Communication and sensing integrated frame structure configuration method, device and equipment, storage medium and program product

Abstract

The invention relates to a communication and sensing integrated frame structure configuration method and device, communication equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a to-be-configured sensing frame structure; the sensing frame structure comprises an uplink time slot, a special time slot and a flexible time slot, the flexible time slot comprises a plurality of flexible symbols, and the special time slot comprises a plurality of flexible symbols, a plurality of guard interval symbols and a plurality of uplink symbols; acquiring a current state including a communication service demand and a sensing service demand reported by the user equipment; identifying a current state by using an artificial intelligence model to obtain an optimal ratio of perception to communication; and configuring the flexible symbol as a downlink symbol or a sensing symbol according to the optimal ratio of sensing to communication to obtain a configured sensing frame structure. By adopting the method, the sensing frame structure can be intelligently configured, the service characteristics can be adapted, the sensing service can be supported as required, the influence on the communication performance is reduced, and the resource utilization rate is improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method, apparatus, communication device, computer-readable storage medium and computer program product for configuring a synaesthesia-integrated frame structure. Background Art

[0002] With the development of mobile communication technology, higher frequency bands (millimeter waves), wider bandwidths, and larger-scale antenna arrays make high-precision and high-resolution perception possible. With the increase in communication needs, Integrated Sensing and Communication (ISAC) has attracted the attention of many scholars and researchers. ISAC refers to a new information processing technology that realizes the coordination of perception and communication functions based on software and hardware resource sharing or information sharing, which can effectively improve the system's spectrum efficiency, hardware efficiency, and information processing efficiency. Communication refers to the transmission of information between two or more points, and perception refers to the detection of parameters of the physical environment, such as speed measurement, target positioning, etc. ISAC refers to the integration of the two functions of communication and perception, so that future communication systems have both communication and perception functions. While transmitting information through wireless channels, they actively recognize and analyze the characteristics of the channel to perceive the physical characteristics of the surrounding environment, so that the communication and perception functions enhance each other.

[0003] In complex application scenarios, the business information processing process presents the characteristics of highly integrated communication perception, and the perception link and the communication link overlap in time and space. Therefore, ISAC has brought new challenges to many key technologies. Among them, the frame structure, as one of the key research objects of air interface technology, plays a vital role in the implementation of ISAC technology. The frame structure is the basis of 5G network, which defines the allocation of time and frequency resources for data transmission. The design of 5G allows flexible frame structure configuration to adapt to different business needs. The 5G frame structure includes multiple time slot formats to support different uplink and downlink transmission ratios to meet scenarios such as enhanced mobile broadband (eMBB), ultra-reliable low latency communication (URLLC) and massive machine type communication (mMTC). However, the 5G frame structure is mainly aimed at traditional communication services, and the integration of perception services has not been fully considered. Looking at the vision of future ISAC, future networks should consider frame structure design solutions with perception capabilities. Summary of the invention

[0004] Based on this, it is necessary to provide a synaesthesia-integrated frame structure configuration method, device, communication equipment, computer-readable storage medium and computer program product to address the above-mentioned technical problems, which can adapt to the needs of different communication services and perception services, intelligently configure the perception frame structure, and have flexibility and scalability.

[0005] In a first aspect, the present application provides a method for configuring a synaesthesia-integrated frame structure, comprising:

[0006] Acquire a perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a plurality of flexible symbols, and the special time slot includes a plurality of flexible symbols, a plurality of guard interval symbols and a plurality of uplink symbols;

[0007] Get the current status; the current status includes the communication service requirements and perception service requirements reported by the user equipment;

[0008] Use artificial intelligence models to identify the current state and obtain the best ratio of perception and communication;

[0009] According to the optimal ratio of perception and communication, the flexible symbols are configured as downlink symbols or perception symbols to obtain a configured perception frame structure.

[0010] In one embodiment, the method further comprises:

[0011] Construct training samples; the training samples include the state of the nth cycle, the configuration action of the nth cycle, the state of the n+1th cycle, and the reward of the nth cycle; n is an integer not less than 1;

[0012] According to the training samples, the artificial intelligence model is reinforced with learning to obtain a trained artificial intelligence model.

[0013] In one embodiment, the method further comprises:

[0014] Obtaining the communication service execution completion degree and the perception service execution completion degree sent by each user equipment in the nth cycle;

[0015] According to the set weight coefficient, the communication service execution completion degree and the perception service execution completion degree are weighted and summed to obtain the reward for the nth cycle.

[0016] In one of the embodiments, before obtaining the perception frame structure to be configured, the method further includes:

[0017] Determine the ratio between the communication frame and the perception frame according to the characteristic information of the target area;

[0018] According to the ratio between the communication frame and the perception frame, time domain configuration information of the periodic arrangement of the communication frame and the perception frame in the time domain is generated;

[0019] According to the time domain configuration information, the perception frame structure of the kth perception frame is configured in a communication frame before the kth perception frame; k is an integer not less than 1.

