CN112468205B - Backscatter safety communication method suitable for unmanned aerial vehicle - Google Patents

Backscatter safety communication method suitable for unmanned aerial vehicle Download PDF

Info

Publication number
CN112468205B
CN112468205B CN202010023743.6A CN202010023743A CN112468205B CN 112468205 B CN112468205 B CN 112468205B CN 202010023743 A CN202010023743 A CN 202010023743A CN 112468205 B CN112468205 B CN 112468205B
Authority
CN
China
Prior art keywords
unmanned aerial
aerial vehicle
equipment
backscattering
backscatter
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010023743.6A
Other languages
Chinese (zh)
Other versions
CN112468205A (en
Inventor
杨鲲
蔡兴鹏
赵毅哲
胡杰
刘亮元
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
University of Electronic Science and Technology of China Zhongshan Institute
Original Assignee
University of Electronic Science and Technology of China Zhongshan Institute
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by University of Electronic Science and Technology of China Zhongshan Institute filed Critical University of Electronic Science and Technology of China Zhongshan Institute
Priority to CN202010023743.6A priority Critical patent/CN112468205B/en
Publication of CN112468205A publication Critical patent/CN112468205A/en
Application granted granted Critical
Publication of CN112468205B publication Critical patent/CN112468205B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/14—Relay systems
    • H04B7/15—Active relay systems
    • H04B7/185—Space-based or airborne stations; Stations for satellite systems
    • H04B7/18502—Airborne stations
    • H04B7/18506—Communications with or from aircraft, i.e. aeronautical mobile service
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/318—Received signal strength
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/391—Modelling the propagation channel
    • H04B17/3912—Simulation models, e.g. distribution of spectral power density or received signal strength indicator [RSSI] for a given geographic region
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/20—Network architectures or network communication protocols for network security for managing network security; network security policies in general

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Computer Security & Cryptography (AREA)
  • Electromagnetism (AREA)
  • General Physics & Mathematics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Astronomy & Astrophysics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Quality & Reliability (AREA)
  • Computer Hardware Design (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Radio Relay Systems (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention discloses a backscattering safety communication method suitable for an unmanned aerial vehicle, which comprises the following steps: determining a network model, a network communication mode and a protocol; simplifying the network model, and discretizing the continuous time; solving the received signal power of each backscattering device on the ground; solving the energy which can be harvested by each backscattering device at any time, solving the backscattering channel capacity, and solving the eavesdropping channel capacity of each eavesdropper; defining an optimization target as maximizing the fair throughput of the backscattering equipment to obtain an optimization target expression and the constraint thereof; simplifying the optimization target problem, and solving the optimization target problem by adopting a block coordinate descent method; the method comprises three parts of unmanned aerial vehicle flight path design, equipment backscattering factor distribution and equipment time slot distribution, and simultaneously the problems of ground equipment harvesting energy and communication safety are considered; in addition, the fairness and the safety of data transmission of a plurality of devices are guaranteed while the energy supply of a plurality of passive devices on the ground is realized.

