WO2021120425A1 - 一种毫米波全双工无人机通信中继传输方法 - Google Patents
一种毫米波全双工无人机通信中继传输方法 Download PDFInfo
- Publication number
- WO2021120425A1 WO2021120425A1 PCT/CN2020/079336 CN2020079336W WO2021120425A1 WO 2021120425 A1 WO2021120425 A1 WO 2021120425A1 CN 2020079336 W CN2020079336 W CN 2020079336W WO 2021120425 A1 WO2021120425 A1 WO 2021120425A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- uav
- base station
- user
- beamforming vector
- beamforming
- Prior art date
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
- H04B7/18504—Aircraft used as relay or high altitude atmospheric platform
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
- H04B7/0842—Weighted combining
- H04B7/086—Weighted combining using weights depending on external parameters, e.g. direction of arrival [DOA], predetermined weights or beamforming
-
- 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
- H04B7/1851—Systems using a satellite or space-based relay
- H04B7/18515—Transmission equipment in satellites or space-based relays
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/22—Traffic simulation tools or models
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Definitions
- the invention belongs to the technical field of millimeter wave communication, and specifically relates to a communication relay transmission method for millimeter wave full-duplex drones.
- millimeter wave communications with rich frequency band resources (30-300GHz) to provide technical support for post 5G and 6G networks.
- millimeter wave communication has high propagation loss, beamforming technology can be used to effectively improve the signal-to-noise ratio.
- the short wavelength of millimeter wave signals enables the deployment of large-scale antennas in a small space to achieve high array gain.
- ground obstacles often hinder the establishment of line-of-sight links, resulting in severe attenuation of the received signal power even if beamforming technology is applied, which limits the coverage capability of the millimeter wave mobile communication system.
- UAVs can operate in higher air and are more likely to establish line-of-sight communication links with ground users.
- UAVs may be subject to strong interference from nearby facilities and equipment, such as nearby base stations, ground equipment, and other aircraft. Interference control has become a key challenge for UAV communication.
- the combination of the two will have unique advantages.
- the weak diffraction ability and high propagation loss of millimeter-wave signals have limited coverage, while UAVs can be deployed flexibly, build multi-hop networks, and expand the coverage of millimeter-wave communication networks.
- UAVs have a higher operating height than ground base stations, making it easier to establish a line-of-sight link.
- millimeter wave communication uses a large-scale antenna array, and the obtained directional beam can effectively increase the channel gain and effectively suppress the interference of UAVs.
- the space deployment, beamforming, and resource allocation methods of UAVs used as communication relays need to be further explored.
- the present invention proposes a millimeter-wave full-duplex drone communication relay transmission method.
- the full-duplex drone relay technology is adopted in millimeter wave communications, and the drone position, beamforming and power control are optimized by optimizing the position of the drone, beamforming, and power control. Large communication capacity.
- Step 1 Establish a spatial location model of base stations, drones and users
- the spatial position model includes the distance, launch angle and arrival angle from the base station to the UAV; and the distance, launch angle and arrival angle from the UAV to the user;
- (x V , y V , h V ) are the UAV coordinates;
- d B2V is the distance from the base station to the UAV;
- ⁇ B represents the launch pitch angle at the base station;
- ⁇ B represents the launch azimuth angle at the base station;
- ⁇ r represents The pitch angle of arrival at the UAV;
- ⁇ r represents the azimuth angle of arrival at the UAV;
- the distance, launch angle and arrival angle of the drone to the user is the distance, launch angle and arrival angle of the drone to the user:
- (x U ,y U ,0) are the user coordinates
- d V2U is the distance from the drone to the user
- ⁇ t represents the launch pitch angle of the drone
- ⁇ t represents the launch azimuth angle of the drone
- ⁇ U It represents the pitch angle of arrival at the user
- ⁇ U represents the azimuth angle of arrival at the user.
- Step 2 Use the spatial position model to establish a channel model of the downlink communication system from the ground base station to the user with the UAV as the relay;
- the channel model includes the channel matrix from the base station to the UAV link, and the channel matrix from the UAV to the user link;
- the channel matrix H B2V of the link from the base station to the UAV is:
- ⁇ is the large-scale attenuation coefficient, and ⁇ is the normalization constant of the channel matrix power.
- a( ⁇ ) is the pointing vector of the uniform planar array antenna:
- d is the distance between adjacent antennas
- the channel matrix H V2U of the UAV-to-user link is:
- Step 3 Using the channel model in the simultaneous same-frequency full-duplex mode, the ground base station transmits signals to the UAV, and the UAV transmits signals to the user equipment;
- the signal y 1 received by the drone is:
- the signal y 2 received by the user equipment is:
- n 2 is the power at the user equipment The zero mean Gaussian white noise.
- Step four the link to the UAV up rate based on the received signal R B2V UAV reception signal and the user equipment, the base station calculates the UAV to the user rate R V2U up link to the base station and the user may Reach rate R B2U ;
- the reachability rate R B2V of the link from the base station to the UAV is expressed as:
- the reachability rate of the UAV to the user link R V2U is expressed as:
- Step 5 Construct the objective function when the reachability rate R B2U from the base station to the user reaches the maximum, and design the constraint conditions of the UAV position, beamforming and signal power allocation;
- the objective function is as follows:
- the constraint conditions for the distribution of the transmitted signal power are:
- Step 6 Calculate the optimal position of the UAV under the constraints of ideal beamforming
- the array gain under ideal beamforming is substituted into the expressions of the reachability rate of the base station to the UAV link and the UAV to the user link, and the reachability rate of the base station to the UAV under the ideal beamforming is obtained.