[0020] In one embodiment, the method further comprises:

[0021] Get neighboring area information;

[0022] Based on the neighboring cell information, the configuration information of the sensing frame structure in the target area is synchronized.

[0023] In one embodiment, obtaining the current state includes:

[0024] Determine the communication service requirements and the perception service requirements received by each communication device in the target area in the current period;

[0025] The current state is determined according to the communication service requirements and the perceived service requirements received by each communication device in the target area.

[0026] In a second aspect, the present application also provides a synaesthesia integrated frame structure configuration device, comprising:

[0027] An acquisition module is used to acquire a perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a number of flexible symbols, and the special time slot includes a number of flexible symbols, a number of guard interval symbols and a number of uplink symbols; acquire a current state; the current state includes a communication service demand and a perception service demand reported by a user device;

[0028] The configuration module is used to use the artificial intelligence model to identify the current state and obtain the optimal ratio of perception and communication; according to the optimal ratio of perception and communication, the flexible symbols are configured as downlink symbols or perception symbols to obtain the configured perception frame structure.

[0029] In a third aspect, the present application further provides a communication device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0030] Acquire a perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a plurality of flexible symbols, and the special time slot includes a plurality of flexible symbols, a plurality of guard interval symbols and a plurality of uplink symbols;

[0031] Get the current status; the current status includes the communication service requirements and perception service requirements reported by the user equipment;

[0032] Use artificial intelligence models to identify the current state and obtain the best ratio of perception and communication;

[0033] According to the optimal ratio of perception and communication, the flexible symbols are configured as downlink symbols or perception symbols to obtain a configured perception frame structure.

[0034] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0035] Acquire a perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a plurality of flexible symbols, and the special time slot includes a plurality of flexible symbols, a plurality of guard interval symbols and a plurality of uplink symbols;

[0036] Get the current status; the current status includes the communication service requirements and perception service requirements reported by the user equipment;

[0037] Use artificial intelligence models to identify the current state and obtain the best ratio of perception and communication;

[0038] According to the optimal ratio of perception and communication, the flexible symbols are configured as downlink symbols or perception symbols to obtain a configured perception frame structure.

[0039] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0040] Acquire a perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a plurality of flexible symbols, and the special time slot includes a plurality of flexible symbols, a plurality of guard interval symbols and a plurality of uplink symbols;

[0041] Get the current status; the current status includes the communication service requirements and perception service requirements reported by the user equipment;

[0042] Use artificial intelligence models to identify the current state and obtain the best ratio of perception and communication;

[0043] According to the optimal ratio of perception and communication, the flexible symbols are configured as downlink symbols or perception symbols to obtain a configured perception frame structure.

[0044] The above-mentioned synaesthesia integrated frame structure configuration method, device, communication equipment, computer-readable storage medium and computer program product obtain the perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a number of flexible symbols, and the special time slot includes a number of flexible symbols, a number of protection interval symbols and a number of uplink symbols; obtain the current state; the current state includes the communication service requirements and perception service requirements reported by the user device; use the artificial intelligence model to identify the current state to obtain the best ratio of perception and communication; according to the best ratio of perception and communication, the flexible symbol is configured as a downlink symbol or a perception symbol to obtain a configured perception frame structure. Through the above method, according to the needs of communication services and perception services, the perception frame structure is intelligently configured, which can support perception services on demand while reducing the impact on communication performance and improving resource utilization. Compared with the preset frame structure, the perception frame structure configured in this application is more flexible and more adaptable to business characteristics, and there is no need to design multiple fixed frame structure formats in advance. At the same time, by configuring the perception frame structure, communication signals and perception signals are time-division multiplexed, avoiding interference between communication services and perception services, and ensuring the quality of communication services and perception services. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0046] FIG1 is an application environment diagram of a method for configuring a frame structure for synaesthesia integration in one embodiment;

[0047] FIG2 is a schematic flow chart of a method for configuring a frame structure for synaesthesia integration in one embodiment;

[0048] FIG3 is a schematic diagram of a commonly used frame structure of millimeter waves in one embodiment;

[0049] FIG4 is a schematic diagram of a perception frame structure to be configured in an embodiment;

[0050] FIG5 is a schematic diagram of the periodic arrangement of communication frames and sensing frames in one embodiment;

[0051] FIG6 is a flow chart of a method for configuring a frame structure for synaesthesia integration in another embodiment;

[0052] FIG7 is a flow chart of a method for configuring a frame structure for synaesthesia integration in yet another embodiment;

[0053] FIG8 is a schematic diagram of a configured perception frame structure in one embodiment;

[0054] FIG9 is a structural block diagram of a synaesthesia integrated frame structure configuration device in one embodiment;