Description

Backscatter safety communication method suitable for unmanned aerial vehicle
Technical Field
The invention relates to the technical field of communication, in particular to a backscattering safety communication method.
Background
At present, the demand of wireless communication on energy is remarkably increased, and among various energy supply communication technologies, a backscattering communication technology is an energy-saving, economic and efficient communication technology with strict energy limitation and prospect, and is very suitable for being applied to large-scale low-cost Internet of things equipment; an Unmanned Aerial Vehicle (UAV) is used as a low-altitude aircraft with high mobility, is widely applied to various fields, and is particularly tightly combined with the communication industry; the low-power consumption Internet of things equipment lacks energy consumption to encrypt data, so that information is easy to hijack by a malicious eavesdropper, and the channel coding theorem provides a lightweight but effective mode for ensuring safe communication by enabling the information transmission rate of a legal communication pair to be higher than the capacity of an eavesdropping channel. However, in the prior art, data transmission in a drone-assisted backscatter communication network while ensuring information security and achieving energy acquisition has not been considered.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a backscattering safety communication method suitable for an unmanned aerial vehicle.
The technical scheme adopted by the invention for solving the technical problems is as follows: .
A backscatter security communication method suitable for unmanned aerial vehicles is characterized by comprising the following steps:
(1) determining a network model and determining a network communication mode and a protocol;
(2) simplifying the network model and discretizing the continuous time;
(3) the position of the unmanned aerial vehicle in the air is known, and the received signal power of each backscattering device on the ground is obtained;
(4) assuming that reflection factors of each piece of reverse equipment on the ground are known, solving the energy which can be harvested by each piece of reverse scattering equipment at any moment, solving the capacity of a reverse scattering channel, and solving the capacity of an eavesdropping channel of each eavesdropper;
(5) defining an optimization target as maximizing the fair throughput of the backscattering equipment to obtain an optimization target expression and the constraint thereof;
(6) and simplifying the optimization target problem, and solving the optimization target problem by adopting a block coordinate descent method.
Preferably, the step (1) specifically comprises the following sub-steps:
(11) the network model is assumed to be composed of an unmanned aerial vehicle, a plurality of ground backscattering devices and a plurality of ground wiretapping devices. Determining the quantity and position coordinates of the backscatter devices and the eavesdropping devices, and simultaneously determining the emission power of the unmanned aerial vehicle, the maximum flight speed of the unmanned aerial vehicle, the flight starting position and the regression position of the unmanned aerial vehicle, the channel noise power, the distance between each backscatter device and the eavesdropping device, the energy conversion efficiency coefficient of the backscatter device and the energy threshold value obtained by the backscatter device;
(12) And the unmanned aerial vehicle collects the information carried by the ground backscatter equipment in a backscatter communication mode, and the information is used as a transmitter of the carrier wave and a receiver of the information. The unmanned aerial vehicle is communicated with the ground backscattering equipment in a time division multiplexing protocol mode, and the task flight time of the unmanned aerial vehicle is determined. The downlink carrier signal of the unmanned aerial vehicle can be used for information modulation of ground backscattering equipment and can also be used for energy acquisition of the ground equipment.
Preferably, the step (5) specifically comprises the following sub-steps:
(51) for each backscattering device, enough energy needs to be harvested for other work tasks of the device, and energy constraint conditions are obtained;
(52) for each backscattering device, when the backscattering device is awakened to communicate with the unmanned aerial vehicle, the safety of information transmission needs to be ensured, and a safety communication constraint condition is obtained;
