unmanned aerial vehicle so as to obtain the optimal solution of the communication transmission rate and the displacement energy consumption of the unmanned aerial vehicle, thereby solving the problem that the unmanned aerial vehicle only moves in the height direction in the prior art, and the energy consumption is large and can not provide communication service for the disaster-affected user for a long time.
It should be understood that all combinations of the foregoing concepts, as well as additional concepts described in more detail below, may be considered as part of the inventive subject matter so long as such concepts are not mutually inconsistent.
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The drawings are not intended to be drawn to scale unless specifically indicated. In the drawings, each identical or nearly identical component that is illustrated in various figures may be represented by a like numeral. For purposes of clarity, not every component may be labeled in every drawing.
Fig. 1 is a scene model diagram of an unmanned aerial vehicle emergency communication flight control method based on average field game.
Fig. 2 is a schematic flow chart of the present invention.
Fig. 3 is a random distribution of all initial unmanned aerial vehicle mobile base stations and users in an unmanned aerial vehicle emergency communication flight control method based on average field game.
Fig. 4 is a graph comparing flight energy of two baselines in an unmanned aerial vehicle emergency communication flight control method based on average field game.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without creative efforts, based on the described embodiments of the present invention fall within the protection scope of the present invention. Unless defined otherwise, technical or scientific terms used herein should be given the ordinary meaning as understood by one of ordinary skill in the art to which this invention belongs.
The terms first, second and the like in the description and in the claims, are not used for any order, quantity or importance, but are used for distinguishing between different elements. Also, unless the context clearly indicates otherwise, singular forms "a," "an," or "the" and similar terms do not denote a limitation of quantity, but rather denote the presence of at least one. The terms "comprises," "comprising," or the like are intended to cover a feature, integer, step, operation, element, and/or component recited as being present in the element or article that "comprises" or "comprising" does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. "up", "down", "left", "right" and the like are used only to indicate a relative positional relationship, and when the absolute position of the object to be described is changed, the relative positional relationship may be changed accordingly.
The invention provides an unmanned aerial vehicle emergency communication flight control method for controlling three-dimensional space positions of unmanned aerial vehicles so as to obtain optimal solutions of communication transmission rate and unmanned aerial vehicle displacement energy consumption.
The unmanned aerial vehicle emergency communication flight control method comprises the following steps:
step one, constructing a system model:
unmanned aerial vehicle is assembled by A representation; user set, use/> And the N unmanned aerial vehicle base stations share the same channel to perform downlink data transmission at the same time, so that communication services are provided for K users.
Step two, establishing a state equation of the emergency communication system of the whole unmanned aerial vehicle:
Data transmission rate R i,k (t) of unmanned plane i and user k at time t:
Where B is the transmission bandwidth, P u is the transmission power of unmanned aerial vehicle i, σ 2 is the noise power, |h i,k(t)|2 represents the channel gains of unmanned aerial vehicle i and user k at time t.
Step three, establishing a cost function:
s1, establishing a total energy consumption function based on unmanned aerial vehicle flight energy consumption and communication transmission energy consumption.
A cost energy consumption function is established based on the minimum successful transmission rate threshold.
S2, establishing a global energy consumption function based on the total energy consumption function and the cost energy consumption function
Calculating an optimal three-dimensional flight control strategy:
S3, calculating the three-dimensional space distance between the unmanned aerial vehicle and the user when the minimum successful transmission rate is calculated based on the minimum successful transmission rate threshold, defining the distance as a target distance, and calculating an optimal three-dimensional flight control strategy by using the target distance and the global cost function.
The most important of the disaster relief tasks is to ensure long-time communication of the user, so that the optimal solution of the communication transmission rate and the displacement energy consumption of the unmanned aerial vehicle is obtained by calculating the optimal three-dimensional flight control strategy by using a global cost function on the basis of calculating the three-dimensional space distance between the unmanned aerial vehicle and the user by using a minimum successful transmission rate threshold as a connection reference, calculating the shortest path from the initial distance between the unmanned aerial vehicle and the user to the target distance, and controlling the three-dimensional space position of the unmanned aerial vehicle.
