A method and system for sensing dynamic time-varying channel spectrum of NGSO constellation system

Abstract

The present invention belongs to the field of spectrum sensing technology, and more particularly relates to a method and system for spectrum sensing of dynamic time-varying channels in an NGSO constellation system. The method comprises: constructing a collaborative spectrum sensing scenario for the NGSO constellation system; establishing a signal model for spectrum sensing of the NGSO constellation system based on a dynamic time-varying sensing channel link; constructing an objective function and constraints for the corresponding sensing link; and designing a collaborative spectrum sensing optimization fusion decision strategy based on the objective function and constraints to obtain an optimal solution for the decision threshold and number of sensing nodes. The method of the present invention achieves good and accurate perception in the dynamic time-varying sensing channel scenario, further improving the efficient utilization of spatial spectrum resources.

Description

Technical Field

[0001] The present invention belongs to the technical field of spectrum sensing, and in particular relates to a method and system for sensing the spectrum of a dynamic time-varying channel of an NGSO constellation system. Background Art

[0002] The large-scale deployment of non-geostationary satellite orbit (NGSO) constellations in recent years, such as those of SpaceX, OneWeb, Telesat, and Leosat, has led to the satellite communications industry facing a complex and numerous satellite orbital configuration, coupled with the use of multiple systems and frequency bands. These large-scale constellations have also led to a sharp increase in demand for broadband spectrum, necessitating the development of effective spectrum compatibility sharing technologies that enable different systems and services to share the same frequency band. Spectrum sensing technology is one approach to addressing spectrum sharing challenges faced by diverse satellite systems.

[0003] Spectrum sensing technology detects and uses idle spectrum within the authorized or primary node (PN) authorized frequency band through sensing or secondary node (SN), and quickly gives up the channel when the authorized node starts to use the frequency band to avoid co-channel interference to the authorized node.

[0004] A lot of research has been carried out on spectrum sensing technology for ground systems at home and abroad. For example, WU SW, ZHU JK, QIU L, et al. proposed a collaborative spectrum sensing technology based on optimal weighting of signal-to-noise ratio; Liu Yulei, Liang Jun, Xiao Nan, et al. proposed a spectrum sensing method based on channel historical state information to break through the performance limit of traditional energy detection; Zhang Hongwei, Da Xinyu, Hu Hang, et al. proposed a high-spectral-efficiency joint optimization algorithm by setting optimization parameters such as the number of sensing nodes, time, and decision threshold; Yang Ming, Li Xiang, Yang Hao, et al. established an optimization model for maximizing energy efficiency based on periodic collaborative spectrum sensing. In the field of satellite communication systems, Xiao Nan, Liang Jun, Zhang Hengyang, and others analyzed the effectiveness and availability of idle spectrum and determined the optimal available spectrum. Wang C, Bian D M, Shi S C, et al. studied a new cognitive satellite network with geostationary and low-Earth orbit systems. Sharma S K, Chatzinotas S, and Ottersten B. utilized the polarization state of the received signal in satellite communications and proposed an optimal polarization joint technique for spectrum sensing to improve efficiency. Zhang C, Jiang C X, and Jin J, et al. proposed a spectrum sensing strategy based on maximum a posteriori probability and derived closed-form expressions for the decision region in the coexistence scenario of downlink and uplink geostationary and non-geostationary satellites. Currently, research on spectrum sensing technology in satellite system spectrum sharing and compatibility scenarios mainly focuses on static fixed link scenarios, mainly involving geostationary satellite orbit (GSO) satellites. There is also little research on the collaborative sensing of spectrum occupancy by multi-node satellites in constellation systems. Summary of the Invention

[0005] The purpose of the present invention is to overcome the defects of the prior art and propose a method and system for dynamic time-varying channel spectrum sensing of an NGSO constellation system.

[0006] To achieve the above technical objectives, the present invention proposes a method for dynamic time-varying channel spectrum sensing in an NGSO constellation system, comprising:

[0007] Step 1) Constructing a collaborative spectrum sensing scenario for the NGSO constellation system;

[0008] Step 2) Based on the dynamic time-varying sensing channel link, a signal model for spectrum sensing of the NGSO constellation system is established;

[0009] Step 3) Construct the objective function and constraints of the corresponding sensing link;

[0010] Step 4) Based on the objective function and constraints, a collaborative spectrum sensing optimization fusion decision strategy is designed to obtain the optimal solution for the decision threshold and number of sensing nodes.

