Position updating method and device, equipment, medium and product

Abstract

The invention relates to the technical field of wireless communication, in particular to a position updating method, device and equipment, a medium and a product, and the method is applied to a communication system comprising an unmanned aerial vehicle relay node and at least two communication nodes deployed on the ground. Comprising the following steps: acquiring first transmitting power of each communication node, second transmitting power of an unmanned aerial vehicle relay node, and channel state information of a communication link between each communication node and the unmanned aerial vehicle relay node; wherein the channel state information comprises the distance between each communication node and the unmanned aerial vehicle relay node, a channel fading coefficient and a path loss coefficient; processing the first transmitting power, the second transmitting power and the channel state information, and determining the signal-to-noise ratio of each communication node after processing; determining a first outage probability of a communication link corresponding to each communication node based on the signal-to-noise ratio, the channel state information and the first transmitting power; and updating the position of the unmanned aerial vehicle relay node based on the first outage probability.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of wireless communication, and in particular, to a position updating method, device, equipment, medium and product. BACKGROUND

[0002] With the continuous development of wireless communication technology, higher requirements are put forward for the reliability and data transmission efficiency of the communication system. Especially in long-distance communication, multipath propagation and complex dynamic environment, the data forwarding mechanism of relay communication has been unable to meet the data transmission demand in complex network environment.

[0003] In the related art, in order to maximize the coverage range, the unmanned aerial vehicle is usually fixed at a specified relay position. The greater the distance between the unmanned aerial vehicle and the communication node, the lower the data quality of the data transmitted by the unmanned aerial vehicle, resulting in insufficient communication efficiency of the unmanned aerial vehicle. SUMMARY

[0004] The present disclosure is proposed in view of the problem of insufficient communication efficiency of the unmanned aerial vehicle. The present disclosure provides a position updating method, device, equipment, medium and product.

[0005] In a first aspect, the embodiments of the present disclosure provide a position updating method applied to a communication system including one unmanned aerial vehicle relay node and at least two communication nodes deployed on the ground, comprising: obtaining a first transmission power of each communication node, a second transmission power of the unmanned aerial vehicle relay node, and channel state information of a communication link between each communication node and the unmanned aerial vehicle relay node; wherein the channel state information includes a distance between each communication node and the unmanned aerial vehicle relay node, a channel fading coefficient and a path loss coefficient.

[0006] processing the first transmission power, the second transmission power and the channel state information to determine a signal-to-noise ratio of each communication node after processing.

[0007] determining a first outage probability of the communication link corresponding to each communication node based on the signal-to-noise ratio, the channel state information and the first transmission power.

[0008] updating the position of the unmanned aerial vehicle relay node based on the first outage probability.

[0009] In an embodiment of the first aspect, processing the first transmission power, the second transmission power and the channel state information to determine a signal-to-noise ratio of each communication node after processing comprises: determining an original signal transmitted by each communication node to the unmanned aerial vehicle relay node and a noise signal of the communication link corresponding to each communication node.

[0010] The original signal is processed based on the first transmit power, the second transmit power, channel state information, and noise signal. The power gain of the UAV relay node is then determined.

[0011] The signal-to-noise ratio of each communication node is determined based on power gain.

[0012] In one embodiment of the first aspect, the original signal is processed based on a first transmit power, a second transmit power, channel state information, and noise signal to determine the power gain of the UAV relay node, including: The original signal is processed based on the first transmit power, distance, channel fading coefficient, path loss coefficient, and noise signal. The processed signal is the first signal received by the UAV relay node from each communication node.

[0013] The power gain of the UAV relay node is determined based on the ratio between the second transmit power and the first signal.

[0014] In one embodiment of the first aspect, determining the signal-to-noise ratio of each communication node based on power gain includes: The first signal is processed based on the power gain to obtain the second signal transmitted by the UAV relay node to each communication node; wherein, the first signal is the signal after processing the original signal based on the first transmission power, distance, channel fading coefficient, path loss coefficient and noise signal.

[0015] The signal-to-noise ratio of each communication node is determined based on the square of the second signal.

[0016] In one embodiment of the first aspect, determining the first interruption probability of the communication link corresponding to each communication node based on the signal-to-noise ratio, channel state information, and a first transmit power includes: The receive power of the UAV relay node for each communication node is determined based on distance, channel fading coefficient, path loss coefficient, and first transmit power.

[0017] The first interruption probability of the communication link corresponding to each communication node is determined based on the distribution function of the received power and the signal-to-noise ratio.

[0018] In one embodiment of the first aspect, updating the location of the UAV relay node based on a first interruption probability includes: The cumulative value of each first interruption probability is determined to be the second interruption probability of the communication system.

