CN115499901A

CN115499901A - Method for determining time-frequency resource to be monitored, terminal equipment and network equipment

Info

Publication number: CN115499901A
Application number: CN202110678493.4A
Authority: CN
Inventors: 石聪; 尤心
Original assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd
Current assignee: Guangdong Oppo Mobile Telecommunications Corp Ltd
Priority date: 2021-06-18
Filing date: 2021-06-18
Publication date: 2022-12-20

Abstract

The embodiment of the application discloses a method for determining time-frequency resources to be monitored, terminal equipment and network equipment, which are applied to the technical field of communication and can solve the problem that the power consumption of the terminal equipment is large due to the fact that the data transceiving behavior of the terminal equipment is controlled based on the network equipment at present. The method comprises the following steps: receiving at least one traffic prediction model indicated by the network device; determining a first time-frequency resource to be monitored according to the first service prediction model; the first business prediction model is one of at least one business prediction model.

Description

Method for determining time-frequency resource to be monitored, terminal equipment and network equipment

Technical Field

The embodiment of the application relates to the technical field of communication, in particular to a method for determining a time-frequency resource to be monitored, a terminal device and a network device.

Background

In the existing communication system, a network device generally issues configuration parameters or data receiving behaviors for a terminal device, so as to achieve the effect of saving power for the terminal device. Specifically, the network device may determine the service activity of the current connection state of the terminal device based on the collected information (the service characteristics of the terminal device, the feedback information of the terminal device, and the like), so as to determine whether to change the configuration parameter or the data transceiving behavior of the terminal device. However, such a mechanism based on network device control does not necessarily achieve a good power saving effect. For example, for related configuration parameters of Discontinuous Reception (DRX) configured by the network device, the terminal wakes up to enter Active Time (Active Time) to monitor the downlink control channel many times, but the terminal may not be able to monitor the downlink control channel in the Active Time period, so that the terminal device continues to monitor the downlink control channel during the Active Time period. Therefore, the problem that the power consumption of the terminal equipment is large still exists when the monitoring behavior of the terminal equipment is controlled based on the network equipment at present.

Disclosure of Invention

The embodiment of the application provides a method for determining a time-frequency resource to be monitored, which is used for solving the problem that the power consumption of terminal equipment is larger because the monitoring behavior of the terminal equipment is controlled based on network equipment at present.

In order to solve the above technical problem, the embodiment of the present application is implemented as follows:

in a first aspect, a method for determining time-frequency resources to be monitored is provided, including:

receiving at least one traffic prediction model indicated by the network device;

determining a first time-frequency resource to be monitored according to the first service prediction model;

wherein the first traffic prediction model is one of the at least one traffic prediction model.

In a second aspect, a method for determining a time-frequency resource with listening is provided, including:

transmitting at least one service prediction model to the terminal device; and each service prediction model in the at least one service prediction model is used for determining time-frequency resources to be monitored.

In a third aspect, a terminal device is provided, including:

the receiving module is used for receiving at least one service prediction model indicated by the network equipment;

the processing module is used for determining a first time-frequency resource to be monitored according to the first service prediction model;

In a fourth aspect, a network device is provided, comprising:

the sending module is used for sending at least one service prediction model to the terminal equipment; and each service prediction model in the at least one service prediction model is used for determining time-frequency resources to be monitored.

In a fifth aspect, a terminal device is provided, which includes: a transceiver, a processor, a memory and a computer program stored on the memory and executable on the processor, the computer program, when executed by the transceiver and the processor, implementing the method for determining a time-frequency resource to listen to as described in the first aspect.

In a sixth aspect, a network device is provided, comprising: a transceiver, a processor, a memory and a computer program stored on the memory and executable on the processor, the computer program, when executed by the transceiver and the processor, implementing the method for determining a time-frequency resource to listen to as described in the second aspect.

In a seventh aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when executed by a processor, the computer program implements the method for determining a time-frequency resource to be listened according to the first aspect or the second aspect.

In an eighth aspect, a computer program product is provided, which stores a computer program that, when being executed by a processor, implements the method for determining a time-frequency resource to be monitored according to the first aspect or the second aspect.

The embodiment of the application provides a method for determining time-frequency resources to be monitored, in which a terminal device may receive at least one service prediction model indicated by a network device, and determine a first time-frequency resource to be monitored according to a first service prediction model therein; the first business prediction model is one of at least one business prediction model. Through the scheme, the terminal equipment can predict the time-frequency resource to be monitored in the future according to the service prediction model indicated by the network equipment, so that compared with a mode that the network equipment controls the monitoring behavior of the terminal equipment, the receiving performance can be ensured, meanwhile, the terminal equipment is not completely controlled by the network equipment, and the problem that the power consumption of the terminal equipment is large can be further improved.

Drawings

Fig. 1 is a schematic diagram of a DRX mechanism according to an embodiment of the present disclosure;

fig. 2 is a schematic diagram of dividing the entire bandwidth into specific bandwidth portions according to an embodiment of the present application;

fig. 3 is a schematic diagram of a basic structure of a neural network according to an embodiment of the present disclosure;

FIG. 4 is a schematic diagram of a convolutional neural network according to an embodiment of the present application;

fig. 5A is a first schematic diagram of a method for determining time-frequency resources to be monitored according to an embodiment of the present application;

fig. 5B is a schematic diagram illustrating a second method for determining time-frequency resources to be monitored according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of a terminal device according to an embodiment of the present application;

fig. 7 is a schematic structural diagram of a network device according to an embodiment of the present application;

fig. 8 is a schematic hardware structure diagram of a terminal device according to an embodiment of the present application;

fig. 9 is a schematic hardware structure diagram of a network device according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.

The term "and/or" in this application is only one kind of association relationship describing the associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The symbol "/" herein denotes an association of or, e.g., a/B denotes a or B.

First, the related technical contents of the embodiments of the present application are introduced:

in the 5G NR technology, in order to save power consumption of a terminal device, some related technologies are introduced:

(1) DRX mechanism

From the perspective of time domain resources, based on a connected DRX mechanism, as shown in TS 38.300 in a standard protocol, when a terminal device is in a connected state, DRX related configuration information configured by a network device may be received, and the DRX related configuration information may pass through a plurality of preconfigured timers, so that the terminal device may monitor a control channel of the network device according to a certain time rule, and thus the network device may schedule the terminal device in time when a service arrives.

Fig. 1 shows a schematic diagram of a DRX mechanism, where relevant configuration parameters of DRX include: a DRX cycle (DRX cycle) and an On Duration (On Duration) according to the DRX cycle start, the Duration belonging to an Active Time (Active Time), and a sleep Time (Opportunity of DRX), also called inactive Time, within the DRX cycle. The activation time includes a time that the UE needs to listen due to other actions, such as a listening event initiated due to scheduling of new data. In the Active Time, the terminal device needs to monitor a Physical Downlink Control Channel (PDCCH), and may not monitor the PDCCH in the sleep Time, periodically wake up the terminal device according to the DRX cycle, and monitor the corresponding Control Channel in the Active Time. Meanwhile, according to a specific scheduling condition and based on a configured activation timer (inactivity timer), the terminal device may further dynamically extend the wake-up duration (i.e., the length of the activation time) to achieve the purpose of continuous monitoring.

According to the DRX mechanism of the connection state, the terminal equipment can determine the activation Time of monitoring the downlink control channel in the Time domain, the terminal equipment needs to continuously monitor the downlink control channel in the Active Time, and the terminal equipment does not need to monitor the downlink control channel in the non-activation Time, so that the aim of saving electricity is fulfilled.

