Multi-node communication path selection method, system and equipment based on terrain awareness

Abstract

The invention discloses a multi-node communication path selection method, system and equipment based on terrain awareness, and relates to the technical field of wireless communication. The method comprises the steps that topographic information data between nodes are received, the topographic information data comprise the distance between the nodes, the shielding area of an obstacle and the type of the obstacle, and signal attenuation calculation is conducted according to the topographic information data; and receiving the residual energy condition of each node, sharing the residual energy data with other nodes, and calculating the energy consumed by signal transmission among the nodes. According to the method, the topographic information between the nodes is acquired and analyzed in real time, the attenuation and shielding conditions of signal propagation are evaluated, the residual energy of each node is monitored, and the energy consumption is evaluated, so that the multi-dimensional optimization of the communication path is realized, the network performance and the resource utilization efficiency are remarkably improved, the communication interruption risk and the energy consumption cost are reduced, and the communication efficiency is improved. Wide application prospects and important technical values are realized.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a method, system and device for selecting a multi-node communication path based on terrain perception. Background Art

[0002] With the rapid development of wireless communication technology, mobile wireless communication networks have been widely used in disaster relief, environmental monitoring and other fields, and will also be used in deep space exploration in the future. In these application scenarios, network nodes are often deployed in complex and changeable environments, such as deep space star charts, mountainous areas, forests, etc. The complex terrain environment will have a significant impact on the propagation of wireless signals. Terrain factors such as height difference, slope and obstacles will cause signal attenuation and obstruction, which in turn affects the stability and reliability of the communication link.

[0003] Traditional multi-node communication path selection algorithms, such as the classic Dijkstra algorithm, mainly determine the communication path based on the shortest path or minimum number of hops between nodes. However, these algorithms usually ignore the impact of terrain factors on signal propagation and fail to fully consider the signal attenuation and occlusion between nodes, resulting in weakened signal strength and reduced communication quality. To this end, we propose a multi-node communication path selection method, system and device based on terrain perception. Summary of the invention

[0004] The purpose of the present invention is to provide a multi-node communication path selection method, system and equipment based on terrain perception, which can evaluate the attenuation and obstruction of signal propagation by acquiring and analyzing the terrain information between nodes in real time. At the same time, it can monitor the residual energy of each node, evaluate the energy consumption, and realize multi-dimensional optimization of the communication path.

[0005] According to a first aspect of the present invention, in order to achieve the above-mentioned purpose, the present invention provides the following technical solution: a multi-node communication path selection method based on terrain perception, comprising the following steps:

[0006] Receive terrain information data between nodes, the terrain information data including the distance between nodes, obstacle blocking area and obstacle type, and perform signal attenuation calculation based on the terrain information data;

[0007] Receive the remaining energy of each node, share the remaining energy data with other nodes, and calculate the energy consumed by signal transmission between nodes;

[0008] Based on the Dijkstra algorithm, a comprehensive path cost function including terrain attenuation, energy consumption and node residual energy is constructed, and efficient search for the optimal communication path is achieved according to the comprehensive path cost function;

[0009] According to the calculation result of the comprehensive path cost function, the path with the lowest cost is selected as the current optimal communication path, and each node of the optimal path and its corresponding path cost are recorded;

[0010] According to the real-time changes in the communication environment and node status, the communication path is dynamically adjusted to ensure that the path selection is always in the optimal state.

[0011] Furthermore, the terrain information data is collected and obtained using a laser rangefinder, GPS or terrain radar.

[0012] Furthermore, the signal attenuation calculation is performed according to the terrain information data, as follows:

[0013] (31) Calculate the signal attenuation L between nodes due to terrain FS , the calculation formula is as follows:

[0014] L FS =20lg(Δd)+20lg(f)+32.44

[0015] Where Δd is the distance between nodes, in kilometers; f is the transmission frequency of the signal, in megahertz;

[0016] (32) According to the obstacle type, set the attenuation coefficient γ k and the decay exponent δ k , combined with the occlusion area A of the obstacle and the shortest distance d between the obstacle and the signal propagation path k , calculate the signal attenuation SOR caused by obstacles, the calculation formula is as follows:

[0017]

[0018] Where L obstacle,entire It is the obstacle impact value determined through the actual network or experiment.