[0019] Determine the initial location information of the drone relay node.

[0020] Calculate the product between the gradient of the second interruption probability and the movement step size; where the movement step size is the maximum movement distance of the UAV relay node within a time slot.

[0021] The difference between the initial position information and the product is determined as the updated position information of the UAV relay node.

[0022] In one embodiment of the first aspect, determining the original signal transmitted by each communication node to the UAV relay node includes: The data to be transmitted by each communication node is network encoded, and the encoded data is the original signal transmitted by each communication node to the UAV relay node.

[0023] In a second aspect, embodiments of this disclosure provide a location update apparatus applied to a communication system including a UAV relay node and at least two communication nodes deployed on the ground, comprising: The data acquisition unit is used to acquire the first transmit power of each communication node, the second transmit power of the UAV relay node, and the channel state information of the communication link between each communication node and the UAV relay node; wherein, the channel state information includes the distance between each communication node and the UAV relay node, the channel fading coefficient, and the path loss coefficient.

[0024] The data processing unit is used to process the first transmit power, the second transmit power, and the channel state information, and then determine the signal-to-noise ratio of each communication node.

[0025] The probability determination unit is used to determine the first interruption probability of the communication link corresponding to each communication node based on the signal-to-noise ratio, channel state information and the first transmit power.

[0026] The location update unit is used to update the location of the UAV relay node based on the first interruption probability.

[0027] In a third aspect, embodiments of this disclosure provide an electronic device, including: a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor communicates with the memory via the bus, and when the machine-readable instructions are executed by the processor, the steps in the above-described position update method are performed.

[0028] In a fourth aspect, embodiments of this disclosure provide a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the aforementioned position update method.

[0029] In a fifth aspect, embodiments of this disclosure provide a computer program product stored in a storage medium, the program product being executed by at least one processor to implement the steps in the above-described position update method.

[0030] As will be described in detail below, a location update method, apparatus, device, medium, and product according to embodiments of this disclosure are disclosed. In embodiments of this disclosure, firstly, a communication system acquires a first transmit power of each communication node, a second transmit power of a UAV relay node, and channel state information of the communication link between each communication node and the UAV relay node. This channel state information includes the distance between each communication node and the UAV relay node, the channel fading coefficient, and the path loss coefficient. Then, the first transmit power, the second transmit power, and the channel state information are processed to determine the signal-to-noise ratio (SNR) of each communication node. Secondly, a first interruption probability of the communication link corresponding to each communication node is determined based on the SNR, the channel state information, and the first transmit power. Finally, the position of the UAV relay node is updated based on the first interruption probability. Through the above processing method, using a UAV as a relay communication node, and by real-time sensing of the channel state of the communication node and the UAV relay node, the SNR and interruption efficiency, which indicate communication quality, are determined. The UAV position is then adjusted according to the interruption efficiency, enabling the UAV to intelligently respond to real-time changes in the channel environment and remain in the area with optimal communication quality, thereby improving the communication efficiency of the UAV.

[0031] It should be understood that both the foregoing general description and the following detailed description are exemplary and intended to provide further illustration of the claimed technology. Attached Figure Description

[0032] The above and other objects, features, and advantages of this disclosure will become more apparent from the more detailed description of the embodiments thereof in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this disclosure and form part of the specification. They are used together with the embodiments of this disclosure to explain the disclosure and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0033] Figure 1 This is a flowchart of a location update method according to an embodiment of the present disclosure.

[0034] Figure 2 This is a schematic diagram of the repetitive cumulative encoding of an embodiment of the present disclosure.

[0035] Figure 3 This is an overall flowchart of a location update process according to an embodiment of the present disclosure.

[0036] Figure 4 This is a schematic diagram of a location update device according to an embodiment of the present disclosure.

[0037] Figure 5 This is a schematic diagram of an electronic device according to an embodiment of the present disclosure.

[0038] Figure 6This is a schematic diagram of a computer program product according to an embodiment of the present disclosure. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of this disclosure more apparent, exemplary embodiments according to this disclosure will now be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this disclosure, and not all embodiments of this disclosure. It should be understood that this disclosure is not limited to the exemplary embodiments described herein.

[0040] To facilitate understanding of this embodiment, a location update method disclosed in this disclosure will first be described in detail, see [link to relevant documentation]. Figure 1 The diagram shows a flowchart of a location update method provided in this embodiment of the present disclosure. The method is applied to a communication system including a UAV relay node and at least two communication nodes deployed on the ground. The method includes steps S101-S104, wherein: Step S101: Obtain the first transmit power of each communication node, the second transmit power of the UAV relay node, and the channel state information of the communication link between each communication node and the UAV relay node; wherein, the channel state information includes the distance between each communication node and the UAV relay node, the channel fading coefficient, and the path loss coefficient.

