Collaborative media access control method for large-scale UAV ad hoc networks

Abstract

The present invention provides a collaborative media access control method for large-scale unmanned aerial vehicle self-organizing networks. A collaborative low-latency MAC protocol CLAM is designed for large-scale unmanned aerial vehicle self-organizing networks. CLAM is divided into task collaboration and segmented access mechanisms. In the task collaboration stage, a regional center selection algorithm is designed to select a central UAV. The segmented access mechanism includes CLAM-Intra and CLAM-Inter processes. The principle of the CLAM method is simple and easy to understand. It can effectively reduce the problem of data packet collision caused by UAVs competing for time slots, while reducing the access delay of nodes, avoiding node starvation in the network, and improving the fairness of the network. In addition, each UAV can autonomously detect the distance between it and the adjacent UAVs in real time, and synchronize its own precise positioning to the surrounding UAVs. In this way, the UAV can quickly adjust the time slot allocation according to the changes in the network topology in a timely manner to improve the efficiency of inter-UAV communication.

Description

Technical Field

[0001] The present invention belongs to the technical field of communication networks, and in particular relates to a collaborative media access control method for large-scale unmanned aerial vehicle ad hoc networks. Background Art

[0002] With the advancement of science and technology, large-scale unmanned aerial vehicle (UAV) ad hoc networks (UAS) have attracted increasing attention. This architecture utilizes an ad-hoc network as the backbone and UAVs as node devices. It boasts strong scalability, survivability, and robustness, and is widely used in military and civilian applications such as emergency communications, disaster search and rescue operations, and forest monitoring. The Media Access Control (MAC) protocol is a key technology in large-scale UAV ad hoc networks. It addresses the efficient sharing of limited wireless channel resources among multiple UAVs (Unmanned Aerial Vehicles), playing a crucial role in overall network performance. The high-speed mobility of nodes in large-scale UAV ad hoc networks leads to frequent changes in network topology. These topology changes exacerbate link fluctuations and outages, impacting the accuracy and timeliness of data delivery. Designing an appropriate MAC protocol is crucial to improving the performance of large-scale, highly dynamic UAV ad hoc networks.

[0003] MAC protocols in large-scale UAV ad hoc networks can be divided into three categories based on their channel access strategies: allocation-based MAC protocols, contention-based MAC protocols, and hybrid MAC protocols. Allocation-based MAC protocols require pre-allocation of time slots based on mission requirements and the number of nodes, making them difficult to implement quickly. Contention-based MAC protocols avoid packet collisions through carrier sensing, control frame interaction, and backoff strategies, offering advantages in large-scale UAV ad hoc networks. Hybrid protocols combine the advantages of both approaches and are suitable for a wider range of application scenarios, but their design is more complex, and achieving optimal performance between the two mechanisms remains a challenge.

[0004] In contention-based MAC protocols, high control packet overhead, hidden terminals, exposed terminals, conflicts, and multiple retransmissions all degrade the performance of drone ad hoc networks. The following existing technologies are used as examples:

[0005] The paper [Medium Access Control With Station Presence Awareness in Crowded Networks] focuses on the issue of network performance degradation in high-traffic wireless ad hoc networks. By sensing the number of transmitting nodes in the network and dynamically adjusting the size of the contention window based on the number of nodes, this approach provides equal contention opportunities for nodes in the network. However, this approach is not suitable for highly dynamic networks and cannot effectively reduce node access latency. The paper [On the performance offlying ad-hoc networks (FANETs) with directional antennas] uses multiple directional antennas on a single drone running the IEEE 802.11 protocol to extend transmission range and reuse frequencies. However, directional antennas require accurate location information for information exchange, and switching between antennas must be intelligent.

[0006] In contention-based MAC protocols, high control packet overhead, hidden and exposed terminals, collisions, and multiple retransmissions all degrade the performance of UAV ad hoc networks. These shortcomings become even more pronounced in large-scale UAV ad hoc networks. Improving the access mechanism of MAC protocols to increase network throughput and reduce access latency is a key research issue at the MAC layer. Summary of the Invention

[0007] In order to solve the above problems existing in the prior art, the present invention provides a collaborative media access control method for large-scale unmanned aerial vehicle ad hoc networks. The technical problem to be solved by the present invention is achieved through the following technical solutions:

[0008] The present invention provides a collaborative media access control method for large-scale unmanned aerial vehicle ad hoc networks, including:

[0009] Step 1: Obtain detection requirements and the total exploration range covered by the UAV ad hoc network, and determine at least one detection area within the total exploration range according to the detection requirements;