(2) Concept of BWP

From the perspective of frequency domain resources, 5G NR introduces the concept of BWP. BWP is a bandwidth part, that is, by dividing the whole bandwidth into specific bandwidth parts, the network device can dynamically control the active bandwidth part where the terminal device is located, so as to improve the data transmission efficiency and save power.

The terminal supports bandwidth parts of different sizes in the frequency domain, and when data traffic is active, the network can switch the terminal to BWP with a larger bandwidth, thereby being able to support high data rate. When the data service is inactive, the network can switch the terminal to the BWP with small bandwidth, thereby achieving the purpose of saving power. Illustratively, in the standard protocol TS 38.300, as shown in fig. 2 below, a schematic diagram of dividing the whole bandwidth into specific bandwidth parts is shown, where BWP1 has a bandwidth of 40MHz, and the bandwidth is relatively large but short in duration; the bandwidth of BWP2 is 10MHz, the bandwidth is smaller, but the duration is long; the bandwidth of BWP3 is 20MHz. When data traffic is active, the network device may switch the terminal device to BWP1 shown in fig. 2 with a larger bandwidth, thereby being able to support high data rates. When the data traffic is not active, the network may switch the terminal device to BWP2 with a small bandwidth as shown in fig. 2, thereby achieving the purpose of power saving.

Furthermore, in NR, the concept of Dormant BWP (Dormant BWP) is introduced to achieve the purpose of further power saving. The dormant BWP is a special BWP on which the end device does not need to listen to the downlink control channel. The dormant BWP is generally applicable to Secondary cells (scells), which are cells operating on a Secondary band. Once the RRC connection between the network device and the terminal device is established, the secondary cell may be configured to provide additional radio resources.

(3) Basic case of artificial intelligence

In recent years, artificial intelligence research represented by Neural Networks (NN) has achieved a great deal of effort in many fields, and it will also play an important role in the production and life of people for a long time in the future.

As shown in fig. 3, a basic structure of a neural network includes: an input layer, a hidden layer and an output layer. The input layer is responsible for receiving data, the hidden layer is responsible for processing the data, and the final result is generated at the output layer. In this case, each node represents a processing unit, which may be considered as a simulation of a neuron, a plurality of neurons form a layer of neural network, and a whole neural network is constructed by multi-layer information transmission and processing.

With the continuous development of neural network research, in recent years, a neural network deep learning algorithm is proposed, more hidden layers are introduced, characteristic learning is carried out through layer-by-layer training of the neural network with multiple hidden layers, the learning and processing capabilities of the neural network are greatly improved, and the neural network deep learning algorithm is widely applied to the aspects of pattern recognition, signal processing, optimal combination, abnormal detection and the like.

Similarly, with the development of deep learning, convolutional Neural Networks (CNN) have been proposed in recent years. As shown in fig. 4, a schematic diagram of a convolutional neural network is shown, and a basic structure of the convolutional neural network includes: the device comprises an input layer, a plurality of convolution layers, a plurality of pooling layers, a full-link layer and an output layer. In the convolutional neural network, the introduction of the convolutional layer and the pooling layer effectively controls the sharp increase of network parameters, limits the number of the parameters, excavates the characteristics of a local structure and improves the robustness of the algorithm.

In an existing communication system, a network device generally issues configuration parameters or data receiving behaviors for a terminal device to achieve an effect of saving power for the terminal device. Specifically, the network device may determine the service activity of the current connection state of the terminal device based on the collected information (the service characteristics of the terminal device, the feedback information of the terminal device, and the like), so as to determine whether to change the configuration parameter or the data transceiving behavior of the terminal device. However, such a mechanism based on network device control does not necessarily achieve a good power saving effect. For example, for relevant configuration parameters of DRX configured by a network device, a terminal wakes up to enter an activation time many times to monitor a downlink control channel, but the terminal may not be able to monitor the downlink control channel in the activation time, so that the terminal device continues to monitor a process of the downlink control channel in the activation time. Therefore, the problem that the power consumption of the terminal equipment is large still exists when the monitoring behavior of the terminal equipment is controlled based on the network equipment at present.

With the improvement of the processing capability of the terminal equipment and the introduction of Artificial Intelligence (AI) capability in the terminal equipment, the terminal equipment can achieve certain service prediction accuracy based on a proper AI model. Under the condition, the AI-based terminal side service prediction can further improve the power saving and ensure the data transceiving performance, so the embodiment of the application provides a method for determining the time-frequency resource to be monitored, and the terminal equipment can receive at least one service prediction model indicated by the network equipment; determining a first time-frequency resource to be monitored according to the first service prediction model; the first business prediction model is one of at least one business prediction model. Compared with the mode that the network equipment controls the monitoring behavior of the terminal equipment, the method can ensure the receiving performance and is not completely controlled by the network equipment, and the problem of larger power consumption of the terminal equipment can be further solved.

In this embodiment, the terminal device may be referred to as a User Equipment (UE), an access terminal, a subscriber unit, a subscriber station, a mobile station, a remote terminal, a mobile device, a user terminal, a wireless communication device, a user agent, a user equipment, or the like.

The terminal device may be a Station (ST) in a WLAN, and may be a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a Wireless Local Loop (WLL) station, a Personal digital assistant (pda) device, a handheld device with Wireless communication capability, a computing device or other processing device connected to a Wireless modem, a vehicle-mounted device, a wearable device, a terminal device in a next generation communication system such as an NR Network, or a terminal device in a future evolved Public Land Mobile Network (PLMN) Network, and so on. In the embodiment of the application, the terminal equipment can be deployed on land, including indoor or outdoor, handheld, wearable or vehicle-mounted; can also be deployed on the water surface (such as a ship and the like); and may also be deployed in the air (e.g., airplanes, balloons, satellites, etc.).

In the embodiment of the present application, the terminal device may be a Mobile Phone (Mobile Phone), a tablet personal computer (Pad), a computer with a wireless transceiving function, a Virtual Reality (VR) terminal device, an Augmented Reality (AR) terminal device, a wireless terminal device in industrial control (industrial control), a wireless terminal device in unmanned driving (self driving), a wireless terminal device in remote medical treatment (remote medical), a wireless terminal device in smart grid (smart grid), a wireless terminal device in transportation safety (transportation safety), a wireless terminal device in smart city (smart city), a wireless terminal device in smart home (smart home), or the like.

By way of example and not limitation, in the embodiments of the present application, the terminal device may also be a wearable device. Wearable equipment can also be called wearable intelligent equipment, is the general term of applying wearable technique to carry out intelligent design, develop the equipment that can dress to daily wearing, like glasses, gloves, wrist-watch, dress and shoes etc.. A wearable device is a portable device that is worn directly on the body or integrated into the clothing or accessories of the user. The wearable device is not only a hardware device, but also realizes powerful functions through software support, data interaction and cloud interaction. The generalized wearable smart device has full functions and large size, and can realize complete or partial functions without depending on a smart phone, for example: smart watches or smart glasses and the like, and only focus on a certain type of application functions, and need to be used in cooperation with other devices such as smart phones, such as various smart bracelets for physical sign monitoring, smart jewelry and the like.

