Intelligent Multi-Domain High-Efficiency Collaborative Information Processing Method, Apparatus, and Storage Medium

Abstract

The present disclosure provides an information processing method, apparatus and storage medium for intelligent multi-domain efficient collaboration, which relates to the field of wireless communication technologies and is used to achieve intelligent multi-domain efficient collaborative management to improve the comprehensive performance of a mobile communication system. The method includes: obtaining N data packets generated by an application domain; determining, according to the N data packets, M feature sets corresponding to the N data packets, where the feature set includes at least one of the following features: spectrum efficiency requirement, transmission delay requirement, reliability requirement, capacity requirement, energy efficiency requirement, quality of service requirement; determining, in a control domain, M configuration information for the N data packets according to the M feature sets corresponding to the N data packets, where the configuration information includes signal domain configuration information and resource domain configuration information; processing the N data packets according to the M configuration information of the N data packets and intelligent technologies, where N and M are positive integers.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular, to an information processing method, apparatus, and storage medium for intelligent multi-domain efficient collaboration. Background Art

[0002] The evolution of wireless communication systems is a continuous process. From early analog communication to digital communication, and then to today's multi-network convergence and collaboration, each stage has marked a major leap in technology and requirements. With the development of emerging technologies such as the Internet of Things, big data, artificial intelligence, and edge computing, wireless communication systems are undergoing a profound transformation, the core of which is to achieve collaborative work between different networks to meet the growing data transmission requirements and diverse application scenarios.

[0003] Here, multi-network convergence refers to the seamless integration of multiple heterogeneous networks, such as cellular networks (2G, 3G, 4G, 5G, and even the future 6G wireless communication network), wireless fidelity (Wi-Fi), satellite communication, and drone networks, to form a unified communication platform. These networks integrate, assist, and influence each other, promoting the mobile communication field into an unprecedented profound transformation. This transformation is reflected in multiple domains such as the application domain, signal domain, control domain, and resource domain.

[0004] However, current wireless communication systems or algorithms are often limited to the optimization of a single domain, and there is a lack of coordination between multiple domains, making it difficult to fully exploit the comprehensive performance of communication systems. Summary of the Invention

[0005] Embodiments of the present disclosure provide an information processing method, apparatus, and storage medium for intelligent multi-domain efficient collaboration, which are used to achieve intelligent multi-domain efficient collaborative management and improve the comprehensive performance of mobile communication networks. The technical solutions provided by the embodiments of the present disclosure are as follows:

[0006] On the one hand, an information processing method for intelligent multi-domain efficient collaboration is provided, which is applied to a wireless communication system. The method includes:

[0007] Obtain N data packets generated by the application domain;

[0008] According to the N data packets, determine M feature sets corresponding to the N data packets. The feature set includes at least one of the following features: spectrum efficiency requirement, transmission delay requirement, reliability requirement, capacity requirement, energy efficiency requirement, and quality of service requirement;

[0009] In the control domain, according to the M feature sets corresponding to the N data packets, determine M configuration information for the N data packets. The configuration information includes signal domain configuration information and resource domain configuration information;

[0010] Processing the N data packets according to M configuration information of the N data packets and intelligent technologies, where N and M are positive integers.

[0011] On the other hand, an information processing device for intelligent multi-domain efficient collaboration is provided, which is applied to a wireless communication system. The device includes:

[0012] An acquisition module, configured to acquire N data packets generated by an application domain;

[0013] A first determination module, configured to determine M feature sets corresponding to the N data packets according to the N data packets, where the feature sets include at least one of the following features: spectrum efficiency requirement, transmission delay requirement, reliability requirement, capacity requirement, energy efficiency requirement, quality of service requirement;

[0014] A second determination module, configured to determine M configuration information of the N data packets in a control domain according to the M feature sets corresponding to the N data packets, where the configuration information includes signal domain configuration information and resource domain configuration information;

[0015] A processing module, configured to process the N data packets according to the M configuration information of the N data packets and intelligent technologies, where N and M are positive integers.

[0016] On yet another aspect, a communication device is provided, including: a memory and a processor; the memory and the processor are coupled; the memory is used to store computer program instructions executable by the processor; when the processor executes the computer program instructions, it implements the information processing method for intelligent multi-domain efficient collaboration in any of the above embodiments.

[0017] On yet another aspect, a computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions run on a computer (such as a communication device or an information processing device for intelligent multi-domain efficient collaboration), the information processing method for intelligent multi-domain efficient collaboration in any of the above embodiments is implemented.

[0018] On yet another aspect, a computer program product is provided, which includes computer program instructions. When the computer program instructions are executed, the information processing method for intelligent multi-domain efficient collaboration in any of the above embodiments is implemented.

[0019] The technical solution provided by the embodiments of the present disclosure obtains N data packets generated by the application domain; determines M feature sets corresponding to the N data packets according to the N data packets, where the feature set includes at least one of the following features: spectral efficiency requirement, transmission delay requirement, reliability requirement, capacity requirement, energy efficiency requirement, quality of service requirement; determines M configuration information of the N data packets in the control domain according to the M feature sets corresponding to the N data packets, and the configuration information includes signal domain configuration information and resource domain configuration information. Process the N data packets according to the M configuration information of the N data packets and intelligent technologies. Thus, intelligent multi-domain (application domain, control domain, signal domain, resource domain) efficient collaborative management is realized, ensuring that each data packet can obtain the optimal or near-optimal processing path and resource allocation, and improving the comprehensive performance of the mobile communication network. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 FIG. is a schematic structural diagram of a communication system provided by an embodiment of the present disclosure;

[0021] Figure 2 FIG. is a schematic structural diagram of another communication system provided by an embodiment of the present disclosure;

[0022] Figure 3 FIG. is a flowchart of an information processing method for intelligent multi-domain efficient collaboration provided by an embodiment of the present disclosure;

[0023] Figure 4 FIG. is a schematic structural diagram of an information processing device for intelligent multi-domain efficient collaboration provided by an embodiment of the present disclosure;

[0024] Figure 5 FIG. is a schematic structural diagram of a communication device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] The following will clearly and completely describe the technical solutions in the embodiments of the present disclosure with reference to the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present disclosure without creative efforts shall fall within the protection scope of the present disclosure.

[0026] It should be understood that the specific implementation described herein is only for explaining the present disclosure and is not used to limit the present disclosure.

[0027] In the following description, suffixes such as "module", "component" or "unit" used to represent elements are only for the convenience of description of the present disclosure, and have no specific meaning by themselves. Therefore, "module", "component" or "unit" can be used interchangeably.

[0028] In the description of the present disclosure, unless otherwise specified, " / " means "or". For example, A / B may mean A or B. The "and / or" herein is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B may mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, "at least one" means one or more, and "a plurality" means two or more. The terms such as "first" and "second" do not limit the quantity and execution order, and the terms such as "first" and "second" do not necessarily limit being different from each other.