- Step 7 Fix the UAV according to the optimal position, and calculate the beamforming vector of the base station, the beamforming vector of the user, and the beamforming vector of the UAV's transmitter and receiver respectively;
- Step 701 Set the optimal beamforming vector of the base station and the user as a pointing vector pointing to the UAV relay;
- Step 702 Initialize the beamforming vector at the receiving end and the beamforming vector at the transmitting end of the UAV relay to the direction vectors pointing to the base station and the user, respectively:
- the step size ⁇ is reduced by design, so that the full-duplex UAV relay self-interference suppression is reduced by ⁇ times in each iteration, and finally approaches 0;
- the counter k is incremented by one, and the optimization process is repeated until convergence; the final beamforming vector optimization result of the UAV relay transmitter is obtained as And the beamforming vector optimization result at the receiving end is
- Step 704 Optimize the beamforming vector results of the transmitting end of the UAV relay respectively And the receiving end beamforming vector optimization result Perform constant modulus normalization:
- Step 8 Substitute the optimal position of the UAV and the optimal beamforming vector at the receiving and sending ends into the objective function, and calculate the optimal transmit power of the base station and UAV to maximize the system reachability and reduce power waste .
- the reachability rates of the base station to the UAV link and the UAV to the user link are calculated respectively:
- This objective function is solved to obtain the optimal position of the UAV and the optimal power setting under the optimal beamforming vector of the transmitting and receiving ends to ensure that the total transmission power of the base station and the UAV is the smallest under the same reachability rate. .
- the optimal transmission power of the base station and UAV is:
- a millimeter-wave full-duplex drone communication relay transmission method of the present invention adopts a full-duplex drone relay, which expands the coverage of millimeter-wave communications and improves the communication capacity of the system;
- a millimeter wave full-duplex UAV communication relay transmission method of the present invention proposes an optimal UAV relay position deployment under an ideal beam
- the invention is a millimeter wave full-duplex UAV communication relay transmission method, and an alternate self-interference suppression algorithm is proposed to alternately optimize the UAV transmission beamforming vector and the receiving beamforming vector;
- a millimeter-wave full-duplex UAV communication relay transmission method of the present invention proposes optimal power control under a given arbitrary UAV relay position and beamforming.
- Figure 1 is a flowchart of a millimeter wave full-duplex UAV communication relay transmission method of the present invention
- Fig. 2 is a downlink communication link model constructed by the present invention for the UAV relay to overcome the obstruction of ground buildings;
- Figure 3 shows the present invention when When, the system reachability rate varies with the base station transmit signal power under several different methods
- Figure 4 shows the present invention when When, the system reachability rate varies with the power of the full-duplex UAV relay transmission signal under several different methods
- Figure 6 shows the present invention when At the time, the system reachability rate varies with the distance from the base station to the user under several different methods.
- the invention discloses a millimeter-wave full-duplex UAV communication relay transmission method.
- the method includes constructing a communication scenario from a ground base station to a ground user using the UAV as a relay, and is designed under ideal beamforming conditions
- the optimal position of the UAV, the beamforming vector is optimized for a given UAV position, and the power of the base station and UAV transmission signal is optimized for the given beamforming vector to reduce the UAV relay self-interference and expand It improves the coverage of millimeter wave communication and improves the communication capacity of the system; it is a full-duplex UAV relay position deployment, beamforming and power control technology.
- Step 1 Establish a spatial location model of base stations, drones and users.
- each planar antenna array is parallel to the xOy plane.
- the user coordinates are (x U ,y U ,0), and the drone coordinates are (x V ,y V ,h V ). From this, the distance, launch angle and arrival angle from the base station to the drone can be obtained:
- d B2V is the distance from the base station to the UAV; ⁇ B represents the launch pitch angle at the base station; ⁇ B represents the launch azimuth angle at the base station; ⁇ r represents the arrival pitch angle at the UAV; ⁇ r represents the drone location Azimuth of arrival;
- d V2U is the distance from the drone to the user
- ⁇ t represents the launch pitch angle of the drone
- ⁇ t represents the launch azimuth angle of the drone
- ⁇ U represents the arrival pitch angle of the user
- ⁇ U represents The azimuth of arrival at the user.
- Step 2 Use the spatial location model to establish a channel model for the downlink communication system from the ground base station to the ground user with the UAV as the relay.
- the base station, drone relay, and user equipment are equipped with uniform planar antenna arrays to overcome path loss.
- the number of base station transmitting antennas is M B ⁇ N B
- the number of user receiving antennas is M U ⁇ N U.
- the human-machine relay is equipped with a transmitting antenna of M t ⁇ N t and a receiving antenna of M r ⁇ N r.
- the base station-to-UAV link and the UAV-to-user link can be expressed as the superposition of multipath components with different launch angles and arrival angles, and air-to-ground communication
- the line-of-sight link is very easy to implement, so it is assumed that the line-of-sight path dominates the space-to-ground transmission.
- the channel matrices of the base station-to-UAV link and the UAV-to-user link are defined as:
- ⁇ is the large-scale attenuation coefficient
- ⁇ is the normalization constant of the channel matrix power
- d is the distance between adjacent antennas
- the far-field condition that is, R ⁇ 2D 2 / ⁇ , is no longer valid in the line-of-sight path of the UAV relay self-interference channel, where R is the distance between the transmitting and receiving antennas, and D is the antenna aperture diameter. Therefore, the self-interference channel needs to use the near-field model:
- r m,n is the distance between the m-th transmitting antenna and the n-th receiving antenna.