The network device related to the embodiment of the present application may be an access network device. The access network device may be a long-term evolution (LTE) system, a Next Radio (NR) system, or an evolved base station (evolved Node B) in an authorized assisted access long-term evolution (LAA-LTE) system, such as an eNB or an e-NodeB) macro base station, a micro base station (also referred to as a "small base station"), a pico base station, an Access Point (AP), a Transmission Point (TP), or a new generation base station (g-NodeB). In this embodiment of the present application, the network device may be a device for communicating with a mobile device, and the network device may be an Access Point (AP) in a WLAN, a Base Station (BTS) in GSM or CDMA, a Base Station (NodeB, NB) in WCDMA, an evolved Node B (eNB or eNodeB) in LTE, a relay Station or an Access Point, a vehicle-mounted device, a wearable device, and a network device (gNB) in an NR network, or a network device in a PLMN network for future evolution, or a network device in an NTN network. In this embodiment of the present application, a network device may provide a service for a cell, and a terminal device communicates with the network device through a transmission resource (e.g., a frequency domain resource or a spectrum resource) used by the cell, where the cell may be a cell corresponding to the network device (e.g., a base station), and the cell may belong to a macro base station or a base station corresponding to a Small cell (Small cell), where the Small cell may include: urban cells (Metro cells), micro cells (Micro cells), pico cells (Pico cells), femto cells (Femto cells), and the like, and the small cells have the characteristics of small coverage area and low transmission power, and are suitable for providing high-rate data transmission services.

The technical scheme of the embodiment of the application can be applied to various communication systems, for example: global System for Mobile communications (GSM) System, code Division Multiple Access (CDMA) System, wideband Code Division Multiple Access (WCDMA) System, general Packet Radio Service (GPRS), long Term Evolution (Long Term Evolution, LTE) System, LTE-a System, new Radio (NR) System, evolution System of NR System, LTE-based Access to unlicensed spectrum, LTE-U) System, NR-based to unlicensed spectrum (NR-U) System, non-Terrestrial communication network (NTN) System, universal Mobile Telecommunications System (UMTS), wireless Local Area Network (WLAN), wireless Fidelity (WiFi), 5th-Generation (5G) System, or other communication systems.

In this embodiment, the terminal device may be a Mobile Phone (Mobile Phone), a tablet computer (Pad), a computer with a wireless transceiving function, a Virtual Reality (VR) terminal device, an Augmented Reality (AR) terminal device, a wireless terminal device in industrial control (industrial control), a wireless terminal device in self driving (self driving), a wireless terminal device in remote medical (remote medical), a wireless terminal device in smart grid (smart grid), a wireless terminal device in transportation safety (transportation safety), a wireless terminal device in city (smart city), a wireless terminal device in smart home (smart home), or the like.

By way of example and not limitation, in the embodiments of the present application, the terminal device may also be a wearable device. Wearable equipment can also be called wearable intelligent equipment, is the general term of equipment that uses wearable technique to carry out intelligent design, develop can dress to daily wearing, such as glasses, gloves, wrist-watch, dress and shoes. The wearable device may be worn directly on the body or may be a portable device integrated into the user's clothing or accessory. The wearable device is not only a hardware device, but also realizes powerful functions through software support, data interaction and cloud interaction. The generalized wearable smart device has full functions and large size, and can realize complete or partial functions without depending on a smart phone, for example: smart watches or smart glasses and the like, and only focus on a certain type of application function, and need to be matched with other equipment such as a smart phone for use, such as various smart bracelets for physical sign monitoring, smart jewelry and the like.

The network device related to the embodiment of the present application may be an access network device. The access network device may be an evolved Node B (eNB or e-NodeB) macro base station, a micro base station (also referred to as a "small base station"), a pico base station, an Access Point (AP), a Transmission Point (TP), a new generation base station (NodeB), or the like in a long-term evolution (LTE) system. In this embodiment, a network device may provide a service for a cell, and a terminal device communicates with the network device through a transmission resource (for example, a frequency domain resource or a spectrum resource) used by the cell, where the cell may be a cell corresponding to the network device (for example, a base station), and the cell may belong to a macro base station or a base station corresponding to a Small cell (Small cell), where the Small cell may include: urban cells (Metro cells), micro cells (Micro cells), pico cells (Pico cells), femto cells (Femto cells), and the like, and the small cells have the characteristics of small coverage area and low transmission power, and are suitable for providing high-rate data transmission services.

It should be understood that the terms "system" and "network" are often used interchangeably herein. The term "and/or" herein is merely an association relationship describing an associated object, and means that there may be three relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter associated objects are in an "or" relationship. It should be understood that "indication" mentioned in the embodiments of the present application may be a direct indication, an indirect indication, or an indication of an association relationship. For example, a indicates B, which may indicate that a directly indicates B, e.g., B may be obtained by a; it may also mean that a indicates B indirectly, e.g. a indicates C, by which B may be obtained; it can also mean that there is an association between a and B. In the description of the embodiments of the present application, the term "correspond" may indicate that there is a direct correspondence or an indirect correspondence between the two, may also indicate that there is an association between the two, and may also indicate and is indicated, configure and is configured, and the like. Optionally, the indication or the indication Information in the embodiment of the present application includes at least one of physical layer signaling, for example, downlink Control Information (DCI), radio Resource Control (RRC) signaling, and Media Access Control Element (MAC CE). Optionally, the high layer parameter or the high layer signaling in the embodiment of the present application includes at least one of a Radio Resource Control (RRC) signaling and a Media Access Control Element (MAC CE).

As shown in fig. 5A, an embodiment of the present application provides a method for determining a time-frequency resource to be monitored, where the method includes:

501. the network device indicates at least one traffic prediction model to the terminal device.

Correspondingly, the terminal equipment receives at least one service prediction model indicated by the network equipment.

Each service prediction model in the at least one service prediction model is used for determining time-frequency resources to be monitored.

In the embodiment of the present application, the time-frequency resources to be monitored (including the first time-domain resource to be monitored and the second time-domain resource to be monitored) include: frequency domain resources to be monitored, and/or time domain resources to be monitored.

Optionally, the at least one traffic prediction model is indicated by at least one of the following modes:

RRC signaling, MAC CE, DCI.

In the embodiments related to the present application, the traffic prediction model refers to an AI-based neural network model. It can be considered that, in the service prediction model of the present application, each AI-based initial neural network model is pre-trained. Optionally, the historical monitoring result of the terminal device may be used as a sample, and the initial neural network model is pre-trained to obtain the service prediction model in the embodiment of the present application.

Optionally, the at least one service prediction model may each include the following cases:

1) A traffic prediction model for time domain resources;

2) A traffic prediction model for frequency domain resources;

3) Traffic prediction models for time domain resources and frequency domain resources.

Optionally, each of the at least one service prediction model corresponds to at least one service type. That is, one service prediction model may be used to predict the time-frequency resource to be monitored for one service type, or one service prediction model may be used to predict the time-frequency resource to be monitored for multiple service types.

In one implementation: the service type may correspond to a Data Radio Bearer (DRB) configured in the terminal device; that is, several DRBs are configured in the terminal device to correspond to several service types, and different DRBs correspond to different service types.

In another implementation: the specific service type in the service types may correspond to a specific terminal type, for example, the internet of things type terminal supports a certain service type, such as a service type of video monitoring, or environmental monitoring. For example, for some low-capability terminal types, one or a limited number of service types are supported, and the terminal may better predict the service arrival situation through a service prediction model.

Optionally, the service type may include, but is not limited to, at least one of the following:

telephone service, telegraph service, facsimile service, broadcast television service, data communication service, and the like.

Optionally, the network device may send an initial monitoring state indication to the terminal device; accordingly, the terminal device may receive the initial listening state indication sent by the network device. The initial listening state indication is used for indicating that the listening is not performed by default, or the initial listening state indication is used for indicating that the listening is performed by default.

That is to say, under the condition that the initial monitoring state indicates default non-monitoring, the terminal device does not adopt the at least one service prediction model to predict the time-frequency resource to be monitored, and does not monitor the time-frequency resource before determining to monitor the resource; and under the condition that the initial monitoring state indicates default monitoring, the terminal equipment continuously monitors the time-frequency resources before the terminal equipment adopts the at least one service prediction model to predict the time-frequency resources to be monitored and determines to monitor the resources.