[0041] Here, communication nodes include base stations or terminals, etc. The communication system disclosed herein may include a UAV relay node, at least one terminal and at least one base station, or it may include a UAV relay node and at least two terminals, or it may include a UAV relay node and at least two base stations. This disclosure does not require that.

[0042] The channel state information disclosed herein is used to indicate the quality of the communication link and may include parameters such as the distance between each communication node and the UAV relay node, channel fading coefficient, path loss coefficient, signal strength, signal quality, and throughput.

[0043] In this embodiment of the disclosure, the communication nodes can communicate with the help of the UAV relay node. In the first time slot, each communication node sends a signal to the UAV relay node at the same time, and in the second time slot, the UAV relay node sends a signal to each communication node at the same time.

[0044] For example, if the communication system includes a UAV relay node U, a communication node B, and a communication node M, then in this process, the communication system acquires the first transmit power of each communication node (i.e., and ), the second transmit power of the UAV relay node Channel state information of the communication link between each communication node and the UAV relay node; the distance between UAV relay node U and communication node B is... The distance between the UAV relay node U and the communication node M is The channel fading coefficient of the communication link between UAV relay node U and communication node B is: The channel fading coefficient of the communication link between UAV relay node U and communication node M is: and path loss coefficient .

[0045] Step S102: Process the first transmit power, the second transmit power and the channel state information, and determine the signal-to-noise ratio of each communication node after processing.

[0046] In this embodiment of the disclosure, the first transmission power can be... Second transmission power The distance between UAV relay node U and communication node B is The channel fading coefficient of the communication link between UAV relay node U and communication node B is: Path loss coefficient The signal-to-noise ratio of communication node B is then determined after processing. Similarly, the signal-to-noise ratio of communication node M can be obtained. .

[0047] Step S103: Determine the first interruption probability of the communication link corresponding to each communication node based on the signal-to-noise ratio, the channel state information, and the first transmit power.

[0048] Here, the interruption probability refers to the probability that the current channel capacity is less than the specified rate, which can be used to evaluate the reliability of the communication system, that is, the probability that the signal-to-noise ratio is less than or equal to the signal-to-noise ratio threshold.

[0049] In this embodiment of the disclosure, the first transmission power can be used as a reference. Signal-to-noise ratio ,distance Channel fading coefficient Path loss coefficient Processing is performed to determine the first probability of communication link interruption corresponding to communication node B. Similarly, the signal-to-noise ratio of communication node M can be obtained. .

[0050] Step S104: Update the position of the UAV relay node based on the first interruption probability.

[0051] Based on this, given that the power of communication node B and communication node M is constant, the optimal UAV position can be calculated using gradient descent based on the first interruption probability, so as to update the position of the UAV relay node.

[0052] In this embodiment, firstly, the communication system can acquire the first transmit power of each communication node, the second transmit power of the UAV relay node, and the channel state information of the communication link between each communication node and the UAV relay node. The channel state information includes the distance between each communication node and the UAV relay node, the channel fading coefficient, and the path loss coefficient. Then, the first transmit power, the second transmit power, and the channel state information are processed to determine the signal-to-noise ratio (SNR) of each communication node. Secondly, the first interruption probability of the communication link corresponding to each communication node is determined based on the SNR, the channel state information, and the first transmit power. Finally, the position of the UAV relay node is updated based on the first interruption probability.

[0053] In the above embodiments, a drone is used as a relay communication node, and the signal-to-noise ratio and interruption efficiency indicating communication quality are determined by real-time sensing of the channel status of the communication node and the drone relay node. The drone position is then adjusted according to the interruption efficiency, enabling the drone to intelligently respond to the real-time changing channel environment and stay in the area with the best communication quality, thereby improving the communication efficiency of the drone.

[0054] In an optional implementation, the above steps process the first transmit power, the second transmit power, and the channel state information to determine the signal-to-noise ratio of each communication node, specifically including the following steps: Determine the original signal transmitted by each communication node to the UAV relay node and the noise signal of the corresponding communication link for each communication node; The original signal is processed based on the first transmission power, the second transmission power, the channel state information, and the noise signal, and the power gain of the UAV relay node is determined after processing. The signal-to-noise ratio of each communication node is determined based on the power gain.

[0055] Here, the original signal is the result of network encoding of the data to be transmitted. The network encoding method can be repeated cumulative encoding or other encoding methods.