[0055] FIG. 10 is a diagram showing the internal structure of a communication device in one embodiment. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0057] The synaesthesia integrated frame structure configuration method provided in the embodiment of the present application can be applied to the application environment shown in FIG. 1. Among them, at least one base station 102 is set in the area n, and each base station communicates with at least one user equipment 104 (UserEquipment, UE). The base station 102 receives the communication service demand and the perception service demand reported by the user equipment 102, identifies the current state by using the artificial intelligence model, obtains the best ratio of perception and communication, and configures the flexible symbols in the perception frame structure to be configured as downlink symbols or perception symbols according to the best ratio of perception and communication, so as to obtain the configured perception frame structure. Optionally, in the synaesthesia integrated system, when processing the communication service, the base station 102 and the user equipment 104 perform wireless signal transmission and reception; when processing the perception service, the base station 102 sends a wireless synaesthesia signal based on the allocated perception resource, and receives the signal echo to perform the perception task. The user equipment can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, Internet of Things devices and portable wearable devices, and the Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car devices, projection devices, etc. Portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. Head-mounted devices may be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc.

[0058] In an exemplary embodiment, as shown in FIG2 , a method for configuring a frame structure for integrated synaesthesia is provided, which is described by taking the method applied to the base station 102 in FIG1 as an example, including:

[0059] Step 202, obtaining a perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a number of flexible symbols, and the special time slot includes a number of flexible symbols, a number of guard interval symbols and a number of uplink symbols.

[0060] It can be understood that the present application takes the commonly used frame structure of millimeter waves as an example to illustrate the structure of communication frames and perception frames. Referring to Figure 3, Figure 3 is a schematic diagram of a commonly used frame structure of millimeter waves in an embodiment; the frame structure is mainly based on the downlink, and the time slot configuration DDDSU includes a downlink time slot (D), a special time slot (S) and an uplink time slot (U). The downlink time slot (D) is composed entirely of downlink symbols, and the special time slot (S) is composed of a downlink symbol D, a guard interval symbol G and an uplink symbol U. The ratio of the downlink time slot (D), the special time slot (S) and the uplink time slot (U) in Figure 3 is 10:2:2. In a specific implementation, the ratio of the frame structure can be set according to actual conditions. The present application adopts the conventional frame structure as the communication frame structure. In practical applications, other conventional frame structures can also be used, and this embodiment does not limit this.

[0061] Based on the commonly used frame structure of millimeter waves shown in Figure 3, this embodiment designs a perception frame structure to be configured as shown in Figure 4. The perception frame structure replaces the downlink time slot (D) of the communication frame with a flexible time slot (F), and modifies the symbol configuration in the special time slot (S). Specifically, the downlink symbols in the downlink time slot (D) and the special time slot (S) of the communication frame are replaced with flexible symbols, which can be configured as downlink symbols or perception symbols.

[0062] Optionally, before each perception frame period arrives, the steps of the synaesthesia integrated frame structure configuration method provided in this embodiment are executed.

[0063] Step 204, obtaining the current state; the current state includes the communication service demand and the perception service demand reported by the user equipment.

[0064] Among them, the communication user equipment with communication services is represented as a set ; The sensing user equipment with sensing services is represented as a set Before each sensing frame period arrives, that is, the communication frame before the sensing frame, the communication user equipment Reporting communication service needs ; Perceive user equipment Report perceived business needs The base station collects the service requirements reported by all service devices as status Optionally, the status The number of communication service demands or perception service demands is recorded, and the amount of resources requested by the communication service demands or perception service demands is also recorded.

[0065] Step 206, using the artificial intelligence model to identify the current state and obtain the best ratio of perception and communication.

[0066] Step 208, according to the best matching ratio between perception and communication, the flexible symbols are configured as downlink symbols or perception symbols to obtain a configured perception frame structure.

[0067] Among them, the base station uses artificial intelligence models based on the status Determine and execute , Indicates that the base station configures flexible symbols according to the strategy of the artificial intelligence model (AI). Specifically, the artificial intelligence model outputs the best ratio of perception and communication based on the read-in state to weigh the execution of the two coexisting services, that is, the best ratio of perception symbols and downlink symbols.

[0068] Optionally, according to the optimal ratio of perception and communication, the front flexible symbols in the perception frame structure to be configured are configured as perception symbols X, and the remaining flexible symbols are configured as downlink symbols D, so as to obtain a configured perception frame structure.

[0069] In an optional implementation, the base station performs communication and perception services based on the configuration of time slot resources. The base station sends a perception signal in a perception symbol and sends a communication signal in a downlink symbol.

[0070] It is understandable that in the integrated synaesthesia system, the wireless infrastructure is reused. Considering the uncertainty of the two services and the time-varying busyness of the services, the future communication services and perception services will coexist for a long time. At different times, users have different demands for the two services. In order to avoid mutual interference between the two services and effectively improve resource utilization, it is necessary to reasonably allocate perception resources to reduce the impact on communication performance.