Optionally, the network device may send at least one of the following indications to the terminal device:

a prediction function start indication for indicating that the at least one service prediction model is allowed to be used to determine time-frequency resources to be monitored;

and the prediction function closing indication is used for indicating that the at least one service prediction model is forbidden to be used and determining the time-frequency resource to be monitored.

Correspondingly, the terminal device may receive the at least one instruction sent by the network device, and may learn whether the at least one service prediction model may be used after receiving the instruction.

Optionally, after receiving the prediction function start instruction, the terminal device determines that the at least one service prediction model can be used to predict the time-frequency resource to be monitored; after receiving the prediction function shutdown indication, the terminal device may determine that the time-frequency resource to be monitored cannot be predicted by using the at least one service prediction model.

502. And the terminal equipment determines a first time-frequency resource to be monitored according to the first service prediction model.

The first business prediction model is one of at least one business prediction model.

Optionally, the first time-frequency resource to be monitored includes at least one of the following:

(1) At least one downlink control channel;

(2) Monitoring the monitoring time of the at least one downlink control channel;

optionally, when the first time-frequency resource to be monitored only includes at least one downlink control channel, the monitoring time for monitoring the at least one downlink control channel may be configured by the network device.

Optionally, in the case that the first to-be-monitored time-frequency resource only includes a monitoring opportunity for monitoring the at least one downlink control channel, the at least one downlink control channel may be configured by the network device.

In another optional implementation manner, the listening opportunity to listen to the at least one downlink control channel may also be indicated by means of a reverse direction indication. For example, the first time-frequency resource to be monitored includes:

(1, 1) at least one downlink control channel;

(2, 1) not monitoring the monitoring time of the at least one downlink control channel;

that is, the monitoring time for monitoring the at least one downlink control channel may be determined according to the monitoring time for not monitoring the at least one downlink control channel.

In another alternative implementation, the monitoring occasion for not monitoring the at least one downlink control channel may be indicated simultaneously on the basis of indicating the monitoring occasion for monitoring the at least one downlink control channel. For example, the first time-frequency resource to be monitored includes:

(1, 2) at least one downlink control channel;

(2, 2) not monitoring the monitoring time of the at least one downlink control channel;

and (3, 2) monitoring the monitoring time of the at least one downlink control channel.

Optionally, the at least one downlink control channel is a downlink control channel configured on the active BWP.

Optionally, the at least one downlink control channel is a downlink control channel scrambled by the first identifier.

Optionally, the network device may send the first identifier scrambling instruction to the terminal device, and correspondingly, the terminal device may receive the first identifier scrambling instruction sent by the network device. The first identifier scrambling indication is used for indicating to monitor a downlink control channel scrambled by the first identifier.

The downlink control channel may be scrambled by using different identifiers, where the Identifier is a Radio Network Temporary Identifier (RNTI). Optionally, the following scrambling schemes may be included but not limited to:

scrambling is performed using System Information RNTI (SI-RNTI);

scrambling by using Paging RNTI (P-RNTI);

scrambling using Random Access RNTI (RA-RNTI);

scrambling by using Temporary Cell RNTI (TC-RNTI);

scrambling by using Cell RNTI (C-RNTI);

scrambling is performed using Semi-persistent Scheduling cell RNTI (Semi persistent Scheduling C-RNTI, SPS-C-RNTI).

Optionally, the monitoring time includes at least one of the following:

a monitoring start time, a monitoring end time, a monitoring duration, at least one time period, and a monitoring period.

For different listening occasions, implementations may include, but are not limited to, the following:

(a) One possible implementation: the monitoring time includes a monitoring start time and a monitoring end time, and then a monitoring time period can be determined according to the monitoring start time and the monitoring end time, and the at least one downlink control channel is monitored in the determined monitoring time period.

For example, assuming that the listening start time is T1 and the listening end time is T2, the at least one downlink control channel may be listened to for a time period between T1 and T2.

(b) One possible implementation: the monitoring time includes a monitoring start time, and a monitoring end time is configured by the network device, or is predefined by a protocol, and the monitoring time period may also be determined, and the at least one downlink control channel is monitored in the determined monitoring time period.

For example, assuming that the listening start time is T1 and the listening end time configured by the network device is T3, the at least one downlink control channel may be listened to in a time period between T1 and T3. T3 may be the timeout of a timer configured by the network; if the timer is overtime, the terminal equipment ends the monitoring.

(c) One possible implementation: the monitoring time includes a monitoring ending time, the monitoring starting time is configured by the network device, or is predefined by a protocol, and a monitoring time period can also be determined, and the at least one downlink control channel is monitored in the determined monitoring time period.

For example, assuming that the monitoring start time configured by the network device is T4 and the monitoring end time is T2, the at least one downlink control channel may be monitored in a time period between T4 and T2.

(d) One possible implementation: the listening occasions may include: and monitoring the starting time and the monitoring duration, so that a monitoring time period can be determined according to the starting time and the monitoring duration, and the at least one downlink control channel is monitored in the determined monitoring time period.

For example, assuming that the listening start time is T1 and the listening duration is 10s, the at least one downlink control channel may be listened to within 10s from the time T1.

(e) One possible implementation: the listening occasions may include: and the monitoring ending time and the monitoring duration time can determine a monitoring time period according to the monitoring ending time and the monitoring duration time, and monitor the at least one downlink control channel in the determined monitoring time period.

For example, assuming that the listening ending time is T2 and the listening duration is 10s, the at least one downlink control channel may be listened to within 10s before the T2 time.

(f) One possible implementation: the listening occasions may include: and the terminal equipment can monitor the at least one downlink control channel in the at least one time period. That is, a plurality of discontinuous time periods may be configured, and then the at least one downlink control channel is monitored in each of the time periods.

(g) One possible implementation: the listening occasions may include: and a monitoring period, according to which the terminal device can periodically monitor the at least one downlink control channel.

For example, it is assumed that the listening period can be set to be one period every 5 seconds, and in each listening period, the first 3 seconds are used for listening, and the last 2 seconds are not used for listening. In this way, the terminal device may listen for the first 3 seconds in each period, then does not listen for 2 seconds, then listens for 3 seconds in the next period, then does not listen for 2 seconds, and so on.

Optionally, if the terminal device receives a prediction function start instruction sent by the network device, the terminal device may determine that at least one service prediction model may be used to predict the time-frequency resource to be monitored, and thus may determine the first time-frequency resource to be monitored according to the first service prediction model.

Optionally, the network device may send an activation indication to the terminal device, where the activation indication may be used to indicate that use of one or more of the at least one traffic prediction model is allowed.

Optionally, the activation indication may be specifically used to indicate that the first traffic prediction model of the at least one traffic prediction model is allowed to be used. After the terminal device receives the activation indication, the first time-frequency resource to be monitored may be determined according to the first service prediction model.

Optionally, the determining, by the terminal device, the first time-frequency resource to be monitored according to the first service prediction model includes: determining a first time-frequency resource to be monitored corresponding to the first service type according to a historical monitoring result of the first service type and a first service prediction model;

the at least one service type corresponding to the first service prediction model comprises a first service type.

Optionally, the network device may send a monitoring result acquisition instruction to the terminal device, and correspondingly, the terminal device may receive the monitoring result acquisition instruction sent by the network device;

the monitoring result acquisition indication includes at least one of the following items:

(A) Identification information of the first service type;

optionally, the identification information of the first service type may include, but is not limited to:

a frequency of average listening of traffic of the first traffic type;

the average size of the data packets for the traffic of the first traffic type.

The identification information of the first service type may be used to identify, by the terminal device, whether the service is a service of the first service type.

(B) And acquiring the time period of the historical monitoring result.