- Step 3 In the simultaneous and same frequency full duplex mode, the ground base station transmits a signal to the UAV with a certain power, and the UAV transmits a signal to the user equipment with a certain power.
- the signal received by the drone is:
- n 1 is the power at the UAV Zero-mean Gaussian white noise
- Represents the base station beamforming vector Represents the beamforming vector at the receiving end of the UAV
- n 1 is the power at the UAV The zero mean Gaussian white noise.
- the signal received by the user equipment is:
- n 2 is the power at the user equipment The zero mean Gaussian white noise.
- Step 4 Calculate the reachability rate of the link from the base station to the drone and the link from the drone to the user based on the received signal from the drone and the user equipment.
- the reachability rates of the base station to the UAV link and the UAV to the user link are respectively expressed as:
- the reachability from the base station to the user is the minimum of the base station UAV link and the UAV to user link reachability rate, namely:
- R B2U min ⁇ R B2V ,R V2U ⁇
- Step 5 Construct the objective function: When the reachability of the system reaches the maximum, design the UAV position deployment, beamforming and signal power distribution.
- the analog beamforming vector has constant modulus constraints:
- the objective function is as follows:
- Step 6 Solve the optimal position of the UAV under ideal beamforming conditions
- Step 601 Define that under ideal beamforming, the base station-to-UAV link and the UAV-to-user link can obtain all the array gains, and the self-interference of the full-duplex UAV relay is 0, that is:
- Step 602 Calculate the upper bound of the reachability rate from the base station to the drone and the drone to the user under the ideal beamforming:
- Step 603 Solve the optimal position of the UAV under ideal beamforming:
- the parameters a, b, and c can be calculated by the following formula:
- Step 7 Fix the UAV according to the optimal position, and calculate the beamforming vector of the base station, the beamforming vector of the user, and the beamforming vector of the UAV's transmitter and receiver respectively;
- Step 701 in order to respectively maximize the effective channel gain of the base station to the UAV link And the effective channel gain of the UAV to the user link First calculate the optimal beamforming vector at the base station and the user, which is the pointing vector to the UAV relay:
- Step 702 At the UAV relay, in order to maximize the effective channel gain from the base station to the UAV link And the effective channel gain of the UAV to the user link Initialize the receiving end beamforming vector and the transmitting end beamforming vector of the UAV relay, which are the pointing vectors to the base station and the user respectively:
- Step 704 Given the beamforming vector at the receiving end obtained in step 703 Optimizing the beamforming vector at the transmitting end maximizes the signal power at the receiving end of the UAV-to-user link while suppressing self-interference:
- Step 705 Design a self-interference suppression factor to ensure that the full-duplex UAV relay self-interference is gradually reduced during the iteration process:
- ⁇ is the reduction step size of the self-interference suppression factor, so that the full-duplex UAV relay self-interference suppression is reduced by ⁇ times each iteration, and finally approaches 0;
- Step 707 After the iteration is terminated, the transmission beamforming vector of the UAV relay is obtained And receive beamforming vector And normalize the constant modulus separately:
- Step 8 Substitute the optimal position of the drone in step 6 and the optimal beamforming vectors at the receiving and transmitting ends in step 7 into the objective function of step 5, and calculate the optimal transmit power of the base station and the drone to maximize Improve the reachability of the system and reduce power waste.
- the optimal transmission power of the base station and UAV is:
- the carrier frequency is 38GHz
- the users are distributed on a disk with a radius of 500m with the base station as the center. Inside, all points in the curve are the average reachability rate calculated from the 10 3 random distribution of users and channel generation calculations.
- the "ideal upper bound” corresponds to the upper bound of the reachability rate under the ideal beamforming in step 6; the "invention method” corresponds to the location deployment, beamforming and and The reachability rate obtained by the power control method; “random position + alternating beamforming” corresponds to the UAV randomly distributed in the area (x V ,y V ) ⁇ [0,x U ] ⁇ [0,y U ], and The reachability rate obtained by using the beamforming in step 7 and the optimal power control in step 8; "optimal position + pointing beamforming” corresponds to the UAV deployed in the optimal position in step 6, and the pointing vector is used The reachability rate obtained as the beamforming vector and the optimal power control in step eight.