[0071] The coexistence of communication services and perception services in ISAC scenarios makes the business model more complex. In order to promote the development of intelligent networks, the embodiments of the present application comprehensively consider the requirements of communication performance and perception performance, and combine the working frequency band, business scenarios, data transmission accuracy, perception accuracy, timeliness, interference and equipment capabilities of the integrated system to perform differentiated design of the integrated frame structure, so as to achieve deep integration of perception services and communication or communication-enhanced perception, and ensure the basic requirements of future networks and services for communication functions and perception functions.

[0072] In the above-mentioned synaesthesia integrated frame structure configuration method, the perception frame structure to be configured is obtained; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes several flexible symbols, and the special time slot includes several flexible symbols, several protection interval symbols and several uplink symbols; the current state is obtained; the current state includes the communication service requirements and the perception service requirements reported by the user device; the current state is identified by the artificial intelligence model to obtain the best ratio of perception and communication; according to the best ratio of perception and communication, the flexible symbol is configured as a downlink symbol or a perception symbol to obtain a configured perception frame structure. Through the above-mentioned method, according to the needs of communication services and perception services, the perception frame structure is intelligently configured, and the perception service can be supported on demand while reducing the impact on communication performance and improving resource utilization. Compared with the preset frame structure, the perception frame structure configured in this application is more flexible and more adaptable to business characteristics, and there is no need to design multiple fixed frame structure formats in advance. At the same time, by configuring the perception frame structure, the communication signal and the perception signal are time-division multiplexed, avoiding the interference between the communication service and the perception service, and ensuring the quality of the communication service and the perception service.

[0073] In an exemplary embodiment, the method also includes: constructing a training sample; the training sample includes the state of the nth cycle, the configuration action of the nth cycle, the state of the n+1th cycle, and the reward of the nth cycle; n is an integer not less than 1; according to the training sample, reinforcement learning is performed on the artificial intelligence model to obtain a trained artificial intelligence model.

[0074] For each sensing frame, the above steps 202 to 208 are repeatedly executed. For the nth sensing frame, the service requirements reported by all service devices in the nth cycle are collected as the status ; and record the configuration actions of the base station to configure flexible symbols according to the strategy of the artificial intelligence model (AI) ; Determine the reward for the nth period by analyzing the perception service and communication service in the nth period ; For the n+1th perception frame, collect the service requirements reported by all service devices in the n+1th cycle as the status The base station will The four-tuple information is stored in the experience pool for AI model training, enabling the AI ​​algorithm to continuously improve frame structure decisions based on dynamic status information, and ultimately obtain the optimal time slot resource allocation strategy, which facilitates the subsequent flexible configuration of the perception frame structure according to business needs.

[0075] In an optional implementation, this embodiment adopts the DRL (Deep Reinforcement Learning) algorithm to train the AI ​​model offline based on historical data or simulation data. In different time slots, the base station can adaptively allocate time slot resources according to the needs of communication services and perception services, so as to achieve the most reasonable frame structure configuration and improve resource utilization. In the case of coexistence of communication and perception services, the execution requirements of all user devices for two different services are comprehensively considered, and time domain resources are allocated on demand. It can be understood that the DRL algorithm is a technology that combines deep learning and reinforcement learning. It learns the optimal strategy through the interaction between the intelligent agent and the environment. DRL shows great potential in the fields of resource management and decision optimization, and is suitable for processing complex and dynamically changing environments. The embodiment of the present application considers using the DRL algorithm to empower the intelligent ISAC frame structure.

[0076] In an exemplary embodiment, the method also includes: obtaining the communication service execution completion degree and the perception service execution completion degree sent by each user device in the nth cycle; and taking the weighted sum of the communication service execution completion degree and the perception service execution completion degree according to the set weight coefficient to obtain the reward for the nth cycle.

[0077] The base station collects the service execution status of different user devices and analyzes and determines the reward for the nth cycle. Specifically, the reward is determined according to the following formula :

[0078] ;

[0079] In the formula, and To set the weight coefficient, and They are respectively the communication service execution completion degree and the perception service execution completion degree of the user equipment.

[0080] This embodiment uses the communication service execution completion and the perception service execution completion as rewards to train the AI ​​model, so that the AI ​​model considers the user completion in the system, improves the frame structure decision, and finally obtains the optimal time slot resource allocation strategy. The trained AI model flexibly configures the perception frame structure according to actual business needs to maximize the user service completion in the system.

[0081] In an exemplary embodiment, before step 202, the method further includes: determining the ratio between the communication frame and the perception frame based on the characteristic information of the target area; generating time domain configuration information of the periodic arrangement of the communication frame and the perception frame in the time domain based on the ratio between the communication frame and the perception frame; configuring the perception frame structure of the kth perception frame in the previous communication frame of the kth perception frame based on the time domain configuration information; k is an integer not less than 1.

[0082] Among them, facing the future synaesthesia integration scenario, in order to support the execution of perception services and minimize the impact of perception services on communication performance, the embodiment of the present application designs perception frames based on communication frames, and intersperses perception frames in the time domain scheduling period of communication frames, forming a periodic arrangement of communication frames and perception frames in the time domain.

