Communication methods and communication devices

Abstract

This disclosure provides a communication method and a communication apparatus. The method includes: a communication device receives first information, the first information indicating process parameter information of at least one clear channel assessment of a first node; the communication device transmits second information, the second information indicating a clear channel assessment policy of the first node, the clear channel assessment policy being obtained based on the first information, the clear channel assessment policy including detection parameter information of the clear channel assessment; in this way, when the reliability of communication is satisfied, the probability of accessing the channel by the communication device is increased.

Description

Technical Field

[0001] [Cross - Reference to Related Applications] This application claims the priority of Chinese Patent Application No. 202111616630.8, titled "COMMUNICATION METHOD AND COMMUNICATION APPARATUS", filed with the China National Intellectual Property Administration on December 27, 2021, and the entire content thereof is incorporated herein by reference.

[0002] [Technical Field] This application relates to the field of communications, and more specifically, to a communication method and a communication apparatus.

Background Art

[0003] Unlicensed spectrum is a public communication resource that can be used without authorization in wireless communication resources. Unlicensed spectrum is distributed at 2.4 gigahertz (GHz), 5 GHz, 6 GHz, etc. Compared with limited licensed frequency band resources, unlicensed spectrum has advantages such as rich resources and low usage costs.

[0004] Although unlicensed spectrum can be used without authorization, the usage rules of unlicensed spectrum need to be complied with so that each communication device can use unlicensed spectrum resources fairly and avoid communication interference on unlicensed spectrum as much as possible. On the premise that the usage rules of unlicensed spectrum resources are satisfied, how to improve the efficiency of performing communication by using unlicensed spectrum is the focus of research on unlicensed - spectrum - based communication.

Summary of the Invention

[0005] This disclosure provides a communication method and a communication apparatus for increasing the probability that a communication device accesses a channel when communication reliability is satisfied.

[0006] According to a first embodiment, a communication method is provided. The method includes the steps of: receiving first information, the first information indicating process parameter information for at least one clear channel assessment of a first node; and transmitting second information, the second information indicating a clear channel assessment policy of the first node, the clear channel assessment policy being obtained based on the first information, and the clear channel assessment policy including detection parameter information for a clear channel assessment.

[0007] Based on the above solution, the second node can obtain the process parameter information for the first node's clear channel assessment by using the first information and provide the first node with a clear channel assessment policy obtained based on the first information. In this case, the first node can obtain a clear channel assessment policy suitable for its own node and increase the probability of accessing the channel when the rules for using the unlicensed spectrum are met and the reliability of unlicensed spectrum-based communication is met, thereby reducing the power consumption caused by frequent channel discovery failures of the first node.

[0008] Referring to the first aspect, in some implementations of the first aspect, the method further includes the step of obtaining a clear channel assessment policy through inference based on the first information.

[0009] Optionally, the step of obtaining a clear channel assessment policy through inference based on first information includes inputting the first information into an intelligent model and obtaining the clear channel assessment policy obtained through inference by the intelligent model.

[0010] Based on the above solution, artificial intelligence technology is applied to assist the first node in selecting appropriate clear channel assessment parameters based on historical data (e.g., process parameter information for clear channel assessment) using the unlicensed spectrum. As a result, the probability of the first node accessing the channel can be increased when the rules for using the unlicensed spectrum are met and the reliability of unlicensed spectrum-based communication is met.

[0011] Referring to the first embodiment, some implementations of the first embodiment further include the steps of transmitting first information to a second node and receiving second information from the second node.

[0012] Based on the above solution, the first node may be a terminal device, and the method may be performed by an access network node or a relay node. Information transmission is achieved through forwarding by the second node, and as a result, the first node can provide the first information to the network and obtain a clear channel assessment policy provided to the first node by the network and suitable for the first node.

[0013] Referring to the first embodiment, in some implementations of the first embodiment, the process parameter information is the following parameters, namely, The system includes one or more of the following: service priority information for the signal used to trigger a clear channel assessment, the clear channel assessment method, channel access priority information, contention window information, detection period information, energy detection threshold, or detection result information.

[0014] Optionally, the contention window information is set to the upper limit CW of the selected contention window. p , the initial count value N of the selected counter int This may include, but is not limited to, one or more parameters such as the number of detection periods in a single clear channel assessment.

[0015] Optionally, the detection period information may include, but is not limited to, the length of the detection period and / or the number of detection intervals within the detection period.

[0016] Optionally, the detection results information includes the following: This includes one or more of the following: the channel state determined after a clear channel assessment; the number or percentage of detection periods in which the channel was detected as clear; the number or percentage of detection periods in which the channel was detected as busy; or the energy values ​​detected during the detection interval.

[0017] In one implementation, the types of parameters specifically included in the process parameter information may be predefined in the protocol. In another implementation, the types of parameters specifically included in the process parameter information are indicated to the first node by a second node.

[0018] Based on the above solution, the first and second nodes reach an agreement on the parameter information of the clear channel assessment policy inferred by the second node, and the second node can obtain the parameters necessary to infer the clear channel assessment policy and infer an intelligent model based on the obtained parameters.

[0019] Referring to the first embodiment, in some implementations of the first embodiment, the clear channel assessment policy includes clear channel assessment detection parameter information corresponding to service priority information for at least one signal.

[0020] Referring to the first embodiment, in some implementations of the first embodiment, the clear channel assessment policy is as follows: It includes one or more of the following: service priority information for the signal to trigger a clear channel assessment, the clear channel assessment method, channel access priority information, contention window information, detection period information, or energy detection threshold.

[0021] Based on the above solution, the clear channel assessment policy provided to the first node by the second node includes one or more of the above detection parameters, and as a result, the first node can execute the clear channel assessment policy based on the corresponding detection parameter to achieve the effect of increasing the probability of accessing the channel.

[0022] Referring to the first aspect, in some implementations of the first aspect, the first information further includes transmission quality information, which indicates the quality of the data transmitted by the first node over an unlicensed spectral resource.

[0023] Optionally, the transmission quality information includes the following: The system displays one or more of the following: channel occupancy time for signal transmission, signal quality information, percentage of successful signal transmissions during a reference period, percentage of failed signal transmissions during a reference period, a first threshold, or information regarding a reference period for evaluating signal transmission quality. The first threshold is a threshold used to evaluate signal transmission quality.

[0024] Based on the above solution, the second node obtains process parameter information that the first node uses to detect the clear state of the channels in the unlicensed spectrum. Furthermore, the second node may also obtain transmission quality information of the communications performed by the first node using the unlicensed spectrum, and as a result, the second node can use the transmission quality information to obtain a clear channel assessment policy with a higher degree of agreement and provide the clear channel assessment policy to the first node.

[0025] Referring to the first embodiment, in some implementations of the first embodiment, the clear channel assessment policy is as follows: The system further includes one or more of the following: information regarding a reference period for evaluating signal transmission quality, a first threshold, the maximum channel occupancy time corresponding to a clear channel assessment, or transmission quality prediction information.

[0026] Based on the above solutions, the clear channel assessment policy may further include parameter information for evaluating transmission quality, thereby enabling the first node to evaluate transmission quality based on the evaluation parameter information and adjust the clear channel assessment parameters based on the transmission quality, thereby enabling the first node to adaptively adjust the clear channel assessment parameters. The clear channel assessment policy may further include a maximum channel occupancy time corresponding to the clear channel assessment, thereby enabling the first node to determine how long the channel can be occupied after it has been accessed by using the clear channel assessment policy, thereby avoiding cases of communication interference or violations of unlicensed spectrum usage rules caused by exceeding the occupancy time. Furthermore, the clear channel assessment policy may further include transmission quality prediction information, thereby enabling the first node to select a clear channel assessment method that satisfies the reliability requirements of signal transmission based on the transmission quality prediction information and the reliability requirements of the signal to be transmitted.

[0027] Referring to the first embodiment, some implementations of the first embodiment include the step of receiving first information from a first node, which is a step of periodically receiving first information, and at least one clear channel assessment is a clear channel assessment performed by the first node in one period.

[0028] Based on the above solution, the second node can periodically acquire the first information and provide the first node with a clear channel assessment policy acquired based on the first information. As a result, the clear channel assessment policy can be updated in a timely manner, and the number of cases in which communication reliability is reduced due to an inappropriate clear channel assessment policy when the channel changes can be reduced.

[0029] A communication method is provided according to a second embodiment. The method includes the steps of: transmitting first information, the first information indicating process parameter information for at least one clear channel assessment of a first node; and receiving second information, the second information indicating a clear channel assessment policy of the first node, the clear channel assessment policy being obtained based on the first information, and the clear channel assessment policy including detection parameter information for a clear channel assessment.

[0030] Referring to the second embodiment, in some implementations of the second embodiment, the method further includes the step of performing a clear channel assessment based on a clear channel assessment policy.

[0031] Referring to the second embodiment, in some implementations of the second embodiment, the process parameter information is the following parameters, namely, The system includes one or more of the following: service priority information for the signal used to trigger a clear channel assessment, the clear channel assessment method, channel access priority information, contention window information, detection period information, energy detection threshold, or detection result information.

[0032] Referring to the second embodiment, in some implementations of the second embodiment, the clear channel assessment policy includes clear channel assessment detection parameter information corresponding to service priority information for at least one signal.

[0033] Referring to the second aspect, in some implementations of the second aspect, the clear channel assessment policy is as follows: It includes one or more of the following: service priority information for the signal to trigger a clear channel assessment, the clear channel assessment method, channel access priority information, contention window information, detection period information, or energy detection threshold.

[0034] Referring to the second aspect, in some implementations of the second aspect, the first information further includes transmission quality information, which indicates the quality of the data transmitted by the first node over the unlicensed spectral resource.

[0035] Referring to the second embodiment, in some implementations of the second embodiment, the transmission quality information is as follows: The system displays one or more of the following: channel occupancy time for signal transmission, signal quality information, percentage of successful signal transmissions during a reference period, percentage of failed signal transmissions during a reference period, a first threshold, or information regarding a reference period for evaluating signal transmission quality. The first threshold is a threshold used to evaluate signal transmission quality.

[0036] Referring to the second aspect, in some implementations of the second aspect, the clear channel assessment policy is as follows: The system further includes one or more of the following: information regarding a reference period for evaluating signal transmission quality, a first threshold, the maximum channel occupancy time corresponding to a clear channel assessment, or transmission quality prediction information. The first threshold is a threshold used to evaluate signal transmission quality.

[0037] Referring to the second embodiment, some implementations of the second embodiment include the step of transmitting first information being a step of periodically transmitting first information, and at least one clear channel assessment being a clear channel assessment performed by the first node in one period.

[0038] According to a third embodiment, a communication method is provided. The method includes the steps of receiving first information, the first information representing process parameter information of at least one clear channel assessment of a first node, The first step is to train an intelligent model based on the information. Includes.

[0039] Referring to the third aspect, in some implementations of the third aspect, the step of training an intelligent model based on first information includes the steps of inputting the first information into the intelligent model to obtain a clear channel assessment policy output by the intelligent model; obtaining updated model parameters of the intelligent model based on the clear channel assessment policy; and updating the parameters of the intelligent model based on the updated model parameters to obtain an updated intelligent model.