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Physics & Mathematics (AREA)
- Astronomy & Astrophysics (AREA)
- Aviation & Aerospace Engineering (AREA)
- General Physics & Mathematics (AREA)
- Electromagnetism (AREA)
- Mobile Radio Communication Systems (AREA)
- Radio Relay Systems (AREA)
Abstract
Description
Claims (4)
- 一种毫米波全双工无人机通信中继传输方法,其特征在于,具体步骤如下:步骤一、建立基站、无人机和用户的空间位置模型;空间位置模型包括基站到无人机的距离,发射角和到达角;以及无人机到用户的距离、发射角和到达角;步骤二、利用空间位置模型,建立以无人机为中继的地面基站到用户的下行通信系统的信道模型;信道模型包括基站到无人机链路的信道矩阵,以及无人机到用户链路的信道矩阵;基站到无人机链路的信道矩阵H B2V为:其中,d是相邻天线之间的距离,λ是毫米波波长,特别地,对半波间距天线阵列来说d=λ/2;θ B代表基站处的发射俯仰角;φ B代表基站处的发射方位角;θ r代表无人机处的到达俯仰角;φ r代表无人机处的到达方位角;无人机到用户链路的信道矩阵H V2U为:θ t代表无人机处的发射俯仰角,φ t代表无人机处的发射方位角,θ U代表用户处的到达俯仰角,φ U代表用户处的到达方位角;步骤三、利用信道模型在同时同频全双工模式下,地面基站向无人机发射信号,无人机向用户设备发射信号;无人机接收到的信号y 1为:代表无人机接收端波束赋形向量, 代表基站波束赋形向量,P B为基站发射信号功率;s 1为基站发射信号, 是无人机中继收发天线之间的自干扰信道矩阵, 代表无人机发送端波束赋形向量,P V为无人机发射信号功率;s 2为无人 机发射信号,n 1是无人机处功率为 的零均值高斯白噪声;用户设备接收的信号y 2为:步骤四、根据无人机接收信号以及用户设备的接收信号,计算基站到无人机链路的可达率R B2V,无人机到用户链路的可达率R V2U和基站到用户的可达率R B2U;基站到无人机链路的可达率R B2V表示为:无人机到用户链路的可达率R V2U表示为:基站到用户的可达率R B2U为:R B2U=min{R B2V,R V2U};步骤五、构建基站到用户的可达率R B2U达到最大时的目标函数,设计无人机位置、波束赋形以及信号功率分配的约束条件;目标函数如下:(x V,y V,h V)为无人机坐标;无人机位置范围的约束条件为:(x V,y V)∈[0,x U]×[0,y U](x U,y U,0)为用户坐标;波束赋形的约束条件为:发射信号功率分配的约束条件为:步骤六、在理想波束赋形的约束条件下计算无人机的最优位置;具体如下:首先、定义理想波束赋形下,基站到无人机链路和无人机到用户链路获得全部阵列增益,并且全双工无人机中继的自干扰为0,即:计算公式如下:最后,根据理想波束赋形下的可达率上界,得到无人机最优位置的闭式解:参数a,b,c由如下公式计算:步骤七、按照最优位置固定无人机,分别计算基站的波束赋形向量、用户的波束赋形向量、以及无人机的发送端和接收端的波束赋形向量;步骤八、将无人机最优位置和收发两端的最优波束赋形向量代入目标函数中,计算基站和无人机的最优发射功率,以最大化系统可达率,并减小功率浪费;首先,在无人机收发两端所得的最优波束赋形向量的条件下,分别计算基站到无人机链路和无人机到用户链路的可达率:此时,基站和无人机的最优发射功率为:
- 如权利要求1所述的一种毫米波全双工无人机通信中继传输方法,其特征在于,所述的步骤703具体为:首先,给定发送端波束赋形向量,优化接收端波束赋形向量使得基站到无人机链路的接收端信号功率最大化,同时抑制自干扰:针对自干扰抑制因子,通过设计减小步长κ,使得全双工无人机中继自干扰抑制每次迭代减小κ倍,最终趋近于0;
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201911302590.2A CN111010223B (zh) | 2019-12-17 | 2019-12-17 | 一种毫米波全双工无人机通信中继传输方法 |
CN201911302590.2 | 2019-12-17 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2021120425A1 true WO2021120425A1 (zh) | 2021-06-24 |
Family
ID=70115939
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2020/079336 WO2021120425A1 (zh) | 2019-12-17 | 2020-03-13 | 一种毫米波全双工无人机通信中继传输方法 |
Country Status (2)
Country | Link |
---|---|
CN (1) | CN111010223B (zh) |
WO (1) | WO2021120425A1 (zh) |
Cited By (35)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113316215A (zh) * | 2021-07-13 | 2021-08-27 | 山东协和学院 | 基于无线能量的数据传输方法及系统 |
CN113541757A (zh) * | 2021-07-13 | 2021-10-22 | 北京航空航天大学 | 一种基于毫米波波束赋形的无人机机间安全通信方法 |
CN113708886A (zh) * | 2021-08-25 | 2021-11-26 | 中国人民解放军陆军工程大学 | 无人机抗干扰通信系统及联合轨迹与波束成形优化方法 |
CN113709883A (zh) * | 2021-08-30 | 2021-11-26 | 北京邮电大学 | 一种多无人机辅助工业场景下的动态资源分配方法及装置 |
CN113872655A (zh) * | 2021-10-20 | 2021-12-31 | 上海交通大学 | 一种多播波束赋形快速计算方法 |
CN113939032A (zh) * | 2021-12-06 | 2022-01-14 | 中国通信建设第四工程局有限公司 | 一种无人机通信系统及无人机通信系统资源分配优化方法 |
CN114006645A (zh) * | 2021-09-07 | 2022-02-01 | 西北工业大学 | 一种认知无人机中继辅助的安全传输方法及系统 |
CN114039652A (zh) * | 2021-11-24 | 2022-02-11 | 西北大学 | 基于建筑物几何分析的毫米波抗阻挡多无人机部署方法 |
CN114124264A (zh) * | 2021-11-26 | 2022-03-01 | 江苏科技大学 | 基于智能反射面时变反射相位的无人机信道模型建立方法 |
CN114158010A (zh) * | 2021-12-06 | 2022-03-08 | 中国通信建设第四工程局有限公司 | 无人机通信系统及基于神经网络的资源分配策略预测方法 |