[0019] Furthermore, the remaining energy of each node is received, the remaining energy data is shared with other nodes, and the energy consumed by signal transmission between nodes is calculated. The calculation formula is as follows:

[0020]

[0021] Where E is the total communication energy consumption of the node, k is the amount of data sent in bits, and E elec is the energy consumption per bit in the electronic circuit at the sending end, E recv is the energy consumption per bit in the receiving electronic circuit, ∈ amp is the energy consumption coefficient of the amplifier, d jkis the distance between the transmitter j and the receiver k, α is the path loss exponent, and α is set between 2 and 4.

[0022] Furthermore, the comprehensive path cost function integrates the signal attenuation cost L FS , obstacle affects SOR, energy consumption cost E and node remaining energy E residual Four factors are normalized, and the specific formula is as follows:

[0023] Signal attenuation L FS,norm :

[0024]

[0025] Signal Occlusion Rate SOR norm :

[0026]

[0027] Node remaining energy E residual_norm :

[0028]

[0029] Energy consumption norm :

[0030]

[0031] Where, L FS,norm is the normalized signal attenuation value, L FS,a is the signal attenuation value of a certain node, L FS,min is the minimum value of signal attenuation among all communication nodes, L FS,max is the maximum value of signal attenuation among all communication nodes; SOR norm is the normalized signal occlusion rate, SOR a is the signal blocking rate of a certain node, SOR min is the minimum signal shielding rate among all communication nodes, SOR max is the maximum value of the signal shielding rate among all communication nodes; E residual_norm is the normalized node residual energy value, E residual is the node residual energy value of a certain node, E residual_min is the minimum value of the remaining energy among all communication nodes, E residual_max is the maximum value of the remaining energy among all communication nodes; E norm is the normalized node energy consumption value, E is the energy consumption value of a certain node, and E min is the minimum energy consumption among all communication nodes, E max is the maximum value of energy consumption among all communication nodes.

[0032] Furthermore, the path cost function (C ij ) is defined as:

[0033] C ij =α·L FS,norm +β·SOR norm +γ·E norm -δ·E residual_norm

[0034] Among them, α, β, γ, and δ are weight coefficients, and satisfy α+β+γ+δ=1.

[0035] Furthermore, according to the real-time changes in the communication environment and node status, the communication path is dynamically adjusted to ensure that the path selection is always in the optimal state, as follows:

[0036] (71) If a change in the communication environment or node status is detected, the cost of the relevant path is recalculated:

[0037]

[0038] Where L FS,norm ', SOR norm ', E norm '、 is the updated normalized signal attenuation, signal shielding rate, energy consumption and node residual energy;

[0039] (72) Compare the current path cost with the updated path cost. If a better path exists, perform path switching: If C new <C current , then switch to the new path, otherwise do not switch;

[0040] (73) Perform path maintenance and continuously optimize communication paths to ensure that path selection is always in the optimal state and adapt to the dynamically changing communication environment and node status.

[0041] According to a second aspect of the present invention, the present invention provides a multi-node communication path selection system based on terrain perception, which is used to implement the above-mentioned multi-node communication path selection method based on terrain perception, comprising:

[0042] A terrain perception module is used to receive terrain information data between nodes, including the distance between nodes, obstacle blocking area and obstacle type, and perform signal attenuation calculation based on the terrain information data;

[0043] Energy sensing module, used to receive the remaining energy status of each node, share the remaining energy data with other nodes, and calculate the energy consumed by signal transmission between nodes;

[0044] The path evaluation module is used to construct a comprehensive path cost function including terrain attenuation, energy consumption and node residual energy based on the Dijkstra algorithm, and realize efficient search for the optimal communication path according to the comprehensive path cost function;

[0045] A selection module is used to select the path with the lowest cost as the current optimal communication path according to the calculation result of the comprehensive path cost function, and record each node of the optimal path and its corresponding path cost;

[0046] The dynamic optimization module is used to dynamically adjust the communication path according to the real-time changes of the communication environment and node status to ensure that the path selection is always in the optimal state.