[0040] Referring to the third aspect, in some implementations of the third aspect, the step of obtaining updated model parameters of an intelligent model based on a clear channel assessment policy includes, by using a loss function, the step of obtaining model check information based on the clear channel assessment policy, and, if the model check information does not satisfy predefined conditions, the step of obtaining updated model parameters based on the model check information.

[0041] Referring to the third aspect, in some implementations of the third aspect, the current intelligent model is used as a trained intelligent model if the model check information satisfies pre-defined conditions.

[0042] Optionally, the trained intelligent model may infer a clear channel assessment policy for the first node in actual communication.

[0043] According to a fourth aspect, a communication device is provided. In a certain design, the device may include a module for performing the method / operation / step / action described in the first aspect. The module may be a hardware circuit, software, or implemented using a combination of hardware circuit and software. In a certain design, the device includes a transceiver unit configured to receive first information, the first information indicating process parameter information for at least one clear channel assessment of a first node. The transceiver unit is further configured to transmit second information, the second information indicating a clear channel assessment policy of a first node, the clear channel assessment policy being obtained based on the first information, and the clear channel assessment policy including detection parameter information for a clear channel assessment.

[0044] Optionally, the device further includes a processing unit configured to obtain a clear channel assessment policy through inference based on the first information.

[0045] According to a fifth aspect, a communication device is provided. In a certain design, the device may include a module for performing the method / operation / step / action described in the second aspect. The module may be a hardware circuit, software, or implemented using a combination of hardware circuit and software. In a certain design, the device includes a transceiver unit configured to transmit first information, the first information indicating process parameter information for at least one clear channel assessment of a first node. The transceiver unit is configured to receive second information, the second information indicating a clear channel assessment policy of a first node, the clear channel assessment policy being obtained based on the first information, and the clear channel assessment policy including detection parameter information for a clear channel assessment.

[0046] Optionally, the device further includes a processing unit configured to determine process parameters for at least one channel assessment policy.

[0047] According to the sixth aspect, a communication device is provided. In a certain design, the device may include a module for performing the method / operation / step / action described in the third aspect. The module may be hardware circuitry, software, or implemented using a combination of hardware circuitry and software. In a certain design, the device includes a transceiver unit configured to receive first information, the first information representing process parameter information of at least one clear channel assessment of a first node, and a processing unit configured to train an intelligent model based on the first information.

[0048] According to the seventh aspect, a communication device is provided, which includes a processor. The processor may implement a method in any one of the first aspect, the third aspect, and any possible implementation of the first or third aspect. Optionally, the communication device further includes memory. The processor may be coupled to the memory and configured to execute instructions in the memory to implement a method in any one of the first aspect, the third aspect, and any possible implementation of the first or third aspect. Optionally, the communication device further includes a communication interface, and the processor is coupled to the communication interface. In this disclosure, the communication interface may be a transceiver, a pin, a circuit, a bus, a module, or any other type of communication interface; however, it is not limited thereto.

[0049] According to the eighth aspect, a communication device is provided, which includes a processor. The processor may implement a method in the second aspect and any one of the possible implementations of the second aspect. Optionally, the communication device further includes memory. The processor may be coupled to the memory and configured to execute instructions in the memory to implement a method in the second aspect and any one of the possible implementations of the second aspect. Optionally, the communication device further includes a communication interface, and the processor is coupled to the communication interface.

[0050] According to the communication device provided in the seventh or eighth embodiment, in one implementation, when the communication device is a communication device, the communication interface may be a transceiver. Optionally, the transceiver may be a transceiver circuit. In other implementations, when the communication device is a chip configured within a communication device, the communication interface may be an input / output interface.

[0051] Optionally, the input / output interface may include input and output circuits.

[0052] In a particular implementation process, the input circuit may be an input pin, the output circuit may be an output pin, and the processor may be a transistor, a gate circuit, a trigger, various logic circuits, etc. The input signal received by the input circuit may be received and input by a receiver, for example, but not limited to this case, and the signal output by the output circuit may be output to a transmitter and transmitted by the transmitter, for example, but not limited to this case, and the input circuit and the output circuit may be the same circuit, and the circuit may be used as an input circuit and an output circuit at different times. Specific implementations of the processor and various circuits are not limited in this disclosure.

[0053] According to the ninth aspect, a computer program product is provided. The computer program product includes a computer program (which may also be called code or instructions). When the computer program is executed, the computer becomes capable of performing any one of the methods in the first to third aspects and the possible implementations of the first to third aspects.

[0054] According to the tenth aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program (which may also be called code or instructions). When the computer program is executed on a computer, the computer becomes capable of performing any one of the methods in the first to third aspects and the possible implementations of the first to third aspects.

[0055] According to the eleventh aspect, a communication system is provided and includes at least one device configured to implement a terminal method and at least one device configured to implement an access network node method. [Brief explanation of the drawing]

[0056] [Figure 1] This is a diagram of the communication system disclosed. [Figure 2] This is an illustrative diagram of an AI application framework in a communication system as disclosed. [Figure 3A] This is a diagram of the network architecture provided in this disclosure. [Figure 3B] This is a diagram of the network architecture provided in this disclosure. [Figure 3C] This is a diagram of the network architecture provided in this disclosure. [Figure 3D] This is a diagram of the network architecture provided in this disclosure. [Figure 3E] This is a diagram of the network architecture provided in this disclosure. [Figure 3F]This is a diagram of the network architecture provided in this disclosure. [Figure 4] This is a diagram of the communication method disclosed. [Figure 5] This is a schematic flowchart of the Clear Channel Assessment Method 1 as disclosed. [Figure 6] This diagram shows the detection period in Clear Channel Assessment Method 2 as disclosed. [Figure 7] This diagram shows the detection period in Clear Channel Assessment Method 3 as disclosed. [Figure 8] This is an illustrative diagram of the training process for the intelligent model described in this disclosure. [Figure 9] This is another diagram of the communication method disclosed. [Figure 10] This is yet another diagram of the communication method disclosed. [Figure 11] This is a schematic block diagram of an example of a communication device according to the embodiments of this disclosure. [Figure 12] This is a diagram showing the structure of an example terminal device according to this embodiment of disclosure. [Figure 13] This is a diagram showing the structure of an example network device according to this embodiment of disclosure. [Modes for carrying out the invention]

[0057] In this disclosure, at least one item may also be described as one or more items, and the number of items may be two, three, four or more, but is not limited to these. " / " may represent an "or" relationship between the related objects. For example, A / B may represent A or B. "And / or" may indicate that there are three relationships between the related objects. For example, A and / or B may represent three cases: that only A exists, that both A and B exist, and that only B exists, and A and B may be singular or plural. To facilitate the description of the technical solutions of this disclosure, phrases such as "first," "second," "A," or "B" may be used to distinguish technical features that have the same or similar function. The phrases such as "first," "second," "A," or "B" are not limited in number or execution order. Furthermore, phrases such as "first," "second," "A," or "B" do not indicate clear distinctions. Phrases such as "example" or "for example" are used to represent examples, evidence, or explanations. Any design solution described as "example" or "for example" should not be described as being preferable to or having more advantages than other design solutions. Phrases such as "example" and "for example" are used to present relevant concepts in a concrete manner to facilitate understanding.

[0058] The technical solutions of this disclosure are described below with reference to the attached drawings.

[0059] Figure 1 is a diagram of the architecture of a communication system 1000 to which this disclosure applies. As shown in Figure 1, the communication system includes a radio access network (RAN) 100 and a core network (CN) 200. Optionally, the communication system 1000 may further include an internet 300. The radio access network 100 may include at least one access network device (e.g., 110a and 110b in Figure 1) and may further include at least one terminal (e.g., 120a to 120j in Figure 1). The terminal is connected to the access network device wirelessly, and the terminal may perform wireless communication with the access network device by using unlicensed spectral resources. The terminal may be connected to another terminal wirelessly, and the terminal may perform wireless communication with another terminal by using unlicensed spectral resources. The access network device is connected to the core network wirelessly or wired. The core network device and the access network device may be different, independent physical devices, or they may be the same physical device integrating the functions of the core network device and the access network device. Alternatively, other possible scenarios may exist. For example, one physical device may integrate the functions of the access network device and some of the functions of the core network device, while another physical device implements the remaining functions of the core network device. The physical form of existence of the core network device and the access network device is not limited in this disclosure. The access network devices may be connected to each other by wire or wireless means. Figure 1 is merely a diagram. The communication system may further include other network devices, such as wireless relay devices and wireless backhaul devices. The communication device shown in Figure 1 may perform wireless communication by using unlicensed spectral resources.When performing communication using unlicensed spectrum resources, a communication device may obtain a clear channel assessment policy by using the communication method provided in this disclosure and perform a clear channel assessment of the unlicensed spectrum based on the obtained clear channel assessment policy.

[0060] Access network devices may include base stations, Node B, evolved Node B (eNode B or eNB), transmission reception points (TRP), next-generation Node B (gNB) in 5th generation (5G) mobile communication systems, access network devices in open radio access networks (O-RAN or open RAN), next-generation base stations in 6th generation (6G) mobile communication systems, base stations in future mobile communication systems, and access nodes in wireless fidelity (Wi-Fi) systems. Alternatively, access network devices may be modules or units that complete some of the functions of a base station, such as central units (CU), distributed units (DU), central unit control plane (CU-CP) modules, or central unit user plane (CU-UP) modules. The access network device may be a macro base station (e.g., 110a in Figure 1), or a micro base station or indoor base station (e.g., 110b in Figure 1), or a relay node, donor node, etc. The specific technologies and device forms used by the access network device are not limited in this disclosure. A 5G system may also be called a new radio (NR) system. An access network node in this disclosure may be an access network device, or a module or unit located within an access network device.

[0061] In this disclosure, the device configured to implement the functions of an access network device may be an access network device, or a device capable of supporting an access network device in implementing its functions, such as a chip system, hardware circuitry, software modules, or hardware circuitry and software modules. The device may be installed on an access network device, or may be adapted with an access network device for use. In this disclosure, a chip system may include a chip, or may include a chip and other discrete components. For ease of explanation, the technical solutions provided in this disclosure will be described below using an example in which the device configured to implement the functions of an access network device is an access network device, and the access network device is a base station.

[0062] (1) Protocol layer structure

[0063] Communication between an access network device and a terminal conforms to a specified protocol layer structure. The protocol layer structure may include a control plane protocol layer structure and a user plane protocol layer structure. For example, the control plane protocol layer structure may include the functions of protocol layers such as the radio resource control (RRC) layer, the packet data convergence protocol (PDCP) layer, the radio link control (RLC) layer, the media access control (MAC) layer, and the physical (PHY) layer. For example, the user plane protocol layer structure may include the functions of protocol layers such as the PDCP layer, the RLC layer, the MAC layer, and the physical layer. In possible implementations, a service data adaptation protocol (SDAP) layer may be further included on top of the PDCP layer.

[0064] Optionally, the protocol layer structure between the access network device and the terminal may further include an AI layer for transmitting data related to artificial intelligence (AI) functions.

[0065] The protocol layer structure between an access network device and a terminal may be considered as an access stratum (AS) structure. Optionally, a non-access stratum (NAS) may exist on top of the AS, used by the access network device to transfer information from the core network device to the terminal, or used by the access network device to transfer information from the terminal to the core network device. In this case, a logical interface may be considered to exist between the terminal and the core network device. The access network device may transfer information between the terminal and the core network device using a transparent transmission method. For example, NAS signaling may be mapped to RRC signaling, or it may be included in RRC signaling and function as an element of RRC signaling.