CN114157333A (zh) * | 2021-10-28 | 2022-03-08 | 电子科技大学长三角研究院(湖州) | 一种新型的基于可重构智能表面的共生无线通信系统 |
CN114205050A (zh) * | 2021-12-01 | 2022-03-18 | 南京理工大学 | 无人机隐蔽通信方法及装置 |
CN114221726A (zh) * | 2021-12-16 | 2022-03-22 | 浙江建德通用航空研究院 | ka频段无人机通信系统的下行链路同频干扰表征方法 |
CN114245448A (zh) * | 2021-11-18 | 2022-03-25 | 国网福建省电力有限公司漳州供电公司 | 一种用于电力5g微基站的功率分配方法 |
CN114285461A (zh) * | 2021-12-31 | 2022-04-05 | 东南大学 | 一种移动中继辅助的高速宽带mimo传输方法 |
CN114337902A (zh) * | 2022-01-19 | 2022-04-12 | 北京交通大学 | 一种irs辅助的毫米波多小区间干扰的抑制方法 |
CN114554510A (zh) * | 2022-01-25 | 2022-05-27 | 西北工业大学 | 一种无人机载基站下行链路最优决策参数配置方法 |
CN114553290A (zh) * | 2022-01-07 | 2022-05-27 | 西安理工大学 | 基于mimo结构的无线紫外光通信跟踪保持方法 |
CN114665947A (zh) * | 2022-02-24 | 2022-06-24 | 南京邮电大学 | 一种无人机支持的中继通信系统联合功率控制及位置规划的优化设计方法 |
CN114745031A (zh) * | 2022-03-10 | 2022-07-12 | 西安电子科技大学 | 一种全双工mimo物理层安全传输方法 |
CN115037337A (zh) * | 2022-06-09 | 2022-09-09 | 北京信息科技大学 | 一种智能反射面驱动的多用户协同传输方法 |
CN115118315A (zh) * | 2022-06-15 | 2022-09-27 | 国家工业信息安全发展研究中心 | 一种低复杂度的通信网络系统、方法和可读介质 |
CN115173914A (zh) * | 2022-07-15 | 2022-10-11 | 南通大学 | 一种多智能反射面辅助通信主被动波束赋形迭代优化方法 |
CN115189801A (zh) * | 2022-06-29 | 2022-10-14 | 安徽农业大学 | 一种无人机网络中人工噪声增强的隐蔽通信设计方法 |
CN115209422A (zh) * | 2022-06-17 | 2022-10-18 | 北京邮电大学 | 一种密集城区下无人机基站协同组网参数配置方法 |
CN115225142A (zh) * | 2022-07-18 | 2022-10-21 | 中国人民解放军国防科技大学 | 多无人机通信中用户匹配与频谱资源联合优化方法及系统 |
CN115276747A (zh) * | 2022-07-20 | 2022-11-01 | 华北电力大学(保定) | 无人机辅助无线通信系统中位置和波束向量联合优化方法 |
CN115473560A (zh) * | 2022-08-29 | 2022-12-13 | 西安电子科技大学 | 无人机通信雷达一体全双工中继传输系统、中继方法及节点 |
RU2786043C1 (ru) * | 2021-12-20 | 2022-12-16 | Федеральное государственное казенное военное образовательное учреждение высшего образования "Санкт-Петербургский военный ордена Жукова институт войск национальной гвардии Российской Федерации" | Способ разнесенной передачи |
CN115694602A (zh) * | 2022-09-26 | 2023-02-03 | 电子科技大学 | 一种毫米波全双工无人机通信系统的联合优化方法 |
WO2023109108A1 (zh) * | 2021-12-16 | 2023-06-22 | 中国矿业大学 | 基于全双工中继的uav空中计算系统及轨迹和功率优化方法 |
WO2023142802A1 (zh) * | 2022-01-28 | 2023-08-03 | 广东省新一代通信与网络创新研究院 | 无人机中继系统的调度、轨迹和功率的联合优化方法 |
CN116709255A (zh) * | 2023-08-04 | 2023-09-05 | 中国人民解放军军事科学院系统工程研究院 | 一种不完全信息条件下的中继无人机分布式选择方法 |
CN116744344A (zh) * | 2023-08-15 | 2023-09-12 | 南京邮电大学 | 一种通信监测优化方法、装置、系统及存储介质 |
CN117200845A (zh) * | 2023-09-12 | 2023-12-08 | 深圳大学 | 一种基于低频信号位置感知的毫米波波束对齐方法 |
Families Citing this family (11)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111556460B (zh) * | 2020-04-28 | 2021-07-13 | 西安交通大学 | 非理想毫米波无线供电通信无人机网络的功率分配方法 |
CN111953397B (zh) * | 2020-05-20 | 2021-09-17 | 南京航空航天大学 | 一种面向自由信道的全双工无人机中继通信方法 |
CN111726813B (zh) * | 2020-05-29 | 2023-04-28 | 西安邮电大学 | 一种空中微基站无线回传方法及无线通信系统 |
US11349550B2 (en) * | 2020-08-21 | 2022-05-31 | Huawei Technologies Co., Ltd. | Systems and methods for angular direction indication in wireless communication |
CN112188588B (zh) * | 2020-08-27 | 2022-07-05 | 清华大学 | 基于无人机网络的近海中继通信传输效率优化方法 |
CN112636804B (zh) * | 2020-11-12 | 2022-08-26 | 北京航空航天大学 | 一种基于毫米波阵列的多无人机基站协同传输方法 |
CN113034981B (zh) * | 2021-04-14 | 2022-07-08 | 北京航空航天大学 | 一种不确定信道环境中多中继无人机航迹规划方法、系统及存储介质 |
CN113301532B (zh) * | 2021-05-26 | 2022-04-26 | 中南大学 | 一种用于无人机辅助毫米波应急通信网的信道分配方法 |
