Multi-antenna unmanned aerial vehicle base station association and beam forming method and system and storage medium

Abstract

The invention provides a multi-antenna unmanned aerial vehicle base station association and beam forming method and system and a storage medium, and the method comprises the steps: 1, calculating the signal quality of downlink communication of an unmanned aerial vehicle through unmanned aerial vehicle positioning information and ground base station information in combination with an unmanned aerial vehicle measurement report and beam forming information; and step 2, adding, updating and releasing associated base stations to the unmanned aerial vehicle according to different intervals in which the signal quality is located. The method has the beneficial effects that the overall gain of the associated base station at the unmanned aerial vehicle can be improved, so that a higher downlink signal to interference plus noise ratio is realized, and the communication reliability can be improved and the time delay can be reduced under the background that a limited block length transmission mechanism is adopted in an unmanned aerial vehicle beyond-visual-range control scene. Meanwhile, the number of the associated base stations is dynamically adjusted according to communication requirements, and the effect of saving base station resources can also be achieved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a multi-antenna UAV base station association and beamforming method, system and storage medium. Background Art

[0002] As the number of civilian drones increases sharply and the application scenarios of drones become more diverse, drone operations often need to be performed beyond visual range, such as using drones for remote delivery and emergency rescue. Traditional point-to-point communication methods cannot achieve ultra-reliable low-latency control of drones beyond visual range. Therefore, third-generation partners began to study the relevant technologies for drone access to cellular networks. Compared with traditional point-to-point communication methods, cellular networks can provide more reliable mobility support for drones under beyond visual range operation conditions.

[0003] At the same time, MIMO technology is fully applied in 5G. At present, relevant technologies support the configuration of multiple antennas for various communication terminals such as vehicles and drones to improve the capacity and spectrum efficiency of communication systems. By weighting and superimposing the phase of the received signal of each antenna, the drone can achieve a certain receiving beam to achieve different receiving gains for signals in different directions.

[0004] In today's cellular networks, ground base station antennas are usually tilted downward to improve ground user coverage, causing aerial drone users to connect to the base station side lobes, resulting in lower antenna gain of the base station in the direction of the drone and a significant change with the flight of the drone. On the other hand, drones are generally higher than ground base stations and buildings. As the altitude of drones increases, the probability of line-of-sight links between drones and base stations increases, causing drones to suffer interference from more base stations and lower signal-to-interference-to-noise ratios of received signals.

[0005] At present, the base station association method provided for drones in traditional Long-Term Evolution (LTE) is based on received power, and the base station switching is based on the A3 event trigger, that is, the switching decision is made based on the measured received power of the target base station and the serving base station. In this association mode, the receiving beam of the drone user in the air cannot effectively suppress the power of the interfering base station, and under multiple connections, it cannot be guaranteed that the drone beam can provide high gain for the associated base station at the same time. Summary of the invention

[0006] The present invention provides a multi-antenna UAV base station association and beamforming method, comprising the following steps:

[0007] Step 1: Calculate the signal quality of the drone's downlink communication by using the drone's positioning information, ground base station information, drone measurement report, and beamforming information;

[0008] Step 2: According to the different ranges of signal quality, add, update and release the associated base stations for the drones respectively.

[0009] As a further improvement of the present invention, in step 1, the receiving power of each base station signal under the drone beam is calculated through the drone positioning information and the ground base station information, and the signal quality of the drone's downlink communication is calculated in combination with the drone measurement report and the beamforming information.

[0010] The present invention also provides a multi-antenna UAV base station association and beamforming system, comprising: a memory, a processor, and a computer program stored on the memory, wherein the computer program is configured to implement the steps of the multi-antenna UAV base station association and beamforming method of the present invention when called by the processor.

[0011] The present invention also provides a computer-readable storage medium, which stores a computer program, and the computer program is configured to implement the steps of the multi-antenna UAV base station association and beamforming method of the present invention when called by a processor.