[0066] (2) Central unit (CU) and distributed unit (DU)

[0067] Access network devices may include CUs and DUs. Multiple DUs may be centrally controlled by a single CU. For example, the interface between a CU and a DU may be called an F1 interface. The control plane (CP) interface may be F1-C, and the user plane (UP) interface may be F1-U. The specific names of the interfaces are not limited in this disclosure. CUs and DUs may be classified based on the protocol layers of the wireless network. For example, the functions of the PDCP layer and the protocol layers above the PDCP layer (such as the RRC layer and SDAP layer) are configured in the CU, and the functions of the protocol layers below the PDCP layer (RLC layer, MAC layer, and PHY layer) are configured in the DU. In other examples, the functions of the protocol layers above the PDCP layer are configured in the CU, and the functions of the PDCP layer and the protocol layers below the PDCP layer are configured in the DU. This is not limited.

[0068] The division of CU and DU processing functions based on protocol layers is merely an example, and the processing functions of CU and DU may be divided in other ways as an alternative. For example, a CU or DU may be divided into functions with more protocol layers. In another example, a CU or DU may be further divided into parts of processing functions with protocol layers. In one design, some of the functions of the RLC layer and the functions of the protocol layer above the RLC layer are configured on the CU, and the remaining functions of the RLC layer and the functions of the protocol layer below the RLC layer are configured on the DU. In other designs, the division of CU or DU functions may be performed on service type or other system requirements as an alternative. For example, the division may be performed on latency. Functions where processing time must meet latency requirements are set on the DU, and functions where processing time does not need to meet latency requirements are set on the CU. In other designs, a CU may, as an alternative, have one or more functions of the core network. For example, a CU may be located on the network side to facilitate central management. In other designs, the radio unit (RU) of the DU is located remotely. Optionally, the RU may have radio frequency functionality.

[0069] Optionally, DU and RU may be separated in the PHY layer. For example, DU may implement higher-layer functions in the PHY layer, and RU may implement lower-layer functions in the PHY layer. When the PHY layer is used for transmission, its functions may include at least one of the following: cyclic redundancy check (CRC) bit addition, channel coding, rate matching, scrambling, modulation, layer mapping, precoding, resource mapping, physical antenna mapping, or radio frequency transmission. When the PHY layer is used for reception, its functions may include at least one of the following: CRC check, channel decoding, rate dematching, descrambling, demodulation, layer demapping, channel detection, resource demapping, physical antenna demapping, or radio frequency reception. The higher-layer functions of the PHY layer may include some of the functions of the PHY layer. Some of these functions are closer to the MAC layer. The lower-layer functions of the PHY layer may include other parts of the functions of the PHY layer. For example, some of these functions are closer to the radio frequency reception function. For example, the upper layer functions of the PHY layer may include CRC bit addition, channel coding, rate matching, scrambling, modulation, and layer mapping, while the lower layer functions of the PHY layer may include precoding, resource mapping, physical antenna mapping, and radio frequency transmission. Alternatively, the upper layer functions of the PHY layer may include CRC bit addition, channel coding, rate matching, scrambling, modulation, layer mapping, and precoding. The lower layer functions of the PHY layer may include resource mapping, physical antenna mapping, and radio frequency transmission. For example, the upper layer functions of the PHY layer may include CRC inspection, channel decoding, rate dematching, decoding, demodulation, and layer demapping, while the lower layer functions of the PHY layer may include channel detection, resource demapping, physical antenna demapping, and radio frequency reception.Alternatively, the upper layer functions of the PHY layer may include CRC inspection, channel decoding, rate dematching, decoding, demodulation, layer demapping, and channel detection, and the lower layer functions of the PHY layer may include resource demapping, physical antenna demapping, and radio frequency reception.

[0070] Optionally, the functionality of a CU may be implemented by one entity (or module) or by different entities. For example, the functionality of a CU may be further divided, with the control plane and user plane being implemented separately using different entities. These separated entities are the control plane CU entity (i.e., the CU-CP entity) and the user plane CU entity (i.e., the CU-UP entity), respectively. The CU-CP entity and the CU-UP entity may be coupled to a DU to jointly complete the functionality of the access network device.

[0071] Optionally, one of DU, CU, CU-CP, CU-UP, and RU may be a software module, a hardware structure, or a combination of a software module and a hardware structure. This is not limited to these. Different entities may exist in different forms. This is not limited to these. For example, DU, CU, CU-CP, and CU-UP are software modules, and RU is a hardware structure. For the sake of brevity, not all possible combinations are listed here. These modules and the methods performed by these modules are also within the scope of protection of this disclosure.

[0072] Terminals may also be called terminal devices, user equipment (UE), mobile stations, mobile terminals, etc. Terminals may be widely used in various scenarios for communication. For example, scenarios include, but are not limited to, at least one of the following: enhanced mobile broadband (eMBB), ultra-reliable low-latency communication (URLLC), massive machine-type communication (mmTC), device-to-device (D2D), vehicle-to-everything (V2X), machine-type communication (MTC), Internet of Things (IoT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grids, smart furniture, smart offices, smart wearables, smart transportation, smart cities, etc. The terminal may be a mobile phone, tablet computer, computer with wireless transceiver functionality, wearable device, vehicle, unmanned aerial vehicle, helicopter, airplane, ship, robot, robotic arm, smart home device, etc. Specific technologies and device forms used by the terminal are not limited in this disclosure.

[0073] In this disclosure, the device configured to implement the functions of a terminal may be a terminal, or a device capable of supporting a terminal in performing its functions, such as a chip system, hardware circuitry, software module, or hardware circuitry and software module. The device may be installed in a terminal, or may be adapted with a terminal for use. For ease of explanation, the technical solutions provided in this disclosure will be described below by using an example in which the device configured to implement the functions of a terminal is a terminal, and optionally by using an example in which the terminal is a UE.

[0074] Base stations and / or terminals may be fixed or mobile. Base stations and / or terminals may be located on the ground, including indoor or outdoor scenarios, and handheld or vehicle-mounted scenarios, on water, or in the air on airplanes, balloons, and satellites. The environments / scenarios in which base stations and terminals are located are not limited in this disclosure. Base stations and terminals may be located in the same environment / scenarios or in different environments / scenarios. For example, base stations and terminals may both be located on the ground. Alternatively, a base station may be located on the ground and a terminal on water. Examples are not provided one by one.

[0075] The roles of base stations and terminals may be relative. For example, the helicopter or unmanned aerial vehicle 120i in Figure 1 may be configured as a mobile base station. For terminal 120j, which accesses the radio access network 100 through 102i, terminal 120i is a base station. However, for base station 110a, 120i is a terminal. In other words, 110a and 120i communicate with each other based on the radio air interface protocol. Alternatively, 110a and 120i communicate with each other based on the interface protocol between base stations. In this case, for 110a, 120i is also a base station. Therefore, both base stations and terminals may be collectively referred to as communication equipment (or communication devices). 110a and 110b in Figure 1 may be called communication equipment having base station functionality, and 120a to 120j in Figure 1 may be called communication equipment having terminal functionality.

[0076] Communication between base stations and terminals, between base stations, and between terminals may be performed on licensed frequency bands, on unlicensed spectrum, or on both licensed and unlicensed frequency bands. Communication may be performed on frequency bands below 6 gigahertz (GHz), on frequency bands above 6 GHz, or simultaneously on frequency bands below 6 GHz and above 6 GHz. The frequency band resources used for wireless communication are not limited in this disclosure.

[0077] In this disclosure, independent network elements (e.g., referred to as AI network elements, AI nodes, or AI devices) may be introduced into the communication system shown in Figure 1 to implement AI-related operations. The AI ​​network elements may be directly connected to a base station or indirectly connected to a base station through a third-party network element. Optionally, the third-party network element may be a core network element such as an access and mobility management function (AMF) network element or a user plane function (UPF) network element. Alternatively, artificial intelligence concrete (AIC) may be placed in other network elements within the communication system to implement AI-related operations. The AI ​​concrete may be referred to as an AI module or by other names. Optionally, the other network elements may be a base station, a core network device, or network management (OAM), etc. In this case, the network element that performs the AI-related operations is a network element with built-in AI functionality. Since both the AI ​​network element and the AI ​​concrete implement AI-related functions, for ease of explanation, the AI ​​network element and the network element with built-in AI functionality will be collectively referred to as an AI unit below. OAM is configured to operate, manage, and / or maintain core network devices (network management of core network devices), and / or to operate, manage, and / or maintain access network devices (network management of access network devices).

[0078] Optionally, to adapt to and support AI, AI concrete may be integrated into a terminal or terminal chip.

[0079] Optionally, in this disclosure, AI concrete may also be referred to by other names, such as AI module or AI unit, and is configured primarily to perform AI functions (which may also be called AI-related operations). The specific names of AI concrete are not limited in this disclosure.

[0080] In this disclosure, an AI model is a specific method for realizing AI functionality. An AI model represents a mapping relationship between the inputs and outputs of a model. An AI model may be a neural network or other machine learning model. An AI model may be abbreviated as a model. AI-related operations may include at least one of the following: data collection, model training, model information release, model inference (also called model inference, inference, prediction, etc.), inference result release, etc.

[0081] Figure 2 is an illustrative diagram of a first application framework for AI in a communication system. In Figure 2, the data source is configured to store training data and inference data. The model training host analyzes or trains the training data provided by the data source to obtain an AI model and deploys the AI ​​model on the model inference host. The AI ​​model represents the mapping relationship between the model's inputs and outputs. Obtaining the AI ​​model through learning by the model training host is equivalent to obtaining the mapping relationship between the model's inputs and outputs through learning by the model training host using the training data. The model inference host uses the AI ​​model to perform inference based on the inference data provided by the data source and obtains the inference result. This method may also be described as follows: The model inference host inputs the inference data into the AI ​​model and obtains the output by using the AI ​​model. The output is the inference result. The inference result may indicate configuration parameters used (acted upon) by the action subject, and / or actions performed by the action subject. The inference results may be planned in a unified manner by the actor entity and sent to one or more subjects of the action (e.g., network elements) for the action. Optionally, the model inference host may feed back its inference results to the model training host. This process may be called model feedback. The fed-back parameters are used by the model training host to update the AI ​​model, and the updated AI model is deployed to the model inference host. Optionally, the subject of the action may feed back network parameters collected by the subject of the action to a data source. This process may be called performance feedback. The fed-back parameters may be used as training data or inference data.

[0082] In this disclosure, the application framework shown in Figure 2 may be deployed to the network elements shown in Figure 1. For example, the application framework in Figure 2 may be deployed to at least one of the terminal device, access network device, core network device, or independently deployed AI network element (not shown) in Figure 1. For example, an AI network element (which may be considered a model training host) may analyze or train a model using training data provided by the terminal device and / or access network device. At least one of the terminal device, access network device, or core network device (which may be considered a model inference host) may perform inference using the model and inference data to obtain the model's output. The inference data may be provided by the terminal device and / or access network device. The model's input includes the inference data, and the model's output is the inference result corresponding to the model. At least one of the terminal device, access network device, or core network device (which may be considered an action subject) may perform a corresponding action based on the inference data and / or the inference result. The model inference host and the action subject may be the same or different, but are not limited to this.

