Communication methods and devices

Abstract

The present application relates to communication methods and devices. A communication method specifically comprises: on the basis of a first model, a first communication device determines first information related to uplink transmission. On the basis of the first model, the first communication device in the embodiments of the present application determines the information related to the uplink transmission, optimizing the uplink transmission and improving the performance of a communication system.

Description

Communication method and device TECHNICAL FIELD

[0001] The present application relates to the field of communication, and more particularly, to a communication method and device. BACKGROUND

[0002] The resources used by the terminal in the connected state to transmit uplink data can be dynamically scheduled by the network or pre-configured. The network can dynamically schedule transmission resources for the terminal based on the current traffic situation of the terminal, and the time delay of the data transmission process is large. In the pre-configuration resource scheme, the network needs to perform matching or de-matching operations on the pre-configuration resources, and the signaling overhead is large. The current work mode for optimizing the performance of the communication system is mostly completed based on theoretical modeling of the actual communication environment or simple parameter selection. The gain brought by this basic work mode is gradually weakening.

[0003] SUMMARY

[0004] The embodiments of the present application provide a communication method and device, which can improve the performance of the communication system.

[0005] The embodiments of the present application provide a communication method, comprising:

[0006] The first communication device determines first information related to uplink transmission based on a first model.

[0007] The embodiments of the present application provide a communication method, comprising:

[0008] The second communication device determines second information of the uplink transmission resource based on a second model.

[0009] The embodiments of the present application provide a first communication device, comprising:

[0010] The first processing unit is configured to determine first information related to uplink transmission based on a first model.

[0011] The embodiments of the present application provide a second communication device, comprising:

[0012] The second processing unit is configured to determine second information of the uplink transmission resource based on a second model.

[0013] The embodiments of the present application provide a communication device, comprising a transceiver, a processor and a memory. The memory is configured to store a computer program, the transceiver is configured to communicate with other devices, and the processor is configured to invoke and run the computer program stored in the memory, so that the communication device executes the above-mentioned communication method.

[0014] The embodiments of the present application provide a chip for implementing the above-mentioned communication method.

[0015] Specifically, the chip includes a processor configured to call and run a computer program from a memory, so that a device installed with the chip performs the communication method described above.

[0016] The embodiment of the present application provides a computer readable storage medium for storing a computer program, which, when executed by a device, causes the device to perform the communication method described above.

[0017] The embodiment of the present application provides a computer program product comprising computer program instructions, which cause a computer to perform the communication method described above.

[0018] The embodiment of the present application provides a computer program, which, when executed on a computer, causes the computer to perform the communication method described above.

[0019] The first communication device of the embodiment of the present application determines the information related to the uplink transmission based on the first model, which can optimize the uplink transmission and improve the performance of the communication system. BRIEF DESCRIPTION OF DRAWINGS

[0020] FIG. 1 is a schematic diagram of an application scenario according to an embodiment of the present application.

[0021] FIG. 2 is a schematic flowchart of a communication method according to an embodiment of the present application.

[0022] FIG. 3 is a schematic flowchart of a communication method according to another embodiment of the present application.

[0023] FIG. 4 is a schematic flowchart of a communication method according to an embodiment of the present application.

[0024] FIG. 5 is a schematic flowchart of a communication method according to another embodiment of the present application.

[0025] FIG. 6 is a schematic block diagram of a first communication device according to an embodiment of the present application.

[0026] FIG. 7 is a schematic block diagram of a first communication device according to another embodiment of the present application.

[0027] FIG. 8 is a schematic block diagram of a second communication device according to an embodiment of the present application.

[0028] FIG. 9 is a schematic block diagram of a second communication device according to an embodiment of the present application.

[0029] FIG. 10 is a schematic block diagram of a communication device according to an embodiment of the present application.

[0030] FIG. 11 is a schematic block diagram of a chip according to an embodiment of the present application.

[0031] FIG. 12 is a schematic block diagram of a communication system according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

[0033] The technical solutions in the embodiments of the present application can be applied to various communication systems, for example, a Long Term Evolution (LTE) system, an Advanced long term evolution (LTE-A) system, a New Radio (NR) system, an evolved system of the NR system, a LTE-based access to unlicensed spectrum (LTE-U) system, a NR-based access to unlicensed spectrum (NR-U) system, a Non-Terrestrial Networks (NTN) system, a Universal Mobile Telecommunication System (UMTS), a Wireless Local Area Networks (WLAN), a Wireless Fidelity (WiFi), a 5th-Generation (5G) system, or other communication systems, etc.

[0034] Generally, a conventional communication system supports a limited number of connections, and is easy to implement. However, with the development of communication technology, a mobile communication system will not only support conventional communication, but also support, for example, Device to Device (D2D) communication, Machine to Machine (M2M) communication, Machine Type Communication (MTC), Vehicle to Vehicle (V2V) communication, or Vehicle to everything (V2X) communication, etc. The embodiments of the present application can also be applied to these communication systems.

[0035] In an implementation manner, the communication system in the embodiments of the present application can be applied to a Carrier Aggregation (CA) scenario, can also be applied to a Dual Connectivity (DC) scenario, and can also be applied to a Standalone (SA) network deployment scenario.

[0036] In an implementation, the communication system in embodiments of the present application can be applied to unlicensed spectrum, which can also be considered as shared spectrum, or applied to licensed spectrum, which can also be considered as unshared spectrum.

[0037] Embodiments of the present application describe various embodiments in combination with network devices and terminal devices, wherein the terminal device can also be referred to as user equipment (UE), access terminal, subscriber unit, subscriber station, mobile station, mobile, remote station, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, or user device, etc.

[0038] The terminal device can be a station (STA) in a WLAN, a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA) device, a handheld device having wireless communication function, a computing device, or other processing device connected to a wireless modem, an in-vehicle device, a wearable device, a terminal device in a next-generation communication system such as an NR network, or a terminal device in a future evolved Public Land Mobile Network (PLMN) network, etc.

[0039] In embodiments of the present application, the terminal device can be deployed on land, including indoor or outdoor, handheld, wearable, or in-vehicle; can also be deployed on water surface (such as ships, etc.); and can also be deployed in the air (such as airplanes, balloons, and satellites, etc.).

[0040] In embodiments of the present application, the terminal device can be a mobile phone, a tablet computer, a computer with wireless transceiver function, a Virtual Reality (VR) terminal device, an Augmented Reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self driving, a wireless terminal device in remote medical treatment, a wireless terminal device in smart grid, a wireless terminal device in transportation safety, a wireless terminal device in smart city, or a wireless terminal device in smart home, etc.

[0041] By way of example and not limitation, in embodiments of the present application, the terminal device can also be a wearable device. The wearable device can also be referred to as a wearable smart device, which is a general term for devices that are designed and developed by applying wearable technology to daily wear, such as glasses, gloves, watches, clothing, and shoes. The wearable device is a portable device that is directly worn on the body or integrated into the clothes or accessories of the user. The wearable device is not only a hardware device, but also a device that realizes powerful functions through software support and data interaction and cloud interaction. The broad sense of wearable smart devices includes devices with full functions and large sizes that can realize complete or partial functions without relying on smart phones, such as smart watches or smart glasses, and devices that focus on a certain type of application function and need to be used in cooperation with other devices, such as smart phones, such as various smart wristbands and smart jewelry for monitoring vital signs.

[0042] In embodiments of the present application, the network device can be a device for communicating with the mobile device, and the network device can be an access point (Access Point, AP) in a WLAN, an evolved node B (Evolutional Node B, eNB or eNodeB) in LTE, or a relay station or an access point, or a vehicle-mounted device, a wearable device, and a network device in an NR network (gNB) or a future evolved PLMN network or a network device in an NTN network, etc.

[0043] By way of example and not limitation, in embodiments of the present application, the network device can have mobile characteristics, for example, the network device can be a mobile device. Alternatively, the network device can be a satellite, a balloon station. For example, the satellite can be a low earth orbit (low earth orbit, LEO) satellite, a medium earth orbit (medium earth orbit, MEO) satellite, a geostationary earth orbit (geostationary earth orbit, GEO) satellite, a high elliptical orbit (High Elliptical Orbit, HEO) satellite, etc. Alternatively, the network device can also be a base station arranged at a position on land, water, etc.