In a further embodiment, in S1, the total energy consumption function E i (t) is:
em,i(t)＝amfi(t)
ew,i(t)＝Pu+ae
Wherein e m,i (t) is flight energy consumption of unmanned aerial vehicle i, e w,i (t) is communication transmission energy consumption of unmanned aerial vehicle i, R i (t) is data transmission rate of unmanned aerial vehicle i at time t, a m is quality of unmanned aerial vehicle, f i (t) is flight distance of unmanned aerial vehicle i, P u is transmission power of unmanned aerial vehicle i, and a e is fixed energy consumption independent of P u.
The cost energy consumption function T i (T) for successful communication is:
Where i h i,k(t)|2 is the channel gain of drone i and user k at time t, and R th is the minimum successful transmission rate threshold.
In S2, the global energy consumption function J i (t) is:
Ji(t)＝ω1Ei(t)+ω2Ti(t)
Where ω 1 is the weight of E i (T) and ω 2 is the weight of T i (T).
The weight is set for the total energy consumption function and the cost energy consumption function with successful communication in the global energy consumption function, so that the flying speed of the unmanned aerial vehicle can be adjusted in actual use, and the problem that the unmanned aerial vehicle is limited by the cost energy consumption function to limit the communication establishment speed is solved.
In a further embodiment, the prior art uses only the ideal value of the channel gain to calculate the cost, and does not take into account that the larger the distance between the user and the drone, the lower the effect on the channel gain, and therefore there is a problem that the actual energy consumption is higher than the theoretical energy consumption.
To solve the above problem, in the cost energy consumption function,
Wherein d i,k represents the Euclidean distance between unmanned aerial vehicle i and user k, alpha is the path loss index and alpha is not less than 2, g i,k (t) represents the channel fading coefficient of unmanned aerial vehicle i and user k at time t, deltax (t) is the transverse coordinate distance of unmanned aerial vehicle i and user k at time t, deltay (t) is the longitudinal coordinate distance of unmanned aerial vehicle i and user k at time t, deltaz (t) is the vertical coordinate distance of unmanned aerial vehicle i and user k at time t.
Namely:
By introducing the three-dimensional space distance between the user and the unmanned plane and the channel fading coefficient, the coincidence degree of actual energy consumption and theoretical energy consumption is further improved.
In a further embodiment, in S3, the calculation function of the target distance D i (t) is as follows:
The flight distance f i (t) of the unmanned aerial vehicle is:
The most important of the disaster relief tasks is to ensure long-time communication of the users, so that the minimum successful transmission rate threshold is used as a connection standard, further, flight consumption of the unmanned aerial vehicle is reduced, namely, the distance between the unmanned aerial vehicle and the users is smaller than the target distance, at the moment, the unmanned aerial vehicle does not need to move to reach the minimum energy consumption, and when the unmanned aerial vehicle is at the target distance from the users, the unmanned aerial vehicle does three-dimensional space to move to the target distance, so that the minimum moving distance is achieved, and the energy consumption is reduced.
In a further embodiment, the channel fading coefficients of the communication of the drone with the user may change due to the time-varying channel, since the drone is in flight.
To solve the above problem, a smooth gaussian process of mean regression is used to process the channel fading coefficients:
Wherein, Mu g and C are positive real numbers, mu g is the long-term average of a smooth Gaussian process,/>Is the long-term mean velocity of the stationary gaussian process, W 1 (t) is the standard brownian motion.
By introducing the influence of the time-varying channel on the channel fading coefficient, the theoretical value is more in line with the actual state.
The illustrations provided in the examples below and the setting of specific parameter values in the models are mainly for illustrating the basic idea of the invention and for performing simulation verification on the invention, and in a specific application environment, the actual scene and the requirements can be appropriately adjusted.
As shown in fig. 1, the present invention considers a disaster area of 10km×10Km, which includes 200 unmanned aerial vehicle base stations, 150 users, and a random distribution of the users and unmanned aerial vehicles with a fixed height.