[0083] Before each sensing frame period arrives, that is, the communication frame before the sensing frame, the base station executes the above steps 202 to 208, thereby configuring the sensing frame structure that is about to arrive.

[0084] It can be understood that the target area is the area where the base station of the frame structure configuration method for synaesthesia integration of the embodiment of the present application is located. The base station of this embodiment pre-configures the ratio between the communication frame and the perception frame based on the characteristic information of the target area. The characteristic information of the target area includes the type of coverage area, the number of users, historical data (records of communication services and perception services), scene demands, etc. Referring to Figure 5, Figure 5 is a schematic diagram of the periodic arrangement of communication frames and perception frames in one embodiment; the ratio between the communication frame and the perception frame is 3:1, and the communication frame and the perception frame are periodically arranged in the time domain. In a specific implementation, in a scenario with high perception demand, the ratio can be appropriately lowered, and conversely, in a scenario with low perception demand, the ratio can be appropriately increased. Through the method of this embodiment, the time domain proportion of the communication frame and the perception frame can be customized, which is more flexible than the fixed configuration, so that the service has a tendency to avoid the waste of resources caused by the mismatch between resources and services.

[0085] In an exemplary embodiment, as shown in FIG6 , the method further includes:

[0086] Step 602, obtaining neighboring cell information.

[0087] The neighboring cell information refers to the relevant information of other cells adjacent to the cell where the base station is located, including at least neighboring cell relations, base station information of the adjacent cells, etc. Optionally, the neighboring cell information may also include a sensing frame structure used by other base stations in the adjacent cells.

[0088] Step 604: Synchronize the configuration information of the sensing frame structure in the target area according to the neighboring cell information.

[0089] Among them, the base station uses the neighboring cell information The frame structure configuration in the target area is synchronized, and the current perceived frame structure configuration is transmitted through RRC (Radio Resource Control) signaling.

[0090] In this embodiment, in order to avoid interference between neighboring areas due to different frame structure configurations, the base station synchronizes the frame structure configuration in an area based on the collected neighboring area information, and finally forms a sliced ​​synaesthesia integrated network. Different areas can allocate perception resources on demand, providing a necessary means for operators to flexibly configure the synaesthesia integrated frame structure. Finally, a mode of configuring the frame structure on demand in different areas is formed, and different areas are independent of each other, and the frame structure configuration in the area is consistent, avoiding interference from neighboring areas and realizing dedicated network. The base station will execute the algorithm online and continuously collect training data during operation to achieve adaptation to the environment.

[0091] In an exemplary embodiment, step 204 includes: determining the communication service demands and perceived service demands received by each communication device in the target area during the current cycle; and determining the current state according to the communication service demands and perceived service demands received by each communication device in the target area.

[0092] The communication equipment is each base station in the target area. The current base station interacts with other base stations in the target area to collect the communication service needs and perception service needs of all user equipment in the target area, and uses the collected needs as the status , using artificial intelligence models, based on state Determine and execute , thereby intelligently configuring the perception frame structure according to the overall communication service needs and perception service needs of the target area. By configuring the perception frame structure, the communication signals and perception signals of each base station in the target area are time-division multiplexed, avoiding interference between the communication service and the perception service, and ensuring the quality of the communication service and perception service of each base station in the target area.

[0093] In an exemplary embodiment, as shown in FIG7 , the method for configuring a synaesthesia integrated frame structure includes the following steps:

[0094] The base station pre-configures the ratio of communication frames and perception frames in the time domain resources, and deploys the DRL algorithm that has been trained offline in the intelligent agent module; before the perception frame arrives, the communication device reports the communication service demand; the perception device reports the perception service demand;

[0095] The base station collects the service requirements reported by all user equipment as status and collects neighboring cell information;

[0096] The DRL algorithm obtains an action strategy based on the input state. The base station sets the perception frame structure according to the algorithm strategy, synchronizes the frame structure configuration in the area according to the neighboring cell information, and transmits the current perception frame structure configuration through RRC signaling;

[0097] Based on the configuration of the time slot resources, the communication service and the sensing service are executed, and the service execution status of different devices is collected as a reward;

[0098] Collect the status of the next perception frame cycle and store the training data. The online training AI model enables the algorithm to continuously improve the frame structure decision based on dynamic status information, and can flexibly configure the perception frame structure according to business needs.

[0099] In an exemplary embodiment, the method for configuring a synaesthesia-integrated frame structure includes the following steps:

[0100] 1. The business of a certain industrial park is mainly communication, and the demand for perception business is relatively small. Based on the business characteristics of the area, the base station pre-configures the ratio of communication frames and perception frames to 4:1, and deploys the DRL algorithm that has been trained offline in the intelligent agent module. The perception frame replaces the downlink time slot D of the communication frame with a flexible time slot F, and modifies the symbol configuration in the special time slot S. Specifically, the downlink symbol D in the communication frame D and S time slots is replaced with a flexible symbol, which can be configured as a downlink symbol D or a perception symbol X.