[0029] Unless the context otherwise requires, throughout the specification and claims, the term "comprise" and its other forms such as the third-person singular form "comprises" and the present participle form "comprising" are interpreted as having an open and inclusive meaning, that is, "including, but not limited to". In the description of the specification, the terms "one embodiment", "some embodiments", "exemplary embodiments", "example", "specific example" or "some examples", etc. are intended to indicate that the specific features, structures, materials or characteristics related to the embodiment or example are included in at least one embodiment or example of the present disclosure. The schematic representations of the above terms do not necessarily refer to the same embodiment or example. In addition, the specific features, structures, materials or characteristics may be included in any one or more embodiments or examples in any suitable manner.

[0030] The terms "first" and "second" are only used for descriptive purposes and should not be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present disclosure, unless otherwise specified, the meaning of "a plurality" is two or more.

[0031] In the embodiments of the present disclosure, words such as "exemplary" or "for example" are used to mean serving as an example, illustration or explanation. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present disclosure should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0032] Additionally, the use of “based on” is meant to be open and inclusive, as a process, step, calculation, or other action “based on” one or more stated conditions or values ​​may, in practice, be based on additional conditions or values ​​beyond those stated.

[0033] After decades of vigorous development, wireless communication technology has successfully crossed over to the glorious stage of the fifth generation (5G). Looking back, the first generation (1G) mobile communication system laid the foundation, mainly focusing on solving basic voice communication needs. Subsequently, the second generation (2G) system took an important step on this basis, not only consolidating the quality of voice calls, but also introducing SMS services and low-speed data services, initially realizing the diversification of communications. With the surging wave of mobile Internet, the third generation (3G) mobile communication system came into being, which greatly improved the data transmission capacity, making simple picture transmission and low-definition video streaming possible, bringing users a more colorful online experience. Immediately afterwards, the fourth generation (4G) mobile communication system achieved a qualitative leap, not only supporting smooth playback of high-definition videos, instant enjoyment of streaming services, and the enjoyable experience of mobile games, but also initially strengthening the connection capabilities of the Internet of Things, paving the way for the era of the Internet of Everything. Today, the fifth generation (5G) mobile communication system is leading a new technological revolution. It is known for its ultra-high-speed download and ultra-low latency characteristics. It can support the seamless connection of large-scale IoT devices and open a new chapter of intelligent interconnection. Looking to the future, mobile communication technology will continue to evolve and is expected to support unprecedented high-speed data transmission and a larger-scale IoT ecosystem. At the same time, the integration of cutting-edge algorithms such as artificial intelligence and large models will bring more intelligent, efficient and flexible application scenarios to the field of wireless communications, and promote the society to enter a new era of digitalization and intelligence.

[0034] In the current vast territory of wireless communications, a new ecosystem is booming, with 2G, 3G, 4G, 5G and even forward-looking 6G networks as the core, and with communication networks deeply integrated with telepathy, satellite communications and drone low-altitude technologies intertwined and coexisting, building an intricate and vibrant network system, and achieving seamless interconnection across fields and media. This new normal not only promotes profound changes in the field of mobile communications, but also leads to an unprecedented technological innovation and integration. And with the research of technology, wireless communication systems have been expanded in multiple domains.

[0035] First of all, in the application domain, it is obvious that the application field has been widely expanded, from multiple scenarios of daily entertainment such as game immersion, instant messaging, high-definition video calls, seamless payment, to the exploratory application of cutting-edge technologies, such as the immersive experience of virtual reality (VR), and even the stringent requirements of ultra-reliable and low-latency communications (URLLC) in the era of Industry 4.0. All are included in its broad service scope, greatly broadening the application boundaries of network communications.

[0036] In terms of the signal domain, wireless communication has also made remarkable leaps. The introduction of multi-base-station multi-user cooperation, distributed large-scale multiple-input-multiple-output (MIMO) technology, and the deep integration of artificial intelligence and wireless communication systems have jointly promoted a leapfrog improvement in spectral efficiency, transmission reliability, and overall system performance, laying a solid technical foundation for the future development of wireless communication.

[0037] The transformation in the control field is equally remarkable. Facing the complex interference challenges brought about by multi-network convergence, technologies such as intelligent interference control technology, efficient network handover strategies, and high-frequency intelligent beam management have emerged, providing strong support for the stable operation and performance optimization of wireless communication systems.

[0038] In the resource domain, with the rapid development of software and hardware technologies, especially the significant improvement in computing power and storage resources, more advanced algorithm support has been introduced into wireless communication systems. For example, the widespread application of artificial intelligence algorithms provides rich resource reserves for achieving larger bandwidths, larger antenna arrays, and cooperative algorithms between communication nodes, further driving a leap in system performance.

[0039] However, current wireless communication systems or algorithms are often limited to single optimization, and there is a lack of coordination between multiple domains, making it difficult to fully exploit the comprehensive performance of communication systems.

[0040] Therefore, how to focus on researching and building a highly intelligent, flexible, and configurable multi-domain collaborative management system is a research issue or topic worthy of attention. This system will rely on advanced signal processing technologies, intelligent prediction and decision-making algorithms, and resource dynamic optimization strategies to comprehensively optimize key performance indicators such as the quality of service (QoS), spectral efficiency, latency, energy efficiency, and network capacity of 5G and future 5G-A / 6G networks to meet the increasingly complex and changing network communication requirements and promote the development of network communication technologies to a higher level.

[0041] In view of this, the present disclosure provides an intelligent multi-domain efficient collaborative information processing method, which includes: obtaining N data packets generated by an application domain; determining M feature sets corresponding to the N data packets according to the N data packets, where the feature set includes at least one of the following features: spectrum efficiency requirement, transmission delay requirement, reliability requirement, capacity requirement, energy efficiency requirement, service quality requirement; determining M configuration information of the N data packets according to the M feature sets corresponding to the N data packets in a control domain, where the configuration information includes signal domain configuration information and resource domain configuration information. Processing the N data packets according to the M configuration information of the N data packets and intelligent technologies. Thereby realizing intelligent multi-domain (application domain, control domain, signal domain, resource domain) efficient collaborative management, ensuring that each data packet can obtain an optimal or near-optimal processing path and resource allocation, and improving the comprehensive performance of the mobile communication network.

[0042] The technical solutions provided in the embodiments of the present disclosure can be applied to various mobile communication networks, for example, 3G, 4G, and the new radio (NR) mobile communication network adopting 5G, future mobile communication networks, such as the 6th-generation mobile communication technology (6G), or various communication fusion systems, etc. The embodiments of the present disclosure do not limit this.

