A Location-Based Resource Scheduling Method for Wireless Ad Hoc Networks

Abstract

This invention discloses a resource scheduling method for wireless ad hoc networks based on location information. Link establishment within a subnet follows a fixed time slot allocation strategy. After initial network establishment within a subnet, the link establishment phase between subnets employs a beam scanning algorithm based on Directed QN (DQN) and is applied in a real-world scenario using offline training. The offline-trained model parameters are stored in the nodes. During actual flight, the local airspace resource adjacency state table and the received neighbor node adjacency state tables are used as inputs to guide the node's beam pointing in the next time slot, accelerating the neighbor discovery process. Finally, an airspace resource adjacency state table for nodes between subnets is formed and dynamically updated. This invention improves neighbor discovery efficiency by updating beam pointing using node location information during multi-node flight while maintaining efficient link transmission during node flight.

Description

Technical Field

[0001] This invention relates to a resource scheduling method for wireless ad hoc networks based on location information, belonging to the field of wireless networks and communications. Background Technology

[0002] In future integrated and information-based communication scenarios, networks will exhibit highly dynamic, highly adversarial, and self-organizing characteristics, with collaborative applications among multiple nodes becoming mainstream. In this scenario, directional communication technology is typically used to improve network anti-interference performance while reducing inter-node interference and network energy consumption. Due to node mobility, rapid neighbor discovery is crucial in high-frequency directional networking. However, using directional narrow beams for communication, while reducing interference, also increases the difficulty of neighbor discovery, thus requiring the network to manage and control beams with fine precision. Therefore, intelligently managing airspace resources and dynamically aligning and connecting multiple beams among multiple nodes is the primary problem to be solved in directional communication technology.

[0003] Current research on time slot scheduling strategies in the neighbor discovery process largely assumes that nodes in ad hoc networks use omnidirectional antennas for communication. Time slot scheduling strategies can be divided into two categories. The first category is deterministic time slot scheduling strategies, which ensure that the working time slots of network nodes appear periodically and regularly according to a pre-defined strategy. The advantage of this type of algorithm is that the worst-case discovery delay can be theoretically derived. The disadvantages are that it lacks flexibility and has a relatively high average discovery delay. Typical deterministic scheduling strategies include Disco, U-Connect, and SearchLight. The second category is stochastic time slot scheduling strategies, which allow the working time slots of nodes to appear randomly with a certain probability. The advantages of this type of algorithm are a lower average discovery delay and greater flexibility. The disadvantages are that it exhibits a long-tail effect and the discovery delay has no boundary. Typical stochastic scheduling strategies include Birthday and PSBA.

[0004] Some scholars have proposed applying the Quorum system to beam scanning. The Quorum system can guarantee beam alignment between any two nodes within a certain timeframe. However, this method lacks flexibility and cannot adapt to changes in the network environment. Other researchers have used reinforcement learning for beam scanning. They define the possible directions the beam can point to as a finite set, using this set as the action space for reinforcement learning. The result of neighbor discovery is used as the reward, and a trained reinforcement learning model is used for beam configuration. This method does not consider the limited data and computational power of individual nodes in real-world scenarios, and it is not friendly to newly added nodes in the network because new nodes need to collect data again for learning. Summary of the Invention

[0005] The technical problem solved by this invention is to overcome the shortcomings of the prior art and provide a location-based wireless ad hoc network resource scheduling method, which realizes the use of node location information to update beam pointing during the flight of multiple nodes in the network to improve neighbor discovery efficiency, while maintaining efficient link transmission during node flight.

[0006] The technical solution of this invention is: a resource scheduling method for wireless ad hoc networks based on location information, wherein:

[0007] Step 1: Establish a node motion model, create an offline training scenario based on the node motion model, train the DQN model parameters, and store the trained model parameters in each gateway node;

[0008] Step 2: Link establishment within the subnet is carried out according to the fixed time slot allocation strategy. After the initial link establishment within the subnet is completed, the beam scanning algorithm based on DQN is used to establish initial links between subnets. That is, the offline trained DQN model parameters are used to guide the current link establishment node in the beam scanning direction of the next time slot to establish initial links between subnets. Each node in the subnet forms its own initial spatial resource adjacency state table.