[0101] 2. The communication user equipment with communication services in the area is represented as a set ; The sensing user equipment with sensing services is represented as a set Before the sensing frame period arrives, the communication user equipment Reporting communication service needs ; Perceive user equipment Report perceived business needs , the base station side collects the service requirements reported by all service devices as status In addition, the base station collects neighboring cell information .

[0102] 3. Base station based on status Execute an action The base station sets the ratio of sensing symbols to downlink symbols according to the DRL algorithm. Referring to FIG8 , FIG8 is a schematic diagram of a sensing frame structure configured in an embodiment, and the optimal ratio of sensing to communication is 1:3. The front flexible symbol is set as the sensing symbol X, and the remaining flexible symbols are set as the downlink symbol D. The base station sets the ratio of sensing symbols to downlink symbols according to the neighboring cell information. Synchronize the frame structure configuration within the area and transmit the current perception frame structure configuration through RRC signaling.

[0103] 4. Based on the configuration of the time slot resources, the communication and sensing services are performed. The base station sends the sensing signal in the sensing symbol and sends the communication signal in the downlink symbol. The base station collects the service execution status of different devices as rewards. ,in and is the weight coefficient, and They are respectively the degree of completion of the communication / perception service execution of the device.

[0104] 5. Repeat steps 3 to 5 and collect the status in step 3 The base station will The quadruple information is stored in the experience pool for online training of AI models to adapt to dynamic environmental conditions.

[0105] Through the method of this embodiment, the industrial park can be assisted to more effectively utilize air interface resources, ensure the quality of the main business (communication) while completing the perception business with certain requirements. Extending to other application scenarios, different perception frame ratios can be configured according to the characteristics of the pilot area, making the configuration between regions more flexible; at the same time, AI technology can flexibly determine the proportion of perception symbols according to business needs to form the most suitable frame structure configuration mode for the area. The business models of different regions are somewhat different, and AI can collect different learning experiences in different regions, so as to train different strategy models, adaptively match regional characteristics, and form a mode of configuring frame structures on demand in different regions, dedicated to dedicated networks.

[0106] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0107] Based on the same inventive concept, the embodiment of the present application also provides a synesthesia integrated frame structure configuration device for implementing the synesthesia integrated frame structure configuration method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of one or more synesthesia integrated frame structure configuration devices provided below can refer to the limitations of the synesthesia integrated frame structure configuration method above, and will not be repeated here.

[0108] In an exemplary embodiment, as shown in FIG9 , a synaesthesia integrated frame structure configuration device is provided, comprising:

[0109] The acquisition module 902 is used to acquire the perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a number of flexible symbols, and the special time slot includes a number of flexible symbols, a number of guard interval symbols and a number of uplink symbols; acquire the current state; the current state includes the communication service demand and the perception service demand reported by the user equipment;

[0110] Configuration module 904 is used to use an artificial intelligence model to identify the current state and obtain the optimal ratio of perception and communication; according to the optimal ratio of perception and communication, the flexible symbol is configured as a downlink symbol or a perception symbol to obtain a configured perception frame structure.

[0111] In the above-mentioned synaesthesia integrated frame structure configuration device, the perception frame structure to be configured is obtained; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a number of flexible symbols, and the special time slot includes a number of flexible symbols, a number of protection interval symbols and a number of uplink symbols; the current state is obtained; the current state includes the communication service requirements and the perception service requirements reported by the user device; the current state is identified by the artificial intelligence model to obtain the best ratio of perception and communication; according to the best ratio of perception and communication, the flexible symbol is configured as a downlink symbol or a perception symbol to obtain a configured perception frame structure. Through the above-mentioned method, according to the needs of communication services and perception services, the perception frame structure is intelligently configured, and the perception service can be supported on demand while reducing the impact on communication performance and improving resource utilization. Compared with the preset frame structure, the perception frame structure configured in this application is more flexible and more adaptable to business characteristics, and there is no need to design multiple fixed frame structure formats in advance. At the same time, by configuring the perception frame structure, the communication signal and the perception signal are time-division multiplexed, avoiding the interference between the communication service and the perception service, and ensuring the quality of the communication service and the perception service.

[0112] In an exemplary embodiment, the apparatus further comprises:

[0113] A training module is used to construct training samples; the training samples include the state of the nth cycle, the configuration action of the nth cycle, the state of the n+1th cycle, and the reward of the nth cycle; n is an integer not less than 1; according to the training samples, reinforcement learning is performed on the artificial intelligence model to obtain a trained artificial intelligence model.

[0114] In an exemplary embodiment, the training module is also used to obtain the communication service execution completion degree and the perception service execution completion degree sent by each user device in the nth cycle; according to the set weight coefficient, the communication service execution completion degree and the perception service execution completion degree are weighted and summed to obtain the reward for the nth cycle.