[0083] The following describes the network architectures to which the communication solutions provided in this disclosure can be applied, with reference to Figures 3A to 3D.

[0084] As shown in Figure 3A, in the first possible implementation, the access network device includes a quasi-real-time access network intelligent controller (RAN intelligent controller, RIC) module configured to perform model training and inference. For example, the quasi-real-time RIC may be configured to train an AI model, and inference is performed by using the AI ​​model. For example, the quasi-real-time RIC may obtain information about the network side and / or terminal side from at least one of the CU, DU, or RU, and this information may be used as training data or inference data. Optionally, the quasi-real-time RIC may submit inference results to at least one of the CU, DU, or RU. Optionally, the CU and DU may exchange inference results. Optionally, the DU and RU may exchange inference results. For example, the quasi-real-time RIC submits inference results to the DU, and the DU forwards the inference results to the RU.

[0085] As shown in Figure 3B, in the second possible implementation, the non-real-time RIC is located outside the access network device (optionally, the non-real-time RIC may be located in the OAM or core network device) and is configured to perform model training and inference. For example, the non-real-time RIC is configured to train an AI model, and inference is performed by using the model. For example, the non-real-time RIC may obtain information about the network side and / or terminal side from at least one of the CU, DU, or RU. This information may be used as training data or inference data, and the inference results may be submitted to at least one of the CU, DU, or RU. Optionally, the CU and DU may exchange inference results. Optionally, the DU and RU may exchange inference results. For example, the non-real-time RIC submits the inference results to the DU, and the DU forwards the inference results to the RU.

[0086] As shown in Figure 3C, in the third possible implementation, the access network device includes a quasi-real-time RIC, and the non-real-time RIC is located outside the access network device (optionally, the non-real-time RIC may be located in the OAM or core network device). Similar to the second possible implementation, the non-real-time RIC may be configured to perform model training and inference, and / or, similar to the first possible implementation, the quasi-real-time RIC may be configured to perform model training and inference, and / or, the quasi-real-time RIC may obtain AI model information from the non-real-time RIC, obtain network-side and / or terminal-side information from at least one of the CU, DU, or RU, and obtain inference results using the information and AI model information. Optionally, the quasi-real-time RIC may submit the inference results to at least one of the CU, DU, or RU. Optionally, the CU and DU may exchange inference results. Optionally, the DU and RU may exchange inference results. For example, the quasi-real-time RIC submits the inference results to the DU, and the DU forwards the inference results to the RU. For example, a quasi-real-time RIC trains model A and performs inference using model A. For example, a non-real-time RIC trains model B and performs inference using model B. For example, a non-real-time RIC is configured to train model C and submit model C to a quasi-real-time RIC, which then performs inference using model C.

[0087] Figure 3D is an illustrative diagram of a network architecture to which the method described herein can be applied. Compared to Figure 3C, in Figure 3C the CU is separated into CU-CP and CU-UP.

[0088] Figure 3E is an illustrative diagram of a network architecture to which the methods described herein can be applied. As shown in Figure 3D, optionally, an access network device includes one or more AI concretes, the functionality of which is similar to that of a quasi-real-time RIC. Optionally, an OAM includes one or more AI concretes, the functionality of which is similar to that of a non-real-time RIC. Optionally, a core network device includes one or more AI concretes, the functionality of which is similar to that of a non-real-time RIC. When the OAM and the core network device each include AI concretes, the models obtained through training with the AI ​​concretes of the OAM and the core network device are different, and / or the models used for inference are different.

[0089] In this disclosure, the models differ with respect to at least one of the following: the structural parameters of the model (e.g., the number of layers in the model, the width of the model, the connectivity between layers, the weights of neurons, the activation functions of neurons, or the offsets of the activation functions), the input parameters of the model (e.g., the type and / or dimensions of the input parameters), or the output parameters of the model (e.g., the type and / or dimensions of the output parameters).

[0090] Figure 3F is an exemplary diagram of a network architecture to which the method described herein can be applied. Compared to Figure 3E, in Figure 3F the access network devices are separated into CUs and DUs. Optionally, the CU may contain AI concrete, the functionality of which is similar to that of a quasi-real-time RIC. Optionally, the DU may contain AI concrete, the functionality of which is similar to that of a quasi-real-time RIC. When the CU and DU each contain AI concrete, the models acquired through training with the AI ​​concrete of the CU and DU are different, and / or the models used for inference are different. Optionally, the CU in Figure 3E may be further divided into CU-CP and CU-UP. Optionally, one or more AI models may be deployed in the CU-CP. Optionally, one or more AI models may be deployed in the CU-UP.

[0091] Optionally, as shown above, in Figure 3E or Figure 3F, the OAM for the access network device and the OAM for the core network device may be deployed separately.

[0092] In this disclosure, one or more parameters may be obtained through inference by using a single model. The training processes for different models may be deployed on different devices or nodes, or on the same device or node. The inference processes for different models may be deployed on different devices or nodes, or on the same device or node.

[0093] The network architectures and service scenarios described in this disclosure are intended to provide a clearer illustration of the technical solutions in this disclosure and do not constitute an limitation on the technical solutions provided herein. Those skilled in the art will recognize that, as network architectures evolve and new service scenarios emerge, the technical solutions provided in this disclosure may also be applicable to similar technical problems.

[0094] Communication devices must meet regulatory requirements set by the radio regulatory body in order to perform communications using unlicensed spectrum. For example, communication devices in wireless fidelity (Wi-Fi) systems, 4th generation (4G) mobile communications long-term evolution (LTE) systems, and 5th generation (5G) mobile communications new radio (NR) systems can all perform communications in the unlicensed spectrum of the 5 GHz frequency band. To ensure fair coexistence of systems, regulatory requirements specify that communication devices using spectrum resources in a frequency band must perform a clear channel assessment (CCA) on the spectrum resources in units of a specified bandwidth to determine whether the channel in the unlicensed spectrum is clear. When it is determined that the channel is clear, the channel is accessible, or in other words, signals can be transmitted using the unlicensed spectrum resource. Clear channel assessment may also be called listen before talk (LBT).

[0095] When regulatory requirements are met, communication devices may autonomously select relevant parameters for performing a clear channel assessment. This disclosure proposes that artificial intelligence techniques be applied to assist communication devices in selecting relevant parameters for a clear channel assessment, and that, provided that the rules for using unlicensed spectrum are met, the probability of accessing a channel by using unlicensed spectrum and the reliability of communication devices performing communications will be increased.

[0096] The communication method provided in this disclosure will be described below with reference to the attached drawings.

[0097] Figure 4 is a schematic flowchart of the communication method 400 according to this disclosure. The first node shown in Figure 4 is a communication node that can perform communication by using an unlicensed spectrum, and the second node can determine a policy for the first node to perform a clear channel assessment based on relevant parameters obtained from the first node. It should be noted that the first and second nodes may be two communication devices, the first and second nodes may be devices (chips, etc.) separately located in different communication devices, or the first and second nodes may be two modules / devices located in the same communication device. This is not limited to this application. The communication method includes, but is not limited to, the following steps.

[0098] S401: The first node transmits the first information to the second node, the first information indicating process parameter information for at least one clear channel assessment of the first node.

[0099] Correspondingly, the second node receives the first information from the first node and determines the process parameter information for at least one clear channel assessment of the first node based on the first information.

[0100] The first node transmits the first information to the second node, and by using the first information, provides the second node with the parameter information required by the second node to infer a clear channel assessment policy, so that the second node can infer the clear channel assessment policy of the first node based on the first information.

[0101] In this implementation, the first node may periodically transmit the first information to the second node, and at least one clear channel assessment is a clear channel assessment performed by the first node in one cycle.

[0102] In other implementations, the first node may send first information to the second node when the clear channel assessment is performed a predetermined number of times, the first information indicating process parameter information for the predetermined number of clear channel assessments.

[0103] For example, a predetermined number of times may be notified by the second node, or it may be defined in advance in the protocol.

[0104] In other implementations, the second node may send instruction information to the first node, instructing the first node to send the first information. After receiving the instruction information, the first node sends the first information to the second node.

[0105] Optionally, the instruction information may instruct the first node to send process parameter information for the most recent N clear channel assessments. After receiving the instruction information, the first node uses the first information to provide the process parameter information for the most recent N clear channel assessments. N is a positive integer. The value of N is agreed upon in the protocol or notified by the second node, but is not limited to this.

[0106] In a specific implementation, the number of clear channel assessments in at least one clear channel assessment may be determined based on the specific implementation. The first information may represent process parameter information for one clear channel assessment performed by the first node, or the first information may represent process parameter information for each clear channel assessment in multiple clear channel assessments performed by the first node. This is not limited to this disclosure.

[0107] When the rules for using unlicensed spectral resources are met, the first node may select a clear channel assessment scheme from several clear channel assessment schemes to perform channel detection based on the signal to be transmitted (which may be control information, data, reference signals, etc.). Different clear channel assessment schemes may have different durations for which a channel is allowed to be occupied after it has been accessed (called channel occupancy time, COT). A longer COT indicates that more resources are available. Correspondingly, more data can be transmitted. Optionally, the first node may determine the clear channel assessment scheme based on the service priority of the signal to be transmitted (a clear channel assessment scheme may also be called a clear channel assessment type). For example, the first node may select a clear channel assessment scheme that conforms to the service priority based on the service priority of the signal to be transmitted. For example, the first node may divide the service priority based on the amount of data, and different amounts of data may correspond to detection schemes with different COTs. In other examples, service priorities may be segmented based on latency requirements. Services with higher latency requirements may correspond to clear channel assessment schemes with shorter detection times and correspondingly shorter channel occupancy times. In other examples, service priorities may be segmented based on reliability requirements. Services with higher reliability requirements may correspond to clear channel assessment schemes with longer detection times. To satisfy reliability requirements, channels are determined to be clear and have low interference through as many detections as possible. Services with lower reliability requirements may correspond to clear channel assessment schemes with shorter detection times. However, this disclosure is not limited to these examples.

[0108] To better understand the communication method provided in this disclosure, the following first describes four clear channel assessment methods. It should be understood that the clear channel assessment method used in a specific implementation manner is not limited in this disclosure.

[0109] Method 1

[0110] FIG. 5 is a schematic flowchart of the clear channel assessment method 1. In the clear channel assessment method 1, the channel access priority is determined based on the service priority of the signal to be transmitted, and the parameters of the clear channel assessment method with the corresponding priority may be determined based on Table 1. [Table 1]

[0111] The clear channel assessment in Method 1 includes, but is not limited to, the following steps.

[0112] 1. The first node determines the channel access priority p based on the service priority of the signal to be transmitted and sets CW p to CW min,p .

[0113] After determining the channel access priority p based on the service priority of the signal to be transmitted, the first node determines the maximum value CW max,p and the minimum value CW min,p of the contention window corresponding to the channel access priority p and the selectable values of the contention window based on the parameter correspondence shown in Table 1. The value of CW p first selected by the terminal device is the minimum value among the selectable values of CW p , that is, CW min,p . CW pThe selected value is used as the upper limit of the selectable range for the initial count value of the counter in step 2. For example, when the channel access priority p is 2, CW p The initial value is 7.

[0114] 2. The first node detects one detection period T d When it is determined that the channel is in a clear state, the first node performs step 3.