[0009] Step 3: After the initial link is established between subnets, during actual flight, each node periodically broadcasts its own position information. Other nodes receive this information and store it in their own airspace resource adjacency state table. When the current sending node A sends information to the adjacent receiving node B, sending node A queries its own airspace resource adjacency state table to obtain the position information of receiving node B.

[0010] Step 4: Using the sending node A as the origin of the coordinate system, calculate the two rotation angles α and β corresponding to the receiving node B;

[0011] Step 5: Based on α, β and the sector number table, look up the sector number where the receiving node B is located at this moment, and modify the sector number information of the receiving node B in the spatial resource adjacency status table accordingly.

[0012] Step 6: For each node whose location has changed, return to Step 3 and continuously update the information in the airspace resource adjacency status table.

[0013] Preferably, the node motion model includes two parameters: node speed and node motion offset angle. After setting the parameters, during the inter-subnet link establishment phase, the gateway node divides its own spatial domain into N sectors.

[0014] Preferably, the inputs to the DQN model are node motion model parameters, the number of sectors N, and the number of one-hop neighbors and two-hop neighbors in each sector; the parameters of the trained DQN model are the sector number and the corresponding action value function, i.e., the Q value.

[0015] Preferably, the process of establishing links between subnets using the beam scanning algorithm based on DQN is as follows:

[0016] Step 2-1: Initialize the spatial resource adjacency state table;

[0017] Step 2-2: The current link establishment gateway node obtains the next time slot scanning sector by running the trained DQN model parameters offline based on the current spatial resource adjacency status table.

[0018] Step 2-3: The current link establishment gateway node selects the next time slot reception or transmission state according to the time slot usage method of the service channel in the initial link establishment stage, and points the beam of the current node to the next time slot scanning sector obtained by the DQN model.

[0019] Step 2-4: If the current time slot is in the sending state, the current link establishment gateway node sends a hello message to the sector to be scanned, carrying the local airspace resource adjacency status table; if the current time slot is in the receiving state, it receives the neighbor node's hello message and updates the local airspace resource adjacency status table.

[0020] Step 2-5: Proceed to Step 2-2 until all gateway nodes that need to be linked are traversed, completing the initial inter-subnet link establishment.

[0021] Preferably, the airspace resource adjacency status table includes information about the neighboring nodes of this node and the sector information corresponding to the neighboring nodes.

[0022] Preferably, with the current processing node as the origin of the coordinate system, the two rotation angles α and β corresponding to the neighboring nodes are calculated, specifically as follows:

[0023] Let the coordinates of the sending node A be (x0, y0, z0), and the coordinates of the receiving node B be (x1, y1, z1); where:

[0024]

[0025] If y1≥y0, then

[0026] Conversely,

[0027] Preferably, each node in the network carries multiple antennas distributed around the node. The number is determined based on the actual situation, but it should be able to cover 360 degrees of communication around the node.

[0028] When two nodes A and B communicate, the sending node A calculates the elevation and azimuth angles of node B relative to node A based on its own position, its own attitude, and the position of the receiving node B, and selects the corresponding antenna for communication.

[0029] Preferably, when two nodes A and B communicate, node A calculates the distance between the two nodes based on its own position and the position of node B, divides the communication distance into different communication rate levels, and determines the corresponding transmission link frame length for information transmission.

[0030] Preferably, when different communication distances are divided into different communication rate levels:

[0031] Short distances correspond to high-speed transmission rates, longer transmission frame lengths, and larger transmission capacity; long distances correspond to low-speed transmission rates, shorter transmission frame lengths, and smaller transmission capacity.

[0032] Preferably, the usage of time slots for the service channel during the initial link establishment phase is as follows: each node's time slot is used for either sending or receiving randomly, with a probability of 1 / 2 for both.

[0033] Compared with the prior art, the present invention has the following advantages:

[0034] (1) This invention proposes a smart beam scanning method based on DQN, which uses the model parameters after offline training, the airspace resource adjacency state table during actual flight and the received neighbor node adjacency state table to update the beam pointing, guide the beam scanning direction of the node in the next time slot, and speed up the neighbor discovery process.