[0043] In the embodiments of the present disclosure, the mobile communication network may include network-side devices (such as, but not limited to, base stations) and receiving-side devices (such as, but not limited to, terminals). And it should be understood that, in this example, for example, in the downlink, the first communication node (which may also be referred to as the first communication node device, the first node) may be a base station-side device, and the second communication node (which may also be referred to as the second communication node device, the second node) may be a terminal-side device. In some examples, for example, in the uplink, the first communication node may also be a terminal-side device, and the second communication node may also be a base station-side device. In some examples, for example, in device-to-device communication between two communication nodes, both the first communication node and the second communication node may be base stations or terminals. Therefore, whether the first node and the second node are base stations or terminals needs to be determined according to the context. In some examples, the communication node may be the first node or the second node. In some embodiments or examples, the communication node may also be simply referred to as a node, and the node may be the first node or the second node.

[0044] Figure 1 Shown is a schematic structural diagram of a communication system provided by an embodiment of the present disclosure. As Figure 1 shown, the communication system includes, but is not limited to, a first node 110 and a second node 120. Among them. Wireless signals can be sent, received, and related interactions, etc. between the first node 110 and the second node 120.

[0045] In a wireless communication scenario, the first node 110 communicates with the second node 120 via a wireless channel. For example, the first node 110 is a base station, the second node 120 is a terminal, and communication is carried out between the base station and the terminal via a wireless channel. Another example is that the first node 110 is a wireless router, the second node 120 is a terminal, and communication is carried out between the wireless router and the terminal via a wireless channel. Another example is that the first node 110 is a first base station, the second node 120 is a second base station, and communication is carried out between the first base station and the second base station via a wireless channel. Another example is that the first node 110 is a first terminal, the second node 120 is a second terminal, and communication is carried out between the first terminal and the second terminal via a wireless channel. Another example is that the first node 110 is a base station, the second node 120 is a repeater, and communication is carried out between the base station and the repeater via a wireless channel. Another example is that the first node 110 is a repeater, the second node 120 is a terminal, and communication is carried out between the repeater and the terminal via a wireless channel. Another example is that the first node 110 is a first repeater, the second node 120 is a second repeater, and communication is carried out between the first repeater and the second repeater via a wireless channel. Another example is that the first node 110 is a base station, the second node 120 is a satellite, and communication is carried out between the satellite and the base station via a wireless channel. Another example is that the first node 110 is a satellite, the second node 120 is a base station, and communication is carried out between the base station and the satellite via a wireless channel. Another example is that the first node 110 is a terminal, the second node 120 is a satellite, and communication is carried out between the satellite and the terminal via a wireless channel. Another example is that the first node 110 is a satellite, the second node 120 is a terminal, and communication is carried out between the terminal and the satellite via a wireless channel. Another example is that the first node 110 is a ground device, the second node 120 is an aircraft, and communication is carried out between the aircraft and the ground device via a wireless channel. Another example is that the first node 110 is a first aircraft, the second node 120 is a second aircraft, and communication is carried out between the first aircraft and the second aircraft via a wireless channel.

[0046] In the present disclosure, the "first" node, "second" node, "first" method, "second" method, "first" matrix, "second" matrix, "first" part, "second" part, unless otherwise specified, are only used for descriptive distinction and do not represent the front-back or sequence order.

[0047] In the present disclosure, the base station may be a base station in Long Term Evolution (LTE), Long Term Evolution Advanced (LTE-A), or an evolved Node B (eNB or eNodeB), a base station device in a 5G network, or a base station in a future communication system (such as 6G, etc.). The base station may include various macro base stations, micro base stations, home base stations (Femtocell or Home eNodeB), remote radio heads, reconfigurable intelligent surfaces (RISs), routers, Wireless Fidelity (WIFI) devices, or various network-side devices such as a primary cell and a secondary cell.

[0048] In the present disclosure, the terminal is a device with wireless transceiver functions that can be deployed on land, including indoors or outdoors; it can also be deployed on the water (such as on a ship); it can also be deployed in the air (such as on an airplane, a balloon, a satellite, etc.). The terminal may be a mobile phone, a tablet computer (Pad), a computer with wireless transceiver functions, a virtual reality (VR) terminal, an augmented reality (AR) terminal, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home, and so on. The embodiments of the present disclosure do not limit the application scenarios. Sometimes the terminal may also be referred to as a user, a user equipment (UE), an access terminal, a UE unit, a UE station, a mobile station, a mobile unit, a remote station, a remote terminal, a mobile device, a UE terminal, a wireless communication device, a UE agent, or a UE device, etc. The embodiments of the present disclosure do not limit this.

[0049] In the present disclosure, high-layer signaling includes, but is not limited to, radio resource control (RRC), media access control control element (MAC CE), and other signaling other than physical layer signaling, such as high-layer signaling of LPP (LTE positioning protocol), high-layer signaling of NRPPa (NR positioning protocol A), and high-layer signaling of LPPa (LTE positioning Protocol A). Physical layer signaling can also be transmitted between a base station and a terminal, such as downlink physical layer signaling transmitted on a physical downlink control channel (PDCCH), or uplink physical layer signaling transmitted on a physical uplink control channel (PUCCH).

[0050] In the present disclosure, the indicator of various resources, which can also be referred to as an index or an identifier (Identifier, ID), are completely equivalent concepts. For example, the resource identifier of a wireless system, where the wireless system resources include, but are not limited to, one of the following: reference signal resources, reference signal resource groups, reference signal resource configurations, channel state information (CSI) reports, CSI report sets, terminals, base stations, panels, neural network models, sub-neural network models, neural network layers, precoding matrices, beams, transmission modes, sending modes, receiving modes, modules, models, functional modules, functions, etc. corresponding indexes. The base station can send the identifier of one or a group of resources to the terminal through various high-layer signaling and / or physical layer signaling. The terminal can send the identifier of one or a group of resources to the base station through various high-layer signaling and / or physical layer signaling.

[0051] In some embodiments, the indicator or index can be an integer from 0 to D - 1, or can be an integer from 1 to D. Here, D is the number of resources corresponding to the indicator or index, and D is an integer greater than or equal to 1. In the subsequent part, the starting point of the indicator is 1 as the minimum value, but it can be replaced with the case where 0 is the minimum value.

[0052] In some embodiments, if an indicator or index i - K is calculated, when i - K is less than 1, the minimum value 1 is taken. When calculating an indicator or index i + K, when i + K is greater than D, the maximum value D is taken. This will not be elaborated one by one later. Here, K is a non-negative integer.

[0053] In some embodiments, transmission includes sending or receiving. For example, sending data or signals, or receiving data or signals.

[0054] In some embodiments, in order to calculate channel state information or perform channel estimation, a communication node needs to send a reference signal (RS). The reference signal includes, but is not limited to, a channel-state information reference signal (CSI-RS), a channel-state information-interference measurement signal (CSI-IM), a sounding reference signal (SRS), a synchronization signals block (SSB), a physical broadcast channel (PBCH), an SSB / PBCH, and a demodulation reference signal (DMRS). NZP CSI-RS can be used to measure the channel or interference, and CSI-RS can also be used for tracking, called CSI-RS for Tracking (TRS). Generally, CSI-IM is used to measure interference, and SRS is used to measure the uplink channel. In addition, the set of resource elements (REs) included in the time-frequency resources for transmitting the reference signal is called the reference signal resource. For example, CSI-RS resource, SRS resource, CSI-IM resource, and SSB resource. In this document, SSB includes the synchronization signals block and / or the physical broadcast channel.