[0011] Preferably, the step 1) includes: constructing a satellite and ground station collaborative downlink perception scenario or a satellite collaborative uplink perception scenario based on the spatial orbital position relationship between the perception and authorization satellites, wherein:

[0012] The satellite and ground station collaborative downlink sensing scenario is: using the satellites of the NGSO constellation system as sensing nodes to collaboratively sense the downlink transmission signals of the authorized satellites; or using multiple ground stations as sensing nodes to collaboratively sense the downlink transmission signals from the satellites of the NGSO constellation system;

[0013] The satellite collaborative uplink perception scenario is: using NGSO constellation system satellites as perception nodes to collaboratively perceive the uplink transmission signals of authorized ground stations.

[0014] Preferably, the signal model for spectrum sensing of the NGSO constellation system established in step 2) is:

[0015] The kth time slot signal x received by the i-th sensing node from the authorization node PN i,k The model is:

[0016]

[0017] Where,

[0018] C i,k =p pn G pnt (θ pnt,i,k )G snr (θ snr,i,k ) / l i,k

[0019] K i =2U i ,k=1,2,...,K i

[0020] Where, is the idle state of the authorized node spectrum, is the spectrum occupancy status of the authorized node, K i is the number of samples in the i-th sensing cycle, U i is the delay-bandwidth product, φ i is the channel phase; C i,k is the power of the signal received by the i-th sensing node, is the sampling signal of the kth time slot transmitted by the authorized node, which obeys the circularly symmetric complex Gaussian distribution with zero mean, n i,kis the k-th time slot additive Gaussian white noise sampling signal received by the i-th sensing node, that is,

[0021] Preferably, the step 3) comprises:

[0022] The global error detection probability P g,e As the objective function to be optimized:

[0023]

[0024] Where M means that the perception system includes M nodes, L means that at least L perception nodes among the M nodes determine the existence of the authorized node. and are the probabilities of spectrum idle and occupied states respectively, I is the set of possible decision results of all nodes, with cardinality i, is the false alarm probability of the jth sensing node under the time-varying channel communication link, is the false alarm probability of the qth sensing node under the time-varying channel communication link, is the conditional detection probability of the j-th sensor node, is the conditional detection probability of the qth sensor node,

[0025] The nonlinear constraints are constructed as follows:

[0026]

[0027] Where, is the false alarm probability of the i-th sensing node under the time-varying channel communication link, P f,th is the false alarm probability limit, P sc,th is the spectrum conflict probability limit, P sc,i is the spectrum conflict probability between the i-th sensing node and the authorized node at a certain moment, satisfying the following formula:

[0028]

[0029]

[0030]

[0031] Where, P eff,i and P ava,i are the effective probability and available probability of idle spectrum of the i-th sensing node, respectively, delay,i is the delay difference between the detection of the i-th sensing node and the spectrum utilization, and the idle state duration X before the spectrum state of the authorized node is transferred idle Obeying the exponential distribution with parameter λ, t d,i is the data transmission duration of the i-th sensing node.

[0032] Preferably, the step 4) comprises:

[0033] Construct the Lagrangian function J1(ξ,L):

[0034]

[0035] Where ξ=[ξ1,ξ2,…,ξ M ] T ; T represents transposition, κ m =(κ m,1,..., κ m,M )≥0 and κ n =(κ n,1 ,...,κ n,M )≥0 is the Lagrangian factor of J1(·);

[0036] Let J1(·) be the value of ξ i The partial derivative function value of and L is 0, and the optimal value of the decision threshold of the sensing node ξ is obtained by the Newton iteration method. i * And the optimal value of quantity L * .

[0037] On the other hand, the present invention proposes a dynamic time-varying channel spectrum sensing system for an NGSO constellation system, the system comprising:

[0038] Scenario building module, used to build collaborative spectrum sensing scenarios for NGSO constellation systems;

[0039] A model building module is used to build a signal model for spectrum sensing of the NGSO constellation system based on a dynamic time-varying sensing channel link;

[0040] Function condition establishment module, used to construct the objective function and constraint conditions of the corresponding perception link;

[0041] The decision strategy module is used to design a collaborative spectrum sensing optimization fusion decision strategy based on the objective function and constraints, and obtain the optimal solution for the decision threshold and number of sensing nodes.

[0042] Compared with the prior art, the advantages of the present invention are:

[0043] The method of the present invention has a good correct perception effect in a dynamic time-varying perception channel scenario, and further improves the effective utilization of spatial spectrum resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 shows a downlink cooperative sensing scenario of an NGSO system, where Figure 1(a) shows a scenario where multiple NGSO satellites cooperatively sense an authorized satellite, and Figure 1(b) shows a scenario where multiple ground stations cooperatively sense an NGSO satellite.