The time period for obtaining the historical monitoring result is used for indicating the terminal equipment to obtain the historical monitoring result in the time period.

For example, the time period may be within 1 day, within 2 days, or within 10 hours before the current historical monitoring result is obtained. For example, a monitoring result within 1 day before the current acquisition of the history monitoring result may be selected as the history monitoring result.

The longer the time period setting, the more accurate the result of the subsequent prediction may be, and the shorter the time period setting, the less complex the process of the subsequent prediction may be. Therefore, the setting of the time period can be determined according to the requirement on the accuracy of the prediction result in practical application and the requirement on complexity in the prediction process, and the embodiment of the application is not limited.

Optionally, the terminal device may obtain the historical monitoring result of the first service type according to the monitoring result obtaining instruction after receiving the monitoring result obtaining instruction sent by the network device.

Optionally, the network device may configure a first timer for the terminal device, and the corresponding terminal device may receive the first timer configured by the network device, where a timing duration of the first timer is used to indicate a service time range of the first service prediction model. Optionally, the terminal device may determine the first time-frequency resource to be monitored according to the first service prediction model after the first timer is started and before the first timer times out.

Optionally, the network device may send a reporting instruction to the terminal device, and correspondingly, the terminal device may receive the reporting instruction sent by the network device, where the reporting instruction is used to instruct to report the time-frequency resource to be monitored, which is determined according to the at least one service prediction model.

Wherein, the reporting indication may include: and reporting at least one of the frequency and the content, wherein the content is a time frequency resource to be monitored, or a designated resource in the time frequency resource to be monitored.

Optionally, the designated resource in the time-frequency resource to be monitored may refer to a resource scrambled by a designated RNTI in a downlink control channel to be monitored.

503. And the terminal equipment monitors the time-frequency resource according to the first time-frequency resource to be monitored.

Optionally, the network device may further send DRX related configuration information to the terminal device, and the corresponding terminal device may receive the DRX related configuration information sent by the network device.

Optionally, the terminal device may further monitor the time-frequency resource according to the first time-frequency resource to be monitored and the DRX-related configuration parameter; and obtains the actual monitoring result.

Optionally, the terminal device may monitor the time-frequency resource according to the first time-frequency resource to be monitored and the DRX-related configuration parameter, in a DRX inactive time period indicated by the DRX-related configuration parameter, during the time-frequency resource monitoring process according to the first time-frequency resource to be monitored.

In the embodiment of the present application, the service prediction model may be updated:

in practice, there may be a case where resources are not monitored when the time-frequency resources are monitored according to the first to-be-monitored video resources, which indicates that the first service prediction model may not be suitable for the current scenario, and at this time, the terminal device may update the first service prediction model according to the first to-be-monitored time-frequency resources and the actual monitoring result.

Optionally, after acquiring the first video resource to be monitored and the actual monitoring result, the terminal device may send the first time-frequency resource to be monitored and the actual monitoring result to the network device, so that the network device may determine whether to update the corresponding service prediction model.

As described in fig. 5B in conjunction with fig. 5A, after step 503, the following steps 504 and 505 may be further included:

504. and the terminal equipment acquires an actual monitoring result.

505. And the terminal equipment sends the first time-frequency resource to be monitored and the actual monitoring result to the network equipment.

When sending the first time-frequency resource to be monitored and the actual monitoring result to the network device, it is further required to indicate to the network device that the first time-frequency resource to be monitored and the actual monitoring result are obtained based on the first service prediction model.

Optionally, after the network device receives the first time-frequency resource to be monitored and the actual monitoring result, the network device may update the first service prediction model according to the first time-frequency resource to be monitored and the actual monitoring result to obtain a second service prediction model; and indicating the second traffic prediction model to the terminal device.

Further, the terminal device may receive a second service prediction model indicated by the network device, and in the subsequent time-frequency resource prediction process, adopt the second service prediction model to predict the video resource to be monitored corresponding to the first service type.

In the above implementation scheme, under the condition that resource monitoring is performed according to the first time-frequency resource to be monitored, if the actual monitoring result is not matched with the first time-frequency resource to be monitored, the first time-frequency resource to be monitored and the resource monitoring result may be compared, and the second service prediction model may be updated according to the comparison condition.

When the monitoring time-frequency resource predicted by the current first service prediction model is not monitored to the corresponding time-frequency resource, the monitoring time-frequency resource can be returned to other service prediction models which are used once to predict the monitoring time-frequency resource, or a downlink control channel is monitored directly according to network configuration, so that the service prediction model can be flexibly adjusted, and invalid monitoring is avoided.

In the embodiment of the present application, the current service prediction model may be rolled back to a more conservative service prediction model, or the current configuration parameters:

in an alternative implementation: if the fallback triggering condition is met, the terminal device can determine a second time-frequency resource to be monitored according to the third service prediction model;

the third service prediction model is an initial service prediction model indicated by the network device, or the third service prediction model is a historical service prediction model used before the first service prediction model.

In another optional implementation: if the fallback triggering condition is met, the terminal device may monitor a downlink control channel according to the DRX related configuration parameters configured by the network device;

the rollback triggering condition is that the time-frequency resource is not monitored at least once according to the first time-frequency resource to be monitored.

Optionally, the network device may configure the fallback triggering condition to the terminal device, and the corresponding terminal device may receive the fallback triggering condition. Therefore, under the condition that the terminal equipment acquires the backspacing triggering condition, when the backspacing triggering condition is met, the time-frequency resource to be monitored can be predicted by adopting the third service prediction model, or the downlink control channel can be monitored directly according to the DRX related configuration parameters.

In the implementation scheme, under the condition that the corresponding time-frequency resource is not monitored for a plurality of times according to the predicted monitoring time-frequency resource, the method can return to other service prediction models which are used once to predict the monitoring time-frequency resource, or monitor the downlink control channel directly according to network configuration, so that the service prediction models can be flexibly adjusted, and invalid monitoring is avoided.

In the method for determining time-frequency resources to be monitored provided by the embodiment of the application, the terminal device may receive at least one service prediction model indicated by the network device, and determine a first time-frequency resource to be monitored according to a first service prediction model therein; the first business prediction model is one of at least one business prediction model. Through the scheme, the terminal equipment can predict the time-frequency resource to be monitored in the future according to the service prediction model indicated by the network equipment, so that compared with a mode that the network equipment controls the monitoring behavior of the terminal equipment, the receiving performance can be ensured, meanwhile, the terminal equipment is not completely controlled by the network equipment, and the problem that the power consumption of the terminal equipment is large can be further improved.

As shown in fig. 6, an embodiment of the present application provides a terminal device, where the terminal device includes:

a receiving module 601, configured to receive at least one service prediction model indicated by a network device;

the processing module 602 determines a first time-frequency resource to be monitored according to the first service prediction model;

Optionally, each service prediction model in the at least one service prediction model corresponds to at least one service type.

Optionally, the processing module 602 is specifically configured to determine, according to the historical monitoring result of the first service type and the first service prediction model, a first time-frequency resource to be monitored, which corresponds to the first service type;

Optionally, the receiving module 601 is further configured to receive a monitoring result obtaining indication sent by the network device;

the monitoring result acquisition indication comprises at least one of the following items:

identification information of a first service type;

and acquiring the time period of the historical monitoring result.

Optionally, the processing module 602 is further configured to obtain a historical monitoring result of the first service type according to the monitoring result obtaining indication.

Optionally, the receiving module 601 is further configured to receive at least one of the following indications sent by the network device;

a prediction function starting indication for indicating that at least one service prediction model is allowed to be used and determining time-frequency resources to be monitored;

and the prediction function closing indication is used for indicating that at least one service prediction model is forbidden to be used and determining the time-frequency resource to be monitored.