[0056] The original signal with unit energy transmitted by communication node B is: The original signal with unit energy transmitted by communication node M is The noise signal can be Gaussian white noise. And it follows a mean of 0 and a variance of . The Gaussian distribution.

[0057] In this embodiment of the disclosure, calculations can be performed using the first transmit power, the second transmit power, channel state information, noise signal, and the original signal to obtain the power gain G of the UAV relay node U. Further calculations are then performed on the power gain G to obtain the signal-to-noise ratio of the communication node B. Signal-to-noise ratio of communication node M .

[0058] In the above embodiments, by introducing noise signals, the reliability of the signal processing process is improved to accurately simulate the real environment in which the UAV relay node is subject to noise and interference, thereby improving the accuracy of calculating the signal-to-noise ratio of each communication node.

[0059] In an optional implementation, the above steps process the original signal based on the first transmit power, the second transmit power, the channel state information, and the noise signal, and determine the power gain of the UAV relay node after processing. Specifically, this includes the following steps: The original signal is processed based on the first transmission power, the distance, the channel fading coefficient, the path loss coefficient, and the noise signal to obtain the first signal received by the UAV relay node from each of the communication nodes. The power gain of the UAV relay node is determined based on the ratio between the second transmit power and the first signal.

[0060] As mentioned above, the first signal can be calculated using the following formula: ,in, The drone relay node receives the first signal from communication node B. This is the first transmit power of communication node B. The distance between UAV relay node U and communication node B. This is the path loss coefficient. Let be the channel fading coefficient of the communication link between UAV relay node U and communication node B. The original signal of unit energy transmitted by communication node B. This is a noise signal.

[0061] Similarly, the first signal received by the UAV relay node from the communication node M can be obtained. , The first signal is the signal after the original signal has been processed based on the first transmit power, distance, channel fading coefficient, path loss coefficient and noise signal, that is, the signal after the original signal has been attenuated.

[0062] The total signal received by the drone relay node is: .

[0063] The power gain of the drone relay node is: ,in, This is the second transmission power. The first transmit power of communication node M, The distance between the UAV relay node U and the communication node M. Let be the channel fading coefficient of the communication link between UAV relay node U and communication node M. Let V be the variance of the noise signal.

[0064] In this embodiment of the disclosure, the first transmit power, distance, channel fading coefficient, path loss coefficient, noise signal and original signal can be calculated to obtain the first signal received by the UAV relay node from each communication node and the total signal received by the UAV relay node, so as to determine the power gain of the UAV relay node according to the ratio between the second transmit power and the first signal.

[0065] In the above embodiments, the power gain of the UAV relay node can be calculated based on the real-time changes in the first signal and the second transmission power, avoiding excessive amplification of noise and ensuring the effectiveness of the signal transmitted by the UAV relay node. This ensures the communication efficiency of the communication link while maintaining its stability.

[0066] In an optional implementation, the above steps, which determine the signal-to-noise ratio of each communication node based on the power gain, specifically include the following steps: The first signal is processed based on the power gain to obtain a second signal transmitted by the UAV relay node to each of the communication nodes; wherein, the first signal is a signal after processing the original signal based on the first transmission power, the distance, the channel fading coefficient, the path loss coefficient, and the noise signal; The signal-to-noise ratio of each of the communication nodes is determined based on the square of the second signal.

[0067] Furthermore, the first signal can be calculated using the following formula: ,in, This is the second signal transmitted by the UAV relay node to communication node B. This is the first transmit power of communication node B. The distance between UAV relay node U and communication node B. This is the path loss coefficient. Let be the channel fading coefficient of the communication link between UAV relay node U and communication node B. The original signal of unit energy transmitted by communication node B. This is a noise signal. For power gain, The first transmit power of communication node M, The distance between the UAV relay node U and the communication node M. Let be the channel fading coefficient of the communication link between UAV relay node U and communication node M. The original signal of unit energy transmitted by communication node M.

[0068] Similarly, the second signal transmitted by the UAV relay node to the communication node M can be obtained: .

[0069] Based on this, the signal-to-noise ratio of each communication node can be obtained from the second signal: That is, the signal-to-noise ratio of communication node B; That is, the signal-to-noise ratio of the communication node M.

[0070] In this embodiment of the disclosure, the power gain and the first signal can be calculated to obtain the second signal transmitted by the UAV relay node to each communication node, and the signal-to-noise ratio of each communication node can be determined based on the square of the second signal.

[0071] In the above embodiments, the signal-to-noise ratio of each communication node can be accurately predicted based on the power gain and the first signal, which makes it convenient to adjust the position of the UAV relay node according to the signal-to-noise ratio without actually deploying the UAV relay node in a designated location for testing, thus effectively improving the efficiency and feasibility of location updates.