[0055] In some embodiments, a time instance represents a time period, such as a time slot, where the time slot can be a slot or a mini-slot, or a group of symbols. A time slot or a mini-slot includes at least one symbol. A symbol refers to a time unit in a sub-frame, a frame, or a time slot, and the unit can be milliseconds, microseconds, nanoseconds, seconds, etc. For example, it can be an orthogonal frequency division multiplexing (OFDM) symbol, a single-carrier frequency division multiple access (SC-FDMA) symbol, an orthogonal frequency division multiple access (OFDMA) symbol, or symbols corresponding to various new waveforms in future communication systems. In some embodiments, the time slot concept used can also be replaced by a time instance.

[0056] In some embodiments, the smallest transmission unit carrying a modulation symbol is a resource element (RE), and an RE includes a frequency-domain sub-carrier and a time-frequency resource on a symbol. The time-frequency resources composed of multiple symbols and multiple sub-carriers constitute a physical resource block (PRB). Among them, the reference signal pattern includes at least one RE, and the reference signal is only transmitted on the fixed RE pre-configured by the base station, which is called a pattern, such as a DMRS pattern.

[0057] In some embodiments, the information processing method can be a traditional information processing method or various advanced information processing methods. The advanced information processing methods include, but are not limited to, information processing methods based on artificial intelligence (AI).

[0058] In some embodiments, artificial intelligence (AI) includes machine learning (ML), deep learning, reinforcement learning, transfer learning, deep reinforcement learning, meta-learning, etc., including devices, components, software, modules, models, functional modules, functional functions, etc. with self-learning capabilities. In some embodiments, artificial intelligence is implemented through an artificial intelligence network (or called a neural network).

[0059] In some embodiments, the antenna is a physical antenna. In some examples, the antenna is a logical antenna. In some examples, the concepts of port and antenna, antenna port, reference signal port, and pilot port are interchangeable. In some examples, the antenna is a transmitting antenna. In some examples, the antenna is a receiving antenna. In some examples, the antenna includes an antenna pair of a transmitting antenna and a receiving antenna. In some examples, the antenna can be a uniform linear array. In some examples, the antenna is a uniform planar array, such as including array elements / antennas of Ng rows and Mg columns, where Ng and Mg are positive integers.

[0060] In some embodiments, the modulation method includes but is not limited to one of the following: modulation order, modulation and coding scheme (MCS), modulation scheme, etc. (such as quadrature amplitude modulation (QAM), 16QAM, 64QAM, 256QAM, quadrature phase shift keying (QPSK), etc.). Among them, that the first modulation scheme is greater than the second modulation scheme means that the modulation order of the first modulation scheme is greater than the modulation order of the second modulation scheme, or that the number of constellation points of the constellation diagram of the first modulation scheme is greater than the number of constellation points of the constellation diagram of the second modulation scheme, or that the first modulation coding scheme is greater than the second modulation coding scheme.

[0061] It should be understood that Figure 1 is an exemplary structural diagram, Figure 1 The number of devices included in the shown communication system is not limited. For example, the number of the first node and the second node is not limited. And, except for Figure 1 the devices shown, Figure 1 the shown communication system may further include other devices, which are not limited herein.

[0062] In some examples, in a wireless communication system, it includes one or more first nodes (such as base stations), and one or more second nodes (such as terminals). For one of them, each first node includes multiple antennas, and each second node may include one or more antennas. The first node transmits a reference signal, and the second node receives the reference signal and measures the reference signal to obtain channel information H. Among them, the channel information H may be one of the following: time-domain channel information, frequency-domain channel information.

[0063] In some embodiments, the transmission resources include, but are not limited to, at least one or more of time-domain resources, frequency-domain resources, code-domain resources, and space-domain resources. In one example, the transmission resources can be used to transmit data. In one example, the transmission resources are used to transmit reference signals. In one instance, the transmission resources are used to multiplex and transmit reference signals and data. The multiplexing here includes at least one of spatial multiplexing, time-domain multiplexing, frequency-domain multiplexing, and code-domain multiplexing. In one example, the transmission resources include one or more resource elements (REs), and each resource element can transmit one modulation symbol, which is a time-frequency resource including one subcarrier and one symbol. In one example, the transmission resources include one or more physical resource blocks.

[0064] In some embodiments, the resource domain configuration information (which can also be referred to as resource domain information or resource domain configuration, etc.) may include transmission resource configuration information, computing power resource configuration information, storage resource configuration information, a first node set, a second node set, etc.

[0065] In some embodiments, the transmission resource configuration information includes, but is not limited to, at least one of the following resources or a combination of resources used to configure the occupied transmission resources: time-domain resources, frequency-domain resources, code-domain resources, and space-domain resources. In some embodiments, the transmission resource configuration information includes, but is not limited to, at least one of the following: time-domain resource configuration information corresponding to the transmission resources, frequency-domain resource configuration information corresponding to the transmission resources, space-domain resource configuration information corresponding to the transmission resources, and code-domain resource configuration information corresponding to the transmission resources. In other embodiments, the transmission resource configuration information is also referred to as transmission resource description information. Here, the configuration information can also be replaced with description information.

[0066] In one example, the time-domain resource configuration information corresponding to the transmission resources includes, but is not limited to, at least one of the following used to configure the corresponding transmission resources: the number of time-domain symbols, the starting index of the time-domain symbols, the ending index of the time-domain symbols, the start and length indicator value (SLIV) of the time-domain symbols. Here, the time-domain symbols can also be referred to as symbols.

[0067] In one example, the frequency-domain resource configuration information corresponding to the transmission resources includes, but is not limited to, at least one of the following used to configure the corresponding transmission resources: the number of subcarriers, the starting index of the subcarriers, the ending index of the subcarriers, the start and length indicator value (SLIV) of the subcarriers. In other examples, the subcarriers here can be replaced with one of the following: physical resource blocks, physical resource block groups, subbands, and bandwidth parts (BWPs).

[0068] In one example, the spatial domain resource configuration information corresponding to the transmission resource includes, but is not limited to, at least one of the following used to configure the transmission resource: reference signal port index, reference signal port group index, reference signal port type, reference signal sequence, number of ports of the reference signal, number of first communication nodes used for transmission, number of second nodes used for transmission. In other examples, the reference signal port here can be replaced by one of the following: port, DMRS port, CSI-RS port, transmitting antenna, receiving antenna, transmitting beam, receiving beam, transmission layer.