[0035] (2) This invention proposes a method for beam alignment using node location information, attitude information, and antenna installation position, and dynamically changes the link transmission frame length according to the distance relationship between nodes, so as to make full use of link resources and improve transmission capacity. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the hierarchical and clustered network architecture in this invention;

[0037] Figure 2 This is a schematic diagram of the beam scanning algorithm based on DQN in this invention;

[0038] Figure 3 This is a schematic diagram of the beam position in this invention;

[0039] Figure 4 This is a schematic diagram of the rotation angle in this invention. Detailed Implementation

[0040] This invention addresses the need for rapid network construction and inter-node links during flight in large-scale wireless networking scenarios, proposing a method for airspace resource scheduling that enables rapid neighbor discovery and maintains efficient link transmission.

[0041] like Figure 1 The diagram shown is a schematic of the hierarchical and clustered network architecture of the present invention. The subnet to which each node belongs is determined according to the network plan. Each subnet is configured with a unique subnet number. Orthogonal frequency hopping is supported between subnets. The network management node manages the node resources within the subnet. Data is exchanged between subnets through the gateway node. Figure 2 This is a schematic diagram of the beam scanning algorithm based on DQN.

[0042] First, determine the type of this node: gateway, network management node, or ordinary node. Different nodes have different functional modules they are responsible for, as follows: 1) Ordinary node: Has basic communication and forwarding functions, and is managed by the network management node. 2) Network management node: In addition to the functions of an ordinary node, it adds network management functions. It manages the identities and resources of all nodes within the subnet. 3) Gateway node: In addition to the functions of an ordinary node, it adds inter-subnet cluster communication functions, becoming the subnet aggregation point and forwarding point for cross-subnet communication.

[0043] Within a subnet, link establishment follows a fixed time slot allocation strategy. After initial network establishment within a subnet, the link establishment phase between subnets employs a beam scanning algorithm based on DQN, applied in a real-world scenario using offline training. The offline-trained model parameters are stored in the nodes. During actual flight, the local airspace resource adjacency state table and the received neighbor node adjacency state tables are used as input to guide the node's beam pointing in the next time slot, accelerating the neighbor discovery process and ultimately forming the airspace resource adjacency state table between subnet nodes. The main process is as follows: Figure 2 As shown. The specific steps are as follows:

[0044] 1. Establish a node motion model, which mainly includes two parameters: node velocity and node motion offset angle. After setting the parameters, during the inter-subnet link establishment phase, the gateway node divides its own spatial domain into N sectors. Based on the node motion model, create an offline training scenario to train the DQN model parameters. The DQN algorithm input is the node motion model parameters, the number of sectors N, and the number of one-hop neighbors and two-hop neighbors in each sector (for example, if the spatial resource adjacency state table of node 1 is [2,3] and the spatial resource adjacency state table of node 5 is [7,8], then after node 1 and node 5 establish a connection, nodes 2, 3, and 5 are one-hop neighbors of node 1, and nodes 7 and 8 are two-hop neighbors of node 1). The trained model parameters are stored in each gateway node. The trained DQN model parameters are the sector number and the corresponding Q value (action value function).

[0045] 2. The gateway node runs the trained DQN model based on the current state (the spatial resource adjacency state table, which mainly includes neighboring nodes and the sectors they belong to) and the spatial resource adjacency state table it receives from neighboring nodes, to obtain the sector number to be scanned in the next time slot (i.e., the sector number corresponding to the largest Q value).

[0046] 3. Nodes select the next time slot's receive / transmit state based on the time slot usage pattern of the service channels during the initial network deployment phase, and direct the current node's beam towards the next time slot's scanning sector. The time slot usage pattern of the service channels during the initial network deployment phase is as follows: each node's transmit or receive state in each time slot is random, with a probability of 1 / 2.

[0047] 4. If this time slot is in the sending state, this gateway node sends a hello message to the sector to be scanned, carrying the local airspace resource adjacency status table (mainly including its own neighbor nodes and the sectors where the neighbor nodes are located).