[0010] Among them, there are multiple drones performing detection tasks in each detection area;

[0011] Step 2: Divide the detection area into square virtual grids;

[0012] Step 3: Treat each UAV as a node and use the regional center selection algorithm to select the center node of each virtual grid;

[0013] Step 4: Any node in each virtual grid uses the segmented access mechanism to sequentially transmit its own data packets to other nodes in the virtual grid;

[0014] Among them, the segmented access mechanism is that any node in the virtual grid determines whether to enter the queue access state or the backoff waiting state according to the transmission time slot number of the central node receiving the data packet; when in the queue access state, it waits for the central node to complete the transmission of the current data packet before exchanging data packets with the destination node; when in the backoff waiting state, it determines whether to exchange data packets with the backoff node based on the status of the backoff nodes in other detection areas and the number of time slots required by the backoff node.

[0015] Beneficial effects of the present invention:

[0016] The present invention provides a collaborative media access control method for large-scale unmanned aerial vehicle self-organizing networks. For large-scale unmanned aerial vehicle self-organizing networks, a collaborative low-latency MAC protocol CLAM is designed. CLAM is divided into task collaboration and segmented access mechanism. In the task collaboration stage, a regional center selection algorithm is designed to select the central UAV. The segmented access mechanism includes CLAM-Intra and CLAM-Inter processes. The principle of the CLAM method is simple and easy to understand. It can effectively reduce the problem of data packet collision caused by UAVs competing for time slots, while reducing the access delay of nodes, avoiding node starvation in the network, and improving the fairness of the network. In addition, each UAV can autonomously detect the distance between the adjacent UAVs in real time and synchronize its own precise positioning to the surrounding UAVs. In this way, the UAV can quickly adjust the time slot allocation according to the changes in the network topology in a timely manner to improve the efficiency of inter-UAV communication.

[0017] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Schematic diagram of the model system of the self-organizing network of unmanned aerial vehicles provided by the present invention;

[0019] Figure 2 This is a flow chart of a collaborative media access control method for large-scale unmanned aerial vehicle ad hoc networks provided by the present invention;

[0020] Figure 3 is a schematic diagram of the CLAM access model provided by the present invention;

[0021] Figure 4 This is a schematic diagram of the access process of CLAM-Intra provided by the present invention;

[0022] Figure 5 This is a schematic diagram of the CLAM-Inter access process provided by the present invention;

[0023] Figure 6 It is the overall implementation flow chart provided by the present invention. DETAILED DESCRIPTION

[0024] The present invention will be further described in detail below with reference to specific examples, but the embodiments of the present invention are not limited thereto.

[0025] The present invention provides a collaborative media access control method for large-scale UAV self-organizing networks, which is applied to UAV self-organizing networks. Figure 1 This is the large-scale flying self-organizing network system model described in the present invention. As the number of drones increases and the search space expands, almost every drone no longer possesses global information. Instead, it achieves group behavior by exchanging information with neighboring nodes. This invention divides different detection zones based on the range of drones' environmental perception and the tasks they perform, serving as the basis for collaborative communication in large-scale drone self-organizing networks. Drone tasks include target detection, target identification, and target tracking. While a single drone cannot simultaneously complete multiple tasks, the coordination of multiple drones can improve the speed and efficiency of task execution. Therefore, the multi-drone collaborative task allocation problem is divided based on three dimensions: the task coverage area, the number of drones required for the task, and the type of tasks performed by the drones. This invention assumes that channels beyond one hop are idle, and all drones within the divided detection zones can exchange data. The number of drones in different detection zones varies, and node communication between zones is achieved through a segmented access mechanism. The CLAM protocol supports drones joining and leaving. Specifically, drones in any zone can join, be forced to leave due to a fault, and notify the corresponding zone's central node to leave after declaring a fault.

[0026] The present invention designs the CLAM protocol for large-scale UAV ad hoc networks, which mainly includes two parts: task coordination and segmented access mechanism, as follows:

[0027] like Figure 2 As shown, the present invention provides a collaborative media access control method for large-scale unmanned aerial vehicle ad hoc networks, including:

[0028] Step 1: Obtain detection requirements and the total exploration range covered by the UAV ad hoc network, and determine at least one detection area within the total exploration range according to the detection requirements;

[0029] Among them, there are multiple drones performing detection tasks in each detection area;

[0030] Step 2: Divide the detection area into square virtual grids;

[0031] This step can be implemented as follows: Step 21: Determine the side length of the square based on the effective propagation distance R of the UAV wireless communication ; Step 22: Divide each detection area into a square virtual grid. .