[0115] Detection period T d = 16μs+m p ×9μs, detection period T d It may also be called defer duration, m p This may be determined based on Table 1 and channel access priority. The first node performs energy detection on frequency domain resources of the specified bandwidth. One period T d m in p When the energy detected at a series of detection intervals is less than the energy threshold, the detection period T d The channel is considered to be in a clear state.

[0116] 3. The first node is [0, CW p A random integer N within the range of ] int Generate and set the counter count value N to N int Set to this.

[0117] The first node sets the initial value of the counter's count N from 0 to CW. p Up to value N int We randomly select N=N int N int It satisfies a uniform distribution and ranges from 0 to CW. p A random value within the range of 0 ≤ N int ≤CW p N int and detection period T dThis determines the length of the contention window actually used in the clear channel assessment, or in other words, the contention window is at least N based on the steps described below. int Individual detection period T d Includes.

[0118] 4. The first node has a channel that detects each detection period T. d m in p The system determines whether or not it is in a clear state at each detection interval. One detection period T d When the channel is in a clear state, the counter's count value N decreases by 1; otherwise, N remains unchanged. Then, in the next period T d Energy continues to be detected in one period T. d Each time a channel is detected to be in a clear state, the counter's count value decreases by 1.

[0119] The energy detection threshold may be pre-configured or obtained by the first node through calculation based on the maximum transmit power and channel bandwidth. The first node preferentially uses the pre-configured energy threshold. If no pre-configured energy threshold exists, the energy threshold obtained through calculation is used.

[0120] 5. When the counter's count value N decreases to 0, the first node transmits a signal.

[0121] After determining the channel access priority, the first node performs a clear channel assessment based on the parameters corresponding to the channel access priority in Table 1, determines that the channel is in a clear state, and thereby transmits the signal. As shown in Table 1, the channel access priority corresponds to the maximum channel occupancy time (maximum COT, MCOT), which is T mcot,pThis is shown as follows: MCOT is the maximum time a channel is allowed to be occupied after it has been accessed using a clear channel assessment scheme corresponding to channel access priority. The channel occupancy time for the first node is T mcot,p It cannot be larger than that.

[0122] 6. The first node determines whether the proportion of negative acknowledgments (NACKs) in hybrid automatic repeat request (HARQ) feedback during the reference period is greater than the first threshold. If the proportion of NACKs during the reference period is greater than or equal to the first threshold, CW p The value of increases. If the percentage of NACKs in the reference period is less than the first threshold, CW p is CW min,p It will be set to this.

[0123] The reference period is the period from the start of a specified channel occupancy time to the end of the first time unit in which transmission of at least one data channel is completed, and the specified channel occupancy time is the channel occupancy time from when the first node starts occupying the channel until the last data channel is transmitted. For example, the data channel may be a physical uplink shared channel (PUSCH) or a physical downlink shared channel (PDSCH). The time unit may be a slot, subframe, or frame. The first threshold is a threshold for determining the signal transmission quality. However, this disclosure is not limited to this.

[0124] After transmitting the data channel, the first node receives NACK feedback from the data channel receiving node. The first node sets the upper limit of the contention window CW based on the percentage of NACKs in the reference time period. pThis may be adjusted. When the percentage of NACKs in the HARQ feedback during the reference period is less than 10% (in other words, the first threshold is 10%), the first node is CW p Set it to the minimum value among the selectable values, otherwise the first node will be CW p The value of CW p Increase to the next selectable value. For example, if a clear channel assessment scheme with channel access priority p=3 is used, and the current value of CWp is 15, and the percentage of NACKs in HARQ feedback during the baseline period is 10% or more, then CW p The value is CW p Increase to the next selectable value, CW p It is set to 31. CW p CW corresponding to the current channel access priority p When set to the maximum selectable value (specifically, the maximum value among the selectable values), CW is issued because the proportion of NACKs in the HARQ feedback during the reference period is 10% or more. p If the value of CW needs to increase, p It remains the maximum selectable value and does not change. CW p When the number of detections in which the value remains at the maximum selectable value reaches a predetermined number (the predetermined number may be pre-configured), CW p It is adjusted to the smallest selectable value (specifically, the smallest value among the selectable values).

[0125] The first node may be a terminal device, and the clear channel assessment method in Method 1 is applicable to the transmission of PUSCH, physical uplink control channel (PUCCH), or sounding reference signal (SRS), and the initiation of a random access process by the terminal device. Alternatively, the first node may be an access network node, and the clear channel assessment method in Method 1 is applicable to the transmission of any of the following signals by the access network node: PDSCH, physical downlink control channel (PDCCH), and reference signal.

[0126] Method 2

[0127] In the clear channel assessment method of Method 2, the detection period is T short = 25 μs, T short is one time interval T f = 16 μs, and time interval T f This includes a single detection interval of 9 μs after that. In method 2, T f The detection interval is 9 μs, starting from the beginning of 16 μs, and the detection period T short This is shown in Figure 6. Detection period T short If the energy detected by the communication device during two 9μs detection intervals is below the energy threshold, the channel is considered to be in a clear state. If it is determined through detection that the channel is in a clear state, the first node must transmit a signal immediately after detection is complete.

[0128] The first node may access the channel using the clear channel assessment method in Method 2 after the signal has been received or after the signal transmission has ended.

[0129] Method 3

[0130] In the clear channel assessment method of method 3, the detection period is T f = 16 μs. In method 3, the detection period T f The detection interval is 9 μs before the end point, and the detection period T f This is shown in Figure 7. Detection period T f If the channel is clear for at least 5 μs, then the channel is considered clear and accessible, and the 5 μs time includes at least 4 μs in the detection interval. In other words, if the channel is clear for at least 4 μs in the detection interval, then the detection period T f If the channel is clear for at least 5 μs, it is considered that the channel is clear and accessible. If it is determined through detection that the channel is clear, the first node must transmit a signal immediately after detection is complete.

[0131] Method 4

[0132] In method 4, the first node can transmit the signal without performing energy detection, but the transmission period cannot exceed 584 μs.

[0133] The above illustrates, with the use of examples, several clear channel assessment schemes in the unlicensed spectrum. It should be understood that the clear channel assessment scheme used by the first node in this disclosure may be one of the clear channel assessment schemes described above, or any other clear channel assessment scheme. If the first information indicates multiple clear channel assessments, it should be noted that the detection schemes used by the first node for the multiple clear channel assessments may be the same or different. The specific scheme may be a clear channel assessment scheme selected by the first node based on the service priority of the signal to be transmitted. This is not limited to this disclosure.

[0134] The first node may, by using the first information, notify the second node of process parameter information for at least one clear channel assessment performed by the first node, and as a result, the second node can, through inference based on the first information, obtain a clear channel assessment policy suitable for the first node and notify the first node of the clear channel assessment policy. In this way, when the rules for using the unlicensed spectrum are met, the probability of the first node accessing the channel increases and the reliability of the communication is improved.

[0135] Optionally, the type of parameter information required by the second node to infer a clear channel assessment policy may be predefined in the protocol, or the second node may send third information to the first node, which indicates the type of parameter information required by the second node to infer a clear channel assessment policy. Based on the third information, the second node determines the type of parameter information required by the second node to infer a clear channel assessment policy, and using the first information, provides the corresponding type of parameter information for the second node. As a result, the second node infers a clear channel assessment policy suitable for the first node based on the first information and notifies the first node of the clear channel assessment policy. In this way, when the rules for using the unlicensed spectrum are met, the probability of the first node accessing the channel increases, and the reliability of the communication is improved.

[0136] Optionally, the process parameter information includes the following information, namely: This includes, but is not limited to, one or more of the following: service priority information for the signal to trigger a clear channel assessment, the clear channel assessment method, channel access priority information, contention window information, detection period information, energy detection threshold, or detection result information.

[0137] Contention window information is the upper limit CW of the selected contention window. p , the initial count value N of the selected counter int The detection period information may include one or more parameters, such as the number of detection periods in a single clear channel assessment. The detection period information may include, but is not limited to, the length of the detection period and / or the number of detection intervals within the detection period. The detection result information includes the following, namely, This includes one or more of the following: the channel state determined after a clear channel assessment; the number or percentage of detection periods in which the channel was detected as clear; the number or percentage of detection periods in which the channel was detected as busy; or the energy values ​​detected during the detection interval.

[0138] For example, at least one clear channel assessment includes a clear channel assessment method in Method 1. For example, when a signal to be transmitted exists, the first node performs a clear channel assessment using the clear channel assessment method in Method 1. The process parameter information for the clear channel assessment indicated by the first information may include service priority information for the signal to trigger the clear channel assessment, the clear channel assessment method, i.e., Method 1, and detection result information. Optionally, the process parameter information may include the channel access priority p specifically selected in Method 1, the upper limit of the contention window CW. p , and the initial count value N of the counter int It may further include the following: For example, the first piece of information may be that the channel access priority p is 3 and the upper limit of the contention window is CW. p The value is 31, and the counter count value is N int This specifically shows that it is 23.

[0139] Optionally, in this example, the process parameter information may further include the number of detection periods detected in this clear channel assessment. Based on the above description of the clear channel assessment in Method 1, the initial count value N of the counter.int The detection period T is the time during which the channel is detected as being in a clear state. d This is to limit the number of detections. When the first node detects that a channel is busy during one detection period, the counter value remains unchanged. Therefore, in order to enable the second node to obtain more accurate relevant information from this clear channel assessment, the first node may further inform the second node of the specific number of detection periods to be detected in this detection.

[0140] Optionally, in this example, the process parameters may further include the energy threshold used in this clear channel assessment, so that the second node knows the criteria for the first node to determine the channel state in this detection. The first information may further indicate detection result information. For example, the detection result information is for each detection period T d The corresponding detection results may include, specifically, whether the channel is clear or busy.

[0141] In other examples, at least one clear channel assessment includes a clear channel assessment method in Method 3, and the process parameter information of the clear channel assessment indicated by the first information may indicate the detection method, i.e., Method 3, energy threshold, and detection result information. For example, the detection result information may indicate that the channel state was determined to be clear or busy through this clear channel assessment. The detection result information is for the detection period T f The duration or percentage of channels that were detected as clear, or the duration or percentage of channels that were busy, may be further indicated. For example, in this clear channel assessment, the first node indicates that the channels were detected during the T f In this case, it is detected that the channel is in a clear state for 8 μs, and the first information may indicate that the period during which the channel is in a clear state is 8 μs, or the channel is detected during the detection period T fIt may also indicate that it is in a clear state during 50% of the time. However, this disclosure is not limited to this.

[0142] In other examples, the process parameter information for a single clear channel assessment indicated by the first information may include the length of the detection period in the current clear channel assessment, the number of detection intervals included in the detection period, the energy threshold, and the detection result information. In other words, the process parameters for a clear channel assessment do not have to indicate the clear channel assessment method, and may indicate detection period information (e.g., the length of the detection period and the number of detection intervals included), the energy threshold, and the detection result information for the clear channel assessment.

[0143] It should be noted that the above uses examples to merely illustrate the types of process parameter information for clear channel assessment as indicated by the first information. The types of process parameter information for clear channel assessment as indicated by the first information may be predefined in the protocol or may be indicated by the second node, but are not limited to this disclosure. The parameter information required by the second node to infer a clear channel assessment policy may further include the transmission quality information described below.