Optionally, the processing module 602 is further configured to determine, if the prediction function start instruction is received, the first time-frequency resource to be monitored according to the first service prediction model.

Optionally, the receiving module 601 is further configured to receive an activation indication sent by the network device, where the activation indication is used to indicate that a first service prediction model in the at least one service prediction model is allowed to be used.

Optionally, the receiving module 601 is further configured to receive a first timer configured by the network device, where a timing duration of the first timer is used to indicate a usage time range of the first service prediction model.

Optionally, the processing module 602 is specifically configured to determine the first time-frequency resource to be monitored according to the first service prediction model after the first timer is started and before the first timer times out.

at least one downlink control channel;

monitoring the monitoring time of at least one downlink control channel;

Optionally, the listening time includes at least one of the following:

Optionally, the receiving module 610 is further configured to receive a first identifier scrambling instruction sent by the network device, where the first identifier scrambling instruction is used to instruct to monitor a downlink control channel scrambled by the first identifier.

Optionally, the receiving module 610 is further configured to receive DRX-related configuration information sent by the network device.

Optionally, the processing module 602 is specifically configured to monitor the time-frequency resource according to the first time-frequency resource to be monitored and the DRX-related configuration parameter; and acquiring an actual monitoring result.

Optionally, the processing module 602 is specifically configured to monitor the time-frequency resource according to the first time-frequency resource to be monitored in the DRX inactive time period indicated by the DRX-related configuration parameter.

Optionally, the processing module 602 is further configured to update the first service prediction model according to the first time-frequency resource to be monitored and the actual monitoring result.

Optionally, as shown in fig. 6, the terminal device further includes:

a sending module 603, configured to send the first time-frequency resource to be monitored and the actual monitoring result to the network device.

Optionally, the receiving module 601 is further configured to receive a second service prediction model indicated by the network device;

and the second service prediction model is obtained by updating the first service prediction model according to the first time-frequency resource to be monitored and the actual monitoring result by the network equipment.

Optionally, the processing module 602 is further configured to determine, according to the third service prediction model, a second time-frequency resource to be monitored if the fallback triggering condition is met;

the backspacing triggering condition is that the time frequency resource is not monitored at least once according to the first time frequency resource to be monitored; the third service prediction model is an initial service prediction model indicated by the network device, or the third service prediction model is a historical service prediction model used before the first service prediction model.

Optionally, the processing module 602 is further configured to monitor a downlink control channel according to DRX-related configuration parameters configured by the network device if the fallback triggering condition is met;

the backspacing triggering condition is that the time frequency resource is not monitored at least once according to the first time frequency resource to be monitored;

optionally, the receiving module 601 is further configured to receive a fallback triggering condition sent by the network device.

Optionally, the receiving module 601 is further configured to receive a reporting instruction sent by the network device, where the reporting instruction is used to instruct reporting of the time-frequency resource to be monitored, which is determined according to the at least one service prediction model;

the reporting indication includes at least one of reporting frequency and reporting content, and the reporting content is a time-frequency resource to be monitored, or a designated resource in the time-frequency resource to be monitored.

Optionally, the receiving module 601 is further configured to receive an initial monitoring state indication sent by the network device;

the initial listening state indication is used for indicating default not listening, or the initial listening state indication is used for indicating default listening.

radio Resource Control (RRC) signaling, a media access control unit (MAC CE) and downlink indication information (DCI).

As shown in fig. 7, an embodiment of the present application provides a network device, including:

a sending module 701, configured to send at least one service prediction model to a terminal device; and each service prediction model in the at least one service prediction model is used for determining the time-frequency resource to be monitored.

Optionally, the sending module 701 is further configured to send a monitoring result obtaining instruction to the terminal device;

identification information of a first service type;

and acquiring the time period of the historical monitoring result.

Optionally, the sending module 701 is further configured to send at least one of the following instructions to the terminal device;

Optionally, the sending module 701 is further configured to send an activation indication to the terminal device, where the activation indication is used to indicate that a first service prediction model in the at least one service prediction model is allowed to be used.

Optionally, as shown in fig. 7, the network device further includes:

a receiving module 702, configured to receive a first timer configured by a network device, where a timing duration of the first timer is used to indicate a service time range of a first service prediction model.

Optionally, the sending module 701 is further configured to send a first identifier scrambling instruction to the terminal device, where the first identifier scrambling instruction is used to instruct to monitor the downlink control channel scrambled by the first identifier.

Optionally, the sending module 701 is further configured to send DRX related configuration information to the terminal device.

Optionally, the receiving module 702 is further configured to receive a first time-frequency resource to be monitored and an actual monitoring result sent by the network device;

the first time-frequency resource to be monitored is determined according to a first service prediction model, and the first service prediction model is one of at least one service prediction model; the actual monitoring result is obtained by performing time-frequency resource monitoring according to the first band monitoring time-frequency resource.

Optionally, as shown in fig. 7, the network device further includes:

the processing module 703 is configured to update the first service prediction model according to the first time-frequency resource to be monitored and the actual monitoring result, so as to obtain a second service prediction model;

the sending module 701 is further configured to indicate the second service prediction model to the terminal device.

Optionally, the sending module 701 is further configured to send a fallback triggering condition to the terminal device; the backspacing triggering condition is that the time frequency resource is not monitored at least once according to the first time frequency resource to be monitored.

Optionally, the sending module 701 is further configured to send a reporting instruction to the terminal device, where the reporting instruction is used to instruct reporting of the time-frequency resource to be monitored, which is determined according to the at least one service prediction model;

Optionally, the sending module 701 is further configured to send an initial monitoring state indication to the terminal device;

the initial monitoring state indication is used for indicating default monitoring, or the initial monitoring state indication is used for indicating default monitoring.

Optionally, the at least one traffic prediction model is indicated by at least one of:

RRC signaling, MAC CE, DCI.

The embodiment of the application also provides a terminal device, which can comprise a transceiver, a processor and a memory; the memory has stored therein a computer program which, when executed by the transceiver and the processor, implements the respective processes involved in the terminal device in the above-described method embodiments.

The embodiment of the application also provides a network device, and the terminal device may include a transceiver, a processor and a memory; the memory stores therein a computer program which, when executed by the transceiver and the processor, implements the respective processes involved by the network device in the above-described method embodiments.

Fig. 8 is a schematic diagram of a hardware structure of a terminal device according to an embodiment of the present application. The terminal device may include: radio Frequency (RF) circuitry 810, memory 820, a processor 830, and the like. The radio frequency circuit 810 includes a receiver and a transmitter, among other things. Those skilled in the art will appreciate that the configuration of the terminal device shown in fig. 8 does not constitute a limitation of the terminal device, and may include more or fewer components than shown, or some components may be combined, or a different arrangement of components.

RF circuit 810 may be used for receiving and transmitting signals during information transmission and reception or during a call, and in particular, for processing downlink information of a base station after receiving the downlink information to processor 830; in addition, the data for designing uplink is transmitted to the base station. In general, RF circuit 810 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a Low Noise Amplifier (LNA), a duplexer, and the like. In addition, the RF circuit 810 may also communicate with networks and other devices via wireless communication. The wireless communication may use any communication standard or protocol, including but not limited to global system for mobile communication (GSM), general Packet Radio Service (GPRS), code Division Multiple Access (CDMA), wideband Code Division Multiple Access (WCDMA), long Term Evolution (LTE), email, short Message Service (SMS), etc.

