A method for calculating dynamic information entropy of a space terahertz communication network

Abstract

The application discloses a kind of space terahertz communication network dynamic information entropy calculation methods, this method includes defining network capacity entropy and link information entropy, and give specific calculation formula.Therein, network capacity entropy is used to quantify the capacity fluctuation size of network in different states, and link information entropy is used to quantify the uncertainty of transmission quality of single link at different time.The method is suitable for dynamic environment in space terahertz information network, can accurately evaluate the uncertainty of network, for supporting system state perception and resource scheduling.By the application of the method, the stability and resource scheduling of network can be improved, and lay a foundation for the further development of space terahertz information network.

Description

Technical Field

[0001] This invention relates to the field of satellite communication network technology, and in particular to a method for calculating dynamic information entropy in space terahertz communication networks. Background Technology

[0002] In space-based terahertz information networks, the stability and capacity face significant challenges due to the high-speed movement of nodes and complex environmental interference. Traditional network performance evaluation methods often struggle to accurately quantify this uncertainty, thus limiting the design of effective anti-interference strategies. To address this issue, a method is needed to accurately assess the capacity fluctuations and link transmission quality uncertainties of the network under different states. The introduction of the concepts of network capacity entropy and link information entropy provides a new approach to quantifying this uncertainty. Network capacity entropy reflects the magnitude of capacity fluctuations under different states, while link information entropy quantifies the uncertainty of transmission quality of a single link at different times. However, an effective dynamic information entropy calculation method for space-based terahertz information networks is currently lacking.

[0003] Chinese invention CN116647852A proposes a robust transmission method for a smart metasurface-assisted terahertz communication system, but does not consider THz characteristics. Summary of the Invention

[0004] 1. A method for calculating dynamic information entropy in a spatial terahertz communication network, comprising: S1, the space terahertz communication network consists of geostationary orbit satellites (GEO), low orbit satellite constellations (LEO), and user equipment (UE). It uses terahertz (THz) band links to achieve high-speed data transmission between LEO and UE, and between LEO and GEO. The terahertz links are characterized by high bandwidth, high path loss, and strong directivity. The channel state changes dynamically with distance, attitude, and absorption environment. S2, based on the signal-to-noise ratio and bandwidth of the terahertz link, calculate the total capacity of the network under different states, and define the network capacity entropy. The dynamic nature of system capacity is characterized by the following formula: ,in For network capacity at time 1, The network capacity at time 2; the formula for calculating network capacity is: ,in Let E be the capacity of each transmission link in the network, e be the e-th edge of the transmission link, and e belong to the edge set E. The network capacity entropy is... The mathematical form employs the concept of relative entropy to quantify the magnitude of capacity fluctuations in a network under different states. The higher the value, the weaker the network's anti-interference capability; S3, according to Shannon's theorem The transmission link capacity can be calculated, where B is the link bandwidth and SNR is the signal-to-noise ratio. S4 defines the link information entropy of a spatial terahertz information network. Its calculation formula is Where qi represents the transmission quality of the link at different times, and P(qi) is the probability corresponding to qi; qi is a function of link capacity C, response delay D, and transmission rate v, i.e. ; S5, Link Information Entropy Using the Shannon entropy definition to reflect the dynamic randomness of the system, the link information entropy is calculated based on the transmission quality qi at different times and its corresponding probability P(qi). It is used to quantify the uncertainty of transmission quality of a single link at different times; Optionally, the terahertz signal-to-noise ratio model considers the atmospheric absorption window effect. When the operating frequency band is in the high absorption region (e.g., 0.56THz to 0.64THz), the absorption loss term... Increased capacity entropy leads to increased network capacity. Decrease.

[0005] Optionally, the beam alignment probability The angle error is dynamically estimated by the antenna array angle error control module and updated in real time as the satellite's attitude and orbit change.

[0006] Optionally, when the link information entropy When the growth rate exceeds the set threshold, the system triggers a link monitoring and beam redirection mechanism to identify channel mutations and connection interruption risks.

[0007] Optionally, this method can be embedded in the network management module of a space terahertz communication system to realize real-time calculation and visualization of network capacity entropy and link information entropy, thereby supporting system status awareness and resource scheduling.

[0008] The present invention has the following advantages: 1. By introducing two key concepts, network capacity entropy and link information entropy, this invention can accurately quantify the capacity fluctuations and link transmission quality uncertainties of the network under different states, providing more accurate data support for network performance evaluation.

[0009] 2. This invention can provide a basis for designing more effective anti-interference strategies, thereby improving the stability and capacity of space terahertz information networks and ensuring reliable network operation in complex environments. .Attached Figure Description Figure 1 This is a schematic diagram of the dynamic information entropy calculation method for spatial terahertz communication networks in this invention; Detailed Implementation

[0011] The present invention will now be described in detail with reference to the accompanying drawings.

