Method and apparatus used in node for wireless communication and artificial intelligence

Abstract

Disclosed in the present application are a method and apparatus used in a node for wireless communication and artificial intelligence. The method comprises: a first node receiving a first information block, which indicates a first resource block set; and sending a second information block, which indicates a first resource set from among the first resource block set, wherein the first resource set is used for dynamic scheduling. The first resource block set is determined on the basis of an AI / ML model; the first resource block set comprises K1 resource blocks, wherein K1 is a positive integer greater than 1, and time-domain resources occupied by at least two of the K1 resource blocks are orthogonal to each other; and the first resource block set depends on an ID of the AI / ML model. The present application realizes dynamic scheduling transmission triggered by a UE, improves the adaptability and intelligence level of a communication system, and supports a more flexible scheduling mechanism, thereby improving the performance, efficiency and user experience of the communication system.

Description

A method and apparatus in a node for wireless communication and artificial intelligence TECHNICAL FIELD

[0001] The present application relates to a signal transmission method and device in a wireless communication system, and in particular to a method and device for scheduling transmission. BACKGROUND

[0002] Using AI / ML (Artificial Intelligence / Machine Learning) technology to improve the performance of 5G networks is an important part of realizing the deep integration of 5G and AI / ML and building intelligent 5G-Advanced (5.5G) networks. The 3GPP (3rd Generation Partnership Project) standard organization has started to study the standardization of intelligent RAN (Radio Access Networks) since Rel-16 (Release-16), mainly focusing on intelligent use cases, data collection enhancement, potential impact on RAN nodes and interfaces, etc. In Rel-18, the establishment of AI / ML-based 5G air interface enhancement has officially begun the international standardization work of the integration of 5G air interface and AI / ML, mainly focusing on use cases, life cycle management (LCM), simulation verification, data collection, etc.

[0003] At present, the development of AI / ML has entered the stage of large models. Communication large models can realize autonomous networks and intelligent services, support network operation optimization, and improve network efficiency. The deep integration of communication and AI is an important direction for future communication evolution. AI will empower the development and upgrading of 5G, 5.5G, and 6G, bringing new management modes such as automatic management of frequency bands and traffic, real-time analysis of user data and network load, and prediction of network status. SUMMARY

[0004] In NR (New Radio), the scheduling mechanism is an important part of resource allocation. The base station scheduler decides which UEs (User Equipment) occupy which resources to transmit and receive data in each scheduling period. The UE will only transmit and receive data after receiving the valid scheduling grant from the base station. The scheduling mechanism is usually divided into two categories: dynamic scheduling and non-dynamic scheduling. Dynamic scheduling is a method in which the base station dynamically allocates resources based on the current network load, channel conditions and user demand through DCI (Downlink Control Information) to adapt to the rapid changes in traffic demand and wireless channel quality. The inventors have found that in future wireless communication systems, especially after the introduction of AI / ML, the existing air interface resource allocation mode will be more flexible, and the corresponding scheduling mechanism will also be more flexible. Therefore, there is further optimization space for the existing scheduling mechanism.

[0005] To solve the above problems, a solution is disclosed in the present application. It should be noted that in the description of the above problems, NR system is taken as an example, and the present application is also applicable to scenarios such as future 6G system, and achieves similar technical effects as NR system. Further, although the original intention of the present application is for AI / ML scenarios, the present application can also be applied to other non-AI / ML scenarios. Further, a unified design scheme for different scenarios (such as other non-AI / ML scenarios, including but not limited to Vehicle to Everything (V2X), capacity enhancement system, near distance communication system, NTN (Non Terrestrial Network), IoT (Internet of Things), URLLC (Ultra Reliable Low Latency Communication) network, etc.) can also help to reduce hardware complexity and cost. In the case of no conflict, the embodiments in any node of the present application and the features in the embodiments can be applied to any other node. In the case of no conflict, the embodiments of the present application and the features in the embodiments can be arbitrarily combined with each other.

[0006] In particular, the explanation of the terminology, nouns, functions, and variables in the present application (if not specifically stated) can refer to the definitions in TS38 series, TS37 series in the technical standards (TS) of 3GPP (the 3rd Generation Partnership Project). If necessary, TS38.211, TS38.212, TS38.213, TS38.214, TS38.215, TS38.300, TS38.304, TS38.305, TS38.321, TS38.331, TS37.355, TS38.423 in the 3GPP technical standards can be referred to for the understanding of the present application.

[0007] As an embodiment, the explanation of the terminology in the present application refers to the definitions in the specification agreement TS38 series of 3GPP.

[0008] As an embodiment, the explanation of the terminology in the present application refers to the definitions in the specification agreement TS37 series of 3GPP.

[0009] As an embodiment, the explanation of the terminology in the present application refers to the definitions in the specification agreement Rel-17 version of 3GPP.

[0010] As an embodiment, the explanation of the terminology in the present application refers to the definitions in the specification agreement Rel-18 version of 3GPP.

[0011] The present application discloses a method for a first node in wireless communication and artificial intelligence, comprising:

[0012] receiving a first information block, the first information block indicating a first resource block set;

[0013] sending a second information block, the second information block indicating a first resource set from the first resource block set, the first resource set being for dynamic scheduling;

[0014] wherein the first resource block set is determined based on an AI / ML model; the first resource block set includes K1 resource blocks, K1 is a positive integer greater than 1, at least two of the K1 resource blocks occupy orthogonal time domain resources; the first resource block set depends on the ID of the AI / ML model.

[0015] As an embodiment, the problem to be solved by the present application includes the implementation of the dynamic scheduling transmission mechanism triggered by the UE.

[0016] As an embodiment, the problem to be solved by the present application includes: configuration and indication of UE triggered dynamic scheduling resource.

[0017] As an embodiment, the features of the above method include: in the present application, the base station configures a first resource block set for UE triggered dynamic scheduling through a first information block, and the first node triggers uplink or downlink transmission of dynamic scheduling by sending a second information block, wherein the resources occupied by the uplink transmission and the downlink belong to the first resource block set.

[0018] As an embodiment, the features of the above method include: the first resource block set is determined by an AI entity based on AI / ML model prediction or inference, and the AI entity is located at the network side, interacts with the network device, or is located inside the network device.

[0019] As an embodiment, the features of the above method include: the present application supports the configuration of a first resource block set common to a UE group.

[0020] As an embodiment, the features of the above method include: the ID of the AI / ML model includes an AI / ML model ID.

[0021] As an embodiment, the features of the above method include: the ID of the AI / ML model includes a functionality ID corresponding to the AI / ML model.

[0022] As an embodiment, the benefits of the above method include: the present application supports the deep integration of AI and communication, improves the adaptability and intelligent level of the communication system, and further improves the performance, efficiency and user experience of the communication system.

[0023] As an embodiment, the benefits of the above method include: the UE performs dynamic scheduling in preconfigured resources, which not only reduces the complexity of implementing UE triggered dynamic scheduling, but also reduces the interference of signal transmission and ensures the robustness of signal transmission.

[0024] As an embodiment, the benefits of the above method include: ensuring the stability of resource allocation, and the network can flexibly cope with changes in load traffic.

[0025] According to one aspect of the present application, the features of the above method are that the K1 resource blocks included in the first resource block set are idle.

[0026] As an embodiment, the features of the above method include: the first node does not initiate random access in the K1 resource blocks.

[0027] As an embodiment, the features of the above method include: the first node does not monitor PDCCH in the K1 resource blocks.

[0028] As an embodiment, the method has the feature that the K1 resource blocks are reserved for the first node to perform UE-triggered dynamic scheduling.

[0029] As an embodiment, the method has the benefit of reducing the probability of signal transmission collision between the base station and the terminal, and reducing interference caused by signal transmission collision.

[0030] As an embodiment, the method has the benefit that pre-configuring a resource set for UE-triggered dynamic scheduling can reduce system complexity and facilitate network management and coordination of terminal signal transmission in the cell.

[0031] According to an aspect of the present application, the method has the feature that it comprises:

[0032] receiving a first sequence;

[0033] receiving a first signal in the first resource set, or transmitting a first signal in the first resource set;

[0034] wherein the first sequence confirms the second information block, and the second information block schedules the first signal.

[0035] As an embodiment, the method has the feature that the first sequence is feedback of the second node to the second information block in the present application.

[0036] As an embodiment, the method has the feature that whether the first node cancels transmission of the first signal depends on whether the first node receives the first sequence.

[0037] As an embodiment, the method has the feature that the first sequence carries at least one bit of information, and the at least one bit of information is used to confirm transmission of the first signal, or the at least one bit of information is used to cancel transmission of the first signal.

[0038] As an embodiment, the method has the feature that the second information block indicates that the first node receives a first signal in the first resource set, or the first node transmits a first signal in the first resource set.

[0039] As an embodiment, the method has the benefit of introducing a scheduling confirmation mechanism to achieve multiplexing of the first resource block set while ensuring reliable signal transmission.

[0040] As an embodiment, the method has the benefit that the first node will only perform data transmission after receiving feedback confirming the second information block, which is conducive to reducing interference between different UEs.

[0041] According to an aspect of the present application, the above method is characterized in comprising:

[0042] receiving the first signaling and receiving the first signal in the first resource subset;

[0043] wherein the first signaling depends on the second information block; the first signaling indicates the first resource subset from the first resource set, and the second information block and the first signaling jointly indicate the first signal.

[0044] As an embodiment, the above method is characterized in that the first signaling is physical layer control signaling.

[0045] As an embodiment, the above method is characterized in that the first signaling carries partial scheduling information of the first signal.

[0046] As an embodiment, the above method is characterized in that the second information block and the first signaling are used jointly to indicate the first resource subset from the first resource block set.

[0047] As an embodiment, the above method is characterized in that it has small changes to standards and good compatibility.

[0048] As an embodiment, the above method is characterized in that it has low requirements for terminals, thereby reducing terminal cost and facilitating deployment and implementation of communication networks.

[0049] As an embodiment, the above method is characterized in that it supports more flexible scheduling mode, and joint indication of transmission signal resources by terminals and base stations is conducive to reducing latency and improving system performance.

[0050] According to an aspect of the present application, the above method is characterized in comprising:

[0051] sending the first signal in the second resource subset;

[0052] wherein the first resource set comprises a plurality of resource subsets, and the second resource subset is one of the plurality of resource subsets.

[0053] As an embodiment, the above method is characterized in that the second information block informs the second node in the present application to receive the first signal.

[0054] As an embodiment, the above method is characterized in that the first resource block set is common to a cell or common to a UE group.

[0055] As an embodiment, the above method is characterized in that the plurality of resource subsets are nested.

[0056] As an embodiment, the above method has the benefit of dynamically sharing resources to improve resource utilization.

[0057] As an embodiment, the above method has the benefit of avoiding additional signaling indication to improve spectrum efficiency and save signaling overhead.

[0058] According to an aspect of the present application, the above method is characterized in that the K1 resource blocks are orthogonal in the time domain, and the second information block is used to indicate K1 resource subsets from the K1 resource blocks, and the first resource set includes the K1 resource subsets.

[0059] As an embodiment, the above method has the benefit of the K1 resource subsets belonging to the K1 resource blocks respectively, and the K1 resource subsets being orthogonal in the time domain.

[0060] As an embodiment, the above method has the benefit of the second information block implicitly indicating the time domain resources of the first resource block set.

[0061] As an embodiment, the above method has the benefit of the first node repeatedly transmitting uplink signals in the K1 resource subsets.

[0062] As an embodiment, the above method has the benefit of the signals transmitted in the multiple resource subsets being generated based on the same transmission block.

[0063] As an embodiment, the above method has the benefit of uplink repetition transmission enabling greater uplink coverage and better transmission performance.

[0064] As an embodiment, the above method has the benefit of reducing code rate by allocating more transmission resources for data packets, thereby improving transmission reliability.

[0065] As an embodiment, the above method has the benefit of obtaining higher coding gain and improving coverage performance.

[0066] According to an aspect of the present application, the above method is characterized in that the ID of the AI / ML model relied on by the first resource block set is updated, and the first resource block set is reset.

[0067] As an embodiment, the method has the feature that the ID of the AI / ML model is used to identify an AI / ML model, however, the AI / ML model identified by the ID of the AI / ML model can be logical, and the mapping relationship from the logical AI / ML model to the physical AI / ML model is usually implemented by the device manufacturer itself, so the ID of the AI / ML model can not be globally unique, and the same physical AI / ML model can correspond to different IDs of the AI / ML model, and the updating of the ID of the AI / ML model in this application includes changes in the logical AI / ML model on which the first resource block set depends and / or changes in the physical AI / ML model to which the ID of the AI / ML model on which the first resource block set depends is mapped.

[0068] As an embodiment, the method has the feature that in the LCM, the AI / ML model can improve the inference performance through retraining or adjustment, and the ID of the AI / ML model corresponding to the same AI / ML model at different nodes of the LCM can be different, so after the ID of the AI / ML model is updated, the result of the AI / ML model inference can change, and resetting the first resource block set is beneficial to improving the system performance.

[0069] As an embodiment, the method has the feature that the network or the terminal can monitor the performance of an AI / ML model inference, and when the performance of an AI / ML model decreases to an unacceptable level, the network or the base station can indicate or configure the switching or reselection of the AI / ML model in the current function or function group through signaling, and the ID of the corresponding AI / ML model is also updated, and resetting the first resource block set can avoid the decrease in system performance caused by the decrease in AI / ML model inference.

[0070] As an embodiment, the method has the benefit of promoting the deep integration of AI and communication, and realizing network intelligence and automation.

[0071] As an embodiment, the method has the benefit of improving the inference performance of the AI / ML model, and thus improving the system performance, which is beneficial to network maintenance.

[0072] As an embodiment, the method has the benefit of being conducive to adapting to rapidly changing channel environments and ensuring signal transmission quality.

[0073] According to an aspect of the application, the method has the feature that the first information block includes a set of configuration parameters for the first resource block set, and the set of configuration parameters includes at least one of a power parameter or a spatial parameter.

[0074] As an embodiment, the method has the feature that the set of configuration parameters of the first set of resource blocks included in the first information block is for a signal transmitted in the first set of resource blocks.

[0075] As an embodiment, the method has the feature that the power parameter includes a transmission power or a maximum transmission power used by a signal transmitted in the first set of resource blocks.

[0076] As an embodiment, the method has the feature that the spatial parameter includes a spatial relation used by a signal transmitted in the first set of resource blocks.

[0077] As an embodiment, the method has the benefit that configuring slowly changing parameters in signal transmission through higher layer signaling can reduce the overhead of dynamic signaling and save spectrum efficiency.

[0078] As an embodiment, the method has the benefit of reducing the complexity of the system, easy to deploy and implement.

[0079] As an embodiment, the method has the benefit of requiring simplicity for UEs and reducing costs.

[0080] According to an aspect of the present application, the method has the feature that the set of configuration parameters includes a predicted idle probability for a resource block in the first set of resource blocks.

[0081] As an embodiment, the method has the feature that the predicted idle probability for a resource block in the first set of resource blocks includes a probability of the first node generating data in the first set of resource blocks.

[0082] As an embodiment, the method has the feature that the first node predicts the probability of the first node transmitting a signal in the first set of resource blocks in advance based on massive data through an AI / ML model to predict user data transmission, cell load and network status.

[0083] As an embodiment, the method has the feature that the first node schedules and transmits signals according to channel priority based on the predicted idle probability.

[0084] As an embodiment, the method has the benefit of realizing autonomous network and intelligent service, supporting network operation optimization, and improving network efficiency.

[0085] As an embodiment, the method has the benefit of predicting the time of signal transmission of the first node in advance and optimizing resource allocation based on prediction to further reduce the latency of signal transmission.

[0086] As an embodiment, the above method has the benefits of reducing the probability of signal collision, and ensuring reliable transmission of signals.

[0087] According to an aspect of the present application, the above method is characterized in that the first node is a user equipment.

[0088] According to an aspect of the present application, the above method is characterized in that the first node is a terminal.

[0089] The present application discloses a method in a second node for wireless communication and artificial intelligence, comprising:

[0090] sending a first information block, the first information block indicating a first resource block set;

[0091] receiving a second information block, the second information block indicating a first resource set from the first resource block set, the first resource set being dynamically scheduled;

[0092] wherein the first resource block set is determined based on an AI / ML model; the first resource block set includes K1 resource blocks, K1 being a positive integer greater than 1, at least two of the K1 resource blocks occupying time domain resources that are orthogonal; the K1 resource blocks included in the first resource block set are idle; the first resource block set depends on the ID of the AI / ML model.

[0093] According to an aspect of the present application, the above method is characterized in that the K1 resource blocks included in the first resource block set are idle.

[0094] As an embodiment, the above method has the features of: the second node does not dynamically schedule the first node in the K1 resource blocks.

[0095] As an embodiment, the above method has the features of: the second node does not dynamically schedule nodes other than the first node within the cell in the K1 resource blocks.

[0096] According to an aspect of the present application, the above method is characterized in that it comprises:

[0097] sending a first sequence;

[0098] sending a first signal in the first resource set, or receiving a first signal in the first resource set;

[0099] wherein the first sequence confirms the second information block, and the second information block schedules the first signal.

[0100] According to an aspect of the present application, the above method is characterized in that it comprises:

[0101] transmitting the first signaling and transmitting the first signal in the first resource subset;

[0102] wherein the first signaling depends on the second information block; the first signaling indicates the first resource subset from the first resource set, and the second information block and the first signaling jointly indicate the first signal.

[0103] According to an aspect of the present application, the above method is characterized in that it comprises:

[0104] receiving the first signal in the second resource subset;

[0105] wherein the first resource set comprises a plurality of resource subsets, and the second resource subset is one of the plurality of resource subsets.

[0106] As an embodiment, the above method is characterized in that it comprises: the second node blindly detects the first signal in the first resource set.

[0107] As an embodiment, the above method is characterized in that it comprises: the second node determines the second resource subset based on the second information block and a predefined configuration, and receives the first signal in the second resource subset.

[0108] As an embodiment, the above method is characterized in that it comprises: the second node determines the sender of the first signal based on the second resource subset.

[0109] As an embodiment, the above method is characterized in that it comprises: improving resource utilization.

[0110] According to an aspect of the present application, the above method is characterized in that the K1 resource blocks are orthogonal in the time domain, the second information block is used to indicate K1 resource subsets from the K1 resource blocks, and the first resource set comprises the K1 resource subsets.

[0111] As an embodiment, the above method is characterized in that it comprises: the second node repeatedly transmits the downlink signal in the K1 resource subsets.

[0112] As an embodiment, the above method is characterized in that it comprises: repeated transmission can achieve greater uplink coverage and better transmission performance.

[0113] As an embodiment, the above method is characterized in that it comprises: improving resource utilization and further improving system performance.

[0114] As an embodiment, the above method is characterized in that it comprises: by allocating more transmission resources for data packets, the code rate is reduced, thereby improving transmission reliability.

[0115] According to an aspect of the present application, the above method is characterized in that the ID of the AI / ML model relied on by the first resource block set is updated, and the first resource block set is reset.

[0116] According to an aspect of the present application, the above method is characterized in that the first information block includes a set of configuration parameters for the first resource block set, and the set of configuration parameters includes at least one of a power parameter or a spatial parameter.

[0117] According to an aspect of the present application, the above method is characterized in that the set of configuration parameters includes a predicted idle probability of a resource block in the first resource block set.

[0118] As an embodiment, the above method is characterized in that the second node obtains, based on prediction, an idle probability of a resource block in the first resource block set, and configures the idle probability to the first node through the first information block.

[0119] As an embodiment, the above method is characterized in that the second node obtains, based on prediction, a probability of the first node transmitting data in the first resource block set, and configures the probability to the first node through the first information block.

[0120] According to an aspect of the present application, the above method is characterized in that the second node is a base station.

[0121] The present application discloses a device for a first node in wireless communication and artificial intelligence, comprising:

[0122] A first receiver receives a first information block, and the first information block indicates a first resource block set;

[0123] A first transmitter transmits a second information block, and the second information block indicates a first resource set from the first resource block set, and the first resource set is for dynamic scheduling.

[0124] The first resource block set is determined based on an AI / ML model; the first resource block set includes K1 resource blocks, K1 is a positive integer greater than 1, at least two resource blocks in the K1 resource blocks occupy orthogonal time domain resources; the first resource block set relies on the ID of the AI / ML model.

[0125] The present application discloses a device for a second node in wireless communication and artificial intelligence, comprising:

[0126] A second transmitter transmits a first information block, and the first information block indicates a first resource block set;

[0127] a second receiver configured to receive a second information block, the second information block indicating a first resource set from the first set of resource blocks, the first resource set being for dynamic scheduling;

[0128] wherein the first set of resource blocks is determined based on an AI / ML model; the first set of resource blocks comprises K1 resource blocks, the K1 being a positive integer greater than 1, at least two of the K1 resource blocks occupying time domain resources that are orthogonal; the first set of resource blocks depends on an ID of the AI / ML model.

[0129] As an embodiment, compared with the conventional scheme, the present application has the following advantages which are not limited to:

[0130] improve the adaptability and intelligence level of the communication system, and further improve the performance, efficiency and user experience of the communication system;

[0131] reduce the complexity of implementing UE-triggered dynamic scheduling, reduce the interference of signal transmission, and ensure the robustness of signal transmission;

[0132] The present application supports multiple terminal-triggered dynamic scheduling models, which can be flexibly applied to different terminals and reduces the requirements for terminal capabilities. BRIEF DESCRIPTION OF DRAWINGS

[0133] Other features, objects and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments with reference to the attached drawings:

[0134] Fig. 1 shows a flowchart of transmission by a first node according to an embodiment of the present application;

[0135] Fig. 2 shows a schematic diagram of a network architecture according to an embodiment of the present application;

[0136] Fig. 3 shows a schematic diagram of an embodiment of a radio protocol architecture for the user plane and control plane according to an embodiment of the present application;

[0137] Fig. 4 shows a schematic diagram of a first communication device and a second communication device according to an embodiment of the present application;

[0138] Fig. 5 shows a first flowchart of transmission between a first node and a second node according to an embodiment of the present application;

[0139] Fig. 6 shows a second flowchart of transmission between a first node and a second node according to an embodiment of the present application;

[0140] Fig. 7 shows a third flowchart of transmission between a first node and a second node according to an embodiment of the present application;

[0141] Figure 8 shows a fourth flow diagram of transmissions between a first node and a second node according to an embodiment of the present application;

[0142] Figure 9 shows a diagram of K1 resource blocks included in a first resource block set according to an embodiment of the present application;

[0143] Figure 10 shows a diagram of a first resource set including multiple resource subsets according to an embodiment of the present application;

[0144] Figure 11 shows a diagram of a set of configuration parameters for a first resource block set according to an embodiment of the present application;

[0145] Figure 12 shows a diagram of RAN domain AI / ML function deployment according to an embodiment of the present application;

[0146] Figure 13 shows a diagram of AI / ML function deployment for a UE according to an embodiment of the present application;

[0147] Figure 14 shows a diagram of an artificial intelligence or machine learning based processing system according to an embodiment of the present application;

[0148] Figure 15 shows a diagram of artificial intelligence or machine learning according to an embodiment of the present application;

[0149] Figure 16 shows a structural block diagram of a processing apparatus for use in a first node according to an embodiment of the present application;

[0150] Figure 17 shows a structural block diagram of a processing apparatus for use in a second node according to an embodiment of the present application. DETAILED DESCRIPTION

[0151] The technical solutions of the present application will be further described in detail below with reference to the accompanying drawings. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other arbitrarily without conflict. Based on performance, flexibility, complexity, overhead and compatibility, etc., the person skilled in the art has the motivation to flexibly combine the embodiments in different drawings without conflict, including but not limited to the embodiments in Figure 1 and the embodiments in Figures 5-17, the embodiments in Figure 5 and the embodiments in Figures 6-17, etc.

[0152] Embodiment 1

[0153] Embodiment 1 illustrates a flow diagram of transmissions by a first node according to an embodiment of the present application, as shown in Figure 1. In Figure 1, each block represents a step. In particular, the order of steps in the blocks does not represent a specific time sequence between the steps.

[0154] The first node receives a first information block in step 101, the first information block indicating a first resource block set; and transmits a second information block in step 102, the second information block indicating a first resource set from the first resource block set, the first resource set being for dynamic scheduling.

[0155] In embodiment 1, the first resource block set is determined based on an AI / ML model; the first resource block set includes K1 resource blocks, the K1 being a positive integer greater than 1, at least two of the K1 resource blocks occupying time domain resources that are orthogonal; and the first resource block set depends on an ID of the AI / ML model.

[0156] As an example, the AI / ML refers to Artificial Intelligence / Machine Learning.

[0157] As an example, the AI / ML includes Machine Learning.

[0158] As an example, the AI / ML includes Deep Learning.

[0159] As an example, the ID refers to IDentify.

[0160] As an example, the ID refers to IDentification.

[0161] As an example, the ID refers to IDentity.

[0162] As an example, the ID refers to IDentifier.

[0163] As an example, the ID refers to InDex.

[0164] As an example, the ID includes Model ID.

[0165] As an example, the ID includes Functionality ID.

[0166] As an example, the first node is the first node in the present application.

[0167] As an example, the first node receives the first information block.

[0168] As one embodiment, the first information block is transmitted by higher layer signaling.

[0169] As one embodiment, the first information block is transmitted by RRC (Radio Resource Control) signaling.

[0170] As one embodiment, the first information block is carried by RRC signaling.

[0171] As one embodiment, the first information block includes one or more RRC IEs (Information Elements).

[0172] As one embodiment, the first information block includes one or more fields in one RRC IE.

[0173] As one embodiment, the first information block includes one or more fields in each of a plurality of RRC IEs.

[0174] As one embodiment, the first information block includes one or more fields in a ServingCellConfig IE.

[0175] As one embodiment, the first information block includes one or more fields in a BWP-UplinkDedicated IE.

[0176] As one embodiment, the first information block includes one or more fields in a PUSCH-Config IE.

[0177] As one embodiment, the first information block includes one or more fields in a PUCCH-Config IE.

[0178] As one embodiment, the first information block includes one or more fields in a PreGrantConfig IE.

[0179] As one embodiment, the first information block includes one or more fields in a PreGrantConfig IE.

[0180] As one embodiment, the first information block includes one or more fields in a BWP-DownlinkDedicated IE.

[0181] As one embodiment, the first information block includes one or more fields in a PDSCH-Config IE.

[0182] As one embodiment, the first information block includes one or more fields in a UE Scheduling PDSCH-Config IE.

[0183] As one embodiment, the first information block is transmitted via Medium Access Control (MAC) layer signaling.

[0184] As one embodiment, the first information block is transmitted via a MAC Control Element (CE).

[0185] As one embodiment, a name of the signaling carrying the first information block includes AI.

[0186] As one embodiment, a name of the signaling carrying the first information block includes ML.

[0187] As one embodiment, a name of the signaling carrying the first information block includes AIorML.

[0188] As one embodiment, a name of the signaling carrying the first information block includes Prediction.

[0189] As one embodiment, a name of the signaling carrying the first information block includes Predicted.

[0190] As one embodiment, a name of the signaling carrying the first information block includes Inference.

[0191] As one embodiment, a name of the signaling carrying the first information block includes Resource.

[0192] As one embodiment, a name of the signaling carrying the first information block includes Pool.

[0193] As one embodiment, a name of the signaling carrying the first information block includes Pre.

[0194] As one embodiment, a name of the signaling carrying the first information block includes Grant.

[0195] As one embodiment, a name of the signaling carrying the first information block includes UEScheduling.

[0196] As one embodiment, the first information block is UE dedicated.

[0197] As one embodiment, the first information block is UE-group dedicated, the UE-group including the first node.

[0198] As one embodiment, the first resource block set includes K1 resource blocks, the K1 being a positive integer greater than 1.

[0199] As one embodiment, the first resource block set is UE dedicated.

[0200] As one embodiment, the first resource block set is UE-group dedicated.

[0201] As one embodiment, the resources occupied in the first resource block set are only for uplink transmission.

[0202] As one embodiment, the resources occupied in the first resource block set are only for downlink transmission.

[0203] As one embodiment, the first resource block set includes both uplink transmission resources and downlink transmission resources.

[0204] As one embodiment, the first resource block set includes resources that can be used for both uplink transmission and downlink transmission.

[0205] As one embodiment, the first resource block set occupies contiguous frequency domain resources.

[0206] As one embodiment, the first resource block set occupies non-contiguous frequency domain resources.

[0207] As one embodiment, the first resource block set occupies contiguous time domain resources.

[0208] As one embodiment, the first resource block set is periodically configured.

[0209] As one embodiment, the time domain resources occupied by the first resource block set are periodic.

[0210] As one embodiment, any of the K1 resource blocks occupies contiguous time domain resources.

[0211] As one embodiment, any of the K1 resource blocks occupies contiguous frequency domain resources.

[0212] As one embodiment, any of the K1 resource blocks is a time-frequency resource block.

[0213] As one sub-embodiment of this embodiment, the time-frequency resource block occupies one or more subframes in time domain.

[0214] As one sub-embodying of the embodiment, the time-frequency resource block occupies one or more slots in time domain.

[0215] As one sub-embodying of the embodiment, the time-frequency resource block occupies one or more time domain symbols in time domain.

[0216] As one sub-embodying of the embodiment, the time-frequency resource block occupies one or more subbands in frequency domain.

[0217] As one sub-embodying of the embodiment, the time-frequency resource block occupies one or more RBs in frequency domain.

[0218] As one sub-embodying of the embodiment, the time-frequency resource block occupies multiple continuous subcarriers in frequency domain.

[0219] As one sub-embodying of the embodiment, the time-frequency resource block occupies one or more REs.

[0220] As one sub-embodying of the embodiment, the time-frequency resource block corresponds to one spatial Tx parameter.

[0221] As one sub-embodying of the embodiment, the time-frequency resource block corresponds to one spatial Rx parameter.

[0222] As one sub-embodying of the embodiment, the time-frequency resource block corresponds to one TCI state.

[0223] As one sub-embodying of the embodiment, the time-frequency resource block corresponds to one CSI-RS resource.

[0224] As one sub-embodying of the embodiment, the time-frequency resource block corresponds to one SSB.

[0225] As one sub-embodying of the embodiment, the time-frequency resource block corresponds to multiple spatial Tx parameters.

[0226] As one sub-embodying of the embodiment, the time-frequency resource block corresponds to multiple spatial Rx parameters.

[0227] As one sub-example of the embodiment, the time-frequency resource block corresponds to multiple TCI States.

[0228] As one sub-example of the embodiment, the time-frequency resource block corresponds to multiple CSI-RS resources.

[0229] As one sub-example of the embodiment, the time-frequency resource block corresponds to multiple SSBs.

[0230] As one sub-example of the embodiment, the time-frequency resource block corresponds to one maximum transmission power value.

[0231] As one sub-example of the embodiment, the time-frequency resource block corresponds to one transmission type, which is at least one of Down Link (DL), Up Link (UL), Flexible, SBFD (SubBand non-overlapping Full Duplex), or Full Duplex.

[0232] As one embodiment, the K1 resource blocks included in the first resource block set respectively occupy K1 time slots in time domain and respectively occupy K1 subbands in frequency domain.

[0233] As one embodiment, the K1 resource blocks included in the first resource block set respectively occupy K1 sets of multi-carrier symbols in time domain and respectively occupy K1 RB sets in frequency domain.

[0234] As one embodiment, any resource block in the K1 resource blocks occupies one time slot in time domain and occupies one subband in frequency domain.

[0235] As one embodiment, any resource block in the K1 resource blocks occupies one time domain symbol in time domain and occupies one RB set in frequency domain.

[0236] As one embodiment, one time slot in the present application includes 14 time domain symbols.

[0237] As one embodiment, one RB in the present application includes 12 continuous subcarriers.

[0238] As one embodiment, one RB in the present application refers to a PRB (Physical Resource Block).

[0239] As one embodiment, one RE in the present application includes one time domain symbol in time domain and one subcarrier in frequency domain.

[0240] As an embodiment, the number of RBs included in one RB set in the present application is configured by a higher layer parameter.

[0241] As an embodiment, one RB set in the present application includes a group of consecutive RBs.

[0242] As an embodiment, there is a guard band between two adjacent RB sets.

[0243] As an embodiment, the time domain resources occupied by at least two resource blocks in the K1 resource blocks are orthogonal.

[0244] As an embodiment, at least two resource blocks in the K1 resource blocks do not overlap in time domain.

[0245] As an embodiment, two resource blocks in the K1 resource blocks occupy overlapping time domain resources.

[0246] As an embodiment, two resource blocks in the K1 resource blocks occupy the same time domain resources.

[0247] As an embodiment, the time domain resources occupied by any two resource blocks in the K1 resource blocks are orthogonal.

[0248] As an embodiment, the time domain resources occupied by any two resource blocks in the K1 resource blocks do not overlap.

[0249] As an embodiment, the time domain resources occupied by the K1 resource blocks are orthogonal.

[0250] As an embodiment, the time domain resources occupied by the K1 resource blocks do not overlap.

[0251] As an embodiment, the meaning that the K1 resource blocks are idle includes that the second node in the present application does not perform Configured Grant (CG) transmission in the K1 resource blocks.

[0252] As an embodiment, the meaning that the K1 resource blocks are idle includes that the second node in the present application does not perform Semi-Persistent Scheduling (SPS) in the K1 resource blocks.

[0253] As an embodiment, the meaning that the K1 resource blocks are idle includes that the second node in the present application does not perform dynamic scheduling in the K1 resource blocks.

[0254] As one embodiment, the K1 resource blocks being free means that the first node does not initiate random access in the K1 resource blocks.

[0255] As one embodiment, the K1 resource blocks being free means that the first node does not monitor PDCCH (Physical Downlink Control CHannel) in the K1 resource blocks.

[0256] As one embodiment, the K1 resource blocks being free means that the K1 resource blocks are reserved for terminal-triggered scheduling.

[0257] As one embodiment, the K1 resource blocks being free means that the K1 resource blocks can or are allowed or are able to be used for UE-triggered scheduling.

[0258] As one embodiment, the K1 resource blocks being free means that the K1 resource blocks are reserved for first-node-triggered scheduling.

[0259] As one embodiment, the K1 resource blocks being free means that the K1 resource blocks can or are allowed or are able to be used for first-node-triggered scheduling.

[0260] As one embodiment, the K1 resource blocks being free means that the K1 resource blocks are reserved for UE-group-triggered scheduling, the UE group including the first node.

[0261] As one embodiment, the K1 resource blocks being free means that the K1 resource blocks can or are allowed or are able to be used for UE-group-triggered scheduling, the UE group including the first node.

[0262] As one embodiment, the first information block indicates the first resource block set.

[0263] As one embodiment, the first information block explicitly indicates the first resource block set.

[0264] As one embodiment, the first information block explicitly indicates time domain resources occupied by the first resource block set.

[0265] As one embodiment, the first resource block set occupies time domain resources in a period, and the first information block explicitly indicates a period and a period offset value of the time domain resources occupied by the first resource block set.

[0266] As one embodiment, the first information block explicitly indicates a duration of time domain resources occupied by the first set of resource blocks.

[0267] As one embodiment, the first information block explicitly indicates a duration of time domain resources occupied by the first set of resource blocks.

[0268] As one embodiment, the first information block explicitly indicates a pattern in time domain of the first set of resource blocks.

[0269] As one embodiment, the first information block explicitly indicates a pattern in frequency domain of the first set of resource blocks.

[0270] As one embodiment, the first information block explicitly indicates a frequency domain resource occupied by the first set of resource blocks.

[0271] As one subembodiment of this embodiment, the explicit indication comprises explicitly indicating a starting frequency domain resource occupied by the first set of resource blocks.

[0272] As one subembodiment of this subembodiment, the occupied starting frequency domain resource refers to an occupied starting RE.

[0273] As one subembodiment of this subembodiment, the occupied starting frequency domain resource refers to an occupied starting PRB.

[0274] As one subembodiment of this subembodiment, the occupied starting frequency domain resource refers to an occupied starting RB set.

[0275] As one subembodiment of this subembodiment, the occupied starting frequency domain resource refers to an occupied starting subband.

[0276] As one subembodiment of this embodiment, the explicit indication comprises explicitly indicating a frequency domain bandwidth occupied by the first set of resource blocks.

[0277] As one subembodiment of this embodiment, the occupied frequency domain bandwidth refers to a number of REs.

[0278] As one subembodiment of this embodiment, the occupied refers to a number of PRBs.

[0279] As one subembodiment of this embodiment, the occupied refers to a number of RB sets.

[0280] As one subembodiment of this embodiment, the occupied refers to a number of subbands.

[0281] As one embodiment, the first information block comprises a bitmap indicating locations of time domain resources occupied by the first set of resource blocks.

[0282] As one embodiment, the first set of resource blocks comprises K1 resource blocks, and the bitmap comprised in the first information block indicates K1 locations of the K1 resource blocks in time domain.

[0283] As one sub-embodiment of the embodiment, the first information block comprises K1 first type information sub-blocks, which respectively indicate K1 frequency domain resources occupied by the K1 resource blocks.

[0284] As one sub-embodiment of the embodiment, the first information block comprises K1 second type information sub-blocks, which respectively indicate K1 spatial parameters corresponding to the K1 resource blocks.

[0285] As one sub-embodiment of the embodiment, the first information block comprises K1 third type information sub-blocks, which respectively indicate K1 idle probability values predicted for the K1 resource blocks.

[0286] As one embodiment, the first information block indirectly indicates the first set of resource blocks.

[0287] As one sub-embodiment of the embodiment, the indirect indication comprises indication by indicating other IE.

[0288] As one sub-embodiment of the embodiment, the indirect indication comprises indication by indicating a predefined table.

[0289] As one embodiment, the first information block explicitly indicates time-frequency resources occupied by the first set of resource blocks.

[0290] As one embodiment, the first information block configures the first set of resource blocks.

[0291] As one embodiment, the first node transmits the second information block, which indicates the first resource set from the first set of resource blocks.

[0292] As one embodiment, the second information block occupies a PUCCH (Physical Uplink Control CHannel).

[0293] As one embodiment, the second information block occupies a PUCCH resource.

[0294] As one embodiment, the second information block comprises UCI (Uplink Control Information).

[0295] As one embodiment, the second information block is UCI.

[0296] As one embodiment, the second information block comprises SR (Scheduling Request).

[0297] As one embodiment, the second information block comprises USI (Uplink Scheduling Indicator).

[0298] As one embodiment, the second information block comprises UCI, which is different from a type of UCI in Rel-18 (Release-18) and before.

[0299] As one sub-embodiment of this embodiment, the type of UCI in Rel-18 and before comprises at least SR, HARQ (Hybrid Automatic Repeat reQuest)-ACK (Acknowledgment) and CSI (Channel State Information).

[0300] As one embodiment, the second information block occupies resources in the first set of resource blocks.

[0301] As one embodiment, the time-frequency resources occupied by the second information block are orthogonal to the time-frequency resources occupied by the first set of resource blocks.

[0302] As one embodiment, the second information block occupies one of M1 sets of candidate uplink resources, and M1 is a positive integer greater than 1.

[0303] As one sub-embodiment of this embodiment, the M1 sets of candidate uplink resources are semi-statically configured.

[0304] As one sub-embodiment of this embodiment, the M1 sets of candidate uplink resources are pre-configured.

[0305] As one sub-embodiment of this embodiment, the M1 sets of candidate uplink resources are configured grant resources.

[0306] As a sub-embodiment of the embodiment, the M1 candidate uplink resource sets are configured by a ConfiguredGrantConfig IE.

[0307] As a sub-embodiment of the embodiment, the second node in the application blindly detects the second information block.

[0308] As a sub-embodiment of the embodiment, the second node in the application blindly detects the second information block by scrambling the CRC (Cyclic Redundancy Check) of the second information block.

[0309] As a sub-embodiment of the embodiment, the second node in the application blindly detects the second information block by scrambling the RNTI (Radio Network Temporary Identifier) carried by the CRC of the second information block.

[0310] As an embodiment, the second information block indicates the first resource set from the first resource block set.

[0311] As an embodiment, the second information block indicates the first resource set from a given resource block in the K1 resource blocks included in the first resource block set, and the first resource set occupies part or all of the resources in the given resource block.

[0312] As an embodiment, the second information block indicates the first resource set from a plurality of resource blocks in the K1 resource blocks included in the first resource block set, and the first resource set occupies part or all of the resources in the plurality of resource blocks.

[0313] As an embodiment, the second information block indicates the first resource set from each resource block in the K1 resource blocks included in the first resource block set, and the first resource set occupies part or all of the resources in each resource block.

[0314] As an embodiment, the first resource set is for dynamic scheduling.

[0315] As an embodiment, the meaning that the first resource set is for dynamic scheduling includes that the first resource block set is for dynamic scheduling, and the first resource set belongs to the first resource block set.

[0316] As an embodiment, the meaning that the first resource set is for dynamic scheduling includes that the second information block is for dynamic scheduling.

[0317] As an embodiment, the first set of resources is for dynamic scheduling in the sense that the second information block is dynamically scheduled.

[0318] As an embodiment, the first set of resources is for dynamic scheduling in the sense that the second information block is a grant for uplink data transmission or the second information block is a grant for downlink data transmission.

[0319] As an embodiment, the first set of resources is for dynamic scheduling in the sense that the indication of the first set of resources is dynamic.

[0320] As an embodiment, the first set of resources is for dynamic scheduling in the sense that the first set of resources is used for one transmission.

[0321] As an embodiment, the first set of resources is for dynamic scheduling in the sense that a wireless signal transmitted in the first set of resources is for one HARQ process.

[0322] As an embodiment, the first set of resources is for dynamic scheduling in the sense that a resource in the first set of resources is used for a dynamically scheduled signal transmission.

[0323] As an embodiment, the first set of resources is for dynamic scheduling in the sense that the first set of resources is for a UE triggered dynamically scheduled transmission.

[0324] As an embodiment, the first set of resources is for dynamic scheduling in the sense that a UE triggered dynamic scheduling occupies a resource in the first set of resources.

[0325] As an embodiment, the first set of resources is for dynamic scheduling in the sense that a signal sent or transmitted in the first set of resources requires dynamic scheduling.

[0326] As an embodiment, the first set of resources is for dynamic scheduling in the sense that a signal sent or received in the first set of resources is not a transmission and reception without dynamic scheduling.

[0327] As an embodiment, the first set of resource blocks is determined based on an AI / ML model.

[0328] As an embodiment, the first set of resource blocks is determined based on an AI / ML model in the sense that the first set of resource blocks is predicted.

[0329] As an embodiment, the first resource block set being determined based on an AI / ML model means that the first resource block set is obtained by inference of an AI / ML model.

[0330] As an embodiment, the first resource block set being determined based on an AI / ML model means that the first resource block set is obtained by prediction of an AI / ML model.

[0331] As an embodiment, the K1 resource blocks included in the first resource block set being idle is based on prediction.

[0332] As an embodiment, the second node in the present application determines that the K1 resource blocks are idle based on prediction.

[0333] As an embodiment, the first node determines that the K1 resource blocks are idle based on prediction.

[0334] As an embodiment, the K1 resource blocks being idle is determined according to an AI / ML model.

[0335] As an embodiment, the second node in the present application determines that the K1 resource blocks are idle based on an AI / ML model.

[0336] As an embodiment, the first node determines that the K1 resource blocks are idle based on an AI / ML model.

[0337] As an embodiment, the K1 resource blocks being idle is based on inference.

[0338] As an embodiment, the second node in the present application determines that the K1 resource blocks are idle based on inference.

[0339] As an embodiment, the first node determines that the K1 resource blocks are idle based on inference.

[0340] As an embodiment, the first resource block set is determined by an AI entity based on prediction or inference of an AI / ML model, the AI entity is located at a network side, interacts with a network device, or is located inside a network device.

[0341] As an embodiment, the first resource block set depends on an ID of the AI / ML model.

[0342] As an embodiment, the ID of the AI / ML model includes: AI / ML model ID.

[0343] As an embodiment, the ID of the AI / ML model comprises: a functionality ID corresponding to the AI / ML model.

[0344] As an embodiment, the AI / ML model identified by the AI / ML model ID described in the present application can be logical, and the mapping relationship from the logical AI / ML model to the physical AI / ML model is usually implemented by the device manufacturer; and the model ID corresponding to the same AI / ML model in different stages of the LCM can be different, that is, the model ID described in the present application can not be globally unique.

[0345] As an embodiment, the functionality described in the present application refers to an AI / ML-enabled feature or feature group (FG) enabled by configuration, wherein the configuration is supported according to the UE capability indication.

[0346] As an embodiment, the meaning that the first resource block set depends on the ID of the AI / ML model comprises: the first information block indicates the first resource block set while also indicating the ID of the AI / ML model.

[0347] As an embodiment, the meaning that the first resource block set depends on the ID of the AI / ML model comprises: the first resource block set is generated per AI / ML model.

[0348] As an embodiment, the meaning that the first resource block set depends on the ID of the AI / ML model comprises: the first resource block set is associated to an AI / ML model.

[0349] As an embodiment, the ID of the AI / ML model on which the first resource block set depends is updated, and the first resource block set is reset.

[0350] As an embodiment, the ID of the AI / ML model on which the first resource block set depends is updated, which comprises: the AI / ML model on which the first resource block set depends is updated.

[0351] As an embodiment, the ID of the AI / ML model on which the first resource block set depends is updated, which comprises: the AI / ML model on which the first resource block set depends is re-indicated.

[0352] As one embodiment, the ID of the AI / ML model on which the first set of resource blocks relies being updated comprises the AI / ML model on which the first set of resource blocks relies being reconfigured.

[0353] As one embodiment, the ID of the AI / ML model on which the first set of resource blocks relies being updated comprises the AI / ML model on which the first set of resource blocks relies being deactivated.

[0354] As one embodiment, the ID of the AI / ML model on which the first set of resource blocks relies being updated comprises the AI / ML model on which the first set of resource blocks relies being fallbacked.

[0355] As one embodiment, the ID of the AI / ML model on which the first set of resource blocks relies being updated comprises the ID of the AI / ML model on which the first set of resource blocks relies being reindicated.

[0356] As one embodiment, the ID of the AI / ML model on which the first set of resource blocks relies being updated comprises the AI / ML model on which the first set of resource blocks relies being reconfigured.

[0357] As one embodiment, the ID of the AI / ML model on which the first set of resource blocks relies being updated comprises the AI / ML model on which the first set of resource blocks relies being changed.

[0358] As one embodiment, the ID of the AI / ML model on which the first set of resource blocks relies being updated comprises the ID of the training dataset of the AI / ML model on which the first set of resource blocks relies being updated.

[0359] As one embodiment, the ID of the AI / ML model on which the first set of resource blocks relies being updated comprises the ID of the inference dataset of the AI / ML model on which the first set of resource blocks relies being updated.

[0360] As one embodiment, the ID of the AI / ML model on which the first set of resource blocks relies being updated comprises the corresponding functionality ID of the AI / ML model on which the first set of resource blocks relies being updated.

[0361] As one embodiment, the first set of resource blocks being reset comprises the first set of resource blocks being released.

[0362] As one embodiment, the first set of resource blocks being reset comprises the first set of resource blocks being released.

[0363] As one embodiment, the first set of resource blocks being reset comprises the first set of resource blocks being deactivated.

[0364] As one embodiment, the first set of resource blocks being reset comprises the first set of resource blocks being reconfigured.

[0365] As one embodiment, the first set of resource blocks being reset comprises the first set of resource blocks being previously configured no longer being in effect.

[0366] As one embodiment, the first set of resource blocks being reset comprises the grant in the first set of resource blocks being cleared.

[0367] As one embodiment, the first set of resource blocks being reset comprises the signal transmission in the first set of resource blocks being cancelled.

[0368] Embodiment 2

[0369] Embodiment 2 illustrates a schematic diagram of a network architecture according to one embodiment of the present application, as shown in FIG. 2.

[0370] FIG. 2 illustrates a network architecture 200. The network architecture 200 is a network architecture for LTE (Long-Term Evolution), LTE-A (Long-Term Evolution Advanced), 5G systems, 5G-Advanced, and future 6G systems. The network architecture for LTE, LTE-A, 5G systems, 5G-Advanced, and future 6G systems is referred to as EPS (Evolved Packet System). The 5G NR or LTE network architecture can be referred to as 5GS (5G System) / EPS or some other suitable terminology; the 6G network architecture can be referred to as 6GS (6G System) / EPS or some other suitable terminology. The network architecture 200 can include one or more UEs 201, a RAN (Next Generation Radio Access Network) 202, a core network 210, a HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and Internet services 230. The network architecture 200 can be interconnected with other access networks, but these entities / interfaces are not shown for simplicity. As shown in FIG. 2, the network architecture 200 provides packet-switched services, however, those skilled in the art will readily appreciate that the various concepts presented throughout this application are amenable to use with networked systems providing circuit-switched services. The RAN 202 includes Node Bs 203 and other nodes 204. The Node Bs 203 provide user and control plane protocol terminations toward the UEs 201. The Node Bs 203 can be connected to the other nodes 204 via an Xn interface (e.g., backhaul). The Node Bs 203 can also be referred to as base stations, base transceiver stations, radio base stations, radio transceivers, transceiver functions, basic service sets (BSSs), extended service sets (ESSs), TRPs (Transmitter Receiver Points), or some other suitable terminology. The Node Bs 203 provide access points to the core network 210 for the UEs 201; the core network 210 is a 5GC (5G Core Network) / EPC (Evolved Packet Core), or alternatively, the core network 210 is a 6GC.Examples of a UE 201 include a cellular phone, a smart phone, a Session Initiation Protocol (SIP) phone, a laptop, a personal digital assistant (PDA), a satellite radio, a global positioning system, a multimedia device, a video device, a digital audio player (e.g., MP3 player), a camera, a game console, a drone, a flying vehicle, a narrowband physical web device, a machine type communication device, a land transport vehicle, a car, a wearable device, or any other similar functional device. Those skilled in the art will also The node 203 is connected by an SI / NG interface to the core network 210. The core network 210 includes a MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MME / AMF / SMF 214, a S-GW (Service Gateway) / UPF (User Plane Function) 212, and a P-GW (Packet Data Network Gateway) / UPF 213. The MME / AMF / SMF 211 is the control node that processes the signaling between the UE 201 and the 5G-CN / EPC 210. The MME / AMF / SMF 211 generally provides bearer and connection management. All user Internet Protocol (IP) packets are transferred through the S-GW / UPF 212, which is itself connected to the P-GW / UPF 213. The P-GW provides UE IP address allocation as well as other functions. The P-GW / UPF 213 is connected to the Internet services 230. The Internet services 230 include operator- correspondent Internet Protocol services, which can specifically include the Internet, intranet, IMS (IP Multimedia Subsystem), and packet-switched services.

[0371] As one embodiment, the first node described in this application includes the UE 201.

[0372] As one embodiment, the second node described in the present application comprises the node 203.

[0373] As one embodiment, the node 203 is a macro cell base station.

[0374] As one embodiment, the node 203 is a micro cell base station.

[0375] As one embodiment, the node 203 is a pico cell base station.

[0376] As one embodiment, the node 203 is a femto cell.

[0377] As one embodiment, the node 203 is a base station device supporting large latency difference.

[0378] As one embodiment, the node 203 is a flying platform device.

[0379] As one embodiment, the node 203 is a satellite device.

[0380] As one embodiment, the node 203 is a test device (e.g. a transceiver simulating part of the functions of a base station, a signaling tester).

[0381] As one embodiment, the UE 201 comprises a mobile phone.

[0382] As one embodiment, the UE 201 comprises a vehicle, including a car.

[0383] As one embodiment, the wireless link from the UE 201 to the node 203 is an uplink, which is used to perform uplink transmission.

[0384] As one embodiment, the wireless link from the node 203 to the UE 201 is a downlink, which is used to perform downlink transmission.

[0385] As one embodiment, the wireless link between the node 203 and the UE 201 comprises a cellular network link.

[0386] As one embodiment, the node 203 and the UE 201 are connected through a Uu air interface.

[0387] As one embodiment, the sender of the first information block described in the present application comprises the node 203.

[0388] As an embodiment, the receiver of the first information block in the present application comprises the UE 201.

[0389] As an embodiment, the transmitter of the second information block in the present application comprises the UE 201.

[0390] As an embodiment, the receiver of the second information block in the present application comprises the node 203.

[0391] As an embodiment, the transmitter of the first sequence in the present application comprises the node 203.

[0392] As an embodiment, the receiver of the first sequence in the present application comprises the UE 201.

[0393] As an embodiment, the transmitter of the first signaling in the present application comprises the node 203.

[0394] As an embodiment, the receiver of the first signaling in the present application comprises the UE 201.

[0395] As an embodiment, the first signal in the present application is an uplink signal, and the transmitter of the first signal comprises the UE 201.

[0396] As an embodiment, the first signal in the present application is an uplink signal, and the receiver of the first signal comprises the node 203.

[0397] As an embodiment, the first signal in the present application is a downlink signal, and the transmitter of the first signal comprises the node 203.

[0398] As an embodiment, the first signal in the present application is a downlink signal, and the receiver of the first signal comprises the UE 201.

[0399] As an embodiment, the node 203 supports deployment of a network-side AI / ML model.

[0400] As an embodiment, the UE 201 supports deployment of a UE-side AI / ML model.

[0401] As an embodiment, the node 203 supports UE-triggered downlink dynamic scheduling.

[0402] As an embodiment, the node 203 supports UE-triggered uplink dynamic scheduling.

[0403] As an embodiment, the UE 201 supports UE-triggered downlink dynamic scheduling.

[0404] As one embodiment, the UE 201 supports UE triggered uplink dynamic scheduling.

[0405] As one embodiment, the UE 201 supports a 5G system.

[0406] As one embodiment, the node 203 supports a 5G system.

[0407] As one embodiment, the UE 201 supports at least a 6G system.

[0408] As one embodiment, the node 203 supports at least a 6G system.

[0409] Embodiment 3

[0410] Embodiment 3 illustrates a diagram of an embodiment of a wireless protocol architecture of a user plane and control plane, according to one embodiment of the application, as shown in FIG. 3.

[0411] Figure 3 is a schematic diagram illustrating an embodiment of a radio protocol architecture for a user plane 350 and a control plane 300, Figure 3 shows the radio protocol architecture for the control plane 300 between a first communication node device (UE or RSU (Road Side Unit) in V2X (Vehicle to Everything), a vehicle mounted device or a vehicle mounted communication module) and a second node device (gNB, UE or RSU in V2X, a vehicle mounted device or a vehicle mounted communication module), or between two UEs, using three layers: Layer 1 (L1), Layer 2 (L2) and Layer 3 (L3). L1 is the lowest layer and implements various PHY (PHYsical layer) signal processing functions. L1 will be referred to as the PHY 301 in this document. Layer 2 305 is above the PHY 301 and is responsible for the link between the first node device and the second node device, or between two UEs, through the PHY 301. Layer 2 305 includes a MAC (Medium Access Control) sublayer 302, a RLC (Radio Link Control) sublayer 303 and a PDCP (Packet Data Convergence Protocol) sublayer 304, which are terminated at the second node device. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. The PDCP sublayer 304 also provides security, by encrypting packets, and handover support for the first communication node device between second communication node devices. The RLC sublayer 303 provides segmentation and reassembly of upper layer packets, retransmission of lost packets, and reordering of packets to compensate for out-of-order reception due to HARQ (Hybrid Automatic Repeat reQuest). The MAC sublayer 302 provides multiplexing between logical and transport channels. The MAC sublayer 302 is also responsible for allocating the various radio resources (e.g., resource blocks) in one cell among the UEs. The MAC sublayer 302 is also responsible for HARQ operations. The RRC (Radio Resource Control) sublayer 306 in Layer 3 in the control plane 300 is responsible for obtaining radio resources (i.e., radio bearers) and configuring the lower layers using RRC signaling between the second communication node device and the first communication node device.The radio protocol architecture of the user plane 350 includes Layer 1 (L1) and Layer 2 (L2), which are substantially the same as the corresponding layers and sublayers in the control plane 300 for the first communication node device and the second communication node device for the physical layer 351, the PDCP sublayer 354 in L2 355, the RLC sublayer 353 in L2 355, and the MAC sublayer 352 in L2 355, but the PDCP sublayer 354 also provides header compression for upper layer data packets to reduce radio transmission overhead. Also included in L2 355 in the user plane 350 is the SDAP (Service Data Adaptation Protocol) sublayer 356, which is responsible for mapping between QoS (Quality of Service) flows and data radio bearers (DRBs) to support diverse traffic types. Although not illustrated, the first communication node device can have several upper layers above L2 355, including a network layer (e.g., IP (Internet Protocol) layer) that terminates at the P-GW on the network side and an application layer that terminates at the other end of the connection (e.g., a remote UE, a server, etc.).

[0412] As one embodiment, the radio protocol architecture in FIG. 3 is applicable to the first node in the present application.

[0413] As one embodiment, the radio protocol architecture in FIG. 3 is applicable to the second node in the present application.

[0414] As one embodiment, the first information block in the present application is generated at the RRC 306.

[0415] As one embodiment, the first information block in the present application is generated at the MAC 302 or the MAC 352.

[0416] As one embodiment, the second information block in the present application is generated at the MAC 302 or the MAC 352.

[0417] As one embodiment, the second information block in the present application is generated at the PHY 301 or the PHY 351.

[0418] As one embodiment, the first signaling in the present application is generated at the PHY 301 or the PHY 351.

[0419] As one embodiment, the higher layer in the present application refers to a layer above the physical layer.

[0420] As one embodiment, the higher layer as described in the present application comprises a RRC layer.

[0421] As one embodiment, the higher layer signaling as described in the present application comprises a RRC IE.

[0422] As one embodiment, the higher layer signaling as described in the present application comprises a RRC message.

[0423] As one embodiment, the higher layer as described in the present application comprises a MAC layer.

[0424] As one embodiment, the higher layer signaling as described in the present application comprises a MAC CE.

[0425] Embodiment 4

[0426] Embodiment 4 illustrates a schematic diagram of a first communication device and a second communication device according to one embodiment of the present application, as shown in FIG. 4. FIG. 4 is a block diagram of a first communication device 410 and a second communication device 450 communicating with each other in an access network.

[0427] The first communication device 410 comprises a controller / processor 475, a memory 476, a receive processor 470, a transmit processor 416, a multi-antenna receive processor 472, a multi-antenna transmit processor 471, a transmitter / receiver 418 and an antenna 420.

[0428] The second communication device 450 comprises a controller / processor 459, a memory 460, a data source 467, a transmit processor 468, a receive processor 456, a multi-antenna transmit processor 457, a multi-antenna receive processor 458, a transmitter / receiver 454 and an antenna 452.

[0429] In transmissions from the first communication device 410 to the second communication device 450, at the first communication device 410, upper layer packets from the core network are provided to the controller / processor 475. The controller / processor 475 implements functionality of L2. In DL, the controller / processor 475 provides header compression, ciphering, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocations for second communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for HARQ operations, retransmission of lost packets, and signaling to the second communication device 450. The transmit processor 416 and the multi-antenna transmit processor 471 implement various signal processing functions for Ll (i.e., physical layer). The transmit processor 416 implements coding and interleaving to facilitate forward error correction (FEC) at the second communication device 450 and mapping onto signal constellations based on various modulation schemes (e.g., binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), M-ary phase shift keying (M-PSK), M-ary quadrature amplitude modulation (M-QAM)). The multi-antenna transmit processor 471 performs digital spatial pre-coding of the coded and modulated symbols, including codebook-based and non-codebook-based pre-coding and beamforming processing, to generate one or more parallel streams. The transmit processor 416 then maps to each of the parallel streams to subcarriers, multiplexes the modulated symbols in time domain and / or frequency domain with reference signals (e.g., pilot) and then performs an inverse fast Fourier transform (IFFT) to generate time domain multicarrier symbol streams. The multi-antenna transmit processor 471 then performs transmit analog pre-coding / beamforming operations on the time domain multicarrier symbol streams. Each transmitter 418 converts the baseband multicarrier symbol streams provided by the multi-antenna transmit processor 471 into radio frequency signals that are transmitted via the corresponding antennas 420.

[0430] In transmission from the first communication device 410 to the second communication device 450, at the second communication device 450, each receiver 454 receives a signal through its respective antenna 452. Each receiver 454 recovers information modulated onto an RF carrier and converts the RF stream into a baseband, multicarrier symbol stream to receive processor 456. The receive processor 456 and the multi-antenna receive processor 458 implement various signal processing functions of the LI. The multi-antenna receive processor 458 performs receive analog precoding / beamforming operation on the baseband, multicarrier symbol stream from the receivers 454. The receive processor 456 converts the baseband, multicarrier symbol stream from the receive analog precoding / beamforming operation from the time domain to the frequency domain using a Fast Fourier Transform (FFT). In the frequency domain, the physical layer data signals and the reference signals are demultiplexed by the receive processor 456, where the reference signals will be used for channel estimation, and the data signals are recovered after multi-antenna detection in the multi-antenna receive processor 458 for any parallel streams destined to the second communication device 450. The symbols on each parallel stream are demodulated and recovered in the receive processor 456 and generate soft decisions. The receive processor 456 then decodes and de-interleaves the soft decisions to recover the upper layer data and control signals transmitted by the first communication device 410 on the physical channels. The upper layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements the functions of the L2. The controller / processor 459 can be associated with a memory 460 that stores program codes and data. The memory 460 can be referred to as a computer-readable medium. In the DL, the controller / processor 459 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, control signal processing to recover upper layer data packets from the core network. The upper layer data packets are then provided to all protocol layers above the L2. Various control signals can also be provided to the L3 for L3 processing. The controller / processor 459 is also responsible for error detection using an ACK and / or negative ACK (NACK) protocol to support HARQ operations.

[0431] In the transmission from the second communication device 450 to the first communication device 410, at the second communication device 450, a data source 467 is used to provide upper layer packets to a controller / processor 459. The data source 467 represents all protocol layers above L2. Similar to the transmit function described at the first communication device 410 in the DL, the controller / processor 459 implements header compression, ciphering, packet segmentation and reordering, and multiplexing between logical and transport channels based on radio resource allocations for the first communication device 410, implements L2 layer functionality for the user plane and control plane. The controller / processor 459 is also responsible for HARQ operations, retransmission of lost packets, and signaling to the first communication device 410. A transmit processor 468, in conjunction with a multi-antenna transmit processor 457, performs modulation mapping, channel coding processing, digital multi-antenna spatial pre-coding including codebook-based and non-codebook-based precoding, and beamforming processing, and then the transmit processor 468 generates parallel streams of symbols that are modulated onto different carriers, and the modulated symbol streams are then provided to different antennas 452 via transmitters 454 after analog pre-coding / beamforming operations in the multi-antenna transmit processor 457. Each transmitter 454 converts a baseband symbol stream into a radio frequency signal that is transmitted via the corresponding antenna 452.

[0432] In the transmission from the second communication device 450 to the first communication device 410, the functionality at the first communication device 410 is similar to the functionality described in connection with the reception at the second communication device 450 in the transmission from the first communication device 410 to the second communication device 450. Each receiver 418 receives a radio frequency signal through its respective antenna 420, converts the received radio frequency signal into a baseband signal, and provides the baseband signal to a multi-antenna receive processor 472 and a receive processor 470. The receive processor 470 and the multi-antenna receive processor 472 together implement L1 layer functionality. A controller / processor 475 implements L2 layer functionality. The controller / processor 475 can be associated with a memory 476 that stores program codes and data. The memory 476 can be referred to as a computer-readable medium. The controller / processor 475 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, control signal processing to recover upper layer packets from the second communication device 450. Upper layer packets from the controller / processor 475 can be provided to a core network. The controller / processor 475 is also responsible for error detection using an ACK and / or NACK protocol to support HARQ operations.

[0433] As one embodiment, the second communication device 450 comprises: at least one processor and at least one memory including a computer program code; the at least one memory and the computer program code are configured to, with the at least one processor, cause the performance of the following: receiving the first information block; transmitting the second information block.

[0434] As one embodiment, the second communication device 450 comprises: a memory storing a computer readable program of instructions which, when executed by at least one processor, causes the performance of the following: receiving the first information block; transmitting the second information block.

[0435] As one embodiment, the first communication device 410 comprises: at least one processor and at least one memory including a computer program code; the at least one memory and the computer program code are configured to, with the at least one processor, cause the performance of the following: transmitting the first information block; receiving the second information block.

[0436] As one embodiment, the first communication device 410 comprises: a memory storing a computer readable program of instructions which, when executed by at least one processor, causes the performance of the following: transmitting the first information block; receiving the second information block.

[0437] As one embodiment, the first node comprises the second communication device 450.

[0438] As an embodiment, the second node described in the present application comprises the first communication device 410.

[0439] As an embodiment, at least one of {the antenna 420, the transmitter 418, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, the memory 476} is configured to transmit the first information block described in the present application; at least one of {the antenna 452, the receiver 454, the receive processor 456, the multi-antenna receive processor 458, the controller / processor 459, the memory 460, the data source 467} is configured to receive the first information block described in the present application.

[0440] As an embodiment, at least one of {the antenna 452, the transmitter 454, the transmit processor 468, the multi-antenna transmit processor 457, the controller / processor 459, the memory 460, the data source 467} is configured to transmit the second information block described in the present application; at least one of {the antenna 420, the receiver 418, the receive processor 470, the multi-antenna receive processor 472, the controller / processor 475, the memory 476} is configured to receive the second information block described in the present application.

[0441] As an embodiment, at least one of {the antenna 420, the transmitter 418, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, the memory 476} is configured to transmit the first sequence described in the present application; at least one of {the antenna 452, the receiver 454, the receive processor 456, the multi-antenna receive processor 458, the controller / processor 459, the memory 460, the data source 467} is configured to receive the first sequence described in the present application.

[0442] As a sub-embodiment of this embodiment, the second information block described in the present application indicates reception of a first signal, at least one of {the antenna 420, the transmitter 418, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, the memory 476} is configured to transmit the first signal in the first set of resources described in the present application; at least one of {the antenna 452, the receiver 454, the receive processor 456, the multi-antenna receive processor 458, the controller / processor 459, the memory 460, the data source 467} is configured to receive the first signal in the first set of resources described in the present application.

[0443] As a sub-embodiment of this embodiment, at least one of {the antenna 452, the transmitter 454, the transmit processor 468, the multi-antenna transmit processor 457, the controller / processor 459, the memory 460, the data source 467} is configured to transmit the first signal in the first resource set as specified in the second information block; at least one of {the antenna 420, the receiver 418, the receive processor 470, the multi-antenna receive processor 472, the controller / processor 475, the memory 476} is configured to receive the first signal in the first resource set as specified in the second information block.

[0444] As an embodiment, at least one of {the antenna 420, the transmitter 418, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, the memory 476} is configured to transmit the first signaling as specified in this application; at least one of {the antenna 452, the receiver 454, the receive processor 456, the multi-antenna receive processor 458, the controller / processor 459, the memory 460, the data source 467} is configured to receive the first signaling as specified in this application.

[0445] As a sub-embodiment of this embodiment, at least one of {the antenna 420, the transmitter 418, the transmit processor 416, the multi-antenna transmit processor 471, the controller / processor 475, the memory 476} is configured to transmit the first signal in the first resource subset as specified in this application; at least one of {the antenna 452, the receiver 454, the receive processor 456, the multi-antenna receive processor 458, the controller / processor 459, the memory 460, the data source 467} is configured to receive the first signal in the first resource subset as specified in this application.

[0446] As an embodiment, at least one of {the antenna 452, the transmitter 454, the transmit processor 468, the multi-antenna transmit processor 457, the controller / processor 459, the memory 460, the data source 467} is configured to transmit the first signal in the second resource subset as specified in this application; at least one of {the antenna 420, the receiver 418, the receive processor 470, the multi-antenna receive processor 472, the controller / processor 475, the memory 476} is configured to receive the first information block in the second resource subset as specified in this application.

[0447] Embodiment 5

[0448] Embodiment 5 illustrates a first flowchart of a transmission between a first node and a second node according to an embodiment of the present application, as shown in FIG. 5. In FIG. 5, the first node U1 communicates with the second node N2 over a wireless link. It is specifically pointed out that the sequence in this embodiment does not limit the sequence of signal transmission and implementation in the present application. The embodiments, sub-embodiments and dependent embodiments in Embodiments 6, 7 and 8 can be applied to Embodiment 5 without conflict; conversely, any embodiment, sub-embodiment and dependent embodiment in Embodiment 5 can be applied to Embodiments 6, 7 and 8 without conflict.

[0449] For the first node U1, the first information block is received in step S510; the second information block is sent in step S511.

[0450] For the second node N2, the first information block is sent in step S520; the second information block is received in step S521.

[0451] In Embodiment 5, the first information block indicates a first set of resource blocks; the second information block indicates a first set of resources from the first set of resource blocks, the first set of resources being for dynamic scheduling; the first set of resource blocks is determined based on an AI / ML model; the first set of resource blocks includes K1 resource blocks, the K1 being a positive integer greater than 1, at least two of the K1 resource blocks occupying time domain resources that are orthogonal; the first set of resource blocks depends on an ID of the AI / ML model.

[0452] As an embodiment, the first node U1 is the first node in the present application.

[0453] As an embodiment, the second node N2 is the second node in the present application.

[0454] As an embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between a base station device and a user equipment.

[0455] As an embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between a relay node device and a user equipment.

[0456] As an embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between a user equipment and a user equipment.

[0457] As an embodiment, the second node N2 and the first node U1 communicate over a Uu interface.

[0458] As one embodiment, the second node N2 is a maintaining base station of a serving cell of the first node U1.

[0459] As one embodiment, the transport channel occupied by the first information block comprises a DL-SCH (DownLink-Shared CHannel).

[0460] As one embodiment, the physical layer channel occupied by the first information block comprises a PDSCH (Physical Downlink Shared CHannel).

[0461] As one embodiment, the physical layer channel occupied by the second information block comprises a PUCCH.

[0462] As one embodiment, the physical layer channel occupied by the second information block comprises a PUSCH (Physical Uplink Shared CHannel).

[0463] As one embodiment, the step S510 is prior to the step S511; the step S520 is prior to the step S521.

[0464] Embodiment 6

[0465] Embodiment 6 illustrates a second flowchart of transmission between a first node and a second node according to one embodiment of the present application, as shown in FIG. 6. In FIG. 6, the first node U3 communicates with the second node N4 through a wireless link. It is particularly stated that the sequence in this embodiment does not limit the sequence of signal transmission and implementation in the present application. In the case of no conflict, the embodiments, sub-embodiments and dependent embodiments in embodiment 6 can be applied to embodiment 5; conversely, in the case of no conflict, any embodiment, sub-embodiment and dependent embodiment in embodiment 5 can be applied to embodiment 6.

[0466] In case (a):

[0467] - for the first node U3, receiving the first sequence in step S630; transmitting the first signal in the first set of resources in step S631a;

[0468] - for the second node N4, transmitting the first sequence in step S640; receiving the first signal in the first set of resources in step S641a.

[0469] In case (b):

[0470] - for the first node U3, receiving the first sequence in step S630; receiving the first signal in the first set of resources in step S631b;

[0471] - for the second node N4, transmitting the first sequence in step S640; transmitting the first signal in the first set of resources in step S641b.

[0472] In embodiment 6, the first sequence confirms the second information block, which schedules the first signal in the present application.

[0473] As an embodiment, the first sequence is a pseudo-random sequence.

[0474] As an embodiment, the first sequence is a ZC (Zadoff-Chu) sequence.

[0475] As an embodiment, the first sequence is a Gold sequence.

[0476] As an embodiment, the first sequence is an m-sequence.

[0477] As an embodiment, the first sequence is an M-sequence.

[0478] As an embodiment, the first sequence is generated by cyclically shifting a pseudo-random sequence.

[0479] As an embodiment, the receiving of the first sequence is implemented by coherent detection.

[0480] As an embodiment, the receiving of the first sequence is implemented by decoding.

[0481] As an embodiment, the time-frequency resources occupied by the first sequence depend on the time-frequency resources occupied by the second information block.

[0482] As an embodiment, the time-domain resources occupied by the first sequence depend on the time-domain resources occupied by the second information block.

[0483] As an embodiment, the frequency-domain resources occupied by the first sequence depend on the frequency-domain resources occupied by the second information block.

[0484] As an embodiment, the spatial receiving parameters adopted by the first sequence depend on the spatial transmitting parameters of the second information block.

[0485] As an embodiment, the receiving of the first sequence is implemented by blind detection.

[0486] As an embodiment, the first sequence carries at least one bit of information.

[0487] As one embodiment, the first node U3 determines the received first sequence information by blind detection.

[0488] As one embodiment, the first sequence confirms the second information block.

[0489] As one embodiment, the first sequence is feedback for the second information block.

[0490] As one embodiment, the first sequence indicates whether the second information block is correctly received by the second node N4.

[0491] As one embodiment, the first sequence indicates that the second information block is correctly received by the second node N4.

[0492] As one embodiment, the first sequence indicates whether to cancel the transmission of the first signal.

[0493] As one embodiment, the first sequence confirms that the transmission of the first signal is not cancelled.

[0494] As one embodiment, the first sequence indicates that the transmission of the first signal is not cancelled.

[0495] As one embodiment, the second information block schedules the first signal.

[0496] As one embodiment, the second information block carries scheduling information of the first signal.

[0497] As one embodiment, the scheduling information of the first signal includes one or more of time domain resource, frequency domain resource, MCS (Modulation and Coding Scheme), DMRS (Demodulation reference signal) ports, HARQ process number, TCI state, RV (Redundancy version), NDI (New Data Indicator), Antenna ports, SRS (Sounding Reference Signal request) indication.

[0498] As one sub-embodiment of this embodiment, the time domain information includes the first resource set.

[0499] As one sub-embodiment of this embodiment, the frequency domain information includes the first resource set.

[0500] As one embodiment, the first signal is a baseband signal.

[0501] As one embodiment, the first signal is a radio frequency signal.

[0502] As one embodiment, the first signal is a wireless signal.

[0503] As one embodiment, the first signal occupies resources of the first resource set.

[0504] As one embodiment, the second information block indicates an MCS adopted by the first signal.

[0505] As one embodiment, the first signal is generated by a bit block.

[0506] As one embodiment, the first signal is generated by at least one transport block.

[0507] As one embodiment, the first signal carries one bit block, and the one bit block includes at least one TB or at least one CBG (Code block group).

[0508] As one embodiment, the step in case (a) in FIG. 5 exists; the step in case (b) does not exist; and the method applied to the first node in the application includes: receiving a first sequence; and transmitting a first signal in a first resource set.

[0509] As one sub-embodiment of the embodiment, resources occupied by the first resource set can be or are allowed to be used for uplink signal transmission.

[0510] As one sub-embodiment of the embodiment, the second information block indicates transmission of the first signal.

[0511] As one sub-embodiment of the embodiment, the second information block notifies the second node N4 of transmission of the first signal.

[0512] As one sub-embodiment of the embodiment, a transmission channel occupied by the first signal includes an UL-SCH (UpLink-Shared CHannel).

[0513] As one sub-embodiment of the embodiment, a physical layer channel occupied by the first signal includes a PUSCH.

[0514] As one sub-embodiment of the embodiment, the step S631a is after the step S630; and the step S641a is after the step S640.

[0515] As a sub-embodiment of this embodiment, the step S630 is after the step S511 in Figure 5; the step S640 is after the step S521.

[0516] As an embodiment, the steps in the case (b) in Figure 5 exist; the steps in the case (a) do not exist; the method applied to the first node in the application comprises: receiving a first sequence; receiving a first signal in a first resource set.

[0517] As a sub-embodiment of this embodiment, the resources occupied by the first resource set can or are allowed to be used for downlink signal transmission.

[0518] As a sub-embodiment of this embodiment, the second information block indicates the reception of the first signal.

[0519] As a sub-embodiment of this embodiment, the second information block notifies the second node N4 to transmit the first signal.

[0520] As a sub-embodiment of this embodiment, the transmission channel occupied by the first signal comprises a DL-SCH.

[0521] As a sub-embodiment of this embodiment, the physical layer channel occupied by the first signal comprises a PDSCH.

[0522] As a sub-embodiment of this embodiment, the step S631b is after the step S630; the step S641b is after the step S640.

[0523] As a sub-embodiment of this embodiment, the step S630 is after the step S511 in Figure 5; the step S640 is after the step S521.

[0524] As an embodiment, the steps S631a and S641a in the case (a) in Figure 5 exist; the steps S631b and S641b in the case (b) do not exist.

[0525] As an embodiment, the steps S631a and S641a in the case (a) in Figure 5 do not exist; the steps S631b and S641b in the case (b) exist.

[0526] As an embodiment, the step S630 in the case (a) in Figure 5 is the step S630 in the case (b); the step S640 in the case (a) is the step S640 in the case (b).

[0527] Embodiment 7

[0528] Embodiment 7 illustrates a third flowchart of transmission between a first node and a second node according to an embodiment of the present application, as shown in FIG. 7. In FIG. 7, the first node U5 communicates with the second node N6 through a wireless link. It is particularly pointed out that the sequence in this embodiment does not limit the sequence of signal transmission and implementation in the present application. The embodiments, sub-embodiments and dependent embodiments in embodiment 5 can be applied to embodiment 7 without conflict; conversely, any embodiment, sub-embodiment and dependent embodiment in embodiment 7 can be applied to embodiment 5 without conflict.

[0529] For the first node U5, the first signaling is received in step S750; the first signal is received in the first resource subset in step S751;

[0530] For the second node N6, the first signaling is sent in step S760; the first signal is sent in the first resource subset in step S761.

[0531] In embodiment 7, the first signaling depends on the second information block; the first signaling indicates the first resource subset from the first resource set, and the second information block and the first signaling jointly indicate the first signal.

[0532] As an embodiment, the first signaling is dynamic signaling.

[0533] As an embodiment, the first signaling is physical layer control signaling.

[0534] As an embodiment, the first signaling is DCI (Downlink Control Information).

[0535] As an embodiment, the first signaling is DL DCI.

[0536] As an embodiment, the first signaling carries scheduling information of the first signal.

[0537] As an embodiment, the scheduling information of the first signal includes one or more of time domain resource, frequency domain resource, MCS, DMRS port, HARQ process number, TCI state, RV, NDI, and Antenna port.

[0538] As a sub-embodiment of this embodiment, the time domain information includes the first resource subset.

[0539] As a sub-example of this example, the frequency domain information comprises the first resource subset.

[0540] As an example, the first signal occupies the first resource subset.

[0541] As an example, the first signaling indicates an MCS employed by the first signal.

[0542] As an example, the second information block comprises a DLSR (DownLink Scheduling Request).

[0543] As an example, the first signaling depends on the second information block.

[0544] As an example, the first signaling comprises feedback for the second information block.

[0545] As an example, the first signaling comprises an acknowledgement for the second information block.

[0546] As an example, the second node N6 sends the first signaling after decoding the second information block.

[0547] As an example, the first signaling is a response of the second node N6 to the second information block.

[0548] As an example, the second information block carries partial scheduling information of the first signal, the partial scheduling information comprising the first resource set.

[0549] As an example, as a response to receiving the second information block, the second node N6 sends the first signaling, the first signaling carrying the partial scheduling information of the first signal, the partial scheduling information comprising the first resource subset.

[0550] As an example, a number of information bits occupied by the first signaling depends on the first resource set indicated by the second information block.

[0551] As an example, a format employed by the first signaling depends on the first resource set indicated by the second information block.

[0552] As an example, the second information block implicitly indicates the first resource set, and the first signaling explicitly indicates the first resource subset.

[0553] As an example, a time domain resource of the second information block implicitly indicates a time domain resource occupied by the first resource set.

[0554] As an embodiment, the first signaling explicitly indicates a time domain starting position of the first resource subset.

[0555] As an embodiment, the first signaling indicates the first resource subset from the first resource set.

[0556] As an embodiment, the first resource set includes the first resource subset.

[0557] As an embodiment, the first resource subset is the first resource set.

[0558] As an embodiment, at least one time-frequency resource belongs to the first resource set and does not belong to the first resource subset.

[0559] As an embodiment, the first resource subset belongs to one of the multiple resource subsets in the embodiment 10.

[0560] As an embodiment, the second information block and the first signaling jointly indicate the first signal.

[0561] As an embodiment, the second information block and the first signaling are jointly used for scheduling the first signal.

[0562] As an embodiment, the second information block and the first signaling are jointly used for indicating the first resource subset from the first resource set.

[0563] As an embodiment, the second information block and the first signaling both carry scheduling information of the first signal.

[0564] As an embodiment, the first signaling occupies a physical layer channel including a PDCCH.

[0565] As an embodiment, the first signal is a baseband signal.

[0566] As an embodiment, the first signal is a radio frequency signal.

[0567] As an embodiment, the first signal is a wireless signal.

[0568] As an embodiment, the first signal is generated by a bit block.

[0569] As an embodiment, the first signal is generated by at least one transport block.

[0570] As an embodiment, the first signal carries one bit block, and the one bit block includes at least one TB or at least one CBG.

[0571] As one embodiment, the transmission channel occupied by the first signal comprises a DL-SCH.

[0572] As one embodiment, the physical layer channel occupied by the first signal comprises a PDSCH.

[0573] As one embodiment, the step S751 is after the step S750; the step S761 is after the step S760.

[0574] As one embodiment, the step S750 is after the step S511 in the FIG. 5; the step S760 is after the step S521.

[0575] Embodiment 8

[0576] Embodiment 8 illustrates a fourth flow chart of transmission between a first node and a second node according to one embodiment of the present application, as shown in the FIG. 8. In the FIG. 8, the first node U7 communicates with the second node N8 through a wireless link. It is particularly noted that the sequence in this embodiment does not limit the sequence of signal transmission and implementation in the present application. In the case of no conflict, the embodiments, sub-embodiments and dependent embodiments in the embodiment 5 can be applied to the embodiment 8; conversely, in the case of no conflict, any embodiment, sub-embodiment and dependent embodiment in the embodiment 8 can be applied to the embodiment 5.

[0577] For the first node U7, in the step S870, a first signal is transmitted in a second resource subset;

[0578] For the second node N8, in the step S880, a first signal is received in a second resource subset.

[0579] In the embodiment 8, the first resource set comprises a plurality of resource subsets, and the second resource subset is one of the plurality of resource subsets.

[0580] As one embodiment, the second node N8 blindly detects the first signal from the plurality of resource subsets.

[0581] As one embodiment, the plurality of resource subsets are X1 resource subsets respectively, the X1 resource subsets occupy X1 number of RBs respectively, and the X1 resource subsets all occupy the RBs occupied by the resource subset with the least number of occupied RBs in the X1 resource subsets.

[0582] As one embodiment, the plurality of resource subsets are X1 resource subsets respectively, the X1 resource subsets occupy X1 number of REs respectively, and the X1 resource subsets all occupy the REs occupied by the resource subset with the least number of occupied REs in the X1 resource subsets.

[0583] As an embodiment, the plurality of resource subsets are the plurality of resource subsets in Embodiment 10 of the present application.

[0584] As an embodiment, the first signal is a baseband signal.

[0585] As an embodiment, the first signal is a radio frequency signal.

[0586] As an embodiment, the first signal is a wireless signal.

[0587] As an embodiment, the first signal is generated by a bit block.

[0588] As an embodiment, the first signal is generated by at least one transport block.

[0589] As an embodiment, the first signal carries one bit block, and the one bit block includes at least one TB or at least one CBG.

[0590] As an embodiment, the transmission channel occupied by the first signal includes UL-SCH.

[0591] As an embodiment, the physical layer channel occupied by the first signal includes PUSCH.

[0592] As an embodiment, the step S870 is after the step S511 in FIG. 5; and the step S880 is after the step S521.

[0593] Embodiment 9

[0594] Embodiment 9 illustrates a schematic diagram of K1 resource blocks included in the first resource block set according to an embodiment of the present application, as shown in FIG. 9. In FIG. 9, the horizontal axis represents time, and the cross-hatched rectangle represents the time domain resource occupied by one resource block in time, and the K1 resource blocks are orthogonal in time domain. It is worth noting that FIG. 10 is only illustrative, and the present application does not limit that each resource block must occupy the same length of time domain resource.

[0595] In Embodiment 9, the second information block is used to indicate K1 resource subsets from the K1 resource blocks, and the first resource set includes the K1 resource subsets.

[0596] As an embodiment, at least two resource blocks in the K1 resource blocks occupy different frequency domain resources.

[0597] As a sub-embodiment of this embodiment, at least two resource blocks in the K1 resource blocks occupy different frequency bandwidths corresponding to the frequency domain resources.

[0598] As one sub-embodiment of the embodiment, the frequency domain starting positions corresponding to the frequency domain resources occupied by at least two of the K1 resource blocks are different.

[0599] As one sub-embodiment of the embodiment, the frequency domain ending positions corresponding to the frequency domain resources occupied by at least two of the K1 resource blocks are different.

[0600] As one embodiment, the first signal comprises K1 sub-signals, which are respectively sent in the K1 resource subsets.

[0601] As one sub-embodiment of the embodiment, the K1 sub-signals are repeatedly sent.

[0602] As one sub-embodiment of the embodiment, the K1 sub-signals are respectively generated by K1 transport blocks.

[0603] As one sub-embodiment of the embodiment, the K1 sub-signals respectively correspond to K1 HARQ processes.

[0604] As one embodiment, the first node sends the first signal of the present application in the K1 resource subsets comprised by the first resource set.

[0605] As one embodiment, the second information block implicitly indicates the time domain resources of the first resource block set.

[0606] As one embodiment, the time domain resources occupied by the second information block implicitly indicate the time domain resources occupied by the first resource block set.

[0607] As one embodiment, the time domain resources occupied by the second information block implicitly indicate the time domain resources occupied by the first resource block set.

[0608] Embodiment 10

[0609] Embodiment 10 illustrates an example of the first resource set including multiple resource subsets according to an embodiment of the present application, as shown in FIG. 10. In FIG. 10, the first resource set includes 4 resource granularities, denoted as resource granularity #1, resource granularity #2, resource granularity #3 and resource granularity #4 respectively, and the resources occupied by the first resource set under each resource granularity are represented by a rectangle with a thick line frame, and a diamond cross-filled rectangle represents the resources occupied by one of the resource subsets in the first resource set. Among them, resource granularity #1 includes 4 resource subsets, resource granularity #2 includes 3 resource subsets, resource granularity #3 includes 1 resource subset, and resource granularity #4 includes 1 resource subset. It should be noted that FIG. 10 is only illustrative and is intended to present the relevant concepts in a specific manner, and the present application does not limit the first resource set to occupy continuous time domain resources or frequency domain resources, nor does it limit the number of resource granularities included in the first resource set and the number of resource subsets included in each resource granularity.

[0610] In Embodiment 10, the first resource set includes multiple resource subsets.

[0611] As an embodiment, the first resource set occupies continuous time domain resources.

[0612] As an embodiment, the first resource set occupies continuous frequency domain resources.

[0613] As a sub-embodiment of the above two embodiments, the continuous resource allocation method is simple to implement, simplifies signal reception processing, and also reduces the signaling overhead of the second information block indicating the first resource set.

[0614] As an embodiment, the first resource set occupies non-continuous time domain resources.

[0615] As an embodiment, the first resource set occupies non-continuous frequency domain resources.

[0616] As a sub-embodiment of the above two embodiments, discrete frequency domain resource allocation can obtain frequency selectivity gain, and discrete time domain resources can improve the reliability of signal transmission through repeated transmission or reduced code rate.

[0617] As an embodiment, the first resource set is supported to employ different resource allocation manners in different channel states in the present application, and an optional implementation manner is that the first node can indicate in the second information block whether the first resource set is based on continuous resource allocation or discrete resource allocation; another optional implementation manner is that the second node indicates the resource allocation manner of the first resource set through a higher layer parameter in the present application, and the higher layer parameter can be transmitted through the first information block.

[0618] As an embodiment, any one of the plurality of resource subsets occupies continuous time domain resources.

[0619] As an embodiment, any one of the plurality of resource subsets occupies discontinuous time domain resources.

[0620] As an embodiment, any one of the plurality of resource subsets occupies continuous frequency domain resources.

[0621] As an embodiment, any one of the plurality of resource subsets occupies discontinuous frequency domain resources.

[0622] As an embodiment, at least one of the plurality of resource subsets occupies continuous time domain resources.

[0623] As an embodiment, at least one of the plurality of resource subsets occupies discontinuous time domain resources.

[0624] As an embodiment, at least one of the plurality of resource subsets occupies continuous frequency domain resources.

[0625] As an embodiment, at least one of the plurality of resource subsets occupies discontinuous frequency domain resources.

[0626] As an embodiment, at least two of the plurality of resource subsets occupy overlapping time-frequency resources.

[0627] As an embodiment, at least two of the plurality of resource subsets occupy orthogonal frequency domain resources.

[0628] As an embodiment, at least two of the plurality of resource subsets occupy orthogonal time domain resources.

[0629] As an embodiment, at least two of the plurality of resource subsets occupy overlapping frequency domain resources.

[0630] As an embodiment, at least two of the plurality of resource subsets occupy overlapping time domain resources.

[0631] As one embodiment, the number of resource granules occupied by any two of the plurality of resource subsets is the same.

[0632] As one embodiment, the number of resource granules occupied by at least two of the plurality of resource subsets is different.

[0633] As one embodiment, the number of resource granules occupied by any two of the plurality of resource subsets is different.

[0634] As one embodiment, the present application supports multiple implementation mechanisms of UE triggered dynamic scheduling, reduces the requirement on UE capability, and can be flexibly applied to different terminals. Correspondingly, the resource subsets occupied by UE triggered dynamic scheduling also support multiple different resource allocation manners for different implementation mechanisms.

[0635] As one embodiment, the resource granularity included in the first resource set is configured by higher layer signaling.

[0636] As one sub-embodiment of the embodiment, the higher layer signaling includes the first information block.

[0637] As one sub-embodiment of the embodiment, the higher layer signaling includes the configuration parameter set for the first resource block set in the present application.

[0638] As one embodiment, the number of resource subsets included in any resource granularity in the first resource set is configured by higher layer signaling.

[0639] As one sub-embodiment of the embodiment, the higher layer signaling includes the first information block.

[0640] As one sub-embodiment of the embodiment, the higher layer signaling includes the configuration parameter set for the first resource block set in the present application.

[0641] As one embodiment, the second node in the present application blindly detects the first signal from the plurality of resource subsets.

[0642] As one embodiment, the plurality of resource subsets are in a nested structure in the first resource set.

[0643] Embodiment 11

[0644] Embodiment 11 illustrates a diagram of a set of configuration parameters for a first set of resource blocks according to an embodiment of the application, as shown in FIG. 11. In FIG. 11, the set of configuration parameters includes at least one of a power parameter or a spatial parameter; optionally, the set of configuration parameters includes a predicted idle probability for a resource block in the first set of resource blocks.

[0645] In Embodiment 11, the first information block includes the set of configuration parameters for the first set of resource blocks.

[0646] As one embodiment, the first information block includes the set of configuration parameters for the first set of resource blocks.

[0647] As one embodiment, the first information block carries the set of configuration parameters for the first set of resource blocks.

[0648] As one embodiment, the set of configuration parameters for the first set of resource blocks includes a power parameter and a spatial parameter.

[0649] As one embodiment, the set of configuration parameters includes a power parameter and a predicted idle probability for a resource block in the first set of resource blocks.

[0650] As one embodiment, the set of configuration parameters includes a spatial parameter and a predicted idle probability for a resource block in the first set of resource blocks.

[0651] As one embodiment, the set of configuration parameters includes a power parameter, a spatial parameter and a predicted idle probability for a resource block in the first set of resource blocks.

[0652] As one embodiment, the set of configuration parameters for the first set of resource blocks configures a default transmission parameter for a wireless signal transmitted in the first set of resource blocks; the advantage of the above scheme is that, especially in a time-frequency resource with slow channel state variation, the dynamic signaling overhead can be reduced and the spectrum resource can be saved by configuring the slowly-varying parameter in advance through a higher layer parameter, however, correspondingly, the more parameters configured in the set of parameters, the more obvious the flexible limitation of transmission configuration; an optional implementation scheme is that the default transmission parameter can be updated through dynamic signaling or further selected or indicated through dynamic signaling.

[0653] As one embodiment, the set of configuration parameters for the first set of resource blocks includes a power parameter, the power parameter indicating a transmission power adopted by a signal transmitted in the first set of resource blocks.

[0654] As one embodiment, the set of configuration parameters for the first set of resource blocks includes a power parameter, which indicates a maximum transmit power value of a wireless signal transmitted in the first set of resource blocks.

[0655] As one embodiment, the set of configuration parameters for the first set of resource blocks includes K1 power parameters, which respectively indicate transmission powers of wireless signals transmitted in K1 resource blocks included in the first set of resource blocks.

[0656] As one embodiment, the set of configuration parameters for the first set of resource blocks includes K1 power parameters, which respectively indicate maximum transmit power values of wireless signals transmitted in K1 resource blocks included in the first set of resource blocks.

[0657] As one embodiment, the set of configuration parameters for the first set of resource blocks includes a spatial parameter, which indicates a spatial relation of a wireless signal transmitted in the first set of resource blocks.

[0658] As one embodiment, the set of configuration parameters for the first set of resource blocks includes K1 spatial parameters, which respectively indicate spatial relations of wireless signals transmitted in K1 resource blocks included in the first set of resource blocks.

[0659] As one embodiment, the set of configuration parameters for the first set of resource blocks includes a spatial parameter, which indicates a spatial transmit parameter or a spatial receive parameter of a wireless signal transmitted in the first set of resource blocks.

[0660] As one embodiment, the set of configuration parameters for the first set of resource blocks includes K1 spatial parameters, which respectively indicate spatial transmit parameters or spatial receive parameters of wireless signals transmitted in K1 resource blocks included in the first set of resource blocks.

[0661] As one embodiment, the set of configuration parameters for the first set of resource blocks includes a spatial parameter, which indicates a TCI State corresponding to a wireless signal transmitted in the first set of resource blocks.

[0662] As one embodiment, the set of configuration parameters for the first set of resource blocks includes K1 spatial parameters, which respectively indicate TCI States of wireless signals transmitted in K1 resource blocks included in the first set of resource blocks.

[0663] As an embodiment, the set of configuration parameters for the first set of resource blocks comprises a spatial parameter, which indicates a QCL relationship of a wireless signal transmitted in the first set of resource blocks.

[0664] As an embodiment, the set of configuration parameters for the first set of resource blocks comprises K1 spatial parameters, which respectively indicate a QCL relationship of a wireless signal transmitted in K1 resource blocks comprised in the first set of resource blocks.

[0665] As an embodiment, the QCL in the present application refers to Quasi Co-Location.

[0666] As an embodiment, the QCL in the present application refers to Quasi Co-Located.

[0667] As an embodiment, the QCL in the present application comprises QCL assumption.

[0668] As an embodiment, the type of QCL in the present application comprises typeA, typeB, typeC and typeD.

[0669] As an embodiment, the QCL parameter of the QCL type of typeA in the present application comprises Doppler shift, Doppler spread, average delay and delay spread; the QCL parameter of the QCL type of typeB in the present application comprises Doppler shift and Doppler spread; the QCL parameter of the QCL type of typeC in the present application comprises Doppler shift and average delay; the QCL parameter of the QCL type of typeD in the present application comprises spatial Rx parameter.

[0670] As an embodiment, the QCL in the present application comprises at least one of Doppler shift, Doppler spread, average delay, delay spread, spatial Tx parameter or spatial Rx parameter.

[0671] As an embodiment, the typeA, the typeB, the typeC and the typeD are defined in 3GPP TS (Technical Specification) 38.214, clause 5.1.5.

[0672] As an embodiment, the spatial transmission parameter includes at least one of a transmission antenna port, a transmission antenna port group, a transmission beam, a transmission analog beamforming matrix, a transmission analog beamforming vector, a transmission beamforming matrix, a transmission beamforming vector, or a spatial transmission filter.

[0673] As an embodiment, the spatial reception parameter includes at least one of a reception beam, a reception analog beamforming matrix, a reception analog beamforming vector, a reception beamforming matrix, a reception beamforming vector, or a spatial reception filter.

[0674] As an embodiment, the set of configuration parameters for the first set of resource blocks includes a predicted probability of being free for a resource block in the first set of resource blocks.

[0675] As an embodiment, the set of configuration parameters for the first set of resource blocks includes K1 probability of being free values, respectively for K1 resource blocks included in the first set of resource blocks.

[0676] As an embodiment, the set of configuration parameters for the first set of resource blocks includes a probability value of the first node transmitting a signal in the first set of resource blocks.

[0677] As an embodiment, the set of configuration parameters for the first set of resource blocks includes a probability value of the first node receiving a signal in the first set of resource blocks.

[0678] As an embodiment, the set of configuration parameters for the first set of resource blocks includes a probability value of the first node having data to transmit in the first set of resource blocks.

[0679] Embodiment 12

[0680] Embodiment 12 illustrates a schematic diagram of RAN domain AI / ML function deployment according to an embodiment of the present application, as shown in FIG. 12. In FIG. 12, the gNB can be replaced by a network device such as an eNB, or a 6G base station, etc.

[0681] In embodiment 12, the management of the ML inference functions of the plurality of base stations is done by the RAN domain management function 1202, i.e. data interaction with the RAN domain MnS (Management Service) consumer / cross-domain management 1201 (as shown by the dashed arrow in Fig. 12). The RAN domain ML training function 1203 is located in the RAN domain management function 1202; while the ML inference functions are located in the base stations, i.e. the AI / ML inference function 1204 is located in the gNB 1205, the AI / ML inference function 1206 is located in the gNB 1207, and so on.

[0682] The AI / ML related functions include ML training function (also referred to as AI training, or AI / ML training), ML testing function, ML inference function (also referred to as AI inference, or AI / ML inference), and so on. The ML training function, the ML testing function, and the ML inference function can be deployed independently, or can be co-located. The deployment of the AI / ML related functions can be implemented by software, e.g. the download and / or running of executable files; or can be implemented by software in combination with hardware, e.g. specific computing units are accelerated by hardware to improve the operation speed or save power consumption.

[0683] For the ML training function, it can be deployed in a cross-domain management system, or a domain-specific management system for managing a RAN domain or a CN (Core Network) domain. For example, for the ML training function of MDA (Management Data Analytics), it can be deployed in a MDAF (Management Data Analytic Function); for the ML training of network data analytics, it can be deployed in a NWDAF (NetWork Data Analytics Function), i.e. the ML training function is a MTLF (Model Training Logical Function).

[0684] For the ML inference function, it can also be deployed in a cross-domain management system, or a domain-specific management system; for example, the ML inference function is a MDAF, or the ML inference function is an AnLF (Analytics Logical Function) located in a NWDAF.

[0685] Similarly, the ML inference function can also be deployed in the cross-domain management system, or the domain-specific management system.

[0686] Optionally, the management of the ML inference function can also be completed by the base station itself, i.e., each base station can independently interact with the RAN domain MnS consumer / cross-domain management 1201.

[0687] It should be noted that embodiment 12 is only one non-limiting implementation; optionally, the ML training function of the RAN domain can also be deployed in the base station; or optionally, part of the base stations deploy the ML inference function and the ML training function of the RAN domain, and part of the base stations only deploy the ML inference function.

[0688] As an embodiment, one gNB (or base station) in embodiment 12 is the second node of the application.

[0689] Embodiment 13

[0690] Embodiment 13 illustrates a schematic diagram of AI / ML function deployment of a UE according to an embodiment of the application, as shown in FIG. 13. In FIG. 13, the RAN domain ML training function 1304 is optional.

[0691] The UE function 1303 is deployed in the first node of the application, and the UE function 1303 includes an AI / ML inference function 1305; the AI / ML inference function 1305 uses a ML model (also referred to as an AI model) for inference; a ML model is usually trained before being used for AI / ML inference.

[0692] As an embodiment, the UE function 1303 includes a RAN domain ML training function 1304, which runs training data through a ML model to derive a related loss, and adjusts parameters of the ML model based on the calculated loss; the ML training includes at least one of ML initial training, ML re-training, and reinforcement learning.

[0693] The above embodiments can reduce the complexity of the base station, or save the air interface resources caused by reporting training data; however, the above embodiments have higher requirements for the processing capability of the UE side.

[0694] Optionally, the UE function 1303 also includes a CN domain ML training function (not included in FIG. 13).

[0695] Optionally, the UE function 1303 further comprises an AI / ML deployment function - not included in Figure 13 - for loading ML models and data.

[0696] As an embodiment, the first node indicates whether the ML training function (RAN domain or CN domain) is supported through capability reporting, which is RRC signaling or NAS (Non-Access Stratum) signaling.

[0697] As an embodiment, the ML model, and related metadata, is loaded by the first node from a network device or a remote server.

[0698] Optionally, the UE function 1303 is a MnS producer that provides data to the CN domain MnF and / or RAN domain MnF and / or cross-domain management system 1301 for management or analysis (as indicated by double-headed arrow 1302).

[0699] Optionally, the UE function 1303 is a MnS consumer that loads data from the CN domain MnF and / or RAN domain MnF and / or cross-domain management system 1301 for AI / ML-related management, such as management data requests, ML model activation, and / or ML training, etc. (as indicated by double-headed arrow 1302).

[0700] As an embodiment, the first set of resource blocks in the present application is obtained through inference by the AI / ML inference function 1305.

[0701] As an embodiment, the probability of resource block idleness in the first set of resource blocks in the present application is obtained through inference by the AI / ML inference function 1305.

[0702] As an embodiment, the ML model is based on NN (Neural Networks).

[0703] As an embodiment, the ML model is based on ANN (Artificial Neural Networks).

[0704] As an embodiment, the ML model is based on CNN (Convolutional Neural Networks).

[0705] As one embodiment, the ML model is based on a LLM (Large Language Model) architecture.

[0706] As one embodiment, the ML model is based on a Transformer architecture.

[0707] As one embodiment, the ML model is based on an LSTM (Long Short-Term Memory).

[0708] As one embodiment, the ML model is based on an MLP (MultiLayer Perceptron).

[0709] As one embodiment, the ML model is based on a GAN (Generative Adversarial Nets).

[0710] As one embodiment, the ML model is based on a light-weight neural network.

[0711] As one sub-embodiment of this embodiment, the light-weight neural network includes one or more of MobileNet, ShuffleNet, and SqueezeNet.

[0712] Embodiment 14

[0713] Embodiment 14 illustrates a schematic diagram of an artificial intelligence or machine learning based processing system according to one embodiment of the present application, as shown in FIG. 14. In FIG. 14, the artificial intelligence or machine learning based processing system includes a first processing machine, a second processing machine, a third processing machine, and a fourth processing machine.

[0714] In embodiment 14, the first processing machine sends a first data set to the second processing machine, and sends a second data set to the third processing machine; the second processing machine generates a target first-class parameter group according to the first data set, and sends the generated target first-class parameter group to the third processing machine; the third processing machine processes the second data set using the target first-class parameter group to obtain a first-class output, and optionally, the third processing machine sends the first-class output to the fourth processing machine. In FIG. 14, a first-class feedback and a second-class feedback are optional; the second processing machine includes an ML training function; and the third processing machine includes an ML inference function.

[0715] As one embodiment, the fourth processing machine includes an ML testing function.

[0716] As an embodiment, the fourth processor comprises performance monitoring / evaluation of the ML model.

[0717] As an embodiment, the third processor sends first type feedback to the second processor; the first type feedback is used to trigger re-computation or update of the target first type parameter group, i.e. trigger ML initial training or ML re-training.

[0718] As an embodiment, the fourth processor sends second type feedback to the first processor; the second type feedback is used to generate the first data set or the second data set, or the second type feedback is used to trigger sending of the first data set or sending of the second data set.

[0719] As an embodiment, the third processor belongs to the first node, and the fourth processor belongs to the second node.

[0720] As an embodiment, the third processor belongs to the second node in the present application.

[0721] As an embodiment, the first data set comprises training data.

[0722] As an embodiment, the second processor is used to train an ML model, and the trained model is described by the target first type parameter group.

[0723] As an embodiment, the second processor belongs to the first node; the above method avoids passing the first data set to the second node.

[0724] As an embodiment, the second processor belongs to the second node in the present application; the above method supports joint training and optimizes system performance.

[0725] As an embodiment, the second processor belongs to a core network; the above method supports network-wide joint training and further optimizes system performance.

[0726] As an embodiment, the second data set comprises inference data.

[0727] As an embodiment, the third processor constructs a model according to the target first type parameter group, and then inputs the second data set into the constructed model to obtain the first type output.

[0728] As an embodiment, the output of the third processor comprises the first resource block set.

[0729] As one embodiment, the output of the third processor includes a predicted free probability for resource blocks in the first set of resource blocks.

[0730] As one embodiment, the output of the third processor includes resources that can be used for dynamic scheduling triggered by the first node.

[0731] As one sub-embodiment of this embodiment, the resources for dynamic scheduling triggered by the first node include the first set of resource blocks.

[0732] As one sub-embodiment of this embodiment, the resources for dynamic scheduling triggered by the first node include a set of configuration parameters for the first set of resource blocks.

[0733] As one embodiment, the ID of the AI / ML model in this application is updated includes that the first dataset is updated.

[0734] As one embodiment, the ID of the AI / ML model in this application is updated includes that the third processor is updated.

[0735] As one embodiment, the third processor generates a recovery dataset according to the first type of output, and an error of the recovery dataset and the second dataset is used to generate the first type of feedback.

[0736] As one embodiment, the first type of feedback is used to reflect the performance of the trained model; when the performance of the trained model cannot meet the requirements, the second processor will recalculate the target first type of parameter group.

[0737] As one embodiment, when the error is too large or has not been updated for too long a time, the performance of the trained model is considered to be unable to meet the requirements.

[0738] As one embodiment, the target first type of parameter group includes one or more of a convolution kernel, a pool core, a pooling function, an activation function, a parameter of the pooling function, or a parameter of the activation function.

[0739] As one embodiment, the target first type of parameter group includes one or more of a convolution kernel size, a convolution layer number, a convolution step size, a pool core size, a pool core step size, a pooling function, an activation function, or a feature map number.

[0740] Embodiment 15

[0741] Embodiment 15 illustrates an AI or ML based schematic diagram according to an embodiment of the present application, as shown in FIG. 15. In FIG. 15, the first operation and the second operation belong to a first phase, the third operation belongs to a second phase, the fourth operation belongs to a third phase, and the fifth operation belongs to a fourth phase; the arrowed line represents the order of the flow.

[0742] As an embodiment, the first operation comprises AI / ML training, the second operation comprises AI / ML testing, the third operation comprises AI / ML emulation, the fourth operation comprises AI / ML entity loading, and the fifth operation comprises AI / ML inference.

[0743] As an embodiment, the first phase comprises a training phase, the second phase comprises an emulation phase, the third phase comprises a deployment phase, and the fourth phase comprises an inference phase.

[0744] As an embodiment, the first phase comprises AI / ML model training.

[0745] As an embodiment, the first phase comprises AI / ML model training and AI / ML testing.

[0746] As an embodiment, the AI / ML model training comprises initial training and re-training of one or a set of AI / ML entities.

[0747] As an embodiment, the AI / ML model training relies on training data.

[0748] As an embodiment, the AI / ML model training comprises AI / ML entity validation.

[0749] As an embodiment, the AI / ML entity validation is used to evaluate the performance of the AI / ML entity.

[0750] As an embodiment, the AI / ML entity validation relies on validation data.

[0751] As an embodiment, if the result of AI / ML entity validation does not meet the expectation, the AI / ML model will be re-trained.

[0752] As one embodiment, the AI / ML testing includes testing the validated AI / ML entity to estimate the performance of the trained AI / ML model.

[0753] As one embodiment, if the result of the AI / ML testing meets the expectation, the AI / ML entity proceeds to the next stage; otherwise, the AI / ML model will be retrained.

[0754] As one embodiment, the AI / ML testing relies on testing data.

[0755] As one embodiment, the second stage includes AI / ML simulation, which simulates the inference of the AI / ML entity in a simulation environment.

[0756] As one embodiment, the AI / ML simulation estimates the performance of the inference of the AI / ML entity in a simulation environment before the AI / ML entity is used.

[0757] As one embodiment, the second stage is optional.

[0758] As one embodiment, the third stage includes AI / ML entity loading, which is to obtain the trained AI / ML entity to obtain the desired AI / ML inference function.

[0759] As one embodiment, the third stage is optional.

[0760] As one embodiment, the third stage is no longer needed when the training function and the inference function are co-located.

[0761] As one embodiment, the fourth stage includes AI / ML inference.

[0762] As one embodiment, the first resource block set is generated based on the fourth stage.

[0763] Embodiment 16

[0764] Embodiment 16 illustrates a structural block diagram of a processing apparatus in a first node according to one embodiment of the present application, as shown in FIG. 16. In FIG. 16, the processing apparatus 1600 in the first node includes a first receiver 1601 and a first transmitter 1602.

[0765] In embodiment 16, the first receiver 1601 receives a first information block, the first information block indicating a first resource block set; the first transmitter 1602 transmits a second information block, the second information block indicating a first resource set from the first resource block set, the first resource set being for dynamic scheduling.

[0766] In Embodiment 16, the first resource block set is determined based on an AI / ML model; the first resource block set includes K1 resource blocks, the K1 is a positive integer greater than 1, at least two resource blocks in the K1 resource blocks occupy orthogonal time domain resources; the first resource block set depends on the ID of the AI / ML model.

[0767] As an embodiment, the K1 resource blocks included in the first resource block set are idle.

[0768] As an embodiment, the first receiver 1601 receives a first sequence; the first receiver 1601 receives a first signal in the first resource set, or the first transmitter 1602 transmits a first signal in the first resource set; the first sequence confirms the second information block, and the second information block schedules the first signal.

[0769] As an embodiment, the first receiver 1601 receives a first signaling and receives a first signal in a first resource subset; the first signaling depends on the second information block; the first signaling indicates the first resource subset from the first resource set, and the second information block and the first signaling jointly indicate the first signal.

[0770] As an embodiment, the first transmitter 1602 transmits a first signal in a second resource subset; the first resource set includes a plurality of resource subsets, and the second resource subset is one of the plurality of resource subsets.

[0771] As an embodiment, the K1 resource blocks are orthogonal in the time domain, the second information block is used to indicate K1 resource subsets from the K1 resource blocks, and the first resource set includes the K1 resource subsets.

[0772] As an embodiment, the ID of the AI / ML model to which the first resource block set depends on is updated, and the first resource block set is reset.

[0773] As an embodiment, the first information block includes a configuration parameter set for the first resource block set, and the configuration parameter set includes at least one of a power parameter or a spatial parameter.

[0774] As an embodiment, the configuration parameter set includes a predicted idle probability for a resource block in the first resource block set.

[0775] As an embodiment, the first resource set is configured with different resource allocation manners in different channel states, and an optional implementation manner is that the first node indicates whether the first resource set is based on continuous resource allocation or discrete resource allocation in the second information block; another optional implementation manner is that the second node indicates the resource allocation manner of the first resource set through a higher layer parameter, and the higher layer parameter can be transmitted through the first information block.

[0776] As an embodiment, the first resource block set is determined by an AI entity based on AI / ML model prediction or inference, and the AI entity is located at a network side, interacts with a network device, or is located inside the network device.

[0777] As an embodiment, the first information block is UE-specific.

[0778] As an embodiment, the first information block is UE group-specific, and the UE group includes the first node.

[0779] As an embodiment, the first resource block set is UE-specific.

[0780] As an embodiment, the first resource block set is UE group-specific.

[0781] As an embodiment, the first resource set is for UE-triggered dynamically scheduled transmission.

[0782] As an embodiment, UE-triggered dynamic scheduling occupies resources in the first resource set.

[0783] As an embodiment, the first node 1600 is a user equipment.

[0784] As an embodiment, the first node 1600 is a terminal.

[0785] As an embodiment, the first node 1600 is a relay node device.

[0786] As an embodiment, the first receiver 1601 includes at least one of {the antenna 452, the receiver 454, the receiving processor 456, the multi-antenna receiving processor 458, the controller / processor 459, the memory 460, the data source 467} in Embodiment 4.

[0787] As one embodiment, the first transmitter 1602 includes at least one of {the antenna 452, the transmitter 454, the transmit processor 468, the multi-antenna transmit processor 457, the controller / processor 459, the memory 460, the data source 467} in embodiment 4.

[0788] Embodiment 17

[0789] Embodiment 17 illustrates a structural block diagram of a processing apparatus in a second node according to an embodiment of the present application, as shown in FIG. 17. In FIG. 17, the processing apparatus 1700 in the second node includes a second transmitter 1701 and a second receiver 1702.

[0790] In embodiment 17, the second transmitter 1701 transmits a first information block, the first information block indicating a first resource block set; the second receiver 1702 receives a second information block, the second information block indicating a first resource set from the first resource block set, the first resource set being for dynamic scheduling.

[0791] In embodiment 17, the first resource block set is determined based on an AI / ML model; the first resource block set includes K1 resource blocks, the K1 being a positive integer greater than 1, at least two resource blocks in the K1 resource blocks occupying time domain resources that are orthogonal; the first resource block set depends on an ID of the AI / ML model.

[0792] As one embodiment, the K1 resource blocks included in the first resource block set are idle.

[0793] As one embodiment, the second transmitter 1701 transmits a first sequence; the second transmitter 1701 transmits a first signal in the first resource set, or the second receiver 1702 receives a first signal in the first resource set;

[0794] wherein the first sequence confirms the second information block, the second information block scheduling the first signal.

[0795] As one embodiment, the second transmitter 1701 transmits a first signaling and a first signal in a first resource subset; the first signaling depends on the second information block; the first signaling indicates the first resource subset from the first resource set, the second information block and the first signaling jointly indicating the first signal.

[0796] As one embodiment, the second receiver 1702 receives a first signal in a second resource subset;

[0797] The first resource set includes a plurality of resource subsets, and the second resource subset is one of the plurality of resource subsets.

[0798] As an embodiment, the K1 resource blocks are orthogonal in the time domain, and the second information block is used to indicate K1 resource subsets from the K1 resource blocks, and the first resource set includes the K1 resource subsets.

[0799] As an embodiment, the ID of the AI / ML model relied on by the first resource block set is updated, and the first resource block set is reset.

[0800] As an embodiment, the first information block includes a set of configuration parameters for the first resource block set, and the set of configuration parameters includes at least one of a power parameter or a spatial parameter.

[0801] As an embodiment, the set of configuration parameters includes a predicted idle probability for a resource block in the first resource block set.

[0802] As an embodiment, the first resource set in this application supports different resource allocation modes in different channel states, and an optional implementation is that the first node can indicate in the second information block whether the first resource set is based on continuous resource allocation or discrete resource allocation; another optional implementation is that the second node indicates the resource allocation mode of the first resource set through a higher layer parameter in this application, and the higher layer parameter can be transmitted through the first information block.

[0803] As an embodiment, the first resource block set is determined by an AI entity based on AI / ML model prediction or inference, and the AI entity is located at the network side, interacts with the network device, or is located inside the network device.

[0804] As an embodiment, the first information block is UE-specific.

[0805] As an embodiment, the first information block is UE group-specific, and the UE group includes the first node.

[0806] As an embodiment, the first resource block set is UE-specific.

[0807] As an embodiment, the first resource block set is UE group-specific.

[0808] As an embodiment, the first resource set is for UE-triggered dynamically scheduled transmission.

[0809] As an embodiment, UE-triggered dynamic scheduling occupies resources in the first resource set.

[0810] As one embodiment, the second node 1700 is a base station device.

[0811] As one embodiment, the second node 1700 is a user equipment.

[0812] As one embodiment, the second node 1700 is a TRP.

[0813] As one embodiment, the second transmitter 1701 includes at least one of {the antenna 420, the transmitter 418, the transmit processor 417, the multi-antenna transmit processor 471, the controller / processor 475, the memory 476} in embodiment 4.

[0814] As one embodiment, the second receiver 1702 includes at least one of {the antenna 420, the receiver 418, the receive processor 470, the multi-antenna receive processor 472, the controller / processor 475, the memory 476} in embodiment 4.

[0815] Those skilled in the art can understand that all or part of the steps in the foregoing method can be instructed by programs to related hardware, and the programs can be stored in a computer readable storage medium, such as a read-only memory, a hard disk, an optical disk or the like. Alternatively, all or part of the steps of the foregoing embodiments can also be implemented using one or more integrated circuits. Correspondingly, each module unit in the foregoing embodiments can be implemented in the form of hardware or in the form of a software function module, and the present application is not limited to any specific form of combination of software and hardware. The user equipment, terminal and UE in the present application include but are not limited to unmanned aerial vehicles, communication modules on unmanned aerial vehicles, remote control aircraft, aircraft, small aircraft, mobile phones, tablet computers, notebook computers, vehicle-mounted communication devices, vehicles, vehicles, RSUs, wireless sensors, network cards, Internet of Things terminals, RFID (Radio Frequency Identification) terminals, NB-IoT (Narrow Band Internet of Things) terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, network cards, vehicle-mounted communication devices, low-cost mobile phones, low-cost tablet computers and other wireless communication devices. The base station or system device in the present application includes but is not limited to macro cellular base stations, micro cellular base stations, small cellular base stations, home base stations, relay base stations, eNB (evolved Node B), gNB, TRP, GNSS (Global Navigation Satellite System), relay satellites, satellite base stations, air base stations, RSUs, unmanned aerial vehicles, test equipment such as wireless communication devices that simulate part of the functions of base stations or signaling testers, and the like.

[0816] Those skilled in the art will understand that the application can be implemented by other specified forms without departing from the core or essential characteristics thereof. Therefore, the presently disclosed embodiments should in no way be considered as descriptive rather than limiting. The scope of the application is determined by the appended claims rather than the preceding description, and all modifications within the equivalent meaning and range of the claims are considered to be included therein.

Claims

1. A first node for wireless communication and artificial intelligence, characterized in that, Comprising: a first receiver that receives a first information block, the first information block indicating a first set of resource blocks; a first transmitter that transmits a second information block, the second information block indicating a first set of resources from the first set of resource blocks, the first set of resources for dynamic scheduling; wherein the first set of resource blocks is determined based on an AI / ML model; the first set of resource blocks comprises K1 resource blocks, the K1 being a positive integer greater than 1, at least two of the K1 resource blocks occupying time domain resources that are orthogonal; the first set of resource blocks depends on an ID of the AI / ML model.

2. The first node of claim 1, characterized in that, The K1 resource blocks comprised by the first set of resource blocks are idle.

3. The first node of claim 1 or 2, wherein, Comprising: the first receiver that receives a first sequence; the first receiver that receives a first signal in the first set of resources; or, the first transmitter that transmits a first signal in the first set of resources; wherein the first sequence acknowledges the second information block, the second information block scheduling the first signal.

4. The first node of claim 1 or 2, wherein, Comprising: the first receiver that receives a first signaling and receives a first signal in a first subset of resources; wherein the first signaling depends on the second information block; the first signaling indicates the first subset of resources from the first set of resources, the second information block and the first signaling jointly indicating the first signal.

5. The first node of claim 1 or 2, wherein, Comprising: the first transmitter that transmits a first signal in a second subset of resources; wherein the first set of resources comprises a plurality of resource subsets, the second subset of resources being one of the plurality of resource subsets.

6. The first node of any of claims 1 to 5, wherein, The K1 resource blocks are orthogonal in time domain, the second information block being used to indicate K1 resource subsets from the K1 resource blocks, the first set of resources comprising the K1 resource subsets.

7. The first node of any of claims 1-6, wherein, The ID of the AI / ML model on which the first set of resource blocks depends is updated, the first set of resource blocks being reset.

8. The first node of any of claims 1-7, wherein, The first information block comprises a set of configuration parameters for the first set of resource blocks, the set of configuration parameters comprising at least one of a power parameter or a spatial parameter.

9. The first node of claim 8, wherein, The set of configuration parameters comprises a predicted idle probability for a resource block in the first set of resource blocks. 10.A second node for wireless communication and artificial intelligence, comprising: Comprising: a second transmitter that transmits a first information block, the first information block indicating a first set of resource blocks; a second receiver that receives a second information block, the second information block indicating a first set of resources from the first set of resource blocks, the first set of resources for dynamic scheduling; wherein the first set of resource blocks is determined based on an AI / ML model; the first set of resource blocks comprises K1 resource blocks, the K1 being a positive integer greater than 1, at least two of the K1 resource blocks occupying time domain resources that are orthogonal; the first set of resource blocks depends on an ID of the AI / ML model.

11. A method for a first node of wireless communication and artificial intelligence, characterized in that, Comprising: receiving a first information block, the first information block indicating a first set of resource blocks; transmitting a second information block, the second information block indicating a first set of resources from the first set of resource blocks, the first set of resources for dynamic scheduling; The first resource block set is determined based on an AI / ML model; the first resource block set includes K1 resource blocks, K1 is a positive integer greater than 1, at least two resource blocks in the K1 resource blocks occupy orthogonal time domain resources; and the first resource block set depends on an ID of the AI / ML model. 12.A method for a second node of wireless communication and artificial intelligence, characterized in that, Comprise: sending a first information block, the first information block indicating a first resource block set; receiving a second information block, the second information block indicating a first resource set from the first resource block set, the first resource set being dynamically scheduled; The first resource block set is determined based on an AI / ML model; the first resource block set includes K1 resource blocks, K1 is a positive integer greater than 1, at least two resource blocks in the K1 resource blocks occupy orthogonal time domain resources; and the first resource block set depends on an ID of the AI / ML model.

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