[0072] In an optional implementation, the above steps determine the first interruption probability of the communication link corresponding to each communication node based on the signal-to-noise ratio, the channel state information, and the first transmit power, specifically including the following steps: The receiving power of the UAV relay node for each of the communication nodes is determined based on the distance, the channel fading coefficient, the path loss coefficient, and the first transmit power. The first interruption probability of the communication link corresponding to each communication node is determined based on the distribution function of the received power and the signal-to-noise ratio.

[0073] The received power can be calculated using the following formula: ,in, This refers to the receiving power of the UAV relay node for communication node B. This refers to the receiving power of the UAV relay node for communication node B. This is the first transmit power of communication node B. The distance between UAV relay node U and communication node B. This is the path loss coefficient. This represents the channel fading coefficient of the communication link between UAV relay node U and communication node B.

[0074] Similarly, the received power of the UAV relay node for communication node M can be obtained. : .

[0075] If the signal-to-noise ratio threshold is Then when the signal-to-noise ratio of communication node B... Less than or equal to When communication node B is determined to be interrupted, the probability of the first interruption of the communication link corresponding to communication node B is: Similarly, the probability of the first interruption of the communication link corresponding to communication node M is... .

[0076] If set Then the signal-to-noise ratio of communication node B is: .

[0077] In this case This can be equivalent to: ,in, , .

[0078] like Follow the mean The exponential distribution, Follow the mean If the distribution follows an exponential pattern, then the probability of the first interruption of the communication link corresponding to communication node B is: .

[0079] Since S and W are independent of each other, therefore, ,because Since it is a constant, therefore, It is 1, because Greater than or equal to 0, therefore, ,Right now .

[0080] like The probability density function is Then we have: If further settings It can be known that And it follows the mean. If the exponential distribution is followed, then: .

[0081] Based on this, we can obtain and will Substituting, we get: .

[0082] Let A be a small constant. satisfy ,available This can convert improper integrals into definite integrals, thereby improving computational efficiency.

[0083] Finally, combining the above formulas, we can obtain: Similarly, set ,available: .

[0084] In the above embodiments, by introducing a distribution function, the randomness of the wireless channel during the fading process can be accurately characterized, and the first interruption probability of each communication link can be determined accordingly. The location update can then be performed based on the first interruption probability to improve the robustness of the location update process.

[0085] In an optional implementation, the above steps update the location of the UAV relay node based on the first interruption probability, specifically including the following steps: The cumulative value of each of the first interruption probabilities is determined to be the second interruption probability of the communication system; Determine the initial position information of the UAV relay node; Calculate the product between the gradient of the second interruption probability and the movement step size; wherein the movement step size is the maximum movement distance of the UAV relay node within one time slot; The difference between the initial position information and the product is determined as the updated position information of the UAV relay node.

[0086] Based on this, the second interruption probability of the communication system for: That is, the channels between communication nodes in a communication system are basically independent.

[0087] If the initial location information of the UAV relay node is set as follows in this disclosure... Furthermore, it can move freely in three-dimensional space, and the gradient of the second interruption probability is: The updated location information of the drone relay node is as follows: ,in, To update the intermediate position information of the drone relay node, For the movement step size, This is the initial location information. Let be the gradient of the second interruption probability.

[0088] By employing gradient descent, it can be ensured that the UAV relay node moves in the direction that minimizes the probability of interruption most quickly during each location update, thereby improving the convergence speed of the optimization process and accurately guiding the optimization path.

[0089] Finally, based on the set interruption probability threshold , Given a very small positive number, iterate continuously until the result meets the condition. This allows us to obtain the final updated location information of the drone relay node.

[0090] In the above implementation, a dynamic position optimization algorithm is incorporated, enabling the UAV relay node to adjust its position in real time according to the actual communication environment. As the position of the UAV relay node is continuously optimized, the probability of interruption will gradually decrease, further improving communication efficiency and stability.

[0091] In an optional implementation, the above steps for determining the original signal transmitted by each of the communication nodes to the UAV relay node specifically include the following steps: The data to be transmitted by each of the communication nodes is network encoded to obtain the original signal transmitted by each of the communication nodes to the UAV relay node.

[0092] As mentioned above, this disclosure also performs network encoding on the data to be transmitted at each communication node.

[0093] refer to Figure 2 As shown, communication node B is represented by base station B, communication node M is represented by base station M, UAV relay node is represented by UAV U, and the network coding method is exemplified by repeat accumulate (RA) coding.

[0094] Specifically, in the first time slot: the data to be transmitted by base station B. Data to be transmitted from base station M Perform RA encoding separately, and obtain the following results: and and send to drone U and This refers to the original signals from communication nodes B and M, which are simultaneously transmitted to the UAV relay node.