[0012] The beneficial effects of the present invention are as follows: the present invention can improve the overall gain of the associated base station at the drone, thereby achieving a higher downlink signal-to-interference-to-noise ratio, and in the context of the limited block length transmission mechanism adopted in the drone beyond-visual-range control scenario, it can improve the reliability of communication and reduce latency. At the same time, dynamically adjusting the number of associated base stations according to communication needs can also save base station resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a schematic diagram of the UAV beyond visual range control network structure;

[0014] Figure 2 This is a schematic diagram of multi-antenna drone signal reception. DETAILED DESCRIPTION

[0015] In order to improve the reliability of the UAV communication system, a multi-connection method is used to serve the UAV, that is, multiple base stations transmit control instructions to the UAV at the same time. The network structure is as follows: Figure 1As shown. Under multiple connections, a base station association method based on signal quality is proposed. Through the positioning of the drone and the location information of the ground base station, combined with the drone measurement report and beamforming information, the signal quality of the drone's downlink communication is calculated. Then, multiple thresholds are set for the signal quality to add, update and release the associated base stations of the drone. Compared with the current switching scheme based on reference signal receive power (RSRP), the multi-antenna drone base station association and beamforming method in the present invention can effectively improve the gain of the associated base station at the drone, thereby improving the signal-to-interference-noise ratio of the communication.

[0016] The coordinates of the drone obtained by positioning are marked as (x u ,y u ,z u ), the coordinates of base station i are marked as (x BSi ,y BSi ,z BSi ). The angle of base station i relative to the drone can be obtained

[0017]

[0018] The drone is equipped with N x ×N y The gain of the antenna array to signals in different directions can be expressed as

[0019]

[0020] Where w and a are the beamforming vector and steering vector, respectively, expressed as

[0021]

[0022] Where d is the antenna spacing, λ is the wavelength, is the target beamforming angle. Multiple target angles are set for the drone in advance, and each angle corresponds to a beamforming vector. All beamforming vectors together constitute the drone’s beamforming codebook C, i.e.

[0023]

[0024] The sets of azimuth and inclination angles are denoted by Φ and Θ respectively.

[0025] The base station is equipped with N t The gain of a uniform linear antenna array with antenna sizes at different vertical angles can be expressed as

[0026]

[0027] Where BW hp is the half-power beamwidth, G m is the antenna zero point threshold. All base stations have the same downtilt angle θ t , height h bs With the transmission power P t , and is omnidirectional in the horizontal direction.

[0028] The path loss between the base station and the drone can be expressed as

[0029]

[0030] in is the straight-line distance between the base station and the UAV, A is the unit path loss, and α is the path loss exponent.

[0031] Small-scale fading is obtained by the Nakagami-m model, and its probability density is

[0032]

[0033] Where m is the fading exponent.

[0034] The receiving power of the drone to the base station i signal is

[0035]

[0036] At time t, the set of drone-associated base stations is denoted as G t At this time, the received power at the drone is

[0037]

[0038] The drone periodically measures the power of the serving base station and surrounding base stations to obtain a measurement report MR. At time t, the measurement result MR = {R1(t), R2(t)...R ||S|| (t)}, S is the set of all base stations measured. Beamforming is performed, and the signal quality of the drone receiving signal is

[0039]

[0040] is the sum of the received powers of the associated base stations.

[0041] If the signal quality q(t) is lower than the threshold q th1 , then initiate the base station switching process. The switching process first screens the measured base stations. The screening criteria are to select base stations with RSRP higher than the associated base station G t Minimum RSRP of base stations A certain percentage η, or above a certain threshold R th1 After screening, a candidate base station group is obtained, and the measurement report of its RSRP composition is MR η , the corresponding base station set is S η .Right now

[0042]

[0043] If the signal quality q(t) is lower than a lower threshold q th2 , then determine the number of base stations associated with the drone at this time || G t || Is it less than the maximum number of associations N? max If it is less than, then add an associated base station for the drone, specifically

[0044]

[0045] If the number of associated base stations reaches the maximum number of associated base stations, or q th2 ≤q(t) th1 , then the associated base station set is updated in the following manner.

[0046]

[0047] If q(t)≥q th1 , then make the following judgment. First, determine whether the signal quality is higher than or equal to a higher threshold q th3 If it is higher than or equal to, then determine whether the number of associated base stations is greater than the minimum number of associated base stations N. min If it is greater than, a base station among the associated base stations is selected to release resources according to the following criteria.

[0048]

[0049] If the number of associated base stations is equal to N min , or q(t) th3 , then the associated base station set remains unchanged and only the drone beam is updated.

[0050]

[0051] Beneficial effects of the present invention:

[0052] ​​The present invention proposes a multi-antenna UAV base station association and beamforming method, which calculates the received power of each base station signal under the UAV beam by using the UAV positioning information and the ground base station information, and then obtains the signal quality. According to the different intervals of signal quality, the associated base station can be added, updated and released to the UAV respectively. The present invention can improve the overall gain of the associated base station at the UAV, thereby achieving a higher downlink signal-to-interference-noise ratio. In the context of the limited block length transmission mechanism used in the UAV beyond-line-of-sight control scenario, it can improve the reliability of communication and reduce latency. At the same time, dynamically adjusting the number of associated base stations according to communication needs can also save base station resources.

