Random access method, terminal and network equipment

Abstract

The present disclosure relates to a random access method, terminal and network device, the method executed by the network device comprising: determining the number of terminals providing random access request messages, the number of terminals being determined based on the random access request messages received by the network device and a first AI model; and scheduling the transmission of the random access response message based on the number of the terminals. Therefore, the network device can determine the number of the terminals providing the random access request message, and schedule the transmission of the random access response message based on the number of the terminals, can provide network service for each terminal based on the determined number of the terminals, and improves the performance of a communication system.

Description

Random access method, terminal, and network device Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a random access method, a terminal, and a network device. Background Art

[0002] In recent years, artificial intelligence (AI) technology has achieved continuous breakthroughs in various fields. The continued development of AI-based technologies such as intelligent voice and computer vision has not only brought a rich variety of applications to smart terminals, but has also found widespread application in education, transportation, home furnishings, healthcare, retail, security, and other fields. While bringing convenience to people's lives, it is also promoting industrial upgrading across various industries.

[0003] Summary of the Invention

[0004] The random access method, terminal, and network device provided in the embodiments of the present disclosure are used to solve the problem that a network device cannot determine the number of terminals providing random access request messages after receiving a random access request message. For the network device, the network device cannot determine the number of terminals providing random access request messages, and will regard random access request messages sent by different terminals as being sent by the same terminal, thereby discarding random access request messages sent by some terminals and subsequently scheduling the transmission of random access response messages. This may result in the inability to provide network services to some terminals and degrade communication system performance.

[0005] The embodiments of the present disclosure provide a random access method, a terminal, and a network device.

[0006] According to a first aspect of an embodiment of the present disclosure, a random access method is proposed, which is performed by a network device, including: determining the number of terminals that provide random access request messages, wherein the number of terminals is determined based on the random access request messages received by the network device and a first AI model; and scheduling the transmission of random access response messages based on the number of terminals.

[0007] In the above embodiment, the network device can determine the number of terminals that provide random access request messages and schedule the transmission of random access response messages based on the number of terminals, thereby providing network services to each terminal based on the determined number of terminals and improving the performance of the communication system.

[0008] According to a second aspect of an embodiment of the present disclosure, a random access method is proposed, which is executed by a first terminal, including: determining the number of terminals providing random access request messages based on a random access request message and a first AI model received by a network device, wherein the number of terminals is used by the network device to schedule the transmission of a random access response message; or receiving first indication information sent by the network device, wherein the first indication information is used to indicate the number of terminals, and the number of terminals is determined by the network device based on the received random access request message and the first AI model.

[0009] In the above embodiment, the first terminal can determine the number of terminals that provide random access request messages for the network device to schedule the transmission of random access response messages; or the network device can determine the number of terminals that provide random access request messages for the network device to schedule the transmission of random access response messages, which can improve the performance of the communication system.

[0010] According to a third aspect of an embodiment of the present disclosure, a random access method is proposed, wherein a first terminal determines the number of terminals providing random access request messages based on a random access request message and a first AI model received by a network device; the network device determines the number of terminals providing random access request messages, wherein the number of terminals is determined based on the random access request message and the first AI model received by the network device; and the network device schedules the transmission of a random access response message based on the number of terminals.

[0011] In the above embodiment, the first terminal and the network device can determine the number of terminals that provide random access request messages, and then the network device can schedule the transmission of random access response messages based on the number of terminals, and can provide network services for each terminal based on the determined number of terminals, thereby improving the performance of the communication system.

[0012] According to a fourth aspect of an embodiment of the present disclosure, a network device is provided, including: a processing module for determining the number of terminals that provide random access request messages, wherein the number of terminals is determined based on the random access request messages received by the network device and a first artificial intelligence (AI) model; the processing module is also used to schedule the transmission of random access response messages based on the number of terminals.

[0013] According to a fifth aspect of an embodiment of the present disclosure, a first terminal is provided, including: a processing module for determining the number of terminals providing random access request messages based on a random access request message and a first AI model received by a network device, wherein the number of terminals is used by the network device to schedule the transmission of a random access response message; or a transceiver module for receiving fourth indication information sent by the network device, wherein the fourth indication information is used to indicate the number of terminals, and the number of terminals is determined by the network device based on the received random access request message and the first AI model.

[0014] According to a sixth aspect of an embodiment of the present disclosure, a network device is provided, comprising: one or more processors; a memory coupled to the processor, wherein the memory stores instructions, and when the instructions are executed by the processor, the network device is used to execute the method described in the first aspect.

[0015] According to the seventh aspect of an embodiment of the present disclosure, a first terminal is provided, comprising: one or more processors; a memory coupled to the processor, wherein the memory stores instructions, and when the instructions are executed by the processor, the first terminal executes the method described in the second aspect.

[0016] According to an eighth aspect of an embodiment of the present disclosure, a communication system is provided, including a first terminal and a network device, wherein the network device is configured to implement the method described in the first aspect, and the first terminal is configured to implement the method described in the second aspect.

[0017] According to a ninth aspect of an embodiment of the present disclosure, a storage medium is provided, wherein the storage medium stores instructions. When the instructions are executed on a communication device, the communication device executes the method described in the first aspect or the second aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] FIG1 is an architecture diagram of a communication system provided by an embodiment of the present disclosure;

[0019] FIG2A is a flowchart of a random access method provided by an embodiment of the present disclosure;

[0020] FIG2B is a flowchart of another random access method provided by an embodiment of the present disclosure;

[0021] FIG2C is a flowchart of another random access method provided by an embodiment of the present disclosure;

[0022] FIG2D is a flowchart of another random access method provided by an embodiment of the present disclosure;

[0023] FIG2E is a flowchart of another random access method provided by an embodiment of the present disclosure;

[0024] FIG2F is a flowchart of another random access method provided by an embodiment of the present disclosure;

[0025] FIG3A is a flowchart of another random access method provided by an embodiment of the present disclosure;

[0026] FIG3B is a flowchart of another random access method provided by an embodiment of the present disclosure;

[0027] FIG3C is a flowchart of another random access method provided by an embodiment of the present disclosure;

[0028] FIG4A is a flowchart of another random access method provided by an embodiment of the present disclosure;

[0029] FIG4B is a flowchart of another random access method provided by an embodiment of the present disclosure;

[0030] FIG4C is a flowchart of another random access method provided by an embodiment of the present disclosure;

[0031] FIG5A is a schematic diagram of a random access process provided by an embodiment of the present disclosure;

[0032] FIG5B is a schematic diagram of a first AI model processing process provided by an embodiment of the present disclosure;

[0033] FIG5C is a schematic diagram of a second AI model processing process provided by an embodiment of the present disclosure;

[0034] FIG6A is a structural diagram of a network device provided by an embodiment of the present disclosure;

[0035] FIG6B is a structural diagram of a first terminal provided by an embodiment of the present disclosure;

[0036] FIG7A is a structural diagram of a communication device provided by an embodiment of the present disclosure;

[0037] FIG7B is a schematic structural diagram of a chip provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0038] The embodiments of the present disclosure provide a random access method, a terminal, and a network device.

[0039] In a first aspect, an embodiment of the present disclosure proposes a random access method, which is executed by a network device, including: determining the number of terminals that provide random access request messages, wherein the number of terminals is determined based on the random access request messages received by the network device and a first AI model; and scheduling the transmission of random access response messages based on the number of terminals.

[0040] In the above embodiment, the network device can determine the number of terminals that provide random access request messages and schedule the transmission of random access response messages based on the number of terminals, thereby providing network services to each terminal based on the determined number of terminals and improving the performance of the communication system.

[0041] In combination with some embodiments of the first aspect, in some embodiments, the network device determines the number of terminals that provide random access request messages, including: determining the number of terminals based on the received random access request message and the first AI model.

[0042] In the above embodiment, the first AI model is deployed on the network device side. The network device can determine the number of terminals based on the received random access request message and the first AI model, and then provide network services to each terminal based on the determined number of terminals, thereby improving the performance of the communication system.

[0043] In combination with some embodiments of the first aspect, in some embodiments, the above method further includes: the network device sends first indication information to the first terminal, wherein the first indication information is used to indicate the number of terminals.

[0044] In the above embodiment, the network device may determine the number of terminals providing random access request messages and indicate the number to the first terminal, so that the first terminal can determine the ToA corresponding to the random access request message provided by each terminal.

[0045] In combination with some embodiments of the first aspect, in some embodiments, the network device determines the number of terminals that provide random access request messages, including: receiving second indication information sent by the first terminal, wherein the second indication information is used to indicate the number of terminals, and the number of terminals is determined by the first terminal based on the random access request message received by the network device and the first AI model; determining the number of terminals based on the second indication information.

[0046] In the above embodiment, the first AI model is deployed on the terminal side, and the network device can receive the second indication information sent by the first terminal, determine the number of terminals that provide random access request messages, and then provide network services for each terminal based on the determined number of terminals, thereby improving the performance of the communication system.

[0047] In combination with some embodiments of the first aspect, in some embodiments, the above method also includes: the network device sends third indication information to the first terminal, wherein the third indication information is used to indicate the random access request message received by the network device.

[0048] In the above embodiment, the first AI model is deployed on the first terminal side, and the network device can send the received random access request message to the first terminal, and determine the number of terminals providing random access request messages based on the random access request message and the first AI model on the first terminal side.

[0049] In combination with some embodiments of the first aspect, in some embodiments, the network device schedules the transmission of a random access response message based on the number of terminals, including: determining the arrival time ToA corresponding to the random access request message provided by each terminal, wherein the ToA corresponding to the random access request message provided by each terminal is determined based on the random access request message, the number of terminals and the second AI model; scheduling the transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal.

[0050] In the above embodiment, the network device can determine the arrival time ToA corresponding to the random access request message provided by each terminal to accurately schedule the transmission of the random access response message of each terminal, thereby improving the performance of the communication system.

[0051] In combination with some embodiments of the first aspect, in some embodiments, the network device determines the arrival time ToA corresponding to the random access request message provided by each terminal, including: determining the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model.

[0052] In the above embodiment, the second AI model is deployed on the network device side. The network device can determine the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model, so as to accurately schedule the transmission of the random access response message of each terminal and improve the performance of the communication system.

[0053] In combination with some embodiments of the first aspect, in some embodiments, the network device determines the arrival time ToA corresponding to the random access request message provided by each terminal, including: receiving third indication information sent by the first terminal, wherein the third indication information is used to indicate the ToA corresponding to the random access request message provided by each terminal, and the ToA corresponding to the random access request message provided by each terminal is determined by the first terminal based on the random access request message, the number of terminals and the second AI model; according to the third indication information, determine the arrival time ToA corresponding to the random access request message provided by each terminal.

[0054] In the above embodiment, the second AI model is deployed on the first terminal side, and the network device can receive the second indication information sent by the first terminal, determine the ToA corresponding to the random access request message provided by each terminal, and then accurately schedule the transmission of the random access response message of each terminal, thereby improving the performance of the communication system.

[0055] In conjunction with some embodiments of the first aspect, in some embodiments, the random access request message includes at least one of the following:

[0056] Message msg1 in the 4-step random access process;

[0057] msg3 in the 4-step random access process;

[0058] msgA in the 2-step random access process.

[0059] In the above embodiment, at least one of the number of terminals providing msg1, the number of terminals providing msg3, and the number of terminals providing msgA can be determined, and then the network device can schedule the transmission of random access response messages based on the determined number of terminals, and can provide network services for each terminal based on the determined number of terminals, thereby improving the performance of the communication system.

[0060] In conjunction with some embodiments of the first aspect, in some embodiments, the random access response message includes at least one of the following:

[0061] msg2 in the 4-step random access process;

[0062] msg4 in the 4-step random access process;

[0063] msgB in the 2-step random access process.

[0064] In the above embodiments, the network device can schedule the transmission of msg2 based on the determined number of terminals providing msg1, or schedule the transmission of msg4 based on the determined number of terminals providing msg3, or schedule the transmission of msgB based on the determined number of terminals providing msgA, and can provide network services for each terminal based on the determined number of terminals, thereby improving the performance of the communication system.

[0065] In combination with some embodiments of the first aspect, in some embodiments, the random access request message is msg1 in the 4-step random access process, wherein the network device determines the number of terminals based on the received random access request message and the first AI model, including: inputting the real part and imaginary part of the discrete Fourier transform DFT coefficient of each symbol in the preamble of the random access message into the first AI model to obtain the number of terminals.

