A method for constructing a UAV networking MAC protocol

Abstract

The application discloses a method for constructing a MAC protocol of a UAV network, a transmission process of data packets with different priorities is modeled by a finite state Markov chain, and a cross-level priority promotion mechanism based on failure counting is introduced. The method aims to solve the problem of long-term blocking of low-priority services caused by traditional fixed-priority protocols in post-disaster emergency communication scenarios, thereby improving the overall throughput, reducing the average delay, and enhancing the fairness among multiple types of services while ensuring the strict service quality of high-priority services.

Description

Technical Field

[0001] This invention belongs to the field of unmanned aerial vehicle (UAV) technology, specifically relating to a method for constructing a UAV networking MAC protocol. Background Technology

[0002] In emergency response to large-scale natural disasters (such as earthquakes and floods), drone swarms need to be rapidly networked to provide temporary communication and sensing coverage. The services carried by this network are highly heterogeneous: services such as rescue commands, survivor location tracking, and vital sign telemetry require extremely high reliability and real-time performance and are considered high-priority services; while services such as environmental monitoring, logistics coordination, and network management, although having slightly lower real-time requirements, are equally crucial for maintaining network stability and supporting global decision-making. Therefore, there is an urgent need for a multi-access protocol that can differentiate service priorities and guarantee the quality of service for high-priority services.

[0003] Existing technologies, such as statistical priority multiple access protocols, achieve basic service differentiation by allocating different channel access probabilities to services of different priorities. However, these protocols typically use fixed access parameters and lack dynamic adjustment mechanisms. Under high network load, low-priority service data packets may experience multiple transmission failures and be discarded due to their low access probability, resulting in the inability to upload critical non-real-time information, thereby weakening the system's overall information perception capability and robustness. Furthermore, existing protocols lack a rigorous mathematical model to characterize the interaction relationships between services of different priorities in a dynamic competitive environment, making protocol parameters often dependent on empirical tuning, which makes it difficult to achieve optimal performance in complex and ever-changing UAV network environments. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, this invention provides a method for constructing a MAC protocol for UAV networking. It models the transmission process of data packets with different priorities using a finite-state Markov chain and introduces a cross-level priority promotion mechanism based on failure counting. This method aims to solve the problem of long-term blocking of low-priority services caused by traditional fixed-priority protocols in post-disaster emergency communication scenarios. It thereby improves the overall system throughput, reduces average latency, and enhances fairness among various service types while ensuring strict quality of service for high-priority services.

[0005] The technical solution adopted by this invention to solve its technical problem is as follows: Step 1: Model the network as a multi-priority, multi-channel time-slot access system; Define the number of priority levels in the system as follows: And define the current priority for each packet. , 0 is the highest priority, and the consecutive failure count at that priority level. Define the maximum number of allowed failures. ; Step 2: The state of each data packet is represented by a tuple. The description is as follows, and the evolution occurs within the time slot according to the following rules: Step 2-1: If the data packet is in state If the transmission is attempted and successful, its state is reset to [state name]. ; Step 2-2: If the transmission fails and the current failure count is... Then its state is updated to And continue trying in subsequent time slots; Steps 2-3: If transmission fails and the current failure count is... : 1) If its current priority is not the highest If so, the data packet will be elevated to a higher priority level. And reset the failure count, the status becomes ; 2) If it is currently at the highest priority, i.e. The data packet remains in the state. Keep trying until you succeed; Step 3: Establish a steady-state performance analysis model based on the Markov chain, and derive the steady-state performance indices of the system, including: (1) System throughput: Total system throughput The sum of data packets successfully transmitted across all priorities, i.e. ,in To enter priority Total data packet arrival rate This represents the probability of failure in a single attempt. (2) Average delay: a delay from priority The average end-to-end delay of the data packets that have begun to be transmitted. The sum of the average dwell time slots across all priorities it experiences, expressed by the formula... To make an estimate, among which In priority Average number of time slots within, To prioritize The probability of upgrading; Step 4: Based on the locally estimated channel state and according to the steady-state performance analysis model based on the Markov chain, the node dynamically adjusts itself in different states. Transmission probability under This is to achieve adaptive load balancing and performance optimization of the network.

[0006] Preferably, the number of priority levels .

[0007] Preferably, the maximum allowed number of failures .

[0008] An electronic device includes: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the above-described method for constructing a UAV network MAC protocol.

[0009] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method for constructing a UAV networking MAC protocol.

[0010] A chip includes a processor for calling and running a computer program from a memory, causing a device equipped with the chip to execute the above-described method for constructing a UAV networking MAC protocol.