[0045] Figure 2 It is a satellite cooperative sensing scenario for the uplink of the NGSO system;

[0046] Figure 3 It is a schematic diagram of spectrum conflicts between M sensing nodes and authorized nodes;

[0047] Figure 4 The signal-to-noise ratio change curve of each ground station when the OneWeb satellite passes by;

[0048] Figure 5(a) shows the characteristic curve of the global conditional detection probability changing with OneWeb's satellite transmission power density;

[0049] Figure 5(b) shows the characteristic curve of the global spectrum conflict probability changing with OneWeb's satellite transmission power density;

[0050] Figure 5(c) shows the characteristic curve of the global correct detection probability changing with OneWeb's satellite transmission power density;

[0051] Figure 6 is the characteristic curve of the global correct detection probability with different sampling numbers versus OneWeb satellite transmit power density;

[0052] Figure 7 It is the signal-to-noise ratio change curve of the NGSO satellite when it passes the authorized satellite;

[0053] Figure 8 is the characteristic curve of the global correct detection probability with different sampling numbers changing with the authorized satellite transmission power density;

[0054] Figure 9 It is the signal-to-noise ratio change curve when the NGSO satellite passes by the ground station;

[0055] Figure 10 is the characteristic curve of the global correct detection probability with different sampling numbers changing with the ground station transmission power density;

[0056] Figure 11 These are comparative analysis curves of the perception effects of different methods in three scenarios. The first row is a comparison of the results of ground station collaborative perception of NGSO satellite downlinks, the second row is a comparison of the results of NGSO constellation system satellite collaborative perception of authorized satellite downlinks, and the third row is a comparison of the results of NGSO constellation system satellite collaborative perception of ground station uplinks. DETAILED DESCRIPTION

[0057] To address spectrum sharing issues between NGSO constellation systems and other satellite systems, this application constructs different uplink and downlink collaborative sensing scenarios based on the connectivity and robustness of the links established by different satellite systems. Multiple ground stations and NGSO system satellites are used as sensing nodes, and the correct detection probability under different sensing modes is quantitatively studied and analyzed. Furthermore, considering the influence of the sensing channel environment, radio wave propagation model, and spectrum conflicts with authorized systems in different scenarios, a mathematical model of dynamic time-varying channel sensing signals is constructed based on the time-varying characteristics of the satellite system's sensing channel. A corresponding collaborative spectrum sensing fusion strategy and solution optimization method are proposed. Parameters such as the decision threshold and number of sensing nodes are optimized, and an objective function and constraints for the global correct detection probability are established. Finally, the sensing effects of different sensing methods are analyzed and compared, providing a reference for addressing spectrum sharing issues between NGSO constellation systems and other satellite systems.

[0058] The technical solution of the present invention is described in detail below with reference to the accompanying drawings and embodiments.

[0059] Example 1

[0060] Embodiment 1 of the present invention proposes a method for dynamic time-varying channel spectrum sensing in an NGSO constellation system. The specific description is as follows:

[0061] 1. Construction of Collaborative Spectrum Sensing Scenario

[0062] 1.1 Satellite and Ground Station Collaborative Downlink Perception Scenario

[0063] In the constructed NGSO satellite system downlink perception scenario, considering the spatial orbital relationship between the perception and authorization satellite systems, as shown in Figure 1, the satellites of the NGSO constellation system are used as perception and authorization nodes, respectively. The downlink perception scenario in Figure 1(a) uses NGSO system satellites as perception nodes, collaboratively perceiving downlink transmission signals from authorized satellites; the downlink perception scenario in Figure 1(b) uses multiple ground stations as perception nodes, collaboratively perceiving downlink transmission signals from NGSO constellation system satellites.

[0064] In Figure 1, the signal power C received by the i-th sensing node from the downlink signal transmitted by the authorized satellite is di and signal-to-noise ratio (SNR)γ di They are

[0065]

[0066] Where p pn is the transmission power of the authorized node, W; G pnt (θ pnt,i) is the transmitting antenna gain of the authorized node, θ pnt,i G is the off-axis angle of the authorized node's transmitting antenna on the i-th sensing link; snr (θ snr,i ) is the receiving antenna gain of the sensing node, θ snr,i is the receiving antenna off-axis angle of the i-th sensing node; k B is the Boltzmann constant, which is 1.38×10 -23 J / K; T is the equivalent noise temperature of the receiving end of the sensing node, K; W is the bandwidth of the sensing communication link, Hz; l i is the link loss of the i-th sensing node, which is specifically

[0067]

[0068] Ignoring line loss and antenna pointing error loss, in Figure 1(a) i is the intersatellite link loss, only considering the space loss; in Figure 1(b) i is the satellite-to-ground link loss. In addition to the space loss, the attenuation caused by rainfall and fog must also be considered. In formula (2), f is the communication frequency, Hz; d sn,i→pn is the distance of the i-th sensing link, m; A r,i is the attenuation value caused by rainfall in the satellite-to-ground link, dB; A c,i is the attenuation value caused by clouds and fog in the satellite-to-ground link, dB.