(53) considering that a plurality of backscattering devices on the ground participate in communication, in order to ensure the fairness of multi-device communication, an objective function of maximizing the minimum throughput value in the plurality of devices is adopted;
(54) and obtaining an optimization target problem.
Preferably, the method according to claim 1, characterized in that said step (6) comprises in particular the sub-steps of:
(61) Simplifying the optimization target problem;
(62) fixing the flight path of the unmanned aerial vehicle, allocating equipment time slots, and solving equipment backscattering factors;
(63) time slot allocation of fixed equipment and equipment backscattering factors are carried out, and the flight path of the unmanned aerial vehicle is solved;
(64) fixing the flight track of the unmanned aerial vehicle and the equipment backscattering factor, and solving equipment time slot allocation;
(65) and carrying out joint design solution according to the step (61), the step (62), the step (63) and the step (64).
The invention has the beneficial effects that: the method comprises three parts of unmanned aerial vehicle flight path design, equipment backscattering factor distribution and equipment time slot distribution, and can also take the problems of ground equipment harvesting energy and communication safety into consideration; in addition, the fairness and the safety of data transmission of a plurality of devices are guaranteed while the energy supply of a plurality of passive devices on the ground is realized.
Drawings
The invention is further illustrated with reference to the following figures and examples.
FIG. 1 is a flow chart of a method of the present invention;
fig. 2 is a schematic diagram of a communication network model of the present invention.
Detailed Description
A backscatter secure communication method suitable for unmanned aerial vehicles is characterized by comprising the following steps:
(1) Determining a network model and determining a network communication mode and a protocol;
(2) simplifying the network model and discretizing the continuous time;
(3) the position of the unmanned aerial vehicle in the air is known, and the received signal power of each backscattering device on the ground is obtained;
(4) assuming that reflection factors of each piece of reverse equipment on the ground are known, solving the energy which can be harvested by each piece of reverse scattering equipment at any moment, solving the capacity of a reverse scattering channel, and solving the capacity of an eavesdropping channel of each eavesdropper;
(5) defining an optimization target as maximizing the fair throughput of the backscattering equipment to obtain an optimization target expression and the constraint thereof;
(6) and simplifying the optimization target problem, and solving the optimization target problem by adopting a fast coordinate descent method.
The method mainly relates to three parts of unmanned aerial vehicle flight path design, equipment backscattering factor distribution and equipment time slot distribution, and can give consideration to the problems of ground equipment harvesting energy and communication safety; in addition, the energy supply to a plurality of passive devices on the ground is realized, meanwhile, the fairness and the safety of data transmission of the devices are ensured, and the optimization of resource scheduling is realized.
The step 1 specifically comprises the following sub-steps:
(11) Assuming that there are K backscatter devices in the UAV based safe backscatter network model, wherein
Figure GDA0003557168230000051
There are also M eavesdropping devices, among which
Figure GDA0003557168230000052
The drone is destined to collect user information for K devices in the area, where the maximum speed at which the drone flies is vmaxThe transmission power of the carrier signal of the unmanned aerial vehicle is Pt，uThe channel noise power is
Figure GDA0003557168230000053
The distance between each backscatter device and the eavesdropping device being dkm＝||bk-emI, where i | · | |, represents the euclidean distance between a pair of vectors. Energy conversion efficiency coefficient of the backscatter device is ηkThe backscatter device obtains an energy threshold of Eth；
(12) The unmanned aerial vehicle collects information carried by the ground backscatter devices in a backscatter communication mode, and the information is used as a transmitter of the carrier wave and a receiver of the information. The unmanned aerial vehicle carries out carrier wave emission in a downlink mode and carries out information receiving in an uplink mode, the unmanned aerial vehicle is communicated with the ground backscatter devices in a time division multiplexing protocol mode, the total working time of the UAV is T, but only one backscatter device is awakened at any time to carry out information transmission with the unmanned aerial vehicle; in addition, the downlink carrier signal of the unmanned aerial vehicle can be used for information modulation of ground backscatter equipment and can also be used for ground equipment to obtain energy.