[0144] Optionally, the first information further includes transmission quality information, which indicates the quality of the signal transmitted by the first node over the unlicensed spectral resource.

[0145] In this disclosure, the signals transmitted by the first node on a channel accessed through a clear channel assessment may be one or more of data, reference signals, or control information. The data may be transport blocks (TB), code blocks (CB), or code block groups (CBG) carried on a PDSCH resource or PUSCH resource. The reference signals may include, but are not limited to, demodulation reference signals (DMRS), channel state information-reference signals (CSI-RS), or sounding reference signals (SRS). The control information may include, but is not limited to, system messages (SI), uplink control information (UCI), or downlink control information. The first node may be an access network node or a terminal device. Specifically, when the first node is an access network node, the transmitted signals may also be downlink signals. When the first node is a terminal device, the transmitted signal may be an uplink signal, a signal transmitted by the terminal device, or a sidelink signal between terminal devices. This is not limited to the above.

[0146] For example, the first node may periodically transmit the first information, and the first information may include signal quality information of the signal transmitted by the first node by using an unlicensed spectral resource in one period.

[0147] In another example, with respect to a clear channel assessment having a detection result that the channel is in a clear state, the first node transmits a signal after the clear channel assessment, and the first information may further include transmission quality information of the signal transmission corresponding to the detection indicated by the first information in at least one clear channel assessment having a detection result that the channel is clear.

[0148] As an example, not limited to the above, transmission quality information includes the following information, namely: The system may indicate one or more of the following: channel occupancy time (COT) for signal transmission, signal quality information, percentage of successful signal transmissions during a reference period, percentage of unsuccessful signal transmissions during a reference period, a first threshold, or a reference period for evaluating signal transmission quality.

[0149] The transmission quality information may include channel occupancy time for signal transmission. For example, a first node periodically transmits the first information to a second node. The first node may use the first information to inform the second node of the channel occupancy time that the first node occupies to transmit a signal after accessing the channel through each clear channel assessment in one cycle. For example, the transmission quality information may include the number of times K that the first node transmits a signal by using an unlicensed spectral resource in one cycle, and the transmission quality information indicates that K segments of a COT are COTs in which the signal is transmitted K times. In another example, the first information includes transmission quality information for signal transmission corresponding to a detection in at least one clear channel assessment that has a detection result of the channel being clear. Each transmission quality information includes the corresponding COT in which the signal is transmitted after the clear channel assessment. However, this disclosure is not limited thereto.

[0150] Transmission quality information may include signal quality information, which indicates the quality of the signal transmitted over the unlicensed spectral resource, and as a result, a second node can infer a clear channel assessment policy based on the quality of the signal transmitted after the first node accesses the channel.

[0151] In one example, when the first node detects that the channel is clear, it transmits the data channel by using an unlicensed spectral resource. The data channel includes a DMRS for demodulation. The node receiving the data channel may measure the signal quality of the DMRS and feed the signal quality back to the first node. The signal quality of the DMRS may represent the transmission quality of the data channel. The first node may notify the second node of the transmission quality by using the signal quality information. For example, the node receiving the data channel may be specified to measure the signal quality of the DMRS on the first data channel within one segment of the COT and feed the signal quality back to the first node to reduce feedback overhead. However, this disclosure is not limited to this.

[0152] In another example, the first node may be an access network node. When it is detected that the channel is clear, the access network node transmits CSI-RS to a terminal device using an unlicensed spectral resource. The terminal device measures the signal quality of the CSI-RS and feeds the signal quality back to the access network node. The first information transmitted by the access network node to the second node includes signal quality information, and the second node is notified of the signal quality of the CSI-RS transmitted by the access network node using the unlicensed spectral resource by using the signal quality information.

[0153] In other examples, the first node may be a terminal device. The terminal device transmits SRS to an access network node by using an unlicensed spectral resource. The access network node measures the signal quality of the SRS and feeds the signal quality back to the terminal device. The first information transmitted by the terminal device to the second node includes signal quality information indicating the signal quality. In this example, the second node may be an access network node or any other node in the network, and the first information may be transmitted transparently to the second node via the access network node.

[0154] As an example, and not an exhaustive list, signal quality may include one or more of the following: reference signal received power (RSRP), reference signal received quality (RSRQ), or signal-to-interference plus noise ratio (SINR).

[0155] Transmission quality information may include the percentage of successful signal transmissions or the percentage of unsuccessful signal transmissions. In the clear channel assessment method 1 described above, it is stated that the first node may adjust the upper limit of the contention window by comparing the percentage of NACK feedback in a reference period with a first threshold. For example, when a channel is detected to be in a clear state, the first node may transmit a data channel by using an unlicensed spectral resource. For example, a data channel may contain multiple CBGs. A node that receives a data channel may send HARQ feedback to the first node, which may determine, based on the HARQ feedback, whether each CBG on the data channel was successfully received. When one CBG on the data channel is successfully received, the node provides feedback of one ACK corresponding to the CBG. When one CBG on the data channel is not successfully received, the node provides feedback of a negative acknowledgement (NACK) corresponding to the CBG, or does not provide feedback of an ACK, indicating that the CBG was not successfully received. Transmission quality information may include the percentage of successful signal transmissions, in other words, the percentage of ACK feedback in a reference period calculated by the first node. Alternatively, transmission quality information may include the rate of signal transmission failures, for example, the rate of NACKs that are fed back during a reference period, or the rate of ACKs that are not fed back during a reference period.

[0156] The reference period may be predefined in the protocol, notified by a second node, or determined by a first node. For example, the reference period may be the period defined in detection method 1 above, or the period defined by a specific implementation method. For example, the reference time may be the period of resources occupied by the last data channel within one segment of the COT. If the reference time period is determined by a first node, the first node may notify the second node of information regarding the reference time period by using transmission quality information.

[0157] The transmission quality information may include a first threshold for determining the signal transmission quality, and as a result, the second node may know the criteria for the first node to determine the transmission quality based on the first threshold. The second node may infer the first node's clear channel assessment policy based on the first threshold.

[0158] In an optional implementation, the first node does not have to transmit transmission quality information to the second node, and the first node may transmit a reference signal by using an unlicensed frequency band resource after accessing the channel, and the second node determines the quality of the signal transmitted by the terminal device over the unlicensed spectral resource based on the reference signal received from the first node. For example, the first node may be a terminal device, and the second node may be an access network node. The access network node may determine the quality of the signal transmitted by the terminal device based on the reference signal transmitted by the terminal device over the unlicensed spectral resource. However, this disclosure is not limited thereto. In a specific implementation, the second node may infer a clear channel assessment policy by referring to the quality of the signal transmitted by the first node. Alternatively, the second node may infer a clear channel assessment policy based only on the process parameter information of the clear channel assessment, without referring to the quality of the signal transmitted by the first node.

[0159] S402: The second node transmits second information to the first node, which indicates the first node's clear channel assessment policy, and the clear channel assessment policy includes clear channel assessment detection parameter information.

[0160] In response, the first node receives second information from the second node and determines a clear channel assessment policy based on the second information.

[0161] As described above, the type of parameter information required by the second node to infer a clear channel assessment policy may be predefined in the protocol, or the second node may transmit third information to the first node, where the third information indicates the type of parameter information required by the second node to infer a clear channel assessment policy. In this case, the first and second nodes can reach an agreement on the type of parameter information required by the second node to infer a clear channel assessment policy, and as a result, the first information transmitted by the first node to the second node includes the corresponding type of parameter information required by the second node. For example, the parameter information required by the second node to infer a clear channel assessment policy may include clear channel assessment process parameter information, or it may include clear channel assessment process parameter information and transmission quality information.

[0162] After receiving the first piece of information, the second node obtains the clear channel assessment policy of the first node through inference based on the first piece of information. For example, the second node consists of an intelligent model for inferring the clear channel assessment policy, and the second node infers the clear channel assessment policy by using the intelligent model. For example, the received first piece of information is input to the intelligent model, and the output obtained by the intelligent model is the clear channel assessment policy obtained by the intelligent model through inference based on the first piece of information.

[0163] In this implementation, the intelligent model may be pre-configured at the second node.

[0164] In other implementations, the intelligent model may be an intelligent model for inference, obtained by performing model training on a second node based on training data.

[0165] For example, Figure 8 is an exemplary diagram of the intelligent model training process. The second node may acquire one training data. For example, the training data may be acquired by the second node from the first node. For example, the first node transmits first information to the second node, and in the intelligent model training process, the second node uses the received first information as training data to train the intelligent model. However, this disclosure is not limited to this. The training data may be downloaded from a network by the second node. For example, the second node is an access network node, and the access network node may download training data from a node such as OAM. As shown in Figure 8, the training data may include training samples, which are used as input, processed by the intelligent model, and then output as inference results, i.e., a clear channel assessment policy. The second node obtains the output of the loss function through computation based on the inference results by using the loss function, and then obtains the intelligent model obtained by optimizing and updating the parameters of the intelligent model by optimizing the model parameters of the intelligent model based on the loss function. In the next training session, the second node processes the training data by using the intelligent model obtained by acquiring other training data and updating its parameters, and outputs the inference result. Multiple training runs are performed on the intelligent model using a large amount of training data. When the output of the loss function satisfies the pre-set conditions, the training of the intelligent model is complete, and a trained intelligent model is obtained, which can be used to infer a clear channel assessment policy.

[0166] In this implementation example, the second node may train the intelligent model using a supervised learning method. For example, the training data may further include labels, which are the correct inference results corresponding to the first information, i.e., the correct clear channel assessment policy corresponding to the first information. In the supervised learning training method, the loss function is used to calculate the error between the inference results and the labels, and the second node may optimize the algorithm using the model parameters to optimize the parameters of the intelligent model based on the error obtained using the loss function. By using a large amount of training data, the intelligent model is trained multiple times, and as a result, training of the intelligent model is completed when the difference between the output of the intelligent model and the labels becomes less than or equal to a first preset value.

[0167] In another example of this implementation, the second node may train the intelligent model using an unsupervised learning method, where the training data does not contain labels. For unsupervised learning, the loss function may be a function used to evaluate the model's performance. The second node learns the internal patterns of the samples by using an algorithm and completes training the intelligent model based on the samples. Multiple training runs are performed on the intelligent model using a large amount of training data, and the training of the intelligent model is completed after the output of the intelligent model exceeds a second preset value.

[0168] It should be understood that the training methods for models used in a particular implementation are not limited in this disclosure.

[0169] In other implementations, the intelligent model of the second node may be obtained by the third node.

[0170] The third node may acquire the intelligent model trained through model training and send the trained intelligent model to the second node. After acquiring the trained intelligent model, the second node infers a clear channel assessment policy by using the intelligent model. The process of training the intelligent model by the third node may be as shown in Figure 8. The third node may acquire training data from the first node. For example, the first node sends the first information to the third node as training data for model training. The third node trains the intelligent model based on the training data. It should be noted that the training data may be sent directly from the first node to the third node, or it may be forwarded to the third node via other nodes. For example, the training data may be forwarded to the third node via the second node or other nodes in the network. The third node may train the intelligent model using supervised learning, or it may train the intelligent model using unsupervised learning. For specific implementations, refer to the above method for training the intelligent model by the second node. For the sake of brevity, I will not go into detail again here.