[0047] Furthermore, the terrain perception module includes:

[0048] A collection unit is used to obtain terrain information data between nodes through sensors or preset terrain maps. The terrain information data specifically includes the distance Δd between nodes, the obstacle blocking area A and the obstacle type;

[0049] A calculation unit, used to calculate the signal attenuation caused by the terrain and the signal attenuation caused by the influence of obstacles according to the terrain information data;

[0050] The energy sensing module comprises:

[0051] Energy monitoring unit, used to monitor the battery power of each node in real time, record the remaining energy of the node, and share the remaining energy data with other nodes;

[0052] An energy consumption calculation unit, used to calculate the energy consumed by signal transmission between nodes;

[0053] The path evaluation module includes:

[0054] A construction unit, used for constructing a comprehensive path cost function including terrain attenuation, energy consumption and node residual energy based on Dijkstra algorithm;

[0055] A path cost calculation unit, used to calculate an optimal communication path with the minimum cost according to a comprehensive path cost function;

[0056] The dynamic optimization module includes:

[0057] An environment change monitoring unit, used to continuously monitor changes in the communication environment and updates to node status;

[0058] A path re-evaluation unit, used to recalculate the cost of the updated communication path;

[0059] The path switching unit is used to compare the current communication path cost with the updated communication path cost, and execute path switching if a better path exists.

[0060] According to a third aspect of the present invention, the present invention provides a terminal device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, wherein the memory stores a computer program capable of running on the processor, and when the processor loads and executes the computer program, the above-mentioned terrain-awareness-based multi-node communication path selection method is adopted.

[0061] The present invention has at least the following beneficial effects:

[0062] The present invention comprehensively considers terrain factors, node energy status and signal propagation characteristics, dynamically optimizes communication path selection, and effectively solves the problems of signal attenuation, link instability and rapid exhaustion of node energy in wireless communication networks under complex terrain environments. The present invention adopts an improved Dijkstra algorithm to construct a comprehensive path cost function, integrating factors such as signal attenuation, energy consumption and node residual energy, to achieve efficient search for the optimal path and adapt to complex and changeable communication environments. At the same time, the present invention can also dynamically adjust the communication path according to real-time changes in the communication environment and node status to ensure that the network always maintains efficient operation. Overall, the method significantly improves network performance and resource utilization efficiency, reduces the risk of communication interruption and energy consumption costs, and has broad application prospects and important technical value.

[0063] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a schematic diagram of the process of the method of the present invention;

[0065] Figure 2 It is a structural schematic diagram of the method of the present invention;

[0066] Figure 3 A schematic diagram of a communication path selection scenario in the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0068] On the lunar surface, a series of probes, lunar rovers and sensor nodes are deployed to form a wireless communication network for scientific exploration and data transmission. Due to the complex and changeable lunar terrain, including craters, ridges and rock arrays, and the absence of an atmosphere, the signal propagation characteristics are significantly different from those of the Earth's environment. Traditional communication path selection methods are difficult to meet the needs of stable and efficient communication on the lunar surface. The technical solution of the present invention can optimize the communication path and improve the stability and energy efficiency of the network.

[0069] Embodiment 1:

[0070] See also Figure 1-Figure 3 The present invention provides a technical solution: a multi-node communication path selection method based on terrain perception, comprising the following steps:

[0071] S1. Receive terrain information data between nodes, including the distance between nodes, obstacle blocking area and obstacle type, and calculate signal attenuation based on the terrain information data;

[0072] (S11) terrain information acquisition: terrain information data is collected using a laser rangefinder, GPS or terrain radar;

[0073] (S12) Signal attenuation calculation:

[0074] (S12.1) Calculate the signal attenuation L between nodes due to terrain FS , the calculation formula is as follows:

[0075] L FS =20lg(Δd)+20lg(f)+32.44

[0076] Where Δd is the distance between nodes, in kilometers (Km), and f is the transmission frequency of the signal, in megahertz (MHz);

[0077] (S12.2) According to the obstacle type, set the attenuation coefficient γ k (dB / m 2 ) and the decay exponent δ k (1 / m), and combined with the occlusion area of ​​the obstacle (A(m 2 )) and the shortest distance between the obstacle and the signal propagation path (d k (m)), the signal attenuation caused by obstacles can be calculated according to the following formula:

[0078]

[0079] Where L obstacle,entire It is the obstacle impact value determined through actual network or experiment;

[0080] S2. Receive the remaining energy of each node, share the remaining energy data with other nodes, and calculate the energy consumed by signal transmission between nodes, as follows:

[0081] (S21) Residual energy monitoring: real-time recording of the residual energy of the node and sharing of residual energy data with other nodes (E residual );

[0082] (S22) Energy consumption calculation:

[0083] The energy consumption required for communication between computing nodes (E c ), the formula is:

[0084]

[0085] Where E is the total communication energy consumption of the node, k is the amount of data sent (number of bits), and E elec is the energy consumption per bit in the electronic circuit at the sending end, E recv is the energy consumption per bit in the receiving electronic circuit, ∈ amp is the energy consumption coefficient of the amplifier, d jk is the distance between the transmitter j and the receiver k

[0086] distance, α is the path loss exponent (usually α is between 2 and 4, depending on the specific environment);

[0087] S3. Based on the Dijkstra algorithm, a comprehensive path cost function including terrain attenuation, energy consumption and node residual energy is constructed, and efficient search for the optimal communication path is achieved according to the comprehensive path cost function, as follows:

[0088] Path cost function (C ij ) is defined as:

[0089] C ij =α·L FS,norm +β·SOR norm +γ·E norm -δ·E residual_norm

[0090] In the formula, α, β, γ, and δ are weight coefficients, and they satisfy α+β+γ+δ=1;

[0091] Among them, in order to comprehensively consider the multi-dimensional characteristics of the communication path, the path cost function integrates the following four main factors: signal attenuation cost (L FS ), obstacle impact (SOR), energy consumption cost (E) and node residual energy (E residual ), in order to unify the dimensions, the above four factors are normalized, and the formula is as follows:

[0092] Signal attenuation L FS,norm :

[0093]

[0094] Signal Occlusion Rate SOR norm :

[0095]

[0096] Node remaining energy E residual_norm :

[0097]

[0098] Energy consumption norm :

[0099]

[0100] Where, L FS,norm is the normalized signal attenuation value, L FS,a is the signal attenuation value of a certain node, L FS,min is the minimum value of signal attenuation among all communication nodes, L FS,max is the maximum value of signal attenuation among all communication nodes; SOR norm is the normalized signal occlusion rate, SOR a is the signal blocking rate of a certain node, SOR min is the minimum signal shielding rate among all communication nodes, SOR max is the maximum value of the signal shielding rate among all communication nodes; E residual_norm is the normalized node residual energy value, E residual is the node residual energy value of a certain node, E residual_min is the minimum value of the remaining energy among all communication nodes, E residual_max is the maximum value of the remaining energy among all communication nodes; E norm is the normalized node energy consumption value, E is the energy consumption value of a certain node, and E min is the minimum energy consumption among all communication nodes, E max is the maximum value of energy consumption among all communication nodes;

[0101] S4. According to the calculation result of the comprehensive path cost function, the path with the lowest cost is selected as the current optimal communication path, and each node of the optimal path and its corresponding path cost are recorded;

[0102] S5. Dynamically adjust the communication path according to the real-time changes in the communication environment and node status to ensure that the path selection is always in the optimal state, as follows:

[0103] (S51) The dynamic optimization module continuously monitors changes in the communication environment (such as terrain changes, node movement) and updates to node states (such as energy changes), and recalculates the cost of the relevant path:

[0104]

[0105] Where L FS,norm ', SOR norm ', E norm '、 is the updated signal attenuation, signal shielding rate, energy consumption and node remaining energy;

[0106] (S52) Compare the current path cost with the updated path cost. If a better path exists, perform path switching: If C new <C current , then switch to the new path, otherwise do not switch;

[0107] (S53) Perform path maintenance and continuously optimize the communication path to ensure that the path selection is always in the optimal state and adapt to the dynamically changing communication environment and node status.

[0108] Next, the present invention is further described in conjunction with specific embodiments:

[0109] 1. System initialization

[0110] Node deployment: Multiple communication nodes are deployed in selected areas on the lunar surface, including fixed landers, mobile lunar rovers and distributed sensors. Each node is equipped with a high-precision positioning system (such as laser rangefinder, starlight navigation) and terrain perception sensors, as well as energy monitoring modules.