Simplifying the network model to discretize the continuous timeMelting; considering that the unmanned aerial vehicle has continuous track flight and involves infinite variables in solving the problem, the model is simplified, and the total working time T is discretized into N points, namely T is Nt, wherein T is very small. Suppose the 3D coordinate of the UAV at the nth time slot is (u [ n ]]，dh) Wherein d ishFor the fixed height of unmanned aerial vehicle flight. Then in the nth time slot, the distance between the drone and the ground device k can be expressed as
Figure GDA0003557168230000054
Considering time division multiplexing protocol, in the nth time slot, a is usedk[n]1 means that device k is activated to upload its information to the drone, and similarly, has ak[n]0 means that the device k is in a deep sleep state. To avoid collision, only one BD can be activated at most at a time, so
Figure GDA0003557168230000061
The discretization can effectively reduce the time and space cost of the algorithm, and improve the classification clustering capability and the anti-noise capability of the system to the samples.
And (4) calculating the received signal power of each backscattering device on the ground under the condition that the air position of the unmanned aerial vehicle is known. In the nth time slot, the position of the unmanned plane is (u [ n ]]，dh). Let us assume that there is a Los channel between the drone and the ground device and the path loss exponent is 2. The corresponding power received by the device k in the time slot is P r，k[n]＝Pt，u/Ωuk[n]Wherein Ω isuk[η]＝Ω0(duk[n]/d0)2，Ω0Denotes a reference distance d0Path loss when.
Assuming that reflection factors of each piece of reverse equipment on the ground are known, solving the energy which can be harvested by each piece of reverse scattering equipment in any time slot, solving the capacity of a reverse scattering channel, and solving the capacity of an eavesdropping channel of each eavesdropper; suppose Γk[n]∈[0，1]Is used for indicating the reflection coefficient of a backscattering device k in a k time slot, and the power of a modulation signal reflected in the time slot is known as gammak[n]Pr，k[n]Therefore, it is
Figure GDA0003557168230000062
Expressed as the backscatter channel capacity of device k with drone at time slot n, where
Figure GDA0003557168230000063
Is the channel noise power; for the carrier signal which is not reflected, the backscattering equipment can harvest the carrier signal as energy, and the energy which can be harvested in the whole nth time slot is Ek[n]＝(1-Γk[n])ηkPr，k[η]t; the information reflected by the back scattering device k is modulated and can be simultaneously stolen and heard by other eavesdropping devices, so the back scattering channel capacity of the device k and the eavesdropping device m in the nth time slot is equal to
Figure GDA0003557168230000064
The step 5 specifically comprises the following sub-steps:
(51) for each backscattering device, enough energy needs to be harvested for other work tasks of the device, and energy constraint conditions are obtained; assuming that the minimum energy required for the device k to harvest during the entire working time is, therefore
Figure GDA0003557168230000071
(52) For each backscattering device, when the backscattering device is awakened to communicate with the unmanned aerial vehicle, the safety of information transmission needs to be ensured, and a safety communication constraint condition is obtained; for the reflection information modulated and reflected by the backscattering equipment, the reflection information can be intercepted by the unmanned aerial vehicle and the interception equipment at the same time when Cku[n]≥Ckm[n]If device k is represented by Cku[n]The information is transmitted at a rate that is not eavesdropped by an eavesdropping device. On the contrary, when Cku[n]＜Ckm[n]Information may be leaked to the eavesdropping device m; therefore, introduce the constraint condition of secure communication, have
Figure GDA0003557168230000072
The method improves the communicationThe security of (2).
(53) Considering that a plurality of backscattering devices on the ground participate in communication, in order to ensure the fairness of multi-device communication, an objective function of maximizing the minimum throughput value in the plurality of devices is adopted; the achievable throughput of the device k is
Figure GDA0003557168230000073