[0044] In the embodiments of the present application, the network device can serve a cell, and a terminal device communicates with the network device through a transmission resource (for example, a frequency domain resource, or a spectrum resource) used by the cell. The cell can be a cell corresponding to the network device (for example, a base station), and the cell can belong to a macro base station or a base station corresponding to a small cell (Small cell). The small cell can include a metro cell, a micro cell, a pico cell, a femto cell, and the like. The small cell has the characteristics of small coverage and low transmit power, and is suitable for providing high-speed data transmission services.

[0045] FIG. 1 illustrates a communication system 100. The communication system includes one network device 110 and two terminal devices 120. In an embodiment, the communication system 100 can include multiple network devices 110, and each network device 110 can include other numbers of terminal devices 120 within its coverage, which is not limited in the embodiments of the present application.

[0046] In an embodiment, the communication system 100 can further include a mobility management entity (MME), an access and mobility management function (AMF), and other network entities, which are not limited in the embodiments of the present application.

[0047] The network device can include an access network device and a core network device. That is, the wireless communication system further includes multiple core networks for communicating with the access network device. The access network device can be an evolved node B (eNB or e-NodeB) macro base station, a micro base station (also referred to as a “small base station”), a pico base station, an access point (AP), a transmission point (TP), or a new generation Node B (gNodeB) in a long-term evolution (LTE) system, a next radio (NR) system, or an authorized auxiliary access long-term evolution (LAA-LTE) system.

[0048] It should be understood that the devices with communication function in the network / system in the embodiments of the present application can be referred to as communication devices. For example, the communication system shown in FIG. 1, the communication devices can include network devices and terminal devices with communication function, which can be specific devices in the embodiments of the present application, and details are not described herein. The communication devices can also include other devices in the communication system, such as network controllers, mobile management entities and other network entities, which are not limited in the embodiments of the present application.

[0049] It should be understood that the terms "system" and "network" are often used interchangeably in this paper. The term "and / or" in this paper is only used to describe the association relationship between the associated objects, which means that there can be three relationships, for example, A and / or B, which can represent three cases: A exists alone, A and B exist together, and B exists alone. In addition, the character " / " generally represents an "or" relationship between the associated objects before and after it.

[0050] It should be understood that the "indication" mentioned in the embodiments of the present application can be direct indication, indirect indication, or can represent an associated relationship. For example, A indicates B, which can mean that B can be obtained directly through A; it can also mean that A indirectly indicates B, for example, A indicates C, and B can be obtained through C; it can also mean that A and B have an associated relationship.

[0051] In the description of the embodiments of the present application, the term "corresponding" can represent a direct or indirect corresponding relationship between the two, or can represent an associated relationship between the two, or can represent an indication and being indicated, configuration and being configured, etc.

[0052] In order to facilitate the understanding of the technical solutions of the embodiments of the present application, the related technologies of the embodiments of the present application are described as follows, which can be combined with the technical solutions of the embodiments of the present application in any way, and all belong to the protection scope of the embodiments of the present application.

[0053] I. Machine learning

[0054] Machine learning is one of the ways to realize artificial intelligence, which provides the system with the ability to automatically learn and improve from experience without explicit programming. Machine learning can be divided into: supervised learning, unsupervised learning and reinforcement learning.

[0055] Supervised learning, also called supervised training, can learn or create a pattern (function / learning model) from training data, and predict new instances based on the pattern. Training data is composed of input objects (usually vectors) and expected outputs. The output of the function can be a continuous value (called regression analysis), or a predicted classification label (called classification). The task of a supervised learner is to predict the output of the function for any possible input, after observing a set of labeled training examples (input and desired output). To achieve this, the learner must generalize from the training data to unseen situations in a "reasonable" way (see induction bias).

[0056] Unsupervised learning is a class of machine learning techniques used to find patterns in data. The input data used by unsupervised learning algorithms is unlabeled, which means that the data is only given input variables (explanatory X), not corresponding data variables (dependent Y). In unsupervised learning, the algorithm itself will discover interesting structures in the data and classify them according to the characteristics or attributes of the data.

[0057] Reinforcement learning emphasizes how to act based on the environment to maximize the expected benefit. Reinforcement learning is the third basic machine learning method in addition to supervised learning and unsupervised learning. Unlike supervised learning, reinforcement learning does not require labeled input-output pairs, nor does it require precise correction of non-optimal solutions. Its focus is on finding the balance between exploration (of unknown areas) and exploitation (of existing knowledge). The exploration-exploitation trade-off in reinforcement learning is most studied in the multi-armed bandit problem and finite Markov decision processes (MDP). In machine learning problems, the environment is usually abstracted as an MDP, because many reinforcement learning algorithms use dynamic programming methods under this assumption. The main difference between traditional dynamic programming methods and reinforcement learning algorithms is that the latter does not require knowledge of the MDP, and is aimed at large-scale MDPs for which exact methods cannot be found.

[0058] II. AI and wireless communication

[0059] In the 3rd Generation Partnership Project (3GPP), it has been studied how to improve the performance of the 5th Generation Mobile Communication Technology (5G) air interface through artificial intelligence / machine learning. The research is driven by three use cases, including: 1. Positioning; 2. Beam management; 3. Channel state information reporting.

[0060] In addition, the air interface artificial intelligence (AI) project also includes some research on the life cycle management of AI models, including model training, model deployment, model inference, model detection, model updating, etc.

[0061] Subsequent standards will define an overall framework for AI / ML applications to air interface use cases, and will conduct relevant standardization work for AI / ML in use cases such as positioning and beam management. In addition, 3GPP will continue to explore the availability of AI / ML in other use cases, such as mobility.

[0062] III. Uplink data transmission

[0063] For a connected UE, the resources for transmitting uplink data can be dynamically scheduled by the network or pre-configured. In the standard protocol, the dynamically scheduled uplink transmission resource is called dynamic grant (DG), and the pre-configured uplink transmission resource is called configured grant (CG).

[0064] When there is uplink data arriving at the UE side, the behavior of the UE includes: 1) triggering a scheduling request (SR) / buffer status report (BSR) to request uplink data transmission resources from the network; 2) receiving the uplink transmission resources scheduled by the network side; 3) performing uplink data transmission on the uplink transmission resources.

[0065] The uplink resource scheduling has the following problems:

[0066] (1) The network usually allocates or activates uplink transmission resources and / or downlink transmission resources for the terminal based on the current traffic situation (such as traffic type, data volume, etc.) of the terminal. For example, when the terminal side has uplink data arriving at the access layer, the terminal triggers a BSR to request the network to allocate uplink transmission resources, and the network determines to schedule dynamic transmission resources for the terminal according to the received BSR, and / or activates / configures one or more groups of pre-configured resources. This immediate resource scheduling method increases the latency of the entire data transmission process.

[0067] (2) The pre-configured resources in the related art are usually UE-specific resources. When the traffic pattern of the uplink data changes, the network needs to frequently (de)configure, (de)activate, etc. CG resources to avoid the problem of resource waste caused by the mismatch between uplink transmission demand and resource configuration, but this also increases the signaling overhead.

[0068] Compared with the previous wireless communication systems, the current wireless communication systems provide more flexibility, emphasize the wide applicability to different scenarios and the full use of limited resources. However, the basic principles of most current work are still based on theoretical modeling of the actual communication environment or simple parameter selection. The gain brought by this basic working method is gradually weakening in the variable scene and complex communication environment. In view of this situation, it is necessary to adopt new methods and ideas combined with traditional wireless communication theory and system, so as to break through the performance bottleneck and further improve the performance of the wireless communication system.

[0069] FIG. 2 is a schematic flowchart of a communication method 200 according to an embodiment of the present application. The method can be optionally applied to the system shown in FIG. 1, but is not limited thereto. The method includes at least part of the following contents.

[0070] In S210, the first communication device determines first information related to uplink transmission based on a first model.

[0071] In the embodiments of the present application, the first communication device can be a terminal device such as a UE, and the second communication device can be a network device such as an access network device, a core network device, etc. The first model can include an artificial intelligence (AI) model. For example, the AI model can be used to select uplink transmission resources. The first communication device can determine one or more first information related to uplink transmission based on the AI model. The first communication device determines the information related to uplink transmission based on the first model, which can optimize the uplink transmission and improve the performance of the communication system. For example, the UE uses the first model to determine the uplink transmission resources, which can reduce the number of times of dynamically scheduling the uplink transmission resources, and in turn reduce the latency of the data transmission process. For another example, the UE uses the first model to determine the uplink transmission resources, and the network does not need to frequently perform one or more operations such as configuring, deconfiguring, activating, deactivating, etc. of the CG resources, and in turn reduces the signaling overhead.

[0072] In an implementation manner, the first information includes at least one of the following:

[0073] a data transmission mode;

[0074] predicted service information.

[0075] In an implementation manner, the data transmission mode includes at least one of the following:

[0076] whether to select a common uplink transmission resource;

[0077] whether to select a dedicated resource of the first communication device for sending a scheduling request (SR) request;

[0078] whether to select a dedicated resource of the first communication device for sending a buffer status report (BSR) request;

[0079] whether to select a dedicated configured grant (CG) resource of the first communication device.

[0080] In an embodiment, the common uplink transmission resource comprises at least one of the following: a random access resource, a configured grant (CG) resource, and a dynamic grant (DG) resource.

[0081] In an embodiment of the present application, the common uplink transmission resource comprises a contention-based uplink transmission resource. For example, in a small data transmission scenario, whether to select the common uplink transmission resource or whether to select the contention-based uplink transmission resource can be determined based on the first model.

[0082] In an embodiment of the present application, the dedicated resource of the first communication device can comprise a dedicated resource of a user equipment (UE). If the first communication device, for example, the UE, selects to send a BSR request for the dedicated resource of the first communication device to the second communication device, for example, a network device, based on the first model, the second communication device can provide the dedicated DG resource for the first communication device in the form of a DG.

[0083] In an embodiment of the present application, the first communication device can also determine whether to select the dedicated CG resource based on the first model.

[0084] In an embodiment, the service information comprises at least one of the following: a service type, a data volume, a period, a start time, and a Quality of Service (QoS) attribute.

[0085] In an embodiment of the present application, examples of the QoS attribute can comprise a Packet Data Unit (PDU) session IDentity (ID), a QoS flow ID, a (user) Data Radio Bearer (DRB) ID, a Logical Channel (LCH) ID, and a Logical Channel Group (LCG) ID.

[0086] In an embodiment, the method further comprises: receiving, by the first communication device, at least one of the following information:

[0087] load information of the common uplink transmission resource;

[0088] user density information obtained by the second communication device;

[0089] a QoS result;

[0090] an output result of the first model.

[0091] In embodiments of the present application, the load information of the contended uplink transmission resource includes load information of the common uplink transmission resource. The load information can be represented by one or more of a bus interface (BI) value, a load level, and the like. Different load levels can correspond to different values of collision rate, different ranges of values of collision rate, different signal strengths, different resource block occupation situations, and the like.

[0092] In embodiments of the present application, the user density obtained by the network device can include the density of active users under each beam or under the cell. For example, the user density is represented by a user density level. Different user density levels correspond to one or more of different values of resource utilization, different ranges of values of resource utilization, different maximum data transmission rates, different call drop rates, different traffic indicators, and the like.

[0093] In embodiments of the present application, the QoS result includes an index reflecting access quality, which can include, for example, the packet loss rate, the latency, the resource consumption, and the like of the first communication device when selecting different data transmission modes. The QoS result can be used as a reward for training the first model.

[0094] In an implementation, the training node of the first model is on the first communication device.

[0095] In embodiments of the present application, the first model can be trained on the first communication device. In this case, the first communication device itself can obtain one or more first-type data from the first communication device, including the downlink measurement result of the first communication device, the BSR of the uplink data, the QoS information of the uplink data, the user density information, and the uplink interference situation. The first communication device can also receive one or more second-type data from the second communication device, such as the network device, including the load information of the common uplink transmission resource, the user density information obtained by the second communication device, and the QoS result. The first-type data and / or the second-type data described above can constitute the training data of the first model. The first communication device can train or adjust the first model based on the training data.

[0096] In an implementation, as shown in FIG. 3, the method further includes: the first communication device sending at least one of the following information:

[0097] the downlink measurement result of the first communication device;

[0098] the BSR of the uplink data;

[0099] the QoS information of the uplink data;

[0100] the user density information obtained by the first communication device;

[0101] Uplink interference situation

[0102] The output result of the first model corresponds to a data transmission evaluation index.

[0103] In the embodiments of the present application, the downlink measurement result of the first communication device can include a downlink measurement result at the UE side. The buffer status report (BSR) is used to report the buffer status of the first communication device. The BSR can be triggered when the first communication device needs to report the amount of data in its buffer and the like information to the network device, for example, the base station. The reporting format and content of the BSR can be adjusted according to the buffer status of the first communication device and the resource situation of the second communication device. The QoS information can include one or more of the wireless bearer identifier to which the data belongs, the logical channel identifier, the logical channel group identifier, the QoS identifier, the delay status (Delay status) and the like. Examples of the user density information obtained by the first communication device include: the first communication device determines the user density in the surrounding area by detecting the Bluetooth, wireless fidelity (Wifi) signal and the like in the surrounding area; the first communication device determines the user density in the surrounding area based on the environment image obtained by the camera.

[0104] In an implementation manner, the training node of the first model is on the second communication device.

[0105] In the embodiments of the present application, the first model can be trained on the second communication device. In this case, the first communication device can send one or more first type data obtained by itself to the second communication device. The second communication device can obtain one or more second type data by itself. The above-mentioned first type data and / or second type data can constitute the training data of the first model. The second communication device can train or adjust the first model based on the training data.

[0106] In embodiments of the present application, the first model can be trained on the second communication device. During the training of the first model, the output of the first model can include the data transmission manner and / or the predicted service information. The second communication device can send the output of the first model during the training to the first communication device. The first communication device can determine the data transmission manner and / or the service information based on the output of the first model, and perform transmission using the determined data transmission manner and / or the service information. In this process, the data transmission evaluation index corresponding to the output of the first model can be generated. The first communication device can transmit one or more data transmission evaluation indexes, such as the number of attempts when selecting a common uplink transmission resource, the average remaining delay of the data packet to be transmitted, or the number of data packets discarded due to the timeout of the discard timer, to the second communication device. The second communication device can also collect some data transmission evaluation indexes, such as the QoS result, by itself. In this way, the second communication device can help collect data transmission evaluation indexes corresponding to different transmission manners selected by the first communication device in different environments. The second communication device can use one or more data transmission evaluation indexes corresponding to different transmission manners for the training of the first model.

[0107] In an embodiment, the inference node of the first model is on the first communication device.

[0108] In embodiments of the present application, the first model can be inferred on the first communication device. In this case, the first communication device can obtain one or more first-type data by itself. The first communication device can also receive one or more second-type data from the second communication device. The first-type data and / or the second-type data described above can constitute the inference data of the first model. The first communication device can infer the first model based on the inference data.

[0109] FIG. 3 is a schematic flowchart of a communication method 300 according to another embodiment of the present application. This embodiment can include one or more features of the method embodiments described above. In an embodiment, as shown in FIG. 3, the method further includes:

[0110] S310, the first communication device receives first event configuration information, the first event configuration information being used to indicate that the first communication device performs a first behavior in the case that a first event occurs.

[0111] In embodiments of the present application, the first communication device can receive the first event configuration information from the second communication device. After the first communication device performs the configuration according to the first event configuration information, when the first communication device detects that the first event occurs, the first communication device can perform the first behavior, such as model management.

[0112] In an embodiment, the first event includes at least one of the following:

[0113] The first communication device performs a cell handover;

[0114] The cell accessed by the first communication device does not belong to a first cell list;

[0115] The first environment information of the first communication device reaches a first threshold value;

[0116] The first environment information of the first communication device does not belong to the environment information associated with the first model;

[0117] The predicted data arrival condition of the first model deviates from the actual data arrival condition;

[0118] The QoS result meets a second threshold value.

[0119] For example, the first communication device performs a cell handover from cell C1 to cell C2, which can trigger the first event.

[0120] For another example, the first cell list can be a cell list associated with the first model, such as a physical cell ID (PCI) list. If the cell accessed by the first communication device belongs to the first cell list, normal communication can be maintained. If the cell accessed by the first communication device does not belong to the first cell list, the first event can be triggered.

[0121] For another example, the first environment information can include one or more of public uplink transmission resource load information, user density, downlink measurement result, and uplink interference condition. Some first environment information higher than the first threshold value can trigger the first event. Some first environment information lower than the first threshold value can trigger the first event. The values of the first threshold values corresponding to different types of first environment information can be different.

[0122] For another example, the QoS result, such as the packet loss rate, is greater than a certain threshold value.

[0123] In an embodiment, the deviation between the predicted data arrival condition and the actual data arrival condition includes at least one of the following:

[0124] The deviation between the actual data amount and the predicted data amount is greater than a third threshold value;

[0125] The actual service type deviates from the predicted service type;

[0126] The deviation between the actual data arrival time and the predicted arrival time is greater than a fourth threshold value.

[0127] In the embodiments of the present application, the first model can predict one or more of the data arrival conditions, such as data volume, data arrival time, and service type. If the output result of the model once or continuously N times deviates from the actual data arrival condition, the first event can be triggered. For example, if the actual arrival data volume is D1 and the predicted data volume is D0, the difference or absolute value of the difference between D1 and D0 is greater than a third threshold, the first event can be triggered. For another example, if the actual arrival service type is S1 and the predicted service type is S0, S1 is different from S0, the first event can be triggered. For another example, if the actual arrival time of a certain data is T1 and the predicted arrival time is T0, the difference or absolute value of the difference between T1 and T0 is greater than a fourth threshold, the first event can be triggered.

[0128] In an implementation, the first behavior includes at least one of the following: updating the model; requesting the second communication device to update the model; selecting the model; activating the model; and deactivating the model.

[0129] In the embodiments of the present application, if the first communication device triggers the first event, the first communication device can update the AI model using the training data, or can request the second communication device to update the AI model and then issue the update result. If the first communication device triggers the first event, the first communication device can select a specific AI model to process the service. If the first communication device triggers the first event, the first communication device can activate or deactivate the AI model associated with the first event.

[0130] FIG. 4 is a schematic flowchart of a communication method 400 according to an embodiment of the present application. The method can optionally be applied to the system shown in FIG. 1, but is not limited to this. The method includes at least part of the following.

[0131] S410, the second communication device determines second information of the uplink transmission resource based on a second model.

[0132] In the embodiments of the present application, the first communication device can be a terminal device, such as a UE, and the second communication device can be a network device, such as an access network device, a core network device, etc. The second model can include an artificial intelligence (AI) model. For example, the AI model can be used to dynamically adjust the uplink resource configuration. The second communication device can determine one or more second information related to uplink transmission based on the AI model. The second communication device determines the information related to uplink transmission based on the second model, which can optimize the uplink transmission and improve the performance of the communication system.

[0133] The first model of the present embodiment and the second model of the above-mentioned embodiments can be the same model, can be different models, can be associated models, or can be models that need to be used in cooperation (such as encoding and decoding models).

[0134] In an embodiment, the second information comprises at least one of the following:

[0135] configuration information of the common uplink transmission resource;

[0136] a grant decision.

[0137] In the embodiments of the present application, the configuration information of the common uplink transmission resource can comprise a common uplink transmission resource configuration.

[0138] In an embodiment, the configuration information of the common uplink transmission resource comprises:

[0139] whether the common uplink transmission resource is configured;

[0140] a number of common uplink transmission resources associated with different Synchronization Signal Block (SSB) threshold ranges;

[0141] a number of common uplink transmission resources associated with different Reference Signal Received Power (RSRP) threshold ranges.

[0142] For example, the common uplink transmission resource configuration can comprise one or more of the following: whether the common uplink transmission resource is configured, the number of common uplink transmission resources associated with different SSB threshold ranges, the number of common uplink transmission resources associated with different RSRP threshold ranges, etc.

[0143] In an embodiment, the common uplink transmission resource comprises at least one of the following: a random access resource, a CG resource, a DG resource.

[0144] In an embodiment, the grant decision comprises a CG decision and / or a DG decision.

[0145] In an embodiment, the CG decision comprises at least one of the following: whether a CG is configured; CG resource activation; CG resource deactivation; CG configuration adjustment.

[0146] In an embodiment, the DG decision comprises at least one of the following: whether a DG is configured; DG resource activation; DG resource deactivation; DG configuration adjustment.

[0147] In an embodiment, the training node and / or the inference node of the first model are on the second communication device. In this case, the method further comprises: the second communication device receiving at least one of the following information:

[0148] downlink measurement results of the first communication device;

[0149] a BSR of the uplink data;

[0150] QoS information of the uplink data;

[0151] location information of the first communication device;

[0152] historical moving track of the first communication device;

[0153] predicted moving track of the first communication device;

[0154] moving speed of the first communication device;

[0155] data transmission evaluation index.

[0156] In the embodiments of the present application, the second model can be trained or inferred on the second communication device. In this case, the second communication device itself can obtain one or more third type of data (which can be partially or entirely the same as the second type of data in the above method embodiments) from the load information of the public uplink transmission resource, the user density information obtained by the second communication device, and the QoS result. The second communication device can also receive one or more fourth type of data (which can be partially or entirely the same as the first type of data in the above method embodiments) from the first communication device, such as the downlink measurement result of the first communication device, the BSR of the uplink data, the QoS information of the uplink data, the location information of the first communication device, the historical moving track of the first communication device, the predicted moving track of the first communication device, the moving speed of the first communication device, and the data transmission evaluation index. The above third type of data and / or fourth type of data can constitute the training data and / or inference data of the second model. The training data and the inference data can be the same, partially the same, or different. The second communication device can train or adjust the second model based on the training data. The second communication device can infer the second model based on the inference data.

[0157] FIG. 5 is a schematic flowchart of a communication method 500 according to another embodiment of the present application. The method can optionally be applied to the system shown in FIG. 1, but is not limited thereto. The method includes at least part of the following. In an implementation, as shown in FIG. 5, the method further includes:

[0158] S510, the second communication device sends second event configuration information, the second event configuration information being used to indicate that the first communication device performs a second behavior in the case where a second event occurs.

[0159] In the embodiments of the present application, the second communication device can send the second event configuration information to the first communication device. After the first communication device performs the configuration according to the second event configuration information, when the first communication device detects the occurrence of the second event, the first communication device can perform the second behavior, such as model management.

[0160] In an embodiment, the second event comprises at least one of the following:

[0161] a data transmission evaluation index reaches a fifth threshold value;

[0162] a downlink measurement result reaches a sixth threshold value;

[0163] an average moving speed reaches a seventh threshold value;

[0164] a data amount reaches an eighth threshold value;

[0165] a service type of the data changes.

[0166] In an embodiment of the present application, the data transmission evaluation index can comprise one or more of the following: a number of attempts when the first communication device selects the common uplink transmission resource, an average remaining delay of a data packet to be transmitted, a number of data packets discarded due to expiration of a discard timer, a QoS result, etc. The threshold values of different indexes can be the same or different. If the data transmission evaluation index reaches (is greater than or less than) the fifth threshold value once or continuously for N times, the second event can be triggered.

[0167] For example, if the number of attempts when the first communication device selects the common uplink transmission resource is greater than the fifth threshold value (a number threshold value), the second event can be triggered. For another example, if the average remaining delay of the data packet to be transmitted is greater than the fifth threshold value (a delay threshold value), the second event can be triggered. For another example, if the number of discarded data packets is greater than the fifth threshold value (a quantity threshold value), the second event can be triggered. For another example, if the number of attempts when the first communication device selects the common uplink transmission resource is greater than the fifth threshold value (a number threshold value) and the number of discarded data packets is greater than the fifth threshold value (a quantity threshold value), the second event can be triggered.

[0168] In an embodiment of the present application, the downlink measurement result of the first communication device can also be one of the following: RSRP, reference signal received quality (RSRQ), etc. If the RSRP is less than the sixth threshold value (a power threshold value), the second event can be triggered. If the RSRQ is less than the sixth threshold value (a quality threshold value), the second event can be triggered.

[0169] In an embodiment of the present application, the average moving speed of the first communication device can be calculated according to a time interval. If the average moving speed of the first communication device is greater than or less than the seventh threshold value (a speed threshold value) within a certain time range, the second event can be triggered.

[0170] In an embodiment of the present application, the data amount of different service types can have the same or different eighth threshold values. If the data amount of a certain service of the first communication device is greater than or less than the eighth threshold value, the second event can be triggered.

[0171] In the embodiments of the present application, the service type of the data being processed or to be processed by the first model of the first communication device changes, which can trigger the second event.

[0172] In an implementation, the second behavior includes at least one of the following: reporting downlink measurement results; reporting location information; reporting a moving track; reporting a moving speed information; reporting uplink data arrival situation; reporting a data transmission evaluation index. The UE reporting can assist in model management. The second behavior can also be considered as a behavior related to model management. For example, the network configures some threshold values for the UE, and the UE feeds back some information to the network based on the threshold values to help the network determine whether the model needs to be adjusted / updated.

[0173] In the embodiments of the present application, if the second communication device triggers the second event, it can report downlink measurement results, report location information, report a moving track, report a moving speed information, report uplink data arrival situation or report a data transmission evaluation index.

[0174] The specific examples of the second communication device executing the methods 400 and 500 of the embodiments can refer to the related descriptions of the second communication device, such as the network device, in the methods 200 and 300 described above. For brevity, the details are not repeated here.

[0175] The embodiments of the present application can use AI technology in the selection and / or configuration of uplink transmission resources in a wireless communication system to optimize the resource selection strategy and the resource configuration mode. The following are several specific examples:

[0176] Example 1: UE-side AI model for selecting uplink transmission resources

[0177] 1. The UE determines at least one of the following information based on the first model:

[0178] (a) Data transmission mode, including: whether to select a common uplink transmission resource, or whether to send an SR / BSR request to the network to request a UE-specific resource. In an implementation, the common uplink transmission resource is a common uplink transmission resource, such as at least one of a random access resource, a CG resource, and a DG resource.

[0179] (b) Predicted service information, including: service type, data volume, period, start time, QoS attribute (such as PDU session ID, QoS flow ID, DRB ID, LCH ID, LCG ID, etc.).

[0180] 2. The training node of the first model is at the UE side or the network side, for example, including the following cases:

[0181] (a) The training node of the first model is at the UE side, in addition to the information that the UE side itself can obtain (see one or more information in case (b) of point 2), the UE collects one or more of the following information for model training. In an implementation, one or more of the following information collected by the UE is contained in the network downlink signaling:

[0182] i. Load information of the common uplink transmission resource. In an implementation, the load information of the common uplink transmission resource is characterized by a BI value, and / or, a load level is characterized, different load levels correspond to different values / value ranges of collision rate, signal strength, resource block occupation, etc.

[0183] ii. User density. For example, the density of active users under each beam or under the cell. In an implementation, the user density is characterized by a user density level, different user density levels correspond to different values / value ranges of resource utilization, maximum data transmission rate, call drop rate, traffic indicators, etc.

[0184] iii. QoS results, such as packet loss rate, latency, resource consumption, etc. when the UE selects different data transmission modes. In an implementation, the QoS result is used as a reward for model training.

[0185] (b) The training node of the first model is at the network side, in addition to the information that the network side itself can obtain (see one or more information in case (a) of point 2), the network side also needs to collect the following information from the UE side for model training:

[0186] i. Downlink measurement results at the UE side.

[0187] ii. BSR of uplink data, and / or, QoS information. In an implementation, the QoS information includes wireless bearer identification, logical channel identification, logical channel group identification, QoS identification, delay status (e.g. remaining transmission delay of data packet) to which the data belongs.

[0188] iii. User density information obtained by the UE. For example, the UE determines the user density in the surrounding area by detecting Bluetooth / Wifi signals in the surrounding area, and / or, the UE determines the user density in the surrounding area based on the environment image obtained by the camera.

[0189] iv. Uplink interference situation.

[0190] In addition, during the model training process, the network indicates the model output result to the UE, and the UE determines the transmission mode of the current data based on the network indication. The UE can use the determined transmission mode for transmission. The network can collect the QoS results corresponding to the transmission mode after the UE uses such transmission mode. In this way, the network can help collect the QoS results corresponding to the selection of different transmission modes by the UE in different environments.

[0191] 3. The inference node of the first model is at the UE side. In addition to the information that the UE itself can obtain (see one or more pieces of information in case (b) of the second point), the UE also needs to obtain one or more of the following information from the network side as input for model inference: load information of the common uplink transmission resource; user density; uplink measurement result.

[0192] 4. The network can configure at least one of the following events (i.e., the first event) for model management. When at least one event is met, the UE's behavior includes one or more of the following: 1) update the model; 2) request the network to update the model; 3) model selection; 4) model (de)activation.

[0193] Examples of events configured by the network are as follows:

[0194] (a) The UE performs cell switching or the cell accessed by the UE does not belong to the first cell list;

[0195] (b) The first environment information is lower / higher than the first threshold / does not belong to the environment information list associated with the first model, and the first environment information includes at least one of the following: load information of the common uplink transmission resource, user density, downlink measurement result, and uplink interference situation. For example, the first model is adapted to the case where the random access load level is 1 and 2, and when the load level in the environment becomes 3, the UE falls back to the traditional access algorithm, or selects to switch to a second model, where the second model is adapted to the case where the load level is 3;

[0196] (c) The QoS result meets the second threshold;

[0197] (d) The model output result deviates from the actual data arrival situation for N consecutive times. For example, the actual data volume deviates from the predicted data volume by more than a third threshold, and / or the actual service type deviates from the predicted service type to be arrived, and / or the time of arrival of the data deviates from the predicted arrival time by more than a fourth threshold.

[0198] Example 2 Network-side Model for Dynamically Adjusting Uplink Resource Configuration

[0199] 1. The network determines at least one of the following information based on the second model:

[0200] (a) Public uplink transmission resource configuration, which can include one or more of the following: whether to configure public uplink transmission resource, the number of public uplink transmission resources associated with different SSB threshold ranges, the number of public uplink transmission resources associated with different RSRP threshold ranges;

[0201] (b) CG decision and / or DG decision, which can include one or more of the following: whether to configure CG, CG resource activation, CG resource deactivation, CG configuration adjustment, etc.

[0202] 2. The training node of the second model is on the network side, in addition to the information that the network side itself can obtain (see one or more information in case (a) of example 1, point 2), the network side also needs to collect at least one of the following information from the UE side for model training:

[0203] (a) Downlink measurement results;

[0204] (b) BSR of uplink data, and / or QoS information; in an implementation, the QoS information includes wireless bearer identification, logical channel identification, logical channel group identification, QoS identification, etc. to which the data belongs;

[0205] (c) UE location information, and / or historical moving track, and / or predicted moving track;

[0206] (d) UE moving speed;

[0207] (e) Data transmission evaluation index, including the number of attempts when the UE selects a public uplink transmission resource, the average remaining delay of the data packet to be transmitted, and the number of data packets discarded due to the timeout of the discard timer. In an implementation, the data transmission evaluation index is used as a reward for model training.

[0208] 3. The inference node of the second model is on the network side, in addition to the information that the network itself can obtain (see one or more information in case (a) of example 1, point 2), the network also needs to obtain the following information from the UE side as the input of model inference:

[0209] (a) Downlink measurement results;

[0210] (b) BSR of uplink data, and / or QoS information; in an implementation, the QoS information includes wireless bearer identification, logical channel identification, logical channel group identification, QoS identification, Delay status (for example, the remaining transmission delay of the data packet), etc. to which the data belongs;

[0211] (c) UE location information, and / or historical moving track, and / or predicted moving track, and / or moving speed.

[0212] 4. The network can configure at least one of the following events (i.e., the second event) for model management. When at least one event is met, the UE's behavior includes one or more of the following: 1) reporting downlink measurement results; 2) reporting location information / moving track / moving speed information; 3) reporting uplink data arrival situation, such as BSR, QoS, etc.; 4) reporting data transmission evaluation index.

[0213] Examples of the event configured by the network are as follows:

[0214] (a) The data transmission evaluation index is higher / lower than a fifth threshold value, including: the number of attempts when the UE selects a common uplink transmission resource is greater than a fifth threshold value / the number of attempts when the UE selects a common uplink transmission resource for N consecutive times is greater than a fourth threshold value; the average remaining delay of data packets to be transmitted is less than a fifth threshold value; the number of data packets discarded due to the expiration of a discard timer is greater than a fifth threshold value;

[0215] (b) The downlink measurement result is higher / lower than a sixth threshold value;

[0216] (c) The average moving speed is higher / lower than a seventh threshold value;

[0217] (d) The data volume is higher / lower than an eighth threshold value;

[0218] (e) The service type of the data changes.

[0219] FIG. 6 is a schematic block diagram of a first communication device 600 according to an embodiment of the present application. The first communication device 600 can include:

[0220] A first processing unit 610 configured to determine first information related to uplink transmission based on a first model.

[0221] In an implementation, the first information includes at least one of the following:

[0222] Data transmission mode;

[0223] Predicted service information.

[0224] In an implementation, the data transmission mode includes at least one of the following:

[0225] Whether to select a common uplink transmission resource;

[0226] Whether to select a dedicated resource of the first communication device for sending an SR request;

[0227] Whether to select a dedicated resource of the first communication device for sending a BSR request;

[0228] whether to select a dedicated CG resource of the first communication device.

[0229] In an embodiment, the common uplink transmission resource comprises at least one of the following: a random access resource, a CG resource, and a DG resource.

[0230] In an embodiment, the service information comprises at least one of the following: a service type, a data volume, a period, a start time, and a QoS attribute.

[0231] FIG. 7 is a schematic block diagram of a first communication device 700 according to another embodiment of the present application. This embodiment can include one or more features of the above-described first communication device embodiments. In an embodiment, the first communication device 700 can include the first processing unit 710 described above, see the related description of the first processing unit 610 above. The first communication device 700 can further include:

[0232] a first receiving unit 720 configured to receive at least one of the following information:

[0233] load information of a common uplink transmission resource;

[0234] user density information obtained by a second communication device;

[0235] a QoS result;

[0236] an output result of the first model.

[0237] In an embodiment, a training node of the first model is on the first communication device.

[0238] In an embodiment, as shown in FIG. 7, the device further includes:

[0239] a first sending unit 730 configured to send at least one of the following information:

[0240] a downlink measurement result of the first communication device;

[0241] a BSR of uplink data;

[0242] QoS information of uplink data;

[0243] user density information obtained by the first communication device;

[0244] an uplink interference condition;

[0245] the output result of the first model corresponds to a data transmission evaluation index.

[0246] In an embodiment, a training node of the first model is on a second communication device.

[0247] In an implementation, the inference node of the first model is on the first communication device.

[0248] In an implementation, as shown in FIG. 7, the device further includes:

[0249] A second receiving unit 740, configured to receive first event configuration information, the first event configuration information being used to indicate that the first communication device performs a first behavior in case of occurrence of a first event.

[0250] In an implementation, the first event includes at least one of the following:

[0251] The first communication device performs cell switching;

[0252] The cell accessed by the first communication device does not belong to a first cell list;

[0253] First environment information of the first communication device reaches a first threshold value;

[0254] The first environment information of the first communication device does not belong to environment information associated with the first model;

[0255] The predicted data arrival condition of the first model is deviated from the actual data arrival condition for a plurality of times of prediction in succession;

[0256] The QoS result meets a second threshold value.

[0257] In an implementation, the predicted data arrival condition is deviated from the actual data arrival condition includes at least one of the following:

[0258] The deviation between the actual data amount and the predicted data amount is greater than a third threshold value;

[0259] The actual arrived service type is different from the predicted service type to be arrived;

[0260] The deviation between the actual arrival time of data and the predicted arrival time is greater than a fourth threshold value.

[0261] In an implementation, the first behavior includes at least one of the following: updating the model; requesting a second communication device to update the model; selecting the model; activating the model; and deactivating the model.

[0262] The first communication device 600, 700 of the embodiments of the present application can realize the corresponding functions of the first communication device in the foregoing method embodiments. The processes, functions, implementation manners, and beneficial effects of the respective modules (sub-modules, units, or components, etc.) in the first communication device 600, 700 can be referred to the corresponding descriptions in the foregoing method embodiments, which will not be described here again. It should be noted that the functions described with respect to the respective modules (sub-modules, units, or components, etc.) in the first communication device 600, 700 of the embodiments of the present application can be realized by different modules (sub-modules, units, or components, etc.), or by the same module (sub-module, unit, or component, etc.).

[0263] FIG. 8 is a schematic block diagram of a second communication device 800 according to an embodiment of the present application. The second communication device 800 can include:

[0264] A second processing unit 810, configured to determine second information of the uplink transmission resource based on a second model.

[0265] In an implementation manner, the second information includes at least one of the following:

[0266] Configuration information of the common uplink transmission resource;

[0267] An authorization decision.

[0268] In an implementation manner, the configuration information of the common uplink transmission resource includes:

[0269] Whether the common uplink transmission resource is configured;

[0270] A number of common uplink transmission resources associated with different SSB threshold ranges;

[0271] A number of common uplink transmission resources associated with different RSRP threshold ranges.

[0272] In an implementation manner, the common uplink transmission resource includes at least one of the following: a random access resource, a CG resource, and a DG resource.

[0273] In an implementation manner, the authorization decision includes a CG decision and / or a DG decision.

[0274] In an implementation manner, the CG decision includes at least one of the following: whether a CG is configured; CG resource activation; CG resource deactivation; and CG configuration adjustment.

[0275] In an implementation manner, the DG decision includes at least one of the following: whether a DG is configured; DG resource activation; DG resource deactivation; and DG configuration adjustment.

[0276] Figure 9 is a schematic block diagram of a second communication device 900 according to an embodiment of the application. The embodiment can include one or more features of the above-described second communication device embodiments. In one implementation, the second communication device 900 can include a second processing unit 910, see the related description of the above-described second processing unit 810. The second communication device 900 can further include:

[0277] a third receiving unit 920 configured to receive at least one of the following information:

[0278] a downlink measurement result of the first communication device;

[0279] a BSR of the uplink data;

[0280] QoS information of the uplink data;

[0281] location information of the first communication device;

[0282] a historical moving trajectory of the first communication device;

[0283] a predicted moving trajectory of the first communication device;

[0284] a moving speed of the first communication device;

[0285] a data transmission evaluation index.

[0286] In one implementation, the training node and / or the inference node of the first model are on the second communication device.

[0287] In one implementation, as shown in Figure 9, the device further includes:

[0288] a second sending unit 930 configured to send second event configuration information, the second event configuration information being used to indicate that the first communication device performs a second behavior in the case that a second event occurs.

[0289] In one implementation, the second event includes at least one of the following:

[0290] the data transmission evaluation index reaches a fifth threshold value;

[0291] the downlink measurement result reaches a sixth threshold value;

[0292] the average moving speed reaches a seventh threshold value;

[0293] the data amount reaches an eighth threshold value;

[0294] a service type of the data changes.

[0295] In an embodiment, the second behavior comprises at least one of the following: reporting a downlink measurement result; reporting location information; reporting a moving track; reporting a moving speed information; reporting an uplink data arrival condition; and reporting a data transmission evaluation index.

[0296] The second communication device 800, 900 of the embodiments of the present application can realize the corresponding functions of the second communication device in the method embodiments described above. The processes, functions, implementation manners and advantages of each module (sub-module, unit or component, etc.) in the second communication device 800, 900 can be referred to the corresponding description in the method embodiments described above, and will not be repeated here. It should be noted that the functions described with respect to each module (sub-module, unit or component, etc.) in the second communication device 800, 900 of the embodiments of the present application can be realized by different modules (sub-modules, units or components, etc.), or can be realized by the same module (sub-module, unit or component, etc.).

[0297] FIG. 10 is a schematic structural diagram of a communication device 1000 according to an embodiment of the present application. The communication device 1000 comprises a processor 1010, which can call and run a computer program from a memory to enable the communication device 1000 to implement the methods in the embodiments of the present application.

[0298] In an embodiment, the communication device 1000 can further comprise a memory 1020. The processor 1010 can call and run a computer program from the memory 1020 to enable the communication device 1000 to implement the methods in the embodiments of the present application.

[0299] The memory 1020 can be a separate device independent of the processor 1010, or can be integrated in the processor 1010.

[0300] In an embodiment, the communication device 1000 can further comprise a transceiver 1030, and the processor 1010 can control the transceiver 1030 to communicate with other devices, specifically, to send information or data to other devices, or to receive information or data sent by other devices.

[0301] The transceiver 1030 can comprise a transmitter and a receiver. The transceiver 1030 can further comprise an antenna, and the number of antennas can be one or more.

[0302] In an embodiment, the communication device 1000 can be the first communication device of the embodiments of the present application, and the communication device 1000 can realize the corresponding processes realized by the first communication device in the various methods of the embodiments of the present application. For brevity, details will not be repeated here.

[0303] In an embodiment, the communication device 1000 can be a second communication device of the embodiments of the present application, and the communication device 1000 can implement corresponding procedures in the methods of the embodiments of the present application implemented by the second communication device. For brevity, details are not repeated here.

[0304] FIG. 11 is a schematic structural diagram of a chip 1100 according to an embodiment of the present application. The chip 1100 includes a processor 1110, which can call and run a computer program from a memory to implement the methods in the embodiments of the present application.

[0305] In an embodiment, the chip 1100 can further include a memory 1120. The processor 1110 can call and run a computer program from the memory 1120 to implement the methods in the embodiments of the present application implemented by the first communication device or the second communication device.

[0306] The memory 1120 can be a separate device independent of the processor 1110, or can be integrated in the processor 1110.

[0307] In an embodiment, the chip 1100 can further include an input interface 1130. The processor 1110 can control the input interface 1130 to communicate with other devices or chips, and specifically, can obtain information or data sent by other devices or chips.

[0308] In an embodiment, the chip 1100 can further include an output interface 1140. The processor 1110 can control the output interface 1140 to communicate with other devices or chips, and specifically, can output information or data to other devices or chips.

[0309] In an embodiment, the chip can be applied to the first communication device in the embodiments of the present application, and the chip can implement corresponding procedures in the methods of the embodiments of the present application implemented by the first communication device. For brevity, details are not repeated here.

[0310] In an embodiment, the chip can be applied to the second communication device in the embodiments of the present application, and the chip can implement corresponding procedures in the methods of the embodiments of the present application implemented by the second communication device. For brevity, details are not repeated here.

[0311] The chip applied to the first communication device and the second communication device can be the same chip or different chips.

[0312] It should be understood that the chip mentioned in the embodiments of the present application can also be referred to as a system-level chip, a system chip, a chip system, or a system-on-chip chip, etc.

[0313] The aforementioned processor can be a general processor, a digital signal processor (DSP), a field programmable gate array (FPGA), an application specific integrated circuit (ASIC) or other programmable logic device, a transistor logic device, a discrete hardware component, etc. Among them, the aforementioned general processor can be a microprocessor or any conventional processor, etc.

[0314] The aforementioned memory can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically EPROM (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM).

[0315] It should be understood that the aforementioned memory is an exemplary but non-limiting description, for example, the memory in the embodiments of the present application can also be a static RAM (SRAM), a dynamic RAM (DRAM), a synchronous DRAM (SDRAM), a double data rate SDRAM (DDR SDRAM), an enhanced SDRAM (ESDRAM), a synch link DRAM (SLDRAM) and a direct memory bus random access memory (Direct Rambus RAM, DR RAM), etc. That is, the memory in the embodiments of the present application is intended to include but not limited to these and any other suitable type of memory.

[0316] FIG. 12 is a schematic block diagram of a communication system 1200 according to an embodiment of the present application. The communication system 1200 includes a first communication device 1210 and a second communication device 1220.

[0317] In an implementation, the first communication device 1210 is configured to determine first information related to uplink transmission based on a first model.

[0318] In an embodiment, the second communication device 1220 is configured to determine the second information of the uplink transmission resource based on the second model.

[0319] The first communication device 1210 can be configured to implement the corresponding functions of the first communication device in the above-described methods, and the second communication device 1220 can be configured to implement the corresponding functions of the second communication device in the above-described methods. For brevity, details are not repeated here.

[0320] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed by a computer, all or part of the computer program instructions generate the processes or functions in the embodiments of the present application. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (Digital Subscriber Line, DSL)) or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that includes one or more available media sets. The available medium can be a magnetic medium (for example, floppy disk, hard disk, magnetic tape), an optical medium (for example, DVD), or a semiconductor medium (for example, solid state disk (Solid State Disk, SSD)) and the like.

[0321] It should be understood that in various embodiments of the present application, the size of the sequence number of each process described above does not mean the order of execution, and the execution order of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0322] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0323] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for communication, comprising: determining, by a first communication device, first information related to uplink transmission based on a first model.

2. The method of claim 1, wherein, The first information comprises at least one of: a data transmission manner; predicted traffic information.

3. The method of claim 2, wherein, The data transmission manner comprises at least one of: whether to select a common uplink transmission resource; whether to select a dedicated resource of the first communication device for sending a scheduling request (SR) request; whether to select a dedicated resource of the first communication device for sending a buffer status report (BSR) request; whether to select a dedicated configured grant (CG) resource of the first communication device.

4. The method of claim 3, wherein, The common uplink transmission resource comprises at least one of: a random access resource, a CG resource, and a dynamic grant (DG) resource.

5. The method of any one of claims 2 to 4, wherein, The traffic information comprises at least one of: a traffic type, a data volume, a period, a start time, and a quality of service (QoS) attribute.

6. The method of any one of claims 1 to 5, wherein, The method further comprises: receiving, by the first communication device, at least one of: load information of a common uplink transmission resource; user density information obtained by a second communication device; a QoS result; an output result of the first model.

7. The method of claim 6, wherein, A training node of the first model is on the first communication device.

8. The method of any one of claims 1 to 5, wherein, The method further comprises: sending, by the first communication device, at least one of: a downlink measurement result of the first communication device; a BSR of uplink data; QoS information of uplink data; user density information obtained by the first communication device; an uplink interference situation; an output result of the first model corresponding to a data transmission evaluation index.

9. The method of claim 8, wherein, A training node of the first model is on a second communication device.

10. The method of any one of claims 1 to 9, wherein, An inference node of the first model is on the first communication device.

11. The method of any one of claims 1 to 10, wherein, The method further comprises: receiving, by the first communication device, first event configuration information, which is used to indicate the first communication device to perform a first behavior in a case where a first event occurs.

12. The method of claim 11, wherein, The first event comprises at least one of: a cell handover of the first communication device; a cell accessed by the first communication device not belonging to a first cell list; first environment information of the first communication device reaching a first threshold; the first environment information of the first communication device not belonging to environment information associated with the first model; a deviation between a predicted data arrival condition and an actual data arrival condition in a plurality of consecutive predictions of the first model; a QoS result satisfying a second threshold.

13. The method of claim 12, wherein, The deviation between the predicted data arrival condition and the actual data arrival condition comprises at least one of: a deviation between an actual data volume and a predicted data volume being greater than a third threshold; an actual traffic type being different from a predicted traffic type to be arrived; a deviation between an actual data arrival time and a predicted arrival time being greater than a fourth threshold.

14. The method of any one of claims 11 to 13, wherein, The first behavior comprises at least one of: updating a model; requesting a second communication device to update a model; selecting a model; activating a model; and deactivating a model. 15.A method for communication, comprising: determining, by a second communication device, second information of an uplink transmission resource based on a second model.

16. The method of claim 15, wherein, The second information comprises at least one of: configuration information of a common uplink transmission resource; an authorization decision.

17. The method of claim 16, wherein, The configuration information of the common uplink transmission resource comprises: whether to configure a common uplink transmission resource; a number of common uplink transmission resources associated with different SSB threshold ranges; a number of common uplink transmission resources associated with different RSRP threshold ranges.

18. The method of claim 16 or 17, wherein, The common uplink transmission resource includes at least one of the following: a random access resource, a CG resource, and a DG resource.

19. The method of any one of claims 16-18, wherein, The authorization decision includes a CG decision and / or a DG decision.

20. The method of claim 19, wherein, The CG decision includes at least one of the following: whether to configure a CG; CG resource activation; CG resource deactivation; and CG configuration adjustment.

21. The method of claim 19 or 20, wherein, The DG decision includes at least one of the following: whether to configure a DG; DG resource activation; DG resource deactivation; and DG configuration adjustment.

22. The method of any one of claims 15 to 21, wherein, The method further includes: The second communication device receives at least one of the following information: downlink measurement results of the first communication device; BSR of uplink data; QoS information of uplink data; location information of the first communication device; historical moving trajectory of the first communication device; predicted moving trajectory of the first communication device; moving speed of the first communication device; a data transmission evaluation index.

23. The method of claim 22, wherein, The training node and / or inference node of the first model are on the second communication device.

24. The method of any one of claims 15 to 23, wherein, The method further includes: The second communication device sends second event configuration information, which is used to instruct the first communication device to perform a second behavior in the case of a second event.

25. The method of claim 24, wherein, The second event includes at least one of the following: the data transmission evaluation index reaches a fifth threshold value; the downlink measurement result reaches a sixth threshold value; the average moving speed reaches a seventh threshold value; the data volume reaches an eighth threshold value; the service type of the data changes.

26. The method of claim 24 or 25, wherein, The second behavior includes at least one of the following: reporting downlink measurement results; reporting location information; reporting moving trajectory; reporting moving speed information; reporting uplink data arrival; and reporting data transmission evaluation index.

27. A first communication device, comprising: a first processing unit configured to determine first information related to uplink transmission based on a first model.

28. The method of claim 27, wherein, The first information includes at least one of the following: a data transmission mode; predicted service information.

29. The apparatus of claim 28, wherein, The data transmission mode includes at least one of the following: whether to select a common uplink transmission resource; whether to select a dedicated resource of the first communication device for sending an SR request; whether to select a dedicated resource of the first communication device for sending a BSR request; whether to select a dedicated CG resource of the first communication device.

30. The apparatus of claim 29, wherein, The common uplink transmission resource includes at least one of the following: a random access resource, a configured grant CG resource, and a dynamic grant DG resource.

31. The apparatus of any one of claims 28-30, wherein, The service information includes at least one of the following: service type, data volume, period, start time, and quality of service QoS attribute.

32. The apparatus of any one of claims 27-31, wherein, The device further includes: a first receiving unit configured to receive at least one of the following information: load information of a common uplink transmission resource; user density information obtained by a second communication device; QoS result; output result of the first model.

33. The apparatus of claim 32, wherein, The training node of the first model is on the first communication device.

34. The apparatus of any one of claims 27-31, wherein, The device further includes: a first sending unit configured to send at least one of the following information: downlink measurement results of the first communication device; BSR of uplink data; QoS information of uplink data; The user density information obtained by the first communication device; The uplink interference condition; The output result of the first model corresponds to a data transmission evaluation index.

35. The apparatus of claim 34, wherein, The training node of the first model is on the second communication device.

36. The apparatus of any one of claims 27-35, wherein, The inference node of the first model is on the first communication device.

37. The apparatus of any one of claims 27-36, wherein, The device further comprises: A second receiving unit configured to receive first event configuration information, the first event configuration information being used to instruct the first communication device to perform a first behavior in the case of occurrence of a first event.

38. The apparatus of claim 37, wherein, The first event comprises at least one of: The first communication device performs cell switching; The cell accessed by the first communication device does not belong to a first cell list; The first environment information of the first communication device reaches a first threshold value; The first environment information of the first communication device does not belong to the environment information associated with the first model; The predicted data arrival condition of the first model is deviated from the actual data arrival condition; The QoS result satisfies a second threshold value.

39. The apparatus of claim 38, wherein, The deviation between the predicted data arrival condition and the actual data arrival condition comprises at least one of: The deviation between the actual data amount and the predicted data amount is greater than a third threshold value; The actual arrived service type is different from the predicted service type to be arrived; The deviation between the actual arrival time of data and the predicted arrival time is greater than a fourth threshold value.

40. The apparatus of any one of claims 37-39, wherein, The first behavior comprises at least one of: updating the model; requesting the second communication device to update the model; selecting the model; activating the model; and deactivating the model.

41. A second communication device, comprising: A second processing unit configured to determine second information of an uplink transmission resource based on a second model.

42. The apparatus of claim 41, wherein, The second information comprises at least one of: Configuration information of a common uplink transmission resource; An authorization decision.

43. The apparatus of claim 42, wherein, The configuration information of the common uplink transmission resource comprises: Whether the common uplink transmission resource is configured; The number of common uplink transmission resources associated with different SSB threshold ranges; The number of common uplink transmission resources associated with different RSRP threshold ranges.

44. The apparatus of claim 42 or 43, wherein, The common uplink transmission resource comprises at least one of: a random access resource, a CG resource, and a DG resource.

45. The apparatus of any one of claims 42-44, wherein, The authorization decision comprises a CG decision and / or a DG decision.

46. The apparatus of claim 45, wherein, The CG decision comprises at least one of: whether the CG is configured; CG resource activation; CG resource deactivation; and CG configuration adjustment.

47. The apparatus of claim 45 or 46, wherein, The DG decision comprises at least one of: whether the DG is configured; DG resource activation; DG resource deactivation; and DG configuration adjustment.

48. The apparatus of any one of claims 41-47, wherein, The device further comprises: A third receiving unit configured to receive at least one of the following information: Downlink measurement result of the first communication device; BSR of uplink data; QoS information of uplink data; Position information of the first communication device; Historical moving track of the first communication device; Predicted moving track of the first communication device; Moving speed of the first communication device; Data transmission evaluation index.

49. The apparatus of claim 48, wherein, The training node and / or the inference node of the first model are on the second communication device.

50. The apparatus of any one of claims 41-49, wherein, The device further comprises: A second sending unit configured to send second event configuration information, the second event configuration information being used to instruct the first communication device to perform a second behavior in the case of occurrence of a second event.

51. The apparatus of claim 50, wherein, The second event includes at least one of the following: a data transmission evaluation index reaches a fifth threshold value; a downlink measurement result reaches a sixth threshold value; an average moving speed reaches a seventh threshold value; a data volume reaches an eighth threshold value; a service type of the data changes.

52. The apparatus of claim 50 or 51, wherein, The second behavior includes at least one of the following: reporting a downlink measurement result; reporting position information; reporting a moving trajectory; reporting moving speed information; reporting an uplink data arrival situation; and reporting a data transmission evaluation index.

53. A communication device comprising: A transceiver, a processor and a memory, the memory is used to store a computer program, the transceiver is used to communicate with other devices, and the processor is used to call and run the computer program stored in the memory, so that the communication device executes the method in any one of claims 1 to 14.

54. A chip comprising: A processor is used to call and run a computer program from a memory, so that a device installed with the chip executes the method in any one of claims 1 to 14 or 15 to 26.

55. A computer readable storage medium is used to store a computer program, when the computer program is run by a device, so that the device executes the method in any one of claims 1 to 14 or 15 to 26.

56. A computer program product includes computer program instructions, which make a computer execute the method in any one of claims 1 to 14 or 15 to 26.

57. A computer program makes a computer execute the method in any one of claims 1 to 14 or 15 to 26.

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