[0066] In combination with some embodiments of the first aspect, in some embodiments, the random access request message is msg1 in the four-step random access process, wherein the network device determines the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model, including: inputting the real part and imaginary part of the DFT coefficient of each symbol in the preamble of the random access message, and the number of terminals into the second AI model to obtain the ToA corresponding to the random access request message provided by each terminal.

[0067] In combination with some embodiments of the first aspect, in some embodiments, the network device is a satellite, and the random access request message is received by the network device during a visible window.

[0068] In the above embodiment, when the network device is a satellite, the number of terminals providing random access request messages can be determined based on the random access request messages received during a shorter visible window period, so as to provide network services to each terminal based on the determined number of terminals, thereby improving the performance of the communication system.

[0069] In combination with some embodiments of the first aspect, in some embodiments, the above method also includes: the network device determines a first training data set, wherein the first training data set includes sample random access request messages provided by multiple terminals; and trains the initial first AI model according to the first training data set to obtain a first AI model.

[0070] In the above embodiment, the network device can train the initial first AI model based on the first training data set to obtain the first AI model, and then deploy it on the network device side, or on the first terminal side, to apply it on the network device side or the terminal side to determine the number of terminals.

[0071] In combination with some embodiments of the first aspect, in some embodiments, the above method also includes: the network device determines a second training data set, wherein the second training data set includes sample random access request messages provided by multiple terminals, and sample ToA corresponding to the sample random access request message sent by each terminal; training the initial second AI model according to the second training data set to obtain a second AI model.

[0072] In the above embodiment, the network device can train the initial second AI model based on the second training data set to obtain a second AI model, which is then deployed on the network device side or on the first terminal side for application on the network device side or the terminal side to determine the ToA corresponding to the random access request message provided by each terminal.

[0073] In the second aspect, an embodiment of the present disclosure proposes a random access method, which is executed by a first terminal, including: determining the number of terminals providing random access request messages based on a random access request message and a first AI model received by a network device, wherein the number of terminals is used by the network device to schedule the transmission of a random access response message; or receiving first indication information sent by the network device, wherein the first indication information is used to indicate the number of terminals, and the number of terminals is determined by the network device based on the received random access request message and the first AI model.

[0074] In the above embodiment, the first terminal can determine the number of terminals that provide random access request messages for the network device to schedule the transmission of random access response messages; or the network device can determine the number of terminals that provide random access request messages for the network device to schedule the transmission of random access response messages, which can improve the performance of the communication system.

[0075] In combination with some embodiments of the second aspect, in some embodiments, the above method also includes: the first terminal sends second indication information to the network device, wherein the second indication information is used to indicate the number of terminals.

[0076] In the above embodiment, after determining the number of terminals, the first terminal can send second indication information to the network device to inform the number of terminals, so as to schedule the transmission of random access response messages based on the number of terminals on the network device side to improve the performance of the communication system.

[0077] In combination with some embodiments of the second aspect, in some embodiments, the above method also includes: the first terminal receives third indication information sent by the network device, wherein the third indication information is used to indicate the random access request message received by the network device.

[0078] In the above embodiment, the first AI model is deployed on the first terminal side, and the first terminal can receive the third indication information sent by the network device, determine the random access request message received by the network device, and then determine the number of terminals providing random access request messages based on the random access request message received by the network device and the first AI model on the first terminal side.

[0079] In combination with some embodiments of the second aspect, in some embodiments, the above method also includes: the first terminal determines the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model.

[0080] In the above embodiment, the second AI model is deployed on the first terminal side. When the first terminal determines the random access request message received by the network device and the number of terminals providing random access request messages, it can determine the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model.

[0081] In combination with some embodiments of the second aspect, in some embodiments, the above method also includes: the first terminal sends fourth indication information to the network device, wherein the fourth indication information is used to indicate the ToA corresponding to the random access request message provided by each terminal.

[0082] In the above embodiment, when the first terminal determines the ToA corresponding to the random access request message provided by each terminal, it can indicate it to the network device so that the network device side can accurately schedule the transmission of the random access response message of each terminal, which can improve the performance of the communication system.

[0083] In conjunction with some embodiments of the second aspect, in some embodiments, the random access request message includes at least one of the following:

[0084] msg1 in the 4-step random access process;

[0085] msg3 in the 4-step random access process;

[0086] msgA in the 2-step random access process.

[0087] In conjunction with some embodiments of the second aspect, in some embodiments, the random access response message includes at least one of the following:

[0088] msg2 in the 4-step random access process;

[0089] msg4 in the 4-step random access process;

[0090] msgB in the 2-step random access process.

[0091] In combination with some embodiments of the second aspect, in some embodiments, the random access request message is msg1 in the 4-step random access process, wherein the first terminal determines the number of terminals providing random access request messages based on the random access request message received by the network device and the first AI model, including: inputting the real part and imaginary part of the discrete Fourier transform DFT coefficient of each symbol in the preamble of the random access message into the first AI model to obtain the number of terminals.

[0092] In combination with some embodiments of the second aspect, in some embodiments, the random access request message is msg1 in the four-step random access process, wherein the first terminal determines the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals, and the second AI model, including: inputting the real part and imaginary part of the DFT coefficient of each symbol in the preamble of the random access message, and the number of terminals into the second AI model to obtain the ToA corresponding to the random access request message provided by each terminal.

[0093] In combination with some embodiments of the second aspect, in some embodiments, the network device is a satellite, and the random access request message is received by the network device during a visible window.

[0094] In combination with some embodiments of the second aspect, in some embodiments, the above method also includes: the first terminal determines a third training data set, wherein the third training data set includes sample random access request messages provided by multiple terminals; and trains the initial third AI model according to the third training data set to obtain the first AI model.

[0095] In the above embodiment, the first terminal can train the initial first AI model based on the first training data set to obtain the first AI model, and then deploy it on the network device side, or on the first terminal side, to apply it on the network device side or the terminal side to determine the number of terminals.

[0096] In combination with some embodiments of the second aspect, in some embodiments, the above method also includes: the first terminal determines a fourth training data set, wherein the fourth training data set includes sample random access request messages provided by multiple terminals, and sample ToA corresponding to the sample random access request message sent by each terminal; training the initial fourth AI model according to the fourth training data set to obtain a second AI model.

[0097] In the above embodiment, the first terminal can train the initial second AI model based on the second training data set to obtain a second AI model, which is then deployed on the network device side, or deployed on the first terminal side, for application on the network device side or the terminal side to determine the ToA corresponding to the random access request message provided by each terminal.

[0098] In a third aspect, an embodiment of the present disclosure proposes a random access method, in which a first terminal determines the number of terminals providing random access request messages based on the random access request message and the first AI model received by the network device; the network device determines the number of terminals providing random access request messages, wherein the number of terminals is determined based on the random access request message and the first AI model received by the network device; the network device schedules the transmission of a random access response message based on the number of terminals.

[0099] In a fourth aspect, an embodiment of the present disclosure proposes a network device, which includes at least one of a transceiver module and a processing module; wherein the network device is used to execute the optional implementation method of the first aspect.

[0100] In a fifth aspect, an embodiment of the present disclosure proposes a first terminal, which includes at least one of a transceiver module and a processing module; wherein the first terminal is used to execute the optional implementation method of the second aspect.

[0101] In a sixth aspect, an embodiment of the present disclosure proposes a network device, which includes: one or more processors; a memory coupled to the processor, on which instructions are stored, and when the instructions are executed by the processor, the network device is used to execute the optional implementation method of the first aspect.

[0102] In the seventh aspect, an embodiment of the present disclosure proposes a first terminal, which includes: one or more processors; a memory coupled to the processor, which stores instructions, and when the instructions are executed by the processor, the first terminal is used to execute the optional implementation method of the second aspect.

[0103] In an eighth aspect, an embodiment of the present disclosure proposes a communication system, which includes: a first terminal and a network device; wherein the network device is configured to execute the method described in the optional implementation manner of the first aspect, and the first terminal is configured to execute the method described in the optional implementation manner of the second aspect.

[0104] In a ninth aspect, an embodiment of the present disclosure proposes a storage medium, which stores instructions. When the instructions are executed on a communication device, the communication device executes the method described in the optional implementation of the first and second aspects.

[0105] In a tenth aspect, an embodiment of the present disclosure proposes a program product. When the program product is executed by a communication device, the communication device executes the method described in the optional implementation of the first and second aspects.

[0106] In an eleventh aspect, an embodiment of the present disclosure proposes a computer program, which, when executed on a computer, enables the computer to execute the method described in the optional implementation of the first and second aspects.

[0107] In a twelfth aspect, an embodiment of the present disclosure provides a chip or a chip system, wherein the chip or chip system includes a processing circuit configured to execute the method described in the optional implementation of the first and second aspects above.

[0108] It is understandable that the first terminal, network device, communication system, storage medium, program product, computer program, chip, or chip system described above are all used to perform the method proposed in the embodiment of the present disclosure. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding method and will not be repeated here.

[0109] The embodiments of the present disclosure provide a random access method, a terminal, and a network device. In some embodiments, the terms random access method, information processing method, communication method, etc. can be used interchangeably.

[0110] The embodiments of the present disclosure are not exhaustive and are merely illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, each step in a certain embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined. For example, some or all steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0111] In each embodiment of the present disclosure, unless otherwise specified or provided for by logic, the terms and / or descriptions between the embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form a new embodiment based on their inherent logical relationships.

[0112] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure.

[0113] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular, such as "a", "an", "the", "above", "said", "the", "the", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun following the article may be understood as a singular expression or a plural expression.

[0114] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0115] In some embodiments, the terms "at least one," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0116] In some embodiments, descriptions such as "at least one of A and B," "A and / or B," "A in one case, B in another case," or "in response to one case A, in response to another case B" may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); and in some embodiments, A and B (both A and B are executed). The above is also applicable when there are more branches such as A, B, and C.

[0117] In some embodiments, "A or B" and other descriptions may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The above is also applicable when there are more branches such as A, B, C, etc.

[0118] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only used to distinguish different description objects and do not constitute any restriction on the position, order, priority, quantity or content of the description objects. For the statement of the description object, please refer to the description in the context of the claims or embodiments, and no unnecessary restriction should be constituted due to the use of prefixes. For example, if the description object is a "field", the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields". "First" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the description object is a "level", the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of description objects is not limited by the ordinal number and can be one or more. Taking "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes can be the same or different. For example, if the description object is "device", then the "first device" and the "second device" can be the same device or different devices, and their types can be the same or different; for another example, if the description object is "information", then the "first information" and the "second information" can be the same information or different information, and their contents can be the same or different.

[0119] In some embodiments, “including A,” “comprising A,” “used to indicate A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0120] In some embodiments, terms such as "in response to...", "in response to determining...", "in the case of...", "at the time of...", "when...", "if...", "if...", etc. can be used interchangeably.

[0121] In some embodiments, terms such as "greater than", "greater than or equal to", "not less than", "more than", "more than or equal to", "not less than", "higher than", "higher than or equal to", "not less than", and "above" can be replaced with each other, and terms such as "less than", "less than or equal to", "not greater than", "less than", "less than or equal to", "not more than", "lower than", "lower than or equal to", "not higher than", and "below" can be replaced with each other.

[0122] In some embodiments, devices, etc. can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. Terms such as "device", "equipment", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", and "subject" can be used interchangeably.

[0123] In some embodiments, "network" can be interpreted as devices included in the network (eg, access network equipment, core network equipment, etc.).

[0124] In some embodiments, the terms "access network device (AN device)", "radio access network device (RAN device)", "base station (BS)", "radio base station" "fixed station", "node", "access point", "transmission point (TP)", "reception point (RP)", "transmission / reception point (TRP)" "panel", "antenna panel", "antenna array", "cell", "macro cell", "small cell", "femto cell", "pico cell", "sector", "cell group", "serving cell", "carrier", "component carrier", "bandwidth part (BWP)" and the like may be used interchangeably.

[0125] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, etc. can be used interchangeably.

