Information processing method, device, equipment and computer readable storage medium

Abstract

The embodiment of the present application provides a method, apparatus, device and computer-readable storage medium for information processing, the method is applied to a first network device, and is characterized by comprising: receiving information related to a second network device; determining a first resource configuration corresponding to a coverage category related to the second network device based on the information; and sending the first resource configuration to the second network device. The method obtains the first resource configuration through prediction and calculation analysis based on the information, realizes dynamic configuration of different coverage categories, saves energy consumption, and improves system capacity and performance.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology. Specifically, the present application relates to an information processing method, device, equipment and computer-readable storage medium. Background Art

[0002] As an important scenario of 5G (5th generation mobile networks), MIoT (Massive Internet of Things) relies on the powerful connection capabilities of 5G to achieve the interconnection of all things through integration with vertical industries, and expands the communication between people to the full-scenario connection between people and things, and things and things. For the MIoT scenario, 3GPP defines a large-scale connection requirement of 1 million connections per square kilometer. In addition, MIoT business applications also have high requirements for low cost, low power consumption and deep coverage.

[0003] To support large-scale connections, 3GPP proposed two cellular IoT protocol standards: NB-IoT (Narrow Band IOT) and eMTC (enhanced machine type communication). In the protocol, 3GPP introduced the concept of CL (Coverage Level), such as Figure 1 As shown, by defining the signal strength threshold (rsrpThreshold) to divide the CL, and defining differentiated resource configurations for each coverage level, the coverage, capacity and management requirements of a large number of terminals are achieved.

[0004] In the existing network, the division of IOT coverage levels and parameters are basically manually configured in a unified manner. In actual network operation, specific problems are analyzed and manual parameter adjustments are made after they occur. This manual, semi-static adjustment method is not only time-consuming and labor-intensive, but also very likely to cause mismatches between parameters and the actual network environment.

[0005] (1) Fixed CL partitioning cannot adapt to the time-varying distribution of IoT terminals, resulting in access congestion and resource waste

[0006] CL division is mainly achieved by defining the RSRP (Reference Signal Receiving Power) threshold. In actual networks, the RSRP threshold is generally determined based on the maximum and deepest coverage of the cell. However, because IoT services are mostly sent infrequently, the distribution of IoT terminals that actually have service transmission and reception needs in the cell has time-varying characteristics. Figure 2 and Figure 3As shown in the figure, for example, IoT terminals are evenly distributed during the day, but at night, most of the terminals sending IoT services are in a range with good signal strength. In this case, the fixed three CL divisions and fixed resource configuration will lead to insufficient resources for CL0, resulting in access congestion. At the same time, the resources reserved for CL1 and CL2 are wasted due to the small number of actual users, reducing resource utilization.

[0007] (2) Semi-static resource configuration cannot adapt to the time-varying distribution of IoT terminals, resulting in increased power consumption and reduced system capacity.

[0008] As mentioned above, the signal strength distribution of IoT terminals with real business transmission and reception needs in the cell has time-varying characteristics. The semi-static resource configuration based on CL cannot adapt to the time-varying characteristics of terminal distribution and may allocate a large number of repetitions, which not only wastes terminal power, but also causes unnecessary waste of resources, thereby reducing system capacity.

[0009] like Figure 4 As shown in the figure, in the morning time period, the actual valid terminals of CL0 in the area are UE1 / UE2; in the noon time period, the actual valid terminals of CL0 are UE1 / UE5; in the afternoon time period, the actual valid terminals of CL0 are UE1 / UE2. Among them, UE1 / UE5 have higher RSRP, and the repetition number is 1 to meet the transmission demand; UE2's RSRP is relatively low, and the repetition number is 2. In this case, if the semi-static repetition number 2 is configured, the repetition number of users UE1 and UE5 will be too high in the noon time period, and the resource occupation will increase.

[0010] In summary, the traditional methods of manual initial configuration or post-adjustment cannot adapt to the changing network environment and IoT service distribution in actual network operation. Summary of the invention

[0011] In view of the shortcomings of the existing methods, the present application proposes an information processing method, device, equipment and computer-readable storage medium to solve the problem of how to save energy consumption and improve system capacity and performance.

[0012] In a first aspect, a method for information processing is provided, which is applied to a first network device, and includes:

[0013] receiving information related to a second network device;

[0014] A first resource configuration corresponding to a coverage category related to the second network device is determined according to the information.

[0015] The first resource configuration is sent to the second network device.

[0016] Optionally, determining, according to the information, a first resource configuration corresponding to a coverage category related to the second network device includes:

[0017] Determine, according to the information, service distribution related information of the terminal user equipment included in the second network equipment corresponding to each coverage characteristic at the first time;

[0018] Predicting or calculating, based on the service distribution related information of the terminal user device at the first time, the service distribution related information of the terminal user device at a second time after the first time, and determining the service distribution related information of the terminal user device at the second time;

[0019] According to the service distribution related information of the terminal user equipment at the second time, a first resource configuration corresponding to the coverage category related to the second network equipment is determined.

[0020] Optionally, before determining, according to the information, information related to service distribution of the terminal user equipment corresponding to each coverage characteristic at the first time, the method further includes:

[0021] Receiving service information sent by an external server, the service information including location information of each terminal user device and feature information of each terminal user device; wherein the location information includes at least one of a location parameter of the terminal user device provided by the positioning server and a flight trajectory parameter provided by the positioning server, and the feature information includes at least one of a service cycle and a periodic reporting time;

[0022] Determine, according to the information, information related to service distribution of the terminal user equipment corresponding to each coverage characteristic at the first time, including:

[0023] According to the information and the service information, information related to service distribution of the terminal user equipment corresponding to each coverage characteristic at the first time is determined.

[0024] Optionally, the information includes at least one of measurement information of the second network device and configuration information of the second network device; the measurement information includes at least one of signal strength data, service data, and performance data; the configuration information includes a coverage category threshold configuration for coverage category division and at least one of resource configuration parameters corresponding to each coverage category, the coverage category threshold configuration is a coverage characteristic indicator value, and the coverage characteristic indicator value is used to divide the coverage area into different coverage categories.

[0025] Optionally, based on the information, determine the service distribution related information of the terminal user equipment corresponding to each coverage characteristic at the first time, including: determining the distribution information of the terminal user equipment that has services to be sent and needs to access the second network device at the first time based on the service data and service information; and determining the access capacity of the random access channel RACH corresponding to different configuration information based on the performance data and configuration information, the service distribution related information includes the distribution information and the access capacity of the RACH corresponding to the different configuration information.

[0026] Optionally, predicting or calculating, according to the service distribution related information of the terminal user device at the first time, service distribution related information of the terminal user device at a second time after the first time, and determining the service distribution related information of the terminal user device at the second time includes:

[0027] Inputting the service distribution related information of the terminal user equipment in N service cycles into a preset prediction model, predicting and calculating the service distribution related information of the terminal user equipment at a second time after the first time through the prediction model, and obtaining the time distribution of the capacity of the service corresponding to each coverage characteristic in the first cycle after N service cycles;

[0028] Among them, the first time includes N service cycles, the second time includes the first cycle, the service distribution related information of the terminal user equipment at the first time is used to characterize the distribution of the capacity of the services corresponding to each coverage characteristic in the N cycles over time, and the service distribution related information of the terminal user equipment at the second time is used to characterize the distribution of the capacity of the services corresponding to each coverage characteristic in the first cycle over time, and N is a positive integer.

[0029] Optionally, determining, according to the service distribution related information of the terminal user device at the second time, a first resource configuration corresponding to the coverage category related to the second network device includes:

[0030] Determine, according to the service distribution related information of the terminal user equipment at the second time, the coverage category thresholds corresponding to the respective coverage categories;

[0031] A first resource configuration corresponding to the coverage category related to the second network device is determined according to the service distribution related information of the terminal user device at the second time and the coverage category thresholds corresponding to the coverage categories respectively.

[0032] Optionally, determining a first resource configuration corresponding to a coverage category related to the second network device according to the service distribution related information of the terminal user device at the second time and the coverage category thresholds corresponding to each coverage category respectively includes:

[0033] Determine the number of transmission repetitions and the modulation and coding strategy MCS configuration of the resources of the terminal user equipment corresponding to each coverage category according to the coverage category thresholds corresponding to each coverage category, where the resources include at least one of the physical downlink control channel PDCCH, the physical downlink shared channel PDSCH, the physical uplink shared channel PUSCH, and the uplink control information UCI;

[0034] Determine the number of coverage categories and the number of terminal user devices corresponding to each coverage category according to the service distribution related information of the terminal user device at the second time and the coverage category thresholds corresponding to each coverage category;

[0035] According to the number of terminal user devices corresponding to each coverage category and the access capacity of the RACH corresponding to the configuration information of the second network device included in the information, the second resource configuration of the RACH corresponding to each coverage category is determined, the first resource configuration corresponding to the coverage category includes the coverage category threshold of the terminal user device corresponding to each coverage category, the number of transmission repetitions of the resource, the MCS configuration of the resource and the second resource configuration of the RACH corresponding to each coverage category, the second resource configuration of the RACH includes at least one of the number of transmission retransmissions of the random access preamble code, the number of RACH subcarriers, and the RACH period.

[0036] Optionally, when the number of coverage categories and the coverage category thresholds respectively corresponding to the coverage categories change, adjusting the number of transmission repetitions of the resources of the terminal user equipment respectively corresponding to the coverage categories and the modulation and coding strategy MCS configuration of the resources;

[0037] Or after determining the number of each coverage category and the coverage category threshold corresponding to each coverage category, adjust the number of transmission repetitions of the resources of the terminal user equipment corresponding to each coverage category and the modulation and coding strategy MCS configuration of the resources.

[0038] Optionally, adjusting the number of transmission repetitions of the resources of the terminal user equipment corresponding to each coverage category includes at least one of the following:

[0039] Adjusting the number of transmission repetitions of the PDCCH, the adjustment of the number of transmission repetitions of the PDCCH includes adjusting the number of transmission repetitions of at least one of the message msg2, the message msg3, and the message msg4 in the common search space, and adjusting the number of transmission repetitions of the dedicated search space;

[0040] Adjust the number of transmission repetitions of the PDSCH, where the adjustment of the number of transmission repetitions of the PDSCH includes at least one of the adjustment of the number of transmission repetitions of the PDSCH carrying the message msg2, the adjustment of the number of transmission repetitions of the PDSCH carrying the message msg4, and the adjustment of the number of transmission repetitions of the PDSCH carrying downlink signaling and data in the connected state;

[0041] Adjust the number of transmission repetitions of the PUSCH, where the adjustment of the number of transmission repetitions of the PUSCH includes at least one of the adjustment of the number of transmission repetitions of the PUSCH carrying the message msg3 and the adjustment of the number of transmission repetitions of the PUSCH carrying uplink signaling and data in the connected state;

[0042] The transmission repetition number of uplink control information UCI is adjusted, and the adjustment of the transmission repetition number of UCI includes at least one of the adjustment of the transmission repetition number of PUSCH carrying downlink transmission ACK and / or NACK and the adjustment of PUCCH carrying downlink transmission ACK and / or NACK.

[0043] Optionally, adjusting the MCS configuration of the resources of the terminal user equipment corresponding to each coverage category includes at least one of the following:

[0044] Adjust the MCS configuration of the PDSCH, where the adjustment of the MCS configuration of the PDSCH includes at least one of the following: adjustment of the MCS configuration of the PDSCH carrying the message msg2, adjustment of the MCS configuration of the PDSCH carrying the message msg4, and adjustment of the MCS configuration of the PDSCH carrying downlink signaling and data in a connected state;

[0045] The MCS configuration of the PUSCH is adjusted, and the adjustment of the MCS configuration of the PUSCH includes at least one of the adjustment of the MCS configuration of the PUSCH carrying the message msg3 and the adjustment of the MCS configuration of the PUSCH carrying uplink signaling and data in the connected state.

[0046] Optionally, receiving information sent by the second network device includes at least one of the following:

[0047] receiving information related to the second network device sent by the service management and orchestration SMO;

[0048] Receive information related to the second network device sent by a quasi real-time RAN intelligent controller Near-RT RIC, wherein the information related to the second network device is obtained by the Near-RT RIC from the second network device.

[0049] Optionally, sending the first resource configuration to the second network device includes one of the following:

[0050] Sending the first resource configuration to the second network device;

[0051] Sending the first resource configuration to the Near-RT RIC, where the Near-RT RIC sends the first resource configuration to the second network device;

[0052] The first resource configuration is sent to the second network device through the Near-RT RIC.

[0053] Optionally, the first network device is a non-real-time RAN intelligent controller Non-RT RIC or a quasi-real-time RAN intelligent controller Near-RT RIC.

[0054] In a second aspect, the present application provides an information processing device, applied to a first network device, including:

[0055] A first processing module, configured to receive information related to the second network device sent by the second network device;

[0056] A second processing module, configured to determine, based on the information, a first resource configuration corresponding to a coverage category associated with the second network device;

[0057] The third processing module is used to send the first resource configuration to the second network device.

[0058] In a third aspect, the present application provides an electronic device, including: a processor, a memory, and a bus;

[0059] A bus, used to connect the processor and memory;

[0060] A memory, used for storing operation instructions;

[0061] The processor is used to execute the information processing method of the first aspect of the present application by calling an operation instruction.

[0062] In a fourth aspect, the present application provides a computer-readable storage medium storing a computer program, which is used to execute the information processing method of the first aspect of the present application.

[0063] The technical solution provided in the embodiments of the present application has at least the following beneficial effects:

[0064] Based on the information, the first resource configuration is obtained through prediction and computational analysis, which realizes dynamic configuration of different coverage categories, saves energy consumption, and improves system capacity and performance.

[0065] Additional aspects and advantages of the present application will be partially given in the following description, which will become apparent from the following description, or will be understood through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in describing the embodiments of the present application are briefly introduced below.

[0067] Figure 1 It is a schematic diagram of 3GPP NB-IoT coverage level CL in the prior art;

[0068] Figure 2 It is a schematic diagram of the time-varying distribution of IoT terminals during the day in the prior art;

[0069] Figure 3 It is a schematic diagram of the time-varying distribution of IoT terminals at night in the prior art;

[0070] Figure 4 It is a schematic diagram of the time-varying characteristics of IoT terminal distribution in the prior art;

[0071] Figure 5 is a schematic diagram of the O-RAN logical architecture;

[0072] Figure 6 A flowchart of an information processing method provided in an embodiment of the present application;

[0073] Figure 7 A schematic diagram of the MassiveIoT intelligent dynamic optimization system provided in an embodiment of the present application;

[0074] Figure 8 A schematic diagram of capacity distribution corresponding to RSRP provided in an embodiment of the present application;

[0075] Fig. 9 A schematic diagram of an RSRP sliding window provided in an embodiment of the present application;

[0076] Fig.10 A schematic diagram of system capacity distribution provided in an embodiment of the present application;

[0077] Figure 11-a A schematic diagram of different RSRP thresholds provided in an embodiment of the present application;

[0078] Figure 11-b A schematic diagram of different RSRP thresholds provided in an embodiment of the present application;

[0079] Figure 11-c A schematic diagram of different RSRP thresholds provided in an embodiment of the present application;

[0080] Fig.12 A schematic diagram of RSRP distribution probability provided in an embodiment of the present application;

[0081] Fig.13 A schematic diagram of the minimum RSRP distribution of each coverage level provided in an embodiment of the present application;

[0082] Fig.14 A schematic diagram of calculating the number of transmission repetitions and MCS according to RSRP provided in an embodiment of the present application;

[0083] Fig.15A schematic diagram of the time-varying distribution of each CL capacity provided in an embodiment of the present application;

[0084] Figure 16-a A schematic diagram of a system framework corresponding to information processing provided in an embodiment of the present application;

[0085] Figure 16-b A schematic diagram of the principle flow of information processing provided by the embodiment of the present application;

[0086] Fig.17 A schematic diagram of the implementation process of information processing provided in the embodiment of the present application;

[0087] Figure 18-a A schematic diagram of a system framework corresponding to information processing provided in an embodiment of the present application;

[0088] Figure 18-b A schematic diagram of the principle flow of information processing provided by the embodiment of the present application;

[0089] Fig.19 A schematic diagram of the implementation process of information processing provided in the embodiment of the present application;

[0090] Figure 20-a A schematic diagram of a system framework corresponding to information processing provided in an embodiment of the present application;

[0091] Figure 20-b A schematic diagram of the principle flow of information processing provided by the embodiment of the present application;

[0092] Fig.21 A schematic diagram of the implementation process of information processing provided in the embodiment of the present application;

[0093] Figure 22-a A schematic diagram of a system framework corresponding to information processing provided in an embodiment of the present application;

[0094] Figure 22-b A schematic diagram of the principle flow of information processing provided by the embodiment of the present application;

[0095] Fig.23 A schematic diagram of the implementation process of information processing provided in the embodiment of the present application;

[0096] Figure 24-a A schematic diagram of a system framework corresponding to information processing provided in an embodiment of the present application;

[0097] Figure 24-b A schematic diagram of the principle flow of information processing provided by the embodiment of the present application;

[0098] Fig.25 A schematic diagram of the implementation process of information processing provided in the embodiment of the present application;

[0099] Fig.26 A schematic diagram of the structure of an information processing device provided in an embodiment of the present application;

[0100] Fig. 27 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0101] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be interpreted as limiting the present application.

[0102] The various operations, methods, steps, measures, and schemes discussed in this application may be alternated, modified, combined, or deleted. The various steps and schemes in this application may be combined; some steps in an embodiment of this application may also be combined into a new scheme, without requiring all the steps in the embodiment.

[0103] It will be understood by those skilled in the art that, unless expressly stated, the singular forms "one", "said", and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present application refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be an intermediate element. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0104] In order to better understand and illustrate the solutions of the embodiments of the present application, some technologies involved in the embodiments of the present application are briefly described below.

[0105] Coverage categories may include or be referred to as coverage levels, coverage domains, etc.

[0106] Coverage characteristics may include RSRP, SINR (Signal to Interference plus Noise Ratio), RSRQ (Reference Signal Receiving Quality) or other indicators that identify coverage categories. According to the current 3GPP protocol, NB-IoT supports a maximum of 3 coverage levels and eMTC supports a maximum of 4 coverage levels. The maximum coverage level may change in other wireless communication systems or future 3GPP protocols.

[0107] According to the current 3GPP protocol, different coverage levels are determined by defining RSRP (Reference Signal Receiving Power) thresholds. In future 3GPP protocols or in other wireless communication systems, the division of coverage categories may be determined by defining other threshold indicators, including SINR, RSRQ or other indicators that identify coverage differences. In this case, RSRP is used as an example.

[0108] The resource configuration for each coverage level (a set of parameters affected by the RSRP threshold) includes:

[0109] Random access resource configuration: includes the time domain / frequency domain resources for sending the preamble (msg1) and the number of preamble repetitions.

[0110] The time domain resources include time domain periods;

[0111] Frequency domain resources include the number of subcarriers;

[0112] Preamble repetition count: represents the number of times a preamble transmission needs to be repeated;

[0113] Scheduling resource configuration: including the transmission repetition times and / or MCS (Modulation and Coding Scheme) configuration of the Physical Downlink Control CHannel (Physical Downlink Shared CHannel, PDSCH), the Physical Uplink Shared CHannel (Physical Uplink Shared CHannel, PUSCH), and the Physical Uplink Control CHannel (Physical Uplink Control CHannel, PUCCH).

[0114] Specifically, the IoT terminal can compare the measured signal strength (RSRP) with the RSRP threshold to determine the CL (Coverage Level) where it is located, and then initiate random access on the corresponding RACH (Random Access Channel) resource. The base station equipment selects the corresponding resource configuration according to the CL accessed by the UE. For example, for CLs with good signal strength, the transmission requirements can be met by not setting the number of repetitions or by a small number of repetitions, while ensuring a high data transmission rate; for CLs with poor signal strength, the coverage characteristics can be met by setting a larger number of repetitions.

[0115] The open radio access network O-RAN focuses on the needs of network intelligence, interface openness, software open source and hardware white box, aiming to promote the openness of wireless device interfaces, realize intelligent wireless networks by introducing new technologies such as artificial intelligence, and bring the openness of next-generation wireless communication networks to a new level.

[0116] According to the open radio access network O-RAN specification, the open radio access network O-RAN logical architecture is as follows Figure 5 The wireless side entities include Near-RT RIC, O-CU-CP, O-CU-UP, O-DU, and O-eNB.

[0117] The Service Management and Orchestration (SMO) entity provides a variety of management services and network management functions, such as RAN management, core network management, transport management, and end-to-end slice management.

[0118] The Non-Real Time RAN Intelligent Controller (Non-RTRIC) is a logical entity built into the SMO. It supports non-real-time control and optimization of RAN network elements and resources, AI / ML model establishment, reasoning and update, optimizes RAN through data analysis and AI / ML training / reasoning, and provides policy guidance and ML model management to the Near-Real Time RAN Intelligent Controller (Near-RT RIC) through the A1 interface.

[0119] The Near-RT RIC logical entity supports quasi-real-time control and optimization of RAN network elements and resources, which can include AI (Artificial Intelligence) / ML (Machine Learning) model training, reasoning and updating, as well as policy guidance. The Near-RT RIC provides network optimization instructions to the E2 node through the E2 interface.

[0120] E2 node: includes O-RAN control unit control plane (O-RAN-Control Unit-Control Plane, O-CU-CP), O-RAN control unit user plane (O-RAN-Control Unit-User Plane, O-CU-UP), O-RAN data unit (O-RAN-Data Unit, O-DU), O-eNB and other entities, among which O-CU-CP, O-CU-UP, O-DU are used for 5G NR access, and O-eNB is used for E-UTRA access. Compared with CU-CP, CU-UP and DU of non-O-RAN system, E2 node supports E2 interface.

[0121] O-eNB: eNB or ng-eNB that supports O-RAN architecture.

[0122] O-Cloud: O-RAN cloud computing platform.

[0123] External servers: servers of various application apps, etc., which can provide SMO with rich data.

[0124] The O-RAN architecture focuses on four interfaces:

[0125] A1: Located between Non-RT RIC and near-RT RIC, it supports policy management, enriched information, and ML model management services.

[0126] E2: Used to connect near-RT RIC and E2 nodes. An E2 node can only be connected to one near-RT RIC. The Near-RT RIC entity can collect quasi-real-time information (UE level or cell level) of the measurements of various functional entities of the wireless network through the E2 interface, and can also send control command words to the base station through the E2 interface. Ultimately, the E2 interface controls the behavior of the base station.

[0127] O1: Interface between O-RAN managed entities (near-RT RIC, E2 node) and O-RAN management entity (SMO), supporting operations and management, including network fault / configuration / billing / performance / security (Fault, Configuration, Accounting, Performance, Security, FCAPS) management, physical network function (PNF) software management and file management.

[0128] O2: The O2 interface connects SMO and O-Cloud to support O-RAN virtualization.

[0129] Open fronthaul M-plane interface: located between the SMO and the O-RAN radio unit (O-RAN-Radio Unit, O-RU) to support O-RU management.

[0130] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0131] The present application provides an information processing method, which is applied to a first network device. The flowchart of the method is as follows: Figure 6 As shown, the method includes:

[0132] Step S101: receiving information related to a second network device.

[0133] Step S102: Determine, according to the information, a first resource configuration corresponding to a coverage category related to the second network device.

[0134] Step S103: Send the first resource configuration to the second network device.

[0135] Optionally, determining, according to the information, a first resource configuration corresponding to a coverage category related to the second network device includes:

[0136] Determine, according to the information, service distribution related information of the terminal user equipment included in the second network equipment corresponding to each coverage characteristic at the first time;

[0137] Predicting or calculating, based on the service distribution related information of the terminal user device at the first time, the service distribution related information of the terminal user device at a second time after the first time, and determining the service distribution related information of the terminal user device at the second time;

[0138] According to the service distribution related information of the terminal user equipment at the second time, a first resource configuration corresponding to the coverage category related to the second network equipment is determined.

[0139] Optionally, the coverage category is a coverage area with different location information; the coverage characteristic is a reference quantity, the reference quantity reflects a feature of the coverage location, and the reference quantity is used to distinguish different coverage categories.

[0140] Optionally, the coverage category includes coverage level, coverage domain, etc.; the coverage characteristics include reference signal received power RSRP, signal to interference plus noise ratio SINR, reference signal received quality RSRQ, and other indicators identifying the coverage category, etc.

[0141] Optionally, the service distribution related information may include the time distribution of the number of terminal connections under the coverage characteristics, the distribution of service delay performance under the coverage characteristics, the distribution of service throughput capacity under the coverage characteristics, the distribution of service location information under the coverage characteristics, the periodic distribution characteristics of service occurrence under the coverage characteristics, and the service capacity performance benchmark under the coverage characteristics. The capacity performance benchmark is the access capacity of the corresponding random access channel RACH under various configuration information. In this application, the time distribution of the number of terminal connections under the coverage characteristics and the service capacity performance benchmark are used as examples for explanation.

[0142] Alternatively, if Figure 7 As shown, the MassiveIoT intelligent dynamic optimization system includes a computing and control unit 101, a network device 102, an external server 103 and an IoT terminal 104. The computing and control unit 101 is mainly responsible for data analysis and dynamic configuration, judgment, and control operations; the computing and control unit 101 is a first network device. The network device 102 can be a conventional 4G base station device, a 5G base station device, an enhanced 4G / 5G base station, such as O-eNB, O-CU, O-DU based on the O-RAN architecture, or a subsequent network device, such as a 6G network device; the second network device includes the network device 102. The external server 103 can provide auxiliary information, and the external server 103 can be a positioning server, a vertical industry service server, etc. The IoT terminal 104 can refer to a terminal that supports the services of the Internet of Things, such as a meter reading terminal, a positioning terminal, a temperature or humidity sensor node, etc.; the second network device also includes a terminal user device, and the terminal user device is the IoT terminal 104.

[0143] Optionally, the computing and control unit 101 may be located in a newly added entity or in an existing entity, such as the network device 102, a RIC entity under the O-RAN architecture, etc.

[0144] Optionally, before determining, according to the information, information related to service distribution of the terminal user equipment corresponding to each coverage characteristic at the first time, the method further includes:

[0145] Receiving service information sent by an external server, the service information including location information of each terminal user device and feature information of each terminal user device; wherein the location information includes at least one of a location parameter of the terminal user device provided by the positioning server and a flight trajectory parameter provided by the positioning server, and the feature information includes at least one of a service cycle and a periodic reporting time;

[0146] Determine, according to the information, information related to service distribution of the terminal user equipment corresponding to each coverage characteristic at the first time, including:

[0147] According to the information and the service information, information related to service distribution of the terminal user equipment corresponding to each coverage characteristic at the first time is determined.

[0148] Optionally, the information includes at least one of measurement information of the second network device and configuration information of the second network device; the measurement information includes at least one of signal strength data, service data, and performance data; the configuration information includes a coverage category threshold configuration for coverage category division and at least one of resource configuration parameters corresponding to each coverage category, the coverage category threshold configuration is a coverage characteristic indicator value, and the coverage characteristic indicator value is used to divide the coverage area into different coverage categories.

[0149] Optionally, the coverage category threshold configuration includes RSRP, SINR, RSRQ and other indicators identifying the coverage category.

[0150] Optionally, based on the information, determine the service distribution related information of the terminal user equipment corresponding to each coverage characteristic at the first time, including: determining the distribution information of the terminal user equipment that has services to be sent and needs to access the second network device at the first time based on the service data and service information; and determining the access capacity of the random access channel RACH corresponding to different configuration information based on the performance data and configuration information, the service distribution related information includes the distribution information and the access capacity of the RACH corresponding to the different configuration information.

[0151] Optionally, predicting or calculating, according to the service distribution related information of the terminal user device at the first time, service distribution related information of the terminal user device at a second time after the first time, and determining the service distribution related information of the terminal user device at the second time includes:

[0152] Inputting the service distribution related information of the terminal user equipment in N service cycles into a preset prediction model, predicting the service distribution related information of the terminal user equipment at a second time after the first time through the prediction model, and obtaining the time distribution of the capacity of the service corresponding to each coverage characteristic in the first cycle after N service cycles;

[0153] Among them, the first time includes N service cycles, the second time includes the first cycle, the service distribution related information of the terminal user equipment at the first time is used to characterize the distribution of the capacity of the services corresponding to each coverage characteristic in the N cycles over time, and the service distribution related information of the terminal user equipment at the second time is used to characterize the distribution of the capacity of the services corresponding to each coverage characteristic in the first cycle over time, and N is a positive integer.

[0154] Optionally, determining, according to the service distribution related information of the terminal user device at the second time, a first resource configuration corresponding to the coverage category related to the second network device includes:

[0155] Determine, according to the service distribution related information of the terminal user equipment at the second time, the coverage category thresholds corresponding to the respective coverage categories;

[0156] A first resource configuration corresponding to the coverage category related to the second network device is determined according to the service distribution related information of the terminal user device at the second time and the coverage category thresholds corresponding to the coverage categories respectively.

[0157] Optionally, determining a first resource configuration corresponding to a coverage category related to the second network device according to the service distribution related information of the terminal user device at the second time and the coverage category thresholds corresponding to each coverage category respectively includes:

[0158] Determine the number of transmission repetitions and the modulation and coding strategy MCS configuration of the resources of the terminal user equipment corresponding to each coverage category according to the coverage category thresholds corresponding to each coverage category, where the resources include at least one of the physical downlink control channel PDCCH, the physical downlink shared channel PDSCH, the physical uplink shared channel PUSCH, and the uplink control information UCI;

[0159] Determine the number of coverage categories and the number of terminal user devices corresponding to each coverage category according to the service distribution related information of the terminal user device at the second time and the coverage category thresholds corresponding to each coverage category;

[0160] According to the number of terminal user devices corresponding to each coverage category and the access capacity of the RACH corresponding to the configuration information of the second network device included in the information, the second resource configuration of the RACH corresponding to each coverage category is determined, the first resource configuration corresponding to the coverage category includes the coverage category threshold of the terminal user device corresponding to each coverage category, the number of transmission repetitions of the resource, the MCS configuration of the resource and the second resource configuration of the RACH corresponding to each coverage category, the second resource configuration of the RACH includes at least one of the number of transmission retransmissions of the random access preamble code, the number of RACH subcarriers, and the RACH period.

[0161] Optionally, when the number of coverage categories and the coverage category thresholds respectively corresponding to the coverage categories change, adjusting the number of transmission repetitions of the resources of the terminal user equipment respectively corresponding to the coverage categories and the modulation and coding strategy MCS configuration of the resources;

[0162] Or after determining the number of each coverage category and the coverage category threshold corresponding to each coverage category, adjust the number of transmission repetitions of the resources of the terminal user equipment corresponding to each coverage category and the modulation and coding strategy MCS configuration of the resources.

[0163] Optionally, adjusting the number of transmission repetitions of the resources of the terminal user equipment corresponding to each coverage category includes at least one of the following:

[0164] Adjusting the number of transmission repetitions of the PDCCH, the adjustment of the number of transmission repetitions of the PDCCH includes adjusting the number of transmission repetitions of at least one of the message msg2, the message msg3, and the message msg4 in the common search space, and adjusting the number of transmission repetitions of the dedicated search space;

[0165] Adjust the number of transmission repetitions of the PDSCH, where the adjustment of the number of transmission repetitions of the PDSCH includes at least one of the adjustment of the number of transmission repetitions of the PDSCH carrying the message msg2, the adjustment of the number of transmission repetitions of the PDSCH carrying the message msg4, and the adjustment of the number of transmission repetitions of the PDSCH carrying downlink signaling and data in the connected state;

[0166] The number of transmission repetitions of the PUSCH is adjusted, and the adjustment of the number of transmission repetitions of the PUSCH includes at least one of the adjustment of the number of transmission repetitions of the PUSCH carrying the message msg3 and the adjustment of the number of transmission repetitions of the PUSCH carrying uplink signaling and data in the connected state.

[0167] The transmission repetition number of uplink control information UCI is adjusted, and the adjustment of the transmission repetition number of UCI includes at least one of the adjustment of the transmission repetition number of PUSCH carrying downlink transmission ACK and / or NACK and the adjustment of PUCCH carrying downlink transmission ACK and / or NACK.

[0168] Optionally, adjusting the MCS configuration of the resources of the terminal user equipment corresponding to each coverage category includes at least one of the following:

[0169] Adjust the MCS configuration of the PDSCH, where the adjustment of the MCS configuration of the PDSCH includes at least one of the following: adjustment of the MCS configuration of the PDSCH carrying the message msg2, adjustment of the MCS configuration of the PDSCH carrying the message msg4, and adjustment of the MCS configuration of the PDSCH carrying downlink signaling and data in a connected state;

[0170] The MCS configuration of the PUSCH is adjusted, and the adjustment of the MCS configuration of the PUSCH includes at least one of the adjustment of the MCS configuration of the PUSCH carrying the message msg3 and the adjustment of the MCS configuration of the PUSCH carrying uplink signaling and data in the connected state.

[0171] Optionally, receiving information sent by the second network device includes at least one of the following:

[0172] receiving information related to the second network device sent by the service management and orchestration SMO;

[0173] Receive information related to the second network device sent by a quasi real-time RAN intelligent controller Near-RT RIC, wherein the information related to the second network device is obtained by the Near-RT RIC from the second network device.

[0174] Optionally, sending the first resource configuration to the second network device includes one of the following:

[0175] Sending the first resource configuration to the second network device;

[0176] Sending the first resource configuration to the Near-RT RIC, where the Near-RT RIC sends the first resource configuration to the second network device;

[0177] The first resource configuration is sent to the second network device through the Near-RT RIC.

[0178] Optionally, the first network device is a non-real-time RAN intelligent controller Non-RT RIC or a quasi-real-time RAN intelligent controller Near-RT RIC.

[0179] The technical solution provided in the embodiments of the present application has at least the following beneficial effects:

[0180] The service distribution related information of the terminal user equipment at a second time after the first time is predicted or calculated, so as to realize the dynamic configuration of different coverage levels in the cell, save energy consumption, and improve the system capacity and performance.

[0181] In order to explain the method provided by the embodiment of the present application in more detail, the scheme of the present application will be comprehensively and thoroughly introduced through multiple optional embodiments below:

[0182] Optional embodiment 1

[0183] Another information processing method is provided in an embodiment of the present application, which is applied to a computing and control unit. The method includes:

[0184] Step 1: The network device is responsible for collecting data and reporting it to the computing and control unit.

[0185] Optionally, the collected data is mainly conventional measurement information and configuration information of the network device.

[0186] Among them, conventional measurement information includes: signal strength data, service data and performance data.

[0187] Signal strength data: Signal strength parameters reported by the UE, such as measured RSRP information.

[0188] Service data: The cache changes of each UE counted by the network equipment, such as uplink cache information and downlink cache information.

[0189] Performance data: Access performance data for each coverage level counted by network equipment, including the number of random access process messages successfully received during the statistical period, the number of preambles (Msg1) and the number of contention resolutions (Msg4).

[0190] The configuration information includes RSRP threshold configuration for coverage level division and resource configuration parameters corresponding to each coverage level.

[0191] The resource configuration parameters corresponding to each coverage level include: PRACH (Physical Random Access Channel) resource configuration parameters and scheduling resource configuration parameters; PRACH resource configuration parameters include PRACH period, number of frequency domain subcarriers, etc.; scheduling resource configuration parameters include the number of transmission repetitions of PDCCH, PDSCH, PUSCH and MCS configuration parameters.

[0192] Step 2: The external server sends external data to the computing and control unit through an open interface.

[0193] Optionally, the external data mainly includes location information of the IoT terminal and characteristic information of the IoT service; the location information of the IoT terminal includes location parameters, flight trajectory parameters, etc. provided by the positioning server; the characteristic information of the IoT service includes the IoT service cycle, periodic reporting time, etc. provided by the industry server.

[0194] Step 3: The calculation and control unit analyzes the measurement data and external data to obtain the time-varying distribution of IoT services under each RSRP.

[0195] Optionally, the calculation and control unit analyzes the measurement data and external data, specifically including:

[0196] By using the reported cache information and IoT service information, the temporal distribution of IoT terminals that have services to be sent and need to access network devices (hereinafter referred to as "IoT service terminals") can be obtained.

[0197] Optionally, external location information may be used to further obtain the temporal distribution of IoT service terminals under each RSRP.

[0198] Using the reported access performance data and configuration information, the capacity performance benchmark of the system under different RACH configurations can be obtained.

[0199] Step 4: The calculation and control unit predicts the distribution of IoT service terminals in the next time period.

[0200] Optionally, step 4 uses the temporal distribution of IoT service terminals under each RSRP obtained in step 3 to predict the temporal distribution of IoT service terminals under each RSRP in the next time period.

[0201] Step 5: The calculation and control unit forms optimized wireless resources and transmission parameters based on the predicted distribution of IoT service terminals.

[0202] Optionally, step 5 uses the IoT service terminal distribution prediction under each RSRP obtained in step 4 to cluster and obtain RSRP thresholds of different coverage levels.

[0203] Optionally, based on the RSRP threshold, the number of repetitions and MCS (Modulation and Coding Scheme) configuration of PDCCH / PDSCH / PUSCH / UCI (Uplink Control Information) of the IoT terminal under each CL are calculated. Specifically, it includes:

[0204] The adjustment of the number of repetitions of the physical downlink control channel includes the adjustment of the number of repetitions of the msg2 message, msg3 message and msg4 message in the common search space, and the adjustment of the number of repetitions of the dedicated search space.

[0205] Adjustment of the number of repetitions and MCS configuration of the physical downlink shared channel, including adjustment of the number of repetitions and MCS configuration of the physical downlink shared channel carrying msg2 messages / msg4 messages, and carrying downlink signaling and data in the connected state.

[0206] The adjustment of the number of repetitions and the MCS configuration of the physical uplink shared channel includes the adjustment of the number of repetitions and the MCS configuration of the physical uplink shared channel that carries the MSG3 message and the uplink signaling and data in the connected state.

[0207] Optionally, the adjustment of the number of repetitions and MCS configuration can occur when the number and threshold of CL coverage levels change, and the number of repetitions and MCS values of each coverage level are adjusted; alternatively, after determining the number and threshold of CL coverage levels, the number of repetitions and MCS values of each coverage level can be adjusted with a finer time granularity.

[0208] Optionally, based on the obtained RSRP threshold and combined with the distribution of IoT service terminals under each RSRP, the number of IoT terminals in each coverage level is obtained.

[0209] Optionally, based on the number of IoT terminals in each coverage level and combined with the access performance capacity benchmark obtained in step 3, the optimal RACH (Random Access Channel) configuration parameters in each coverage level are obtained.

[0210] Step 6: The calculation and control unit sends the optimized radio resources and transmission parameters to the network device, and the network device updates the parameters and executes the configuration.

[0211] Optionally, for step 4, the calculation and control unit uses at least one of the artificial intelligence AI model and the machine learning ML model to predict the service distribution in the next time period, which involves training the AI model using historical data (such as data from the past year), and predicting the distribution of the capacity of IoT services over time under different RSRPs in the next cycle based on the distribution characteristics of the most recent N (>=1) cycles. For example, the predicted demand capacity distribution under the i-th RSRP in the next cycle T is formula (1), and formula (1) is as follows:

[0212] Capacity_RSRP i (t) (0 < t < T) Formula (1)

[0213] Optionally, for step 5, the calculation and control unit forms optimized radio resources and transmission parameters based on the predicted distribution of IoT service terminals, specifically including:

[0214] Step 5-1: Estimate the classification configuration parameters of CL in the system, including the RSRP threshold value and the number of CLs.

[0215] Based on the predicted distribution of IoT service terminals, the method of analysis of variance is used to obtain the number of coverage levels and the corresponding RSRP thresholds.

[0216] Step 1: According to the AI prediction result obtained in step 4, calculate the sum of capacity demands under the i-th RSRP in the prediction cycle T using formula (2), and formula (2) is as follows:

[0217] Capacity_RSRP i(T) = ∑ T Capacity_RSRP i (t) Formula (2)

[0218] Then we can get the distribution of demand capacity in period T. Figure 8 As shown, the X-axis is the RSRP value, and the Y-axis is the capacity corresponding to each RSRP within the prediction period T.

[0219] Step 2: If Fig. 9 As shown, the RSRP distribution range within the period T is divided into m regions using a sliding window. The number of sliding windows set depends on the maximum coverage level supported by the system. If the maximum coverage level supported by the system is M (for example, 3 in the current NBIOT system, and this case takes 3 as an example for analysis), M-1 sliding windows are used for division, and m=1~M. )

[0220] Step 3: Perform variance analysis on the m partitioned regions obtained by each sliding of the sliding window in step 2, such as Fig.10 As shown, considering the influence of capacity distribution, corresponding weighted processing is performed, and the weighted variance of the i-th area is formula (3), which is as follows:

[0221]

[0222] Among them, CL i : i-th coverage level, i = 1 to M; r i : RSRP value of IoT service terminal, the range is [RSRPmin, RSRPmax]; C(r): capacity function; N i : The total value of RSRP under the ith coverage level; M: The maximum coverage level supported by the system.

[0223] Step 4: Choose the value RSRP TH 1 &TH 2 &…&TH M-1 value, so that in this divided area, the discreteness variance corresponding to the system is minimized, as shown in formula (4), which represents the minimum value of the sum of M weighted variances.

[0224]

[0225] Step 5: Based on the RSRPTH obtained in step 4 1 &TH 2 &…&TH M-1 value to obtain the system configuration of the RSRP threshold.

[0226] Optionally, NB-IoT supports a maximum of 3 coverage levels.

[0227] The RSRP TH obtained according to Step 4 1 &TH 2 value can be divided into Figure 11-a , 11-b and the three cases shown in Figure 11-c:

[0228] As Figure 11-a shown, if the TH with the smallest variance 1 = RSRPmax, TH 2 = RSRPmin, it is considered that the RSRP distribution of all IoT terminals has the smallest variance without dividing the range. Therefore, there is no need to configure the RSRP threshold, and the cell has only 1 coverage level.

[0229] As Figure 11-b shown, if the TH with the smallest variance 2 = RSRPmin, TH 1 != RSRPmin, it is determined that only 1 threshold needs to be configured as TH 1 , and the cell is divided into 2 coverage levels.

[0230] As Figure 11-c shown, if the TH with the smallest variance 2 != RSRPmin, TH 1 != TH2, and TH 1 != RSRPmax, it is determined that the thresholds are TH 1 and TH 2 , and the cell is divided into 3 coverage levels.

[0231] Step 5-2-1, calculate the configuration of data parameters under different CLs, including the number of retransmissions and the MCS value.

[0232] Step 1: Estimate the distribution of the minimum RSRP value of the IOT service over time within different CL ranges. According to the RSRP threshold values obtained previously, the RSRP value ranges within different CLs in the next cycle can be obtained.

[0233] Optionally, as Fig.12 shown, the capacity demand distribution at each RSRP can be obtained based on AI prediction, as shown in formula (1): Capacity_RSRP i (t)(0 < t < T)

[0234] Optionally, when Capacity_RSRP i (t 1 ) = 0 or Capacity_RSRP i (t 1 ) < Capacity_Threshold, then at t 1moment, in RSRP i If the probability of IOT service occurrence is zero (or very small), there will be no data transmission, then the corresponding RSRP existence probability is 0, otherwise the existence probability is 1.

[0235] Optionally, by analyzing all RSRPs within the CL range at each time t within the time period T, an RSRP set with a probability of 1 for all RSRPs within the CL range is obtained, and then the minimum RSRP value corresponding to the system at each time t within the period T is obtained, that is, the distribution of the minimum RSRP value within the CL over time.

[0236] Alternatively, if Fig.13 As shown, the distribution of the minimum RSRP value under each CL of the system over time can be obtained.

[0237] Step 2: Analyze the minimum RSRP within each CL min (t) The value fluctuates over time. The calculation time is t d1 With t d2 The two time periods before and after t 1 With t 2 The minimum RSRP change is as shown in formula (5):

[0238] ΔRSRP=RSRP min (t 2 )-RSRP min (t 1 )Formula (5)

[0239] Step 3: Based on ΔRSRP, estimate the 2 The change in the number of data transmission repetitions and the configuration of MCS. The change in the number of repetitions is defined as ΔRep, and the change in the coding modulation is defined as ΔMCS. A possible related algorithm is as follows Fig.14 As shown, the X, Y, and Z values ​​depend on the performance of the device and can be pre-configured.

[0240] Based on the ΔRSRP obtained in S301, the integer difference is obtained;

[0241] S302, determine whether ΔRSRP is not less than XdB; when ΔRSRP is not less than XdB, the change of the number of transmission repetitions is:

[0242] S303, ΔRep=floor(ΔRSRP / X);

[0243] After the number of repetitions is adjusted, the remaining RSRP difference is:

[0244] S304, ΔRSRPr=ΔRSRP-X*ΔRep;

[0245] S305, determine whether ΔRSRPr is greater than YdB;

[0246] When ΔRSRPr is less than YdB, then in S309, the MCS configuration does not change: ΔMCS=0;

[0247] S306, determining whether ΔRSRPr is greater than ZdB;

[0248] When ΔRSRPr is greater than YdB but less than ZdB, then in S307 , the MCS configuration changes to: ΔMCS=1;

[0249] When ΔRSRPr is greater than ZdB, then in S308, the MCS configuration changes to: ΔMCS=2;

[0250] S302 determines whether ΔRSRP is not less than XdB; if ΔRSRP is less than XdB, the number of transmission repetitions does not change, S310 ΔRep = 0; the MCS configuration changes to:

[0251] S311, determine whether ΔRSRPr is greater than YdB;

[0252] When ΔRSRP is less than YdB, then in S312, the MCS configuration does not change: ΔMCS=0;

[0253] S313, determine whether ΔRSRPr is greater than ZdB;

[0254] When ΔRSRP is greater than YdB but less than ZdB, then in S314, the MCS configuration changes to: ΔMCS=1;

[0255] When ΔRSRP is greater than ZdB, then in S315 , the MCS configuration changes to: ΔMCS=2.

[0256] Step 4: Based on time period t 1 The number of data transmission repetitions RepNum 1 and MCS 1 , configured in time period t 2 The number of data transmission repetitions RepNum 2 and MCS 2 , as shown in formulas (6) and (7):

[0257] RepNum 2 =RepNum 1 +ΔRep formula (6)

[0258] MCS 2 =MCS 1 +ΔMCS formula (7)

[0259] Step 5-2-2: Calculate the RACH parameter configuration under different CLs, including the number of random access preamble retransmissions, the number of subcarriers, and the period.

[0260] Step 1: Estimate the distribution of capacity requirements of IoT services over time within different CL ranges

[0261] First, the range of RSRP values ​​in different CLs in the next period can be obtained based on the RSRP threshold value obtained previously;

[0262] The demand capacity distribution under each RSRP obtained based on AI prediction is shown in formula (1):

[0263] Capacity_RSRP i (t)(0 <t<T)

[0264] In period T, the distribution characteristics of the total demand capacity of IOT services under CLx over time are shown in formula (8):

[0265] Capacity CLx _RSRP(t)=∑ i Capacity_RSRP i (t) Formula (8)

[0266] Thus, the distribution of capacity demand of IOT services under each CL of the system over time can be obtained, such as Fig.15 shown.

[0267] Step 2: Analyze the fluctuation characteristics of IOT capacity demand in each CL over time. The calculation time is t d1 With t d1 The two time periods before and after t 1 With t 2 The change in content volume demand is shown in formula (9):

[0268] ΔCapacity=Capacity CLx _RSRP(t 2 )-Capacity CLx _RSRP(t 1 )Formula (9)

[0269] Step 3: Determine whether to reconfigure CL's RACH resources based on ΔCapacity.

[0270] If ΔCapacity is greater than the threshold ΔCapacity_Threshold, it is considered that the current IoT capacity has increased, the existing RACH resources cannot meet the access requirements, and the RACH resources need to be reconfigured; otherwise, the RACH resource configuration remains unchanged.

[0271] Step 4: Determine the resource configuration of RACH under CL.

[0272] Based on the capacity performance benchmarks obtained earlier under different RACH configurations, it is estimated that in time period t 2 Satisfy CapacityCLx_RSRP(t 2 ) RACH resource configuration based on capacity requirements, including: number of repetitions, period and number of subcarriers.

[0273] The capacity performance benchmark gives the system access success rate or system access capacity value under different RACH resource configurations (number of repetitions, cycles, number of subcarriers) and number of users with access requirements.

[0274] According to the estimated required capacity CapacityCLx_RSRP(t 2 ), select the configuration that makes the system access success rate highest under the required capacity in the capacity benchmark as time period t 2 Configuration of the internal RACH.

[0275] Optional Embodiment 2

[0276] Figure 16-a and Figure 16-b The figure shows the principle flow of information processing in the O-RAN system and the corresponding modules and interfaces in the O-RAN system framework. Figure 16-a and Figure 16-b As shown:

[0277] Step (1): The SMO module collects the location information of the terminal and the characteristic information of the IOT service, such as the periodic characteristics of the service, from the application server. The above information is used to estimate and predict the IOT coverage characteristics and service characteristics in the cell.

[0278] Most IoT users are stationary (e.g. meter reading) or have regular operation trajectories (e.g. high-voltage power line inspection). Operators can obtain relevant information from vertical industries and store it in the operation server in advance.

[0279] IoT services generally have periodic regularity. For example, humidity detection services detect and report the humidity index of the surrounding environment at fixed time intervals. Operators can also store relevant demand information of vertical industries in the operation server in advance.

[0280] Through the public interface, SMO can obtain the configuration information of terminals and services from vertical industries (such as location and periodicity of business occurrence) that is stored in the server in advance from the running server.

[0281] Step (2): SMO receives information from O-eNB or O-DU through O1 interface, and the information includes: measurement quantities RSRP and BSR reported by IOT terminal, and base station measurement statistics and configuration information; the base station measurement statistics and configuration information includes: the number of Msg1 received in each CL, the number of Msg4 received in each CL, and the UE downlink BO size; the current cell configuration information includes: RACH configuration information (the number of subcarrier resources of each CL, the number of repetitions of preamble code, and the period), the MCS value of uplink transmission of each CL, the number of repetitions of uplink transmission of each CL, the number of retransmissions of Ack / NACK of Msg4 of each CL, the number of retransmissions of Ack / NACK of PDSCH under each CL, the MCS value of downlink transmission of each CL, the number of repetitions of downlink transmission of each CL, the number of repetitions of CSS transmission of each CL, the number of repetitions of USS transmission of each CL, and the RSRP threshold value corresponding to the CL in the cell.

[0282] Step (3): SMO transmits the received measurement quantity to Non-RT RIC through the internal bus. Non-RT RIC analyzes the measurement and statistical results, which involves using the preset cycle or time setting of the user BO and the vertical industry to obtain the periodic characteristics of the IOT service under each RSRP coverage; it involves using the number of Msg1 and Msg4 received in each CL and the corresponding RACH configuration information to analyze and obtain the capacity performance benchmark under different RACH configurations. The capacity benchmark gives different RACH configurations (number of repetitions, cycle, number of subcarriers), under any number of access demand users, the system access success rate or the system access capacity value.

[0283] Step (4): Non-RT RIC uses AI / ML to predict the service distribution of the next time period, which involves Non-RT RIC using historical data (such as data from the past year) to train the AI ​​model to obtain an AI model suitable for IOT services in the cell. It involves using the trained AI model, combined with the service cycle distribution characteristics obtained in step (3) and the actual measurement data in the last N (>=1) cycles to predict the capacity distribution of IOT services over time under different RSRPs in the next cycle.

[0284] Step (5): Non-RT RIC dynamically configures the cell wireless resources and transmission parameters based on the distribution characteristics of IOT services in the cell, including: clustering IOT terminals in the same cell using the capacity-weighted variance analysis method, which is specifically achieved by estimating and setting different RSRP threshold values. Furthermore, for IOT users in the same cluster, the fluctuation characteristics of the coverage characteristics over time are estimated, and the number of repetitions and MCS changes required for data transmission are dynamically estimated based on the fluctuation characteristics, so as to obtain the optimal configuration of the number of repetitions and MCS for data transmission of the same type of IOT users in different time periods. On the other hand, in order to ensure the access performance of the same type of IOT users, the capacity demand distribution of IOT services of the same type of users in different time periods is estimated, and the capacity performance benchmark under different RACH configurations obtained in step (3) is used to estimate the optimal RACH resource and transmission parameter configuration (including the number of RACH subcarriers, period, and number of repetitions) in different time periods.

[0285] Step (6): The resource and transmission parameter configuration obtained in step (5) is transmitted to the SMO through the internal bus interface Non-RT RIC. Next, the SMO uses the O1 interface to send the relevant parameter configuration to the O-eNB or O-DU. Finally, the O-eNB or O-DU completes the update of the resource configuration parameters.

[0286] Optionally, a principle flow of information processing, such as Fig.17 As shown:

[0287] S401, OAM receives data information sent by an external server.

[0288] Optionally, the data information includes: location information of the IOT terminal, characteristic information of the IOT service, such as the time and period of the service.

[0289] S402, OAM receives measurement and configuration information from the E2 node through the O1 interface: RSRP measurement value, data volume in the terminal buffer, RACH-related configuration and performance information, data and control channel and other cell configuration information, etc.

[0290] S403, OAM extracts the data and transmits it to Non-RT RIC.

[0291] S404, Non-RT RIC analysis obtains coverage characteristics, cycle characteristics and capacity performance of the IoT service.

[0292] S405, Non-RT RIC trains the AI / ML model and predicts the capacity distribution at the RSRP level.

[0293] S406, Non-RT RIC estimates and determines the service coverage level and transmission and resource configuration parameters.

[0294] S407, the Non-RT RIC transmits the configuration information of the IOT service to the OAM through the internal bus.

[0295] S408, OAM sends the configuration information of the cell IOT service to the E2 node through the O1 interface.

[0296] Optional embodiment three

[0297] Figure 18-a and Figure 18-b The principle flow of information processing in the O-RAN system and the modules and interfaces in the corresponding O-RAN system framework are shown. Compared with the second embodiment, the transmission interface of the configuration parameters in the third embodiment is different. Figure 18-a and Figure 18-b As shown:

[0298] Steps (1) to (5): are the same as the corresponding steps (1) to (5) in Example 2.

[0299] Step (6): The resource and transmission parameter configuration results obtained by the Non-RT RIC in step (5) are sent to the Near-RT RIC via the A1 interface. Then, they are sent to the O-eNB or O-DU via the E2 interface. Finally, the O-eNB or O-DU completes the update of the resource configuration parameters.

[0300] Optionally, a principle flow of information processing, such as Fig.19 As shown:

[0301] S501, OAM receives data information sent by an external server.

[0302] Optionally, the data information includes: location information of the IOT terminal, characteristic information of the IOT service, such as the time and period of the service.

[0303] S502, OAM receives measurement and configuration information from the E2 node through the O1 interface: RSRP measurement value, data volume in the terminal buffer, RACH-related configuration and performance information, data and control channel and other cell configuration information, etc.

[0304] S503, OAM extracts the data and transmits it to the Non-RT RIC.

[0305] S504, Non-RT RIC analysis obtains coverage characteristics, cycle characteristics and capacity performance of the IoT service.

[0306] S505, Non-RT RIC trains the AI / ML model and predicts the capacity distribution at the RSRP level.

[0307] S506, Non-RT RIC estimates and determines the service coverage level and transmission and resource configuration parameters.

[0308] S507, the Non-RT RIC sends the configuration of the cell IOT service to the Near-RT RIC through the A1 interface.

[0309] S508, Near-RT RIC sends the configuration information of the cell IOT service through the E2 interface.

[0310] Optional Embodiment 4

[0311] Figure 20-a and Figure 20-b The figure shows the principle flow of information processing in the O-RAN system and the corresponding modules and interfaces in the O-RAN system framework. Figure 20-a and Figure 20-b As shown:

[0312] Step (1): The SMO module collects the location information of the terminal and the characteristic information of the IOT service, such as the periodic characteristics of the service, from the application server. The above information is used to estimate and predict the IOT coverage characteristics and service characteristics in the cell.

[0313] Most IoT users are stationary (e.g. meter reading) or have regular operation trajectories (e.g. high-voltage power line inspection). Operators can obtain relevant information from vertical industries and store it in the operation server in advance.

[0314] IoT services generally have periodic regularity. For example, humidity detection services detect and report the humidity index of the surrounding environment at fixed time intervals. Operators can also store relevant demand information of vertical industries in the operation server in advance.

[0315] Through the public interface, SMO can obtain the configuration information of terminals and services from vertical industries (such as location and periodicity of business occurrence) that is stored in the server in advance from the running server.

[0316] Step (2.1): SMO receives information from O-eNB or O-DU through O1 interface, including measurement quantities RSRP and BSR reported by IOT terminals, as well as base station measurement statistics and configuration information: the number of Msg1 received in each CL, the number of Msg4 received in each CL, the UE downlink BO size, the current cell configuration information, including RACH configuration information (the number of subcarrier resources for each CL, the number of repetitions of the preamble code, and the period), the MCS value of uplink transmission for each CL, the number of repetitions of uplink transmission for each CL, the number of retransmissions of Ack / NACK for Msg4 for each CL, the number of retransmissions of Ack / NACK for PDSCH under each CL, the MCS value of downlink transmission for each CL, the number of repetitions of downlink transmission for each CL, the number of repetitions of CSS transmission for each CL, the number of repetitions of USS transmission for each CL, and the RSRP threshold value corresponding to the CL in the cell.

[0317] Step (2.2): Near-RT RIC receives information from O-eNB or O-DU through the E2 interface, including the measurement quantities RSRP and BSR reported by the IOT terminal, as well as the measurement statistics and configuration information of the base station: the BO size of the UE downlink, the configuration information of the current cell, the MCS value of the uplink transmission of each CL, the number of repetitions of the uplink transmission of each CL, the number of retransmissions of the Ack / NACK of Msg4 of each CL, the number of retransmissions of the Ack / NACK of the PDSCH under each CL, the MCS value of the downlink transmission of each CL, the number of repetitions of the downlink transmission of each CL, the number of repetitions of the CSS transmission of each CL, the number of repetitions of the USS transmission of each CL, and the RSRP threshold value corresponding to the CL in the cell.

[0318] Step (3.1): SMO transmits the received measurement quantity to Non-RT RIC through the internal bus. Non-RT RIC analyzes the measurement and statistical results, which involves using the preset cycle or time setting of the user BO and the vertical industry to obtain the periodic characteristics of the IOT service under each RSRP coverage; it involves using the number of Msg1 and Msg4 received in each CL and the corresponding RACH configuration information to analyze and obtain the capacity performance benchmark under different RACH configurations. The capacity benchmark gives different RACH configurations (number of repetitions, cycle, number of subcarriers), under any number of access demand users, the system access success rate or the system access capacity value.

[0319] Step (3.2): The Non-RT RIC transmits the periodic characteristics of the IOT services under each RSRP coverage and the capacity performance benchmark results under different RACH configurations obtained through the A1 interface to the Near-RT RIC.

[0320] Step (4.1): Non-RT RIC uses long-term historical data (e.g., data from the past year) to train the AI ​​model and obtain an AI model suitable for IOT services within the community.

[0321] Step (4.2): Non-RT RIC uses the O1 interface to deploy the trained AI model suitable for IOT services to Near-RT RIC.

[0322] Step (4.3): Near-RT RIC uses the AI / ML model to predict the service distribution in the next time period, which involves using the trained AI model, combined with the service cycle distribution characteristics obtained in step (3.2) and the actual measurement data collected in the last N (>=1) cycles in step (2.2) to predict the capacity distribution of IOT services under different RSRPs in the next cycle over time.

[0323] Step (5): Near-RT RIC dynamically configures the cell wireless resources and transmission parameters according to the distribution characteristics of IOT services in the cell, including: clustering IOT terminals in the same cell using the capacity-weighted variance analysis method, which is specifically achieved by estimating and setting different RSRP threshold values. Furthermore, for IOT users in the same cluster, the fluctuation characteristics of the coverage characteristics over time are estimated, and the number of repetitions and MCS changes required for data transmission are dynamically estimated based on the fluctuation characteristics, so as to obtain the optimal configuration of the number of repetitions and MCS for data transmission of the same type of IOT users in different time periods. On the other hand, in order to ensure the access performance of the same type of IOT users, the capacity demand distribution of IOT services of the same type of users in different time periods is estimated, and the capacity performance benchmark under different RACH configurations obtained in step (3.2) is used to estimate the optimal RACH resource and transmission parameter configuration (including the number of RACH subcarriers, period, and number of repetitions) in different time periods.

[0324] Step (6): The Near-RT RIC is sent to the O-eNB or O-DU using the E2 interface, and the O-eNB or O-DU completes the update of resource configuration parameters.

[0325] Optionally, a principle flow of information processing, such as Fig.21 As shown:

[0326] S601, OAM receives data information sent by an external server.

[0327] Optionally, the data information includes: location information of the IOT terminal, characteristic information of the IOT service, such as the time and period of the service.

[0328] S602, OAM receives measurement and configuration information from the E2 node through the O1 interface: RSRP measurement value, data volume in the terminal buffer, RACH-related configuration and performance information, data and control channel and other cell configuration information, etc.

[0329] S603, OAM extracts the data and transmits it to the Non-RT RIC.

[0330] S604, Non-RT RIC analysis obtains coverage characteristics, cycle characteristics and capacity performance of the IoT service.

[0331] S605, Non-RT RIC uses long-term historical measurement data to train AI / ML models.

[0332] S606, the Non-RT RIC transmits the AI / ML model to the near-RT RIC through the O1 interface.

[0333] S607, the Non-RT RIC transmits the analyzed service characteristics and performance information to the near-RTRIC via the A1 interface.

[0334] S608, the near-RT RIC receives measurement and configuration information from the E2 node through the E2 interface: RSRP measurement value, data volume in the terminal buffer, RACH-related configuration and performance information, data and control channel and other cell configuration information, etc.

[0335] S609, near-RT RIC trains AI / ML models and predicts capacity distribution at the RSRP level.

[0336] S610, near-RT RIC estimates and determines the service coverage level and transmission and resource configuration parameters.

[0337] S611, near-RT RIC sends the configuration information of the cell IOT service through the E2 interface.

[0338] Optional Embodiment 5

[0339] Figure 22-a and Figure 22-b The figure shows the principle flow of information processing in the O-RAN system and the corresponding modules and interfaces in the O-RAN system framework. Figure 22-a and Figure 22-b As shown:

[0340] Step (1), the SMO module collects the location information of the terminal and the characteristic information of the IOT service, such as the periodic characteristics of the service, from the application server. The above information is used to estimate and predict the IOT coverage characteristics and service characteristics in the cell.

[0341] Most IoT users are stationary (e.g. meter reading) or have regular operation trajectories (e.g. high-voltage power line inspection). Operators can obtain relevant information from vertical industries and store it in the operation server in advance.

[0342] IoT services generally have periodic regularity. For example, humidity detection services detect and report the humidity index of the surrounding environment at fixed time intervals. Operators can also store relevant demand information of vertical industries in the operation server in advance.

[0343] SMO can obtain the configuration information of terminals and services from vertical industries (such as location and periodicity of services) stored in the server in advance from the running server through the public interface.

[0344] Step (2.1), ()SMO receives information from O-eNB or O-DU through O1 interface, including measurement quantities RSRP and BSR reported by IOT terminals, and base station measurement statistics and configuration information: the number of Msg1 received in each CL, the number of Msg4 received in each CL, the BO size of UE downlink, the configuration information of the current cell, including the configuration information of RACH (the number of subcarrier resources for each CL, the number of repetitions of the preamble code, and the period), the MCS value of uplink transmission of each CL, the number of repetitions of uplink transmission of each CL, the number of retransmissions of Ack / NACK of Msg4 of each CL, the number of retransmissions of Ack / NACK of PDSCH under each CL, the MCS value of downlink transmission of each CL, the number of repetitions of downlink transmission of each CL, the number of repetitions of CSS transmission of each CL, the number of repetitions of USS transmission of each CL, and the RSRP threshold value corresponding to CL in the cell.

[0345] In step (2.2), the Near-RT RIC receives the system resource configuration information from the O-eNB or O-DU through the E2 interface: the MCS value of the uplink transmission of each CL, the number of repetitions of the uplink transmission of each CL, the number of retransmissions of the Ack / NACK of Msg4 of each CL, the number of retransmissions of the Ack / NACK of the PDSCH under each CL, the MCS value of the downlink transmission of each CL, the number of repetitions of the downlink transmission of each CL, the number of repetitions of the CSS transmission of each CL, the number of repetitions of the USS transmission of each CL, and the RSRP threshold value corresponding to the CL in the cell.

[0346] In step (3.1), SMO transmits the received measurement quantity to Non-RT RIC through the internal bus. Non-RT RIC analyzes the measurement and statistical results, which involves using the preset cycle or time setting of the user BO and the vertical industry to obtain the periodic characteristics of the IOT service under each RSRP coverage; it involves using the number of Msg1 and Msg4 received in each CL and the corresponding RACH configuration information to analyze and obtain the capacity performance benchmark under different RACH configurations. The capacity benchmark gives different RACH configurations (number of repetitions, cycle, number of subcarriers), and the access success rate or access capacity value of the system under any number of access demand users. Among them, the periodic characteristics of the IOT service under each RSRP coverage will be passed to the AI ​​prediction processing link inside the Non-RT RIC.

[0347] In step (3.2), the Non-RT RIC transmits the capacity performance benchmark results under different RACH configurations obtained through analysis to the Near-RT RIC via the A1 interface.

[0348] In step (4.1), Non-RT RIC uses long-term historical data (such as data from the past year) to train the AI ​​model to obtain an AI model suitable for IOT services in the cell. Non-RT RIC uses the trained AI model, combined with the service cycle distribution characteristics obtained in step (3.1) and the actual measurement data collected in the last N (>=1) cycles in step (2.1) to predict the capacity distribution of IOT services under different RSRPs in the next cycle over time.

[0349] In step (4.2), the Non-RT RIC uses the A1 interface to transmit the predicted capacity distribution information of IOT services under different RSRPs over time to the Near-RT RIC.

[0350] Step (5), Near-RT RIC dynamically configures the cell wireless resources and transmission parameters according to the distribution characteristics of IOT services in the cell, including: clustering IOT terminals in the same cell using the capacity weighted variance analysis method, which is specifically achieved by estimating and setting different RSRP threshold values. Further, for IOT users in the same cluster, the fluctuation characteristics of the coverage characteristics over time are estimated, and the number of repetitions and MCS changes required for data transmission are dynamically estimated based on the fluctuation characteristics, so as to obtain the optimal configuration of the number of repetitions and MCS for data transmission of the same type of IOT users in different time periods. On the other hand, in order to ensure the access performance of the same type of IOT users, the capacity demand distribution of IOT services of the same type of users in different time periods is estimated, and the capacity performance benchmark under different RACH configurations obtained in step (3.2) is used to estimate the optimal RACH resource and transmission parameter configuration (including the number of RACH subcarriers, period, and number of repetitions) in different time periods.

[0351] Step (6): Near-RT RIC is sent to O-eNB or O-DU using E2 interface, and O-eNB or O-DU completes the update of resource configuration parameters.

[0352] Optionally, a principle flow of information processing, such as Fig.23 As shown:

[0353] S701, OAM receives data information sent by an external server.

[0354] Optionally, the data information includes: location information of the IOT terminal, characteristic information of the IOT service, such as the time and period of the service.

[0355] S702, OAM receives measurement and configuration information from the E2 node through the O1 interface: RSRP measurement value, data volume in the terminal buffer, RACH-related configuration and performance information, data and control channel and other cell configuration information, etc.

[0356] S703, OAM extracts the data and transmits it to the Non-RT RIC.

[0357] S704, Non-RT RIC analysis obtains coverage characteristics, cycle characteristics and capacity performance of the IoT service.

[0358] S705, Non-RT RIC uses long-term historical measurement data to train AI / ML models.

[0359] S706, Non-RT RIC trains the AI / ML model and predicts the capacity distribution at the RSRP level.

[0360] S707, the Non-RT RIC transmits the analyzed service characteristics and performance information to the near-RTRIC via the A1 interface.

[0361] S708, the Non-RT RIC transmits the predicted capacity distribution information to the near-RT RIC through the A1 interface.

[0362] S709, the near-RT RIC receives configuration information from the E2 node through the E2 interface: RACH-related configuration, data and control channel and other cell configuration information, etc.

[0363] S710, the near-RT RIC estimates and determines the service coverage level and transmission and resource configuration parameters.

[0364] S711, near-RT RIC sends the configuration information of the cell IOT service through the E2 interface.

[0365] Optional Embodiment 6

[0366] Figure 24-a and Figure 24-b The principle flow of information processing in the O-RAN system and the corresponding modules and interfaces in the O-RAN system framework are shown.

[0367] like Figure 24-a and Figure 24-b As shown: Step (1), the SMO module collects the location information of the terminal and the characteristic information of the IOT service, such as the periodic characteristics of the service, from the application server. The above information is used to estimate and predict the IOT coverage characteristics and service characteristics in the cell.

[0368] Most IoT users are stationary (e.g. meter reading) or have regular operation trajectories (e.g. high-voltage power line inspection). Operators can obtain relevant information from vertical industries and store it in the operation server in advance.

[0369] IoT services generally have periodic regularity. For example, humidity detection services detect and report the humidity index of the surrounding environment at fixed time intervals. Operators can also store relevant demand information of vertical industries in the operation server in advance.

[0370] Through the public interface, SMO can obtain the configuration information of terminals and services from vertical industries (such as location and periodicity of business occurrence) that is stored in the server in advance from the running server.

[0371] In step (2.1), the Near-RT RIC receives information from the O-eNB or O-DU through the E2 interface, including the measurement quantities RSRP and BSR reported by the IOT terminal, as well as the measurement statistics and configuration information of the base station: the number of Msg1 received in each CL, the number of Msg4 received in each CL, the BO size of the UE downlink, the configuration information of the current cell, including the configuration information of the RACH (the number of subcarrier resources of each CL, the number of repetitions of the preamble code, and the period), the MCS value of the uplink transmission of each CL, the number of repetitions of the uplink transmission of each CL, the number of retransmissions of the Ack / NACK of Msg4 of each CL, the number of retransmissions of the Ack / NACK of the PDSCH under each CL, the MCS value of the downlink transmission of each CL, the number of repetitions of the downlink transmission of each CL, the number of repetitions of the CSS transmission of each CL, the number of repetitions of the USS transmission of each CL, and the RSRP threshold value corresponding to the CL in the cell.

[0372] Step (2.2), Near-RT RIC forwards the configuration information from O-eNB or O-DU to SMO through O1 interface.

[0373] In step (3.1), SMO transmits the received and configured information to Non-RT RIC through the internal bus. Non-RT RIC analyzes the measurement and statistical results, which involves using the preset cycle or time settings of the user BO and the vertical industry to obtain the periodic characteristics of the IOT service under each RSRP coverage; it involves using the number of Msg1 and Msg4 received in each CL and the corresponding RACH configuration information to analyze and obtain the capacity performance benchmark under different RACH configurations. The capacity benchmark gives different RACH configurations (number of repetitions, cycle, number of subcarriers), under any number of access demand users, the system access success rate or the system access capacity value.

[0374] In step (3.2), the Non-RT RIC transmits the analyzed periodic characteristics of IOT services under each RSRP coverage and the capacity performance benchmark results under different RACH configurations to the Near-RT RIC through the A1 interface.

[0375] In step (4.1), Non-RT RIC uses long-term historical data (e.g., data from the past year) to train the AI ​​model and obtain an AI model suitable for IOT services within the community.

[0376] In step (4.2), the Non-RT RIC uses the O1 interface to deploy the trained AI model suitable for IOT services to the Near-RT RIC.

[0377] In step (4.3), Near-RT RIC uses the AI / ML model to predict the service distribution of the next time period, which involves using the trained AI model combined with the service cycle distribution characteristics obtained in step (3.2) and the actual measurement data collected in the last N (>=1) cycles in step (2.1) to predict the capacity distribution of IOT services under different RSRPs in the next cycle over time.

[0378] Step (5), Near-RT RIC dynamically configures the cell wireless resources and transmission parameters according to the distribution characteristics of IOT services in the cell, including: clustering IOT terminals in the same cell using the capacity weighted variance analysis method, which is specifically achieved by estimating and setting different RSRP threshold values. Further, for IOT users in the same cluster, the fluctuation characteristics of the coverage characteristics over time are estimated, and the number of repetitions and MCS changes required for data transmission are dynamically estimated based on the fluctuation characteristics, so as to obtain the optimal configuration of the number of repetitions and MCS for data transmission of the same type of IOT users in different time periods. On the other hand, in order to ensure the access performance of the same type of IOT users, the capacity demand distribution of IOT services of the same type of users in different time periods is estimated, and the capacity performance benchmark under different RACH configurations obtained in step (3.2) is used to estimate the optimal RACH resource and transmission parameter configuration (including the number of RACH subcarriers, period, and number of repetitions) in different time periods.

[0379] Step (6): Near-RT RIC is sent to O-eNB or O-DU using E2 interface, and O-eNB or O-DU completes the update of resource configuration parameters.

[0380] Optionally, a principle flow of information processing, such as Fig.25 As shown:

[0381] S801, OAM receives data information sent by an external server.

[0382] Optionally, the data information includes: location information of the IOT terminal, characteristic information of the IOT service, such as the time and period of the service.

[0383] S802, the near-RT RIC receives measurement and configuration information from the E2 node through the E2 interface.

[0384] S803, OAM receives measurement information from the E2 node sent by the near-RT RIC through the O1 interface.

[0385] S804, OAM extracts the data and transmits it to the Non-RT RIC.

[0386] S805, Non-RT RIC analysis obtains coverage characteristics, cycle characteristics and capacity performance of the IoT service.

[0387] S806, Non-RT RIC uses long-term historical measurement data to train AI / ML models.

[0388] S807, Non-RT RIC transmits the AI / ML model to near-RT RIC through the O1 interface.

[0389] S808, the Non-RT RIC transmits the analyzed service characteristics and performance information through the A1 interface.

[0390] S809, near-RT RIC trains AI / ML models and predicts capacity distribution at the RSRP level.

[0391] S810, the near-RT RIC estimates and determines the service coverage level and transmission and resource configuration parameters.

[0392] S811, near-RT RIC sends the configuration information of the cell IOT service through the E2 interface.

[0393] It should be noted that in order to implement the above-described embodiments of the present application, the following messages need to be introduced:

[0394] A1 interface, downlink direction: 1), if data analysis and prediction are implemented in Non-RT RIC, and the final resource configuration parameters are estimated (Example 1 and Example 2), the optimized configuration parameter values ​​can be passed to Near-RT RIC (Example 2) through the A1 interface. At this time, the configuration parameters that need to be provided by the A1 interface include: RSRP threshold value corresponding to each CL, RACH resource configuration under each CL (number of subcarriers, period and repetition times), each CL downlink data transmission parameter configuration (MCS, number of repetitions of data channel, number of repetitions of control channel), each CL uplink data transmission parameter configuration (MCS, number of repetitions of data channel, number of repetitions of feedback information). 2), if AI / ML prediction is implemented in Near-RT RIC (Example C and Example E), the parameters that need to be provided by the A1 interface include: periodic characteristics of IOT services under each RSRP coverage and capacity performance benchmark results under different RACH configurations. 3) If AI / ML prediction is implemented in None-RT RIC, but the configuration estimation processing is implemented in Near-RT RIC (Implementation Example D), the parameters required to be provided by the A1 interface include: capacity performance benchmark results under different RACH configurations, and capacity distribution information of IOT services under different RSRPs predicted by AI over time.

[0395] E2 interface, downlink direction: If the Near-RT RIC receives the configuration information from the A1 interface or performs data estimation processing in the Near-RT RIC to obtain the final system configuration information, the parameters that the downlink direction of the E2 interface needs to provide include: the RSRP threshold value corresponding to each CL, the RACH resource configuration under each CL (number of subcarriers, period and repetition number), the downlink data transmission parameter configuration of each CL (MCS, repetition number of data channel, repetition number of control channel), and the uplink data transmission parameter configuration of each CL (MCS, repetition number of data channel, repetition number of feedback information).

[0396] E2 interface, uplink direction: 1), if AI / ML prediction is implemented in Near-RT RIC (Implementation Example C and Implementation Example E), the parameters that need to be provided by the E2 interface include: the measurement quantities RSRP and BSR reported by the IOT terminal, and the base station measurement statistics and configuration information: the BO size of the UE downlink, the current cell configuration information: the MCS value of the uplink transmission of each CL, the number of repetitions of the uplink transmission of each CL, the number of retransmissions of the Ack / NACK of the Msg4 of each CL, the number of retransmissions of the Ack / NACK of the PDSCH under each CL, the MCS value of the downlink transmission of each CL, the number of repetitions of the downlink transmission of each CL, the number of repetitions of the CSS transmission of each CL, the number of repetitions of the USS transmission of each CL, and the RSRP threshold value corresponding to the CL in the cell. 2) If AI / ML prediction is implemented in None-RTRIC, but the configured estimation processing is implemented in Near-RT RIC (Implementation Example D), the parameters that need to be provided in the uplink direction of the E2 interface include: the MCS value of the uplink transmission of each CL, the number of repetitions of the uplink transmission of each CL, the number of retransmissions of Ack / NACK of Msg4 of each CL, the number of retransmissions of Ack / NACK of PDSCH under each CL, the MCS value of the downlink transmission of each CL, the number of repetitions of the downlink transmission of each CL, the number of repetitions of CSS transmission of each CL, the number of repetitions of USS transmission of each CL, and the RSRP threshold value corresponding to the CL in the cell.

[0397] O1 interface, uplink direction: it is necessary to support reporting of relevant measurement data, including the measurement quantities RSRP and BSR reported by the IOT terminal, as well as the measurement statistics and configuration information of the base station, involving the number of Msg1 received in each CL, the number of Msg4 received in each CL, the BO size of the UE downlink, the configuration information of the current cell, including the configuration information of RACH (the number of subcarrier resources for each CL, the number of repetitions of the preamble code, and the period), the MCS value of the uplink transmission of each CL, the number of repetitions of the uplink transmission of each CL, the number of retransmissions of Ack / NACK of Msg4 of each CL, the number of retransmissions of Ack / NACK of PDSCH under each CL, the MCS value of the downlink transmission of each CL, the number of repetitions of downlink transmission of each CL, the number of repetitions of CSS transmission of each CL, the number of repetitions of USS transmission of each CL, and the RSRP threshold value corresponding to the CL in the cell.

[0398] O1 interface, downlink direction: The obtained resources and transmission parameter configuration are transmitted to SMO through the internal bus interface Non-RT RIC. SMO uses the O1 interface to send the relevant parameter configuration to O-eNB or O-DU. The parameters that the downlink direction of the O1 interface needs to provide include: RSRP threshold value corresponding to each CL, RACH resource configuration under each CL (number of subcarriers, period and repetition times), downlink data transmission parameter configuration of each CL (MCS, repetition times of data channel, repetition times of control channel), uplink data transmission parameter configuration of each CL (MCS, repetition times of data channel, repetition times of feedback information).

[0399] Optionally, in order to support the embodiments of the present application, the interface adds the following IE:

[0400] 1.IOT_RACH_Configuations, defined as shown in Table (1):

[0401] Table (1)IOT_RACH_Configuations

[0402]

[0403] This structure is used for configuration reporting and distribution, and the interfaces involved are O1, E2, and A1.

[0404] 2.IOT_DL_Configuations, defined as shown in Table (2):

[0405] Table (2)IOT_DL_Configuations

[0406]

[0407]

[0408] This structure is used to report and send configuration information, and the interfaces involved are O1, E2, and A1.

[0409] 3.IOT_UL_Configuations, defined as shown in Table (3):

[0410] Table (3) IOT_UL_Configuations

[0411]

[0412] The technical solution provided in the embodiments of the present application has at least the following beneficial effects:

[0413] By calling Non-RT RIC or Near-RT RIC to predict the service distribution related information of IOT terminals, dynamic configuration of different coverage levels CL in the cell is achieved, saving energy consumption and improving system capacity and performance.

[0414] Based on the same inventive concept as the above-mentioned embodiment, the embodiment of the present application further provides an information processing device, which is applied to a first network device. The structural diagram of the device is shown in FIG. Fig.26 As shown, the information processing device 30 includes a first processing module 301 , a second processing module 302 and a third processing module 303 .

[0415] A first processing module 301 is used to receive information related to a second network device;

[0416] A second processing module 302, configured to determine, based on the information, a first resource configuration corresponding to a coverage category associated with the second network device;

[0417] The third processing module 303 is configured to send the first resource configuration to the second network device.

[0418] Optionally, the second processing module 302 is specifically used to determine, based on the information, the service distribution related information of the terminal user equipment included in the second network equipment corresponding to each coverage characteristic at the first time; predict or calculate the service distribution related information of the terminal user equipment at a second time after the first time based on the service distribution related information of the terminal user equipment at the first time, and determine the service distribution related information of the terminal user equipment at the second time; determine the first resource configuration corresponding to the coverage category related to the second network equipment based on the service distribution related information of the terminal user equipment at the second time; the coverage category includes at least one of the coverage level and the coverage domain.

[0419] Optionally, the first processing module 301 is also used to receive business information sent by an external server, the business information including location information of each terminal user device and characteristic information of each terminal user device; wherein the location information includes at least one of the location parameters of the terminal user device provided by the positioning server and the flight trajectory parameters provided by the positioning server, and the characteristic information includes at least one of the business cycle and the periodic reporting time.

[0420] The second processing module 302 is specifically configured to determine service distribution related information of the terminal user equipment corresponding to each coverage characteristic at the first time according to the information and the service information.

[0421] Optionally, the information includes at least one of measurement information of the second network device and configuration information of the second network device; the measurement information includes at least one of signal strength data, service data, and performance data; the configuration information includes a coverage category threshold configuration for coverage category division and at least one of resource configuration parameters corresponding to each coverage category, the coverage category threshold configuration is a coverage characteristic indicator value, and the coverage characteristic indicator value is used to divide the coverage area into different coverage categories.

[0422] Optionally, the second processing module 302 is specifically used to determine, based on the service data and service information, the distribution information of the terminal user equipment that has services to be sent and needs to access the second network equipment at the first time; and determine, based on the performance data and configuration information, the access capacity of the random access channel RACH corresponding to different configuration information, and the service distribution related information includes the distribution information and the access capacity of the RACH corresponding to different configuration information.

[0423] Optionally, the second processing module 302 is specifically used to input information related to the service distribution of the terminal user device in N service cycles into a preset prediction model, and predict the service distribution information of the terminal user device at a second time after the first time through the prediction model to obtain the time distribution of the capacity of the services corresponding to each coverage characteristic in the first cycle after N service cycles; wherein the first time includes N service cycles, the second time includes the first cycle, the service distribution information of the terminal user device at the first time is used to characterize the time distribution of the capacity of the services corresponding to each coverage characteristic in the N cycles, and the service distribution information of the terminal user device at the second time is used to characterize the time distribution of the capacity of the services corresponding to each coverage characteristic in the first cycle, and N is a positive integer.

[0424] Optionally, the second processing module 302 is specifically used to determine the coverage category thresholds corresponding to each coverage category based on the service distribution related information of the terminal user device at the second time; determine the first resource configuration corresponding to the coverage category related to the second network device based on the service distribution related information of the terminal user device at the second time and the coverage category thresholds corresponding to each coverage category.

[0425] Optionally, the second processing module 302 is specifically used to determine the number of transmission repetitions and the modulation and coding strategy MCS configuration of the resources of the terminal user equipment corresponding to each coverage category according to the coverage category thresholds corresponding to each coverage category, where the resources include at least one of the physical downlink control channel PDCCH, the physical downlink shared channel PDSCH, the physical uplink shared channel PUSCH, and the uplink control information UCI; determine the number of coverage categories and the number of terminal user equipment corresponding to each coverage category according to the service distribution related information of the terminal user equipment at the second time and the coverage category thresholds corresponding to each coverage category; determine the second resource configuration of the RACH corresponding to each coverage category according to the number of terminal user equipment corresponding to each coverage category and the access capacity of the RACH corresponding to the configuration information of the second network device included in the information, the first resource configuration corresponding to the coverage category includes the coverage category threshold of the terminal user equipment corresponding to each coverage category, the number of transmission repetitions of the resources, the MCS configuration of the resources, and the second resource configuration of the RACH corresponding to each coverage category, and the second resource configuration of the RACH includes at least one of the number of transmission retransmissions of the random access preamble code, the number of RACH subcarriers, and the RACH period.

[0426] Optionally, when the number of coverage categories and the coverage category thresholds respectively corresponding to the coverage categories change, adjusting the number of transmission repetitions of the resources of the terminal user equipment respectively corresponding to the coverage categories and the modulation and coding strategy MCS configuration of the resources;

[0427] Or after determining the number of each coverage category and the coverage category threshold corresponding to each coverage category, adjust the number of transmission repetitions of the resources of the terminal user equipment corresponding to each coverage category and the modulation and coding strategy MCS configuration of the resources.

[0428] Optionally, adjusting the number of transmission repetitions of the resources of the terminal user equipment corresponding to each coverage category includes at least one of the following:

[0429] Adjusting the number of transmission repetitions of the PDCCH, the adjustment of the number of transmission repetitions of the PDCCH includes adjusting the number of transmission repetitions of at least one of the message msg2, the message msg3, and the message msg4 in the common search space, and adjusting the number of transmission repetitions of the dedicated search space;

[0430] Adjust the number of transmission repetitions of the PDSCH, where the adjustment of the number of transmission repetitions of the PDSCH includes at least one of the adjustment of the number of transmission repetitions of the PDSCH carrying the message msg2, the adjustment of the number of transmission repetitions of the PDSCH carrying the message msg4, and the adjustment of the number of transmission repetitions of the PDSCH carrying downlink signaling and data in the connected state;

[0431] Adjust the number of transmission repetitions of the PUSCH, where the adjustment of the number of transmission repetitions of the PUSCH includes at least one of the adjustment of the number of transmission repetitions of the PUSCH carrying the message msg3 and the adjustment of the number of transmission repetitions of the PUSCH carrying uplink signaling and data in the connected state;

[0432] The transmission repetition number of uplink control information UCI is adjusted, and the adjustment of the transmission repetition number of UCI includes at least one of the adjustment of the transmission repetition number of PUSCH carrying downlink transmission ACK and / or NACK and the adjustment of PUCCH carrying downlink transmission ACK and / or NACK.

[0433] Optionally, adjusting the MCS configuration of the resources of the terminal user equipment corresponding to each coverage category includes at least one of the following:

[0434] Adjust the MCS configuration of the PDSCH, where the adjustment of the MCS configuration of the PDSCH includes at least one of the following: adjustment of the MCS configuration of the PDSCH carrying the message msg2, adjustment of the MCS configuration of the PDSCH carrying the message msg4, and adjustment of the MCS configuration of the PDSCH carrying downlink signaling and data in a connected state;

[0435] The MCS configuration of the PUSCH is adjusted, and the adjustment of the MCS configuration of the PUSCH includes at least one of the adjustment of the MCS configuration of the PUSCH carrying the message msg3 and the adjustment of the MCS configuration of the PUSCH carrying uplink signaling and data in the connected state.

[0436] Optionally, the first processing module 301 is specifically configured to receive information sent by the second network device, including at least one of the following:

[0437] receiving information related to the second network device sent by the service management and orchestration SMO;

[0438] Receive information related to the second network device sent by a quasi real-time RAN intelligent controller Near-RT RIC, wherein the information related to the second network device is obtained by the Near-RT RIC from the second network device.

[0439] Optionally, the third processing module 303 is specifically configured to send the first resource configuration to the second network device, including one of the following:

[0440] Sending the first resource configuration to the second network device;

[0441] Sending the first resource configuration to the Near-RT RIC, where the Near-RT RIC sends the first resource configuration to the second network device;

[0442] The first resource configuration is sent to the second network device through the Near-RT RIC.

[0443] Optionally, the first network device is a non-real-time RAN intelligent controller Non-RT RIC or a quasi-real-time RAN intelligent controller Near-RT RIC.

[0444] The technical solution provided in the embodiments of the present application has at least the following beneficial effects:

[0445] The service distribution related information of the terminal user equipment at a second time after the first time is predicted, so as to realize the dynamic configuration of different coverage levels in the cell, save energy consumption, and improve the system capacity and performance.

[0446] Based on the same inventive concept, the present application also provides an electronic device, the structural diagram of the electronic device is as follows: Fig. 27 As shown, the electronic device 6000 includes at least one processor 6001, a memory 6002 and a bus 6003, and the at least one processor 6001 is electrically connected to the memory 6002; the memory 6002 is configured to store at least one computer-executable instruction, and the processor 6001 is configured to execute the at least one computer-executable instruction, thereby executing the steps of any information processing method provided in any embodiment or any optional implementation manner in the embodiments of the present application.

[0447] Furthermore, the processor 6001 may be a Field-Programmable Gate Array (FPGA) or other devices with logic processing capabilities, such as a Microcontroller Unit (MCU) or a Central Process Unit (CPU).

[0448] The application of the embodiments of the present application has at least the following beneficial effects:

[0449] It achieves dynamic configuration of different coverage levels, saving energy while improving system capacity and performance.

[0450] Based on the same inventive concept, an embodiment of the present application also provides another computer-readable storage medium, which stores a computer program, which is used to implement the steps of any information processing method provided by any embodiment or any optional implementation method in the embodiment of the present application when executed by a processor.

[0451] The computer-readable storage medium provided in the embodiments of the present application includes, but is not limited to, any type of disk (including floppy disk, hard disk, optical disk, CD-ROM, and magneto-optical disk), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card or optical card. That is, the readable storage medium includes any medium that can store or transmit information in a readable form by a device (e.g., a computer).

[0452] The application of the embodiments of the present application has at least the following beneficial effects:

[0453] It achieves dynamic configuration of different coverage levels, saving energy while improving system capacity and performance.

[0454] Those skilled in the art will appreciate that each block in these structure diagrams and / or block diagrams and / or flow charts and combinations of blocks in these structure diagrams and / or block diagrams and / or flow charts can be implemented using computer program instructions. Those skilled in the art will appreciate that these computer program instructions can be provided to a general-purpose computer, a professional computer, or a processor of other programmable data processing methods to implement, thereby executing the scheme specified in the block or multiple blocks of the structure diagrams and / or block diagrams and / or flow charts disclosed in this application through the processor of the computer or other programmable data processing method.

[0455] Those skilled in the art will appreciate that the various operations, methods, steps, measures, and schemes in the processes discussed in this application may be alternated, altered, combined, or deleted. Further, other steps, measures, and schemes in the various operations, methods, and processes discussed in this application may also be alternated, altered, rearranged, decomposed, combined, or deleted. Further, the steps, measures, and schemes in the prior art that are similar to those disclosed in this application may also be alternated, altered, rearranged, decomposed, combined, or deleted.

[0456] The above description is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method performed by a first network node, characterized in that include: receiving information related to a second network node; Determine, based on the information related to the second network node, service distribution related information of the user equipment corresponding to each coverage characteristic at the first time; predicting, based on the service distribution related information of the user equipment at the first time, the service distribution related information of the user equipment at a second time after the first time; Determine, based on the service distribution related information of the user equipment at the second time, a first resource configuration corresponding to the coverage category related to the second network node; The first resource configuration is sent to the second network node.

2. The method according to claim 1, characterized in that Also includes: Receiving service information sent by an external server, the service information including location information of each user device and feature information of each user device; wherein the location information includes at least one of a location parameter of the user device provided by the positioning server and a flight trajectory parameter provided by the positioning server, and the feature information includes at least one of a service cycle and a periodic reporting time; According to the information and the service information, information related to service distribution of user equipment corresponding to each coverage characteristic at the first time is determined.

3. The method according to claim 2, characterized in that The information includes at least one of measurement information of the second network node and configuration information of the second network node; The measurement information includes at least one of signal strength data, service data, and performance data; The configuration information includes at least one of a coverage category threshold configuration for coverage category division and a resource configuration parameter corresponding to each coverage category; The coverage category threshold is configured as a coverage characteristic index value, and the coverage characteristic index value is used to divide the coverage area into different coverage categories.

4. The method according to claim 3, characterized in that The determining, based on the information related to the second network node, information related to service distribution of user equipment corresponding to each coverage characteristic at a first time includes: Determine, according to the service data and the service information, distribution information of user equipment having services to be sent and needing to access the second network node at a first time; Determining access capacity of a random access channel RACH corresponding to different configuration information according to the performance data and the configuration information; The service distribution related information at the first time includes: the distribution information and the access capacity of the RACH corresponding to the different configuration information.

5. The method according to claim 1, characterized in that The predicting, based on the service distribution related information of the user equipment at the first time, service distribution related information of the user equipment at a second time after the first time includes: Inputting the service distribution related information of the user equipment in N service cycles into a preset prediction model, predicting the service distribution related information of the user equipment at a second time after the first time by using the prediction model, and obtaining the time distribution of the capacity of the services corresponding to each coverage characteristic in the first cycle after the N service cycles; Among them, the first time includes N service cycles, the second time includes the first cycle, the service distribution related information of the user equipment at the first time is used to characterize the distribution of the capacity of the services corresponding to each coverage characteristic in the N service cycles over time, and the service distribution related information of the user equipment at the second time is used to characterize the distribution of the capacity of the services corresponding to each coverage characteristic in the first cycle over time, and N is a positive integer.

6. The method according to claim 1, characterized in that The determining, based on the service distribution related information of the user equipment at the second time, a first resource configuration corresponding to the coverage category related to the second network node includes: Determine, according to the service distribution related information of the user equipment at the second time, the coverage category thresholds corresponding to the respective coverage categories; A first resource configuration corresponding to the coverage category associated with the second network node is determined according to the service distribution related information of the user equipment at the second time and the coverage category thresholds respectively corresponding to the coverage categories.

7. The method according to claim 6, characterized in that The determining, according to the service distribution related information of the user equipment at the second time and the coverage category thresholds corresponding to the respective coverage categories, a first resource configuration corresponding to the coverage category related to the second network node includes: Determine, according to the coverage category thresholds corresponding to the coverage categories, the number of transmission repetitions of the resources of the user equipment corresponding to the coverage categories and the modulation and coding strategy MCS configuration of the resources, wherein the resources include at least one of a physical downlink control channel PDCCH, a physical downlink shared channel PDSCH, a physical uplink shared channel PUSCH, and uplink control information UCI; Determine the number of the coverage categories and the number of user equipments corresponding to the coverage categories respectively according to the service distribution related information of the user equipment at the second time and the coverage category thresholds respectively corresponding to the coverage categories; According to the number of user equipment corresponding to each coverage category and the access capacity of the RACH corresponding to the configuration information of the second network node included in the information, determine the second resource configuration of the RACH corresponding to each coverage category, the first resource configuration corresponding to the coverage category includes the coverage category threshold of the user equipment corresponding to each coverage category, the number of transmission repetitions of the resource, the MCS configuration of the resource, and the second resource configuration of the RACH corresponding to each coverage category, the second resource configuration of the RACH includes at least one of the number of transmission retransmissions of the random access preamble code, the number of RACH subcarriers, and the RACH period.

8. The method according to claim 7, characterized in that The method further includes: When the number of the coverage categories and the coverage category thresholds respectively corresponding to the coverage categories change, adjusting the number of transmission repetitions of the resources of the user equipment respectively corresponding to the coverage categories and the modulation and coding strategy MCS configuration of the resources; Or after determining the number of the coverage categories and the coverage category thresholds respectively corresponding to the coverage categories, the number of transmission repetitions of the resources of the user equipment respectively corresponding to the coverage categories and the modulation and coding strategy MCS configuration of the resources are adjusted.

9. The method according to claim 8, characterized in that The adjusting the number of transmission repetitions of the resources of the user equipment corresponding to each coverage category includes at least one of the following: Adjusting the number of transmission repetitions of the PDCCH, wherein the adjustment of the number of transmission repetitions of the PDCCH includes adjusting the number of transmission repetitions of at least one of message msg2, message msg3, and message msg4 in the common search space, and adjusting the number of transmission repetitions of the dedicated search space; Adjust the number of transmission repetitions of the PDSCH, wherein the adjustment of the number of transmission repetitions of the PDSCH includes at least one of the adjustment of the number of transmission repetitions of the PDSCH carrying the message msg2, the adjustment of the number of transmission repetitions of the PDSCH carrying the message msg4, and the adjustment of the number of transmission repetitions of the PDSCH carrying downlink signaling and data in the connected state; Adjusting the number of transmission repetitions of the PUSCH, wherein the adjustment of the number of transmission repetitions of the PUSCH includes at least one of adjusting the number of transmission repetitions of the PUSCH carrying the message msg3 and adjusting the number of transmission repetitions of the PUSCH carrying uplink signaling and data in a connected state; The transmission repetition number of the uplink control information UCI is adjusted, and the adjustment of the transmission repetition number of the UCI includes at least one of the adjustment of the transmission repetition number of the PUSCH carrying the downlink transmission ACK and / or NACK and the adjustment of the PUCCH carrying the downlink transmission ACK and / or NACK.

10. The method according to claim 8, characterized in that The adjusting of the MCS configuration of the resources of the user equipment corresponding to each coverage category includes at least one of the following: Adjust the MCS configuration of the PDSCH, wherein the adjustment of the MCS configuration of the PDSCH includes at least one of the following: adjusting the MCS configuration of the PDSCH carrying message msg2, adjusting the MCS configuration of the PDSCH carrying message msg4, and adjusting the MCS configuration of the PDSCH carrying downlink signaling and data in a connected state; The MCS configuration of the PUSCH is adjusted, and the adjustment of the MCS configuration of the PUSCH includes at least one of the adjustment of the MCS configuration of the PUSCH carrying the message msg3 and the adjustment of the MCS configuration of the PUSCH carrying uplink signaling and data in the connected state.

11. The method according to claim 1, characterized in that: The receiving information sent by the second network node includes at least one of the following: receiving information related to the second network node sent by the service management and orchestration SMO; Receive information related to the second network node sent by a quasi real-time RAN intelligent controller Near-RT RIC, wherein the information related to the second network node is obtained by the Near-RT RIC from the second network node.

12. The method according to claim 1, characterized in that The sending the first resource configuration to the second network node comprises one of the following: sending the first resource configuration to the second network node; Sending the first resource configuration to a quasi real-time RAN intelligent controller Near-RT RIC, wherein the Near-RT RIC sends the first resource configuration to the second network node; The first resource configuration is sent to the second network node through the Near-RT RIC.

13. The method according to any one of claims 1 to 12, characterized in that: The first network node includes a non-real-time RAN intelligent controller Non-RT RIC or a quasi-real-time RAN intelligent controller Near-RT RIC.

14. The method according to claim 1, characterized in that The receiving information related to the second network node includes: receiving first information related to a coverage level of the base station from at least one of a base station or an external server; The method further comprises: receiving second information related to the user equipment sent by the external server; Determine, based on the first information and the second information, service distribution related information of a cell of a base station serving the user equipment, where the service distribution related information includes distribution information of user equipment based on coverage level distribution; The determining, based on the service distribution related information of the user equipment at the second time, a first resource configuration corresponding to the coverage category related to the second network node includes: Based on the service distribution information, determine the coverage level configuration used at the second time, the coverage level configuration including at least one of the coverage levels of the cell or the threshold for coverage level division, and determine the resource configuration corresponding to each coverage level of the cell.

15. The method according to claim 14, characterized in that The business distribution related information also includes: Distribution information of service delay based on the coverage level distribution, distribution information of service throughput based on the coverage level allocation, or distribution information of service events based on the coverage level distribution.

16. The method according to claim 14, characterized in that The first information related to the coverage level of the base station includes: A coverage level configuration, the coverage level configuration comprising a threshold for coverage level division determined for the base station at the first time; and A resource configuration corresponding to each coverage level determined by the base station at the first time.

17. The method according to claim 14, characterized in that The second information related to the user equipment includes: the received signal strength determined by the user equipment at the first time, the location information related to the user equipment determined by the external server at the first time, and the characteristic information related to the user equipment determined by the external server at the first time, and the characteristic information related to the user equipment includes a service time period and a periodic reporting time.

18. The method according to claim 14, characterized in that The determining, based on the first information and the second information, service distribution information of a cell of a base station serving the terminal includes: Determining distribution information of user equipment based on the coverage level distribution at a first time; An access capacity of a random access channel (RACH) associated with the base station is determined.

19. The method according to claim 14, characterized in that The base station includes: Open Radio Access Network O-RAN control unit control plane O-CU-CP, O-RAN control unit user plane O-CU-UP and O-RAN data unit O-DU.

20. The method according to any one of claims 1 to 19, characterized in that: The user equipment is an IoT terminal.

21. A network node, comprising: processor; as well as A memory configured to store machine-readable instructions, wherein when the instructions are executed by the processor, the processor performs the method according to any one of claims 1 to 20.

22. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and the computer program is used to implement the method according to any one of claims 1 to 20 when executed by a processor.

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