[0011] A computer program product includes a computer storage medium storing a computer program, the computer program including instructions executable by at least one processor, which, when executed by the at least one processor, implement the above-described method for constructing a UAV networking MAC protocol.

[0012] The beneficial effects of this invention are as follows: This invention effectively prevents the "starvation" phenomenon caused by long-term channel contention failures by introducing a failure-count-triggered dynamic priority promotion mechanism, significantly improving the throughput and transmission success rate of low- and medium-priority services. Rigorous modeling based on Markov chains provides a solid basis for the design and optimization of protocol parameters, enhancing the protocol's robustness in dynamic network environments. This method maintains more stable latency performance and higher channel slot utilization as node density increases, thus ensuring the overall communication efficiency and reliability of large-scale UAV networks in emergency scenarios, achieving a good balance between low latency for high-priority services and high overall system throughput and fairness. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of a post-disaster drone communication system model; Figure 2 This is a flowchart of the EDMA protocol operation provided in the embodiment; Figure 3 It is the state transition diagram of the constructed multi-priority Markov retransmission chain; Figure 4 This is a comparison chart of EDMA and the traditional SPMA protocol on different performance metrics. Detailed Implementation

[0014] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0015] The purpose of this invention is to overcome the aforementioned deficiencies of the prior art and provide a method and system for dynamic priority-upgrading access based on Markov chains. This method aims to solve the problem of long-term blocking of low-priority services caused by traditional fixed-priority protocols in post-disaster emergency communication scenarios, thereby improving overall system throughput, reducing average latency, and enhancing fairness among various service types while ensuring strict quality of service for high-priority services.

[0016] To achieve the above objectives, this invention proposes a media access control protocol called EDMA. Its core lies in modeling the transmission process of data packets with different priorities using a finite-state Markov chain and introducing a cross-level priority promotion mechanism based on failure counting. The specific steps of this technical solution are as follows: Step 1: Model the network as a multi-priority, multi-channel time-slot access system. Define the number of priority levels in the system as follows: And define the current priority for each packet. ( (0 being the highest priority) and the consecutive failure count at that priority level. Define the maximum number of allowed failures. .

[0017] Step 2: The state of each data packet is represented by a tuple. The description is as follows, and the evolution occurs within the time slot according to the following rules: (1) If the data packet is in state If the transmission is attempted and successful, its state is reset to [state name]. .

[0018] (2) If the transmission fails and the current failure count is... Then its state is updated to And continue trying in subsequent time slots.

[0019] (3) If the transmission fails and the current failure count is... : 3.1) If its current priority is not the highest (i.e. If the packet is elevated to a higher priority level, then the packet will be promoted to a higher priority level. And reset the failure count, the status becomes .

[0020] 3.2) If it is currently at the highest priority (i.e. If the data packet remains in the state, then the packet is held in the state. Keep trying until you succeed.

[0021] Step 3: Based on the Markov chain, derive the steady-state performance indices of the system to provide a theoretical basis for parameter optimization. Key performance indices include: (1) System throughput: Total system throughput The sum of data packets successfully transmitted across all priorities, i.e. ,in To enter priority Total data packet arrival rate This represents the probability of failure in a single attempt.

[0022] (2) Average delay: a delay from priority The average end-to-end delay of the data packets that have begun to be transmitted. The sum of the average dwell time slots across all priorities it experiences can be expressed by the formula... To make an estimate, among which In priority Average number of time slots within, To prioritize The probability of upgrading.

[0023] Step 4: The node estimates the channel state locally (e.g., collision probability). Based on the above performance analysis model, it dynamically adjusts its performance in different states. Transmission probability under This is to achieve adaptive load balancing and performance optimization of the network.

[0024] Example: This embodiment is based on a typical post-disaster drone communication scenario (such as...). Figure 1 The system, as shown in the figure, comprises 36 UAV nodes and multiple ground terminals, forming a multi-hop self-organizing network. The system uses eight orthogonal channels, each with a transmission rate of 2 Mbit / s, and the time is divided into discrete time slots of 0.5 ms in length.

[0025] Step 1: In this embodiment, the key system parameters are first initialized and configured: the system priority level is set. This configuration effectively controls protocol state complexity while ensuring sufficient service differentiation; it sets the maximum allowed number of failures for each data packet within a single priority level. This value has been proven to strike a good balance between avoiding over-upgrading and preventing long-term blockage; at the same time, for each priority level... ( Configure a set of basic transmission probabilities Its value decreases as priority decreases, for example, from the highest priority... Decrease to lowest priority In addition, each network node maintains a queue of data packets to be transmitted, and dynamically maintains a state variable for each data packet in the queue to record its current state. .

[0026] Step 2: The overall process for this step can be found in [link to relevant documentation]. Figure 2 The diagram shows the EDMA protocol operation flowchart.