[0032] Step 3: Treat each UAV as a node and use the regional center selection algorithm to select the center node of each virtual grid;

[0033] This step includes:

[0034] Step 31: For each node in the same virtual grid, calculate the speed similarity and motion similarity with neighboring nodes based on the node's speed;

[0035] Step 32: For each node in the same virtual grid, calculate the position similarity with the neighboring nodes based on the distance between the nodes;

[0036] Step 33: Calculate the total weight factor of the node according to the speed similarity, motion similarity and position similarity;

[0037] Step 34: Determine the node with the largest total weight factor as the central node of the virtual grid.

[0038] The task coordination part of step 1 to step 3 of the present invention is introduced in detail below.

[0039] 1. Task Collaboration

[0040] Key considerations for large-scale UAV ad hoc networks include the sensor payload of the drone swarm, the mobility of the mission target, and the urgency of the mission timeline. Furthermore, collaborative search is the foundation and prerequisite for large-scale UAV ad hoc networks. In such environments, drones carrying multiple sensors are often required to achieve search objectives through sensor collaboration. Therefore, the Cooperative Low Latency MAC (CLAM) protocol divides detection areas based on the different payloads and detection ranges of the drones.

[0041] Assume that each node knows its exact position relative to other nodes based on the BeiDou positioning system, and the entire area where the nodes are distributed is divided into small virtual grids. Before dividing the detection area, the spatial position is divided into grids with a side length of Each node in the Beidou positioning system returns its own square area number and corresponding location coordinates based on the Beidou positioning system. The purpose of the square area division is to cover all drone nodes and ensure that each node can enter the corresponding detection area. Next, a central node is elected within each detection area based on the regional center selection algorithm. This process is repeated when the detection area is re-divided. Steps 1 to 3 of the present invention constitute task coordination.

[0042] Let the virtual grid be a grid with a side length of The effective propagation distance of wireless communication of UAV is R. The conditions that need to be met are as follows.

[0043]

[0044] The regional center selection algorithm is used to determine whether a node is eligible to become a regional center. The main factors considered are: motion similarity, speed similarity, and position similarity.

[0045] (1) Speed similarity

[0046] The velocity of a node is v, and the distance from its neighbor is d. The velocity similarity can be expressed as:

[0047]

[0048] in

[0049]

[0050] n represents the number of neighbor nodes, represents the velocity of the i-th node.

[0051] (2) Motion similarity

[0052] Speed similarity can only describe the similarity of the mobility of a node in a detection area with its neighboring nodes, but it cannot reflect whether the mobility of nodes in the same detection area is the same. When the movement direction of the regional center and the member nodes in the region is very different or even opposite, it is easy to cause the network topology to change frequently and drastically, affecting the overall performance of the network. Therefore, the motion similarity parameter is used to describe the similarity of the movement trend of the central node and its neighboring nodes. The motion similarity of the central node and its neighboring nodes in the x and y axis directions is and .

[0053]

[0054] node The motion similarity with its neighbor nodes is .

[0055]

[0056] (3) Location similarity

[0057] Position similarity indicates the positional relationship between the central node and the nodes in its area. The closer the distance between the neighboring nodes and the center, the greater the probability that the node is in the center of the area, and the longer the communication distance can be maintained. The coordinates of the center position are expressed as:

[0058]

[0059] in, It is The coordinates of the nodes, the position similarity can be expressed as:

[0060]

[0061] The objective function is established based on speed similarity, motion similarity, and position similarity to determine the UAV collaborative mission model. The weight of a node in the region becoming the central node can be calculated according to the following formula. is the total weight factor, which can be expressed as:

[0062]

[0063] in 、 、 is the weight factor, ranging from 0 to 1, summing to 1. To simplify the analysis, we set all weight factors to 1 / 3. The precise planning of the weight factors for each parameter requires detailed analysis based on the application scenario and actual needs. In this step, the node with the largest total weight factor is selected as the center node of the virtual grid.

[0064] The segmented access mechanism of the present invention is described in detail below.