As shown in fig. 4, comparing the flight energy comparison graphs of the two baselines, it can be seen from fig. 4 that each unmanned aerial vehicle finds its own optimal position at the initial time, which results in higher flight energy consumption, but after t=0.2, the flight energy consumption gradually decreases after using the algorithm proposed by the present invention, and becomes lower than the uniform flight pattern after t=0.5. Finally, the N drones reach an optimal position, so that the average flight energy consumption converges to a fixed value, since the energy cost E i (t) of the drone is the total energy consumption of the downlink transmissions and mechanical movements per unit downlink rate, also taking into account the effect of its transmit power, which is the natural power of the base station of the drone, and therefore of the fixed value.
While the invention has been described with reference to preferred embodiments, it is not intended to be limiting. Those skilled in the art will appreciate that various modifications and adaptations can be made without departing from the spirit and scope of the present invention. Accordingly, the scope of the invention is defined by the appended claims.
Claims (3)
1. The unmanned aerial vehicle emergency communication flight control method is characterized by comprising the following steps of:
s1, establishing a total energy consumption function based on unmanned aerial vehicle flight energy consumption and communication transmission energy consumption;
establishing a cost energy consumption function based on a minimum successful transmission rate threshold;
s2, establishing a global energy consumption function based on the total energy consumption function and the cost energy consumption function;
s3, calculating the dimension space distance between the unmanned aerial vehicle and the user when the minimum successful transmission rate is calculated based on the minimum successful transmission rate threshold, defining the distance as a target distance, and calculating an optimal three-dimensional flight control strategy by using the target distance and the global cost function;
In S1, the total energy consumption function E i (t) is:
em,i(t)＝amfi(t)
ew,i(t)＝Pu+ae
Wherein e m,i (t) is flight energy consumption of the unmanned aerial vehicle i, e w,i (t) is communication transmission energy consumption of the unmanned aerial vehicle i, R i (t) is data transmission rate of the unmanned aerial vehicle i at the time t, a m is mass of the unmanned aerial vehicle, f i (t) is flight distance of the unmanned aerial vehicle i, P u is transmission power of the unmanned aerial vehicle i, and a e is fixed energy consumption independent of P u;
the cost energy consumption function T i (T) is:
wherein, |h i,k(t)|2 is the channel gain of unmanned plane i and user k at time t, P u is the transmission power of unmanned plane i, R th is the minimum successful transmission rate threshold, B is the transmission bandwidth, σ 2 is the noise power;
In the function of the cost and energy consumption,
Wherein d i,k represents the total distance between the unmanned aerial vehicle i and the user k, alpha is a path loss index, alpha is equal to or greater than 2, g i,k (t) represents a channel fading coefficient of the unmanned aerial vehicle i and the user k at time t, deltax (t) is a transverse coordinate distance of the unmanned aerial vehicle i and the user k at time t, deltay (t) is a longitudinal coordinate distance of the unmanned aerial vehicle i and the user k at time t, and Deltaz (t) is a vertical coordinate distance of the unmanned aerial vehicle i and the user k at time t;
In S2, the global energy consumption function J i (t) is:
Ji(t)＝ω1Ei(t)+ω2Ti(t)
Where ω 1 is the weight of E i (T) and ω 2 is the weight of T i (T).
2. The unmanned aerial vehicle emergency communication flight control method of claim 1, wherein,
In S3, the calculation function of the target distance D i (t) is as follows:
The flight distance f i (t) of the unmanned aerial vehicle is:
3. The unmanned aerial vehicle emergency communication flight control method of claim 1, wherein,
The channel fading coefficients are processed using a smooth gaussian process of mean regression:
Wherein, Mu g and C are positive real numbers, mu g is the long-term average of a smooth Gaussian process,/>Is the long-term mean velocity of the stationary gaussian process, W 1 (t) is the standard brownian motion.
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| CN113406965A (en) * | 2021-05-31 | 2021-09-17 | 南京邮电大学 | Unmanned aerial vehicle energy consumption optimization method based on reinforcement learning |
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