[0012] As shown in the figure, this invention discloses a method for calculating dynamic information entropy in a space terahertz communication network, including: S1, the space terahertz communication network consists of geostationary orbit satellites (GEO), low orbit satellite constellations (LEO), and user equipment (UE). It uses terahertz (THz) band links to achieve high-speed data transmission between LEO and UE, and between LEO and GEO. The terahertz links are characterized by high bandwidth, high path loss, and strong directivity. The channel state changes dynamically with distance, attitude, and absorption environment. S2, based on the signal-to-noise ratio and bandwidth of the terahertz link, calculate the total capacity of the network under different states, and define the network capacity entropy. The dynamic nature of system capacity is characterized by the following formula: ,in For network capacity at time 1, The network capacity at time 2; the formula for calculating network capacity is: ,in The network capacity entropy represents the capacity of each transmission link in the network. The mathematical form employs the concept of relative entropy to quantify the magnitude of capacity fluctuations in a network under different states. The higher the value, the weaker the network's anti-interference capability; S3, according to Shannon's theorem The transmission link capacity can be calculated, where B is the link bandwidth and SNR is the signal-to-noise ratio. S4 defines the link information entropy of a spatial terahertz information network. Its calculation formula is Where qi represents the transmission quality of the link at different times, and P(qi) is the probability corresponding to qi; qi is a function of link capacity C, response delay D, and transmission rate v, i.e. ; S5, Link Information Entropy Using the Shannon entropy definition to reflect the dynamic randomness of the system, the link information entropy is calculated based on the transmission quality qi at different times and its corresponding probability P(qi). It is used to quantify the uncertainty of transmission quality of a single link at different times; Optionally, the terahertz signal-to-noise ratio model considers the atmospheric absorption window effect. When the operating frequency band is in the high absorption region (e.g., 0.56THz to 0.64THz), the absorption loss term... Increased capacity entropy leads to increased network capacity. Decrease.

[0013] Optionally, the beam alignment probability The angle error is dynamically estimated by the antenna array angle error control module and updated in real time as the satellite's attitude and orbit change.

[0014] Optionally, when the link information entropy When the growth rate exceeds the set threshold, the system triggers a link monitoring and beam redirection mechanism to identify channel mutations and connection interruption risks.

[0015] Optionally, this method is embedded in the network management module of a space terahertz communication system to realize real-time calculation and visualization of network capacity entropy and link information entropy, thereby supporting system status awareness and resource scheduling.

[0016] The present invention has been described in detail above with reference to the accompanying drawings. However, those skilled in the art should understand that the specification is for interpreting the claims, and the scope of protection of the present invention is determined by the claims. Any modifications, equivalent substitutions, and improvements made based on the present invention should be within the scope of protection claimed.

Claims

1. A method for calculating dynamic information entropy in a spatial terahertz communication network, characterized in that, The space-based terahertz communication network consists of geostationary orbit (GEO) satellites, low Earth orbit (LEO) satellite constellations, and user terminals (UEs). It utilizes terahertz frequency band links to achieve high-speed data transmission between LEO and UE, and between LEO and GEO. These terahertz links are characterized by high bandwidth, high path loss, and strong directivity, with channel states dynamically changing depending on distance, attitude, and absorption environment. The method includes: S1. Based on the signal-to-noise ratio and bandwidth of the terahertz link, calculate the total capacity of the network under different states, and define the network capacity entropy. The dynamic nature of system capacity is characterized by the following formula: ,in For network capacity at time 1, The network capacity at time 2; the formula for calculating network capacity is: ,in Let E be the capacity of each transmission link in the network, and let e be the e-th edge of the transmission link, where e belongs to the edge set E; network capacity entropy. The mathematical form employs the concept of relative entropy to quantify the magnitude of capacity fluctuations in a network under different states. The higher the value, the weaker the network's anti-interference capability; S2, according to Shannon's theorem Calculate the transmission link capacity, where B is the link bandwidth and SNR is the signal-to-noise ratio. S3 defines the link information entropy of a spatial terahertz information network. Its calculation formula is Where qi represents the transmission quality of the link at different times, and P(qi) is the probability corresponding to qi; qi is a function of link capacity C, response delay D, and transmission rate v, i.e. ; S4, Link Information Entropy Using the Shannon entropy definition to reflect the dynamic randomness of the system, the link information entropy is calculated based on the transmission quality qi at different times and its corresponding probability P(qi). It is used to quantify the uncertainty of transmission quality of a single link at different times.

2. The method according to claim 1, characterized in that: The signal-to-noise ratio model for terahertz links considers the atmospheric absorption window effect. When the operating frequency band is in the high absorption region, the absorption loss term... Increased capacity entropy leads to increased network capacity. Decrease.

3. The method according to claim 1, characterized in that: Beam alignment probability The angle error is dynamically estimated by the antenna array angle error control module and updated in real time as the satellite's attitude and orbit change.

4. The method according to claim 1, characterized in that: When link information entropy When the growth rate exceeds the set threshold, the system triggers a link monitoring and beam redirection mechanism to identify channel mutations and connection interruption risks.

5. The method according to claim 1, characterized in that: This method is embedded in the network management module of a space terahertz communication system to realize real-time calculation and visualization of network capacity entropy and link information entropy, which is used to support system status awareness and resource scheduling.

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