CN114025361B (zh) * | 2021-10-20 | 2023-08-15 | 北京航空航天大学 | 面向协同中继任务的多无人机网络拓扑构造与规划方法 |
CN114268903B (zh) * | 2021-12-28 | 2022-09-30 | 北京航空航天大学 | 一种地理信息辅助的无人机中继位置部署以及功率分配方法 |
CN115348610B (zh) * | 2022-10-18 | 2023-03-24 | 成都市以太节点科技有限公司 | 一种毫米波多链路自适应通信方法、电子设备及存储介质 |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108419286A (zh) * | 2018-01-18 | 2018-08-17 | 北京邮电大学 | 一种面对5g无人机通信联合波束与功率的分配算法 |
CN109257089A (zh) * | 2018-09-11 | 2019-01-22 | 北京航空航天大学 | 应用于大范围临空监视系统的远距离低仰角链路传输方法 |
CN109347530A (zh) * | 2018-10-22 | 2019-02-15 | 北京航空航天大学 | 临空阵列通信非正交多址接入上行传输方法 |
US20190116605A1 (en) * | 2017-10-12 | 2019-04-18 | Qualcomm Incorporated | Beam management schemes |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110365386B (zh) * | 2019-07-10 | 2022-06-17 | 中国水利水电第四工程局有限公司 | 无人机的通信增强方法和无人机 |
-
2019
- 2019-12-17 CN CN201911302590.2A patent/CN111010223B/zh active Active
-
2020
- 2020-03-13 WO PCT/CN2020/079336 patent/WO2021120425A1/zh active Application Filing
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20190116605A1 (en) * | 2017-10-12 | 2019-04-18 | Qualcomm Incorporated | Beam management schemes |
CN108419286A (zh) * | 2018-01-18 | 2018-08-17 | 北京邮电大学 | 一种面对5g无人机通信联合波束与功率的分配算法 |
CN109257089A (zh) * | 2018-09-11 | 2019-01-22 | 北京航空航天大学 | 应用于大范围临空监视系统的远距离低仰角链路传输方法 |
CN109347530A (zh) * | 2018-10-22 | 2019-02-15 | 北京航空航天大学 | 临空阵列通信非正交多址接入上行传输方法 |
Non-Patent Citations (1)
Title |
---|
ZHU LIPENG; ZHANG JUN; XIAO ZHENYU; CAO XIANBIN; WU DAPENG OLIVER; XIA XIANG-GEN: "3-D Beamforming for Flexible Coverage in Millimeter-Wave UAV Communications", IEEE WIRELESS COMMUNICATIONS LETTERS, vol. 8, no. 3, 1 June 2019 (2019-06-01), Piscataway, NJ, USA, pages 837 - 840, XP011730964, ISSN: 2162-2337, DOI: 10.1109/LWC.2019.2895597 * |
Cited By (57)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113316215B (zh) * | 2021-07-13 | 2022-10-11 | 山东协和学院 | 基于无线能量的数据传输方法及系统 |
CN113541757A (zh) * | 2021-07-13 | 2021-10-22 | 北京航空航天大学 | 一种基于毫米波波束赋形的无人机机间安全通信方法 |
CN113316215A (zh) * | 2021-07-13 | 2021-08-27 | 山东协和学院 | 基于无线能量的数据传输方法及系统 |
CN113708886A (zh) * | 2021-08-25 | 2021-11-26 | 中国人民解放军陆军工程大学 | 无人机抗干扰通信系统及联合轨迹与波束成形优化方法 |
CN113709883A (zh) * | 2021-08-30 | 2021-11-26 | 北京邮电大学 | 一种多无人机辅助工业场景下的动态资源分配方法及装置 |
CN113709883B (zh) * | 2021-08-30 | 2023-12-05 | 北京邮电大学 | 一种多无人机辅助工业场景下的动态资源分配方法及装置 |
CN114006645A (zh) * | 2021-09-07 | 2022-02-01 | 西北工业大学 | 一种认知无人机中继辅助的安全传输方法及系统 |
CN113872655B (zh) * | 2021-10-20 | 2023-03-21 | 上海交通大学 | 一种多播波束赋形快速计算方法 |
CN113872655A (zh) * | 2021-10-20 | 2021-12-31 | 上海交通大学 | 一种多播波束赋形快速计算方法 |
CN114157333A (zh) * | 2021-10-28 | 2022-03-08 | 电子科技大学长三角研究院(湖州) | 一种新型的基于可重构智能表面的共生无线通信系统 |
CN114245448A (zh) * | 2021-11-18 | 2022-03-25 | 国网福建省电力有限公司漳州供电公司 | 一种用于电力5g微基站的功率分配方法 |
CN114039652A (zh) * | 2021-11-24 | 2022-02-11 | 西北大学 | 基于建筑物几何分析的毫米波抗阻挡多无人机部署方法 |
CN114039652B (zh) * | 2021-11-24 | 2024-03-08 | 西北大学 | 基于建筑物几何分析的毫米波抗阻挡多无人机部署方法 |
CN114124264A (zh) * | 2021-11-26 | 2022-03-01 | 江苏科技大学 | 基于智能反射面时变反射相位的无人机信道模型建立方法 |
CN114124264B (zh) * | 2021-11-26 | 2023-09-22 | 江苏科技大学 | 基于智能反射面时变反射相位的无人机信道模型建立方法 |
CN114205050B (zh) * | 2021-12-01 | 2024-04-09 | 南京理工大学 | 无人机隐蔽通信方法及装置 |
