Dynamic spectrum resource coordination method, device, equipment, medium and product

Abstract

The invention provides a dynamic spectrum resource coordination method, device and equipment, a medium and a product, and relates to the technical field of mobile communication network spectrum management. The method comprises the following steps: acquiring signal strength information and neighbor relation of a plurality of cells in the hybrid network; selecting a target cell from the plurality of cells; according to the signal strength information of the plurality of cells and the adjacent cell relationship, determining a cell meeting an association condition with the target cell in the plurality of cells as an interference cell; dynamically associating the interference cell with the target cell to obtain an interference coordination cluster; obtaining hybrid network resource data and historical network resource data in the cluster; performing telephone traffic prediction according to the hybrid network resource data and the historical network resource data to obtain a service prediction result under the dynamic spectrum sharing network; and performing time domain and / or frequency domain cooperative adjustment on the dynamic spectrum resources in the hybrid network according to the service prediction result. Time domain and / or frequency domain resource configuration is carried out in the interference coordination cluster, so that the overall utilization efficiency of spectrum resources can be improved to the greatest extent.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of spectrum management of mobile communication networks, and in particular to a dynamic spectrum resource coordination method, device, equipment, medium and product. BACKGROUND

[0002] With the large-scale deployment and rapid development of networks, low-frequency spectrum has become a key resource for realizing wide-area continuous coverage and high-speed transmission due to its excellent coverage capability and propagation characteristics. However, the low-frequency spectrum is usually occupied by the 4th Generation Long-Term Evolution (4G LTE) network, and if independent dedicated spectrum is directly allocated for the 5th Generation New Radio (5G NR), it will inevitably cause insufficient utilization of valuable spectrum resources.

[0003] At present, the common spectrum sharing method is to configure independent carriers and allocate fixed spectrum resources for different standard networks in the same frequency band. This method cannot be dynamically adjusted according to real-time business needs, and the resource utilization efficiency is low. SUMMARY

[0004] The embodiments of the present application provide a dynamic spectrum resource coordination method, device, equipment, medium and product to solve the technical problem of low resource utilization efficiency caused by the prior art.

[0005] In a first aspect, the embodiments of the present application provide a dynamic spectrum resource coordination method, comprising:

[0006] Obtaining signal strength information and neighbor relation of a plurality of cells in a hybrid network;

[0007] Selecting one cell as a target cell from the plurality of cells;

[0008] According to the signal strength information of the plurality of cells and the neighbor relation, determining a cell that meets an association condition with the target cell as an interference cell from the plurality of cells;

[0009] Dynamically associating the interference cell and the target cell to obtain an interference coordination cluster;

[0010] Real-time obtaining of hybrid network resource data and historical network resource data in the interference coordination cluster;

[0011] According to the hybrid network resource data and the historical network resource data, performing traffic prediction processing to obtain a service prediction result under a dynamic spectrum sharing network;

[0012] According to the service prediction result, time domain and / or frequency domain collaborative adjustment is performed on the dynamic spectrum resource in the hybrid networking.

[0013] In a possible implementation, the determining, according to the signal strength information of the plurality of cells and the neighbor relation, of a cell in the plurality of cells as an interference cell when the cell meets an association condition with the target cell, includes:

[0014] According to the signal strength information of the plurality of cells, a cell signal strength difference between each cell and the target cell is determined.

[0015] The cell in the plurality of cells with a cell signal strength difference less than a preset strength threshold is selected as a candidate cell.

[0016] According to the neighbor relation, a candidate cell having a neighbor association relation with the target cell is selected from all candidate cells as an interference cell.

[0017] In a possible implementation, the hybrid network resource data includes a real-time network load matrix and a real-time interference coefficient, and the historical network resource data includes a historical network load matrix and historical traffic data.

[0018] Correspondingly, the traffic prediction processing according to the hybrid network resource data and the historical network resource data to obtain the service prediction result under the dynamic spectrum sharing network includes:

[0019] The real-time network load matrix, the real-time interference coefficient, the historical network load matrix, and the historical traffic data are input into a pre-trained machine learning model for traffic prediction processing to obtain a service change trend and a service demand for network resources of a first standard under the dynamic spectrum sharing network, and a service change trend and a service demand for network resources of a second standard under the dynamic spectrum sharing network.

[0020] The service change trend and the service demand for network resources of the first standard and the service change trend and the service demand for network resources of the second standard are taken as the service prediction result.

[0021] In a possible implementation, the time domain and / or frequency domain collaborative adjustment is performed on the dynamic spectrum resource in the hybrid networking according to the service prediction result, including:

[0022] According to the service prediction result, the dynamic spectrum resource in the hybrid networking is collaboratively adjusted by dynamically configuring a multimedia broadcast multicast single frequency network (MBSFN) subframe ratio to change a resource proportion of the first standard network and the second standard network in the time domain.

[0023] and / or switching part of the frequency domain resources from a dynamically shared state to a second mode network exclusive state in the dynamic spectrum resources according to the service prediction result and a preset threshold condition, and the rest of the frequency domain resources remain in the dynamically shared state, thereby completing the collaborative adjustment.

[0024] In a possible implementation, the dynamic spectrum resource in the mixed networking is adjusted in time domain and / or frequency domain according to the service prediction result, including:

[0025] According to the service prediction result, when a period of time is detected in which the second mode network service is in a peak and the first mode network is in a valley, part of the first mode network resource in the dynamic spectrum resource is released to the second mode network resource for use by increasing the number of multimedia broadcast multicast single frequency network subframes, and vice versa.

[0026] In a possible implementation, the dynamic spectrum resource in the mixed networking is adjusted in time domain and / or frequency domain according to the service prediction result, further including:

[0027] Obtaining interference data of an edge cell in the interference collaborative cluster;

[0028] According to the interference data, the inter-cluster interference avoidance is implemented by reducing the transmission power of the cell-specific reference signal (CRS) of the first mode network, enabling a preset resource element level rate matching, or frequency selection scheduling.