[0111] Initial communication: Establish initial communication links between nodes and begin to exchange basic terrain and energy status;

[0112] 2. Terrain information acquisition and analysis

[0113] Terrain data acquisition: Nodes use laser rangefinders, radars, and cameras to obtain surrounding terrain data, including the distance Δd between nodes, the obstruction area of ​​craters and rock arrays, and the types of obstacles;

[0114] Terrain impact model generation: Based on the collected data, a lunar terrain impact model is built, taking into account the unique terrain features of the lunar surface;

[0115] Free space path loss L FS :

[0116] L FS =20lg(Δd)+20lg(f)+32.44

[0117] Where Δd is the distance between nodes, in kilometers (Km), and f is the transmission frequency of the signal, in megahertz (MHz);

[0118] Obstacle attenuation L obstacle :

[0119] According to the type of obstacles on the lunar surface (such as rocks, lunar soil accumulation), set the corresponding attenuation coefficient γ k (dB / m 2 ) and the decay exponent δ k (1 / m);

[0120] Calculate the signal attenuation caused by obstacles:

[0121]

[0122] Signal Occlusion Rate (SOR):

[0123]

[0124] Where L obstacle,entire It is the maximum value of the obstacle impact determined through actual network or experiment;

[0125] 3. Energy status monitoring and evaluation

[0126] Residual energy monitoring: The node monitors its own residual energy E in real time. residual , and share this information with other nodes, predict the endurance of the node based on the remaining energy, and evaluate the energy consumption required for communication between nodes;

[0127] Energy consumption calculation:

[0128]

[0129] E: total communication energy consumption of the node;

[0130] k: the amount of data sent (number of bits);

[0131] E elec : The energy consumption per bit in the electronic circuit at the sending end;

[0132] E recv : The energy consumption per bit in the receiving electronic circuit;

[0133] ∈ amp is the energy consumption coefficient of the amplifier;

[0134] d jk is the distance between the transmitter j and the receiver k;

[0135] α is the path loss exponent (usually α is between 2 and 4, depending on the specific environment);

[0136] 4. Path cost calculation and evaluation

[0137] Normalization:

[0138] Signal attenuation normalization L FS,norm :

[0139]

[0140] Signal Occlusion Rate Normalized SOR norm :

[0141]

[0142] Energy consumption normalized E norm :

[0143]

[0144] Node residual energy normalization E residual_norm :

[0145]

[0146] Path cost function calculation:

[0147] C ij =α·L FS,norm +β·SOR norm +γ·E norm -δ·E residual_norm

[0148] Among them, α, β, γ, δ are weight coefficients, and they satisfy α+β+γ+δ=1;

[0149] 5. Optimal path selection

[0150] Path search: Use the improved Dijkstra algorithm based on the calculated path cost C ij , search for the path with the lowest cost from the source node to the target node, such as Figure 2 ABE path in;

[0151] Path record: record the node sequence and corresponding path cost of the optimal path for reference by the dynamic optimization module;

[0152] 6. Dynamic Path Optimization

[0153] Environmental change detection: Continuously monitor lunar terrain changes (such as terrain changes caused by micrometeorite impacts), node position changes (moving lunar rovers), and node energy status updates;

[0154] Path re-evaluation:

[0155]

[0156] L FS,norm ', SOR norm ', E norm '、 is the updated normalized parameter;

[0157] Path switching:

[0158] Compare the current path cost with the updated path cost. If C new <C current , then switch to the new path.

[0159] In summary, the present invention comprehensively considers terrain factors, node energy status and signal propagation characteristics, dynamically optimizes communication path selection, and effectively solves the problems of signal attenuation, link instability and rapid exhaustion of node energy in wireless communication networks under complex terrain environments; the present invention adopts an improved Dijkstra algorithm to construct a comprehensive path cost function, integrating factors such as signal attenuation, energy consumption and node residual energy, to achieve efficient search for the optimal path and adapt to complex and changeable communication environments; at the same time, the dynamic optimization module can dynamically adjust the communication path according to the real-time changes of the communication environment and node status to ensure that the network always maintains efficient operation. Overall, the present invention can significantly improve the stability of the communication link under extreme conditions such as complex terrain and harsh communication environment, extend the overall survival time of the network, and reduce the risk of communication interruption and energy consumption cost. It is suitable for mobile wireless communication networks under extreme environmental conditions, and meets the communication priority and energy management strategies under different application requirements. It has broad application prospects and important practical significance.