[0126] In some embodiments, the access network device, the core network device, or the network device can be replaced by a terminal. For example, the various embodiments of the present disclosure can also be applied to a structure in which the communication between the access network device, the core network device, or the network device and the terminal is replaced by communication between multiple terminals (for example, device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, it is also possible to set the structure in which the terminal has all or part of the functions of the access network device. In addition, terms such as "uplink" and "downlink" can also be replaced by terms corresponding to communication between terminals (for example, "side"). For example, uplink channels, downlink channels, etc. can be replaced by side channels, and uplinks, downlinks, etc. can be replaced by side links.

[0127] In some embodiments, the terminal may be replaced by an access network device, a core network device, or a network device. In this case, the access network device, the core network device, or the network device may have a structure that has all or part of the functions of the terminal.

[0128] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0129] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0130] In addition, each element, each row, or each column in the table of the embodiment of the present disclosure can be implemented as an independent embodiment, and the combination of any elements, any rows, and any columns can also be implemented as an independent embodiment.

[0131] FIG1 is an architecture diagram of a communication system provided by an embodiment of the present disclosure.

[0132] As shown in FIG1 , a communication system 100 includes a terminal 101 and a network device 102 .

[0133] In some embodiments, the terminal 101 includes, for example, a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, and at least one of a wireless terminal device in a smart home, but is not limited thereto.

[0134] In some embodiments, the network device 102 may include at least one of an access network device and a core network device.

[0135] In some embodiments, the access network device is, for example, a node or device that accesses a terminal to a wireless network. The access network device may include an evolved NodeB (eNB), a next generation evolved NodeB (ng-eNB), a next generation NodeB (gNB), a node B (NB), a home node B (HNB), a home evolved nodeB (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an open base station (Open RAN), a cloud base station (cloud RAN), a base station in other communication systems, and at least one of an access node in a Wi-Fi system, but is not limited thereto.

[0136] In some embodiments, the core network device may be a single device including a first network function, a second network function, etc., or may be a plurality of devices or a group of devices each including all or part of the first network function, the second network function, etc. The network function may be virtual or physical. The core network may include, for example, at least one of an evolved packet core (EPC), a 5G core network (5GCN), and a next generation core (NGC).

[0137] In some embodiments, the first network function is, for example, an access and mobility management function (AMF).

[0138] In some embodiments, the first network function is used for access control and mobility management of the terminal accessing the operator network, for example, including functions such as mobile status management, allocation of user temporary identity, authentication and authorization of users, etc., and its name is not limited to this.

[0139] It can be understood that the communication system described in the embodiment of the present disclosure is for the purpose of more clearly illustrating the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution proposed in the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of the system architecture and the emergence of new business scenarios, the technical solution proposed in the embodiment of the present disclosure is also applicable to similar technical problems.

[0140] The following embodiments of the present disclosure may be applied to the communication system 100 shown in FIG1 , or a portion thereof, but are not limited thereto. The entities shown in FIG1 are illustrative only. The communication system may include all or part of the entities shown in FIG1 , or may include other entities outside of FIG1 . The number and form of the entities are arbitrary, and the entities may be physical or virtual. The connection relationships between the entities are illustrative only. The entities may be connected or disconnected, and the connection may be in any manner, including direct or indirect, wired or wireless.

[0141] The embodiments of the present disclosure may be applied to long term evolution (LTE), LTE-advanced (LTE-A), LTE-beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G new radio (NR), future radio access (FRA), new radio access technology (RAT), new radio (NR), new radio access (NX), future generation radio access (FX), global system for mobile communications (GSM (registered trademark)), CDMA2000, ultra mobile broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, ultra-wideband (UWB), and the like. band, UWB), Bluetooth (registered trademark), public land mobile network (PLMN) network, device-to-device (D2D) system, machine-to-machine (M2M) system, Internet of Things (IoT) system, vehicle-to-everything (V2X), systems using other communication methods, and next-generation systems based on them. In addition, multiple systems can also be combined (for example, a combination of LTE or LTE-A and 5G) for application.

[0142] In the related art, for a random access request message received by a network device, it is impossible to determine the number of terminals providing the random access request message, which is a problem that needs to be solved urgently.

[0143] Based on this, embodiments of the present disclosure provide a random access method, terminal, and network device, wherein the method performed by the network device includes: determining the number of terminals that provide random access request messages, wherein the number of terminals is determined based on the random access request messages received by the network device and a first AI model; and scheduling the transmission of random access response messages based on the number of terminals. Thus, the network device can determine the number of terminals that provide random access request messages and schedule the transmission of random access response messages based on the number of terminals, thereby providing network services to each terminal based on the determined number of terminals, thereby improving the performance of the communication system.

[0144] FIG2A is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG2A , the embodiment of the present disclosure relates to a random access method, which includes:

[0145] S201A: The network device determines the number of terminals that provide random access request messages, and schedules transmission of random access response messages based on the number of terminals.

[0146] It is understandable that the network device may receive multiple random access request messages sent by at least one terminal in a short period of time or at the same time. For the multiple random access request messages received, message flow congestion may occur. The network device cannot respond to each random access request message in a timely manner, which may cause some of the messages to be discarded, resulting in network services for some terminals being unavailable and communication system performance being degraded.

[0147] In this case, in an embodiment of the present disclosure, the network device can determine the number of terminals that provide random access request messages and, based on the number of terminals, schedule the transmission of random access response messages. Thus, the network device can provide network services to each terminal based on the determined number of terminals, thereby improving the performance of the communication system.

[0148] In some embodiments, the number of terminals is determined based on the random access request message received by the network device and the first AI model.

[0149] In one possible implementation, the first AI model is deployed on the network device side. After receiving the random access request message, the network device can determine the number of terminals based on the received random access request message and the first AI model. Then, the network device can schedule the transmission of the random access response message based on the number of terminals.

[0150] In another possible implementation, the first AI model is deployed on a specific terminal side, for example, on the first terminal side. After receiving the random access request message, the network device may send the random access request message to the first terminal. The first terminal side determines the number of terminals based on the random access request message received by the network device and the first AI model. Furthermore, the first terminal may send the determined number of terminals to the network device, and the network device may schedule the transmission of the random access response message based on the number of terminals.

[0151] In an embodiment of the present disclosure, the network device determines the number of terminals that provide random access request messages, and may determine the number of terminals that provide random access request messages based on the received random access request message and a first AI model deployed on the network device side; or the network device may send the received random access request message to the first terminal, determine the number of terminals on the first terminal side based on the random access request message and the first AI model deployed on the first terminal side, and further receive an indication sent by the terminal to determine the number of terminals that provide random access request messages.

[0152] In an embodiment of the present disclosure, a network device, upon determining the number of terminals that provide random access request messages, can schedule the transmission of random access response messages based on the number of terminals. Thus, the network device can provide network services to each terminal based on the determined number of terminals, thereby improving the performance of the communication system.

[0153] It can be understood that the first AI model is deployed on the network device side. It can be trained on the network device side, or it can be sent to the network device after training on a specific terminal side (for example, the first terminal side).

[0154] In some embodiments, when the first AI model is obtained through training on the network device side, the network device determines a first training data set, wherein the first training data set includes sample random access request messages provided by multiple terminals; and trains the initial first AI model according to the first training data set to obtain the first AI model.

[0155] In an embodiment of the present disclosure, when the first AI model is obtained through training on the network device side, the network device can determine a first training data set, train the initial first AI model according to the first training data set, and obtain the first AI model.

[0156] The first training data set includes sample random access request messages provided by multiple terminals, and the network device can collect the random access request messages sent by multiple terminals as the first training data set.

[0157] It should be noted that the initial first AI model can be a neural network model, a machine learning model, etc.

[0158] It can be understood that the first AI model is deployed on the first terminal side. It can be obtained by training on the first terminal side, or it can be sent to the first terminal after training on the network device side.

[0159] In some embodiments, when the first AI model is obtained through training on the first terminal side, the first terminal determines a third training data set, wherein the third training data set includes sample random access request messages provided by multiple terminals; and trains the initial third AI model according to the third training data set to obtain the first AI model.

[0160] In an embodiment of the present disclosure, when the first AI model is obtained through training on the first terminal side, the first terminal can determine a third training data set, train the initial third AI model according to the third training data set, and obtain the first AI model.

[0161] Among them, the third training data set includes sample random access request messages provided by multiple terminals. The network device can collect random access request messages sent by multiple terminals and provide them to the first terminal, so that the first terminal can obtain multiple random access request messages sent from the network device as the third training data set.

[0162] It should be noted that the initial third AI model can be a neural network model, a machine learning model, etc.

[0163] In some embodiments, the random access request message includes at least one of the following:

[0164] Message msg1 in the 4-step random access process;

[0165] msg3 in the 4-step random access process;

[0166] msgA in the 2-step random access process.

[0167] In the embodiment of the present disclosure, the random access request message includes msg1 in the four-step random access process.

[0168] Exemplarily, the network device receives multiple msg1s sent by at least one terminal, determines the number of terminals providing the multiple msg1s, and then schedules transmission of random access response messages based on the number of terminals.

[0169] In the embodiment of the present disclosure, the random access request message includes msg3 in the four-step random access process.

[0170] Exemplarily, the network device receives multiple msg3s sent by at least one terminal, determines the number of terminals providing multiple msg1s, and then schedules transmission of random access response messages based on the number of terminals.

[0171] In the embodiment of the present disclosure, the random access request message includes msgA in the 2-step random access process.

[0172] Exemplarily, the network device receives multiple msgAs sent by at least one terminal, determines the number of terminals providing multiple msg1s, and then schedules transmission of random access response messages based on the number of terminals.

[0173] In some embodiments, the random access response message includes at least one of the following:

[0174] msg2 in the 4-step random access process;

[0175] msg4 in the 4-step random access process;

[0176] msgB in the 2-step random access process.

[0177] In the embodiment of the present disclosure, the random access response message includes msg2 in the 4-step random access process.

[0178] Exemplarily, the network device receives multiple msg1s sent by at least one terminal, determines the number of terminals providing the multiple msg1s, and then schedules transmission of msg2 based on the number of terminals.

[0179] In the embodiment of the present disclosure, the random access response message includes msg4 in the 4-step random access process.

[0180] Exemplarily, the network device receives multiple msg3s sent by at least one terminal, determines the number of terminals providing the multiple msg3s, and then schedules the transmission of msg4 based on the number of terminals.

[0181] In the embodiment of the present disclosure, the random access response message includes msgB in the 2-step random access process.

[0182] Exemplarily, the network device receives multiple msgA sent by at least one terminal, determines the number of terminals providing the multiple msgA, and then schedules the transmission of msgB based on the number of terminals.

[0183] In some embodiments, the random access request message is msg1 in a four-step random access process, wherein the network device determines the number of terminals based on the received random access request message and the first AI model, including: inputting the real part and the imaginary part of the discrete Fourier transform DFT coefficient of each symbol in the preamble of the random access message into the first AI model to obtain the number of terminals.

[0184] In an embodiment of the present disclosure, the network device determines the number of terminals based on the received random access request message and the first AI model. The real part (Re(y)) and the imaginary part (Im(y)) of the discrete Fourier transform (DFT) coefficient of each symbol in the preamble of the random access message can be input into the first AI model deployed on the network device side. After prediction by the first AI model, the number of terminals is obtained.

[0185] In some embodiments, the random access request message is msg1 in a four-step random access process, wherein the first terminal determines the number of terminals providing the random access request message based on the random access request message received by the network device and the first AI model, including: inputting the real part and the imaginary part of the discrete Fourier transform DFT coefficient of each symbol in the preamble of the random access message into the first AI model to obtain the number of terminals.

[0186] In an embodiment of the present disclosure, the first terminal determines the number of terminals based on the random access request message and the first AI model received by the network device. The real part and the imaginary part of the DFT coefficient of each symbol in the preamble of the random access message can be input into the first AI model deployed on the first terminal side. The number of terminals is obtained through prediction by the first AI model.

[0187] In some embodiments, the network device is a satellite, and the access request message is received by the network device during a visibility window.

[0188] It is understandable that the network device is a satellite, which has a visible window period, and the visible window period of the satellite is relatively short. When multiple terminals access the network device during a relatively short visible window period, the random access request messages of multiple terminals will cause message flow congestion. The network device cannot respond to each random access request message in a timely manner, which may cause some of the messages to be discarded, resulting in network services for some terminals being unavailable and communication system performance being degraded.