CN114205050A (zh) * | 2021-12-01 | 2022-03-18 | 南京理工大学 | 无人机隐蔽通信方法及装置 |
CN113939032A (zh) * | 2021-12-06 | 2022-01-14 | 中国通信建设第四工程局有限公司 | 一种无人机通信系统及无人机通信系统资源分配优化方法 |
CN113939032B (zh) * | 2021-12-06 | 2024-06-07 | 中国通信建设第四工程局有限公司 | 一种无人机通信系统及无人机通信系统资源分配优化方法 |
CN114158010B (zh) * | 2021-12-06 | 2024-06-07 | 中国通信建设第四工程局有限公司 | 无人机通信系统及基于神经网络的资源分配策略预测方法 |
CN114158010A (zh) * | 2021-12-06 | 2022-03-08 | 中国通信建设第四工程局有限公司 | 无人机通信系统及基于神经网络的资源分配策略预测方法 |
CN114221726A (zh) * | 2021-12-16 | 2022-03-22 | 浙江建德通用航空研究院 | ka频段无人机通信系统的下行链路同频干扰表征方法 |
WO2023109108A1 (zh) * | 2021-12-16 | 2023-06-22 | 中国矿业大学 | 基于全双工中继的uav空中计算系统及轨迹和功率优化方法 |
CN114221726B (zh) * | 2021-12-16 | 2024-04-12 | 浙江建德通用航空研究院 | ka频段无人机通信系统的下行链路同频干扰表征方法 |
RU2786043C1 (ru) * | 2021-12-20 | 2022-12-16 | Федеральное государственное казенное военное образовательное учреждение высшего образования "Санкт-Петербургский военный ордена Жукова институт войск национальной гвардии Российской Федерации" | Способ разнесенной передачи |
CN114285461A (zh) * | 2021-12-31 | 2022-04-05 | 东南大学 | 一种移动中继辅助的高速宽带mimo传输方法 |
CN114285461B (zh) * | 2021-12-31 | 2024-01-30 | 东南大学 | 一种移动中继辅助的高速宽带mimo传输方法 |
CN114553290A (zh) * | 2022-01-07 | 2022-05-27 | 西安理工大学 | 基于mimo结构的无线紫外光通信跟踪保持方法 |
CN114337902B (zh) * | 2022-01-19 | 2023-10-31 | 北京交通大学 | 一种irs辅助的毫米波多小区间干扰的抑制方法 |
CN114337902A (zh) * | 2022-01-19 | 2022-04-12 | 北京交通大学 | 一种irs辅助的毫米波多小区间干扰的抑制方法 |
CN114554510A (zh) * | 2022-01-25 | 2022-05-27 | 西北工业大学 | 一种无人机载基站下行链路最优决策参数配置方法 |
CN114554510B (zh) * | 2022-01-25 | 2023-07-21 | 西北工业大学 | 一种无人机载基站下行链路最优决策参数配置方法 |
WO2023142802A1 (zh) * | 2022-01-28 | 2023-08-03 | 广东省新一代通信与网络创新研究院 | 无人机中继系统的调度、轨迹和功率的联合优化方法 |
CN114665947B (zh) * | 2022-02-24 | 2023-07-25 | 南京邮电大学 | 一种无人机支持的中继通信系统联合功率控制及位置规划的优化设计方法 |
CN114665947A (zh) * | 2022-02-24 | 2022-06-24 | 南京邮电大学 | 一种无人机支持的中继通信系统联合功率控制及位置规划的优化设计方法 |
CN114745031A (zh) * | 2022-03-10 | 2022-07-12 | 西安电子科技大学 | 一种全双工mimo物理层安全传输方法 |
CN114745031B (zh) * | 2022-03-10 | 2024-03-01 | 西安电子科技大学 | 一种全双工mimo物理层安全传输方法 |
CN115037337A (zh) * | 2022-06-09 | 2022-09-09 | 北京信息科技大学 | 一种智能反射面驱动的多用户协同传输方法 |
CN115118315A (zh) * | 2022-06-15 | 2022-09-27 | 国家工业信息安全发展研究中心 | 一种低复杂度的通信网络系统、方法和可读介质 |
CN115209422B (zh) * | 2022-06-17 | 2024-05-24 | 北京邮电大学 | 一种密集城区下无人机基站协同组网参数配置方法 |
CN115209422A (zh) * | 2022-06-17 | 2022-10-18 | 北京邮电大学 | 一种密集城区下无人机基站协同组网参数配置方法 |
CN115189801A (zh) * | 2022-06-29 | 2022-10-14 | 安徽农业大学 | 一种无人机网络中人工噪声增强的隐蔽通信设计方法 |
CN115189801B (zh) * | 2022-06-29 | 2024-04-12 | 安徽农业大学 | 一种无人机网络中人工噪声增强的隐蔽通信设计方法 |
CN115173914A (zh) * | 2022-07-15 | 2022-10-11 | 南通大学 | 一种多智能反射面辅助通信主被动波束赋形迭代优化方法 |
CN115173914B (zh) * | 2022-07-15 | 2023-12-26 | 南通大学 | 一种多智能反射面辅助通信主被动波束赋形迭代优化方法 |
CN115225142B (zh) * | 2022-07-18 | 2023-09-26 | 中国人民解放军国防科技大学 | 多无人机通信中用户匹配与频谱资源联合优化方法及系统 |
CN115225142A (zh) * | 2022-07-18 | 2022-10-21 | 中国人民解放军国防科技大学 | 多无人机通信中用户匹配与频谱资源联合优化方法及系统 |
CN115276747B (zh) * | 2022-07-20 | 2024-05-03 | 华北电力大学(保定) | 无人机辅助无线通信系统中位置和波束向量联合优化方法 |
CN115276747A (zh) * | 2022-07-20 | 2022-11-01 | 华北电力大学(保定) | 无人机辅助无线通信系统中位置和波束向量联合优化方法 |
CN115473560B (zh) * | 2022-08-29 | 2024-02-06 | 西安电子科技大学 | 无人机通信雷达一体全双工中继传输系统、中继方法及节点 |
CN115473560A (zh) * | 2022-08-29 | 2022-12-13 | 西安电子科技大学 | 无人机通信雷达一体全双工中继传输系统、中继方法及节点 |