The memory 820 may be used to store software programs and modules, and the processor 830 may execute various functional applications of the terminal device and data processing by operating the software programs and modules stored in the memory 820. The memory 820 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the terminal device, and the like. Further, the memory 820 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The processor 830 is a control center that connects various parts of the entire terminal device using various interfaces and lines, performs various functions of the terminal device and processes data by operating or executing software programs and/or modules stored in the memory 820 and calling data stored in the memory 820, thereby integrally monitoring the terminal device. Optionally, processor 830 may include one or more processing units; preferably, the processor 830 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into processor 830.

In this embodiment, the RF circuit 810 is configured to receive at least one traffic prediction model indicated by a network device;

the processor 830, according to the first service prediction model, determines a first time-frequency resource to be monitored;

Optionally, the processor 830 is specifically configured to determine, according to the historical monitoring result of the first service type and the first service prediction model, a first time-frequency resource to be monitored, which corresponds to the first service type;

Optionally, the RF circuit 810 is further configured to receive a monitoring result obtaining indication sent by the network device;

identification information of a first service type;

and acquiring the time period of the historical monitoring result.

Optionally, the processor 830 is further configured to obtain a historical monitoring result of the first service type according to the monitoring result obtaining indication.

Optionally, the RF circuit 810 is further configured to receive at least one of the following indications sent by the network device;

Optionally, the processor 830 is further configured to determine the first time-frequency resource to be monitored according to the first service prediction model if the prediction function start instruction is received.

Optionally, the RF circuit 810 is further configured to receive an activation indication sent by the network device, where the activation indication is used to indicate that a first traffic prediction model of the at least one traffic prediction model is allowed to be used.

Optionally, the RF circuit 810 is further configured to receive a first timer configured by the network device, where a timing duration of the first timer is used to indicate a usage time range of the first traffic prediction model.

Optionally, the processor 830 is specifically configured to determine the first time-frequency resource to be monitored according to the first service prediction model after the first timer is started and before the first timer times out.

at least one downlink control channel;

monitoring the monitoring time of at least one downlink control channel;

Optionally, the listening time includes at least one of the following:

Optionally, at least one downlink control channel is a first identifier scrambled downlink control channel.

Optionally, the RF circuit 810 is further configured to receive a first identifier scrambling instruction sent by the network device, where the first identifier scrambling instruction is used to instruct to monitor a downlink control channel scrambled by the first identifier.

Optionally, the RF circuit 810 is further configured to receive DRX-related configuration information sent by the network device.

Optionally, the processor 830 is specifically configured to monitor the time-frequency resource according to the first time-frequency resource to be monitored and the DRX-related configuration parameter; and acquiring an actual monitoring result.

Optionally, the processor 830 is specifically configured to monitor the time-frequency resource according to the first time-frequency resource to be monitored in the DRX inactivity time period indicated by the DRX-related configuration parameter.

Optionally, the processor 830 is further configured to update the first service prediction model according to the first time-frequency resource to be monitored and the actual monitoring result.

The RF circuit 810 is further configured to send the first time-frequency resource to be monitored and the actual monitoring result to the network device.

Optionally, the RF circuit 810 is further configured to receive a second traffic prediction model indicated by the network device;

Optionally, the processor 830 is further configured to determine, according to the third service prediction model, a second time-frequency resource to be monitored if the fallback triggering condition is met;

Optionally, the processor 830 is further configured to monitor a downlink control channel according to a DRX-related configuration parameter configured by the network device if the fallback triggering condition is met;

optionally, the RF circuit 810 is further configured to receive a fallback triggering condition sent by the network device.

Optionally, the RF circuit 810 is further configured to receive a reporting instruction sent by the network device, where the reporting instruction is used to instruct reporting of the time-frequency resource to be monitored, where the time-frequency resource is determined according to the at least one service prediction model;

Optionally, the RF circuit 810 is further configured to receive an initial listening status indication sent by the network device;

As shown in fig. 9, a network device according to an embodiment of the present application may be a base station, where the base station includes:

a transmitter 901, configured to transmit at least one service prediction model to a terminal device; and each service prediction model in the at least one service prediction model is used for determining the time-frequency resource to be monitored.

Optionally, the transmitter 901 is further configured to send a monitoring result obtaining indication to the terminal device;

identification information of a first service type;

and acquiring the time period of the historical monitoring result.

Optionally, the transmitter 901 is further configured to transmit at least one of the following indications to the terminal device;

Optionally, the transmitter 901 is further configured to transmit an activation indication to the terminal device, where the activation indication is used to indicate that the use of a first service prediction model in the at least one service prediction model is allowed.

Optionally, as shown in fig. 9, the base station further includes:

the receiver 902 is configured to receive a first timer configured by a base station, where a timing duration of the first timer is used to indicate a usage time range of the first traffic prediction model.

Optionally, the transmitter 901 is further configured to transmit a first identifier scrambling instruction to the terminal device, where the first identifier scrambling instruction is used to instruct to monitor a downlink control channel scrambled by the first identifier.

Optionally, the transmitter 901 is further configured to transmit DRX-related configuration information to the terminal device.

Optionally, the receiver 902 is further configured to receive a first time-frequency resource to be monitored and an actual monitoring result sent by the base station;

the first time-frequency resource to be monitored is determined according to a first service prediction model, and the first service prediction model is one of at least one service prediction model; the actual monitoring result is the result obtained by monitoring the time frequency resource according to the first band monitoring time frequency resource.

Optionally, as shown in fig. 9, the base station further includes:

the processor 903 is configured to update the first service prediction model according to the first time-frequency resource to be monitored and the actual monitoring result, so as to obtain a second service prediction model;

the transmitter 901 is further configured to indicate the second traffic prediction model to the terminal device.

Optionally, the transmitter 901 is further configured to send a fallback triggering condition to the terminal device; and the backspacing triggering condition is that the time frequency resource is not monitored at least once according to the first time frequency resource to be monitored.

Optionally, the transmitter 901 is further configured to send a reporting instruction to the terminal device, where the reporting instruction is used to instruct reporting of the time-frequency resource to be monitored, which is determined according to the at least one service prediction model;

the reporting indication includes at least one of a reporting frequency and a reporting content, and the reporting content is a time frequency resource to be monitored, or a specified resource in the time frequency resource to be monitored.

Optionally, the transmitter 901 is further configured to send an initial monitoring state indication to the terminal device;

RRC signaling, MAC CE, DCI.

An embodiment of the present application provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process executed by a terminal device in the foregoing method embodiments, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.

An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process executed by the network device in the foregoing method embodiments, and can achieve the same technical effect, and in order to avoid repetition, the computer program is not described herein again.

The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.

The embodiment of the present application further provides a computer program product, where the computer program is stored, and when being executed by a processor, the computer program implements each process executed by the terminal device in the foregoing method embodiments, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.

The embodiments of the present application further provide a computer program product, where the computer program is stored, and when being executed by a processor, the computer program implements each process executed by the network device in the foregoing method embodiments, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a component of' 8230; \8230;" does not exclude the presence of another like element in a process, method, article, or apparatus that comprises the element.

Through the description of the foregoing embodiments, it is clear to those skilled in the art that the method of the foregoing embodiments may be implemented by software plus a necessary general hardware platform, and certainly may also be implemented by hardware, but in many cases, the former is a better implementation. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method of the embodiments of the present application.

While the present embodiments have been described with reference to the accompanying drawings, it is to be understood that the present embodiments are not limited to those precise embodiments, which are intended to be illustrative rather than restrictive, and that various changes and modifications may be effected therein by one skilled in the art without departing from the scope of the appended claims.

Claims

1. A method for determining time-frequency resources to be monitored is characterized by comprising the following steps:

2. The method of claim 1, wherein each of the at least one traffic prediction model corresponds to at least one traffic type.

3. The method according to claim 1 or 2, wherein determining the first to-be-monitored time-frequency resource according to the first traffic prediction model comprises:

determining the first time-frequency resource to be monitored corresponding to the first service type according to the historical monitoring result of the first service type and the first service prediction model;

wherein, at least one service type corresponding to the first service prediction model comprises the first service type.