[0115] In an exemplary embodiment, the configuration module 904 is also used to determine the ratio between the communication frame and the perception frame based on the characteristic information of the target area; generate time domain configuration information in which the communication frame and the perception frame are periodically arranged in the time domain according to the ratio between the communication frame and the perception frame; and configure the perception frame structure of the kth perception frame in the previous communication frame of the kth perception frame according to the time domain configuration information; k is an integer not less than 1.

[0116] In an exemplary embodiment, the apparatus further comprises:

[0117] The synchronization module is used to obtain neighboring cell information; based on the neighboring cell information, the configuration information of the perception frame structure in the target area is synchronized.

[0118] In an exemplary embodiment, the acquisition module 902 is also used to determine the communication service requirements and perceived service requirements received by each communication device in the target area during the current cycle; and determine the current state based on the communication service requirements and perceived service requirements received by each communication device in the target area.

[0119] Each module in the above-mentioned synaesthesia integrated frame structure configuration device can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the communication device in the form of hardware, or can be stored in the memory in the communication device in the form of software, so that the processor can call and execute the corresponding operations of each of the above modules.

[0120] In an exemplary embodiment, a communication device is provided, which may be a server, and its internal structure diagram may be shown in FIG10. The communication device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the communication device is used to provide computing and control capabilities. The memory of the communication device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the communication device is used to exchange information between the processor and an external device. The communication interface of the communication device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a frame structure configuration method for integrating synaesthesia is realized.

[0121] Those skilled in the art will understand that the structure shown in FIG. 10 is merely a block diagram of a partial structure related to the scheme of the present application, and does not constitute a limitation on the communication device to which the scheme of the present application is applied. The specific communication device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0122] In an exemplary embodiment, a communication device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the following steps when executing the computer program: obtaining a perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a number of flexible symbols, and the special time slot includes a number of flexible symbols, a number of protection interval symbols and a number of uplink symbols; obtaining a current state; the current state includes communication service requirements and perception service requirements reported by a user device; using an artificial intelligence model to identify the current state to obtain the best ratio of perception and communication; according to the best ratio of perception and communication, configuring the flexible symbols as downlink symbols or perception symbols to obtain a configured perception frame structure.

[0123] In one embodiment, the processor also implements the following steps when executing the computer program: constructing a training sample; the training sample includes the state of the nth cycle, the configuration action of the nth cycle, the state of the n+1th cycle, and the reward of the nth cycle; n is an integer not less than 1; based on the training sample, reinforcement learning is performed on the artificial intelligence model to obtain a trained artificial intelligence model.

[0124] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining the communication service execution completion degree and the perception service execution completion degree sent by each user device in the nth cycle; and taking a weighted sum of the communication service execution completion degree and the perception service execution completion degree according to the set weight coefficient to obtain a reward for the nth cycle.

[0125] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the ratio between the communication frame and the perception frame based on the characteristic information of the target area; generating time domain configuration information in which the communication frame and the perception frame are periodically arranged in the time domain based on the ratio between the communication frame and the perception frame; configuring the perception frame structure of the kth perception frame in the previous communication frame of the kth perception frame based on the time domain configuration information; k is an integer not less than 1.

[0126] In one embodiment, when the processor executes the computer program, the following steps are also implemented: obtaining neighboring cell information; and synchronizing configuration information of the perception frame structure in the target area based on the neighboring cell information.

[0127] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the communication service demands and perceived service demands received by each communication device in the target area during the current cycle; and determining the current state based on the communication service demands and perceived service demands received by each communication device in the target area.

[0128] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: obtaining a perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a number of flexible symbols, and the special time slot includes a number of flexible symbols, a number of protection interval symbols and a number of uplink symbols; obtaining a current state; the current state includes communication service requirements and perception service requirements reported by a user device; using an artificial intelligence model to identify the current state to obtain the best ratio of perception and communication; according to the best ratio of perception and communication, the flexible symbols are configured as downlink symbols or perception symbols to obtain a configured perception frame structure.

[0129] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: constructing a training sample; the training sample includes the state of the nth cycle, the configuration action of the nth cycle, the state of the n+1th cycle, and the reward of the nth cycle; n is an integer not less than 1; based on the training sample, reinforcement learning is performed on the artificial intelligence model to obtain a trained artificial intelligence model.

[0130] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the communication service execution completion degree and the perception service execution completion degree sent by each user device in the nth cycle; taking weighted sum of the communication service execution completion degree and the perception service execution completion degree according to the set weight coefficient to obtain the reward for the nth cycle.

[0131] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the ratio between the communication frame and the perception frame based on the characteristic information of the target area; generating time domain configuration information of the periodic arrangement of the communication frame and the perception frame in the time domain based on the ratio between the communication frame and the perception frame; configuring the perception frame structure of the kth perception frame in the previous communication frame of the kth perception frame based on the time domain configuration information; k is an integer not less than 1.