[0095] In the second time slot: UAV U performs virtual RA decoding on the original signal to obtain... Then it is sent to base station B and base station M respectively. Base station B uses... get Base station M via get .

[0096] In the above embodiments, one information exchange between communication nodes can be completed in two time slots. The communication method based on physical layer network coding in this disclosure doubles the communication rate compared to traditional methods. Moreover, by introducing network coding technology, the UAV is not only a simple relay node, but can also encode and process data. This reduces redundant data transmission and improves bandwidth utilization.

[0097] In summary, this disclosure combines the efficiency of network coding with the flexibility of UAV relay communication, and uses a position optimization algorithm to ensure that the probability of communication interruption is minimized, thereby achieving the best communication quality and improving the communication efficiency of UAVs.

[0098] The following is combined with Figure 3 The above location update process is described in detail below: S301: Obtain the first transmit power of each communication node, the second transmit power of the UAV relay node, and the channel status information of the communication link between each communication node and the UAV relay node.

[0099] Here, the channel state information includes the distance between each communication node and the UAV relay node, the channel fading coefficient, and the path loss coefficient.

[0100] S302: Determine the original signal transmitted by each communication node to the UAV relay node and the noise signal of the corresponding communication link for each communication node.

[0101] S303: The original signal is processed based on the first transmit power, distance, channel fading coefficient, path loss coefficient and noise signal, and the processed signal is the first signal received by the UAV relay node from each communication node.

[0102] S304: Determine the power gain of the UAV relay node based on the ratio between the second transmit power and the first signal.

[0103] S305: The first signal is processed based on the power gain, and the processed signal is the second signal transmitted by the UAV relay node to each communication node.

[0104] Here, the first signal is the original signal after attenuation.

[0105] S306: Determine the signal-to-noise ratio of each communication node based on the square of the second signal.

[0106] S307: Determine the first interruption probability of the communication link corresponding to each communication node based on the signal-to-noise ratio, channel state information and the first transmit power.

[0107] S308: Update the position of the UAV relay node based on the first interruption probability.

[0108] Based on the same inventive concept, this disclosure also provides a location update device corresponding to the location update method. Since the principle of the device in this disclosure for solving the problem is similar to the location update method described above in this disclosure, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0109] Reference Figure 4 The diagram shown is a schematic representation of a location update device provided in an embodiment of this disclosure. The device includes: a data acquisition unit 40, a data processing unit 41, a probability determination unit 42, and a location update unit 43; wherein: The data acquisition unit is used to acquire the first transmit power of each of the communication nodes, the second transmit power of the UAV relay node, and the channel state information of the communication link between each of the communication nodes and the UAV relay node; wherein, the channel state information includes the distance between each of the communication nodes and the UAV relay node, the channel fading coefficient, and the path loss coefficient; The data processing unit is used to process the first transmission power, the second transmission power and the channel state information, and determine the signal-to-noise ratio of each communication node after processing. The probability determination unit is used to determine the first interruption probability of the communication link corresponding to each communication node based on the signal-to-noise ratio, the channel state information, and the first transmit power; A location update unit is used to update the location of the UAV relay node based on the first interruption probability.

[0110] In one possible implementation, the device is also used for: Determine the original signal transmitted by each communication node to the UAV relay node and the noise signal of the corresponding communication link for each communication node; The original signal is processed based on the first transmission power, the second transmission power, the channel state information, and the noise signal, and the power gain of the UAV relay node is determined after processing. The signal-to-noise ratio of each communication node is determined based on the power gain.

[0111] In one possible implementation, the device is also used for: The original signal is processed based on the first transmission power, the distance, the channel fading coefficient, the path loss coefficient, and the noise signal to obtain the first signal received by the UAV relay node from each of the communication nodes. The power gain of the UAV relay node is determined based on the ratio between the second transmit power and the first signal.

[0112] In one possible implementation, the device is also used for: The first signal is processed based on the power gain to obtain a second signal transmitted by the UAV relay node to each of the communication nodes; wherein, the first signal is a signal after processing the original signal based on the first transmission power, the distance, the channel fading coefficient, the path loss coefficient, and the noise signal; The signal-to-noise ratio of each of the communication nodes is determined based on the square of the second signal.

[0113] In one possible implementation, the device is also used for: The receiving power of the UAV relay node for each of the communication nodes is determined based on the distance, the channel fading coefficient, the path loss coefficient, and the first transmit power. The first interruption probability of the communication link corresponding to each communication node is determined based on the distribution function of the received power and the signal-to-noise ratio.