[0065] Step 4: Any node in each virtual grid uses the segmented access mechanism to sequentially transmit its own data packets to other nodes in the virtual grid;

[0066] The segmented access mechanism involves any node in the virtual grid determining whether to enter a queued access state or a backoff waiting state based on the number of transmission slots of the destination node receiving the data packet. When in the queued access state, the node waits for the destination node to complete transmission of the current data packet before exchanging data packets with the destination node. When in the backoff waiting state, the node determines whether to exchange data packets with the backoff node based on the status of other backoff nodes in the detection area and the number of time slots required by the backoff node. These data packets include information about joining and exiting the UAV ad hoc network, as well as detection data.

[0067] Step 41: Any node in each virtual grid determines a central node that receives the data packet sent by itself;

[0068] Step 42: When any node senses that a DIFS channel is idle, it randomly selects a backoff value within the backoff window and sends an RTS frame to the central node when the backoff count reaches 0.

[0069] Step 43: If multiple nodes send RTS frames to the central node, the RTS frames sent by the nodes collide with each other. The colliding nodes double the backoff window and randomly select a backoff value within the backoff window to repeatedly send RTS to the destination node until the central node receives the RTS frame sent by one node.

[0070] Step 44: After receiving the RTS frame, the central node broadcasts CTS to its neighbor nodes to inform them of the number of time slots required to exchange data packets with the node that sent the RTS frame;

[0071] Step 45: Any neighboring node listens to the carrier to obtain the number of time slots in the CTS, and determines whether it needs to enter the access waiting state or the backoff waiting state based on the number of time slots and the time required for its own data packet transmission;

[0072] Step 46: If the node is in the waiting access state, it waits for the next transmission opportunity to exchange data packets with the central node to transmit its own data packets to other nodes;

[0073] Step 47: If the node is in the backoff waiting state, it exchanges data with other nodes in the detection area that are also in the backoff waiting state, so as to transmit its own data packet to other nodes.

[0074] Step 471: If any node in a detection area is in a backoff waiting state, the node is determined as backoff node 1, and the nodes in other detection areas that are in a backoff waiting state are determined as backoff nodes 2;

[0075] Step 472: Select the backoff node 2 closest to the backoff node 1 as the backoff node 3, and send the RTD frame to the backoff node 3;

[0076] The RTD frame includes the detection area number of the node, the information that nodes in the same detection area cannot establish a communication link, and the number of time slots required for the data packet;

[0077] Step 473: When backoff node 3 receives the RTD frame, it determines whether its backoff time can complete the data packet transmission of backoff node 1. If so, it replies with CTD information to backoff node 1.

[0078] Step 474: After receiving the CTD information, back-off node 1 sends a data packet to back-off node 3 to perform data packet exchange, thereby transmitting its own data packet to other nodes.

[0079] 2. Segmented Access Mechanism

[0080] By leveraging task collaboration to simplify access in large-scale drone ad hoc networks, the MAC protocol design, characterized by numerous nodes, high collision probability, and inability to guarantee fairness, is transformed into two types: intra-regional access (CLAM-Intra) and inter-regional access (CLAM-Inter). By dividing detection zones based on detection range and drone mission requirements, multiple drones can better coordinate and improve network throughput. Details of the segmented access mechanism are as follows.

[0081] Figure 3 This is the CLAM access model of the present invention, which analyzes the access situation of node A. The MAC protocol refers to a channel access mechanism. It assumes that the channel is idle beyond one hop. When node C receives a data packet from node B, node A considers that the channel is idle and can receive information from nodes E, F or H.

[0082] In large-scale unmanned aerial vehicle (UAV) ad hoc networks, line of sight exists between drones in most situations, enabling direct data packet exchange after establishing a communication link. The designed CLAM protocol allows nodes with long access latency within a region to exchange data packets with adjacent nodes in different detection areas, reducing access latency and improving spatial reuse. The segmented access process in the CLAM protocol consists of two phases: CLAM-Intra and CLAM-Inter. It is important to note that the CLAM protocol assigns each node two states: queuing access node (QA) and backoff access node (BA). The node state has different impacts on the access process.