[0048] 5. If the current time slot is in receiving state and a hello message is received from a neighboring node, update the local airspace resource adjacency state table and the neighbor adjacency state table, update the current state, and proceed to step 2 until the initial network construction process is completed.

[0049] In three-dimensional space, the position of any point can be represented by coordinates (x, y, z). The line connecting this point to the origin is denoted as u. The projection of u onto the XOY plane of the current node's (sending node A) body coordinate system is denoted as v. The rotation angle from the positive X-axis direction counterclockwise to the projection v on the XOY plane is denoted as α, where α ∈ [0, 2π). The rotation angle from the positive Z-axis direction towards the line u to u is denoted as β, where β ∈ [0, π]. For example... Figure 4 As shown. The specific location of a point in space can be determined by two rotation angles, α and β, and its specific coordinates can be obtained from the distance between the point and the origin.

[0050] The beam alignment algorithm based on position information during node flight calculates the deviation angle of neighboring nodes based on the position information of neighboring nodes, its own position, and attitude information, thereby updating the sector information of the neighboring nodes. The specific algorithm flow is as follows:

[0051] 1. After the initial link is established between subnets, during the actual flight process, each node periodically broadcasts its own location information. Other nodes receive this information and store it in their own neighbor location information table. When the network completes the initial link establishment and is running normally, taking the current sending node A and the adjacent receiving node B as an example, when node A wants to send information to node B, node A knows its own location and then queries its own stored neighbor location information table to obtain node B's location information.

[0052] 2. Obtain the coordinates (x0, y0, z0) of node A (sending node) at this moment and the coordinates (x1, y1, z1) of its neighbor node B (receiving node);

[0053] 3. According to Figure 3 The diagram illustrates the rotation angles. Calculate the two rotation angles α and β corresponding to the neighboring node B, with node A as the origin of the coordinate system: If y1≥y0, then Conversely,

[0054] 4. Using α, β, and the sector numbering rules, look up the sector number num_1 where the neighboring node B is located at this moment. The sector numbering rules are as follows:

[0055] Since each beam uniquely corresponds to a set of azimuth and elevation angles (α, β), the beam sector number and its corresponding (α, β) are shown in the table below, where x is the beamwidth.

[0056] 5. Modify the sector number of the neighbor node in the neighbor location information table to num_1;

[0057] 6. Each node in the network carries multiple antennas, which are distributed around the node. The number of antennas is determined based on the actual situation and must be able to handle 360-degree communication around the node. When two nodes A and B communicate, node A will calculate the elevation angle and azimuth angle of node B relative to node A based on its own position, its own attitude and the position of node B, and select the corresponding antenna for communication.

[0058] 7. Calculate the distance between node A and node B based on their position coordinates.

[0059] 8. Divide the communication distance into different communication rate levels, determine the corresponding transmission link frame length for information transmission, and utilize link resources to improve transmission capacity by transmitting information in different levels.

[0060] Short distances correspond to high-speed transmission rates, longer frame lengths, and larger transmission capacities; long distances correspond to low-speed transmission rates, shorter frame lengths, and smaller transmission capacities. Dividing the transmission rate into different levels is to adaptively change the transmission capacity according to the distance, which can make better use of resources compared to a fixed transmission rate.

[0061] The contents not described in detail in this specification are existing technologies known to those skilled in the art.