Considering the fairness of information transfer by a plurality of ground devices, an optimization goal is defined to maximize the fair throughput of the backscatter devices, i.e.
Figure GDA0003557168230000074
(54) Obtaining an optimization target problem, wherein the optimization target expression is shown as a formula (P1), wherein RfairExpressed as the minimum information rate among all backscatter devices, as shown in equation (P1-a); the expression (P1-b) expresses that no information is leaked to the eavesdropping device during the communication; the equations (P1-c) and (P1-d) are the velocity constraint and the initial regression position constraint of the unmanned plane flight; the formula (P1-e) and the formula (P1-f) define a time division multiplexing protocol mode; the formula (P1-g) is the device reflection factor coefficient range; the formula (P1-h) expresses that for each device k it requires the least harvest to E thThe energy of (a);
(P1)：
Figure GDA0003557168230000081
Figure GDA0003557168230000082
Figure GDA0003557168230000083
||u[n+1]-u[n]||≤dΔ，n＝1，..，N-1， (P1-c)
u[1]＝u[N]＝ubegin， (P1-d)
Figure GDA0003557168230000084
Figure GDA0003557168230000085
Figure GDA0003557168230000086
Figure GDA0003557168230000087
(6) simplifying the optimization objective problem, and solving the optimization objective problem by adopting a fast coordinate descent method according to the optimization objective problem, wherein the steps are as follows:
(61) simplifying the optimization target problem; for constraints (P1-f), scaling to continuous variable constraints
Figure GDA0003557168230000088
For the constraint (P1-b), it can be equivalently converted into a logarithmic function property
Figure GDA0003557168230000089
(62) Fixed unmanned aerial vehicle trajectory { u [ n ]]1, …, N and slot allocation factor ak[n]1, …, N, K1, …, K, solving for the backscattering device scattering factor { Γk[n]And l N is 1, …, N, K is 1, …, K, the function is a convex function, and an optimal solution can be obtained by adopting a convex optimization method.
(63) Fixed backscatter device scattering factor { Γk[n]1, …, N, K1, …, K and slot allocation factor { a |k[n]And solving the unmanned aerial vehicle track { u [ N ] for 1, …, N, K for 1, … and K }, wherein N is equal to 1, …, N, K is equal to 1, and N is equal to K]I N is 1, …, N, the function is a non-convex function, and the auxiliary variable q is introduced firstuk[n]And let it replace that in P1
Figure GDA00035571682300000810
Figure GDA0003557168230000091
The non-convex constraints (P1-a) and (P1-h) are converted into convex constraints by processing the convex constraints by a method of first-order Taylor expansion
Figure GDA0003557168230000092
And
Figure GDA0003557168230000093
(P2)：
Figure GDA0003557168230000094
Figure GDA0003557168230000095
Figure GDA0003557168230000096
Figure GDA0003557168230000097
(P1-c)，(P1-d)，(1.3)
p2 is a convex problem, and a convex optimization method can be adopted to obtain an optimal solution.
(64) Fixed unmanned aerial vehicle trajectory { u [ n ]]1, …, N and backscatter device scattering factor { Γ k[n]1, …, N, K1, …, K, solving for the slot allocation factor ak[η]|n＝1，…N, K is 1, …, K, which is a convex function, and the optimal solution can be obtained by using a convex optimization method. For the obtained ak[n]Existence of
Figure GDA0003557168230000098
Let us
Figure GDA0003557168230000099
And
Figure GDA00035571682300000910
to satisfy (P1-e) and (P1-f).
(65) Carrying out alternate iterative solution through the step 62, the step 63 and the step 64 until the objective function value is converged; the method comprises the following steps:
one, setting an initial feasible solution { u }(0)[n]}，
Figure GDA00035571682300000911
And initial relaxation variables
Figure GDA00035571682300000912
Derived from the initial feasible solution
Figure GDA00035571682300000913
Is provided with
Figure GDA00035571682300000914
And i ← 0;
II, updating i ← i + 1;
three, given { u(i-1)[n]}，
Figure GDA0003557168230000101
Solving by said step 62
Figure GDA0003557168230000102
Fourth, update
Figure GDA0003557168230000103
Fifthly, setting
Figure GDA0003557168230000104
Solving for { u } through said step 63(i)[n]}，
Figure GDA0003557168230000105
Sixthly, setting
Figure GDA0003557168230000106
{u(i)[n]Is solved by said step 64
Figure GDA0003557168230000107
And
Figure GDA0003557168230000108
seventh, judge
Figure GDA0003557168230000109
If yes, performing a second step; if not, returning the result
Figure GDA00035571682300001010
{u(i)[η]}，
Figure GDA00035571682300001011
The above embodiments do not limit the scope of the present invention, and those skilled in the art can make equivalent modifications and variations without departing from the overall concept of the present invention.