[0027] (1) When a new data packet arrives at the node, it is first mapped to the corresponding initial priority according to its service type (such as emergency command, video stream, environmental data, etc.). ( (At its highest level). The packet was then assigned an initial state. And then enter the node's pending transmission queue.

[0028] (2) At the beginning of each time slot, the node has the data packets at the head of its queue (in state). Calculate the current actual transmission probability. (3) If a node decides to access the network, it sends a data packet on a randomly selected idle channel. After sending the packet, the node waits for an acknowledgment (ACK) from the physical layer.

[0029] (4) If an ACK is received within the predetermined time, the transmission is considered successful. The data packet is deemed to have been successfully transmitted and removed from its queue. At the same time, the state machine of the data packet terminates, and the resources it occupied are released.

[0030] (5) If no ACK is received (i.e., a collision or channel error has occurred), the transmission is considered a failure. The node increments the failure counter for this data packet. Increase ,Right now .

[0031] (6) This step is the core of the invention, and its state transition logic is as follows: Figure 3 The Markov chain model shown.

[0032] 6.1) If the updated failure count The data packet will remain at its current priority. Its status is updated to And return to step 2 (2) to wait for the next transmission opportunity.

[0033] 6.2) If the updated failure count If the maximum number of retries allowed for this priority level has been reached, then the priority promotion mechanism will be triggered: 6.2.1) If the current priority If the packet is not of the highest priority, then a priority upgrade will be performed: the priority of the packet will be increased by one level, i.e. and reset the failure counter. The new status of the data packet is , and re-enter the competition with its new priority base transmission probability, and return to step 2 (2).

[0034] 6.2.2) If the current priority If it is already the highest priority, then execute the highest level of persistence: the data packet will no longer be updated, and the state will remain unchanged. and in subsequent time slots, with their corresponding transmission probabilities Keep trying until you succeed.

[0035] Step 3: During system operation, each node periodically (e.g., every 1000 time slots) monitors its transmission results on each priority channel and calculates the real-time failure probability. The monitored Substitute these values ​​into the performance analysis model constructed in this invention. For example, calculate the actual throughput of the current network: .

Claims

1. A method for constructing a MAC protocol for unmanned aerial vehicle (UAV) networking, characterized in that, Includes the following steps: Step 1: Model the network as a multi-priority, multi-channel time-slot access system; Define the number of priority levels in the system as follows: And define the current priority for each packet. , 0 is the highest priority, and the consecutive failure count at that priority level. ; Define the maximum number of allowed failures ; Step 2: The state of each data packet is represented by a tuple. The description is as follows, and the evolution occurs within the time slot according to the following rules: Step 2-1: If the data packet is in state If the transmission is attempted and successful, its state is reset to [state name]. ; Step 2-2: If the transmission fails and the current failure count is... Then its state is updated to And continue trying in subsequent time slots; Steps 2-3: If transmission fails and the current failure count is... : 1) If its current priority is not the highest If so, the data packet will be elevated to a higher priority level. And reset the failure count, the status becomes ; 2) If it is currently at the highest priority, i.e. The data packet remains in the state. Keep trying until you succeed; Step 3: Establish a steady-state performance analysis model based on the Markov chain, and derive the steady-state performance indices of the system, including: (1) System throughput: Total system throughput The sum of data packets successfully transmitted across all priorities, i.e. ,in To enter priority Total data packet arrival rate This represents the probability of failure in a single attempt. (2) Average delay: a delay from priority The average end-to-end delay of the data packets that have begun to be transmitted. The sum of the average dwell time slots across all priorities it experiences, expressed by the formula... To make an estimate, among which In priority Average number of time slots within, To prioritize The probability of upgrading; Step 4: Based on the locally estimated channel state and according to the steady-state performance analysis model based on the Markov chain, the node dynamically adjusts itself in different states. Transmission probability under This is to achieve adaptive load balancing and performance optimization of the network.

2. The method for constructing a MAC protocol for UAV networking according to claim 1, characterized in that, The priority level number .

3. The method for constructing a MAC protocol for UAV networking according to claim 1, characterized in that, The maximum allowed number of failures .

4. An electronic device, characterized in that, include: Processor and memory; The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to cause the electronic device to perform the method as described in any one of claims 1 to 3.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 3.

6. A chip, characterized in that, include: A processor for retrieving and running a computer program from memory, causing a device on which the chip is mounted to perform the method as described in any one of claims 1 to 3.

7. A computer program product, characterized in that, The computer program product includes a computer storage medium storing a computer program, the computer program including instructions executable by at least one processor, which, when executed by the at least one processor, implement the method as described in any one of claims 1 to 3.

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