[0171] For example, the second node may be an access network node, and the access network node may obtain an intelligent model from the third node. For example, the third node may be a core network node or an OAM. However, this disclosure is not limited to these. For example, the second node may, alternatively, be an AI concrete within a core network device, and the third node may be an OAM. After receiving the first information from the first node in S401, the second node obtains the clear channel assessment policy of the first node through inference using the intelligent model. Optionally, the clear channel assessment policy includes the following detection parameter information, i.e., This includes one or more of the following: service priority information for the signal used to trigger a clear channel assessment, the clear channel assessment method, channel access priority information, contention window information, detection period information, or energy detection threshold. See the above description for details of the above information. For brevity, further details will not be explained here.

[0172] Optionally, the clear channel assessment policy includes clear channel assessment detection parameter information corresponding to each of the service priorities of at least one signal, and as a result, the first node can perform a clear channel assessment by using the clear channel assessment detection parameter information corresponding to the service priorities in the clear channel assessment policy, based on the service priorities of the signals to be transmitted.

[0173] Optionally, the clear channel assessment policy further includes one or more of the following: information about a reference period for evaluating signal transmission quality, a first threshold, a maximum channel occupancy time corresponding to the clear channel assessment, or transmission quality prediction information. For example, the clear channel assessment policy further includes information about a reference period corresponding to signal transmission quality obtained through inference by an intelligent model, where the reference period information indicates a reference period for evaluating signal transmission quality. The clear channel assessment policy may further include a first threshold for evaluating signal transmission quality, so that the first node can adjust the length of the contention window based on the signal transmission quality in the reference period. Alternatively, the clear channel assessment policy may not include information about a reference period and may include only the first threshold. The reference period may be predefined or determined by the first node. The first node may determine the signal transmission quality in the reference period based on the first threshold.

[0174] In another example, the clear channel assessment policy may include a maximum channel occupancy time. After the first node receives the clear channel assessment policy and performs a clear channel assessment to access the channel, the maximum period the channel can be occupied will not exceed the maximum channel occupancy time indicated by the clear channel assessment policy, and as a result, the reliability of signal transmission can be improved.

[0175] In other examples, the clear channel assessment policy may further include transmission quality prediction information. This transmission quality prediction information is the quality of the signal transmitted after a clear channel assessment is performed by a first node using the clear channel assessment policy to access the channel, and which is then acquired by a second node through inference. For example, the clear channel assessment policy may include multiple clear channel assessment methods, and the transmission quality prediction information further indicates the quality of the signal transmitted after the channel is accessed by each detection method, and which is then predicted by the second node. The first node may select a clear channel assessment method that satisfies the reliability requirements for signal transmission based on the transmission quality prediction information and the reliability requirements of the signal to be transmitted.

[0176] The communication method shown in Figure 4 may be applicable to multiple application scenarios. Several application scenarios are described below with examples. It should be understood that this disclosure is not limited to these.

[0177] Example 1: The first node may be a terminal device or a device located on the terminal device, and the second node may be an access network node, for example, an access network device or a device located on the access network device. The terminal device provides the access network node with parameter information for inferring a clear channel assessment policy by using the first information. The access network node obtains a clear channel assessment policy suitable for the terminal device through inference based on the first information, and then transmits the clear channel assessment policy to the terminal device. For example, the access network node may be an AI concrete within an access network device, for example, an RIC module within an access network device. However, this disclosure is not limited thereto.

[0178] Example 2: The first node may be an access network node, and the second node may be an AI concrete (i.e., an AIC).

[0179] For example, as shown in Figure 9, the access network node executes S901 to send first information to the AIC and provides the AIC with parameter information for inferring a clear channel assessment policy using the first information. The AIC executes S902 to obtain a clear channel assessment policy suitable for the access network node based on the first information, and then executes S903 to send the clear channel assessment policy to the access network node. When the access network node needs to send a signal to a terminal device by using an unlicensed spectral resource, the access network node may detect the clear state of the downlink channel based on the clear channel assessment policy and send a signal when the downlink channel is clear. The access network node may be an access network device, or a module or unit of an access network device. In one method, the AI ​​concrete may be a network node other than an access network device in the network, e.g., an OAM. In another method, the AI ​​concrete and the access network node may be two nodes located in the same access network device. For example, the access network node may be a CU, DU, or RU of the access network device, and the AI ​​concrete may be a quasi-real-time RIC within the access network device. It should be understood that the above uses examples to merely illustrate specific implementation scenarios for access network nodes and AI concrete. However, this disclosure is not limited to these examples.

[0180] An access network node may transmit the first information directly to a third-party node, or it may transfer the first information to a third-party node through a transfer by another network node. This is not limited to the above.

[0181] Example 3: The first node may be a terminal device or a device located on a terminal device, or it may be a third-party node other than a terminal device and an access network node. For example, the third-party node may have AI functionality or be a network element in the network where AI concrete is located. The terminal device may transfer the first information to the third-party node through transfer using an access network node.

[0182] For example, as shown in Figure 10, the first node is a terminal device. The terminal device executes S1001 to send the first information to the access network node. After receiving the first information, the access network node executes S1002 to send the first information to a third-party node. The third-party node executes S1003 to obtain a clear channel assessment policy suitable for the terminal device through inference based on the first information, and then notifies the terminal device of the clear channel assessment policy by using the second information. Specifically, the third-party node executes S1004 to send the second information to the access network node. After receiving the second information, the access network node executes S1005 to forward the second information to the terminal device, and as a result, the terminal device determines a clear channel assessment policy based on the second information after receiving it, and executes S1006 to perform a clear channel assessment based on the clear channel assessment policy when it is necessary for the signal to be transmitted by using unlicensed spectral resources. For example, when a signal is to be sent to an access network node, the terminal device detects the clear state of the uplink channel based on the clear channel assessment policy, and if the uplink channel is clear, it sends the signal to the access network node using an unlicensed spectral resource. In another example, when a signal is to be sent to another terminal device, the terminal device detects the clear state of the sidelink channel based on the clear channel assessment policy, and if the sidelink channel is clear, it sends the signal to the target terminal device using an unlicensed spectral resource. In this example, it should be noted that communication information may be exchanged directly between the access network node and the third-party node, and at least one additional communication node may be included between the access network node and the third-party node.Communication information transmitted by an access network node to a third-party node may be forwarded to the third-party node by at least one communication node, and communication information transmitted by a third-party node to an access network node may be forwarded to the access network node by at least one communication node.

[0183] Based on the above solution, the second node may obtain the process parameter information for the clear channel assessment of the first node by using the first information and provide the first node with the clear channel assessment policy obtained based on the first information. In this case, the first node can obtain a clear channel assessment policy suitable for the first node, increasing the probability that the first node will access the channel when the rules for using the unlicensed spectrum are met and the reliability of unlicensed spectrum-based communication is met, thereby reducing the power consumption caused by frequent channel discovery failures of the first node.

[0184] In this disclosure, a network element may perform some or all of the steps or actions associated with the network element. These steps or actions are merely examples. In this disclosure, other actions or various variations of actions may be performed further. Furthermore, the steps may be performed in an order different from the order presented in this disclosure, and not all actions in this disclosure may be performed.

[0185] In the various examples of this disclosure, unless otherwise stated or unless there is a logical contradiction, the terminology and / or descriptions in different examples are consistent and may be referenced to one another, and the technical features in different examples may be combined on the basis of their internal logical relationships to form new examples.

[0186] The methods provided in this disclosure are described in detail above with reference to Figures 4 to 10. The following accompanying drawings describe the communication equipment and communication devices provided in this disclosure. To realize the functions in the methods provided in this disclosure, each network element includes a hardware structure and / or a software module, and the above functions may be realized in the form of a hardware structure, a software module, or a combination of a hardware structure and a software module. Whether the functions among the above functions are performed using a hardware structure, a software module, or a combination of a hardware structure and a software module depends on the specific application and design constraints of the technical solution.

[0187] Figure 11 is a schematic block diagram of the communication device according to this disclosure. As shown in Figure 11, the communication device 1100 may include a transceiver unit 1120.

[0188] In possible designs, the communication device 1100 may correspond to the first node in the above method, a chip located at (or used at) the first node, or other devices, modules, circuits, units, etc. that can implement the method of the first node.

[0189] It should be understood that the communication device 1100 may include units configured to perform the methods performed by the first node in the manner shown in Figures 4, 9, and 10. Furthermore, the units within the communication device 1100 and the other operations and / or functions described above are separately intended to implement the corresponding steps in the manner shown in Figures 4, 9, and 10.

[0190] Optionally, the communication device 1100 may further include a processing unit 1110. The processing unit 1110 may be configured to process instructions or data to realize corresponding operations.

[0191] When the communication device 1100 is a chip located (or used) in the first node, it should be further understood that the transceiver unit 1120 within the communication device 1100 may be an input / output interface or circuit within the chip, and the processing unit 1110 within the communication device 1100 may be a processor within the chip.

[0192] Optionally, the communication device 1100 may further include a storage unit 1130. The storage unit 1130 may be configured to store instructions or data. The processing unit 1110 may execute the instructions or data stored in the storage unit, enabling the communication device to perform the corresponding operation.

[0193] It should be understood that the transceiver unit 1120 in the communication device 1100 may be implemented through a communication interface (e.g., a transceiver or an input / output interface), and may correspond, for example, to the transceiver 1210 in the first node 1200 shown in Figure 12. The processing unit 1110 in the communication device 1100 may be implemented through at least one processor, and may correspond, for example, to the processor 1220 in the first node 1200 shown in Figure 12. Alternatively, the processing unit 1110 in the communication device 1100 may be implemented through at least one logic circuit. The storage unit 1130 in the communication device 1100 may correspond to the memory in the first node 1200 shown in Figure 12.

[0194] It should be further understood that the specific process by which the unit performs the corresponding steps described above is explained in detail in the method described above. For the sake of brevity, the details will not be explained again here.

[0195] In other possible designs, the communication device 1100 may correspond to a second node in the method described above, for example, a chip located at (or used at) the second node, or other device, module, circuit or unit capable of implementing the method of the second node.

[0196] It should be understood that the communication device 1100 may include a unit configured to perform the method performed by the second node in the manner shown in Figures 4, 9, and 10. Furthermore, the units within the communication device 1100 and the other operations and / or functions described above are separately intended to implement the corresponding steps in the manner shown in Figures 4, 9, and 10.

[0197] Optionally, the communication device 1100 may further include a processing unit 1110. The processing unit 1110 may be configured to process instructions or data to realize corresponding operations.

[0198] When the communication device 1100 is a chip located (or used) in the second node, it should be further understood that the transceiver unit 1120 within the communication device 1100 may be an input / output interface or circuit within the chip, and the processing unit 1110 within the communication device 1100 may be a processor within the chip.

[0199] Optionally, the communication device 1100 may further include a storage unit 1130. The storage unit 1130 may be configured to store instructions or data. The processing unit 1110 may execute the instructions or data stored in the storage unit, enabling the communication device to perform the corresponding operation.

[0200] When the communication device 1100 is the second node, it should be understood that the transceiver unit 1120 within the communication device 1100 may be implemented through a communication interface (e.g., a transceiver or an input / output interface), and may correspond to, for example, the transceiver 1310 within the network device 1300 shown in Figure 13. The processing unit 1310 within the communication device 1300 may be implemented through at least one processor, and may correspond to, for example, the processor 1320 within the network device 1300 shown in Figure 13. The processing unit 1110 within the communication device 1100 may be implemented through at least one logic circuit. The storage unit 1130 within the communication device 1100 may correspond to the memory within the network device 1300 shown in Figure 13.