4. The method according to claim 3, wherein the acquisition instruction of the listening result sent by the network device is received;

identification information of the first service type;

and acquiring the time period of the historical monitoring result.

5. The method of claim 4, further comprising:

and acquiring a historical monitoring result of the first service type according to the monitoring result acquisition instruction.

6. The method of any of claims 1 to 5, further comprising: receiving at least one of the following indications sent by the network equipment;

and the prediction function closing instruction is used for indicating that the at least one service prediction model is forbidden to be used and determining the time-frequency resource to be monitored.

7. The method of claim 6, further comprising:

and if the prediction function starting instruction is received, determining the first time-frequency resource to be monitored according to the first service prediction model.

8. The method of any one of claims 1 to 7, further comprising:

receiving an activation indication sent by the network device, wherein the activation indication is used for indicating that the first traffic prediction model in the at least one traffic prediction model is allowed to be used.

9. The method of any one of claims 1 to 8, further comprising:

and receiving a first timer configured by the network equipment, wherein the timing duration of the first timer is used for indicating the service time range of the first service prediction model.

10. The method of claim 9, wherein the determining the first to-be-monitored time-frequency resource according to the first traffic prediction model comprises:

and after the first timer is started and before the first timer is overtime, determining the first time-frequency resource to be monitored according to the first service prediction model.

11. The method according to any one of claims 1 to 10,

the first time-frequency resource to be monitored comprises at least one of the following:

at least one downlink control channel;

and monitoring the monitoring time of the at least one downlink control channel.

12. The method according to claim 11, wherein the at least one downlink control channel is a downlink control channel configured on active BWP.

13. The method of claim 11, wherein the listening occasions comprise at least one of:

14. The method of claim 13, wherein the at least one downlink control channel is a first identity scrambled downlink control channel.

15. The method of claim 14, further comprising:

receiving a first identifier scrambling instruction sent by a network device, wherein the first identifier scrambling instruction is used for instructing to monitor a downlink control channel scrambled by the first identifier.

16. The method of any one of claims 11 to 15, further comprising:

and receiving DRX related configuration information sent by the network equipment.

17. The method of claim 16, further comprising:

monitoring the time frequency resource according to the first time frequency resource to be monitored and the DRX related configuration parameter;

and acquiring an actual monitoring result.

18. The method according to claim 17, wherein the performing time-frequency resource monitoring according to the first time-frequency resource to be monitored and the DRX-related configuration parameter comprises:

and monitoring time frequency resources according to the first time frequency resources to be monitored in the DRX non-activated time period indicated by the DRX related configuration parameters.

19. The method of claim 17, further comprising:

and updating the first service prediction model according to the first time-frequency resource to be monitored and the actual monitoring result.

20. The method of claim 17, further comprising:

and sending the first time-frequency resource to be monitored and the actual monitoring result to the network equipment.

21. The method of claim 20, further comprising:

receiving a second service prediction model indicated by the network equipment;

and the second service prediction model is obtained by updating the first service prediction model by the network equipment according to the first time-frequency resource to be monitored and the actual monitoring result.

22. The method of any one of claims 11 to 21, further comprising:

if the backspacing triggering condition is met, determining a second time-frequency resource to be monitored according to a third service prediction model;

23. The method of any one of claims 11 to 21, further comprising:

if the back-off triggering condition is met, monitoring a downlink control channel according to DRX related configuration parameters configured by the network equipment;

and the backspacing triggering condition is that the time frequency resource is not monitored at least once according to the first time frequency resource to be monitored.

24. The method of claim 22 or 23, further comprising:

and receiving the rollback triggering condition sent by the network equipment.

25. The method of any one of claims 1 to 24, further comprising:

receiving a reporting instruction sent by the network equipment, wherein the reporting instruction is used for indicating to report the time-frequency resource to be monitored determined according to the at least one service prediction model;

the reporting indication includes at least one of reporting frequency and reporting content, where the reporting content is the time-frequency resource to be monitored, or a designated resource in the time-frequency resource to be monitored.

26. The method of any one of claims 1 to 25, further comprising:

receiving an initial monitoring state indication sent by the network equipment;

the initial listening state indication is used for indicating default non-listening, or the initial listening state indication is used for indicating default listening.

27. The method according to any of the claims 1 to 26, wherein said at least one traffic prediction model is indicated by at least one of:

28. A method for determining time-frequency resources to be monitored is characterized by comprising the following steps:

29. The method of claim 28, wherein each of the at least one traffic prediction model corresponds to at least one traffic type.

30. The method of claim 29, wherein an acquisition instruction of the listening result is sent to the terminal device;

identification information of the first service type;

and acquiring the time period of the historical monitoring result.

31. A method according to any one of claims 28 to 30, characterized by transmitting an indication of at least one of the following to the terminal device;

32. The method of any one of claims 28 to 31, further comprising:

and sending an activation indication to the terminal equipment, wherein the activation indication is used for indicating that the use of a first business prediction model in the at least one business prediction model is allowed.

33. The method of claim 32, further comprising:

34. The method of claim 28, further comprising:

and sending a first identifier scrambling instruction to the terminal equipment, wherein the first identifier scrambling instruction is used for indicating to monitor the downlink control channel scrambled by the first identifier.

35. The method of any one of claims 28 to 34, further comprising:

and sending DRX related configuration information to the terminal equipment.

36. The method of any one of claims 28 to 35, further comprising:

receiving a first time-frequency resource to be monitored and an actual monitoring result which are sent by the network equipment;

the first time-frequency resource to be monitored is determined according to a first service prediction model, and the first service prediction model is one of the at least one service prediction model; and the actual monitoring result is obtained by monitoring the time frequency resource according to the first band monitoring time frequency resource.

37. The method of claim 36, further comprising:

updating the first service prediction model according to the first time-frequency resource to be monitored and the actual monitoring result to obtain a second service prediction model;

indicating the second traffic prediction model to the terminal device.

38. The method of any one of claims 28 to 27, further comprising:

sending a backspacing triggering condition to the terminal equipment; and the backspacing triggering condition is that the time frequency resource is not monitored at least once according to the first time frequency resource to be monitored.

39. The method of any one of claims 28 to 38, further comprising:

sending a reporting instruction to the terminal equipment, wherein the reporting instruction is used for indicating to report the time-frequency resource to be monitored determined according to the at least one service prediction model;

40. The method of any one of claims 28 to 39, further comprising:

sending an initial monitoring state indication to the terminal equipment;

41. The method according to any of the claims 28 to 40, wherein said at least one traffic prediction model is indicated by at least one of:

RRC signaling, MAC CE, DCI.

42. A terminal device, comprising:

43. A network device, comprising:

44. A terminal device, comprising: a transceiver, a processor, and a memory;

the memory has stored therein a computer program which, when being executed by the transceiver and the processor, carries out the method of determining time-frequency resources to listen as claimed in any one of claims 1 to 27.

45. A network device, comprising: a transceiver, a processor, and a memory;

the memory has stored therein a computer program which, when being executed by the transceiver and the processor, carries out the method of determining time-frequency resources to listen as claimed in any one of claims 28 to 41.

46. A computer-readable storage medium, comprising: computer program stored on the computer readable storage medium, which, when being executed by a processor, is adapted to carry out a method for determining time-frequency resources to listen to as claimed in any one of claims 1 to 27.

47. A computer-readable storage medium, comprising: computer program stored on the computer readable storage medium, which, when being executed by a processor, is adapted to carry out a method for determining time-frequency resources to listen to as claimed in any one of claims 28 to 41.