[0114] In one possible implementation, the device is also used for: The cumulative value of each of the first interruption probabilities is determined to be the second interruption probability of the communication system; Determine the initial position information of the UAV relay node; Calculate the product between the gradient of the second interruption probability and the movement step size; wherein the movement step size is the maximum movement distance of the UAV relay node within one time slot; The difference between the initial position information and the product is determined as the updated position information of the UAV relay node.

[0115] In one possible implementation, the device is also used for: The data to be transmitted by each of the communication nodes is network encoded to obtain the original signal transmitted by each of the communication nodes to the UAV relay node.

[0116] The processing flow of each module in the device and the interaction flow between each module can be referred to the relevant descriptions in the above method embodiments, and will not be detailed here.

[0117] Corresponding to Figure 1 In addition to the location update method in this disclosure, embodiments of the present disclosure also provide an electronic device 50, such as... Figure 5 The diagram shown is a schematic representation of an electronic device 50 provided in an embodiment of this disclosure, including: The system includes a processor 51, a memory 52, and a bus 53. The memory 52 stores execution instructions and includes main memory 521 and external memory 522. The main memory 521, also called internal memory, temporarily stores the computational data in the processor 51, as well as data exchanged with external memory such as a hard disk. The processor 51 exchanges data with the external memory 522 through the main memory 521. When the electronic device 50 is running, the processor 51 communicates with the memory 52 through the bus 53, causing the processor 51 to execute the following instructions: The system acquires the first transmit power of each communication node, the second transmit power of the UAV relay node, and the channel state information of the communication link between each communication node and the UAV relay node; wherein the channel state information includes the distance between each communication node and the UAV relay node, the channel fading coefficient, and the path loss coefficient. The first transmit power, the second transmit power, and the channel state information are processed to determine the signal-to-noise ratio of each communication node. The first interruption probability of the communication link corresponding to each communication node is determined based on the signal-to-noise ratio, the channel state information, and the first transmit power. The location of the UAV relay node is updated based on the first interruption probability.

[0118] This disclosure also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the position update method described in the above method embodiments. The storage medium may be a volatile or non-volatile computer-readable storage medium.

[0119] This disclosure also provides a computer program product 60, such as... Figure 6 The diagram shown is a schematic diagram of the structure of a computer program product 60 provided in an embodiment of this disclosure. The computer program product 60 carries a computer program 61. The program included in the computer program 61 can be used to execute the steps of the position update method described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0120] The above description, with reference to the accompanying drawings, outlines a location update method, apparatus, device, medium, and product according to embodiments of this disclosure. In these embodiments, firstly, the communication system acquires a first transmit power of each communication node, a second transmit power of a UAV relay node, and channel state information of the communication link between each communication node and the UAV relay node. This channel state information includes the distance between each communication node and the UAV relay node, the channel fading coefficient, and the path loss coefficient. Then, the first transmit power, the second transmit power, and the channel state information are processed to determine the signal-to-noise ratio (SNR) of each communication node. Secondly, a first interruption probability of the communication link corresponding to each communication node is determined based on the SNR, the channel state information, and the first transmit power. Finally, the position of the UAV relay node is updated based on the first interruption probability. By utilizing the UAV as a relay communication node and by real-time sensing of the channel state of the communication node and the UAV relay node, the SNR and interruption efficiency, which indicate communication quality, are determined. The UAV position is then adjusted based on the interruption efficiency, enabling the UAV to intelligently respond to real-time changes in the channel environment and remain in the area with optimal communication quality, thereby improving the UAV's communication efficiency.

[0121] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.

[0122] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0123] Additionally, as used herein, the "or" used in a list of items beginning with "at least one" indicates a separate list, such that a list of, for example, "at least one of A, B, or C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not imply that the described example is preferred or better than other examples.

[0124] It should also be noted that in the systems and methods of this disclosure, the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered as equivalent solutions to this disclosure.

[0125] Various changes, substitutions, and modifications can be made to the technology described herein without departing from the teachings defined by the appended claims. Furthermore, the scope of the claims of this disclosure is not limited to the specific aspects of the processes, machines, manufactures, events, means, methods, and actions described above. Currently existing or later-developed processes, machines, manufactures, events, means, methods, or actions that perform substantially the same function or achieve substantially the same result as the corresponding aspects described herein can be utilized. Therefore, the appended claims include such processes, machines, manufactures, events, means, methods, or actions within their scope.