[0201] It should be further understood that the specific process by which the unit performs the corresponding steps described above is explained in detail in the method described above. For the sake of brevity, the details will not be explained again here.

[0202] Figure 12 is a diagram illustrating the structure of a terminal device 1200 according to this disclosure. The terminal device 1200 may be used in the system shown in Figure 1 to perform the functions of a terminal device in the manner described above. As shown in the drawing, the terminal device 1200 includes a processor 1220 and a transceiver 1210. Optionally, the terminal device 1200 further includes memory. The processor 1220, transceiver 1210 and memory may communicate with each other through an internal connection path to transmit control signals and / or data signals. The memory is configured to store computer programs, and the processor 1220 is configured to execute the computer programs in memory and control the transceiver 1210 to receive and transmit signals.

[0203] The processor 1220 may be configured to perform operations that are implemented within the terminal device as described in the above method. The transceiver 1210 may be configured in the above method to perform a transmit action by the terminal device or a receive action from the network device for the network device. See the description in the above method for further details. Further details will not be described again here.

[0204] Optionally, the terminal device 1200 may further include a power supply configured to supply power to various components or circuits within the terminal device.

[0205] Figure 13 is a diagram illustrating the structure of a network device 1300 according to this disclosure. The network device 1300 may be used in the system shown in Figure 1 to perform the function of a second node in the method described above. As shown in the drawing, the network device 1300 includes a processor 1320 and a transceiver 1310. Optionally, the network device 1300 further includes memory. The processor 1320, the transceiver 1310 and the memory may communicate with each other through an internal connection path to transfer control signals and / or data signals. The memory is configured to store computer programs, and the processor 1320 is configured to execute the computer programs in the memory and control the transceiver 1310 to receive and transmit signals.

[0206] The processor 1320 may be configured to perform operations implemented within the network device as described in the above method. The transceiver 1310 may be configured in the above method to perform transmit actions by the network device or receive actions from the network device on behalf of the network device. See the description in the above method for further details. Further details will not be described again here.

[0207] Optionally, the network device 1300 may further include a power supply configured to provide power to various components or circuits within the network device.

[0208] In the terminal device shown in Figure 12 and the network device shown in Figure 13, the processor and memory may be combined into a single processing unit, and the processor is configured to execute program code stored in memory to realize the above functions. In specific implementations, the memory may be integrated into the processor or may be independent of the processor. The processor may correspond to the processing unit in Figure 11. The transceiver may correspond to the transceiver unit in Figure 11. The transceiver 1210 may include a receiver (also called a receiver machine or receiver circuit) and a transmitter (also called a transmitter machine or transmitter circuit). The receiver is configured to receive signals, and the transmitter is configured to transmit signals.

[0209] In this disclosure, the processor may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, which may implement or execute the methods, steps and logic block diagrams in this disclosure. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods in this disclosure may be implemented directly by the hardware processor, or by a combination of hardware and software modules within the processor.

[0210] In this disclosure, memory may be non-volatile memory, such as a hard disk drive (HDD) or solid-state drive (SSD), or volatile memory, such as random-access memory (RAM). Memory may be any other medium that can carry or store program code, envisioned in the form of instructions or data structures, and that is accessible by a computer. Alternatively, memory in this application may be any other circuit or device that can implement a storage function and is configured to store program instructions and / or data.

[0211] This disclosure further provides a processing apparatus, which includes a processor and a (communication) interface. The processor is configured to perform a method in any one of the methods described above.

[0212] It should be understood that the processing unit may consist of one or more chips. For example, the processing unit may be a field programmable gate array (FPGA), application-specific integrated circuit (ASIC), system on chip (SoC), central processing unit (CPU), network processor (NP), digital signal processor (DSP), microcontroller unit (MCU), programmable logic device (PLD), or other integrated chip.

[0213] The methods provided in this disclosure further provide a computer program product, which includes computer program code. When the computer program code is executed by one or more processors, a device including the processors becomes capable of performing the methods shown in Figures 4, 9, and 10.

[0214] All or part of the technical solutions provided in this disclosure may be implemented using software, hardware, firmware, or a combination thereof. When software is used to implement an embodiment, all or part of the embodiment may be implemented in the form of a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded into a computer and executed, all or part of the procedures or functions of the present invention are generated. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. The computer-readable storage medium may be any available medium accessible by a computer, or a data storage device such as a server or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, or magnetic tapes), optical media (e.g., digital video discs (DVDs)), semiconductor media, etc.

[0215] The methods provided in this disclosure further provide a computer-readable storage medium for storing program code. When the program code is executed by one or more processors, a device including the processors becomes capable of performing the methods shown in Figures 4, 9, and 10.

[0216] According to the methods provided in this disclosure, this disclosure further provides a system comprising one or more of the above-described first devices. The system may further comprise one or more of the above-described third devices.

[0217] In some embodiments provided in this disclosure, it should be understood that the disclosed systems, apparatus, and methods may be implemented in other ways. For example, the described apparatus is an example. For example, the unit division is merely a logical functional division, and other divisions may be used in actual implementations. For example, multiple units or components may be combined or integrated into other systems, or some features may be ignored or not performed. Furthermore, the mutual coupling, direct coupling, or communication connection indicated or discussed may be implemented by using some interfaces. Indirect coupling or communication connection between apparatus or units may be implemented electronically, mechanically, or in other forms.

[0218] Units described as separate parts may or may not be physically separate, and parts shown as units may or may not be physical units, may be located in one place, or may be distributed across multiple network units. Some or all of the units may be selected based on the actual requirements to achieve the objectives of the solution of the embodiment.

[0219] The above description merely outlines a specific way of implementing this disclosure and is not intended to limit the scope of protection provided for this disclosure. Any modification or substitution that is readily conceivable by a person skilled in the art within the technical scope disclosed in this disclosure shall fall within the scope of protection provided for this disclosure. Accordingly, the scope of protection provided for this disclosure shall be subject to the scope of protection provided for in the claims.

Claims

1. A communication method executed by an access network node or a chip or module of said access network node, The steps include: transmitting first information to an AI module or AI unit for realizing artificial intelligence (AI) functionality, wherein the first information represents process parameter information of at least one clear channel assessment of the access network node; The steps include receiving second information from the AI ​​module or AI unit, wherein the second information indicates the clear channel assessment policy of the access network node, the clear channel assessment policy is obtained through inference based on the first information, based on the AI ​​model, and the clear channel assessment policy includes detection parameter information for the clear channel assessment. A method that includes this.

2. The method according to claim 1, further comprising the step of performing a clear channel assessment based on the clear channel assessment policy.

3. The aforementioned process parameter information includes the following parameters, namely, The method according to claim 1, comprising one or more of the following: service priority information for a signal to trigger the clear channel assessment, the clear channel assessment method, channel access priority information, contention window information, detection period information, energy detection threshold, or detection result information.

4. The method according to claim 1, wherein the clear channel assessment policy includes clear channel assessment detection parameter information corresponding to service priority information of at least one signal.

5. The aforementioned Clear Channel Assessment Policy is as follows: The method according to claim 4, comprising one or more of the following: service priority information for a signal to trigger the clear channel assessment, the clear channel assessment method, channel access priority information, contention window information, detection period information, or energy detection threshold.

6. The method according to claim 1, wherein the first information further includes transmission quality information, the transmission quality information indicating the quality of data transmitted over an unlicensed spectral resource.

7. The aforementioned transmission quality information includes the following, namely: The system displays one or more of the following: channel occupancy time for signal transmission, signal quality information, percentage of successful signal transmissions during a reference period, percentage of failed signal transmissions during a reference period, a first threshold, or information regarding a reference period for evaluating signal transmission quality. The method according to claim 6, wherein the first threshold is a threshold for evaluating the signal transmission quality.

8. The aforementioned Clear Channel Assessment Policy is as follows: The system further includes one or more of the following: information regarding a reference period for evaluating signal transmission quality, a first threshold, the maximum channel occupancy time corresponding to the clear channel assessment, or transmission quality prediction information. The method according to claim 1, wherein the first threshold is a threshold for evaluating the signal transmission quality.

9. The first step of sending information is: The method according to claim 1, comprising the step of periodically transmitting the first information, wherein the at least one clear channel assessment is a clear channel assessment performed by the access network node or the chip or module of the access network node in one period.

10. A communication method executed by an AI module or AI unit for realizing artificial intelligence (AI) functions, The steps include receiving first information from an access network node, wherein the first information represents process parameter information for at least one clear channel assessment of the access network node, and The steps include obtaining a clear channel assessment policy through inference based on the first information, based on an AI model, wherein the clear channel assessment policy includes detection parameter information for the clear channel assessment. The steps include: transmitting a second piece of information to the access network node, wherein the second piece of information indicates the access network node's clear channel assessment policy; A method that includes this.

11. The aforementioned process parameter information includes the following parameters, namely, The method according to claim 10, comprising one or more of the following: service priority information for a signal to trigger the clear channel assessment, the clear channel assessment method, channel access priority information, contention window information, detection period information, energy detection threshold, or detection result information.

12. The method according to claim 10, wherein the clear channel assessment policy includes clear channel assessment detection parameter information corresponding to service priority information of at least one signal.

13. The aforementioned Clear Channel Assessment Policy is as follows: The method according to claim 12, comprising one or more of the following: service priority information for a signal to trigger the clear channel assessment, the clear channel assessment method, channel access priority information, contention window information, detection period information, or energy detection threshold.

14. The method according to claim 10, wherein the first information further includes transmission quality information, the transmission quality information indicating the quality of data transmitted over an unlicensed spectral resource.

15. The aforementioned transmission quality information includes the following, namely: The system displays one or more of the following: channel occupancy time for signal transmission, signal quality information, percentage of successful signal transmissions during a reference period, percentage of failed signal transmissions during a reference period, a first threshold, or information regarding a reference period for evaluating signal transmission quality. The method according to claim 14, wherein the first threshold is a threshold for evaluating the signal transmission quality.

16. The aforementioned Clear Channel Assessment Policy is as follows: The system further includes one or more of the following: information regarding a reference period for evaluating signal transmission quality, a first threshold, the maximum channel occupancy time corresponding to the clear channel assessment, or transmission quality prediction information. The method according to claim 10, wherein the first threshold is a threshold for evaluating the signal transmission quality.

17. The step of receiving first information from an access network node is: The method according to claim 10, comprising the step of periodically receiving the first information, wherein the at least one clear channel assessment is a clear channel assessment performed by the access network node or a chip or module of the access network node in one period.

18. A communication device including a processor and memory, A communication device wherein the memory is coupled to the processor, and the processor is configured to perform the method according to any one of claims 10 to 17.

19. A communication device including a processor and memory, A communication device wherein the memory is coupled to the processor, and the processor is configured to perform the method according to any one of claims 1 to 9.

20. A computer-readable storage medium for storing instructions, wherein when the instructions are executed on a computer, the computer is able to perform the method according to any one of claims 1 to 17.

21. A program that includes instructions, A program in which, when the instruction is executed on a computer, the computer is able to perform the method according to any one of claims 1 to 17.

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