[0132] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining neighboring cell information; and synchronizing configuration information of the perception frame structure in the target area based on the neighboring cell information.

[0133] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the communication service demands and perceived service demands received by each communication device in the target area during the current cycle; and determining the current state based on the communication service demands and perceived service demands received by each communication device in the target area.

[0134] In one embodiment, a computer program product is provided, including a computer program, which implements the following steps when executed by a processor: obtaining a perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a number of flexible symbols, and the special time slot includes a number of flexible symbols, a number of protection interval symbols and a number of uplink symbols; obtaining a current state; the current state includes communication service requirements and perception service requirements reported by a user device; using an artificial intelligence model to identify the current state to obtain the best ratio of perception and communication; according to the best ratio of perception and communication, the flexible symbols are configured as downlink symbols or perception symbols to obtain a configured perception frame structure.

[0135] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: constructing a training sample; the training sample includes the state of the nth cycle, the configuration action of the nth cycle, the state of the n+1th cycle, and the reward of the nth cycle; n is an integer not less than 1; based on the training sample, reinforcement learning is performed on the artificial intelligence model to obtain a trained artificial intelligence model.

[0136] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining the communication service execution completion degree and the perception service execution completion degree sent by each user device in the nth cycle; taking weighted sum of the communication service execution completion degree and the perception service execution completion degree according to the set weight coefficient to obtain the reward for the nth cycle.

[0137] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the ratio between the communication frame and the perception frame based on the characteristic information of the target area; generating time domain configuration information of the periodic arrangement of the communication frame and the perception frame in the time domain based on the ratio between the communication frame and the perception frame; configuring the perception frame structure of the kth perception frame in the previous communication frame of the kth perception frame based on the time domain configuration information; k is an integer not less than 1.

[0138] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: obtaining neighboring cell information; and synchronizing configuration information of the perception frame structure in the target area based on the neighboring cell information.

[0139] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the communication service demands and perceived service demands received by each communication device in the target area during the current cycle; and determining the current state based on the communication service demands and perceived service demands received by each communication device in the target area.

[0140] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0141] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0142] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0143] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for configuring a synaesthesia-integrated frame structure, characterized in that: The method comprises: Acquire a perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a plurality of flexible symbols, and the special time slot includes a plurality of flexible symbols, a plurality of guard interval symbols and a plurality of uplink symbols; Acquire the current state; the current state includes the communication service demand and the perception service demand reported by the user equipment; Using an artificial intelligence model to identify the current state and obtain the best ratio of perception and communication; According to the optimal ratio of the perception and the communication, the flexible symbol is configured as a downlink symbol or a perception symbol to obtain a configured perception frame structure.

2. The method according to claim 1, characterized in that The method further comprises: Constructing a training sample; the training sample includes the state of the nth cycle, the configuration action of the nth cycle, the state of the n+1th cycle, and the reward of the nth cycle; n is an integer not less than 1; According to the training samples, reinforcement learning is performed on the artificial intelligence model to obtain a trained artificial intelligence model.

3. The method according to claim 2, characterized in that The method further comprises: Obtaining the communication service execution completion degree and the perception service execution completion degree sent by each user equipment in the nth cycle; According to the set weight coefficient, the communication service execution completion degree and the perception service execution completion degree are weighted and summed to obtain the reward of the nth cycle.

4. The method according to claim 1, characterized in that: Before acquiring the perception frame structure to be configured, the method further includes: Determine the ratio between the communication frame and the perception frame according to the characteristic information of the target area; According to the ratio between the communication frame and the perception frame, generating time domain configuration information in which the communication frame and the perception frame are periodically arranged in the time domain; According to the time domain configuration information, the perception frame structure of the kth perception frame is configured in a communication frame before the kth perception frame; k is an integer not less than 1.

5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: Get neighboring area information; According to the neighboring area information, configuration information of the perception frame structure in the target area is synchronized.

6. The method according to any one of claims 1 to 4, characterized in that The obtaining of the current status includes: Determine the communication service requirements and the perception service requirements received by each communication device in the target area in the current period; A current state is determined according to the communication service demand and the perceived service demand received by each communication device in the target area.

7. A synaesthesia integrated frame structure configuration device, characterized in that: The device comprises: An acquisition module is used to acquire a perception frame structure to be configured; the perception frame structure includes an uplink time slot, a special time slot and a flexible time slot, the flexible time slot includes a number of flexible symbols, and the special time slot includes a number of flexible symbols, a number of guard interval symbols and a number of uplink symbols; acquire a current state; the current state includes a communication service demand and a perception service demand reported by a user device; A configuration module is used to use an artificial intelligence model to identify the current state and obtain the best ratio of perception and communication; according to the best ratio of perception and communication, the flexible symbol is configured as a downlink symbol or a perception symbol to obtain a configured perception frame structure.

8. A communication device, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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