[0189] In this case, in an embodiment of the present disclosure, the network device can determine the number of terminals that provide random access request messages and, based on the number of terminals, schedule the transmission of random access response messages. Thus, the network device can provide network services to each terminal based on the determined number of terminals, thereby improving the performance of the communication system.

[0190] By implementing the embodiments of the present disclosure, a network device determines the number of terminals that provide random access request messages and schedules the transmission of random access response messages based on the number of terminals. Thus, the network device can provide network services to each terminal based on the determined number of terminals, thereby improving the performance of the communication system.

[0191] In some embodiments, the names of information, etc. are not limited to the names described in the embodiments, and terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", "field", "symbol", "symbol", "codeword", "codebook", "codeword", "codepoint", "bit", "data", "program", and "chip" can be used interchangeably.

[0192] In some embodiments, terms such as "moment", "time point", "time", and "time position" can be replaced with each other, and terms such as "duration", "period", "time window", "window", and "time" can be replaced with each other.

[0193] In some embodiments, terms such as "frame", "radio frame", "subframe", "slot", "sub-slot", "mini-slot", "symbol", "symbol", and "transmission time interval (TTI)" can be used interchangeably.

[0194] In some embodiments, "obtain", "get", "get", "receive", "transmit", "bidirectional transmission", "send and / or receive" can be interchangeable, and can be interpreted as receiving from other entities, obtaining from protocols, obtaining from higher layers, obtaining by self-processing, autonomous implementation, etc.

[0195] In some embodiments, terms such as "send", "transmit", "report", "download", "transmit", "bidirectional transmission", "send and / or receive" can be used interchangeably.

[0196] In some embodiments, terms such as "certain", "preset", "preset", "setting", "indicated", "a certain", "any", and "first" can be interchangeable. "Specific A", "preset A", "preset A", "setting A", "indicated A", "a certain A", "any A", and "first A" can be interpreted as A pre-specified in a protocol, etc., or as A obtained through setting, configuration, or indication, etc., or as specific A, a certain A, any A, or first A, etc., but not limited to this.

[0197] FIG2B is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG2B , the embodiment of the present disclosure relates to a random access method, which includes:

[0198] S201B: The network device determines the number of terminals that provide random access request messages.

[0199] In some embodiments, the number of terminals is determined based on the random access request message received by the network device and the first AI model.

[0200] Among them, the optional implementation of S201B can refer to the optional implementation of S201A in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0201] S202B: The network device determines the arrival time ToA corresponding to the random access request message provided by each terminal.

[0202] In some embodiments, a time of arrival (ToA) corresponding to the random access request message provided by each terminal is determined based on the random access request message, the number of terminals, and the second AI model.

[0203] In one possible implementation, the second AI model is deployed on the network device side. When determining the number of terminals providing random access request messages, the network device can determine the ToA corresponding to the random access request message provided by each terminal based on the combination of the received random access request message, the number of terminals and the second AI model.

[0204] In another possible implementation, the second AI model is deployed on a specific terminal side, for example, on the first terminal side. When the network device determines the number of terminals that provide random access request messages, it can provide the number of terminals and the random access request message to the first terminal. On the first terminal side, based on the random access request message, the number of terminals and the second AI model, the ToA corresponding to the random access request message provided by each terminal is determined.

[0205] The method for the network device to determine to provide a random access request message may refer to the relevant description in the above embodiment, which will not be repeated here.

[0206] In another possible implementation, the second AI model is deployed on a specific terminal side, for example, on a first terminal side. The network device may provide a random access request message to the first terminal. The first terminal may determine the number of terminals based on the random access request message and the first AI model. Then, on the first terminal side, based on the random access request message, the number of terminals and the second AI model, the ToA corresponding to the random access request message provided by each terminal is determined.

[0207] In some embodiments, the random access request message is msg1 in a four-step random access process, wherein the network device determines the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model, including: inputting the real part and the imaginary part of the DFT coefficient of each symbol in the preamble of the random access message, and the number of terminals into the second AI model to obtain the ToA corresponding to the random access request message provided by each terminal.

[0208] In an embodiment of the present disclosure, the network device determines the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model. The real part (Re(y)) and imaginary part (Im(y)) of the DFT coefficient of each symbol in the preamble of the random access message, as well as the number of terminals, can be input into the second AI model deployed on the network device side. After prediction by the second AI model, the ToA corresponding to the random access request message provided by each terminal is obtained.

[0209] In some embodiments, the random access request message is msg1 in a four-step random access process, wherein the first terminal determines the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model, including: inputting the real part and imaginary part of the DFT coefficient of each symbol in the preamble of the random access message, and the number of terminals into the second AI model to obtain the ToA corresponding to the random access request message provided by each terminal.

[0210] In an embodiment of the present disclosure, the first terminal determines the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model. The real part and imaginary part of the DFT coefficient of each symbol in the preamble of the random access message and the number of terminals can be input into the second AI model deployed on the first terminal side. After prediction by the second AI model, the ToA corresponding to the random access request message provided by each terminal is obtained.

[0211] It can be understood that the second AI model is deployed on the network device side. It can be obtained through training on the network device side, or it can be sent to the network device after training on a specific terminal side (for example, the first terminal side).

[0212] In some embodiments, when the second AI model is obtained through training on the network device side, the network device determines a second training data set, wherein the second training data set includes sample random access request messages provided by multiple terminals and sample ToA corresponding to the sample random access request message sent by each terminal; the initial second AI model is trained according to the second training data set to obtain a second AI model.

[0213] In an embodiment of the present disclosure, when the second AI model is obtained through training on the network device side, the network device can determine a second training data set, train the initial second AI model according to the second training data set, and obtain the second AI model.

[0214] Among them, the second training data set includes sample random access request messages provided by multiple terminals and the sample ToA corresponding to the sample random access request message sent by each terminal. The network device can collect the random access request messages sent by multiple terminals and the sample ToA corresponding to the sample random access request message sent by each terminal as the second training data set.

[0215] It should be noted that the initial second AI model can be a neural network model, a machine learning model, etc.

[0216] It can be understood that the second AI model is deployed on the first terminal side. It can be obtained through training on the first terminal side, or it can be sent to the first terminal after training on the network device side.

[0217] In some embodiments, when the second AI model is obtained through training on the first terminal side, the first terminal determines a fourth training data set, wherein the fourth training data set includes sample random access request messages provided by multiple terminals and sample ToA corresponding to the sample random access request message sent by each terminal; the initial fourth AI model is trained according to the fourth training data set to obtain a second AI model.

[0218] In an embodiment of the present disclosure, when the second AI model is obtained through training on the first terminal side, the first terminal can determine a fourth training data set, train the initial fourth AI model according to the fourth training data set, and obtain the second AI model.

[0219] Among them, the fourth training data set includes sample random access request messages provided by multiple terminals and the sample ToA corresponding to the sample random access request message sent by each terminal. The network device can collect the random access request messages sent by multiple terminals and the sample ToA corresponding to the sample random access request message sent by each terminal, and provide them to the first terminal, so that the first terminal can obtain multiple random access request messages sent and the sample ToA corresponding to the sample random access request message sent by each terminal from the network device as the fourth training data set.

[0220] It should be noted that the initial fourth AI model can be a neural network model, a machine learning model, etc.

[0221] S203B: The network device schedules transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal.

[0222] In an embodiment of the present disclosure, the network device, upon determining the number of terminals and the ToA corresponding to the random access request message provided by each terminal, can schedule the transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal, thereby accurately providing network services to each terminal and improving the performance of the communication system.

[0223] Exemplarily, the network device may determine the sending time or sending order of the random access response message for each terminal based on the ToA corresponding to the random access request message provided by each terminal, and then schedule the transmission of the random access response message according to the corresponding time sequence.

[0224] It should be noted that, for the relevant description of the random access request message and the random access response message, reference may be made to the relevant description in the above embodiment, which will not be repeated here.

[0225] In some embodiments, the network device is a satellite, and the access request message is received by the network device during a visibility window.

[0226] It is understandable that the network device is a satellite, which has a visible window period, and the visible window period of the satellite is relatively short. When multiple terminals access the network device during a relatively short visible window period, the random access request messages of multiple terminals will cause message flow congestion. The network device cannot respond to each random access request message in a timely manner, which may cause some of the messages to be discarded, resulting in network services for some terminals being unavailable and communication system performance being degraded.

[0227] In this case, in an embodiment of the present disclosure, the network device can determine the number of terminals that provide random access request messages and the ToA corresponding to the random access request message provided by each terminal, and then schedule the transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal. As a result, the network device can provide network services to each terminal based on the determined number of terminals and the ToA corresponding to the random access request message provided by each terminal, thereby improving the performance of the communication system.

[0228] The communication method involved in the embodiments of the present disclosure may include at least one of S201B to S203B. For example, S201B may be implemented as an independent embodiment, S202B may be implemented as an independent embodiment, S203B may be implemented as an independent embodiment, S201B+S203B may be implemented as an independent embodiment, and S202B+S203B may be implemented as an independent embodiment, but the present invention is not limited thereto.

[0229] FIG2C is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG2C , the embodiment of the present disclosure relates to a random access method, which includes:

[0230] S201C: The network device determines the number of terminals based on the received random access request message and the first AI model.

[0231] In the embodiment of the present disclosure, the network device may receive a random access request message sent by at least one terminal.

[0232] In some embodiments, the network device is a satellite, and the access request message is received by the network device during a visibility window.

[0233] It can be understood that the network device is a satellite, the satellite has a visible window period, and the visible window period of the satellite is relatively short. The network device, which is a satellite, receives a random access request message sent by at least one terminal during the visible window period. Since the visible window period of the satellite is relatively short, the network device receives multiple random access request messages in a short period of time, and it is impossible to determine whether they are sent by the same terminal or different terminals.

[0234] Based on this, in an embodiment of the present disclosure, the network device may determine the number of terminals based on the received random access request message and the first AI model.

[0235] It can be understood that the first AI model is deployed on the network device side. It can be trained on the network device side, or it can be sent to the network device after training on a specific terminal side (for example, the first terminal side).

[0236] Among them, the relevant description of obtaining the first AI model by training on the network device side, or obtaining the first AI model by training on the first terminal side can be found in the relevant description in the above embodiments, and will not be repeated here.

[0237] In some embodiments, the random access request message is msg1 in a four-step random access process, wherein the network device determines the number of terminals based on the received random access request message and the first AI model, including: inputting the real part and the imaginary part of the discrete Fourier transform DFT coefficient of each symbol in the preamble of the random access message into the first AI model to obtain the number of terminals.

[0238] In an embodiment of the present disclosure, the network device determines the number of terminals based on the received random access request message and the first AI model. The real part (Re(y)) and the imaginary part (Im(y)) of the DFT coefficient of each symbol in the preamble of the random access message can be input into the first AI model deployed on the network device side. The number of terminals can be obtained through prediction by the first AI model.

[0239] S202C: The network device determines a ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals, and the second AI model.

[0240] In an embodiment of the present disclosure, a network device receives a random access request message sent by at least one terminal, determines the number of terminals based on the received random access request message and a first AI model, and then determines a ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals, and the second AI model.

[0241] In an embodiment of the present disclosure, the second AI model is deployed on the network device side. When the network device determines the number of terminals providing random access request messages, it can determine the ToA corresponding to the random access request message provided by each terminal based on the combination of the received random access request message, the number of terminals and the second AI model.

[0242] It can be understood that the second AI model is deployed on the network device side. It can be obtained through training on the network device side, or it can be sent to the network device after training on a specific terminal side (for example, the first terminal side).

[0243] Among them, the relevant description of obtaining the second AI model by training on the network device side, or obtaining the second AI model by training on the first terminal side can be found in the relevant description in the above embodiments, and will not be repeated here.

[0244] In some embodiments, the random access request message is msg1 in a four-step random access process, wherein the network device determines the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model, including: inputting the real part and the imaginary part of the DFT coefficient of each symbol in the preamble of the random access message, and the number of terminals into the second AI model to obtain the ToA corresponding to the random access request message provided by each terminal.

[0245] In an embodiment of the present disclosure, the network device determines the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model. The real part (Re(y)) and imaginary part (Im(y)) of the DFT coefficient of each symbol in the preamble of the random access message, as well as the number of terminals, can be input into the second AI model deployed on the network device side. After prediction by the second AI model, the ToA corresponding to the random access request message provided by each terminal is obtained.