Claims (2)

1. A backscatter secure communication method suitable for unmanned aerial vehicles is characterized by comprising the following steps:
(1) Determining a network model and determining a network communication mode and a protocol;
(2) simplifying the network model and discretizing the continuous time;
(3) the position of the unmanned aerial vehicle in the air is known, and the received signal power of each backscattering device on the ground is obtained;
(4) the reflection factors of all the reverse devices on the ground are known, the energy which can be harvested by all the reverse scattering devices at any moment is obtained, the capacity of a reverse scattering channel is obtained, and the capacity of an eavesdropping channel of each eavesdropper is obtained;
(5) defining an optimization target as maximizing the fair throughput of the backscattering equipment to obtain an optimization target expression and the constraint thereof;
(6) simplifying the optimization target problem, and solving the optimization target problem by adopting a block coordinate descent method;
the step (5) comprises the following steps:
(51) for each backscattering device, energy is required to be harvested for other work tasks of the device, and energy constraint conditions are obtained; suppose that during the entire working time, the device
Figure DEST_PATH_IMAGE001
The minimum energy to be harvested is
Figure 938687DEST_PATH_IMAGE002
Therefore it has
Figure DEST_PATH_IMAGE003
；
(52) For each backscattering device, when the backscattering device is awakened to communicate with the unmanned aerial vehicle, the safety of information transmission needs to be ensured, and a safety communication constraint condition is obtained; for the reflection information modulated and reflected by the backscattering equipment, the reflection information can be intercepted by the unmanned aerial vehicle and the interception equipment at the same time
Figure 753059DEST_PATH_IMAGE004
If the equipment is
Figure 778784DEST_PATH_IMAGE001
To be provided with
Figure DEST_PATH_IMAGE005
Is transmitted at a rate such that the information is not eavesdropped by an eavesdropping device, but, conversely, when
Figure 45817DEST_PATH_IMAGE006
Information may be leaked to the wiretapping apparatus
Figure DEST_PATH_IMAGE007
(ii) a Therefore, introduce the constraint condition of secure communication, have
Figure 195782DEST_PATH_IMAGE008
；
(53) Adopting an objective function which maximizes a minimum throughput value among the plurality of devices; device
Figure 864661DEST_PATH_IMAGE001
The achievable throughput is
Figure DEST_PATH_IMAGE009
(ii) a Considering the fairness of information transfer by a plurality of ground devices, an optimization goal is defined to maximize the fair throughput of the backscatter devices, i.e.
Figure 795708DEST_PATH_IMAGE010
；
(54) Obtaining an optimization target problem, wherein the optimization target expression is shown as a formula (P1), wherein
Figure DEST_PATH_IMAGE011
Expressed as the minimum information rate among all backscatter devices, as shown in equation (P1-a); the expression (P1-b) expresses that no information is leaked to the eavesdropping device during the communication; the equations (P1-c) and (P1-d) are the velocity constraint and the initial regression position constraint of the unmanned plane flight; the formula (P1-e) and the formula (P1-f) define a time division multiplexing protocol mode; the formula (P1-g) is the device reflection factor coefficient range; formula (P)1-h) for each device
Figure 736988DEST_PATH_IMAGE001
Which need to be harvested at a minimum
Figure 474000DEST_PATH_IMAGE012
The energy of (a);
Figure DEST_PATH_IMAGE013
；
the step (6) comprises the following steps:
(61) simplifying the optimization target problem;
(62) Fixing the flight path of the unmanned aerial vehicle, allocating equipment time slots, and solving equipment backscattering factors;
(63) time slot allocation of fixed equipment and equipment backscattering factors are carried out, and the flight path of the unmanned aerial vehicle is solved;
(64) fixing the flight track of the unmanned aerial vehicle and the equipment backscattering factor, and solving equipment time slot allocation;
(65) and carrying out joint design solution according to the step (61), the step (62), the step (63) and the step (64).
2. The method according to claim 1, characterized in that said step (1) comprises in particular the sub-steps of:
(11) the network model is assumed to be composed of an unmanned aerial vehicle, a plurality of ground backscatter devices and a plurality of ground eavesdropping devices, the number and position coordinates of the backscatter devices and the eavesdropping devices are determined, and meanwhile, the emission power of the unmanned aerial vehicle, the maximum flight speed of the unmanned aerial vehicle, the flight starting position and the flight returning position of the unmanned aerial vehicle, the channel noise power, the distance between each backscatter device and the eavesdropping device, the energy conversion efficiency coefficient of the backscatter device and the energy threshold value obtained by the backscatter device are determined;
(12) the unmanned aerial vehicle collects information carried by ground backscatter equipment in a backscatter communication mode, the unmanned aerial vehicle is used as a transmitter of a carrier wave and a receiver of the information, the unmanned aerial vehicle communicates with the ground backscatter equipment in a time division multiplexing protocol mode to determine the task flight time of the unmanned aerial vehicle, and downlink carrier signals of the unmanned aerial vehicle can be used for the ground backscatter equipment to perform information modulation and can also be used for the ground equipment to acquire energy.
CN202010023743.6A 2020-01-09 2020-01-09 Backscatter safety communication method suitable for unmanned aerial vehicle Active CN112468205B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010023743.6A CN112468205B (en) 2020-01-09 2020-01-09 Backscatter safety communication method suitable for unmanned aerial vehicle