[0160] Embodiment 2:

[0161] The present invention provides a multi-node communication path selection system based on terrain perception, which is used to implement the multi-node communication path selection method based on terrain perception described in the first embodiment, including:

[0162] A terrain perception module is used to receive terrain information data between nodes, including the distance between nodes, obstacle blocking area and obstacle type, and perform signal attenuation calculation based on the terrain information data;

[0163] Energy sensing module, used to receive the remaining energy status of each node, share the remaining energy data with other nodes, and calculate the energy consumed by signal transmission between nodes;

[0164] The path evaluation module is used to construct a comprehensive path cost function including terrain attenuation, energy consumption and node residual energy based on the Dijkstra algorithm, and realize efficient search for the optimal communication path according to the comprehensive path cost function;

[0165] A selection module is used to select the path with the lowest cost as the current optimal communication path according to the calculation result of the comprehensive path cost function, and record each node of the optimal path and its corresponding path cost;

[0166] The dynamic optimization module is used to dynamically adjust the communication path according to the real-time changes of the communication environment and node status to ensure that the path selection is always in the optimal state.

[0167] Furthermore, the terrain perception module includes:

[0168] The acquisition unit is used to obtain terrain information data between nodes through sensors or preset terrain maps. The terrain information data specifically includes the distance between nodes, obstacle blocking area and obstacle type;

[0169] A calculation unit, used to calculate the signal attenuation caused by the terrain and the signal attenuation caused by the influence of obstacles according to the terrain information data;

[0170] The energy sensing module comprises:

[0171] Energy monitoring unit, used to monitor the battery power of each node in real time, record the remaining energy of the node, and share the remaining energy data with other nodes;

[0172] An energy consumption calculation unit, used to calculate the energy consumed by signal transmission between nodes;

[0173] The path evaluation module includes:

[0174] A construction unit, used for constructing a comprehensive path cost function including terrain attenuation, energy consumption and node residual energy based on Dijkstra algorithm;

[0175] A path cost calculation unit, used to calculate an optimal communication path with the minimum cost according to a comprehensive path cost function;

[0176] The dynamic optimization module includes:

[0177] An environment change monitoring unit, used to continuously monitor changes in the communication environment and updates to node status;

[0178] A path re-evaluation unit, used to recalculate the cost of the updated communication path;

[0179] The path switching unit is used to compare the current communication path cost with the updated communication path cost, and execute path switching if a better path exists.

[0180] Specifically, the above-mentioned terrain perception module, energy perception module, path evaluation module, selection module and dynamic optimization module can be embedded in a computer processing system. The computer calls the above-mentioned modules to complete the task of selecting the communication path according to the above-mentioned multi-node communication path selection method based on terrain perception; the above-mentioned terrain perception module, energy perception module, path evaluation module, selection module and dynamic optimization module can perform operations according to the specific steps given in the multi-node communication path selection method based on terrain perception.

[0181] It should be noted that it should be understood that the division of the various modules of the above system is only the division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated, and these modules can all be implemented in the form of software calling through processing elements; they can also be all implemented in the form of hardware; some modules can also be implemented in the form of software calling through processing elements, and some modules can be implemented in the form of hardware. For example, the terrain perception module can be a separate processing element, or it can be integrated in a chip of the above device. In addition, it can also be stored in the memory of the above device in the form of program code, and called and executed by a processing element of the above device. The implementation of other modules is similar. In addition, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element described here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each module can be completed by the hardware integrated logic circuit in the processor element or the instructions in the form of software.

[0182] For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuits (ASIC), or one or more digital singnal processors (DSP), or one or more field programmable gate arrays (FPGA). For another example, when a module is implemented in the form of a processing element scheduling program code, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processors that can call program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0183] Embodiment three:

[0184] The present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The memory stores a computer program capable of running on the processor, and when the processor loads and executes the computer program, the above-mentioned terrain-aware based multi-node communication path selection method is adopted.