[0069] 1.2 Satellite Collaborative Uplink Perception Scenario

[0070] To avoid the adverse effects of multi-mechanism channel noise on electromagnetic wave propagation in the ground-to-ground link between ground stations, this section only considers NGSO satellites as spectrum sensing nodes for the uplink communication link. It studies the uplink spectrum sensing technology based on NGSO satellite collaboration and does not currently involve the case where ground stations are used as sensing nodes. Figure 2 The NGSO system satellites are used as sensing nodes to collaboratively sense the uplink transmission signal of the authorized ground station. The power C of the uplink transmission signal received by the i-th sensing node from the authorized ground station is ui and signal-to-noise ratio γ ui The calculation of can refer to formula (1), where l i is the satellite-to-ground link transmission loss.

[0071] 2 Perception Signal Model and Distribution Characteristics

[0072] The sensing link types of satellite systems can be divided into time-invariant and time-varying channel communication links. Among them, the time-invariant channel communication link refers to a link in which the channel gain does not change with the sensing time slot. That is, under the condition that the spectrum occupancy state of the authorized node remains unchanged, the signal power value received by the sensing node in different sampling time slots does not change with the sampling time; the time-varying channel communication link refers to a link in which the channel gain has time-varying characteristics. The signal power value received by the sensing node in different time slots varies with the channel characteristics.

[0073] The perception signal model commonly used in existing technologies is mainly aimed at time-invariant channel communication links, and there are few studies that consider the time-varying characteristics of link channels. Figure 2 The time-varying characteristics of the perception link in the constructed scenario are considered, and the construction of the corresponding perception signal model is studied below, taking into account the influence of the channel environment and the radio wave propagation model.

[0074] 2.1 Signal Model of Time-Varying Channel Communication Link

[0075] The existing technology has little research on the perception signal model of time-varying channel links. The main method is to take the average of the signal-to-noise ratios of different time slots received during the perception period, and then perform corresponding modeling according to the method of time-invariant channel links. Based on the research in Section 1, this section studies the downlink scenario Figure 1(a), Figure 1(b) and the uplink scenario Figure 2 The three cases involved derive the kth time slot signal x of the authorized node received by the i-th sensing node under the time-varying channel link condition. i,k The model is

[0076]

[0077] Where,

[0078] C i,k =p pn G pnt (θ pnt,i,k )G snr (θ snr,i,k ) / l i,k ,

[0079] K i =2U i ,k=1,2,...,K i (4)

[0080] Where, The idle state of the spectrum of the authorized node; is the spectrum occupancy status of the authorized node; K i is the number of samples in the i-th sensing cycle, U i is the delay-bandwidth product; φ i is the channel phase; Ci,k is the power of the signal received by the i-th sensing node; is the sampling signal of the kth time slot transmitted by the authorized node, which obeys the circularly symmetric complex Gaussian (CSCG) distribution with zero mean, n i,k is the k-th time slot additive Gaussian white noise sampling signal received by the i-th sensing node, that is,

[0081] 2.2 Signal Distribution Characteristics of Time-Varying Channel Communication Links

[0082] The i-th sensor node receives the signal x i,k The test statistic R i (x i,k ) is defined as

[0083]

[0084] Taking into account Under the condition that the i-th sensing node only receives the noise signal power Therefore, in Under the condition, R i The degree of freedom is 2K i Chi-square distribution of Their probability density functions (PDFs) are

[0085]

[0086] Where H(ρ) is the Heaviside step function. Therefore, the false alarm probability of the i-th sensing node in the time-varying channel communication link is for

[0087]

[0088] Taking into account With {n i,k} are independent of each other, then Under the condition, x i,k Obey the zero-mean CSCG distribution, the specific form is Considering the signal power value C received by the sensing node in different time slots i,k is a function of the sampling time slot k, so {x i,k} is K i A set of independent complex Gaussian random variables with different variances, the detection statistic R corresponding to the i-th sensor node i (x i,k ) obeys a generalized chi-square distribution, whose PDF is

[0089]

[0090] In particular, if there is C i,k =C i,l ,k≠l, then Z i A subset of elements with different values ​​is defined as {ε j |j∈Z i ,1≤Z i ≤K i}. Element ε j In the collection The number of times it appears in is r j , the specific form is

[0091]

[0092] r j satisfy

[0093]

[0094] In the case of formula (16,17), R i (x i,k ) is

[0095]

[0096] Where, k,l,r for

[0097]

[0098]

[0099] Conditional detection probability The probability density function The specific form is:

[0100]

[0101] The false detection probability P of the i-th sensor node e,i and the correct detection probability P c,i They are

[0102]

[0103] Where, and are the conditional detection probabilities ( Conditions) and false alarm probability ( condition); and are the probabilities of spectrum idle and occupied states, respectively.