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010023743.6A CN112468205B (en) 2020-01-09 2020-01-09 Backscatter safety communication method suitable for unmanned aerial vehicle

Publications (2)

Publication Number Publication Date
CN112468205A CN112468205A (en) 2021-03-09
CN112468205B true CN112468205B (en) 2022-05-27

Family

ID=74832749

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010023743.6A Active CN112468205B (en) 2020-01-09 2020-01-09 Backscatter safety communication method suitable for unmanned aerial vehicle

Country Status (1)

Country Link
CN (1) CN112468205B (en)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113255218B (en) * 2021-05-27 2022-05-31 电子科技大学 Unmanned aerial vehicle autonomous navigation and resource scheduling method of wireless self-powered communication network
CN113641184B (en) * 2021-07-27 2024-03-19 电子科技大学长三角研究院(湖州) 3D path planning and resource scheduling method suitable for multifunctional communication of unmanned aerial vehicle
CN114124705B (en) * 2021-11-26 2024-02-02 重庆邮电大学 Max-min fairness-based resource allocation method for unmanned aerial vehicle auxiliary backscatter communication system

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109640257A (en) * 2019-01-23 2019-04-16 中国人民解放军陆军工程大学 A kind of IOT network security transmission method based on unmanned plane

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8874477B2 (en) * 2005-10-04 2014-10-28 Steven Mark Hoffberg Multifactorial optimization system and method
WO2014036001A1 (en) * 2012-08-27 2014-03-06 University Of Houston System System and method for securing backscatter wireless communication
US11102650B2 (en) * 2018-05-15 2021-08-24 Noodle Technology Inc. Secure beacon identity

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109640257A (en) * 2019-01-23 2019-04-16 中国人民解放军陆军工程大学 A kind of IOT network security transmission method based on unmanned plane

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
Relay selection for secure backscatter;Xiaowei Wang等;《Electronics Letters》;20150630;第951-952页 *
Throughput Maximization for UAV-Aided Backscatter Communication Networks;Meng Hua 等;《IEEE Transactions on Communications》;20191214;第68卷(第2期);第1254-1269页 *
反向散射通信技术与物联网;王公仆等;《物联网学报》;20170630(第01期);全文 *
无人机自组网研究进展综述;卓琨等;《电信科学》;20150420(第04期);全文 *

Also Published As

Publication number Publication date
CN112468205A (en) 2021-03-09

Similar Documents

Publication Publication Date Title
CN112468205B (en) Backscatter safety communication method suitable for unmanned aerial vehicle
Zhou et al. UAV-enabled mobile edge computing: Offloading optimization and trajectory design
Du et al. Energy-efficient resource allocation in UAV based MEC system for IoT devices
Zhan et al. Aerial–ground cost tradeoff for multi-UAV-enabled data collection in wireless sensor networks
Zhan et al. Energy minimization in Internet-of-Things system based on rotary-wing UAV
CN110730031B (en) Unmanned aerial vehicle track and resource allocation joint optimization method for multi-carrier communication
Jiang et al. Resource allocation and trajectory optimization for UAV-enabled multi-user covert communications
CN110730028B (en) Unmanned aerial vehicle-assisted backscatter communication device and resource allocation control method
Ye et al. Optimization for wireless-powered IoT networks enabled by an energy-limited UAV under practical energy consumption model
CN110138443B (en) Unmanned aerial vehicle flight path and signal transmission power combined optimization method facing wireless relay
CN112532300B (en) Trajectory optimization and resource allocation method for single unmanned aerial vehicle backscatter communication network
CN113490176B (en) Unmanned aerial vehicle communication anti-interference method based on three-dimensional track power optimization
CN110224723A (en) A kind of unmanned plane assisted backscatter Communication System Design method
Jing et al. ISAC from the sky: UAV trajectory design for joint communication and target localization
CN114070379B (en) Unmanned aerial vehicle track optimization and resource allocation method based on safety energy efficiency fairness
Tran-Dinh et al. Energy-efficient trajectory design for UAV-enabled wireless communications with latency constraints
CN112887993A (en) Full-duplex unmanned aerial vehicle base station safety energy efficiency optimization method based on time slot priority
CN115002800A (en) Unmanned aerial vehicle-assisted NOMA (non-orthogonal multiple Access) backscattering communication system and rate maximization method
Patra et al. Optimisation of spectrum and energy efficiency in UAV-enabled mobile relaying using bisection and PSO method
Xue et al. Energy minimization in UAV-aided wireless sensor networks with OFDMA
Guo et al. Energy-efficient full-duplex UAV relaying with trajectory optimization and power control in maritime communication environments
CN115802494A (en) Unmanned aerial vehicle covert communication system track optimization and communication resource allocation method and system
Tao et al. Secrecy Energy Efficiency Maximization for UAV Enabled Communication Systems
CN113691302B (en) Energy efficiency optimization method of multi-rotor unmanned aerial vehicle auxiliary backscatter communication system
CN113641184B (en) 3D path planning and resource scheduling method suitable for multifunctional communication of unmanned aerial vehicle

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant