Spectrum resource allocation method, device, equipment, medium and program product

Abstract

The invention provides a spectrum resource allocation method and device, equipment, a medium and a program product, and relates to the field of communication. The method is applied to a base station and specifically comprises the steps that load information of a passive Internet of Things terminal in a coverage area of the base station is acquired, and the passive Internet of Things terminal reflects information to the base station based on a carrier signal provided by external equipment; obtaining channel state information of an uplink from an active Internet of Things terminal to the base station according to a reference signal sent by the active Internet of Things terminal in the coverage area of the base station; according to the load information and the channel state information, a resource block allocation table of downlink spectrum resources of the base station in the next time slice is determined, the resource block allocation table comprises allocation information of resource blocks by all the Internet of Things terminals, and the Internet of Things terminals comprise passive Internet of Things terminals and active Internet of Things terminals. According to the scheme provided by the invention, the problems of limited spectrum utilization rate and insufficient flexibility of a spectrum resource allocation method in the prior art can be solved.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a spectrum resource allocation method, apparatus, device, medium, and program product. Background Technology

[0002] With the widespread adoption of Passive Internet of Things (PIoT) tags in warehousing, logistics, and other scenarios, their battery-free nature significantly reduces deployment and maintenance costs. However, the massive concurrent access of PIoT tags further exacerbates the already strained supply and demand imbalance of licensed spectrum resources in cellular networks (base stations). To address this issue, existing technologies (such as In-band mode) attempt to reuse LTE frequency bands, but this inevitably leads to co-channel interference with primary cellular services. Traditional spectrum resource management methods, whether centralized decision-making (reporting-decision-issuance), fixed allocation, or coarse-grained dynamic adjustment, are all inadequate in the complex and ever-changing IoT environment. Specifically, traditional spectrum resource management methods suffer from the following main drawbacks: 1. Limited spectrum utilization. Traditional mechanisms cannot match spectrum resources in real time with service fluctuations, resulting in both spectrum idleness and conflicts. During specific periods or regions, some frequency bands are over-occupied, leading to hotspot spectrum overload; while adjacent or different frequency bands remain idle for extended periods, resulting in fragmented spectrum idleness. This structural waste has resulted in overall spectrum utilization remaining low for a long time.

[0003] 2. Insufficient flexibility. On the one hand, traditional centralized decision-making or coarse-grained dynamic adjustment mechanisms typically have a closed-loop cycle of second-level scheduling links (reporting-decision-distribution), which is difficult to match the millisecond-level transient energy capture characteristics of passive IoT tags. On the other hand, this slow response mechanism cannot respond in real time to rapid fluctuations in business needs and millisecond-level environmental changes such as instantaneous interference caused by tag movement, making it difficult to adapt to complex and diverse IoT business scenarios. Summary of the Invention

[0004] This application provides a spectrum resource allocation method, apparatus, device, medium, and program product, which at least solves the technical problems of limited spectrum utilization and insufficient flexibility in existing spectrum resource allocation methods.

[0005] In a first aspect, embodiments of this application provide a spectrum resource allocation method applied to a base station, the method comprising: The load information of passive IoT terminals within the coverage area of ​​the base station is obtained, and the passive IoT terminals reflect the information to the base station based on carrier signals provided by external devices; Based on the reference signals sent by active IoT terminals within the coverage area of ​​the base station, the channel state information of the uplink from the active IoT terminal to the base station is obtained. Based on the load information and the channel state information, a resource block allocation table for the downlink spectrum resources of the base station in the next time slice is determined. The resource block allocation table includes the allocation information of each IoT terminal for the resource blocks. The IoT terminals include passive IoT terminals and active IoT terminals.

[0006] Secondly, embodiments of this application provide a spectrum resource allocation device deployed in a base station, the device comprising: The first acquisition module is used to acquire the load information of passive IoT terminals within the coverage area of ​​the base station, wherein the passive IoT terminals reflect the information to the base station based on carrier signals provided by external devices; The second acquisition module is used to acquire the channel state information of the uplink from the active IoT terminal to the base station based on the reference signal sent by the active IoT terminal in the coverage area of ​​the base station. The determination module is used to determine the resource block allocation table of the downlink spectrum resources of the base station in the next time slice based on the load information and the channel state information. The resource block allocation table includes the allocation information of each IoT terminal for the resource blocks. The IoT terminals include passive IoT terminals and active IoT terminals.

[0007] Thirdly, embodiments of this application provide an electronic device, including a processor and a memory storing a computer program, wherein the processor executes the program to implement the steps of the spectrum resource allocation method described in the first aspect.

[0008] Fourthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the spectrum resource allocation method described in the first aspect.

[0009] Fifthly, embodiments of this application provide a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the spectrum resource allocation method described in the first aspect.

[0010] The spectrum resource allocation method of this application first obtains the load information of passive IoT terminals within the coverage area of ​​the base station, wherein the passive IoT terminals reflect information to the base station based on carrier signals provided by external devices; then, based on reference signals sent by active IoT terminals within the coverage area of ​​the base station, the channel state information of the uplink from the active IoT terminals to the base station is obtained; finally, based on the load information and the channel state information, a resource block allocation table for the downlink spectrum resources of the base station in the next time slice is determined, wherein the resource block allocation table includes allocation information for resource blocks by each IoT terminal, and the IoT terminals include passive IoT terminals and active IoT terminals. The method provided by this application has at least the following technical effects: First, it significantly improves spectrum utilization and solves the problem of limited spectrum utilization. This application can accurately perceive the actual needs and channel status of each IoT terminal by obtaining real-time load information and channel status information. This makes the generated resource block allocation table no longer static, but a precise match tailored to each IoT terminal for the next time slice. This allows the base station to inject fragmented spectrum resources into the resource block allocation table, avoiding over-allocation of spectrum resources in areas with poor channel status or low load, thereby greatly improving spectrum utilization.

[0011] Secondly, it greatly enhances system flexibility and solves the problem of insufficient flexibility. This application obtains channel state information based on reference signals sent by active IoT terminals and determines the resource block allocation table for the next time slice, constructing a millisecond-level fast response scheduling closed loop. When the load information of passive IoT terminals changes abruptly, or when the channel state information of active IoT terminals jitters instantaneously, the base station can detect it in a very short time and immediately adjust the resource block allocation strategy within the upcoming next time slice (millisecond level). This agile response capability can completely solve the latency and rigidity problems caused by traditional second-level scheduling, enabling the system to respond to environmental changes in real time and meet the millisecond-level dynamic requirements of passive IoT. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart illustrating a spectrum resource allocation method according to an embodiment of this application; Figure 2 This is a structural block diagram of a spectrum resource allocation device shown in an embodiment of this application; Figure 3 This is a schematic diagram of the physical structure of an electronic device as shown in an embodiment of this application. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0015] With the widespread adoption of Passive Internet of Things (PIoT) tags in warehousing, logistics, and other scenarios, their battery-free nature significantly reduces deployment and maintenance costs. However, the concurrent access of massive numbers of PIoT tags further exacerbates the already strained supply and demand imbalance of licensed spectrum resources in cellular networks (base stations). In-band mode, a traditional spectrum resource management solution, refers to PIoT tags not using dedicated spectrum but sharing and overlapping (i.e., reusing) existing LTE licensed frequency bands with cellular main services such as mobile phones. While In-band mode allows PIoT tags to directly reuse LTE network frequency bands, its rigid occupation of Physical Resource Blocks (PRBs) inevitably leads to co-channel interference with cellular main services, resulting in decreased communication reliability. Therefore, 3GPPAIOTSI (Cellular Internet of Things Research Project) has prioritized dynamic spectrum sharing as a key research area, aiming to achieve more granular intelligent scheduling at the time slot level within licensed frequency bands to improve spectrum reuse efficiency.

[0016] Regarding the spectrum requirements of passive IoT systems, both the downlink and uplink must meet specific data rates and power budgets. According to 3GPP TR38.827, passive IoT tags must ensure that the downlink occupies at least 4 PRBs (720kHz) and supports 26dBm of reflected power; the uplink requires 7 PRBs (1.26MHz) to achieve a rate of 100kbps (including 15% FEC). If a Frequency Division Multiple Access (FDMA) architecture is further adopted, additional guard bands must be reserved and terminal frequency hopping must be supported, which undoubtedly further increases spectrum overhead. 3GPP TR38.821 measurements show that when tag density > At that time, static physical resource block allocation can lead to co-channel interference, and the bit error rate in interference scenarios is greater than 100%. (37% higher than in interference-free scenarios), channel capacity decreased by 4%, making it difficult to adapt to scenarios with massive passive IoT tag access. Passive IoT systems include passive IoT terminals, relay devices, and base stations.

[0017] Traditional spectrum resource management methods, whether centralized decision-making (reporting-decision-distribution), fixed allocation, or coarse-grained dynamic adjustment, cannot adapt to two characteristics of passive IoT tags: first, the transient nature of energy capture, meaning the tags have no batteries and can only operate and reflect signals for a very short instant (millisecond-level energy window) after capturing radio frequency energy; second, the tidal nature of service demand, meaning the communication needs of tags are extremely uneven, potentially resulting in massive concurrent access in an instant or prolonged periods of silence. Furthermore, when tags move or the environment changes, millisecond-level transient interference occurs, while the decision-making chain of traditional spectrum resource management methods takes up to seconds, making it impossible to respond to such rapid changes in real time. In summary, traditional spectrum resource management methods suffer from at least the following problems: First, spectrum utilization is limited: hot spot spectrum overload and fragmented spectrum idleness coexist. That is, in a specific period or region, some frequency bands are over-occupied, while adjacent or different frequency bands are idle for a long time, resulting in a long-term low spectrum utilization rate.

[0018] Second, insufficient flexibility: Traditional centralized decision-making or coarse-grained dynamic adjustment mechanisms typically have a closed-loop scheduling cycle of seconds, which is difficult to match the millisecond-level energy window of passive IoT tags. They cannot respond in real time to fluctuations in business needs and changes in the environment, and are difficult to adapt to complex and diverse IoT business scenarios.

[0019] Third, weak anti-interference capability: When a large number of devices communicate concurrently, the fixed allocation mechanism or coarse-grained dynamic adjustment mechanism lacks effective coordination means, which can easily induce co-channel or adjacent-channel interference, directly reducing communication quality and the stability of the entire Internet of Things system.

[0020] Fourth, high energy consumption: Active IoT terminals need to continuously transmit reference signals, which results in high power consumption of active IoT terminals, leading to high uplink energy consumption.

[0021] Fifth, poor scenario adaptability: Using a fixed threshold to trigger spectrum resource management actions cannot cope with the sudden density changes of passive IoT tags. For example, when the tag density suddenly increases, the fixed threshold is set too high, causing the system to only trigger a response long after the congestion occurs; or when the tag density suddenly decreases, the fixed threshold is set too low, causing the system to release shared bandwidth prematurely.

[0022] To address the aforementioned issues, this application provides a spectrum resource allocation method for cellular passive IoT, applied to a base station. Cellular passive IoT is a system architecture designed to integrate passive IoT technology with cellular mobile communication networks (e.g., 5G, 6G). Its core objective is to leverage the wide coverage, high reliability, and deployed infrastructure advantages of cellular networks (base stations) to empower a massive number of passive IoT terminals. In this architecture, the cellular network not only serves traditional active IoT terminals but also acts as a reader / writer and power source for passive IoT terminals: the base station transmits high-power signals to power the passive IoT terminals and provides the incident carrier; the passive IoT terminals reflect data back to the base station via backscattering.

[0023] The following section will describe in detail how this application addresses the five issues mentioned above step by step.

[0024] Figure 1 This is a flowchart illustrating a spectrum resource allocation method according to an embodiment of this application. (Refer to...) Figure 1 The method of this application includes the following steps: Step S101: Obtain the load information of passive IoT terminals within the coverage area of ​​the base station. The passive IoT terminals reflect information to the base station based on the carrier signal provided by the external device.

[0025] In this embodiment, an IoT terminal refers to a physical device deployed in the physical world to implement IoT functions. IoT terminals include passive IoT terminals and active IoT terminals.

[0026] Passive IoT terminals can be, for example, passive IoT tags, whose key feature is that they do not rely on built-in batteries to complete their communication tasks. The working stages of a passive IoT terminal include: (1) energy capture: capturing energy from the surrounding environment (e.g., capturing energy from radio frequency signals emitted by external devices) and converting it into DC power required for operation; (2) information reflection: not actively generating radio frequency carriers during communication, but modulating and reflecting carrier signals emitted by external devices by changing the impedance characteristics of its own antenna.

[0027] The external device can be either a base station or a relay device. The external device continuously broadcasts radio frequency signals. The energy captured by the passive IoT terminal can be expressed using the following formula: in, It is the energy captured by the passive IoT terminal; It refers to the transmission power of external devices; It refers to the physical distance between the passive IoT terminal and the external device; The path loss index describes the rate attenuation of radio frequency energy as it propagates in a specific environment.

[0028] In this embodiment, the load information includes the number of passive IoT terminals, the energy capture efficiency of the passive IoT terminals, and the service arrival rate of the passive IoT terminals. Energy capture efficiency measures the ability of a passive IoT terminal to convert the energy of its received radio frequency signals into usable DC power. Service arrival rate describes the amount of data requested by the passive IoT terminals per unit time.

[0029] In this embodiment, the relay device can obtain the load information of each passive IoT terminal in the coverage area of ​​the base station in real time, convert these load information into vectors (hereinafter referred to as PIoT load vectors), and finally report the obtained vectors to the base station.

[0030] Step S102: Based on the reference signals sent by active IoT terminals within the coverage area of ​​the base station, obtain the channel state information of the uplink from the active IoT terminal to the base station.

[0031] In this embodiment, the active IoT terminal can be, for example, a smartphone, whose key feature is that it relies on a built-in power source to maintain its computing, sensing, and communication functions. In terms of communication, the active IoT terminal has a complete radio frequency transceiver, capable of actively generating and transmitting radio frequency signals according to a protocol to establish a connection with the base station and transmit data.

[0032] In this embodiment, each active IoT terminal within the coverage area of ​​the base station periodically transmits a reference signal (RS) in the uplink. After receiving the reference signal, the base station obtains the uplink channel state information (CSI) by measuring the signal strength, phase, interference, etc. of the reference signal.

[0033] Step S103: Based on the load information and channel state information, determine the resource block allocation table of the downlink spectrum resources of the base station in the next time slice. The resource block allocation table includes the allocation information of each IoT terminal for the resource blocks.

[0034] Among them, resource blocks are physical resource blocks.

[0035] In this embodiment, after obtaining the uplink channel state information, the base station first predicts the downlink channel state information directly using the uplink channel state information based on the principle of channel reciprocity (i.e., the uplink and downlink physical channels have high consistency within the same frequency band during coherence time). Next, the base station predicts the downlink spectrum resource allocation table (PRB mapping table) for the next time slice based on the PIoT load vector representing load information and the downlink channel state information. The PRB mapping table includes the allocation information of physical resource blocks for each IoT terminal; in other words, based on the PRB mapping table, it can be determined which portion of physical resource blocks each IoT terminal will use in the next time slice.

[0036] Steps S101-S103 above describe how the base station allocates downlink spectrum resources for the next time slice within the current time slice. In actual implementation, the allocation principle of the base station for downlink spectrum resources in the next time slice within each time slice is the same as the allocation principle shown in steps S101-S103 above. The size of the time slice can be set according to actual needs.

[0037] The spectrum resource allocation method provided in this application has at least the following technical advantages: First, it significantly improves spectrum utilization and solves the problem of limited spectrum utilization. This application can accurately perceive the actual needs and channel status of each IoT terminal by obtaining real-time load information and channel status information. This makes the generated resource block allocation table no longer static, but a precise match tailored to each IoT terminal for the next time slice. This allows the base station to inject fragmented spectrum resources into the resource block allocation table, avoiding over-allocation of spectrum resources in areas with poor channel status or low load, thereby greatly improving spectrum utilization.

[0038] Secondly, it greatly enhances system flexibility and solves the problem of insufficient flexibility. This application obtains channel state information based on reference signals sent by active IoT terminals and determines the resource block allocation table for the next time slice, constructing a millisecond-level fast response scheduling closed loop. When the load information of passive IoT terminals changes abruptly, or when the channel state information of active IoT terminals jitters instantaneously, the base station can detect it in a very short time and immediately adjust the resource block allocation strategy within the upcoming next time slice (millisecond level). This agile response capability can completely solve the latency and rigidity problems caused by traditional second-level scheduling, enabling the system to respond to environmental changes in real time and meet the millisecond-level dynamic requirements of passive IoT.

[0039] In conjunction with the above embodiments, in one implementation, step S103 may include: Step S1031: Based on the principle of channel reciprocity, determine the channel quality of the downlink from the base station to the active IoT terminal according to the channel state information.

[0040] In this embodiment, after obtaining the uplink channel state information, the base station not only predicts the downlink channel state information based on the principle of channel reciprocity, but also predicts the downlink channel quality indicator (CQI) based on the uplink channel state information.

[0041] Step S1032: Based on the load information, channel state information, and channel quality, determine the resource block allocation table for the downlink spectrum resources of the base station in the next time slice.

[0042] In step S1032, the base station predicts the resource block allocation table of downlink spectrum resources for the next time slice based on the PIoT load vector representing load information, the channel state information of the downlink, and the channel quality of the downlink.

[0043] In this embodiment, the base station introduces downlink channel quality based on the PIoT load vector and downlink channel state information. When the channel quality is higher than a preset quality (higher channel quality), the number of resource blocks in the link with the active IoT terminal is increased, and the modulation order of the signal transmitted to the active IoT terminal is increased to maximize data throughput. Conversely, when the channel quality is lower than the preset quality (lower channel quality), the number of resource blocks in the link with the active IoT terminal is reduced, and the modulation order of the signal transmitted to the active IoT terminal is decreased, thus prioritizing the robustness and reliability of the link. Through this mechanism, this embodiment can deeply integrate the traffic requirements of the service side with the physical layer's carrying capacity, thereby obtaining a higher-quality resource block allocation table.

[0044] In one implementation, in conjunction with the above embodiments, step S1032 may include: While meeting the data transmission rate requirements and maximum power level requirements for interference tolerance of each IoT terminal, and with the goal of minimizing the total transmit power consumed when allocating all resource blocks, the resource block allocation table for the downlink spectrum resources of the base station in the next time slice is determined based on load information, channel state information, and channel quality.

[0045] In this embodiment, the total transmit power consumed when allocating all resource blocks can be expressed as: ,in, This indicates the total number of physical resource blocks in the downlink spectrum resources of the next time slice.

[0046] Meeting the data transmission rate requirements of each IoT terminal means that the data transmission rate of each IoT terminal needs to be greater than the data transmission rate of the IoT terminal. , This refers to the minimum data transmission rate that the system must guarantee to meet the business needs of specific IoT terminals. The system in this application includes base stations, IoT terminals, and relay equipment.

[0047] Meeting the maximum power level requirement for interference tolerance of each IoT terminal means that the maximum power level of interference tolerance of each IoT terminal must be less than [the specified value]. . This refers to the upper limit of interference tolerance set by the system to ensure that the communication quality does not deteriorate.

[0048] In this embodiment, by treating the data transmission rate requirements of each IoT terminal as a hard constraint, service quality under different business scenarios can be guaranteed, ensuring that critical tasks are not interrupted due to resource constraints. Simultaneously, incorporating the maximum power level tolerable interference into the constraint effectively avoids link degradation caused by co-channel interference, enhancing communication robustness. Based on this, with minimizing total transmit power as the core optimization objective, a multi-dimensional joint solution combining real-time load information and channel state can quickly generate an optimal resource block allocation table for the next time slice. This mechanism enables on-demand dynamic allocation of physical layer resources at the millisecond level, significantly reducing overall system energy consumption while greatly improving spectrum utilization efficiency.

[0049] In conjunction with the above embodiments, in one implementation, this application, addressing diverse scenario requirements and demands for spectrum continuity, device compatibility, and real-time communication, can further divide available spectrum resources into three resource pools according to service type, spectrum characteristics, and real-time requirements, from high to low: (1) Advanced Resource Pool: This pool aggregates spectrum resources with good frequency domain continuity and low interference levels. Advanced resources can effectively support high data rate transmission and low latency communication, and can be used to carry mission-critical services with extremely high quality of service requirements, such as emergency rescue and industrial automation control. In addition, advanced resources have elastic scheduling capabilities. When resources within the pool are scarce, the system allows it to dynamically borrow resources from the lower-level resource pool to prioritize the continuity of critical services.

[0050] (2) Intermediate resource pool: Suitable for carrying services that require a certain level of real-time performance but can tolerate a small amount of latency, such as high-definition video transmission and intelligent transportation systems. In addition, the intermediate resource pool has a flexible resource management mechanism. When resources are scarce, by appropriately adjusting the resource allocation ratio (for example, reducing the proportion of resources during non-critical periods), it can prioritize ensuring that the basic communication performance of the service is not affected.

[0051] (3) Low-level resource pool: Used to aggregate scattered or fragmented spectrum resources. Although these resources have weak physical continuity, they can still effectively meet the basic communication requirements of low power consumption and low data volume. Therefore, they are suitable for carrying services with low tolerance for real-time and data rate requirements, such as IoT sensor data acquisition, environmental monitoring, and periodic inventory. In terms of resource scheduling strategy, the low-level resource pool follows the principle of residual allocation, that is, only after the system has prioritized meeting the resource needs of the high-level and mid-level resource pools will the remaining idle spectrum resources be allocated to the low-level resource pool.

[0052] In this embodiment, all physical resource blocks in the high-level resource pool are marked with a first-level identifier, all physical resource blocks in the mid-level resource pool are marked with a second-level identifier, and all physical resource blocks in the low-level resource pool are marked with a third-level identifier. The physical resource blocks marked with a first-level identifier have a higher level than those marked with a second-level identifier, and the physical resource blocks marked with a second-level identifier have a higher level than those marked with a third-level identifier.

[0053] Therefore, based on the above division of the three types of resource pools, it can be considered that the downlink spectrum resources of this application include multiple resource blocks, each carrying a level identifier. Based on this, step S1032 may include: Determine the service type corresponding to each IoT terminal in the next time slice; Under the premise of meeting the data transmission rate requirements of each IoT terminal, the maximum power level requirements for interference tolerance, and the constraints between service type and level identifier, with the goal of minimizing the total transmit power consumed when allocating all resource blocks, the resource block allocation table of the base station's downlink spectrum resources in the next time slice is determined based on load information, channel state information, and channel quality.

[0054] In this embodiment, the constraint relationship between service type and level identifier is: what level identifier the physical resource block used by the service type has.

[0055] This embodiment takes into account that some IoT terminal services may require the use of physical resource blocks marked with specific level identifiers. For example, emergency rescue services require physical resource blocks marked with a first-level identifier, while high-definition video transmission services require physical resource blocks marked with a second-level identifier. Therefore, when planning the resource block allocation table for downlink spectrum resources in the next time slice, the mapping relationship between service type and resource block level identifiers is established as a hard constraint in the scheduling process. This ensures that IoT terminals with special communication needs (such as the extremely low latency required for emergency rescue or the high bandwidth required for high-definition video) can deterministically acquire specific level spectrum resources with the most suitable physical attributes (such as good continuity, low interference, or abundant resources). This mechanism can effectively avoid performance bottlenecks caused by resource mismatch (such as the misuse of fragmented frequency bands for critical tasks), thereby ensuring the communication reliability and real-time performance of mission-critical services in complex electromagnetic environments.

[0056] In conjunction with the above embodiments, in one implementation, the method of this application further includes: Based on channel state information and historical traffic data generated by base stations, determine the spectrum resource requirements of IoT terminals in future time slices; Based on the spectrum resource requirements, determine the downlink spectrum resources for the next time slice.

[0057] In this embodiment, the base station obtains uplink channel state information in real time and determines downlink channel state information in real time based on the uplink channel state information. Then, the downlink channel state information and historical traffic data are input into the prediction model to obtain a refined spectrum demand curve for IoT terminals in future time slices. The prediction model uses a linear regression algorithm to capture the linear trend of the input data and a Long Short-Term Memory (LSTM) network to mine nonlinear temporal dependencies, thereby obtaining accurate prediction information. The prediction model at least in advance... Output the spectrum demand curve (e.g., 50-100ms). Then, based on the spectrum resource demand curve, the base station determines the downlink spectrum resources for the next time slice, and completes the configuration of the three types of resource pools in advance based on the determined downlink spectrum resources before the actual service traffic peak arrives.

[0058] In this embodiment, both the passive IoT terminals and the base station are equipped with miniature spectrum sensing modules. These modules are configured to scan the base station's coverage area synchronously with a millisecond-level time resolution, collecting triplet data representing spectrum quality: occupancy rate, interference level, and signal-to-noise ratio. The base station receives and aggregates the triplet data from each passive IoT terminal, creating a high-resolution spectrum heatmap in real time that reflects the electromagnetic environment of the base station's coverage area. This provides a visual representation of the dynamic distribution characteristics of spectrum resources in both spatial and temporal dimensions. Furthermore, the base station simultaneously acquires communication demand information from each IoT terminal, including parameters such as service rate, communication frequency, and priority. Finally, based on the deep fusion of communication demand information and the high-resolution spectrum heatmap, the base station establishes and maintains a spectrum usage status database that can be updated in seconds, providing data support for subsequent resource scheduling.

[0059] Therefore, in this embodiment, the base station can predict the spectrum resource requirements of IoT terminals in future time slices based on the spectrum usage status database, thereby obtaining a higher quality resource block allocation table.

[0060] In this embodiment, by predicting the spectrum resource demand of future time slices in advance, it can be ensured that the supply of spectrum resources always leads the fluctuation of service demand, thereby realizing zero-wait access for IoT terminals. This can fundamentally eliminate the access latency caused by traditional delayed scheduling, avoid instantaneous congestion caused by sudden service surges, and enhance the system's real-time response capability to dynamic spectrum demand.

[0061] In conjunction with the above embodiments, in one implementation, the downlink spectrum resources include passive IoT private bandwidth, shared bandwidth, and cellular communication private bandwidth, each of which includes multiple resource blocks.

[0062] In this embodiment, the downlink spectrum resources can also be divided into passive IoT private bandwidth, shared bandwidth, and cellular communication private bandwidth. Among them, the physical resource blocks in the passive IoT private bandwidth are only allocated to the services of passive IoT terminals, the physical resource blocks in the cellular communication private bandwidth can only be allocated to the services of active IoT terminals, and the physical resource blocks in the shared bandwidth can be allocated to the services of both passive and active IoT terminals.

[0063] In other words, in this embodiment, each physical resource block in the downlink spectrum resources has both a type identifier and a level identifier. The type identifier indicates which type it belongs to: passive IoT private bandwidth, shared bandwidth, or cellular communication private bandwidth. The level identifier indicates which of the three resource pools it belongs to.

[0064] In this embodiment, downlink spectrum resources are divided into passive IoT private bandwidth, shared bandwidth, and cellular communication private bandwidth, achieving an organic combination of resource isolation and flexible sharing. Passive IoT private bandwidth provides dedicated physical-level resource protection for passive IoT terminals, while cellular communication private bandwidth provides dedicated physical-level resource protection for active IoT terminals, effectively avoiding co-channel interference between basic services. Shared bandwidth breaks down the boundaries between different types of terminals, utilizing service tidal characteristics to achieve dynamic resource reuse, significantly improving spectrum utilization efficiency and system scheduling flexibility while ensuring communication reliability.

[0065] In conjunction with the above embodiments, in one implementation, this application also provides an interference coordination mechanism based on multi-dimensional collaboration. This mechanism is mainly applied to the data backhaul stage of the uplink to solve the problems of weak reflected signals of passive IoT terminals and susceptibility to interference from environmental noise and co-frequency devices.

[0066] Specifically, to comprehensively suppress interference, this embodiment deeply integrates physical layer technologies such as spectrum shaping and filtering, and on this basis, introduces a synchronous overlay scheme of Frequency-Hopping Spread Spectrum (FHSS) technology, Reed-Solomon error correction coding, and a power backoff mechanism. The FHSS frequency hopping sequence is dynamically generated and periodically updated by the relay device based on the real-time spatial location of the passive IoT terminal. This customized frequency hopping strategy, combined with the power backoff mechanism to suppress the intensity of sudden interference and the strong error correction capability of RS coding, can effectively isolate sudden interference and repair damaged data during transmission, significantly improving the robustness of the link and the reliability of communication.

[0067] In this application, a spectrum monitoring module is deployed in the relay equipment. The spectrum monitoring module continuously refreshes the interference level of the current frequency band at millisecond intervals and dynamically adjusts the interference coordination mechanism based on real-time monitoring results: when the system determines that the current environmental interference level is low, the existing interference coordination mechanism is maintained to reduce system overhead; once the interference level is detected to exceed the preset interference threshold, the system will immediately trigger the interference coordination mechanism adjustment scheme, actively avoiding interference by switching frequency hopping sequences, increasing power back-off, or enhancing coding redundancy, thereby ensuring that the cellular passive IoT can maintain a highly robust communication connection in complex electromagnetic environments.

[0068] In conjunction with the above embodiments, in one implementation, the method of this application may further include: Based on the historical throughput of the base station, the historical data transmission latency between the base station and the IoT terminal, and the energy capture efficiency of the passive IoT terminal, the strategy for generating the resource block allocation table is adjusted. The adjustment items include at least: the number of resource blocks carrying various level identifiers, and the constraint relationship between service type and level identifier.

[0069] In this embodiment, the base station refreshes the resource block allocation table in each time slice and evaluates the effectiveness of the resource block allocation table at preset intervals. Specifically, the base station performs a comprehensive analysis based on system operation data (such as the base station's historical throughput, historical data transmission latency between the base station and IoT terminals, and the energy capture efficiency of passive IoT terminals), and adjusts the strategy for generating the resource block allocation table based on the analysis results. If the evaluation result is good, the strategy used when generating the current resource block allocation table is not adjusted; otherwise, the strategy used when generating the current resource block allocation table is adjusted.

[0070] In addition to the various types of data listed above, system operation data can also include user feedback information, which can be set according to actual needs. Similarly, adjustment items can include the various types listed above, as well as parameters in interference coordination mechanisms and prediction models, which can be set according to actual needs.

[0071] In this embodiment, the strategy used to generate the resource block allocation table is adjusted based on the historical throughput of the base station, the historical data transmission latency between the base station and the IoT terminal, and the energy capture efficiency of the passive IoT terminal, which can effectively improve the quality of the subsequently generated resource block allocation table.

[0072] In conjunction with the above embodiments, in one implementation, the uplink spectrum resources of the base station include passive IoT private bandwidth and shared bandwidth. Accordingly, the method of this application may further include: Obtain the bandwidth utilization rate of the shared bandwidth in the uplink spectrum resources; If the bandwidth utilization rate of the shared bandwidth is less than the first utilization rate, the services of passive IoT terminals occupying resource blocks in the shared bandwidth will be migrated to resource blocks in the passive IoT private bandwidth for execution.

[0073] In this embodiment, the types of uplink spectrum resources also include passive IoT private bandwidth, shared bandwidth, and cellular communication private bandwidth.

[0074] When managing uplink spectrum resources, the base station monitors the bandwidth utilization rate of the shared bandwidth in real time. The bandwidth utilization rate of shared bandwidth = the number of physical resource blocks used in the shared bandwidth / the total number of physical resource blocks in the shared bandwidth. Once the bandwidth utilization rate of shared bandwidth is detected to be less than the first utilization rate... This indicates that there are many idle resource blocks in the shared bandwidth, and the shared bandwidth is in a low-load state. Subsequently, the base station determines that the passive IoT terminal cannot use the shared bandwidth, and smoothly migrates the services of the passive IoT terminal occupying the resource blocks in the shared bandwidth to the idle resource blocks in the passive IoT private bandwidth for execution, thereby actively releasing the shared bandwidth so that the shared bandwidth can be used to process the base station's main services (such as the services of active IoT terminals).

[0075] Among them, the first occupancy rate You can set it based on experience, for example, it can be 40%.

[0076] In this embodiment, when the shared bandwidth is under low load, the services of the passive IoT terminal are migrated to the passive IoT private bandwidth for execution, so that the shared bandwidth can handle more important base station services, thereby enabling the base station to have a strong scheduling capability when facing a surge in major service volume.

[0077] In conjunction with the above embodiments, in one implementation, the method of this application may further include: If the bandwidth occupancy rate of the shared bandwidth is greater than the second occupancy rate, or the interference level of the shared bandwidth is greater than the interference threshold, the services of passive IoT terminals occupying resource blocks in the shared bandwidth will be migrated to resource blocks in the passive IoT private bandwidth for execution, or the services of active IoT terminals occupying resource blocks in the shared bandwidth will be migrated to resource blocks in the cellular communication private bandwidth for execution, where the second occupancy rate is greater than the first occupancy rate.

[0078] In this embodiment, if the bandwidth utilization rate of the shared bandwidth is greater than the second utilization rate... Or, the level of interference in shared bandwidth. The power level to which interference can be tolerated is greater than the interference threshold. This indicates that the shared bandwidth utilization is too high or the interference level is too high. In this case, some services occupying physical resource blocks in the shared bandwidth can be migrated to other types of bandwidth. For example, services from passive IoT terminals occupying resource blocks in the shared bandwidth can be migrated to resource blocks in the passive IoT private bandwidth, or services from active IoT terminals occupying resource blocks in the shared bandwidth can be migrated to resource blocks in the cellular communication private bandwidth. During the migration, the base station can also dynamically adjust the transmission power based on the interference margin of other bandwidths. With modulation order (MCS), interference is further reduced.

[0079] Among them, the second occupancy rate You can set it based on experience, for example, it can be 85%.

[0080] In this embodiment, when the bandwidth occupancy rate of the shared bandwidth is too high or the interference level is too high, migrating part of the services occupying physical resource blocks in the shared bandwidth to other types of bandwidth can effectively alleviate spectrum pressure or reduce interference and ensure service continuity.

[0081] In conjunction with the above embodiments, in one implementation, the method of this application may further include: If the bandwidth utilization rate of the shared bandwidth is greater than the second utilization rate, or the interference level of the shared bandwidth is greater than the interference threshold; The distributed game mechanism determines the allocation information of resource blocks in the shared bandwidth for each passive IoT terminal that needs to occupy them.

[0082] In this embodiment, if the bandwidth occupancy rate of the shared bandwidth is greater than the second occupancy rate, or the interference level of the shared bandwidth is greater than the interference threshold, it is determined that the shared bandwidth is in a high load or high interference state. At this time, a distributed game between passive IoT terminals can be initiated, allowing each passive IoT terminal to compete for spectrum resources, thereby determining the allocation information of each passive IoT terminal that needs to occupy the resource blocks in the shared bandwidth.

[0083] Specifically, through a distributed game mechanism, the passive IoT terminals that need to occupy resource blocks in the shared bandwidth are determined. The allocation information for resource blocks in the shared bandwidth may include: Send a game-starting signal to each passive IoT terminal that needs to occupy a resource block in the shared bandwidth; The game initiation signal is used to instruct the first passive IoT terminal to broadcast a spectrum allocation request to the second passive IoT terminal, receive the response information of the second passive IoT terminal to the spectrum allocation request, determine the target resource block that needs to be occupied in the shared bandwidth based on the response information, and broadcast the information of the target resource block to the second passive IoT terminal. The first passive IoT terminal is any terminal among the passive IoT terminals that need to occupy the resource block in the shared bandwidth, and the second terminal is any terminal among the passive IoT terminals that need to occupy the resource block in the shared bandwidth except for the first terminal.

[0084] In this embodiment, at the start of the game, each passive IoT terminal performs the same operations as the first passive IoT terminal. This embodiment uses the first passive IoT terminal as an example for illustration, and specifically includes the following steps: (1) Broadcast spectrum allocation request: The first passive IoT terminal detects the spectrum usage in real time, extracts information on available frequency bands (i.e. available physical resource blocks), including but not limited to center frequency, bandwidth, signal strength and interference level, and then broadcasts a spectrum allocation request to the surrounding second passive IoT terminals. The request carries the ID, communication requirements, priority and available frequency band information of the first passive IoT terminal.

[0085] (2) Game-like bidding: The second passive IoT terminal, upon receiving the spectrum allocation request, generates response information based on its own needs and available frequency bands, and sends the response information to the first passive IoT terminal. The response information carries the suggested allocated frequency band, communication plan, etc.

[0086] (3) Conflict avoidance: The first passive IoT terminal selects an optimal frequency band (target resource block) for communication based on the received response information and its own communication needs and priorities. If there is a conflict between the frequency bands suggested by multiple second passive IoT terminals, the first passive IoT terminal will make a decision based on preset rules (such as priority, frequency band quality, etc.) and broadcast the information of the finally selected frequency band to the surrounding second passive IoT terminals.

[0087] (4) Result synchronization: After each second passive IoT terminal receives the information of the final selected frequency band broadcast by the first passive IoT terminal, it updates its own spectrum usage record to avoid communication on the same frequency band (i.e. avoid using the target resource block again), thereby realizing dynamic spectrum allocation and conflict avoidance.

[0088] In this application, when the bandwidth occupancy rate of the shared bandwidth is too high or the interference level is too large, some services occupying physical resource blocks in the shared bandwidth can be migrated to other types of bandwidth first, as described above. After the migration, the allocation information of each passive IoT terminal that needs to occupy resource blocks in the shared bandwidth is determined through a distributed game mechanism. That is, the two methods can be combined to improve the flexibility of spectrum resource management.

[0089] In this embodiment, firstly, the decision-making power for resource allocation is decentralized from the base station to the passive IoT terminals. Each passive IoT terminal autonomously competes and negotiates, eliminating the need to wait in line for complex centralized global scheduling by the base station. This significantly reduces signaling overhead and latency associated with interaction with the base station, enabling millisecond-level rapid resource decisions in network congestion or high-interference scenarios. Secondly, by monitoring bandwidth utilization and interference levels in real time, the system can quickly detect high-load conditions and trigger a game mechanism, effectively breaking the deadlock of static allocation and achieving dynamic interference avoidance and load balancing under high-pressure environments. Thirdly, the distributed competition mechanism prioritizes spectrum resources for passive IoT terminals with better channel quality or more urgent service needs, thereby significantly improving the resource utilization and allocation fairness of shared bandwidth while ensuring system communication stability.

[0090] In conjunction with the above embodiments, in one implementation, the method of this application may further include: When a passive IoT terminal that has obtained the target resource block transmits data, a near-blank subframe mechanism is used to prevent passive IoT terminals that have not obtained the target resource block from transmitting data.

[0091] In this embodiment, when passive IoT terminals compete for spectrum resources, they can also use the Almost Blank Subframe (ABS) mechanism to silence some time slots, prohibiting passive IoT terminals that have not obtained the target resource block from transmitting data, thereby avoiding conflicting frequency bands and realizing millisecond-level resource reclamation and redistribution.

[0092] In conjunction with the above embodiments, in one implementation, the method of this application may further include: Based on channel state information and historical traffic data generated by base stations, determine the spectrum resource requirements of IoT terminals in future time slices; Update the first and second occupancy rates based on the spectrum resource requirements of future time slices.

[0093] In this embodiment, after obtaining the spectrum resource requirements of the IoT terminal in the future time slice, the spectrum resource requirements of the IoT terminal in the future time slice can be immediately converted into a first occupancy rate. Second occupancy rate The correction amount, and use that correction amount for the first occupancy rate. Second occupancy rate Making adjustments in advance (avoiding adjustments only when peak hours are reached) ensures that spectrum migration and reclamation always precede service peaks, avoiding instantaneous congestion and guaranteeing the smooth operation of base station services.

[0094] In conjunction with the above embodiments, in one implementation, the method of this application may further include: Obtain the bandwidth utilization rate of passive IoT private bandwidth in the uplink spectrum resources; If the bandwidth utilization rate of the passive IoT private bandwidth is greater than the second utilization rate, the services of passive IoT terminals that occupy resource blocks in the passive IoT private bandwidth will be migrated to resource blocks in the shared bandwidth.

[0095] In this embodiment, the bandwidth utilization rate of the passive IoT private bandwidth can also be monitored. Once it is detected that the bandwidth utilization rate of the passive IoT private bandwidth is greater than the second utilization rate... This allows services of passive IoT terminals that occupy resource blocks in the private bandwidth of passive IoT to be migrated to resource blocks in the shared bandwidth for execution.

[0096] In this embodiment, when the private bandwidth resources of passive IoT are detected to be scarce, the risk of congestion on the dedicated channel can be effectively avoided by migrating congested services to the shared bandwidth, thereby achieving dynamic load balancing across frequency bands. This not only makes full use of the idle resources of the shared bandwidth, but also significantly improves the overall spectrum utilization of the system, ensuring the continuity and communication stability of passive terminal services in high-concurrency scenarios.

[0097] In conjunction with the above embodiments, in one implementation, the method of this application may further include: Obtain the bandwidth utilization rate of cellular communication private bandwidth in the uplink spectrum resources; If the bandwidth utilization rate of the private cellular bandwidth is greater than the second utilization rate, the services of passive IoT terminals that occupy resource blocks in the private cellular bandwidth will be migrated to resource blocks in the shared bandwidth for execution.

[0098] In this embodiment, the bandwidth utilization rate of the active IoT private bandwidth can also be monitored. Once it is detected that the bandwidth utilization rate of the active IoT private bandwidth is greater than the second utilization rate... This allows the services of active IoT terminals that occupy resource blocks in the private bandwidth of active IoT to be migrated to resource blocks in the shared bandwidth for execution.

[0099] In this embodiment, by migrating congested services on the active IoT private bandwidth to the shared bandwidth, the risk of congestion on the dedicated channel can be effectively avoided. This not only makes full use of the idle resources of the shared bandwidth, but also significantly improves the overall spectrum utilization of the system.

[0100] In one implementation, in conjunction with the above embodiments, the first occupancy rate and the second occupancy rate are determined based on the base occupancy rate, which is determined based on the density of passive IoT tags in the coverage area and the area of ​​the coverage area.

[0101] Among them, the basic occupancy rate The formula is: ,in, Let A be the density of passive IoT terminals within the coverage area of ​​the base station, and let A be the coverage area of ​​the base station. = Total number of passive IoT terminals within the base station's coverage area / Coverage area A of the base station.

[0102] In this embodiment, the engineer can pre-determine based on Based on experience, determine and .after, and The frequency can be dynamically adjusted based on the spectrum resource requirements of future time slices, as described above.

[0103] In this embodiment, by linking the occupancy rate determination threshold with the density and coverage area of ​​passive IoT terminals within the base station's coverage area, adaptive configuration of the load assessment standard can be achieved. This ensures that the system's determination of congestion status can accurately match the actual terminal distribution density and environmental characteristics, avoiding decision bias caused by a single fixed threshold and significantly improving the flexibility of resource scheduling strategies.

[0104] This application also implements a dynamic frequency band reclamation and reuse allocation mechanism, achieving closed-loop resource management by continuously monitoring the communication status and transmission progress of IoT terminals. If the communication status of an IoT terminal is detected to be normal, the system maintains its current frequency band occupancy; once an abnormal communication interruption or data transmission task is detected, the system will immediately trigger the reclamation mechanism, releasing the frequency band occupied by the IoT terminal and marking it as available for allocation. The reclaimed frequency band is given priority to the candidate pool for rapid response to the immediate needs of high-priority or urgent services; if there is no matching demand in the candidate pool, the frequency band will be automatically merged into the global shared bandwidth pool for allocation in the next round of allocation. This mechanism ensures that idle resources can be reclaimed in a timely manner and transferred to high-value services, significantly improving spectrum utilization efficiency.

[0105] In summary, the spectrum resource allocation scheme of this application has at least the following technical effects: First, it solves the problem of limited spectrum utilization: This application divides available spectrum resources into high, medium, and low-priority resource pools through a three-pool hierarchical structure and an advanced prediction mechanism, accurately matching services of different priorities and avoiding disorderly competition between high-value and low-speed services in the same frequency band. Simultaneously, by combining an LSTM + linear regression prediction model to predict historical traffic and environmental factors in advance, resources can be reserved or released in advance, enabling aggregation during busy periods and release during off-peak periods. This effectively solves the problem of simultaneous hotspot overload and fragmented idleness, significantly improving the overall spectrum utilization of the system.

[0106] Second, it solves the problem of insufficient flexibility: This application abandons the traditional centralized scheduling with a second-level closed loop and adopts a distributed autonomous game mechanism, which decentralizes the decision-making power to the passive IoT terminal side. Each passive IoT terminal completes frequency band negotiation and resource reselection within a millisecond-level window. This decentralized autonomous mode can respond to business tides and millisecond-level energy window changes in real time, and achieve flexible adaptation to complex and diverse IoT services.

[0107] Third, it addresses the issue of weak anti-interference capability: This application constructs a location-aware real-time FHSS frequency hopping sequence as the core anti-interference scheme. When high interference or conflict is detected, a game between passive IoT terminals is immediately triggered, supplemented by a near-blank subframe silence mechanism and a power backoff strategy, isolating and reallocating conflicting frequency bands within milliseconds. Furthermore, conflict resolution incorporates service priorities, ensuring that critical services prioritize channel access while other tags probabilistically avoid interference, effectively reducing co-channel and adjacent-channel interference and guaranteeing communication quality and system stability.

[0108] Fourth, it solves the problem of high energy consumption: The physical layer base of this application deeply integrates a dual-mode collaborative mechanism of backscatter communication and CSI feedback. Passive IoT terminals utilize carrier signal reflection information from external devices in the uplink, eliminating the need for active RF signal transmission and achieving zero PRB and zero power consumption. Active IoT terminals only report simplified CSI at millisecond intervals when necessary, and the base station completes downlink prediction using the principle of channel reciprocity. This design can significantly reduce the uplink overhead caused by reference signal transmission and scheduling requests, and significantly reduce the overall system energy consumption.

[0109] Fifth, it solves the problem of poor scene adaptability: This application introduces a density-area coupled exponential dynamic threshold mechanism ( The decision threshold automatically adjusts in real time based on tag density and cell area: the threshold rises to prevent overload when density suddenly increases, and falls to release spectrum when density suddenly decreases. This adaptive drift characteristic, which requires no manual reconfiguration, ensures that the system can smoothly adapt to various complex scenarios.

[0110] The spectrum resource allocation apparatus provided in the embodiments of this application is described below. The spectrum resource allocation apparatus described below can be referred to in correspondence with the spectrum resource allocation method described above.

[0111] This application first provides a spectrum resource allocation device 200, which is deployed in a base station. Figure 2 This is a structural block diagram of a spectrum resource allocation device shown in an embodiment of this application. (Refer to...) Figure 2 The spectrum resource allocation device 200 of this application may include: The first acquisition module 201 is used to acquire the load information of passive IoT terminals within the coverage area of ​​the base station, wherein the passive IoT terminals reflect information to the base station based on carrier signals provided by external devices. The second acquisition module 202 is used to acquire the channel state information of the uplink from the active IoT terminal to the base station based on the reference signal sent by the active IoT terminal in the coverage area of ​​the base station. The determining module 203 is used to determine the resource block allocation table of the downlink spectrum resources of the base station in the next time slice based on the load information and the channel state information. The resource block allocation table includes the allocation information of each IoT terminal to the resource blocks. The IoT terminals include passive IoT terminals and active IoT terminals.

[0112] According to the spectrum resource allocation device 200 provided in this application, the determining module 203 is specifically used for: determining the channel quality of the downlink from the base station to the active IoT terminal based on the channel reciprocity principle and the channel state information; and determining the resource block allocation table of the downlink spectrum resources of the base station in the next time slice based on the load information, the channel state information and the channel quality.

[0113] According to the spectrum resource allocation device 200 provided in this application, the determining module 203 is specifically used to: under the premise of meeting the data transmission rate requirements and the maximum power level requirements for interference tolerance of each of the IoT terminals, with the goal of minimizing the total transmit power consumed when allocating all resource blocks, determine the resource block allocation table of the downlink spectrum resources of the base station in the next time slice based on the load information, the channel state information and the channel quality.

[0114] According to the spectrum resource allocation device 200 provided in this application, the downlink spectrum resources include multiple resource blocks, each of which carries a level identifier. The determining module 203 is specifically used to: determine the service type corresponding to each of the IoT terminals in the next time slice; and, under the premise of satisfying the data transmission rate requirements, the maximum power level requirements for interference tolerance, and the constraint relationship between the service type and the level identifier of each of the IoT terminals, determine the resource block allocation table of the downlink spectrum resources of the base station in the next time slice based on the load information, the channel state information, and the channel quality, with the goal of minimizing the total transmit power consumed when allocating all resource blocks.

[0115] The spectrum resource allocation device 200 provided in this application further includes: an adjustment module, configured to: adjust the strategy for generating the resource block allocation table based on the historical throughput of the base station, the historical data transmission delay between the base station and the IoT terminal, and the energy capture efficiency of the passive IoT terminal, wherein the adjustment items include at least: the number of resource blocks carrying various grade identifiers, and the constraint relationship between the service type and the grade identifier.

[0116] The spectrum resource allocation device 200 provided in this application further includes: a prediction module, configured to: determine the spectrum resource requirements of the Internet of Things terminal in a future time slice based on the channel state information and the historical traffic data generated by the base station; and determine the downlink spectrum resources for the next time slice based on the spectrum resource requirements.

[0117] According to the spectrum resource allocation device 200 provided in this application, the downlink spectrum resources include passive IoT private bandwidth, shared bandwidth and cellular communication private bandwidth, and the passive IoT private bandwidth, the shared bandwidth and the cellular communication private bandwidth each include multiple resource blocks.

[0118] According to the spectrum resource allocation device 200 provided in this application, the uplink spectrum resources of the base station include passive IoT private bandwidth and shared bandwidth. The device 200 further includes: a first monitoring module, used to obtain the bandwidth occupancy rate of the shared bandwidth in the uplink spectrum resources; when the bandwidth occupancy rate of the shared bandwidth is less than a first occupancy rate, the services of passive IoT terminals occupying resource blocks in the shared bandwidth are migrated to resource blocks in the passive IoT private bandwidth.

[0119] According to the spectrum resource allocation device 200 provided in this application, the uplink spectrum resource also includes cellular communication private bandwidth. The device 200 further includes: a second monitoring module, configured to: when the bandwidth occupancy rate of the shared bandwidth is greater than a second occupancy rate, or when the interference level of the shared bandwidth is greater than an interference threshold, migrate the services of passive IoT terminals occupying resource blocks in the shared bandwidth to resource blocks in the passive IoT private bandwidth, or migrate the services of active IoT terminals occupying resource blocks in the shared bandwidth to resource blocks in the cellular communication private bandwidth, wherein the second occupancy rate is greater than the first occupancy rate.

[0120] The spectrum resource allocation device 200 provided in this application further includes: a third monitoring module, used to: determine the allocation information of each passive IoT terminal that needs to occupy a resource block in the shared bandwidth to the resource block in the shared bandwidth through a distributed game mechanism when the bandwidth occupancy rate of the shared bandwidth is greater than a second occupancy rate, or the interference level of the shared bandwidth is greater than an interference threshold.

[0121] According to the spectrum resource allocation device 200 provided in this application, the third monitoring module is specifically used to: send a game start signal to each passive IoT terminal that needs to occupy a resource block in the shared bandwidth; the game start signal is used to instruct the first passive IoT terminal to broadcast a spectrum allocation request to the second passive IoT terminal, receive the response information of the second passive IoT terminal to the spectrum allocation request, determine the target resource block that needs to be occupied in the shared bandwidth according to the response information, and broadcast the information of the target resource block to the second passive IoT terminal, wherein the first passive IoT terminal is any one of the passive IoT terminals that needs to occupy a resource block in the shared bandwidth, and the second terminal is any one of the passive IoT terminals that needs to occupy a resource block in the shared bandwidth except for the first terminal.

[0122] According to the spectrum resource allocation device 200 provided in this application, the third monitoring module is further configured to: when a passive IoT terminal that has obtained the target resource block is transmitting data, prohibit a passive IoT terminal that has not obtained the target resource block from transmitting data through an almost blank subframe mechanism.

[0123] The spectrum resource allocation device 200 provided in this application further includes: an update module, configured to: determine the spectrum resource requirements of the Internet of Things terminal in a future time slice based on the channel state information and the historical traffic data generated by the base station; and update the first occupancy rate and the second occupancy rate based on the spectrum resource requirements in the future time slice.

[0124] According to the spectrum resource allocation device 200 provided in this application, the uplink spectrum resources of the base station include passive IoT private bandwidth and shared bandwidth. The device 200 further includes: a fourth monitoring module, used to: obtain the bandwidth occupancy rate of the passive IoT private bandwidth in the uplink spectrum resources; if the bandwidth occupancy rate of the passive IoT private bandwidth is greater than a second occupancy rate, the services of passive IoT terminals occupying resource blocks in the passive IoT private bandwidth will be migrated to resource blocks in the shared bandwidth.

[0125] According to the spectrum resource allocation device 200 provided in this application, the uplink spectrum resources of the base station include shared bandwidth and cellular communication private bandwidth. The device 200 further includes: a fifth monitoring module, used to: obtain the bandwidth occupancy rate of the cellular communication private bandwidth in the uplink spectrum resources; if the bandwidth occupancy rate of the cellular communication private bandwidth is greater than a second occupancy rate, the services of passive IoT terminals occupying resource blocks in the cellular communication private bandwidth will be migrated to resource blocks in the shared bandwidth.

[0126] According to the spectrum resource allocation device 200 provided in this application, the first occupancy rate and the second occupancy rate are determined based on a base occupancy rate, which is determined based on the density of passive IoT tags in the coverage area and the area of ​​the coverage area.

[0127] Figure 3 This is a schematic diagram of the physical structure of an electronic device shown in an embodiment of this application, such as... Figure 3 As shown, the electronic device may include a processor 310, a communication interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communication interface 320, and the memory 330 communicate with each other via the communication bus 340. The processor 310 can call a computer program in the memory 330 to execute the steps of a spectrum resource allocation method.

[0128] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0129] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the steps of a spectrum resource allocation method provided in the above embodiments.

[0130] On the other hand, embodiments of this application also provide a processor-readable storage medium storing a computer program for causing a processor to execute the steps of a spectrum resource allocation method provided in the above embodiments.

[0131] The processor-readable storage medium can be any available medium or data storage device that the processor can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).

[0132] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0133] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method of spectrum resource allocation, the method comprising: The method is applied to a base station, and comprises the following steps: Obtaining load information of passive Internet of Things terminals in a coverage area of the base station, wherein the passive Internet of Things terminals reflect information to the base station based on a carrier signal provided by an external device; Obtaining channel state information of uplink of active Internet of Things terminals to the base station according to a reference signal sent by the active Internet of Things terminals in the coverage area of the base station; Determining a resource block allocation table of downlink spectrum resources of the base station in a next time slice according to the load information and the channel state information, wherein the resource block allocation table comprises allocation information of resource blocks of each Internet of Things terminal, and the Internet of Things terminal comprises the passive Internet of Things terminal and the active Internet of Things terminal.

2. The method of claim 1, wherein, The step of determining the resource block allocation table of the downlink spectrum resources of the base station in the next time slice according to the load information and the channel state information comprises the following steps: Determining channel quality of downlink of the base station to the active Internet of Things terminals according to the channel state information based on a channel reciprocity principle; Determining the resource block allocation table of the downlink spectrum resources of the base station in the next time slice according to the load information, the channel state information and the channel quality.

3. The method of claim 2, wherein, The step of determining the resource block allocation table of the downlink spectrum resources of the base station in the next time slice according to the load information, the channel state information and the channel quality comprises the following steps: In a case where data transmission rate requirements of each Internet of Things terminal and maximum power level requirements of interference bearing are met, the resource block allocation table of the downlink spectrum resources of the base station in the next time slice is determined according to the load information, the channel state information and the channel quality, with a target of minimizing total transmission power consumed when all resource blocks are allocated.

4. The method of claim 2, wherein, The downlink spectrum resources comprise a plurality of resource blocks, each resource block carries a level identifier, and the step of determining the resource block allocation table of the downlink spectrum resources of the base station in the next time slice according to the load information, the channel state information and the channel quality comprises the following steps: Determining a service type of each Internet of Things terminal in the next time slice; In a case where data transmission rate requirements of each Internet of Things terminal, maximum power level requirements of interference bearing and a constraint relationship between the service type and the level identifier are met, the resource block allocation table of the downlink spectrum resources of the base station in the next time slice is determined according to the load information, the channel state information and the channel quality, with a target of minimizing total transmission power consumed when all resource blocks are allocated.

5. The method of claim 4, wherein, Further comprising the following steps: Adjusting a strategy for generating the resource block allocation table according to historical throughput of the base station, historical data transmission delay between the base station and the Internet of Things terminal and energy harvesting efficiency of the passive Internet of Things terminal, and the adjustment items at least comprise a number of resource blocks carrying various level identifiers and a constraint relationship between the service type and the level identifier.

6. The method of claim 1, wherein, Further comprising the following steps: Determining spectrum resource requirements of the Internet of Things terminal in a future time slice according to the channel state information and historical traffic data generated by the base station; According to the spectrum resource requirement, determine the downlink spectrum resource of the next time slice.

7. The method of claim 1-6, wherein, The type of the downlink spectrum resource includes a passive Internet of Things private bandwidth, a shared bandwidth, and a cellular communication private bandwidth, and the passive Internet of Things private bandwidth, the shared bandwidth, and the cellular communication private bandwidth each include a plurality of resource blocks.

8. The method of claim 1, wherein, The type of the uplink spectrum resource of the base station includes a passive Internet of Things private bandwidth and a shared bandwidth, and the method further includes: Obtaining a bandwidth occupancy rate of the shared bandwidth in the uplink spectrum resource; In a case where the bandwidth occupancy rate of the shared bandwidth is less than a first occupancy rate, migrating a service of a passive Internet of Things terminal occupying a resource block in the shared bandwidth to a resource block in the passive Internet of Things private bandwidth.

9. The method of claim 8, wherein, The uplink spectrum resource further includes a cellular communication private bandwidth, and the method further includes: In a case where the bandwidth occupancy rate of the shared bandwidth is greater than a second occupancy rate or an interference level of the shared bandwidth is greater than an interference threshold, migrating a service of a passive Internet of Things terminal occupying a resource block in the shared bandwidth to a resource block in the passive Internet of Things private bandwidth or migrating a service of an active Internet of Things terminal occupying a resource block in the shared bandwidth to a resource block in the cellular communication private bandwidth, the second occupancy rate being greater than the first occupancy rate.

10. The cellular passive internet of things dynamic spectrum sharing method of claim 8, wherein, Further include: In a case where the bandwidth occupancy rate of the shared bandwidth is greater than a second occupancy rate or an interference level of the shared bandwidth is greater than an interference threshold, determining, by a distributed game mechanism, allocation information of a resource block in the shared bandwidth for each passive Internet of Things terminal needing to occupy the resource block in the shared bandwidth.

11. The spectrum resource allocation method of claim 10, wherein, The determining, by the distributed game mechanism, of the allocation information of the resource block in the shared bandwidth for each passive Internet of Things terminal needing to occupy the resource block in the shared bandwidth includes: sending a game start signal to each passive Internet of Things terminal needing to occupy the resource block in the shared bandwidth; the game start signal is used to instruct a first passive Internet of Things terminal to broadcast a spectrum allocation request to a second passive Internet of Things terminal, receive response information of the second passive Internet of Things terminal to the spectrum allocation request, determine a target resource block needing to be occupied in the shared bandwidth according to the response information, and broadcast information of the target resource block to the second passive Internet of Things terminal, the first passive Internet of Things terminal being any one of each passive Internet of Things terminal needing to occupy the resource block in the shared bandwidth, and the second terminal being a terminal other than the first terminal among each passive Internet of Things terminal needing to occupy the resource block in the shared bandwidth.

12. The method of claim 11, wherein, Further include: when a passive Internet of Things terminal obtaining the target resource block performs data transmission, prohibiting passive Internet of Things terminals not obtaining the target resource block from performing data transmission by an almost blank subframe mechanism.

13. The method of claim 9, wherein, Further include: determining a spectrum resource requirement of the Internet of Things terminal in a future time slice according to the channel state information and historical traffic data generated by the base station; updating the first occupancy rate and the second occupancy rate according to the spectrum resource requirement of the future time slice.

14. The method of claim 1, wherein, The type of uplink spectrum resource of the base station includes a passive Internet of Things private bandwidth and a shared bandwidth, and the method further includes: acquiring a bandwidth occupancy rate of the passive Internet of Things private bandwidth in the uplink spectrum resource; if the bandwidth occupancy rate of the passive Internet of Things private bandwidth is greater than a second occupancy rate, migrating services of passive Internet of Things terminals occupying resource blocks in the passive Internet of Things private bandwidth to resource blocks in the shared bandwidth.

15. The method of claim 1, wherein, The type of uplink spectrum resource of the base station includes a shared bandwidth and a cellular communication private bandwidth, and the method further includes: acquiring a bandwidth occupancy rate of the cellular communication private bandwidth in the uplink spectrum resource; if the bandwidth occupancy rate of the cellular communication private bandwidth is greater than a second occupancy rate, migrating services of passive Internet of Things terminals occupying resource blocks in the cellular communication private bandwidth to resource blocks in the shared bandwidth.

16. The method of claim 9, wherein, The first occupancy rate and the second occupancy rate are determined according to a basic occupancy rate, and the basic occupancy rate is determined according to the density of passive Internet of Things tags in the coverage area and the area of the coverage area.

17. An apparatus for spectrum resource allocation, the apparatus comprising: The device is deployed in a base station, and the device includes: a first acquisition module configured to acquire load information of passive Internet of Things terminals in a coverage area of the base station, the passive Internet of Things terminals reflecting information to the base station based on a carrier signal provided by an external device; a second acquisition module configured to acquire channel state information of uplink of active Internet of Things terminals to the base station according to a reference signal sent by the active Internet of Things terminals in the coverage area of the base station; a determination module configured to determine a resource block allocation table of downlink spectrum resource of the base station in a next time slice according to the load information and the channel state information, the resource block allocation table including allocation information of resource blocks of each Internet of Things terminal, the Internet of Things terminal including a passive Internet of Things terminal and an active Internet of Things terminal.

18. An electronic device comprising a processor and a memory having a computer program stored therein, characterized in that, The processor executes the computer program to implement the steps of the spectrum resource allocation method of any one of claims 1 to 16. 19.A non-transitory computer-readable storage medium having stored thereon a computer program, wherein, The computer program is executed by the processor to implement the spectrum resource allocation method of any one of claims 1 to 16.

20. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the spectrum resource allocation method of any one of claims 1 to 16.

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