[0069] In one example, the code domain resource configuration information corresponding to the transmission resource includes, but is not limited to, at least one of the following corresponding to the transmission resource: orthogonal cover codes (OCC), code division multiplexing (CDM), OCC length, OCC sequence, OCC index / indicator.

[0070] In one example, the following at least one can be jointly indicated by one or more higher layer and / or physical layer signaling: time domain resource configuration information corresponding to the transmission resource, frequency domain resource configuration information corresponding to the transmission resource, spatial domain resource configuration information corresponding to the transmission resource, code domain resource configuration information corresponding to the transmission resource.

[0071] In some embodiments, the wireless communication system includes one or more wireless communication networks such as 2G, 3G, 4G, 5G, 4G-A, 5G-A, etc. co-networked, and may also include wireless communication networks such as 6G in the future. These coexisting one or more wireless communication systems cooperate with, complement, and influence each other, including but not limited to more or less spectrum interference and mutual restriction of energy consumption between each other.

[0072] In some embodiments, the wireless communication system includes multiple base stations of the same type or different types, and also includes one or more terminals of the same type or different types. The wireless communication system also includes at least one of the following: one or more core networks, one or more storage devices, one or more central controllers, one or more third-party servers for functions such as storing data or models, one or more computing power servers, one or more computing power units.

[0073] In one example, the computing power unit includes, but is not limited to, at least one of the following: central processing unit (CPU), graphics processing unit (GPU), tensor processing unit (TPU).

[0074] In some embodiments, the communication system includes one or more domains, including but not limited to at least one of the following: application domain, control domain, signal domain, resource domain.

[0075] In some examples, the application domain includes one or more application services, and the application domain services include but are not limited to at least one of the following: game service, voice service, long video service, short video service, picture service, payment service, location service, chat service, web page service, high-definition video, virtual reality, augmented reality, mixed reality, perception service.

[0076] In some examples, the service requirements of the application domain can be predicted, so as to extract and perform scheduling and resource allocation.

[0077] In some examples, the control domain can perform resource allocation and physical layer quality of service (QoS) guarantee configuration according to the requirements of different services. For example, through technologies such as dense networking, handover technology, reconfigurable intelligent surface (RIS), distributed multiple-input multiple-output technology (D-MIMO), centralized multiple-input multiple-output technology, joint transmission of multiple transmission nodes (JT), joint reception of multiple nodes (such as virtual MIMO, joint reception of multiple terminals, etc.), high-frequency beamforming, etc., to achieve network interference management, load balancing, QoS guarantee, etc. during information transmission.

[0078] In some examples, the signal domain is physical layer signal processing technology, including but not limited to relevant algorithms in time domain, frequency domain, antenna domain, and code domain resources, such as multi-user MIMO algorithm, CSI feedback algorithm, SRS overhead compression algorithm, coding scheme determination, etc. In one instance, the multi-user MIMO algorithm can include but is not limited to AI-based user pairing, precoding scheme selection, zero-forcing (ZF) algorithm, block diagonalization (BD) algorithm, dirty paper coding (DPC), Tomlinson-Harashima precoding (THP), etc. In one example, in the CSI feedback algorithm, it includes but is not limited to joint source-channel coding, multiple basis vector feedback, AI-based CSI compression algorithm.

[0079] In some examples, the resource domain includes but is not limited to at least one of the following: transmission resources, computing power resources, storage resources, etc. Among them, the transmission resources include time-domain resources, frequency-domain resources, antenna-domain or space-domain resources, code-domain resources, etc.

[0080] In one example, the multi-antenna technology includes but is not limited to one of the following: reconfigurable intelligent surface technology, distributed multiple-input multiple-output technology, centralized multiple-input multiple-output technology, joint transmission of multiple transmission nodes, joint reception of multiple nodes, high-frequency beamforming. Among them, the joint reception of multiple nodes may include but is not limited to one of the following: virtual MIMO, joint reception of multiple terminals, joint reception of multiple base stations. The joint transmission of multiple nodes includes but is not limited to non-coherent joint transmission (NC-JT) and coherent joint transmission (C-JT).

[0081] Exemplarily, Figure 2 Provide a schematic diagram of the structure of a communication system, which includes an application domain, a control domain, and a signal domain.

[0082] In some embodiments, there may be some contradictions in different domains. It is necessary to apply intelligent technologies to the communication system to improve the system performance. For example, through digital twin technology, each domain can be coordinately managed to enhance the comprehensive performance of the wireless communication network. In one example, the wireless communication system is only optimized in specific fields, so it can only obtain a local optimal solution, lacking flexibility and scalability. Usually, optimizing one domain may lead to a decline in the performance of another domain. In one example, through intelligent technologies, multiple domains can be coordinately managed. Generally, from a global perspective, the overall performance can be optimized, so that the intelligent and balanced utilization of resources can be achieved, and the cost can be reduced. It also realizes the flexible response of the wireless communication system, enhancing stability and reliability. Such multi-objective coordination can maximize the comprehensive benefits.

[0083] In some embodiments, through the intelligent multi-domain efficient coordination method described in this solution, the comprehensive performance of the wireless communication network can be improved. The improvement of the comprehensive performance of the wireless communication network includes but is not limited to one of the following: improvement of user satisfaction, improvement of energy efficiency, improvement of network capacity, improvement of edge user throughput, improvement of detection signal capacity, reduction of end-to-end transmission delay, reduction of handover delay, reduction of feedback overhead, etc. The description of the improvement of the comprehensive performance of the wireless communication network will not be elaborated one by one in other examples or embodiments.

[0084] In a specific example, the improvement of the comprehensive performance of the wireless communication network specifically includes at least one of the following: the satisfaction of users is increased by more than 1 time, the energy efficiency is increased by more than 15 times, the network capacity is increased by more than 4 times, the throughput of edge users is increased by more than 2 times, the capacity of detection signals is increased by more than 2 times, the end-to-end transmission delay is reduced by more than 1 time, the handover delay is reduced by more than 1 time, and the feedback overhead is reduced by 90%.

[0085] In one example, for the application domain, in order to provide a more rich and personalized user experience, it is necessary to collect and analyze various data of users, which inevitably involves the issue of user data privacy. We need to ensure the security and privacy of user data are not violated while meeting the personalized user experience.

[0086] In one example, for the control domain, in order to achieve efficient communication and wide coverage, dense networking has become an important trend, but this inevitably leads to an increase in user interference. We need to ensure that user interference is effectively controlled while meeting the requirements of efficient communication.

[0087] In one example, for the signal domain, in order to improve the capacity of data transmission, maximizing spectral efficiency has become the core pursuit, which inevitably exacerbates the complexity of wireless channel acquisition and use. We need to comprehensively improve the reliability and effectiveness of wireless channel use while pursuing spectral efficiency.

[0088] The embodiments of the present disclosure provide an information processing method for intelligent multi-domain efficient collaboration, which is applied to a wireless communication system. As Figure 3 shown, the method includes the following steps:

[0089] S101. Obtain N data packets generated by the application domain.