[0104] 3 Basic principles and optimization methods of fusion decision strategy based on time-varying channel characteristics

[0105] Based on the research on the perception signal model in Section 2, for the orbital configuration of the authorized system satellite and the actual scenario of collaborative perception of satellites or ground stations in the perception constellation system, it is necessary to design the corresponding weighted decision algorithm of the perception node according to the time-varying characteristics of the link, and finally make a fusion decision.

[0106] 3.1 Basic Principles of OFD-TVC Strategy

[0107] Based on the perception signal model constructed in Section 2.2, the cooperative perception strategy under time-varying channel link conditions is studied. It is necessary to consider the variation characteristics of the signal power received by different perception nodes with different sampling time slots, the perception channel characteristics and R i (x i,k )’s statistical properties.

[0108] Assume that the number of samples of each sensor node is K i Same, that is, K i =K, this section will divide each sensor node according to its ξ i The threshold judgment is performed separately, and then the results of each sensing node are fused and decided. The fusion decision criterion is: if at least L sensing nodes in the M nodes of the sensing system judge that the authorized node exists, the final result of the fusion judgment is that the authorized node is state, namely the "L out of M" criterion, and accordingly, the global conditional detection probability P g,d and false alarm probability P g,f for

[0109]

[0110]

[0111] Where L is the rank of the "L out of M" criterion. If L = 1, it is the "OR" criterion, and if L = M, it is the "AND" criterion. I is the set of all possible decision results of all nodes, with a cardinality of i. and Calculated in Section 2.2.

[0112] From (17,18), we can get the global correct detection probability P g,c and the global error detection probability P g,e for

[0113]

[0114]

[0115] Based on this, this section proposes an optimal L-rank and each sensing node decision threshold ξ=[ξ1,ξ2,…,ξ M ] T The joint calculation method is called the optimal fusion decision for time-varying channel link (OFD-TVC) strategy. This strategy uses the global error detection probability P g,e As the objective function to be optimized, its form is

[0116]

[0117] In the downlink and uplink cooperative sensing scenarios of the NGSO system, when using the cooperative sensing of multiple satellites or ground stations in the constellation system, when selecting the ground station, it is necessary to consider whether the sensing link it builds meets the minimum elevation angle requirement, and take into account the round-trip delay of electromagnetic wave propagation in the satellite-to-ground and inter-satellite links. In view of the "protection" requirements of the International Telecommunication Union (ITU) for authorized satellites, when further studying the constraints corresponding to the objective function of Equation (21), the proposed OFD-TVC strategy needs to consider not only the limit conditions satisfied by the false alarm probability of the cooperative sensing node, but also the limit conditions of the corresponding spectrum conflict probability.

[0118] Figure 3 It reflects the spectrum conflict between M sensing nodes and authorized nodes. is the duration of the spectrum idle state of the authorized node; t d,i is the duration of data transmission of the i-th sensing node; t h,i is the spectrum idle time caused by the i-th sensing node not being used; t delay,i is the delay difference between detection and spectrum utilization of the i-th sensing node.

[0119] When studying the spectrum conflict model during spectrum sensing, the idle state duration X before the authorized node spectrum state transition is idle Obeying the exponential distribution with parameter λ, the maximum likelihood estimate of λ for in, For X idle The sample mean of .

[0120] This section assumes that when the spectrum state of the authorized node changes, the sensing node will immediately make a detection response, that is, t delay,i =t h,i For the i-th sensing node, the effective probability P of idle spectrum is eff,i and the availability probability Pava,i Defined as

[0121]

[0122]

[0123] The spectrum conflict probability P between the i-th sensing node and the authorized node at a certain moment is sc,i for

[0124]

[0125] Substituting equations (22, 23) into (24), we can obtain

[0126]

[0127] Global spectrum conflict probability P g,sc Can be defined as

[0128]

[0129] Where, and are the average effective probability and average available probability of idle spectrum respectively.

[0130] In summary, the proposed OFD-TVC strategy needs to consider the false alarm probability of each collaborative sensing node. and spectrum conflict probability P sc,i The limiting condition of P sc,i Calculate the required corresponding delay t delay,i Determined by the specific link type. The nonlinear constraint corresponding to formula (21) is:

[0131]

[0132] 3.2 Optimization method for solving OFD-TVC strategy

[0133] The OFD-TVC strategy proposed in Section 3.1 can be solved and optimized by using the subgradient method based on Lagrangian duality theory. The specific solution and optimization process is described as follows.

[0134] The Lagrangian function J1(ξ,L) of formula (21,27) is constructed as

[0135]

[0136] Where ξ=[ξ1,ξ2,…,ξ M ] T κ m =(κ m,1 ,...,κ m,M )≥0 and κn =(κ n,1 ,...,κ n,M )≥0 is the Lagrangian factor of J1(·). Let J1(·) be the Lagrangian factor of ξ i The partial derivative function value of and L is 0, and the optimal value ξ can be obtained by Newton iteration method i * and L * , the specific solution algorithm is shown in Table 1.