[0029] In a second aspect, an embodiment of the present application provides a dynamic spectrum resource collaborative device, including:

[0030] A first information obtaining module is configured to obtain signal strength information and neighbor relation of a plurality of cells in a mixed networking;

[0031] A target cell determining module is configured to select one cell as a target cell from the plurality of cells;

[0032] An interference cell determining module is configured to determine a cell that meets an association condition with the target cell as an interference cell from the plurality of cells according to the signal strength information and the neighbor relation of the plurality of cells;

[0033] A second information obtaining module is configured to dynamically associate the interference cell and the target cell to obtain an interference collaborative cluster;

[0034] A third information obtaining module is configured to obtain mixed network resource data and historical network resource data in the interference collaborative cluster in real time;

[0035] a prediction module, configured to perform traffic prediction processing according to the hybrid network resource data and the historical network resource data, to obtain a service prediction result under the dynamic spectrum sharing network;

[0036] an adjustment module, configured to perform time domain and / or frequency domain coordinated adjustment on the dynamic spectrum resource in the hybrid networking according to the service prediction result.

[0037] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, and a memory connected with the processor in communication;

[0038] The memory stores computer execution instructions.

[0039] The processor executes the computer execution instructions stored in the memory, to implement the dynamic spectrum resource coordination method in any one of claims 1 to 6.

[0040] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, which stores computer execution instructions, and the computer execution instructions are executed by a processor to implement the dynamic spectrum resource coordination method in any one of claims 1 to 6.

[0041] In a fifth aspect, an embodiment of the present application provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the dynamic spectrum resource coordination method in any one of claims 1 to 6.

[0042] The present application provides a dynamic spectrum resource coordination method, device, equipment, medium and product, comprising: obtaining signal strength information and neighbor relation of a plurality of cells in hybrid networking; selecting one cell as a target cell in the plurality of cells; determining a cell satisfying an association condition with the target cell as an interference cell in the plurality of cells according to the signal strength information and the neighbor relation of the plurality of cells; dynamically associating the interference cell and the target cell to obtain an interference coordination cluster; obtaining hybrid network resource data and historical network resource data in the interference coordination cluster in real time; performing traffic prediction processing according to the hybrid network resource data and the historical network resource data, to obtain a service prediction result under the dynamic spectrum sharing network; and performing time domain and / or frequency domain coordinated adjustment on the dynamic spectrum resource in the hybrid networking according to the service prediction result. Through the above method, the following technical effects are achieved: traffic prediction processing is performed on the hybrid network resource data and the historical network resource data in the interference coordination cluster, and time domain and / or frequency domain coordinated adjustment is performed using the obtained service prediction result, so that resource configuration in the time domain and / or the frequency domain is performed in advance in the interference coordination cluster, the resource supply accurately fits the service demand curve, resource idling and congestion can be significantly reduced, user experience is ensured, and the overall utilization efficiency of spectrum resources is maximized. BRIEF DESCRIPTION OF DRAWINGS

[0043] The accompanying drawings, which are incorporated herein and constitute part of this specification, illustrate embodiments consistent with the application and, together with the description, further serve to explain the principles of the application.

[0044] Figure 1 An application scenario diagram of a dynamic spectrum resource coordination method provided by an embodiment of the application;

[0045] Figure 2 A flowchart of a dynamic spectrum resource coordination method provided by an embodiment of the application Figure One ;

[0046] Figure 3 A flowchart of a dynamic spectrum resource coordination method provided by an embodiment of the application Figure Two ;

[0047] Figure 4 A flowchart of a dynamic spectrum resource coordination method provided by an embodiment of the application Figure Three ;

[0048] Figure 5 A structural diagram of a dynamic spectrum resource coordination apparatus provided by an embodiment of the application;

[0049] Figure 6 A structural diagram of an electronic device provided by an embodiment of the application.

[0050] Explanation of reference signs:

[0051] 110 - terminal; 120 - server; 801 - processor; 802 - memory; 803 - communication component; 804 - bus.

[0052] The specific embodiments of the application have been shown by the above-described drawings, and will be described in more detail hereinafter. These drawings and the written description are not intended to restrict the scope of the concept of the application by any means, but to illustrate the concept of the application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0053] The exemplary embodiments will be described in detail herein below with reference to the drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the application. Instead, they are merely examples of apparatuses and methods consistent with some aspects of the application as detailed in the appended claims.

[0054] In the embodiments of the present application, the same items or similar items with basically the same functions and effects are distinguished by using "first", "second", and the like. Those skilled in the art can understand that "first", "second", and the like do not limit the quantity and execution order, and "first", "second", and the like do not necessarily mean different. It should be noted that in the embodiments of the present application, "exemplary" or "for example" is used to represent an example, illustration, or description. Any embodiment or design scheme described as "exemplary" or "for example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, "exemplary" or "for example" is used to present the relevant concept in a specific manner. In the embodiments of the present application, "at least one" means one or more, and "multiple" means two or more.

[0055] It should be noted that "at" in the embodiments of the present application can be at the moment when a certain condition occurs, or within a period of time after a certain condition occurs, which is not limited in the embodiments of the present application. In addition, the dynamic spectrum resource coordination method provided in the embodiments of the present application is only an example, and the dynamic spectrum resource coordination method can include more or less content.

[0056] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards, and provide corresponding operation portal for user to choose authorization or refusal.

[0057] First, the terms are explained.

[0058] Mixed networking: different generations or different types of communication technologies exist and are used at the same time in a communication network.

[0059] In order to clearly understand the technical solutions of the present application, the prior art solutions are first introduced in detail.

[0060] At present, the common spectrum sharing mode is to configure independent carriers and allocate fixed spectrum resources for different system networks in the same frequency band. This mode cannot be dynamically adjusted according to real-time business needs, and the resource utilization efficiency is low.

[0061] In summary, how to design a technology that can solve the technical problem of low resource utilization efficiency caused by the prior art is a problem that needs to be solved urgently in the present application.

[0062] Therefore, in view of the above technical problems in the prior art, the embodiment of the present application provides a dynamic spectrum resource coordination method, device, equipment, medium and product, which aims to effectively improve the resource utilization efficiency.

[0063] The application scenario of the dynamic spectrum resource coordination method, device, equipment, medium and product provided by the embodiment of the present application is introduced below. The following application scenarios are only examples, and the purpose is to help those skilled in the art to understand the technical content of the present application, but it does not mean that the embodiment of the present application cannot be used for other devices, systems, environments or scenarios.

[0064] Low-frequency dynamic spectrum sharing deployment scenario: through the dynamic spectrum resource coordination method, device, equipment, medium and product provided by the embodiment of the present application, the shared spectrum resources between different systems can be intelligently predicted and dynamically allocated, which is a key technical support for realizing 5G NR fast wide-area coverage and guaranteeing the experience of 4G LTE inventory users.

[0065] Figure 1 The application scenario of the dynamic spectrum resource coordination method provided by the embodiment of the present application is shown in FIG. 1, which includes a terminal 110 and a server 120. Figure 1

[0066] The terminal 110 can be a user terminal under a 5G NR or 4G LTE network. The server 120 is configured to perform time domain and / or frequency domain coordination adjustment on the dynamic spectrum resources in the hybrid networking according to the business prediction result.

[0067] Figure 2 The flowchart of the dynamic spectrum resource coordination method provided by the embodiment of the present application is shown in FIG. 2. Figure One The execution subject of the embodiment can be the server 120 in FIG. 1, or other computer-related devices, which are not particularly limited in the embodiment. The dynamic spectrum resource coordination method provided by the embodiment includes the following steps. Figure 1

[0068] S101, obtain the signal strength information and the adjacent cell relationship of a plurality of cells in the hybrid networking.

[0069] In the embodiment, the signal strength information includes but is not limited to the reference signal received power (RSRP) and the signal to interference plus noise ratio (SINR). The adjacent cell relationship is a list of all possible interactive cells around each cell in the hybrid networking. Optionally, the signal strength information and the adjacent cell relationship of the plurality of cells can be obtained through the network side background data and the terminal side field measurement data.​​

[0070] S102, selecting one cell as a target cell from the plurality of cells.

[0071] In this embodiment, as an optional implementation, if the RSRP of the A cell in the plurality of cells fluctuates greatly in a certain time period, the A cell is selected as the target cell.

[0072] As an optional implementation, a pre-stored algorithm is used to determine the target cell.

[0073] S103, determining, according to the signal strength information of the plurality of cells and the adjacent cell relationship, a cell that meets the association condition with the target cell as an interference cell from the plurality of cells.

[0074] In this embodiment, through an automatic learning mechanism, a cell that is adjacent to the topology structure of the target cell and has significant interference is determined as an interference cell according to the interference characteristics between cells.

[0075] S104, dynamically associating the interference cell and the target cell to obtain an interference coordination cluster.

[0076] In this embodiment, after the interference cell is obtained, the interference cell and the target cell are dynamically associated to generate an interference coordination cluster, which serves as a basic unit for subsequent resource allocation and interference coordination. Under this architecture, each cell will be classified into a corresponding interference coordination cluster. It should be noted that although the conventional dynamic spectrum sharing (DDS) network mechanism realizes complete orthogonal isolation of 4G LTE and 5G NR networks within a single physical cell, in a cross-cell scenario, substantial interference will still occur between 5G NR and surrounding 4G LTE cells.

[0077] S105, acquiring mixed network resource data and historical network resource data in the interference coordination cluster in real time.

[0078] In this embodiment, the mixed network resource data and the historical network resource data can be obtained through a pre-stored database.

[0079] S106, performing traffic prediction processing according to the mixed network resource data and the historical network resource data to obtain a service prediction result under a dynamic spectrum sharing network.

[0080] In this embodiment, the traffic prediction processing based on the mixed network resource data and the historical network resource data can improve the accuracy of the prediction data.

[0081] S107, performing time domain and / or frequency domain coordination adjustment on the dynamic spectrum resources in the mixed networking according to the service prediction result.

[0082] In this embodiment, the interference coordination cluster cell real-time interaction network load data is interfered, and according to the interference coordination cluster cell service prediction result, that is, the service change trend corresponding to 4G LTE and 5G NR two modes respectively under the interference coordination cluster DSS network, the demand of service on network resource, the available network resources of 4G LTE and 5G NR two modes are adjusted through time domain, frequency domain and time-frequency superposition adjustment mode, and the accurate matching of service demand and resource allocation is realized.

[0083] By traffic prediction processing on the mixed network resource data and historical network resource data in the interference coordination cluster, and using the obtained service prediction result for time domain and / or frequency domain coordination adjustment, the resource configuration in time domain and / or frequency domain in the interference coordination cluster is carried out in advance, so that the resource supply accurately matches the service demand curve, which can significantly reduce resource idling and congestion, while ensuring user experience, and maximally improves the overall utilization efficiency of spectrum resources.

[0084] The application provides a dynamic spectrum resource coordination method, comprising: acquiring signal strength information and neighbor relation of a plurality of cells in a mixed networking; selecting one cell as a target cell in the plurality of cells; determining a cell that meets an association condition with the target cell as an interference cell in the plurality of cells according to the signal strength information and the neighbor relation of the plurality of cells; dynamically associating the interference cell and the target cell to obtain an interference coordination cluster; acquiring mixed network resource data and historical network resource data in the interference coordination cluster in real time; performing traffic prediction processing on the mixed network resource data and the historical network resource data to obtain a service prediction result under a dynamic spectrum sharing network; and performing time domain and / or frequency domain coordination adjustment on dynamic spectrum resources in the mixed networking according to the service prediction result. Through the above method, the following technical effects are realized: by performing traffic prediction processing on the mixed network resource data and the historical network resource data in the interference coordination cluster, and using the obtained service prediction result for time domain and / or frequency domain coordination adjustment, resource configuration in time domain and / or frequency domain in the interference coordination cluster is carried out in advance, so that the resource supply accurately matches the service demand curve, which can significantly reduce resource idling and congestion, while ensuring user experience, and maximally improves the overall utilization efficiency of spectrum resources.

[0085] Figure 3 A flowchart of a dynamic spectrum resource coordination method provided by the embodiment of the application Figure Two In the dynamic spectrum resource coordination method provided by the embodiment of the application, S103 comprises the following steps:

[0086] S201, according to the signal strength information of the plurality of cells, determining the cell signal strength difference between each cell and the target cell.

[0087] In this embodiment, the cell signal strength difference between each cell in the plurality of cells and the target cell. The cell signal strength difference includes but is not limited to RSRP difference and SINR difference.

[0088] S202, the cell with a cell signal strength difference less than a preset strength threshold in the plurality of cells is selected as a candidate cell.

[0089] In this embodiment, optionally, when the cell signal strength difference is RSRP difference, the preset strength threshold is 6dBm, and the cell with a cell signal strength difference less than 6dBm in the plurality of cells is selected as a candidate cell; when the cell signal strength difference is SINR difference, the preset strength threshold is 6dB, and the cell with a cell signal strength difference less than 6dB in the plurality of cells is selected as a candidate cell. Here, the preset strength threshold is not limited specifically.

[0090] S203, according to the neighbor relation, a candidate cell with a neighbor relation with the target cell is selected from all candidate cells as an interference cell.

[0091] In this embodiment, a topologically adjacent cell configured with a neighbor relation with the target cell is selected from all candidate cells as an interference cell, and the interference cell in this embodiment is a high-interference cell.

[0092] The interference coordination cluster is a dynamic and adaptive interference coordination basic unit, and its generation not only considers topological adjacency, but more importantly, takes the accurate interference measurement standard of cell signal strength difference as the core basis, to ensure that the cells in the cluster indeed have a strong interference relationship, and provides accurate and efficient operation objects for subsequent coordinated resource adjustment and interference management.

[0093] The cell signal strength difference and the neighbor relation are combined for double screening, so as to more accurately and efficiently determine the interference cell, not only avoiding the possible misjudgment due to simply relying on the signal strength difference, but also significantly reducing the coordination and optimization range, so that the subsequent interference coordination strategy can focus on the truly relevant cells, improving the accuracy of resource adjustment and the overall spectrum efficiency of the network.

[0094] Figure 4 Flowchart of a dynamic spectrum resource coordination method provided by the embodiment of the present application Figure Three In the dynamic spectrum resource coordination method provided by the embodiment of the present application, the mixed network resource data includes real-time network load matrix and real-time interference coefficient, the historical network resource data includes historical network load matrix and historical traffic data, and S106 includes the following steps:

[0095] S301, input the real-time network load matrix, real-time interference coefficient, historical network load matrix and historical traffic data into the pre-trained machine learning model for traffic prediction processing to obtain the service change trend and service demand for network resources of the first system under the dynamic spectrum sharing network, and the service change trend and service demand for network resources of the second system under the dynamic spectrum sharing network.

[0096] In this embodiment, the network load matrix includes the physical resource block (PRB) utilization rate, radio resource control (RRC) user connection number and uplink and downlink rate of the 4G LTE and 5G NR networks. The first system is 4G LTE and the second system is 5G NR. The service change trend of the first system includes the service change trend, service demand peak value and tidal law of 4G LTE, and the service change trend of the second system includes the service change trend, service demand peak value and tidal law of 5G NR.

[0097] Optionally, the pre-trained machine learning model is a traffic pattern based long short-term memory network (TP-LSTM). The real-time network load matrix, real-time interference coefficient, historical network load matrix and historical traffic data are input into the TP-LSTM for traffic prediction processing to obtain the service change trend, service demand peak value and tidal law of 4G LTE under the dynamic spectrum sharing network, and the service change trend, service demand peak value and tidal law of 5G NR under the dynamic spectrum sharing network. Then, the service demand for network resources of 4G LTE is analyzed according to the service change trend, service demand peak value and tidal law of 4G LTE, and the service demand for network resources of 5G NR is analyzed according to the service change trend, service demand peak value and tidal law of 5G NR. The service demand for network resources of 4G LTE and the service demand for network resources of 5G NR can provide a prediction basis for resource scheduling and enhance the foresight of resource allocation.

[0098] As an optional implementation, first, the average resource demand of the future reference period is estimated based on the service change trend of the 4G LTE, such as the monthly or annual growth rate; then, the service demand peak of the 4G LTE is identified, the highest load point in a specific event or time period is analyzed, and the maximum resource reserve required to cope with the peak is calculated; then, the resource allocation is refined in the fluctuation of different time periods, such as increasing resources in peak hours and reducing resources in low hours, in combination with the tide law of the 4G LTE, such as daily or weekly periodic fluctuations; finally, the specific demand of the 4G LTE service for PRB, bandwidth and other network resources in different scenarios is quantified by combining the prediction results of the service change trend, the service demand peak and the tide law, and the specific demand is converted into executable resource scheduling parameters, so as to obtain the demand of the 4G LTE service for network resources. The way of obtaining the demand of the 5G NR service for network resources is similar to that of obtaining the demand of the 4G LTE service for network resources, and details are not repeated here.

[0099] S302, the service change trend and the demand of the service for network resources of the first mode and the service change trend and the demand of the service for network resources of the second mode are taken as the service prediction results.

[0100] In this embodiment, the service change trend of the 4G LTE, the demand of the 4G LTE service for network resources, the service change trend of the 5G NR and the demand of the 5G NR service for network resources are taken as the service prediction results.

[0101] For the complex scenario of coexistence and mutual influence of 4G LTE and 5G NR services in the DSS network, by mining historical multi-dimensional data, not only the service tide law of each mode can be predicted, but also the competitive demand trend of 4G LTE and 5G NR services for resources can be analyzed, which provides a forward-looking decision basis for subsequent multi-dimensional resource coordination, which is the premise of realizing accurate pre-allocation of resources.

[0102] By accurately predicting the service change trend and the demand of the service for network resources of different modes through a pre-trained machine learning model, a forward-looking and intelligent decision basis is provided for the dynamic spectrum sharing system, and adaptive and efficient allocation of spectrum resources between different networks is realized, which maximizes the utilization efficiency of the overall spectrum resources while ensuring the user experience of the dual-network.

[0103] On the basis of the above-mentioned embodiments, the embodiment of the present application provides a dynamic spectrum resource coordination method. In the dynamic spectrum resource coordination method provided by the embodiment, S107 includes the following steps:

[0104] S401, according to the service prediction result, the proportion of the dynamic spectrum resource in the mixed networking is dynamically configured as the MBSFN subframe to change the resource proportion of the first mode network and the second mode network in the time domain, and the collaborative adjustment is completed.

[0105] In the embodiment, the implementation scheme of the time domain collaborative adjustment is as follows: the proportion of the MBSFN subframe is dynamically configured according to the service prediction result.

[0106] The principle of the time domain collaborative adjustment is as follows: under the DSS network, by configuring part of the subframes of the 4G LTE as the MBSFN subframe, the 4G LTE does not send the reference signal and does not occupy the PRB resource in the corresponding time domain, that is, all the network resources are temporarily exclusively allocated to the 5G NR in the corresponding time domain, so that the 5G NR realizes the high resource proportion, and the experience of the 5G NR user is improved. Under the 4G LTE single frame, at most 6 MBSFN subframes can be configured, which is equivalent to that the 5G NR can exclusively occupy 60% of the network resources at most, and the remaining 40% of the resources are still shared and allocated by the DSS.

[0107] The configuration of the subframes 1 to 9 in the MBSFN subframe is as follows: the subframes 0 and 5 can be used for transmitting the synchronization signal and the paging signal; the subframes 4 and 9 are used for transmitting the paging signal, and the subframes 0, 5, 4 and 9 are not allocated to the MBSFN.

[0108] In the MBSFN subframe, the 4G LTE control channel occupies the left part of the time domain symbol resource, and the remaining time domain symbol resource on the right is the area available for the 5G NR and without the interference of the 4G LTE neighbor.

[0109] By dynamically configuring the proportion of the MBSFN subframe, the resource is “borrowed” for the 5G NR in the peak period of the 5G NR service, and is returned to the 4G LTE after the peak, so that the “time multiplexing” of the resource is realized.

[0110] S402, according to the service prediction result and the preset threshold condition, part of the frequency domain resource is switched from the dynamic sharing state in the dynamic spectrum resource to the second mode network exclusive state, and the remaining frequency domain resource remains in the dynamic sharing state, and the collaborative adjustment is completed.

[0111] In this embodiment, optionally, the preset threshold condition is 20%, which is not limited here. The implementation scheme of the frequency domain coordinated adjustment is as follows: the 5G NR exclusive frequency domain resource is flexibly configured according to the service prediction result. For example, according to the service prediction result, it is identified that the 5G NR in the interference coordination cluster is in a service peak and the 4G LTE is in a service low estimation period, that is, the instantaneous service of the 5G NR cannot meet the demand of the network resource under the existing DSS resource scheduling, and then part of the frequency domain resource is set as the 5G NR exclusive resource, and the remaining frequency domain resource is kept in the dynamic sharing state, for example, in a 10MHz bandwidth spectrum, from the first state of the 10MHz bandwidth spectrum shared by the 4G LTE and the 5G NR, to the second state of the 2MHz spectrum exclusively occupied by the 5G NR, and the remaining 8MHz spectrum dynamically shared by the 4G LTE and the 5G NR. Conversely, when the load of the 4G LTE becomes high and the 5G NR has no higher network resource demand, the 4G LTE resource is recovered, the 5G NR resource is down-regulated, the additional spectrum occupied by the 5G NR is returned to the 4G LTE, and finally the 4G LTE and the 5G NR share the 10MHz bandwidth spectrum and return to the balanced sharing mode.

[0112] The principle of the frequency domain coordinated adjustment is as follows: under the initial DSS, for example, the 4G LTE and the 5G NR occupy the 10MHz bandwidth spectrum for dynamic spectrum sharing, according to the service prediction result, if the 4G LTE load is low and the service demand is small, and the 5G NR load is relatively high, the existing DSS resource scheduling cannot meet the service demand of the 5G NR, at this time, a part of the frequency domain resource can be set as the 5G NR exclusive state, by increasing the 5G NR exclusive spectrum, the 5G NR can have less interference and more available spectrum resource under the exclusive spectrum, and thus the user perceived rate of the 5G NR can be improved.

[0113] The trigger threshold of the frequency domain adjustment function can be flexibly configured according to different scenes and demands, for example, when the PRB utilization rate and the RRC user connection number of the 4G LTE are lower than the set threshold and the PRB utilization rate and the RRC user connection number of the 5G NR are higher than the set threshold, the 5G NR resource up-regulation is triggered.

[0114] When it is detected that the 5G NR is in a general service peak period, that is, the demand of the service of the 5G NR for the network resource does not exceed the preset threshold, the time domain coordinated adjustment is performed; when it is detected that the 5G NR is in an extremely high service peak period, that is, the demand of the service of the 5G NR for the network resource exceeds the preset threshold, the frequency domain coordinated adjustment is performed; in other cases, the time domain and the frequency domain coordinated adjustment are performed at the same time. Optionally, in the case that the demand of the service for the network resource is the PRB utilization rate, the preset threshold can be 60%, which is not limited here.

[0115] The concept of 5G NR exclusive spectrum is introduced. When the demand for 5G NR is very high and the demand for 4G LTE is very low, part of the shared spectrum is temporarily divided into 5G NR exclusive, and the rest continues to be shared. This not only increases the available resources of 5G NR, but more importantly, significantly reduces the co-channel interference of 5G NR in the exclusive frequency band, thereby greatly improving the user perceived rate.

[0116] Based on the accurate business prediction result, the resource proportion of different networks is flexibly and dynamically adjusted in the time domain and / or frequency domain, the real-time optimization allocation of spectrum resources is realized according to the change of business demand, so that the spectrum utilization efficiency and the overall network performance are significantly improved while the quality of service of multi-standard network is ensured.

[0117] On the basis of the above-mentioned embodiments, the embodiment of the present application provides a dynamic spectrum resource coordination method. In the dynamic spectrum resource coordination method provided by the embodiment, the step of dynamically configuring the proportion of multimedia broadcast multicast single frequency network MBSFN subframes in the dynamic spectrum resource in the mixed networking according to the business prediction result in S401 includes the following steps:

[0118] S501, according to the business prediction result, when it is detected that the current is a peak period of the second standard network business in the dynamic spectrum resource and a valley period of the first standard network, then part of the first standard network resource in the dynamic spectrum resource is released to the second standard network resource for use by increasing the number of multimedia broadcast multicast single frequency network subframes, and vice versa.

[0119] In the embodiment, if it is identified according to the business prediction result that 5G NR is in a business peak and 4G LTE is in a business low estimate period, and the instantaneous business of 5G NR cannot meet the demand for network resources under the existing DSS resource scheduling, then part of the 4G LTE subframe resource is released to 5G NR for use by increasing the number of configured MBSFN subframes, thereby improving the experience rate of 5G NR users in the peak period.

[0120] It also includes: if it is identified according to the business prediction result that the demand for 4G LTE business is high, and 5G NR has no higher demand, then the configuration proportion of MBSFN subframes is reduced, the resource of 4G LTE is improved, and the user experience of 4G LTE is ensured.

[0121] Based on the accurate business prediction result, the spectrum resources are realized in the bidirectional and dynamic flexible allocation between different networks, so as to intelligently allocate resources in the double-network business tidal effect, ensure that the resources are always preferentially served to the side with higher demand, and maximize the overall utilization efficiency of spectrum resources while effectively ensuring the user experience.

[0122] On the basis of the above-mentioned embodiments, the application provides a dynamic spectrum resource coordination method. The dynamic spectrum resource coordination method provided by the embodiments comprises the following steps:

[0123] S601, obtaining interference data of an edge cell in the interference coordination cluster.

[0124] In the embodiments, the edge cell is a cell located at the periphery of the interference coordination cluster, the coverage area of which overlaps with that of other adjacent interference coordination clusters, and thus the cell is most likely to cause and suffer from inter-cluster co-channel interference. The interference data includes but is not limited to RSRP, SINR and throughput data.

[0125] S602, avoiding inter-cluster interference by reducing the transmission power of the cell-specific reference signal (CRS) of the first mode network, enabling preset resource element (RE) level rate matching or frequency selection scheduling according to the interference data of the edge cell in the interference coordination cluster.

[0126] In the embodiments, according to the interference data of the edge cell in the interference coordination cluster, the transmission power of the cell-specific reference signal (CRS) of the adjacent 4G LTE is reduced, and preset resource element (RE) level rate matching or frequency selection scheduling is enabled to avoid inter-cluster interference and implement accurate interference coordination, which can improve the signal quality of edge users and improve the overall network spectrum efficiency.

[0127] When it is detected that the NR cell of the edge cell of the interference coordination cluster is interfered by the surrounding LTE co-channel, and the interference noise ratio reaches -10 dB, the transmission power of the interference cell LTE is reduced by 3 dB through intelligent power control, so that the interference noise ratio is improved to -15 dB.

[0128] The following is a specific embodiment:

[0129] In a 900 MHz band DSS network deployed in a certain city, after applying the dynamic spectrum resource coordination provided by the embodiments, the average downlink rate of 5G NR is improved from 10.83 Mbps to 12.11 Mbps, with a gain of 11.8%, and the performance of 4G LTE service remains stable, which verifies the effectiveness and practicability of the embodiments.

[0130] Firstly, taking cell B as a target cell, taking 54 cells which are topologically adjacent and have high interference as interference cells as a reference, dynamically associating the interference cells and the target cell to obtain an interference collaborative cluster; secondly, collecting mixed network resource data and historical network resource data of the 54 cells in the interference collaborative cluster for 14 days, training and analyzing uplink PRB utilization, downlink PRB utilization, RRC user connection number and other data of 4G LTE and 5G NR to generate a service prediction result; finally, according to the service prediction result, performing time domain and / or frequency domain collaborative adjustment on dynamic spectrum resources in the mixed networking.

[0131] In the embodiment of the application, the preset threshold condition of the frequency domain adjustment function can be that when the PRB utilization of 4G LTE is lower than 25%, the RRC user connection number is lower than a first preset threshold, and the PRB utilization of 5G NR is higher than 60% and the RRC user connection number is higher than a second preset threshold, the 5G NR resource is triggered to be adjusted upward, that is, adjusted to the second state. Here, the preset threshold condition, the first preset threshold and the second preset threshold are not specifically limited. Through the comparison of network management key performance indicators (Key Performance Indicator, KPI), the average rate and other related indicators of 4G LTE remain stable before and after the resource adjustment function of the frequency domain is started in the embodiment of the application, while the average downlink rate of 5G NR is increased from 10.83 Mbps to 12.11 Mbps, an increase of 11.8%.

[0132] The system architecture is divided into a data collection layer, an intelligent analysis layer and a spectrum arrangement execution layer, and through closed-loop control, full-process automation from data collection to policy execution is realized. The data collection layer is used to collect basic working parameter data of 5G NR or 4G LTE, traffic data of 5G NR or 4G LTE and interference measurement data, and the traffic data can be PRB occupation number, user number and rate; the intelligent analysis layer is used to dynamically associate interference cells and target cells to obtain an interference collaborative cluster, obtain a service prediction result based on a pre-trained machine learning model, and perform time domain and / or frequency domain collaborative adjustment on dynamic spectrum resources in the mixed networking based on the service prediction result; and the spectrum arrangement execution layer is used to manage the interference collaborative cluster, allocate resources and control interference.

[0133] To realize the optimal matching of spectrum resources with service resources, the spectrum arrangement combines the dynamic generation of clusters, network load prediction, multi-dimensional cluster-level dynamic resource collaboration and adjustment, and intelligent scheduling and interference avoidance within the cluster to realize regional optimization of spectrum efficiency.

[0134] Figure 5 A structure diagram of a dynamic spectrum resource collaboration device provided in the embodiment of the application is shown in FIG. 1. Figure 5 As shown in FIG. 1, in the embodiment, the dynamic spectrum resource collaboration device comprises:

[0135] The first information acquisition module 701 is configured to acquire signal strength information and neighbor cell relations of a plurality of cells in the hybrid networking.

[0136] The target cell determination module 702 is configured to select one cell from the plurality of cells as a target cell.

[0137] The interference cell determination module 703 is configured to determine, according to the signal strength information and the neighbor cell relations of the plurality of cells, a cell that satisfies an association condition with the target cell as an interference cell from the plurality of cells.

[0138] The second information acquisition module 704 is configured to dynamically associate the interference cell and the target cell to obtain an interference coordination cluster.

[0139] The third information acquisition module 705 is configured to acquire hybrid network resource data and historical network resource data in the interference coordination cluster in real time.

[0140] The prediction module 706 is configured to perform traffic prediction processing according to the hybrid network resource data and the historical network resource data to obtain a service prediction result under a dynamic spectrum sharing network.

[0141] The adjustment module 707 is configured to perform time domain and / or frequency domain coordination adjustment on dynamic spectrum resources in the hybrid networking according to the service prediction result.

[0142] The dynamic spectrum resource coordination device provided in the embodiment can perform Figure 2 The technical scheme of the dynamic spectrum resource coordination method embodiment shown in the figure is similar to that of the dynamic spectrum resource coordination device embodiment shown in the figure in terms of implementation principle and technical effects, and will not be described here one by one. Figure 2 The technical scheme of the dynamic spectrum resource coordination method embodiment shown in the figure is similar to that of the dynamic spectrum resource coordination device embodiment shown in the figure in terms of implementation principle and technical effects, and will not be described here one by one.

[0143] Meanwhile, the dynamic spectrum resource coordination device provided in the present application further refines the dynamic spectrum resource coordination device on the basis of the dynamic spectrum resource coordination device provided in the previous embodiment.

[0144] Optionally, in the embodiment, the interference cell determination module 703 is further configured to:

[0145] determine a cell signal strength difference between each cell and the target cell according to the signal strength information of the plurality of cells, select a cell with a cell signal strength difference less than a preset strength threshold as a candidate cell from the plurality of cells, and select a candidate cell that has a neighbor cell association relation with the target cell from all candidate cells as the interference cell according to the neighbor cell relations.

[0146] Optionally, in the embodiment, the hybrid network resource data includes a real-time network load matrix and a real-time interference coefficient, the historical network resource data includes a historical network load matrix and historical traffic data, and the prediction module 706 is further configured to:

[0147] inputting the real-time network load matrix, the real-time interference coefficient, the historical network load matrix and the historical traffic data into the pre-trained machine learning model to perform traffic prediction processing, to obtain a service change trend and a service demand for network resources of the first standard under the dynamic spectrum sharing network, and a service change trend and a service demand for network resources of the second standard under the dynamic spectrum sharing network; and taking the service change trend and the service demand for network resources of the first standard and the service change trend and the service demand for network resources of the second standard as a traffic prediction result.

[0148] Optionally, in the embodiment, the adjusting module 707 is further configured to:

[0149] According to the traffic prediction result, the dynamic spectrum resources in the hybrid networking are configured by a dynamic configuration of a multimedia broadcast multicast single frequency network (MBSFN) subframe ratio, to change a resource proportion of the first standard network and the second standard network in the time domain, to complete the collaborative adjustment; and / or according to the traffic prediction result and a preset threshold condition, part of the frequency domain resources are switched from a dynamic sharing state in the dynamic spectrum resources to a second standard network exclusive state, and the remaining frequency domain resources remain in the dynamic sharing state, to complete the collaborative adjustment.

[0150] Optionally, in the embodiment, the adjusting module 707 is further configured to:

[0151] According to the traffic prediction result, when it is detected that the current is a second standard network service peak in the dynamic spectrum resources and a first standard network valley period, then part of the first standard network resources in the dynamic spectrum resources are released to the second standard network resource for use by increasing the number of multimedia broadcast multicast single frequency network subframes, and vice versa.

[0152] Optionally, in the embodiment, the adjusting module 707 is further configured to:

[0153] Obtain interference data of an edge cell in the interference collaborative cluster; and according to the interference data, implement cluster interference avoidance by reducing a cell-specific reference signal (CRS) transmission power of the first standard network, enabling a preset resource element level rate matching or frequency selection scheduling.

[0154] Figure 6 A structural schematic diagram of an electronic device is provided for the embodiments of the present application. The electronic device is intended for various electronic devices that can perform the dynamic spectrum resource collaborative method, such as microcomputers, single-chip microcomputers and other suitable computers. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0155] As Figure 6As shown, the electronic device includes at least one processor 801 and a memory 802. The electronic device also includes a communication component 803. The processor 801, the memory 802, and the communication component 803 are connected through a bus 804.

[0156] In the implementation process, the at least one processor 801 executes the computer-executable instructions stored in the memory 802, so that the at least one processor 801 performs the dynamic spectrum resource coordination method as executed by the electronic device side.

[0157] The implementation process of the processor 801 can refer to the above-mentioned dynamic spectrum resource coordination method embodiments, which have similar implementation principles and technical effects, and will not be described here.

[0158] In the above embodiments, it should be understood that the processor 801 can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), etc. The general-purpose processor 801 can be a microprocessor or any conventional processor. The steps of the method disclosed in the application can be directly embodied as execution completed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

[0159] The memory 802 can include a high-speed RAM memory, and can also include a non-volatile storage NVM, such as at least one disk memory.

[0160] The bus 804 can be an industry standard architecture (ISA) bus, a peripheral component (PCI) bus, or an extended industry standard architecture (EISA) bus. The bus 804 can be divided into an address bus, a data bus, and a control bus. For the convenience of representation, the bus 804 in the drawings of the present application does not limit to only one bus or one type of bus.

[0161] The functions implemented by the electronic device and the host device are described above, and the solutions provided by the embodiments of the present application are introduced. It can be understood that, in order to implement the above functions, the electronic device or the host device comprises a hardware structure and / or a software module corresponding to the execution of each function. In combination with the units and algorithm steps of the examples described in the embodiments of the present application, the embodiments of the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is implemented in hardware or computer software driven hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the technical solutions of the embodiments of the present application.

[0162] The present application also provides a computer readable storage medium, which stores computer execution instructions, and when a processor executes the computer execution instructions, the dynamic spectrum resource coordination method is realized.

[0163] The above computer readable storage medium can be implemented by any type of volatile, non-volatile storage device or their combination, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0164] An exemplary readable storage medium is coupled to the processor, so that the processor can read information from the readable storage medium, and can write information to the readable storage medium. The readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). The processor and the readable storage medium can also exist as discrete components in the electronic device or the host device.

[0165] The memory 802 is a non-transitory computer readable storage medium provided by the present application. The non-transitory computer readable storage medium of the present application stores computer instructions for causing a computer to execute the dynamic spectrum resource coordination method provided by the present application.

[0166] The memory 802 as a non-transitory computer readable storage medium can be used to store non-transitory software programs, non-transitory computer executable programs and modules. The processor 801 executes various functional applications and data processing by running the non-transitory software programs, instructions and modules stored in the memory 802, that is, realizes the dynamic spectrum resource coordination method in the above method embodiments.

[0167] Meanwhile, the embodiment also provides a computer program product comprising a computer program, which is used for implementing the dynamic spectrum resource coordination method of the above embodiment when executed by a processor.

[0168] It should be noted that, for the above-mentioned method embodiments, in order to simply describe, they are all expressed as a series of action combinations, but those skilled in the art should know that the present application is not limited to the action sequence described, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0169] It should be further noted that, although each step in the flowchart is displayed in sequence according to the arrow, these steps are not necessarily executed in sequence according to the arrow. Unless otherwise stated in this article, the execution of these steps has no strict sequence limitation, and these steps can be executed in other sequences. Moreover, at least part of the steps in the flowchart can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these sub-steps or stages is not necessarily sequential, but can be executed in rotation or alternation with other steps or sub-steps or stages of other steps.

[0170] It should be understood that the above-mentioned device embodiments are only schematic, and the device of the present application can also be realized by other ways. For example, the division of units / modules in the above-mentioned embodiments is only a logical function division, and another division way can be used in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0171] In addition, unless otherwise specified, each functional unit / module in each embodiment of the present application can be integrated in one unit / module, or each unit / module can exist physically, or two or more units / modules can be integrated together. The integrated unit / module can be realized in the form of hardware or in the form of software program module.

[0172] In the above-mentioned embodiments, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments. Each technical feature of the above-mentioned embodiments can be combined arbitrarily, and in order to make the description simple, not all possible combinations of each technical feature in the above-mentioned embodiments are described, however, as long as the combination of these technical features does not exist contradictory, it should be considered as the scope of the present application.

[0173] Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0174] It is to be understood that the application is not limited to the precise construction herein disclosed and shown in the drawings, and that various modifications and changes can be made by those skilled in the art without departing from the scope of the application. The scope of the application is limited only by the claims that follow.

Claims

1. A dynamic spectrum resource coordination method, characterized in that, include: Obtain signal strength information and neighbor cell relationships of multiple cells in a hybrid network; Select one cell from the plurality of cells as the target cell; Based on the signal strength information of the plurality of cells and the neighbor cell relationship, cells that meet the association conditions with the target cell are identified as interfering cells among the plurality of cells; The interfering cell and the target cell are dynamically associated to obtain an interfering cooperative cluster; Real-time acquisition of hybrid network resource data and historical network resource data within the interference coordination cluster; Based on the hybrid network resource data and the historical network resource data, traffic prediction processing is performed to obtain the service prediction results under the dynamic spectrum sharing network. Based on the service forecast results, the dynamic spectrum resources in the hybrid network are adjusted in a coordinated manner in the time domain and / or frequency domain.

2. The method according to claim 1, characterized in that, The step of determining, based on the signal strength information of the plurality of cells and the neighbor cell relationship, a cell that meets the association condition with the target cell as an interfering cell includes: Based on the signal strength information of the multiple cells, determine the cell signal strength difference between each cell and the target cell; Cells whose signal strength difference is less than a preset strength threshold among the plurality of cells are selected as candidate cells; Based on the neighbor cell relationship, candidate cells that have a neighbor cell relationship with the target cell are selected as interfering cells from all candidate cells.

3. The method according to claim 1, characterized in that, The hybrid network resource data includes a real-time network load matrix and a real-time interference coefficient, and the historical network resource data includes a historical network load matrix and historical traffic data. Accordingly, the step of performing traffic prediction processing based on the hybrid network resource data and the historical network resource data to obtain the service prediction result under the dynamic spectrum sharing network includes: The real-time network load matrix, the real-time interference coefficient, the historical network load matrix, and the historical traffic data are input into a pre-trained machine learning model for traffic prediction processing to obtain the service change trend and service demand for network resources of the first standard under the dynamic spectrum sharing network, as well as the service change trend and service demand for network resources of the second standard under the dynamic spectrum sharing network. The service change trends and network resource requirements of the first standard, as well as the service change trends and network resource requirements of the second standard, are used as the service forecast results.

4. The method according to claim 1, characterized in that, The step of coordinating time-domain and / or frequency-domain adjustments to dynamic spectrum resources in the hybrid network based on the service prediction results includes: Based on the service prediction results, the dynamic spectrum resources in the hybrid network are dynamically configured by adjusting the proportion of MBSFN subframes to change the resource ratio of the first-mode network and the second-mode network in the time domain, thereby completing the coordinated adjustment. And / or, based on the service prediction results and preset threshold conditions, some frequency domain resources are switched from the dynamic sharing state in the dynamic spectrum resources to the second-standard network exclusive state, while the remaining frequency domain resources remain in the dynamic sharing state, thus completing the coordinated adjustment.

5. The method according to claim 4, characterized in that, The step of dynamically configuring the proportion of MBSFN subframes in the hybrid network based on the service prediction results includes: Based on the service prediction results, when it is detected that the current period is a peak time for the second-mode network service and a low time for the first-mode network in the dynamic spectrum resources, the number of subframes in the multimedia broadcast multicast single-frequency network is increased to release some of the first-mode network resources in the dynamic spectrum resources to the second-mode network resources. Conversely, the number of subframes in the multimedia broadcast multicast single-frequency network is reduced.

6. The method according to any one of claims 1 to 5, characterized in that, The step of coordinating time-domain and / or frequency-domain adjustments to dynamic spectrum resources in the hybrid network based on the service prediction results also includes: Obtain the interference data of the edge cells in the interference coordination cluster; Inter-cluster interference avoidance is achieved by reducing the transmission power of the cell-specific reference signal (CRS) of the first-mode network, enabling preset resource element-level rate matching, or frequency-selective scheduling based on the interfered data.

7. A dynamic spectrum resource coordination device, characterized in that, include: The first information acquisition module is used to acquire signal strength information and neighbor cell relationships of multiple cells in a hybrid network. The target cell determination module is used to select one cell from the plurality of cells as the target cell; The interfering cell determination module is used to determine, based on the signal strength information of the plurality of cells and the neighbor cell relationship, a cell that meets the association condition with the target cell as an interfering cell among the plurality of cells; The second information acquisition module is used to dynamically associate the interfering cell and the target cell to obtain an interfering cooperative cluster; The third information acquisition module is used to acquire hybrid network resource data and historical network resource data within the interference cooperative cluster in real time. The prediction module is used to perform traffic prediction processing based on the hybrid network resource data and the historical network resource data to obtain the service prediction results under the dynamic spectrum sharing network. The adjustment module is used to perform time-domain and / or frequency-domain coordinated adjustment of dynamic spectrum resources in the hybrid network based on the service prediction results.

8. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the dynamic spectrum resource coordination method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the dynamic spectrum resource coordination method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, is used to implement the dynamic spectrum resource coordination method as described in any one of claims 1 to 6.

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