[0246] S203C: The network device schedules transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal.

[0247] Among them, the optional implementation of S203C can refer to the optional implementation of S203B in Figure 2B and other related parts in the embodiment involved in Figure 2B, which will not be repeated here.

[0248] The communication method involved in the embodiments of the present disclosure may include at least one of S201C to S203C. For example, S201C may be implemented as an independent embodiment, S202C may be implemented as an independent embodiment, S203C may be implemented as an independent embodiment, S201C + S203C may be implemented as an independent embodiment, and S202C + S203C may be implemented as an independent embodiment, but the present invention is not limited thereto.

[0249] FIG2D is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG2D , the embodiment of the present disclosure relates to a random access method, which includes:

[0250] S201D: The network device sends third indication information to the first terminal, where the third indication information is used to indicate the random access request message received by the network device.

[0251] In an embodiment of the present disclosure, a network device receives a random access request message sent by at least one terminal and may send third indication information to a first terminal, where the third indication information is used to indicate the random access request message received by the network device.

[0252] In some embodiments, the network device sends the third indication information to the first terminal on its own, or sends the third indication information to the first terminal when a specific condition is met.

[0253] Exemplarily, when the first terminal is required to determine ToA information corresponding to the random access request message provided by each terminal, the network device sends third indication information to the first terminal.

[0254] In some embodiments, the network device reuses existing signaling or messages to send the third indication information to the first terminal, or uses new signaling or messages to send the third indication information to the first terminal.

[0255] It can be understood that the network device and the first terminal can communicate, and the first terminal has established a communication connection with the network device.

[0256] S202D: The network device determines the number of terminals based on the received random access request message and the first AI model.

[0257] Among them, the optional implementation of S202B can refer to the optional implementation of S201A in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0258] S203D: The network device sends first indication information to the first terminal, where the first indication information is used to indicate the number of terminals.

[0259] In an embodiment of the present disclosure, when determining the number of terminals that provide random access request messages, the network device may send first indication information to the first terminal, where the first indication information is used to indicate the number of terminals.

[0260] In some embodiments, the network device sends the first indication information to the first terminal on its own, or sends the first indication information to the first terminal when a specific condition is met.

[0261] Exemplarily, when the first terminal is required to determine ToA information corresponding to the random access request message provided by each terminal, the network device sends the first indication information to the first terminal.

[0262] In some embodiments, the network device reuses existing signaling or messages to send the first indication information to the first terminal, or uses new signaling or messages to send the first indication information to the first terminal.

[0263] It can be understood that the network device and the first terminal can communicate, and the first terminal has established a communication connection with the network device.

[0264] S204D: The first terminal determines, based on the random access request message, the number of terminals, and the second AI model, a ToA corresponding to the random access request message provided by each terminal.

[0265] In an embodiment of the present disclosure, the second AI model is deployed on the first terminal side. The first terminal receives the first indication information sent by the network device and can determine the number of terminals. In addition, the first terminal receives the third indication information sent by the network device and can determine the random access request message received by the network device. Then, the first terminal can determine the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model.

[0266] In some embodiments, the first terminal receives different signaling or messages sent by the network device, wherein the different signaling or messages respectively carry the first indication information and the third indication information; or the first terminal receives a single signaling or message sent by the network device, wherein the single signaling or message carries the first indication information and the third indication information. Thus, the first terminal can determine the number of terminals and the random access request message received by the network device.

[0267] It can be understood that the second AI model is deployed on the first terminal side. It can be obtained through training on the first terminal side, or it can be sent to the first terminal after training on the network device side.

[0268] Among them, the relevant description of obtaining the second AI model by training on the first terminal side, or obtaining the second AI model by training on the network device side can be found in the relevant description in the above embodiments, and will not be repeated here.

[0269] In some embodiments, the random access request message is msg1 in a four-step random access process, wherein the first terminal determines the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model, including: inputting the real part and imaginary part of the DFT coefficient of each symbol in the preamble of the random access message, and the number of terminals into the second AI model to obtain the ToA corresponding to the random access request message provided by each terminal.

[0270] In an embodiment of the present disclosure, the first terminal determines the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals and the second AI model. The real part and imaginary part of the DFT coefficient of each symbol in the preamble of the random access message and the number of terminals can be input into the second AI model deployed on the first terminal side. After prediction by the second AI model, the ToA corresponding to the random access request message provided by each terminal is obtained.

[0271] S205D: The first terminal sends fourth indication information to the network device, where the fourth indication information is used to indicate the ToA corresponding to the random access request message provided by each terminal.

[0272] In the embodiment of the present disclosure, when the first terminal determines the ToA corresponding to the random access request message provided by each terminal, it can send fourth indication information to the network device, where the fourth indication information is used to indicate the ToA corresponding to the random access request message provided by each terminal.

[0273] In some embodiments, the first terminal sends the fourth indication information to the network device on its own, or may also send the fourth indication information to the network device when specific conditions are met.

[0274] Exemplarily, when determining the ToA corresponding to the random access request message provided by each terminal, the first terminal sends fourth indication information to the network device based on the indication of the network device.

[0275] S206D: The network device schedules transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal.

[0276] Among them, the optional implementation of S206D can refer to the optional implementation of S203B in Figure 2B and other related parts in the embodiment involved in Figure 2B, which will not be repeated here.

[0277] The communication method involved in the embodiments of the present disclosure may include at least one of S201D to S206D. For example, S201D may be implemented as an independent embodiment, S202D may be implemented as an independent embodiment, S203D may be implemented as an independent embodiment, S204D may be implemented as an independent embodiment, S205D may be implemented as an independent embodiment, and S206D may be implemented as an independent embodiment, but are not limited thereto.

[0278] In some embodiments, S201D and S202D may be executed in an exchanged order or simultaneously, and S201D and S203D may be executed in an exchanged order or simultaneously.

[0279] FIG2E is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG2E , the embodiment of the present disclosure relates to a random access method, which includes:

[0280] S201E: The network device sends third indication information to the first terminal, where the third indication information is used to indicate a random access request message received by the network device.

[0281] Among them, the optional implementation of S201E can refer to the optional implementation of S201D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0282] S202E: The first terminal determines the number of terminals that provide random access request messages based on the random access request message received by the network device and the first AI model.

[0283] In an embodiment of the present disclosure, the first AI model is deployed on the first terminal side. After the first terminal receives the third indication information sent by the network device and determines that the network device has received a random access request message, the number of terminals can be determined based on the random access request message received by the network device and the first AI model.

[0284] It can be understood that the first AI model is deployed on the first terminal side. It can be obtained by training on the first terminal side, or it can be sent to the first terminal after training on the network device side.

[0285] Among them, the relevant description of obtaining the first AI model by training on the first terminal side, or obtaining the first AI model by training on the network device side can be found in the relevant description in the above embodiments, and will not be repeated here.

[0286] In some embodiments, the random access request message is msg1 in a four-step random access process, wherein the first terminal determines the number of terminals providing the random access request message based on the random access request message received by the network device and the first AI model, including: inputting the real part and the imaginary part of the discrete Fourier transform DFT coefficient of each symbol in the preamble of the random access message into the first AI model to obtain the number of terminals.

[0287] In an embodiment of the present disclosure, the first terminal determines the number of terminals based on the random access request message and the first AI model received by the network device. The real part and the imaginary part of the DFT coefficient of each symbol in the preamble of the random access message can be input into the first AI model deployed on the first terminal side. The number of terminals is obtained through prediction by the first AI model.

[0288] S203E: The first terminal sends second indication information to the network device, where the second indication information is used to indicate the number of terminals.

[0289] In the embodiment of the present disclosure, when the first terminal determines the number of terminals, it may send second indication information to the network device, where the second indication information is used to indicate the number of terminals.

[0290] In some embodiments, the first terminal sends the second indication information to the network device on its own, or may also send the second indication information to the network device when specific conditions are met.

[0291] Exemplarily, when determining the number of terminals, the first terminal sends second indication information to the network device based on an indication of the network device.

[0292] S204E: The network device determines a ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals, and the second AI model.

[0293] Among them, the optional implementation of S204E can refer to the optional implementation of S202C in Figure 2C and other related parts in the embodiment involved in Figure 2C, which will not be repeated here.

[0294] S205E: The network device schedules transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal.

[0295] Among them, the optional implementation of S205E can refer to the optional implementation of S203B in Figure 2B and other related parts in the embodiment involved in Figure 2B, which will not be repeated here.

[0296] The communication method involved in the embodiments of the present disclosure may include at least one of S201E to S205E. For example, S201E may be implemented as an independent embodiment, S202E may be implemented as an independent embodiment, S203E may be implemented as an independent embodiment, S204E may be implemented as an independent embodiment, and S205E may be implemented as an independent embodiment, but are not limited thereto.

[0297] FIG2F is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG2F , the embodiment of the present disclosure relates to a random access method, which includes:

[0298] S201F: The network device sends third indication information to the first terminal, where the third indication information is used to indicate the random access request message received by the network device.

[0299] Among them, the optional implementation of S201F can refer to the optional implementation of S201D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0300] S202F: The first terminal determines the number of terminals that provide random access request messages based on the random access request message received by the network device and the first AI model.

[0301] Among them, the optional implementation of S202F can refer to the optional implementation of S202E in Figure 2E and other related parts in the embodiment involved in Figure 2E, which will not be repeated here.

[0302] S203F, the first terminal sends second indication information to the network device, where the second indication information is used to indicate the number of terminals.

[0303] Among them, the optional implementation of S203F can refer to the optional implementation of S203E in Figure 2E and other related parts in the embodiment involved in Figure 2E, which will not be repeated here.

[0304] S204F: The first terminal determines, based on the random access request message, the number of terminals, and the second AI model, a ToA corresponding to the random access request message provided by each terminal.

[0305] Among them, the optional implementation of S204F can refer to the optional implementation of S204D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0306] S205F: The first terminal sends fourth indication information to the network device, where the fourth indication information is used to indicate the ToA corresponding to the random access request message provided by each terminal.

[0307] Among them, the optional implementation of S205F can refer to the optional implementation of S205D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0308] S206F: The network device schedules transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal.

[0309] Among them, the optional implementation of S206F can refer to the optional implementation of S203B in Figure 2B and other related parts in the embodiment involved in Figure 2B, which will not be repeated here.

[0310] The communication method involved in the embodiments of the present disclosure may include at least one of S201F to S206F. For example, S201F may be implemented as an independent embodiment, S202F may be implemented as an independent embodiment, S203F may be implemented as an independent embodiment, S204F may be implemented as an independent embodiment, S205F may be implemented as an independent embodiment, and S206F may be implemented as an independent embodiment, but are not limited thereto.

[0311] In some embodiments, S203F and S204F may be executed in an exchanged order or simultaneously, and S203F and S205F may be executed in an exchanged order or simultaneously.

[0312] FIG3A is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG3A , the embodiment of the present disclosure relates to a random access method, which is executed by a network device and includes:

[0313] S301A, sending third indication information.

[0314] Among them, the optional implementation of S301A can refer to the optional implementation of S201D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0315] In some embodiments, the network device sends the third indication information to the first terminal, but is not limited thereto, and the third indication information may also be sent to other entities.

[0316] Optionally, the third indication information is used by the first terminal to determine a ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals, and the second AI model. For optional implementations, see the optional implementation of S204D in Figure 2D and other related parts of the embodiment involved in Figure 2D, which will not be repeated here.

[0317] In some embodiments, the third indication information is used to indicate a random access request message received by the network device.

[0318] S302A: Determine the number of terminals based on the received random access request message and the first AI model.

[0319] Among them, the optional implementation of S302A can refer to the optional implementation of S201A in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0320] S303A, sending first indication information.

[0321] Among them, the optional implementation of S303A can refer to the optional implementation of S203D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0322] In some embodiments, the network device sends the first indication information to the first terminal, but is not limited thereto, and the first indication information may also be sent to other entities.

[0323] Optionally, the first indication information is used by the first terminal to determine a ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals, and the second AI model. For optional implementations, see the optional implementation of S204D in Figure 2D and other related parts of the embodiment involved in Figure 2D, which will not be repeated here.