[0185] It should be noted that the terminal device can be a computer device such as a desktop computer, a laptop computer or a cloud server, and the terminal device includes but is not limited to a processor and a memory. For example, the terminal device can also include input and output devices, network access devices and buses.

[0186] Furthermore, the processor may adopt a central processing unit (CPU). Of course, according to actual usage, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. may also be adopted. The general-purpose processor may adopt a microprocessor or any conventional processor, etc., and the present application does not impose any restrictions on this.

[0187] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0188] For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. When an element is referred to as being "assembled on", "installed on", "fixed on" or "set on" another element, it can be directly on the other element or there can also be a centered element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be a centered element at the same time. The terms "vertical", "horizontal", "up", "down", "left", "right" and similar expressions used herein are only for illustrative purposes and are not intended to be the only implementation method.

[0189] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

[0190] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

Claims

1. A multi-node communication path selection method based on terrain perception, characterized in that: The following steps are involved: Receive terrain information data between nodes, the terrain information data including the distance between nodes, obstacle blocking area and obstacle type, and perform signal attenuation calculation based on the terrain information data; Receive the remaining energy of each node, share the remaining energy data with other nodes, and calculate the energy consumed by signal transmission between nodes; Based on the Dijkstra algorithm, a comprehensive path cost function including terrain attenuation, energy consumption and node residual energy is constructed, and efficient search for the optimal communication path is achieved according to the comprehensive path cost function; According to the calculation result of the comprehensive path cost function, the path with the lowest cost is selected as the current optimal communication path, and each node of the optimal path and its corresponding path cost are recorded; According to the real-time changes in the communication environment and node status, the communication path is dynamically adjusted to ensure that the path selection is always in the optimal state.

2. The method for selecting a multi-node communication path based on terrain perception according to claim 1, characterized in that: The terrain information data is collected by using a laser rangefinder, GPS or terrain radar.

3. The method for selecting a multi-node communication path based on terrain perception according to claim 2, characterized in that: The signal attenuation calculation is performed according to the terrain information data, specifically as follows: (31) Calculate the signal attenuation L between nodes due to terrain FS , the calculation formula is as follows: L FS =20lg(Δd)+20lg(f)+32.44 Where Δd is the distance between nodes, in kilometers; f is the transmission frequency of the signal, in megahertz; (32) According to the obstacle type, set the attenuation coefficient γ k and the decay exponent δ k , combined with the occlusion area A of the obstacle and the shortest distance d between the obstacle and the signal propagation path k , calculate the signal attenuation SOR caused by obstacles, the calculation formula is as follows: Where L obstacle,entire It is the obstacle impact value determined through the actual network or experiment.

4. The method for selecting a multi-node communication path based on terrain perception according to claim 3, characterized in that: Receive the remaining energy of each node, share the remaining energy data with other nodes, and calculate the energy consumed by signal transmission between nodes. The calculation formula is as follows: Where E is the total communication energy consumption of the node, k is the amount of data sent in bits, and E elec is the energy consumption per bit in the electronic circuit at the sending end, E recv is the energy consumption per bit in the receiving electronic circuit, ∈ amp is the energy consumption coefficient of the amplifier, d jk is the distance between the transmitter j and the receiver k, α is the path loss exponent, and α is set between 2 and 4.

5. The method for selecting a multi-node communication path based on terrain perception according to claim 4, characterized in that: The comprehensive path cost function integrates the signal attenuation cost L FS , obstacle affects SOR, energy consumption cost E and node remaining energy E residual Four factors are normalized, and the specific formula is as follows: Signal attenuation L FS,norm : Signal Occlusion Rate SOR norm : Node remaining energy E residual_norm : Energy consumption norm : Where, L FS,norm is the normalized signal attenuation value, L FS,a is the signal attenuation value of a certain node, L FS,min is the minimum value of signal attenuation among all communication nodes, L FS,max is the maximum value of signal attenuation among all communication nodes; SOR norm is the normalized signal occlusion rate, SOR a is the signal blocking rate of a certain node, SOR min is the minimum signal shielding rate among all communication nodes, SOR max is the maximum value of the signal shielding rate among all communication nodes; E residual_norm is the normalized node residual energy value, E residual is the node residual energy value of a certain node, E residual_min is the minimum value of the remaining energy among all communication nodes, E residual_max is the maximum value of the remaining energy among all communication nodes; E norm is the normalized node energy consumption value, E is the energy consumption value of a certain node, and E min is the minimum energy consumption among all communication nodes, E max is the maximum value of energy consumption among all communication nodes.