[0137] Table 1 OFD-TVC strategy solution algorithm

[0138]

[0139]

[0140] 4OFD-TVC strategy simulation implementation and effect analysis

[0141] 4.1 Analysis of the Effect of Ground Station Collaborative Perception of NGSO Satellite Downlinks

[0142] The beam and air interface parameters of the sensing ground station are shown in Table 2. The orbital parameters and beam air interface parameters of the authorized NGSO satellite refer to the downlink GTA beam and air interface parameters of OneWeb's satellite registered with the ITU. The antenna beam points to its sub-satellite point, as shown in Table 3.

[0143] Table 2 Perception ground station downlink beam and air interface parameters

[0144]

[0145] Table 3 Authorized NGSO satellite downlink orbit, beam and air interface parameters

[0146]

[0147] Sensing ground stations are randomly deployed within the latitude range of 25°N to 35°N and longitude range of 110°E to 120°E for simulation verification and analysis, and must meet the minimum elevation angle requirements. Figure 4 The figure shows the change in the signal-to-noise ratio received by each ground station when the OneWeb satellite passes by. In the figure, the number of sensing ground stations is 10, the lowest elevation angle is 15°, and the satellite transmission power density is -61.1dB (W·Hz -1 ).

[0148] exist Figure 4 In the scenario, Figure 5 reflects the correct detection, conditional detection and spectrum conflict probability of the sensing ground station using the OFD-TVC strategy under different transmission power density conditions of OneWeb's satellites, where Spectrum conflict probability limit P sc,thThe effective probability limit and available probability limit of idle spectrum are 0.8. Considering that the false alarm probability of spectrum sensing terminal required by IEEE802.22 protocol is Therefore, the false alarm probability limit P f,th Take 0.1.

[0149] In Figure 5, the OFD-TVC strategy is adopted, with K=100, Under these conditions, when the transmission power density of OneWeb satellite is -80dB (W·Hz -1 ), the correct detection probability can reach 0.81.

[0150] Figure 6 Reflects the probability of different spectrum states The characteristic curve of the correct detection probability under the conditions. In the figure, when K=100, the transmission power density of OneWeb satellite is -80dB(W·Hz -1 ) condition, when When , the correct detection probability can reach 0.85; when When , the correct detection probability can reach 0.88.

[0151] 4.2 Analysis of the Effect of Satellite Collaborative Perception Authorization Satellite Downlink in NGSO Constellation System

[0152] The orbital parameters and beam air interface parameters of the authorized satellite refer to the downlink KADWB beam and air interface parameters of the CHNNEWSAT-G1-118E satellite registered with the ITU. The antenna beam is pointed to its sub-satellite point as shown in Table 4. The orbital parameters and beam air interface parameters of the constructed sensing NGSO satellite are shown in Table 5. Six NGSO satellites within the visible range of the authorized satellite are selected for sensing.

[0153] Table 4 Authorized system satellite downlink orbit, beam and air interface parameters

[0154]

[0155]

[0156] Table 5 Perception of NGSO system satellite orbit, receiving beam and air interface parameters

[0157]

[0158] Figure 7 The six selected NGSO satellites are sent through the authorized satellite to detect the signal-to-noise ratio changes of the NGSO satellites received from the authorized satellites. The authorized satellite transmits a power density of -52.9dB (W·Hz). -1 ).

[0159] according to Figure 7 The scene shown, Figure 8 It reflects the correct detection probability of NGSO satellites using OFD-TVC strategy under different transmission power density conditions of authorized satellites, where the false alarm probability limit P f,th is 0.1.

[0160] Figure 8 In the

[15] , considering the dynamics of the link when the NGSO satellite transmits the beam through the authorized satellite and the low average signal-to-noise ratio, the correct detection probability is lower than that of the ground station perception cooperation. When K = 100, Under these conditions, when the authorized satellite's transmission power density is -70dB (W·Hz -1 ), the correct detection probability is 0.51; when the transmission power density of the authorized satellite is -60dB (W·Hz -1 ), the correct detection probability is 0.88.

[0161] 4.3 Analysis of the Uplink Effect of Satellite Collaborative Perception Ground Stations in NGSO Constellation Systems

[0162] The orbital parameters, receiving beam and air interface parameters of the NGSO satellite are shown in Table 5. The authorized ground station is located at the sub-satellite point of CHNNEWSAT-G1-118E. The uplink transmit beam and air interface parameters are based on the uplink KAUWB beam information of CHNNEWSAT-G1-118E satellite registered with the ITU, as shown in Table 6.