[0324] In some embodiments, the first indication information is used to indicate the number of terminals.

[0325] S304A, obtain fourth indication information.

[0326] Among them, the optional implementation of S304A can refer to the optional implementation of S205D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0327] In some embodiments, the network device receives the fourth indication information sent by the first terminal, but is not limited thereto, and may also receive the fourth indication information sent by other entities.

[0328] In some embodiments, the network device obtains fourth indication information specified by the protocol.

[0329] In some embodiments, the network device obtains the fourth indication information from an upper layer(s).

[0330] In some embodiments, the network device performs processing to obtain the fourth indication information.

[0331] In some embodiments, S304A is omitted, and the network device autonomously implements the function indicated by the fourth indication information, or the above function is default or acquiescent.

[0332] In some embodiments, the fourth indication information is used to indicate the ToA corresponding to the random access request message provided by each terminal.

[0333] In some embodiments, the ToA corresponding to the random access request message provided by each terminal is determined by the first terminal based on the random access request message, the number of terminals and the second AI model.

[0334] S305A: Schedule transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal.

[0335] Among them, the optional implementation of S305A can refer to the optional implementation of S203B in Figure 2B and other related parts in the embodiment involved in Figure 2B, which will not be repeated here.

[0336] It should be noted that, for the relevant description of the random access request message and the random access response message, reference may be made to the relevant description in the above embodiment, which will not be repeated here.

[0337] The communication method involved in the embodiments of the present disclosure may include at least one of S301A to S305A. For example, S301A may be implemented as an independent embodiment, S302A may be implemented as an independent embodiment, S303A may be implemented as an independent embodiment, S304A may be implemented as an independent embodiment, and S305A may be implemented as an independent embodiment, but are not limited thereto.

[0338] In some embodiments, S301A and S302A may be executed in an exchanged order or simultaneously, and S301A and S303A may be executed in an exchanged order or simultaneously.

[0339] FIG3B is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG3B , the embodiment of the present disclosure relates to a random access method, which is executed by a network device and includes:

[0340] S301B, sending third indication information.

[0341] Among them, the optional implementation of S301B can refer to the optional implementation of S201D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0342] Among them, the optional implementation of S301B can refer to the optional implementation of S301A in Figure 3A and other related parts in the embodiment involved in Figure 3A, which will not be repeated here.

[0343] In some embodiments, the third indication information is used to indicate a random access request message received by the network device.

[0344] S302B: Obtain second indication information.

[0345] Among them, the optional implementation of S302B can refer to the optional implementation of S203E in Figure 2E and other related parts in the embodiment involved in Figure 2E, which will not be repeated here.

[0346] In some embodiments, the network device receives the second indication information sent by the first terminal, but is not limited thereto, and may also receive the second indication information sent by other entities.

[0347] In some embodiments, the network device obtains second indication information specified by a protocol.

[0348] In some embodiments, the network device obtains the second indication information from an upper layer(s).

[0349] In some embodiments, the network device performs processing to obtain the second indication information.

[0350] In some embodiments, S302B is omitted, and the network device autonomously implements the function indicated by the second indication information, or the above function is default or acquiescent.

[0351] In some embodiments, the second indication information is used to indicate the number of terminals.

[0352] In some embodiments, the number of terminals is determined by the first terminal based on the random access request message received by the network device and the first AI model.

[0353] S303B: Determine, based on the random access request message, the number of terminals, and the second AI model, a ToA corresponding to the random access request message provided by each terminal.

[0354] Among them, the optional implementation of S303B can refer to the optional implementation of S202C in Figure 2C and other related parts in the embodiment involved in Figure 2C, which will not be repeated here.

[0355] S304B: Schedule transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal.

[0356] Among them, the optional implementation of S304B can refer to the optional implementation of S203B in Figure 2B and other related parts in the embodiment involved in Figure 2B, which will not be repeated here.

[0357] It should be noted that, for the relevant description of the random access request message and the random access response message, reference may be made to the relevant description in the above embodiment, which will not be repeated here.

[0358] The communication method involved in the embodiments of the present disclosure may include at least one of S301B to S304B. For example, S301B may be implemented as an independent embodiment, S302B may be implemented as an independent embodiment, S303B may be implemented as an independent embodiment, and S304B may be implemented as an independent embodiment, but are not limited thereto.

[0359] FIG3C is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG3C , the embodiment of the present disclosure relates to a random access method, which is executed by a network device and includes:

[0360] S301C, sending third indication information.

[0361] Among them, the optional implementation of S301C can refer to the optional implementation of S201D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0362] Among them, the optional implementation of S301C can refer to the optional implementation of S301A in Figure 3A and other related parts in the embodiment involved in Figure 3A, which will not be repeated here.

[0363] In some embodiments, the third indication information is used to indicate a random access request message received by the network device.

[0364] S302C: Obtain second indication information.

[0365] Among them, the optional implementation of S302C can refer to the optional implementation of S203E in Figure 2E and other related parts in the embodiment involved in Figure 2E, which will not be repeated here.

[0366] Among them, the optional implementation of S302C can refer to the optional implementation of S302A in Figure 3A and other related parts in the embodiment involved in Figure 3A, which will not be repeated here.

[0367] In some embodiments, the second indication information is used to indicate the number of terminals.

[0368] S303C, obtain fourth indication information.

[0369] Among them, the optional implementation of S303C can refer to the optional implementation of S205D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0370] Among them, the optional implementation of S303C can refer to the optional implementation of S304A in Figure 3A and other related parts in the embodiment involved in Figure 3A, which will not be repeated here.

[0371] In some embodiments, the fourth indication information is used to indicate the ToA corresponding to the random access request message provided by each terminal.

[0372] S304C: Schedule transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal.

[0373] Among them, the optional implementation of S304C can refer to the optional implementation of S203B in Figure 2B and other related parts in the embodiment involved in Figure 2B, which will not be repeated here.

[0374] It should be noted that, for the relevant description of the random access request message and the random access response message, reference may be made to the relevant description in the above embodiment, which will not be repeated here.

[0375] The communication method involved in the embodiments of the present disclosure may include at least one of S301C to S304C. For example, S301C may be implemented as an independent embodiment, S302C may be implemented as an independent embodiment, S303C may be implemented as an independent embodiment, and S304C may be implemented as an independent embodiment, but are not limited thereto.

[0376] In some embodiments, S302C and S303C may be executed in an interchanged order or simultaneously.

[0377] FIG4A is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG4A , the embodiment of the present disclosure relates to a random access method, which is performed by a first terminal and includes:

[0378] S401A, obtain third indication information.

[0379] Among them, the optional implementation of S401A can refer to the optional implementation of S201D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0380] In some embodiments, the first terminal receives the third indication information sent by the network device, but is not limited thereto, and may also receive the third indication information sent by other entities.

[0381] In some embodiments, the first terminal obtains third indication information specified by the protocol.

[0382] In some embodiments, the first terminal obtains the third indication information from an upper layer(s).

[0383] In some embodiments, the first terminal performs processing to obtain the third indication information.

[0384] In some embodiments, S3101 is omitted, and the first terminal autonomously implements the function indicated by the third indication information, or the above function is default or acquiescent.

[0385] In some embodiments, the third indication information is used to indicate a random access request message received by the network device.

[0386] S402A, obtain first indication information.

[0387] Among them, the optional implementation of S402A can refer to the optional implementation of S203D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0388] In some embodiments, the first terminal receives the first indication information sent by the network device, but is not limited thereto, and may also receive the first indication information sent by other entities.

[0389] In some embodiments, the first terminal obtains first indication information specified by a protocol.

[0390] In some embodiments, the first terminal obtains the first indication information from an upper layer(s).

[0391] In some embodiments, the first terminal performs processing to obtain the first indication information.

[0392] In some embodiments, S3101 is omitted, and the first terminal autonomously implements the function indicated by the first indication information, or the above function is default or acquiescent.

[0393] In some embodiments, the first indication information is used to indicate the number of terminals.

[0394] S403A: Determine, based on the random access request message, the number of terminals, and the second AI model, a ToA corresponding to the random access request message provided by each terminal.

[0395] Among them, the optional implementation of S403A can refer to the optional implementation of S204D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0396] S404A, sending fourth indication information.

[0397] Among them, the optional implementation of S404A can refer to the optional implementation of S205D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0398] In some embodiments, the fourth indication information is used to indicate the ToA corresponding to the random access request message provided by each terminal.

[0399] In some embodiments, the first terminal sends the fourth indication information to the network device, but is not limited thereto, and the fourth indication information may also be sent to other entities.

[0400] Optionally, the fourth indication information is used by the network device to schedule the transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal. For optional implementations, see the optional implementation of S206D in FIG. 2D and other related parts of the embodiment involved in FIG. 2D , which will not be repeated here.

[0401] The communication method involved in the embodiments of the present disclosure may include at least one of S401A to S404A. For example, S401A may be implemented as an independent embodiment, S402A may be implemented as an independent embodiment, S403A may be implemented as an independent embodiment, and S404A may be implemented as an independent embodiment, but are not limited thereto.

[0402] In some embodiments, S401A and S402A may be executed in an interchanged order or simultaneously.

[0403] FIG4B is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG4B , the embodiment of the present disclosure relates to a random access method, which is performed by a first terminal and includes:

[0404] S401B, obtain third indication information.

[0405] Among them, the optional implementation of S401B can refer to the optional implementation of S201D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0406] Among them, the optional implementation of S401B can refer to the optional implementation of S401A in Figure 4A and other related parts in the embodiment involved in Figure 4A, which will not be repeated here.

[0407] In some embodiments, the third indication information is used to indicate a random access request message received by the network device.

[0408] S402B: Determine the number of terminals that provide random access request messages based on the random access request message received by the network device and the first AI model.

[0409] Among them, the optional implementation of S402B can refer to the optional implementation of S202E in Figure 2E and other related parts in the embodiment involved in Figure 2E, which will not be repeated here.

[0410] S403B, sending second indication information.

[0411] Among them, the optional implementation of S403B can refer to the optional implementation of S203E in Figure 2E and other related parts in the embodiment involved in Figure 2E, which will not be repeated here.

[0412] In some embodiments, the second indication information is used to indicate the number of terminals.

[0413] In some embodiments, the first terminal sends the second indication information to the network device, but is not limited thereto, and the second indication information may also be sent to other entities.

[0414] Optionally, the second indication information is used by the network device to determine the ToA corresponding to the random access request message provided by each terminal based on the random access request message, the number of terminals, and the second AI model. Furthermore, the network device may schedule the transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal. For optional implementations, see S204E and S205E of Figure 2E , as well as other related parts of the embodiment involved in Figure 2E , which will not be repeated here.

[0415] The communication method involved in the embodiments of the present disclosure may include at least one of S401B to S403B. For example, S401B may be implemented as an independent embodiment, S402B may be implemented as an independent embodiment, and S403B may be implemented as an independent embodiment, but are not limited thereto.

[0416] FIG4C is an interactive diagram of a random access method according to an embodiment of the present disclosure. As shown in FIG4C , the embodiment of the present disclosure relates to a random access method, which is performed by a first terminal and includes:

[0417] S401C, obtain third indication information.

[0418] Among them, the optional implementation of S401C can refer to the optional implementation of S201D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0419] Among them, the optional implementation of S401C can refer to the optional implementation of S401A in Figure 4A and other related parts in the embodiment involved in Figure 4A, which will not be repeated here.

[0420] In some embodiments, the third indication information is used to indicate a random access request message received by the network device.

[0421] S402C: Determine the number of terminals that provide random access request messages based on the random access request message received by the network device and the first AI model.

[0422] Among them, the optional implementation of S402C can refer to the optional implementation of S202E in Figure 2E and other related parts in the embodiment involved in Figure 2E, which will not be repeated here.

[0423] S403C, sending second indication information.

[0424] Among them, the optional implementation of S403C can refer to the optional implementation of S203E in Figure 2E and other related parts in the embodiment involved in Figure 2E, which will not be repeated here.

[0425] Among them, the optional implementation of S403C can refer to the optional implementation of S403B in Figure 4B and other related parts in the embodiment involved in Figure 4B, which will not be repeated here.

[0426] In some embodiments, the second indication information is used to indicate the number of terminals.

[0427] S404C: Determine, based on the random access request message, the number of terminals, and the second AI model, a ToA corresponding to the random access request message provided by each terminal.