[0090] Wherein, N is a positive integer.

[0091] In some embodiments, the N data packets correspond to K different application domain services, and the application domain services include at least one of the following: game service, voice service, long video service, short video service, picture service, payment service, positioning service, chat service, web page service, high-definition video, virtual reality, augmented reality, mixed reality, perception service, wherein, K is a positive integer, and K is less than or equal to N.

[0092] In one example, the N data packets corresponding to K different application domain services means that the N data packets are generated according to K different application services. Among them, there may be a situation where one reference service generates one or more data packets.

[0093] S102. Determine M feature sets corresponding to the N data packets according to the N data packets.

[0094] where M is a positive integer.

[0095] In some embodiments, the feature set includes at least one of the following features: spectral efficiency requirement, transmission delay requirement, reliability requirement, capacity requirement, energy efficiency requirement, quality of service requirement. It can be understood that in other embodiments, the reliability requirement, capacity requirement, energy efficiency requirement, and quality of service requirement can be replaced by spectral efficiency metric, transmission delay metric, reliability metric, capacity metric, energy efficiency metric, and quality of service metric respectively, and their values can be real numbers.

[0096] In some embodiments, the spectral efficiency requirement includes an average spectral efficiency requirement and / or an edge spectral efficiency requirement.

[0097] In some embodiments, N data packets obtained from the application domain can be subjected to feature extraction through statistical or intelligent techniques to obtain M feature sets corresponding to the N data packets.

[0098] In some embodiments, M feature sets corresponding to the N data packets are determined according to the feature parameters of each of the N data packets. The feature parameters include at least one of the following: quality of service of the data packet, size of the data packet, generation frequency of the data packet.

[0099] In some examples, the feature set of the i-th data packet among the N data packets is analyzed based on the feature parameters of the i-th data packet, where i = 1, …, N and N = M. That is, the meaning of the M feature sets corresponding to the N data packets is that the i-th data packet corresponds to the i-th feature set. In some embodiments, the feature sets corresponding to one or more data packets are the same, so there are only M different feature sets among the N feature sets, where M is less than or equal to N.

[0100] In some embodiments, among the M feature sets corresponding to the N data packets, each data packet corresponds to a feature set. For example, the i-th data packet corresponds to the j-th feature set. Among them, some feature sets correspond to one or more data packets, or the feature sets corresponding to multiple data packets are the same. Here, i = 1, …, N, and j is an integer less than or equal to M.

[0101] In some embodiments, the feature parameters of each of the N data packets are input into an artificial intelligence model to obtain M feature sets corresponding to the N data packets.

[0102] Among them, some layers of the artificial intelligence model may include at least one of the following: at least one residual block (resnet), at least one dense block (densenet), at least one long short-term memory network (LSTM), at least one encoder, and at least one decoder. In one example, the artificial intelligence model includes 2 residual blocks. In one example, the artificial intelligence model includes 2 dense blocks. In one example, the artificial intelligence model includes an LSTM and a resnet. In one example, the artificial intelligence model is implemented by a Transformer model, and a Transformer model includes one or more encoders and one or more decoders.

[0103] In some examples, the characteristic parameters in the i-th data packet among the N data packets are input into the artificial intelligence model to obtain a characteristic set corresponding to the i-th data packet, where i is less than or equal to N. Here, there may be multiple data packets corresponding to the same characteristic set as long as the multiple data packets have the same characteristic parameters.

[0104] In some embodiments, when the number of characteristic sets corresponding to the N data packets is greater than N, a merging operation is performed on the multiple characteristic sets according to the similarity distance between the characteristic sets corresponding to the N data packets until the number of characteristic sets is less than or equal to N, obtaining M characteristic sets.

[0105] In this way, performing a merging operation on multiple characteristic sets using the similarity distance between the characteristic sets can help remove redundant or duplicate characteristic sets, making the processing of data packets more efficient and clear. This helps improve data quality and processing accuracy.

[0106] S103. Determine M configuration information of the N data packets according to the M characteristic sets corresponding to the N data packets in the control domain.

[0107] Among them, the configuration information includes signal domain configuration information and resource domain configuration information.

[0108] In some embodiments, the signal domain configuration information includes at least one of the following: carrier frequency, carrier aggregation mode, modulation method, demodulation reference signal configuration information, channel state information reference signal configuration information, multiplexing method, multi-antenna mode, information processing method. Details will not be elaborated one by one in other examples or embodiments.

[0109] In some embodiments, the multi-antenna mode includes but is not limited to: single-user MIMO, multi-user MIMO, multi-node non-coherent joint transmission, multi-node coherent transmission, multi-node joint reception. Among them, multi-node joint reception is also called virtual MIMO. Details will not be elaborated one by one in other embodiments.

[0110] In some embodiments, the information processing methods include, but are not limited to, linear information processing methods and non-linear information processing methods. Among them, the non-linear information processing methods include, but are not limited to, artificial intelligence, deep learning, large models, etc. The linear information processing method can be other classical information processing methods other than the artificial intelligence method. This will not be elaborated one by one in other examples or embodiments.

[0111] In some embodiments, the reference signal configuration information includes at least one of the following: time domain resource configuration information of the reference signal, frequency domain resource configuration information, code domain resource configuration information, and spatial domain resource configuration information. This will not be elaborated one by one in other embodiments.

[0112] In some embodiments, the resource domain configuration information includes at least one of the following: time domain resource configuration information, frequency domain resource configuration information, spatial domain resource configuration information, code domain resource configuration information, computing power resource configuration information, storage resource configuration information, the first node set (transmission node set), and the second node set (reception node set). This will not be elaborated one by one hereinafter.

[0113] In some embodiments, determining M configuration information of N data packets according to M feature sets corresponding to the N data packets includes:

[0114] When M is equal to N, determining the configuration information of the i-th data packet according to the feature set of the i-th data packet, where i is a non-negative integer less than or equal to M.

[0115] In some embodiments, determining the configuration information of the i-th data packet according to the feature set of the i-th data packet includes:

[0116] Inputting the feature set of the i-th data packet into an artificial intelligence model to obtain the configuration information of the i-th data packet. Exemplarily, the configuration information of the i-th data packet is determined based on the following formula:

[0117] [l i ,R i =f 1 (F i )

[0118] where i is a non-negative integer less than or equal to M. F i represents one or more features in the feature set of the i-th data packet among the N data packets, l i represents the information domain configuration information of the i-th data packet, R i represents the resource domain configuration information of the i-th data packet, and f 1Denote the first generating function, which can be implemented by an artificial intelligence model or be a pre-agreed mapping rule for mapping one or more features in the feature set to information domain configuration information and resource domain configuration information.