[0163] Table 6 Authorization system ground station uplink beam and air interface parameters

[0164]

[0165]

[0166] Figure 9 The six selected NGSO satellites are sent through the ground station to detect the change in the signal-to-noise ratio received by the NGSO satellites from the ground station. The ground station transmit power density is -47.30dB (W·Hz -1 ).

[0167] refer to Figure 9 The scene shown, Figure 10 It reflects the correct detection probability of the NGSO satellite passing through the authorized ground station under different transmission power density conditions of the ground station, among which the false alarm probability limit P f,th is 0.1.

[0168] Figure 10 In the case of K=100, Under these conditions, when the transmission power density of the authorized ground station is -70dB (W·Hz-1 ), the correct detection probability is 0.55; when the transmission power density of the ground station is -60dB (W·Hz -1 ), the correct detection probability is 0.85.

[0169] 4.4 Comparative Analysis of Perception Results in Each Scenario

[0170] In the above three perception scenarios, in order to further verify the effectiveness of the proposed method, the proposed OFD-TVC strategy is compared and analyzed with other related literature, such as Figure 11 The results shown in the figure mainly involve the energy detection (ED) method mentioned in the introduction and the collaborative spectrum sensing method based on optimal signal-to-noise ratio weighting. The first row shows the comparison of ground station collaborative sensing results for NGSO satellite downlinks, the second row shows the comparison of NGSO constellation system satellite collaborative sensing results for authorized satellite downlinks, and the third row shows the comparison of NGSO constellation system satellite collaborative sensing results for ground station uplinks.

[0171] In the scenario of ground station cooperative sensing of NGSO satellite downlink, when the authorized satellite transmit power density is -75dB (W·Hz -1 ), the correct detection probability is improved by 20.2% to 34.8% compared with other literatures; in the NGSO constellation system satellite cooperative sensing authorized satellite downlink scenario, when the authorized satellite transmit power density is -60dB (W·Hz -1 ), the correct detection probability is improved by 10.3% to 18.4% compared with other literatures; in the NGSO constellation system satellite cooperative sensing ground station uplink scenario, when the ground station transmit power density is -65dB (W·Hz -1 ), the correct detection probability is increased by 5.6% to 10.4% compared with other literatures.

[0172] Example 2

[0173] Embodiment 2 of the present invention proposes a dynamic time-varying channel spectrum sensing system for an NGSO constellation system, which is implemented based on the method of embodiment 1. The system includes:

[0174] Scenario building module, used to build collaborative spectrum sensing scenarios for NGSO constellation systems;

[0175] A model building module is used to build a signal model for spectrum sensing of the NGSO constellation system based on a dynamic time-varying sensing channel link;

[0176] Function condition establishment module, used to construct the objective function and constraint conditions of the corresponding perception link;

[0177] The decision strategy module is used to design a collaborative spectrum sensing optimization fusion decision strategy based on the objective function and constraints, and obtain the optimal solution for the decision threshold and number of sensing nodes.

[0178] in conclusion:

[0179] In the spectrum sensing simulation analysis of the NGSO constellation system and other satellite systems in the spectrum coexistence scenario:

[0180] 1) A flexible perception scenario model was established, the perception effects were quantitatively studied and analyzed in different scenarios, and a mathematical model of the perception signal of the time-varying channel was constructed.

[0181] 2) For dynamic time-varying channels, a collaborative spectrum sensing fusion OFD-TVC strategy is proposed, which takes into account the influence of the perceived channel environment, the radio wave propagation model, and the spectrum conflict with the authorized system.

[0182] 3) The perception effect of the proposed method is analyzed in three scenarios: ground station cooperative perception of NGSO satellite downlink, NGSO satellite cooperative perception of authorized satellite downlink and ground station uplink. When K≥100, Authorized node transmission power density ≥ -60dB (W·Hz -1 ) conditions, the correct detection probability can reach above 0.85.

[0183] To address the spectrum sharing issue between non-geostationary satellite orbit (NGSO) satellite constellations and other satellite systems, this paper proposes a collaborative spectrum sensing method that takes into account the dynamic, time-varying characteristics of satellite sensing channels. First, based on the dynamic, time-varying sensing channel link, a signal model for spectrum sensing in the NGSO constellation system is established. The objective function and constraints of the corresponding sensing link are constructed, and parameters such as the decision threshold and number of sensing nodes are optimized. Based on this, a collaborative spectrum sensing optimization fusion decision strategy is proposed and an algorithm is implemented. Finally, in a spectrum sensing scenario constructed using actual satellite network data registered by the International Telecommunication Union (ITU), multiple ground stations and NGSO satellites are used as sensing nodes, and the correct detection probability under different sensing modes and channel environments is quantitatively studied and analyzed. Simulation results demonstrate that the proposed collaborative spectrum sensing method achieves good correct perception results in dynamic, time-varying sensing channel scenarios, further improving the efficient utilization of spatial spectrum resources.