[0428] Among them, the optional implementation of S404C can refer to the optional implementation of S204D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0429] S405C, sending fourth indication information.

[0430] Among them, the optional implementation of S405C can refer to the optional implementation of S205D in Figure 2D and other related parts in the embodiment involved in Figure 2D, which will not be repeated here.

[0431] Among them, the optional implementation of S405C can refer to the optional implementation of S404A in Figure 4A and other related parts in the embodiment involved in Figure 4A, which will not be repeated here.

[0432] In some embodiments, the fourth indication information is used to indicate the ToA corresponding to the random access request message provided by each terminal.

[0433] Optionally, the second indication information and / or the fourth indication information are used by the network device to schedule the transmission of the random access response message based on the number of terminals and the ToA corresponding to the random access request message provided by each terminal. For optional implementations thereof, see the optional implementation of S206D in FIG. 2D and other related portions of the embodiment involved in FIG. 2D , and will not be further described here.

[0434] The communication method involved in the embodiments of the present disclosure may include at least one of S401C to S405C. For example, S401C may be implemented as an independent embodiment, S402C may be implemented as an independent embodiment, S403C may be implemented as an independent embodiment, S404C may be implemented as an independent embodiment, and S405C may be implemented as an independent embodiment, but are not limited thereto.

[0435] In some embodiments, S403C and S404C may be executed in an exchanged order or simultaneously, and S403C and S405C may be executed in an exchanged order or simultaneously.

[0436] In some embodiments, a non-terrestrial network (NTN) is one of the enabling technologies for implementing a global 6G system.

[0437] In some embodiments, NTN components fully integrated into 6G infrastructure will not only enable the integration and expansion of terrestrial networks in densely populated and rural areas, but will also provide greater resilience, improved sustainability, high spectrum availability, and greater flexibility.

[0438] In some embodiments, 6G NTN networks utilize a multi-dimensional, multi-layer architecture consisting of space and airborne flying nodes and incorporating novel enablers such as artificial network intelligence (AI). The added value that NTN components bring to ground system architecture has also been recognized by the Third Generation Partnership Project (3GPP), which is integrating NTN into the New Radio (NR) architecture. The NTN journey in the 5G ecosystem continues.

[0439] FIG5A is a schematic diagram of a random access process.

[0440] In some embodiments, when downlink data arrives (the terminal receives a synchronization signal block (SSB) / physical broadcast channel block (PBCH) / system information block (SIB)), the terminal triggers a random access process.

[0441] In some embodiments, the terminal sends msg1 to the network device through a physical random access channel (PRACH), where msg1 includes a preamble; after receiving the preamble, the network device generates a random access response (RAR) for the preamble and sends the RAR (i.e., msg2), where the RAR is carried on a first physical downlink shared channel (PDSCH), the first PDSCH is scheduled by a first physical downlink control channel (PDCCH), the RAR carries a temporary cell radio network temporary identifier (TC-RNTI), and the first PDCCH uses a random access radio network temporary identifier (TC-RNTI). After the terminal sends the Preamble, if it monitors the first PDCCH scrambled by the RA-RNTI, it receives the first PDSCH according to the monitored first PDCCH and demodulates the first PDSCH to obtain the RAR carried on the first PDSCH, and then sends msg3 to the network device. MSG3 is carried on the physical uplink shared channel (PUSCH). After receiving the PUSCH sent by the terminal, the network device generates a response to the PUSCH (i.e., msg4). The response to the PUSCH is carried on the second PDSCH. The second PDSCH is scheduled by the second PDCCH and scrambled with the TC-RNTI. The response to the PUSCH may include a terminal contention resolution identity (CRID), where the CRID may be a cell radio network temporary identifier (Cell Radio Network Temporary Identifier). identifier, C-RNTI), the terminal can determine whether the contention access is successful according to the C-RNTI; after sending the PUSCH, if the terminal monitors the second PDCCH scrambled with the TC-RNTI, it receives the second PDSCH according to the monitored second PDCCH and demodulates the second PDSCH to obtain the C-RNTI carried on the second PDSCH, and determines whether the contention access is successful according to the C-RNTI.

[0442] It is understandable that when a large number of satellite terminals are randomly accessing the network, the short satellite visibility window will cause message flow congestion. All terminals within the satellite beam will compete for network access simultaneously and must provide services within the short visibility period of the flight platform, thus causing congestion. Congestion can lead to system performance degradation or even service unavailability.

[0443] The disclosed embodiments improve the capacity of the random access phase by not discarding the signals of random access terminals, thereby increasing the number of service terminals during a short satellite visibility window.

[0444] The present disclosure proposes a method for preamble detection and synchronization parameter estimation based on AI (convolutional neural network CNN):

[0445] First, as shown in Figure 5B, the number of colliding users is detected (the number of colliding users is equivalent to the number of terminals in some of the above embodiments). Exemplarily, the process is as in some of the above embodiments, where the real and imaginary parts of the discrete Fourier transform DFT coefficients of each symbol in the preamble of the random access message are input into the first AI model to obtain the number of terminals.

[0446] Then, as shown in FIG5C , their time of arrival (ToA) is estimated under different propagation conditions and satellite configurations. For example, the process is similar to that in some of the above embodiments. The real and imaginary parts of the DFT coefficients of each symbol in the preamble of the random access message and the number of terminals are input into the second AI model to obtain the ToA corresponding to the random access request message provided by each terminal.

[0447] The collision detection neural network takes the real and imaginary parts of the DFT coefficients of each symbol (Re(y); Im(y)) as input and is trained to predict the number of devices transmitting the same preamble.

[0448] After the leader collision classification, ToA estimation is performed by the second CNN.

[0449] For each preamble, the neural network adds the real and imaginary parts of the DFT coefficients of each symbol (Re(y); Im(y)) to the value of the number of colliding users detected by the previous network and trains it to estimate the ToA of the colliding terminals in each signal.

[0450] The satellite network side can schedule Msg2 based on the number of colliding devices and their ToA, and then apply detection and classification technology on Msg3.

[0451] The more accurate the estimation of these parameters, the better the network performance in terms of network access time, access probability and throughput.

[0452] In the disclosed embodiments, the number of served users is increased during the short satellite visibility window, thereby improving network performance in terms of throughput.

[0453] The embodiments of the present disclosure further provide an apparatus for implementing any of the above methods. For example, an apparatus is provided, comprising units or modules for implementing each step performed by a terminal in any of the above methods. For another example, another apparatus is provided, comprising units or modules for implementing each step performed by a network device (e.g., an access network device, a core network function node, a core network device, etc.) in any of the above methods.

[0454] It should be understood that the division of the various units or modules in the above device is merely a division of logical functions. In actual implementation, they may be fully or partially integrated into a physical entity, or they may be physically separated. In addition, the units or modules in the device may be implemented in the form of a processor calling software: for example, the device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or implement the functions of the various units or modules of the above device, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units or modules can be realized by designing the hardware circuits. The above-mentioned hardware circuits can be understood as one or more processors; for example, in one implementation, the above-mentioned hardware circuit is an application-specific integrated circuit (ASIC), which realizes the functions of some or all of the above units or modules by designing the logical relationship of the components in the circuit; for example, in another implementation, the above-mentioned hardware circuit can be realized by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by configuring the configuration file, thereby realizing the functions of some or all of the above units or modules. All units or modules of the above devices can be realized in the form of software called by the processor, or in the form of hardware circuits, or in part by the form of software called by the processor, and the rest by hardware circuits.

[0455] In the embodiments of the present disclosure, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationship of the hardware circuit. The logical relationship of the above-mentioned hardware circuit is fixed or reconfigurable. For example, the processor is a hardware circuit implemented by an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and implementing the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0456] FIG6A is a schematic diagram of the structure of a network device according to an embodiment of the present disclosure. As shown in FIG6A , the network device 102 may include at least one of a transceiver module 11 and a processing module 12 .

[0457] In some embodiments, the above-mentioned processing module 12 is used to determine the number of terminals that provide random access request messages, wherein the number of terminals is determined based on the random access request message received by the network device and the first artificial intelligence AI model; the processing module 12 is also used to schedule the transmission of the random access response message based on the number of terminals.

[0458] The transceiver module 11 is configured to execute at least one of the communication steps (e.g., S201A, S201B-S203B, S201C-S203C, S201D-S206D, S201E-S205E, S201F-S206F, but not limited thereto) performed by the network device 102 in any of the above methods, which are not described in detail here. Optionally, the processing module 12 is configured to execute at least one of the other steps (e.g., S201A, S201B-S203B, S201C-S203C, S201D-S206D, S201E-S205E, S201F-S206F, but not limited thereto) performed by the network device 102 in any of the above methods, which are not described in detail here.

[0459] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module, and the transmitting module and the receiving module may be separate or integrated. Optionally, the transceiver module may be interchangeable with the transceiver.

[0460] In some embodiments, the processing module can be a single module or can include multiple submodules. Optionally, the multiple submodules respectively execute all or part of the steps required to be executed by the processing module. Optionally, the processing module can be interchangeable with the processor.

[0461] FIG6B is a schematic diagram of the structure of the first terminal proposed in an embodiment of the present disclosure. As shown in FIG6B , the first terminal 20 may include at least one of a transceiver module 21 and a processing module 22 .

[0462] In some embodiments, the above-mentioned processing module 22 is used to determine the number of terminals that provide random access request messages based on the random access request message and the first AI model received by the network device, wherein the number of terminals is used by the network device to schedule the transmission of random access response messages; or the transceiver module 21 is used to receive fourth indication information sent by the network device, wherein the fourth indication information is used to indicate the number of terminals, and the number of terminals is determined by the network device based on the received random access request message and the first AI model.

[0463] The transceiver module 21 is configured to execute at least one of the communication steps (e.g., S201D to S206D, S201E to S205E, S201F to S206F, but not limited thereto) performed by the first terminal 20 in any of the above methods, and will not be described in detail here. Optionally, the processing module 22 is configured to execute at least one of the other steps (e.g., S201D to S206D, S201E to S205E, S201F to S206F, but not limited thereto) performed by the first terminal 20 in any of the above methods, and will not be described in detail here.

[0464] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module, and the transmitting module and the receiving module may be separate or integrated. Optionally, the transceiver module may be interchangeable with the transceiver.

[0465] In some embodiments, the processing module can be a single module or can include multiple submodules. Optionally, the multiple submodules respectively execute all or part of the steps required to be executed by the processing module. Optionally, the processing module can be interchangeable with the processor.

[0466] Figure 7A is a schematic diagram of the structure of a communication device 8100 proposed in an embodiment of the present disclosure. Communication device 8100 can be a network device (e.g., an access network device, a core network device, etc.), a terminal (e.g., a first terminal, etc.), a chip, a chip system, or a processor that supports a network device in implementing any of the above methods, or a chip, a chip system, or a processor that supports a first terminal in implementing any of the above methods. Communication device 8100 can be used to implement the methods described in the above method embodiments. For details, please refer to the description of the above method embodiments.

[0467] As shown in Figure 7A, the communication device 8100 includes one or more processors 8101. The processor 8101 can be a general-purpose processor or a dedicated processor, for example, a baseband processor or a central processing unit. The baseband processor can be used to process the communication protocol and communication data, and the central processing unit can be used to control the communication device (such as a base station, a baseband chip, a terminal device, a terminal device chip, a DU or a CU, etc.), execute programs, and process program data. Optionally, the communication device 8100 is used to perform any of the above methods. Optionally, one or more processors 8101 are used to call instructions to enable the communication device 8100 to perform any of the above methods.

[0468] In some embodiments, the communication device 8100 further includes one or more transceivers 8102. When the communication device 8100 includes one or more transceivers 8102, the transceiver 8102 performs at least one of the communication steps of sending and / or receiving in the above method (e.g., S201A, S201B-S203B, S201C-S203C, S201D-S206D, S201E-S205E, S201F-S206F, but not limited thereto), and the processor 8101 performs at least one of the other steps (e.g., S201A, S201B-S203B, S201C-S203C, S201D-S206D, S201E-S205E, S201F-S206F, but not limited thereto). In alternative embodiments, the transceiver may include a receiver and / or a transmitter, and the receiver and transmitter may be separate or integrated. Optionally, terms such as transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, and interface can be replaced with each other, terms such as transmitter, transmitting unit, transmitter, and transmitting circuit can be replaced with each other, and terms such as receiver, receiving unit, receiver, and receiving circuit can be replaced with each other.