Claims

1. A resource scheduling method for wireless ad hoc networks based on location information, characterized in that... include: Step 1: Establish a node motion model, create an offline training scenario based on the node motion model, train the DQN model parameters, and store the trained model parameters in each gateway node; Step 2: Establish links within the subnet according to the fixed time slot allocation strategy; After the initial link establishment is completed within the subnet, the beam scanning algorithm based on DQN is used to establish the initial link establishment between subnets. That is, the offline trained DQN model parameters are used to guide the current link establishment node in the beam scanning direction of the next time slot to establish the initial link establishment between subnets. Each node in the subnet forms its own initial spatial resource adjacency state table. Step 3: After the initial link is established between subnets, during actual flight, each node periodically broadcasts its own position information. Other nodes receive this information and store it in their own airspace resource adjacency state table. When the current sending node A sends information to the adjacent receiving node B, sending node A queries its own airspace resource adjacency state table to obtain the position information of receiving node B. Step 4: Using the sending node A as the origin of the coordinate system, calculate the two rotation angles α and β corresponding to the receiving node B; Step 5: Based on α, β and the sector number table, look up the sector number where the receiving node B is located at this moment, and modify the sector number information of the receiving node B in the spatial resource adjacency status table accordingly. Step 6: For each node whose location has changed, return to Step 3 and continuously update the information in the airspace resource adjacency status table; The process of establishing links between subnets using the beam scanning algorithm based on DQN is as follows: Step 2-1: Initialize the spatial resource adjacency state table; Step 2-2: The current link establishment gateway node obtains the next time slot scanning sector by running the trained DQN model parameters offline based on the current spatial resource adjacency status table. Step 2-3: The current link establishment gateway node selects the next time slot reception or transmission state according to the time slot usage method of the service channel in the initial link establishment stage, and points the beam of the current node to the next time slot scanning sector obtained by the DQN model. Step 2-4: If the current time slot is in the sending state, the current link establishment gateway node sends a hello message to the sector to be scanned, carrying the local airspace resource adjacency status table. If the current time slot is in receiving mode, a hello message from a neighboring node will be received, and the local airspace resource adjacency status table will be updated. Step 2-5: Proceed to Step 2-2 until all gateway nodes that need to be linked are traversed, completing the initial inter-subnet link establishment.

2. The method for resource scheduling in a location-based wireless ad hoc network according to claim 1, characterized in that: The node motion model includes two parameters: node speed and node motion offset angle. After setting the parameters, during the link establishment phase between subnets, the gateway node divides its own airspace into N sectors.

3. The method for resource scheduling in a location-based wireless ad hoc network according to claim 1, characterized in that: The inputs to the DQN model are the node motion model parameters, the number of sectors N, and the number of one-hop neighbors and two-hop neighbors in each sector; The parameters of the trained DQN model are the sector number and the corresponding action value function, i.e., the Q value.

4. The method for resource scheduling in a location-based wireless ad hoc network according to claim 1, characterized in that: The airspace resource adjacency status table includes information about the neighboring nodes of this node and the sector information corresponding to the neighboring nodes.

5. A method for resource scheduling in a location-based wireless ad hoc network according to claim 1, characterized in that: Using the current processing node as the origin of the coordinate system, calculate the two rotation angles α and β corresponding to the neighboring nodes, specifically: Let the coordinates of the sending node A be (x0, y0, z0), and the coordinates of the receiving node B be (x1, y1, z1); where: If y1≥y0, then Conversely, 6. A method for resource scheduling in a location-based wireless ad hoc network according to claim 1, characterized in that: Each node in the network carries multiple antennas, distributed around the node. The number is determined based on the actual situation, but it should be able to cover a minimum of 360 degrees of communication. When two nodes A and B communicate, the sending node A calculates the elevation and azimuth angles of node B relative to node A based on its own position, its own attitude, and the position of the receiving node B, and selects the corresponding antenna for communication.

7. A method for resource scheduling in a location-based wireless ad hoc network according to claim 1, characterized in that: When two nodes A and B communicate, node A calculates the distance between the two nodes based on its own position and the position of node B, divides the communication distance into different communication rate levels, and determines the corresponding transmission link frame length for information transmission.

8. A method for resource scheduling in a wireless ad hoc network based on location information according to claim 7, characterized in that: When different communication distances are divided into different communication rate levels: Short distances correspond to high-speed transmission rates, longer transmission frame lengths, and larger transmission capacity; long distances correspond to low-speed transmission rates, shorter transmission frame lengths, and smaller transmission capacity.

9. A method for resource scheduling in a location-based wireless ad hoc network according to claim 1, characterized in that: During the initial link establishment phase, the usage of time slots for the service channel is as follows: each node's time slot is used for either sending or receiving randomly, with a probability of 1 / 2.

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