[0126] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0127] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this disclosure to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A location updating method, characterized by, Applied to a communication system comprising one unmanned aerial vehicle relay node and at least two communication nodes deployed on the ground, comprising: obtaining a first transmission power of each of the communication nodes, a second transmission power of the unmanned aerial vehicle relay node, and channel state information of a communication link between each of the communication nodes and the unmanned aerial vehicle relay node; wherein the channel state information comprises a distance between each of the communication nodes and the unmanned aerial vehicle relay node, a channel fading coefficient, and a path loss coefficient; processing the first transmission power, the second transmission power, and the channel state information to determine a signal-to-noise ratio of each of the communication nodes after processing; determining a first outage probability of a corresponding communication link of each of the communication nodes based on the signal-to-noise ratio, the channel state information, and the first transmission power; updating a position of the unmanned aerial vehicle relay node based on the first outage probability.

2. The method of claim 1, wherein, The processing of the first transmission power, the second transmission power, and the channel state information to determine a signal-to-noise ratio of each of the communication nodes after processing comprises: determining an original signal transmitted by each of the communication nodes to the unmanned aerial vehicle relay node and a noise signal of a corresponding communication link of each of the communication nodes; processing the original signal based on the first transmission power, the second transmission power, the channel state information, and the noise signal to determine a power gain of the unmanned aerial vehicle relay node after processing; determining a signal-to-noise ratio of each of the communication nodes based on the power gain.

3. The method of claim 2, wherein, The processing of the original signal based on the first transmission power, the second transmission power, the channel state information, and the noise signal to determine a power gain of the unmanned aerial vehicle relay node after processing comprises: processing the original signal based on the first transmission power, the distance, the channel fading coefficient, the path loss coefficient, and the noise signal to obtain a first signal received by the unmanned aerial vehicle relay node from each of the communication nodes after processing; determining a power gain of the unmanned aerial vehicle relay node based on a ratio between the second transmission power and the first signal.

4. The method of claim 2, wherein, The determination of a signal-to-noise ratio of each of the communication nodes based on the power gain comprises: processing the first signal based on the power gain to obtain a second signal transmitted by the unmanned aerial vehicle relay node to each of the communication nodes after processing; wherein the first signal is the original signal processed based on the first transmission power, the distance, the channel fading coefficient, the path loss coefficient, and the noise signal; determining a signal-to-noise ratio of each of the communication nodes based on a square of the second signal.

5. The method of claim 1, wherein, The determination of a first outage probability of a corresponding communication link of each of the communication nodes based on the signal-to-noise ratio, the channel state information, and the first transmission power comprises: determining a received power of the unmanned aerial vehicle relay node for each of the communication nodes based on the distance, the channel fading coefficient, the path loss coefficient, and the first transmission power; determining a first outage probability of a corresponding communication link of each of the communication nodes based on a distribution function of the received power and the signal-to-noise ratio.

6. The method of claim 1, wherein, The updating the position of the UAV relay node based on the first outage probability comprises: determining a cumulative value of each of the first outage probability as a second outage probability of the communication system; determining initial position information of the UAV relay node; calculating a product between a gradient of the second outage probability and a moving step length; wherein the moving step length is a maximum moving distance of the UAV relay node in a time slot; determining a difference between the initial position information and the product as updated position information of the UAV relay node.

7. The method of claim 1, wherein, The determining the original signal transmitted by each of the communication nodes to the UAV relay node comprises: network coding the data to be transmitted by each of the communication nodes to obtain the original signal transmitted by each of the communication nodes to the UAV relay node.

8. A location updating apparatus, characterized by comprising: The application is applied to a communication system comprising one UAV relay node and at least two communication nodes deployed on the ground, and comprises: a data acquisition unit configured to acquire a first transmission power of each of the communication nodes, a second transmission power of the UAV relay node, and channel state information of a communication link between each of the communication nodes and the UAV relay node; wherein the channel state information comprises a distance between each of the communication nodes and the UAV relay node, a channel fading coefficient, and a path loss coefficient; a data processing unit configured to process the first transmission power, the second transmission power, and the channel state information to determine a signal-to-noise ratio of each of the communication nodes; a probability determination unit configured to determine a first outage probability of a corresponding communication link of each of the communication nodes based on the signal-to-noise ratio, the channel state information, and the first transmission power; a position updating unit configured to update a position of the UAV relay node based on the first outage probability.

9. An electronic device, comprising: The application comprises: a processor, a memory, and a bus, the memory stores machine readable instructions executable by the processor, when the electronic device is running, the processor and the memory communicate through the bus, and the machine readable instructions are executed by the processor to perform the steps of the position updating method according to any one of claims 1 to 7.

10. A computer program product, characterised in that, The computer program product is stored in a storage medium, and the program product is executed by at least one processor to implement the position updating method according to any one of claims 1 to 7.

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