[0119] In some embodiments, determining the configuration information of the i-th data packet according to the feature set of the i-th data packet includes:

[0120] Determining the feature combination to which the feature set of the i-th data packet belongs according to at least one feature in the feature set of the i-th data packet;

[0121] Determining the configuration information of the i-th data packet according to the feature combination of the i-th data packet, wherein the corresponding relationship between the feature combination and the configuration information is predefined.

[0122] In some examples, the spectral efficiency requirement is divided into one or more sets or range intervals, such as the spectral efficiency being greater than or equal to a i , less than a i+1 represents the i-th spectral efficiency set or spectral efficiency range interval S i , where a i is a real number greater than 0, and a i is less than a i+1 , i = 1, …, N1, and N1 is a positive integer greater than 1.

[0123] In some examples, the transmission delay requirement is divided into one or more sets or range intervals, such as the transmission delay being greater than or equal to b i , less than b i+1 represents the i-th transmission time domain set or transmission delay set interval range D i , where b i is a real number greater than 0, and b i is less than b i+1 , i = 1, …, N2, and N2 is a positive integer greater than 1.

[0124] In some examples, the reliability requirement is divided into one or more sets or range intervals, such as the reliability being greater than or equal to c i , less than c i+1 represents the i-th reliability set or reliability range interval R i , where c i is a real number greater than 0, and c i is less than c i+1 , i = 1, …, N3, and N3 is a positive integer greater than 1.

[0125] In some examples, the capacity requirement is divided into one or more sets or range intervals, such as the capacity being greater than or equal to di , less than d i+1 represents the i-th capacity set or capacity interval range C when i , where d i is a real number greater than 0, and d i is less than d i+1 , i = 1, …, N4, and N4 is a positive integer greater than 1.

[0126] In some examples, the energy efficiency requirement is divided into one or more sets or interval ranges, such as energy efficiency greater than or equal to e i , less than e i+1 represents the i-th energy efficiency set or energy efficiency interval range E when i , where e i is a real number greater than 0, and e i is less than e i+1 , i = 1, …, N5, and N5 is a positive integer greater than 1.

[0127] In some examples, the quality of service requirement is divided into one or more sets or interval ranges, such as quality of service greater than or equal to f i , less than f i+1 represents the i-th quality of service set or quality of service interval range Q when i , where f i is a real number greater than 0, and f i is less than f i+1 , i = 1, …, N6, and N6 is a positive integer greater than 1.

[0128] In other examples or embodiments, the descriptions of dividing the spectral efficiency requirement, transmission delay requirement, reliability requirement, capacity requirement, energy efficiency requirement, quality of service, etc. into one or more sets or intervals will not be elaborated one by one.

[0129] In some embodiments, the feature combination includes the combination of one or more of the following sets: a spectral efficiency set S, a transmission delay set D, a reliability set R, a capacity set C, an energy efficiency set E, and a quality of service set Q. The description of the feature combination will not be elaborated one by one in other embodiments.

[0130] In one example, a feature combination includes S 1 and D 1 . In one example, a feature combination includes S 1 , D 1 and R 1 . In one example, a feature combination includes S 1 , D 1 , R 1 and C 1. In one example, a feature combination includes S 1 , D 1 , R 1 and E 1 . In one example, a feature combination includes S 1 , D 1 , R 1 , C 1 and Q 1 . In one example, a feature combination includes S 1 , D 1 , R 1 , E 1 , C 1 and Q 1 . In one example, a feature combination includes S 1 , D 1 , R 1 , E 1 , C 1 and Q 1 or more of them.

[0131] In other examples, a feature combination can replace one or more of S 1 , D 1 , R 1 , E 1 , C 1 and Q 1 with other sets whose set indices are greater than 1. For example, a feature combination includes S i , D j , R k , E h , C m and Q n , or more of them, where i, j, k, h, m, n are respectively greater than or equal to 1 and less than or equal to the number N 1 , N 2 , N 3 , N 4 , N 5 of their corresponding sets. The description of the feature combination will not be elaborated one by one in other examples or embodiments.

[0132] Exemplarily, one or more features covered by the feature set (for example, one or more of spectral efficiency requirements, transmission delay requirements, reliability requirements, capacity requirements, energy efficiency requirements, service quality requirements) are respectively divided into T feature combinations FG g , g = 1,..., T. Each feature combination corresponds to a set of configuration information (including information domain configuration and resource domain configuration). If the feature set F iIf at least one feature in the [packet] belongs to the j-th feature combination, the configuration information of the i-th data packet is determined to be the j-th feature combination FG j The corresponding configuration information, where i = 1, …, N and j is an integer less than or equal to T.

[0133] In some embodiments, M configuration information of the N data packets is determined according to the M feature sets corresponding to the N data packets and the capabilities of the communication system.

[0134] Among them, the capabilities of the communication system include at least one of the following: the signal domain capabilities of the communication system, the resource domain capabilities of the communication system.

[0135] In this way, when there are at least two data packets with the same corresponding feature sets among the N data packets, determining the configuration information of the data packets only based on the feature sets may cause ambiguity. Combining the feature sets and the capabilities of the communication system can improve the accuracy of determining the configuration information of the data packets.

[0136] In some examples, when M is less than or equal to N, the configuration information of the i-th data packet is determined according to the feature set corresponding to the i-th data packet among the N data packets and the capabilities of the communication system.

[0137] In some embodiments, the signal domain capabilities of a communication system include at least one of the following: whether the first node supports joint transmission, the type of joint transmission supported by the first node, whether the first node supports distributed precoding, the maximum number of data streams transmitted by the first node, whether the first node supports repeated transmission, the type of repeated transmission supported by the first node, whether the second node supports multi-node joint reception, whether the second node supports repeated transmission, the supported modulation method, support for high-frequency beamforming, the supported bandwidth size, whether artificial intelligence is supported, and the type of artificial intelligence model, etc. In one embodiment, the type of joint transmission supported by the first node may be non-coherent joint transmission (NCJT) or coherent joint transmission (CJT), or multi-node selection transmission, coordinated scheduling / beamforming (CS / CB), etc. In one example, the type of repeated transmission includes, but is not limited to, one of the following: repeated transmission on different time domain resources, repeated transmission on different spatial domain resources (such as different data streams), repeated transmission on different frequency domain resources. Of course, it can also be repeated transmission on at least two of the space-time-frequency domains. In one example, the joint reception of the second node can also be referred to as virtual MIMO, which means that multiple terminals cooperate to form a large terminal joint reception data stream. In one example, the artificial intelligence model type can include a positioning model, a CSI compression model, a CSI prediction model, a beam prediction model, a channel estimation model, etc. according to functional differentiation. In one example, the artificial intelligence model type can include a fully connected model, a convolutional model, a recurrent network model, etc. according to network structure. In other examples or embodiments, the description of the signal domain capabilities of the communication system will not be elaborated one by one.