[0469] In some embodiments, the communication device 8100 further includes one or more memories 8103 for storing data. Alternatively, all or part of the memories 8103 may be located outside the communication device 8100. In alternative embodiments, the communication device 8100 may include one or more interface circuits 8104. Optionally, the interface circuits 8104 are connected to the memory 8102 and may be configured to receive data from the memory 8102 or other devices, or to send data to the memory 8102 or other devices. For example, the interface circuits 8104 may read data stored in the memory 8102 and send the data to the processor 8101.

[0470] The communication device 8100 described in the above embodiment may be a network device or a terminal, but the scope of the communication device 8100 described in the present disclosure is not limited thereto, and the structure of the communication device 8100 may not be limited by FIG. 7A. The communication device may be an independent device or may be part of a larger device. For example, the communication device may be: 1) an independent integrated circuit IC, or a chip, or a chip system or subsystem; (2) a collection of one or more ICs, optionally, the above IC collection may also include a storage component for storing data or programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, an intelligent terminal device, a cellular phone, a wireless device, a handheld device, a mobile unit, an in-vehicle device, a network device, a cloud device, an artificial intelligence device, etc.; (6) others, etc.

[0471] 7B is a schematic diagram of the structure of the chip 8200 proposed in an embodiment of the present disclosure. If the communication device 8100 can be a chip or a chip system, please refer to the schematic diagram of the structure of the chip 8200 shown in FIG7B , but the present disclosure is not limited thereto.

[0472] The chip 8200 includes one or more processors 8201. The chip 8200 is configured to execute any of the above methods.

[0473] In some embodiments, chip 8200 further includes one or more interface circuits 8202. Terms such as interface circuit, interface, and transceiver pins may be used interchangeably. In some embodiments, chip 8200 further includes one or more memories 8203 for storing data. Alternatively, all or part of memory 8203 may be located external to chip 8200. Optionally, interface circuit 8202 is connected to memory 8203 and may be used to receive data from memory 8203 or other devices, or may be used to send data to memory 8203 or other devices. For example, interface circuit 8202 may read data stored in memory 8203 and send the data to processor 8201.

[0474] In some embodiments, the interface circuit 8202 performs at least one of the communication steps (e.g., S201A, S201B-S203B, S201C-S203C, S201D-S206D, S201E-S205E, S201F-S206F) in the above method. The interface circuit 8202 performing the communication steps (e.g., S201A, S201B-S203B, S201C-S203C, S201D-S206D, S201E-S205E, S201F-S206F) in the above method, for example, means that the interface circuit 8202 performs data exchange between the processor 8201, the chip 8200, the memory 8203, or the transceiver device. In some embodiments, the processor 8201 performs at least one of the other steps (e.g., S201A, S201B-S203B, S201C-S203C, S201D-S206D, S201E-S205E, S201F-S206F, but not limited thereto).

[0475] The present disclosure also proposes a storage medium having instructions stored thereon, which, when executed on the communication device 8100, causes the communication device 8100 to execute any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but is not limited thereto, and may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but is not limited thereto, and may also be a temporary storage medium.

[0476] The present disclosure also provides a program product, which, when executed by the communication device 8100, enables the communication device 8100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0477] The present disclosure also proposes a computer program, which, when executed on a computer, causes the computer to perform any one of the above methods.

[0478] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0479] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0480] The above description is merely a specific embodiment of the present disclosure, but the scope of protection of the present disclosure is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this disclosure should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A random access method, characterized in that: The method is performed by a network device and includes: Determine the number of terminals that provide random access request messages, wherein the number of terminals is determined based on the random access request message received by the network device and a first artificial intelligence AI model; The transmission of random access response messages is scheduled based on the number of the terminals.

2. The method according to claim 1, characterized in that The determining the number of terminals that provide random access request messages includes: The number of the terminals is determined based on the received random access request message and the first AI model.

3. The method according to claim 2, characterized in that The method further comprises: First indication information is sent to the first terminal, wherein the first indication information is used to indicate the number of the terminals.

4. The method according to claim 1, characterized in that The determining the number of terminals that provide random access request messages includes: receiving second indication information sent by the first terminal, wherein the second indication information is used to indicate the number of the terminals, and the number of the terminals is determined by the first terminal based on the random access request message received by the network device and the first AI model; The number of the terminals is determined according to the second indication information.

5. The method according to claim 4, characterized in that The method further comprises: Sending third indication information to the first terminal, wherein the third indication information is used to indicate the random access request message received by the network device.

6. The method according to any one of claims 1 to 5, characterized in that The scheduling, based on the number of the terminals, of transmission of a random access response message includes: Determine an arrival time ToA corresponding to the random access request message provided by each of the terminals, wherein the ToA corresponding to the random access request message provided by each of the terminals is determined based on the random access request message, the number of the terminals, and the second AI model; The transmission of the random access response message is scheduled based on the number of the terminals and the ToA corresponding to the random access request message provided by each of the terminals.

7. The method according to claim 6, characterized in that The determining the arrival time ToA corresponding to the random access request message provided by each terminal includes: Based on the random access request message, the number of the terminals and the second AI model, a ToA corresponding to the random access request message provided by each of the terminals is determined.

8. The method according to claim 6, characterized in that The determining the arrival time ToA corresponding to the random access request message provided by each terminal includes: receiving fourth indication information sent by the first terminal, wherein the fourth indication information is used to indicate a ToA corresponding to the random access request message provided by each of the terminals, and the ToA corresponding to the random access request message provided by each of the terminals is determined by the first terminal based on the random access request message, the number of the terminals, and the second AI model; Determine, according to the fourth indication information, an arrival time ToA corresponding to the random access request message provided by each terminal.

9. The method according to any one of claims 1 to 8, characterized in that The random access request message includes at least one of the following: Message msg1 in the 4-step random access process; msg3 in the 4-step random access process; msgA during the 2-step random access process.

10. The method according to any one of claims 1 to 9, characterized in that The random access response message includes at least one of the following: msg2 in the 4-step random access process; msg4 in the 4-step random access process; msgB in the 2-step random access process.

11. The method according to claim 2 or 3, characterized in that: The random access request message is msg1 in a 4-step random access process, wherein determining the number of the terminals based on the received random access request message and the first AI model includes: The real part and the imaginary part of the discrete Fourier transform DFT coefficient of each symbol in the preamble of the random access message are input into the first AI model to obtain the number of the terminals.

12. The method according to claim 7, characterized in that The random access request message is msg1 in a 4-step random access process, wherein determining, based on the random access request message, the number of the terminals, and the second AI model, the ToA corresponding to the random access request message provided by each terminal includes: The real part and the imaginary part of the DFT coefficient of each symbol in the preamble code of the random access message and the number of the terminals are input into the second AI model to obtain the ToA corresponding to the random access request message provided by each terminal.

13. The method according to any one of claims 1 to 12, characterized in that The network device is a satellite, and the random access request message is received by the network device during a visible window.

14. The method according to claim 2 or 11, characterized in that: The method further comprises: Determining a first training data set, wherein the first training data set includes sample random access request messages provided by multiple terminals; An initial first AI model is trained according to the first training data set to obtain the first AI model.

15. The method according to claim 7 or 12, characterized in that: The method further comprises: Determine a second training data set, wherein the second training data set includes sample random access request messages provided by multiple terminals and sample ToA corresponding to the sample random access request message sent by each of the terminals; The initial second AI model is trained according to the second training data set to obtain the second AI model.

16. A random access method, characterized in that: The method is performed by a first terminal and includes: Determine, based on the random access request message received by the network device and the first AI model, the number of terminals providing the random access request message, wherein the number of terminals is used by the network device to schedule transmission of a random access response message; or Receive first indication information sent by a network device, wherein the first indication information is used to indicate the number of terminals, and the number of terminals is determined by the network device based on a received random access request message and a first AI model.

17. The method according to claim 16, characterized in that The method further comprises: Sending second indication information to the network device, wherein the second indication information is used to indicate the number of the terminals.

18. The method according to claim 16 or 17, characterized in that The method further comprises: Receive third indication information sent by the network device, wherein the third indication information is used to indicate the random access request message received by the network device.

19. The method according to any one of claims 16 to 18, characterized in that The method further comprises: Based on the random access request message, the number of the terminals and the second AI model, a ToA corresponding to the random access request message provided by each of the terminals is determined.

20. The method of claim 19, wherein: The method further comprises: Send fourth indication information to the network device, wherein the fourth indication information is used to indicate a ToA corresponding to the random access request message provided by each of the terminals.

21. The method according to any one of claims 16 to 20, characterized in that The random access request message includes at least one of the following: msg1 in the 4-step random access process; msg3 in the 4-step random access process; msgA during the 2-step random access process.

22. The method according to any one of claims 16 to 21, characterized in that The random access response message includes at least one of the following: msg2 in the 4-step random access process; msg4 in the 4-step random access process; msgB in the 2-step random access process.

23. The method according to any one of claims 16 to 22, characterized in that The random access request message is msg1 in a 4-step random access process, wherein the determining the number of terminals providing the random access request message based on the random access request message received by the network device and the first AI model includes: The real part and the imaginary part of the discrete Fourier transform DFT coefficient of each symbol in the preamble of the random access message are input into the first AI model to obtain the number of the terminals.

24. The method according to claim 19 or 20, characterized in that The random access request message is msg1 in a 4-step random access process, wherein determining, based on the random access request message, the number of the terminals, and the second AI model, the ToA corresponding to the random access request message provided by each terminal includes: The real part and the imaginary part of the DFT coefficient of each symbol in the preamble code of the random access message and the number of the terminals are input into the second AI model to obtain the ToA corresponding to the random access request message provided by each terminal.

25. The method according to any one of claims 16 to 24, characterized in that The network device is a satellite, and the random access request message is received by the network device during a visible window.

26. The method according to any one of claims 16 to 25, characterized in that The method further comprises: Determining a third training data set, wherein the third training data set includes sample random access request messages provided by a plurality of terminals; The initial third AI model is trained according to the third training data set to obtain the first AI model.

27. The method of claim 19, 20 or 24, wherein: The method further comprises: Determine a fourth training data set, wherein the fourth training data set includes sample random access request messages provided by multiple terminals and sample ToA corresponding to the sample random access request message sent by each of the terminals; The initial fourth AI model is trained according to the fourth training data set to obtain the second AI model.

28. A random access method, characterized in that: include: The first terminal determines, based on the random access request message received by the network device and the first AI model, the number of terminals providing the random access request message; The network device determines the number of terminals that provide random access request messages, wherein the number of terminals is determined based on the random access request message received by the network device and the first AI model; The network device schedules the transmission of the random access response message based on the number of the terminals.

29. A network device, characterized in that: include: A processing module, configured to determine the number of terminals providing random access request messages, wherein the number of terminals is determined based on the random access request message received by the network device and a first artificial intelligence AI model; The processing module is further used to schedule the transmission of the random access response message based on the number of the terminals.

30. A first terminal, characterized in that: include: a processing module, configured to determine, based on the random access request message received by the network device and the first AI model, the number of terminals providing the random access request message, wherein the number of terminals is used by the network device to schedule transmission of a random access response message; or A transceiver module is used to receive fourth indication information sent by a network device, wherein the fourth indication information is used to indicate the number of terminals, and the number of terminals is determined by the network device based on a received random access request message and a first AI model.

31. A network device, characterized in that: include: one or more processors; A memory coupled to the processor, wherein instructions are stored in the memory, and when the instructions are executed by the processor, the network device executes the method according to any one of claims 1 to 15.

32. A first terminal, characterized in that: include: one or more processors; A memory coupled to the processor, wherein instructions are stored in the memory, and when the instructions are executed by the processor, the first terminal executes the method according to any one of claims 16 to 27.

33. A communication system, characterized in that: The method comprises a network device and a first terminal, wherein the network device is configured to implement the method according to any one of claims 1 to 15, and the first terminal is configured to implement the method according to any one of claims 16 to 27.

34. A storage medium storing instructions, characterized in that: When the instructions are executed on a communication device, the communication device is caused to execute the method according to any one of claims 1 to 15 and 16 to 27.

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