CN115694602A (zh) * | 2022-09-26 | 2023-02-03 | 电子科技大学 | 一种毫米波全双工无人机通信系统的联合优化方法 |
CN116709255B (zh) * | 2023-08-04 | 2023-10-31 | 中国人民解放军军事科学院系统工程研究院 | 一种不完全信息条件下的中继无人机分布式选择方法 |
CN116709255A (zh) * | 2023-08-04 | 2023-09-05 | 中国人民解放军军事科学院系统工程研究院 | 一种不完全信息条件下的中继无人机分布式选择方法 |
CN116744344B (zh) * | 2023-08-15 | 2023-11-14 | 南京邮电大学 | 无人机主动通信监测优化方法、装置、系统及存储介质 |
CN116744344A (zh) * | 2023-08-15 | 2023-09-12 | 南京邮电大学 | 一种通信监测优化方法、装置、系统及存储介质 |
CN117200845A (zh) * | 2023-09-12 | 2023-12-08 | 深圳大学 | 一种基于低频信号位置感知的毫米波波束对齐方法 |
Also Published As
Publication number | Publication date |
---|---|
CN111010223A (zh) | 2020-04-14 |
CN111010223B (zh) | 2021-04-23 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2021120425A1 (zh) | 一种毫米波全双工无人机通信中继传输方法 | |
Zhu et al. | Millimeter-wave full-duplex UAV relay: Joint positioning, beamforming, and power control | |
Zhang et al. | A survey on 5G millimeter wave communications for UAV-assisted wireless networks | |
CN113973305B (zh) | 搭载于无人机上的智能反射面位置和波束联合优化方法 | |
CN110266362B (zh) | 一种基于毫米波的星群多波束接收的干扰抑制方法 | |
CN113873575B (zh) | 智能反射面辅助的非正交多址无人机空地通信网络节能优化方法 | |
CN109586773B (zh) | 临空通信毫米波非正交多址接入技术联合收发端波束赋形及功率分配方法 | |
US7248897B2 (en) | Method of optimizing radiation pattern of smart antenna | |
CN110535518B (zh) | 一种宽波束发射波束形成优化设计方法 | |
Alluhaibi et al. | Capacity maximisation for hybrid digital-to-analog beamforming mm-wave systems | |
Liu et al. | Access points in the air: Modeling and optimization of fixed-wing UAV network | |
CN110650525B (zh) | 一种多波束分配功率mac协议通信方法 | |
Mahmood et al. | Spherical array-based joint beamforming and UAV positioning in massive MIMO systems | |
Yao et al. | Multi-beam on-demand power allocation MAC protocol for MIMO terahertz communication networks | |
CN114630297B (zh) | 一种携带智能反射面的无人机中继的位置优化方法 | |
CN101783699B (zh) | 多用户mimo系统中下行链路的信号发射方法和装置 | |
CN114665947B (zh) | 一种无人机支持的中继通信系统联合功率控制及位置规划的优化设计方法 | |
CN116667890A (zh) | 一种去蜂窝大规模mimo下行抗窃听传输方法 | |
Prabhath et al. | Intelligent reflecting surface orientation optimization to enhance the performance of wireless communications systems | |
Su et al. | Energy Efficiency Optimization for D2D communications in UAV-assisted Networks with SWIPT | |
Ahmed et al. | Maximizing Mobile Communication Efficiency with Smart Antenna Systems using Beam forming and DOA Algorithms | |
Cao et al. | RIS-Assisted Coverage Extension for LEO Satellite Communication in Blockage Scenarios | |
Liu et al. | Connectivity analysis of UAV-to-satellite communications in non-terrestrial networks | |
Okada et al. | A study on antenna polarization plane for UL/DL drone access network | |
WO2022050187A1 (ja) | 無線通信システム |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 20901345 Country of ref document: EP Kind code of ref document: A1 |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 20901345 Country of ref document: EP Kind code of ref document: A1 |
|
32PN | Ep: public notification in the ep bulletin as address of the adressee cannot be established |
Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 08/02/2023) |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 20901345 Country of ref document: EP Kind code of ref document: A1 |