[0053] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A multi-antenna UAV base station association and beamforming method, It is characterized in that The steps include: Step 1: Calculate the signal quality of the drone's downlink communication by using the drone's positioning information, ground base station information, drone measurement report, and beamforming information; Step 2: According to the different ranges of signal quality, add, update and release the associated base stations for the drones respectively.

2. The multi-antenna UAV base station association and beamforming method according to claim 1, Features: In step 1, the received power of each base station signal under the drone beam is calculated through the drone positioning information and the ground base station information, and the signal quality of the drone's downlink communication is calculated in combination with the drone measurement report and the beamforming information.

3. The multi-antenna UAV base station association and beamforming method according to claim 2, Features: In step 1, the coordinates of the drone are marked as (x u ,y u ,z u ), the coordinates of base station i are marked as 4. The multi-antenna UAV base station association and beamforming method according to claim 3, Features: In step 1, the angle of base station i relative to the drone is The drone is equipped with N x ×N y The gain of the antenna array for signals in different directions is expressed as Where w and a are the beamforming vector and steering vector respectively, and θ represents the downtilt angle of the base station relative to the drone. Indicates the azimuth of the base station relative to the drone, are the target beamforming angles, respectively expressed as Where d is the antenna spacing, λ is the wavelength; multiple target angles are set for the drone in advance, and each angle corresponds to a beamforming vector; all beamforming vectors together constitute the drone's beamforming codebook C, that is, The sets of azimuth and inclination are denoted as Φ and Θ respectively; The base station is equipped with N t The gain of a uniform linear antenna array with antenna sizes at different vertical angles is expressed as Where BW hp is the half-power beamwidth, G m is the antenna zero point threshold; all base stations have the same downtilt angle θ t , height h bs With the transmission power P t , and is omnidirectional in the horizontal direction.

5. The multi-antenna UAV base station association and beamforming method according to claim 4, Features: In step 1, the receiving power of the drone to the base station i signal is In the above formula, ζ i With Ω i They represent the path loss and shadow fading in the signal transmission of base station i respectively; At time t, the set of drone-associated base stations is denoted as G t ; At this time, the received power at the drone is The drone periodically measures the received signal power of the serving base station and surrounding base stations to obtain a measurement report MR; at time t, the measured result MR = {R 1 (t),R 2 (t)...R ||S|| (t)}, S is the set of all measured base stations; if the drone at this moment is at an angle Beamforming is performed, and the signal quality of the drone receiving signal is is the sum of the received powers of the associated base stations.

6. The multi-antenna UAV base station association and beamforming method according to claim 1, Features: In step 2, if the signal quality q(t) is lower than the threshold q th1 , then initiate the base station switching process. The switching process first screens the measured base stations; the screening criteria are to select base stations with RSRP higher than the associated base station G t Minimum RSRP of base stations A certain percentage η, or above a certain threshold R th1 After screening, a candidate base station group is obtained, and the measurement report of its RSRP composition is MR η , the corresponding base station set is S η ;Right now 7. The multi-antenna UAV base station association and beamforming method according to claim 1, Features: In step 2, if the signal quality q(t) is lower than the threshold q th2 , then determine the number of base stations associated with the drone at this time || G t || Is it less than the maximum number of associations N? max ; If it is less than, then add an associated base station for the drone, specifically If the number of associated base stations reaches the maximum number of associated base stations, or q th2 ≤q(t) th1 , then the associated base station set is updated in the following manner;​ 8. The multi-antenna UAV base station association and beamforming method according to claim 1, Features: In step 2, if q(t)≥q th1 , then make the following judgments: first, determine whether the signal quality is higher than or equal to the threshold q th3 ; If it is higher than or equal to, then determine whether the number of associated base stations is greater than the minimum number of associated base stations N min ; If it is greater, select a base station among the associated base stations to release resources according to the following criteria; If the number of associated base stations is equal to N min , or q(t) th3 , then keep the associated base station set unchanged and only update the drone beam;​ 9. A multi-antenna UAV base station association and beamforming system, It is characterized in that include: A memory, a processor, and a computer program stored on the memory, wherein the computer program is configured to implement the steps of the multi-antenna UAV base station association and beamforming method described in any one of claims 1 to 8 when called by the processor.

10. A computer-readable storage medium, Features: The computer-readable storage medium stores a computer program, and the computer program is configured to implement the steps of the multi-antenna drone base station association and beamforming method described in any one of claims 1 to 8 when called by a processor.

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