[0083] Figure 4This article describes the access process of CLAM-Intra, an improvement on IEEE 802.11. Each UAV node is equipped with both an omnidirectional antenna and a directional antenna, enabling directional transmission and omnidirectional reception. Node access within the area is similar to the IEEE 802.11 access mechanism. Nodes A, B, and D have data packets to transmit to node C. When they detect a DIFS (DCF Interframe Space) idle channel, they begin randomly selecting a backoff value using IEEE 802.11, setting the backoff window (CW) to a binary backoff window. When their random backoff counters reach 0, they each send a Request To Send (RTS) frame to node C. If a collision occurs between the nodes, they begin backing off and waiting for retransmission. When nodes B and C exchange data packets, node C broadcasts a Clear To Send (CTS) omnidirectionally, containing the number of time slots required for node B to transmit the data packet. This information is received by all one-hop neighbors within node C's communication range. After obtaining channel access, node B begins sending data packets to node C. Node C responds with an ACK (Acknowledgement) signaling the completion of the transmission, and the channel enters the idle state. While nodes B and C are communicating, nodes A and D are in the Network Allocation Vector (NAV) state and listening to the carrier. Node A considers node B's transmission time and the time required to send its own data packet to determine whether to continue waiting for access to node C or select a node in an adjacent detection area for data exchange. These are the two states: QA and BA. If the QA state is selected, the node continues to wait for the next transmission opportunity. If the BA state is selected, the CLAM-Inter process begins. Nodes in adjacent detection areas all access each other using the same MAC protocol.

[0084] Table 1 shows an analysis of inter-region access for node A. Spatial reuse is possible in the first and third scenarios. Node A is in the same state as nodes E and H, requiring a long backoff period before access can be established. In this scenario, the ideal state is directional access between nodes A and either E or H. Figure 5This is the CLAM-Inter access process. Nodes A and E perform the RTD-CTD process. Node A sends a directed RTD (Request To Delivery). The RTD contains the node's area number. Nodes in the same area cannot establish a communication link. Node E hears the RTD and determines that the backoff time is sufficient to complete the data packet exchange between nodes A and E. Therefore, node E responds with a CTD (Clear To Delivery). Nodes A and E then perform a directed data packet exchange. If there are multiple nodes in the BA state, the closest node is selected based on their relative positions at that moment.

[0085] Table 1 Analysis of access between node A regions

[0086]

[0087] The number of nodes in the BA state determines the access efficiency of the CLAM-Inter process. By adjusting the number of nodes in different states in the network, access latency can be significantly reduced and network throughput can be improved. During the RTD-CTD process, the duration of data exchange is determined by the number of backoff slots. If a node is in the BA state but the waiting time to access the central node is insufficient to complete a data packet exchange, the RTD-CTD process will not be initiated. After the RTD-CTD process completes data exchange, the node will no longer compete for access to the corresponding regional center.

[0088] refer to Figure 6 The overall implementation flow chart of the present invention is as follows: Figure 6 As shown. The present invention first divides the detection area, then selects the central node of each virtual grid according to the regional center algorithm. Then, the carrier sense channel of each node is checked to see if it is idle. If so, the process enters the CLAM-Intra phase, and then selects the appropriate CW for data packet exchange. If a collision occurs, the process enters the NAV process, determines whether the nodes in other detection areas support RTD-CTD, and if so, enters the CLAM-Inter phase to determine whether they can complete data packet exchange. If so, data packet exchange is carried out, and the transmission is successful. If not, the carrier sense continues.

[0089] The present invention provides a collaborative media access control method for large-scale unmanned aerial vehicle self-organizing networks. For large-scale unmanned aerial vehicle self-organizing networks, a collaborative low-latency MAC protocol CLAM is designed. CLAM is divided into task collaboration and segmented access mechanism. In the task collaboration stage, a regional center selection algorithm is designed to select the central UAV. The segmented access mechanism includes CLAM-Intra and CLAM-Inter processes. The principle of the CLAM method is simple and easy to understand. It can effectively reduce the problem of data packet collision caused by UAVs competing for time slots, while reducing the access delay of nodes, avoiding node starvation in the network, and improving the fairness of the network. In addition, each UAV can autonomously detect the distance between the adjacent UAVs in real time and synchronize its own precise positioning to the surrounding UAVs. In this way, the UAV can quickly adjust the time slot allocation according to the changes in the network topology in a timely manner to improve the efficiency of inter-UAV communication.

[0090] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature identified as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0091] Although the present application is described herein with reference to various embodiments, those skilled in the art will be able to understand and implement other variations of the disclosed embodiments in practicing the claimed application by reviewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality.

[0092] The above is a further detailed description of the present invention in conjunction with specific preferred embodiments, and the specific implementation of the present invention should not be considered to be limited to these descriptions. For those skilled in the art of the present invention, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should be considered to fall within the scope of protection of the present invention.