[0184] Finally, it should be noted that the above embodiments are intended only to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention and are intended to be encompassed by the claims of the present invention.

Claims

1. A method for dynamic time-varying channel spectrum sensing in an NGSO constellation system, comprising: Step 1) Constructing a collaborative spectrum sensing scenario for the NGSO constellation system; Step 2) Based on the dynamic time-varying sensing channel link, a signal model for spectrum sensing of the NGSO constellation system is established; Step 3) Construct the objective function and constraints of the corresponding sensing link; Step 4) Based on the objective function and constraints, a collaborative spectrum sensing optimization fusion decision strategy is designed to obtain the optimal solution for the decision threshold and number of sensing nodes; The step 3) comprises: The global error detection probability P g,e As the objective function to be optimized: Where M means that the perception system includes M nodes, L means that at least L perception nodes among the M nodes determine the existence of the authorized node. and are the probabilities of spectrum idle and occupied states respectively, I is the set of possible decision results of all nodes, with cardinality i, is the false alarm probability of the jth sensing node under the time-varying channel communication link, is the false alarm probability of the qth sensing node under the time-varying channel communication link, is the conditional detection probability of the j-th sensor node, is the conditional detection probability of the qth sensor node, The nonlinear constraints are constructed as follows: Where, is the false alarm probability of the i-th sensing node under the time-varying channel communication link, P f,th is the false alarm probability limit, P sc,th is the spectrum conflict probability limit, P sc,i is the spectrum conflict probability between the i-th sensing node and the authorized node at a certain moment, satisfying the following formula: Where, P eff,i and P ava,i are the effective probability and available probability of idle spectrum of the i-th sensing node, respectively, delay,i is the delay difference between the detection of the i-th sensing node and the spectrum utilization, and the idle state duration X before the spectrum state of the authorized node is transferred idle Obeying the exponential distribution with parameter λ, t d,i is the duration of data transmission of the i-th sensing node; The step 4) comprises: Construct the Lagrangian function J1(ξ,L): Where ξ=[ξ1,ξ2,…,ξ M ] T ; T represents transposition, κ m =(κ m,1 ,...,κ m,M )≥0 and κ n =(κ n,1 ,...,κ n,M )≥0 is the Lagrangian factor of J1(·); Let J1(·) be the value of ξ i The partial derivative function value of and L is 0, and the optimal value of the decision threshold of the sensing node ξ is obtained by the Newton iteration method. i * And the optimal value of quantity L * .

2. The method for dynamic time-varying channel spectrum sensing of an NGSO constellation system according to claim 1, wherein: The step 1) includes: constructing a satellite and ground station collaborative downlink perception scenario or a satellite collaborative uplink perception scenario based on the spatial orbital position relationship between the perception and authorization satellites, wherein: The satellite and ground station collaborative downlink sensing scenario is: using the satellites of the NGSO constellation system as sensing nodes to collaboratively sense the downlink transmission signals of the authorized satellites; or using multiple ground stations as sensing nodes to collaboratively sense the downlink transmission signals from the satellites of the NGSO constellation system; The satellite collaborative uplink perception scenario is: using NGSO constellation system satellites as perception nodes to collaboratively perceive the uplink transmission signals of authorized ground stations.

3. The method for dynamic time-varying channel spectrum sensing of an NGSO constellation system according to claim 1, characterized in that: The signal model for spectrum sensing of the NGSO constellation system established in step 2) is: The kth time slot signal x received by the i-th sensing node from the authorization node PN i,k The model is: Where, C i,k =p pn G pnt (i pnt,i,k )G snr (i snr,i,k ) / l i,k K i =2U i ,k=1,2,...,K i Where, is the idle state of the authorized node spectrum, is the spectrum occupancy status of the authorized node, K i is the number of samples in the i-th sensing cycle, U i is the delay-bandwidth product, φ i is the channel phase; C i,k is the power of the signal received by the i-th sensing node, is the sampling signal of the kth time slot transmitted by the authorized node, which obeys the circularly symmetric complex Gaussian distribution with zero mean, n i,k is the k-th time slot additive Gaussian white noise sampling signal received by the i-th sensing node, that is, 4. A system based on the NGSO constellation system dynamic time-varying channel spectrum sensing method according to claim 1, characterized in that: The system comprises: Scenario building module, used to build collaborative spectrum sensing scenarios for NGSO constellation systems; A model building module is used to build a signal model for spectrum sensing of the NGSO constellation system based on a dynamic time-varying sensing channel link; Function condition building module, used to build the objective function and constraint conditions of the corresponding perception link; and The decision strategy module is used to design a collaborative spectrum sensing optimization fusion decision strategy based on the objective function and constraints, and obtain the optimal solution for the decision threshold and number of sensing nodes.

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