6. The method for selecting a multi-node communication path based on terrain perception according to claim 5, characterized in that: The path cost function (C ij ) is defined as: C ij =α·L FS,norm +β·SOR norm +γ·E norm -d·E residual_norm Among them, α, β, γ, and δ are weight coefficients, and satisfy α+β+γ+δ=1.

7. The method for selecting a multi-node communication path based on terrain perception according to claim 6, characterized in that: According to the real-time changes in the communication environment and node status, the communication path is dynamically adjusted to ensure that the path selection is always in the optimal state, as follows: (71) If a change in the communication environment or node status is detected, the cost of the relevant path is recalculated: C updated =α·L FS,norm '+β·SOR norm '+γ·E norm '-d·E residualnorm ' Where L FS,norm ', SOR norm ', E norm ', E residualnorm ' is the updated normalized signal attenuation, signal shielding rate, energy consumption and node residual energy; (72) Compare the current path cost with the updated path cost. If a better path exists, perform path switching: If C new <C current , then switch to the new path, otherwise do not switch; (73) Perform path maintenance and continuously optimize communication paths to ensure that path selection is always in the optimal state and adapt to the dynamically changing communication environment and node status.

8. A multi-node communication path selection system based on terrain perception, used to implement the multi-node communication path selection method based on terrain perception according to any one of claims 1 to 8, characterized in that: include: A terrain perception module is used to receive terrain information data between nodes, including the distance between nodes, obstacle blocking area and obstacle type, and perform signal attenuation calculation based on the terrain information data; Energy sensing module, used to receive the remaining energy status of each node, share the remaining energy data with other nodes, and calculate the energy consumed by signal transmission between nodes; The path evaluation module is used to construct a comprehensive path cost function including terrain attenuation, energy consumption and node residual energy based on the Dijkstra algorithm, and realize efficient search for the optimal communication path according to the comprehensive path cost function; A selection module is used to select the path with the lowest cost as the current optimal communication path according to the calculation result of the comprehensive path cost function, and record each node of the optimal path and its corresponding path cost; The dynamic optimization module is used to dynamically adjust the communication path according to the real-time changes of the communication environment and node status to ensure that the path selection is always in the optimal state.

9. The multi-node communication path selection system based on terrain perception according to claim 8, characterized in that: The terrain perception module includes: A collection unit is used to obtain terrain information data between nodes through sensors or preset terrain maps. The terrain information data specifically includes the distance Δd between nodes, the obstacle blocking area A and the obstacle type; A calculation unit, used to calculate the signal attenuation caused by the terrain and the signal attenuation caused by the influence of obstacles according to the terrain information data; The energy sensing module comprises: Energy monitoring unit, used to monitor the battery power of each node in real time, record the remaining energy of the node, and share the remaining energy data with other nodes; An energy consumption calculation unit, used to calculate the energy consumed by signal transmission between nodes; The path evaluation module includes: A construction unit, used for constructing a comprehensive path cost function including terrain attenuation, energy consumption and node residual energy based on Dijkstra algorithm; A path cost calculation unit, used to calculate an optimal communication path with the minimum cost according to a comprehensive path cost function; The dynamic optimization module includes: An environment change monitoring unit, used to continuously monitor changes in the communication environment and updates to node status; A path re-evaluation unit, used to recalculate the cost of the updated communication path; The path switching unit is used to compare the current communication path cost with the updated communication path cost, and execute path switching if a better path exists.

10. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: The memory stores a computer program that can be run on the processor. When the processor loads and executes the computer program, the terrain-aware multi-node communication path selection method according to any one of claims 1 to 7 is adopted.

Images