Claims

1. A collaborative media access control method for large-scale unmanned aerial vehicle ad hoc networks, characterized in that: include: Step 1: Obtain detection requirements and the total exploration range covered by the UAV ad hoc network, and determine at least one detection area within the total exploration range according to the detection requirements; Among them, there are multiple drones performing detection tasks in each detection area; Step 2: Divide the detection area into square virtual grids; Step 3: Treat each UAV as a node and use the regional center selection algorithm to select the center node of each virtual grid; Step 4: Each node in each virtual grid transmits its own data packet to the central node in turn in the virtual grid using the segmented access mechanism; Among them, the segmented access mechanism is that any node in the virtual grid determines whether it enters the queue access state or the backoff waiting state according to the transmission time slot number of the central node receiving the data packet; when in the queue access state, it waits for the central node to complete the transmission of the current data packet and then exchanges data packets with the central node; when in the backoff waiting state, it determines whether to exchange data packets with the backoff node based on the status of the backoff nodes in other detection areas and the number of time slots required by the backoff node. The data packet includes the situation of joining and exiting the drone self-organizing network and detection data.

2. The collaborative media access control method for large-scale unmanned aerial vehicle ad hoc networks according to claim 1, characterized in that: Step 2 includes: Step 21: Determine the side length of the square based on the effective propagation distance R of the drone's wireless communication ; Step 22: Divide each detection area into a square virtual grid; in, .

3. The collaborative media access control method for large-scale unmanned aerial vehicle ad hoc networks according to claim 1, characterized in that: Step 3 includes: Step 31: For each node in the same virtual grid, calculate the speed similarity and motion similarity with neighboring nodes based on the node's speed; Step 32: For each node in the same virtual grid, calculate the position similarity with the neighboring nodes based on the distance between the nodes; Step 33: Calculate the total weight factor of the node according to the speed similarity, motion similarity and position similarity; Step 34: Determine the node with the largest total weight factor as the central node of the virtual grid.

4. The collaborative media access control method for large-scale unmanned aerial vehicle ad hoc networks according to claim 3, characterized in that: The speed similarity in step 31 is: in, , n represents the number of neighbor nodes, represents the speed of the i-th node; The motion similarity in step 31 is: ; Among them, the movement similarity between the central node and its neighboring nodes in the x and y axis directions is and , ； The position similarity in step 32 is: ; The coordinates of the center position are: , It is The coordinates of the nodes; The total weight factor of the node in step 33 is: in, 、 、 is a weight factor, ranging from 0 to 1, and sums to 1.

5. The collaborative media access control method for large-scale unmanned aerial vehicle ad hoc networks according to claim 1, characterized in that: Step 4 includes: Step 41: Any node in each virtual grid determines a central node that receives the data packet sent by itself; Step 42: When any node senses that a DIFS channel is idle, it randomly selects a backoff value within the backoff window and sends an RTS frame to the central node when the backoff count reaches 0. Step 43: If multiple nodes send RTS frames to the central node, the RTS frames sent by the nodes collide with each other. The colliding nodes repeat sending RTS to the central node by doubling the backoff window and randomly selecting a backoff value within the backoff window until the central node receives the RTS frame sent by a node. Step 44: After receiving the RTS frame, the central node broadcasts CTS to its neighbor nodes to inform them of the number of time slots required to exchange data packets with the node that sent the RTS frame; Step 45: Any neighboring node listens to the carrier to obtain the number of time slots in the CTS, and determines whether it needs to enter the access waiting state or the backoff waiting state based on the number of time slots and the time required for its own data packet transmission; Step 46: If the node is in the waiting access state, it waits for the next transmission opportunity to arrive and exchanges data packets with the central node to transmit its own data packets to the central node; Step 47: If the node is in the backoff waiting state, it exchanges data with other nodes in the detection area that are also in the backoff waiting state, so as to transmit its own data packet to other nodes.

6. The collaborative media access control method for large-scale unmanned aerial vehicle ad hoc networks according to claim 5, characterized in that: Step 47 includes: Step 471: If any node in a detection area is in a backoff waiting state, the node is determined as backoff node 1, and the nodes in other detection areas that are in a backoff waiting state are determined as backoff nodes 2; Step 472: Select the backoff node 2 closest to the backoff node 1 as the backoff node 3, and send the RTD frame to the backoff node 3; The RTD frame includes the detection area number of the node, the information that nodes in the same detection area cannot establish a communication link, and the number of time slots required for the data packet; Step 473: When backoff node 3 receives the RTD frame, it determines whether its backoff time can complete the data packet transmission of backoff node 1. If so, it replies with CTD information to backoff node 1. Step 474: After receiving the CTD information, back-off node 1 sends a data packet to back-off node 3 to perform data packet exchange, thereby transmitting its own data packet to other nodes.

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