[0138] In some embodiments, the resource domain capabilities of the communication system include at least one of the following: computing power resource capabilities, storage resource capabilities. Among them, the computing power resource capabilities include at least one of the following: the number of supported graphics processors, the number of supported central processing units, the type of supported graphics processors, the type of supported central processing units, the remaining computing power resource size, the data types and precisions supported by the hardware. The storage resource capabilities include one of the following: the memory size, the number of registers, the video memory size of the graphics processor, the remaining storage resource size. In other examples or embodiments, the description of the resource domain capabilities of the communication system will not be elaborated one by one.

[0139] In some embodiments, the resource domain capabilities and the signal domain capabilities of the communication system are collectively referred to as the capabilities of the communication system, and their parameters can be described together. Some parameters of the signal domain capabilities of the communication system can be described in the resource domain capabilities of the communication system.

[0140] In some embodiments, determining M configuration information of N data packets according to M feature sets corresponding to the N data packets and the capabilities of the communication system includes:

[0141] Inputting the M feature sets of the N data packets and the capabilities of the communication system into an artificial intelligence model to obtain M configuration information of the N data packets.

[0142] In some embodiments, inputting the M feature sets of the N data packets and the capabilities of the communication system into an artificial intelligence model to obtain M configuration information of the N data packets includes at least one of the following:

[0143] Inputting the M feature sets of the N data packets and the signal domain capabilities of the communication system into a first artificial intelligence model to obtain M configuration information of the N data packets;

[0144] Inputting the M feature sets of the N data packets and the resource domain capabilities of the communication system into a second artificial intelligence model to obtain M configuration information of the N data packets;

[0145] Inputting the M feature sets of the N data packets, the signal domain capabilities of the communication system, and the resource domain capabilities of the communication system into a third artificial intelligence model to obtain M configuration information of the N data packets.

[0146] Among them, the first artificial intelligence model, the second artificial intelligence model, and the third artificial intelligence model can be different artificial intelligence models. Some layers of the artificial intelligence model can include at least one of the following: at least one residual block (resnet), at least one dense block (densenet), at least one long short-term memory network (LSTM), at least one encoder, and at least one decoder.

[0147] In some examples, the signal domain capabilities of the communication system are divided into one or more signal domain capability sets, and the signal domain capability set IA of the ith communication system i , i = 1,..., N6. It can be a plurality of sets pre-allocated according to the signal domain capabilities of the communication system. In one example, when the first node supports coherent joint transmission and the bandwidth is greater than g 1 , and the terminal supports multi-node joint reception, the signal domain capability set is IA 1 . In one example, when the first node supports coherent joint transmission and the bandwidth is less than g 1 , and the terminal supports multi-node joint reception, the signal domain capability set is IA 2 . In one example, when the first node supports non-coherent joint transmission and the bandwidth is greater than g 1 , the signal domain capability set is IA 3Here, N6 is a positive integer. In other examples or embodiments, different sets of signal domain capabilities can be preset according to other signal domain capabilities of the communication system, and no further examples will be given one by one. Regarding the description of dividing the signal domain capabilities of the communication system into multiple sets of signal domain capabilities, it will not be elaborated one by one in other examples or embodiments.

[0148] In some examples, dividing the resource domain capabilities of the communication system into one or more resource domain capability sets, compared with the resource domain capability set RA of the i-th communication system i , i = 1,..., N7. It can be multiple sets pre-allocated according to the resource domain capabilities of the communication system. In one example, the computing power is greater than h i , less than h i+1 , and the storage capacity is greater than g j less than or equal to g j+1 , and the resource domain capability set is RA k . Among them, h i is a positive real number, g j is a positive real number, and h i is less than h i+1 , g j is less than g j+1 . i = 1,..., N8, j = 1,..., N9, k = 1,..., N7. Here, N7, N8, and N9 are all positive integers. In other examples or embodiments, different resource domain capability sets can be preset according to other resource domain capabilities of the communication system, and no further examples will be given one by one. Regarding the description of dividing the resource domain capabilities of the communication system into multiple resource domain capability sets, it will not be elaborated one by one in other examples or embodiments.

[0149] In some examples, one or more of S i , D j , R k , E h , C m , Q n , and one or more of RA g , IA f form a feature and capability combination, where i, j, k, h, m, n, g, f are respectively greater than or equal to 1 and respectively less than or equal to the number N of their corresponding sets 1 , N 2 , N 3 , N 4 , N 5 , N 8 , N 9 . The description of the feature and capability combination will not be elaborated one by one in other examples or embodiments.

[0150] Exemplarily, when M is less than or equal to N, the configuration information of the i-th data packet is determined based on the following formula:

[0151] [l i ,R i =f 2 (F i ,IA i )

[0152] Wherein, i is a non-negative integer less than or equal to N. F i represents one or more features in the feature set of the i-th data packet among N data packets, IA i represents the signal domain capability of the communication system, l i represents the information domain configuration information of the i-th data packet, R i represents the resource domain configuration information of the i-th data packet, f 2 represents a second generation function, and the second generation function can be implemented by the above-mentioned first artificial intelligence model, or F i and IA i can be mapped to l i and R i through a preset mapping rule.

[0153] Exemplarily, when M is less than or equal to N, the configuration information of the i-th data packet is determined based on the following formula:

[0154] [l i ,R i =f 3 (F i ,RA i )

[0155] Wherein, i is a non-negative integer less than or equal to N. F i represents one or more features in the feature set of the i-th data packet among N data packets, RA i represents the resource domain capability of the communication system, l i represents the information domain configuration information of the i-th data packet, R i represents the resource domain configuration information of the i-th data packet, f 2 represents a third generation function, and the third generation function can be implemented by the above-mentioned second artificial intelligence model, or F i and RA i can be mapped to l i and R i through a preset mapping rule.

[0156] Exemplarily, when M is less than or equal to N, the configuration information of the i-th data packet is determined based on the following formula:

[0157] [l i ,R i = f 4 (F i , IA i , RA i )

[0158] Wherein, F i represents one or more features in the feature set of the i-th data packet among N data packets, IA i represents the signal domain capability of the communication system, RA i represents the resource domain capability of the communication system, l i represents the information domain configuration information of the i-th data packet, R i represents the resource domain configuration information of the i-th data packet, f 2 represents the fourth generation function, and the fourth generation function can be implemented by the above-mentioned third artificial intelligence model, or F i , IA i and RA i can be mapped to l i and R i , i = 1,..., N.

[0159] In some embodiments, determining M configuration information of N data packets according to M feature sets corresponding to the N data packets and the capabilities of the communication system includes:

[0160] For each feature set among the M feature sets corresponding to the N data packets, determining the feature and capability combination to which the feature set and the capabilities of the communication system belong according to at least one feature in the feature set and the capabilities of the communication system;

[0161] Determining the configuration information of the data packet corresponding to the feature set according to the feature and capability combination to which the feature set and the capabilities of the communication system belong, and the corresponding relationship between the feature and capability combination and the configuration information is predefined.

[0162] In some embodiments, for the i-th data packet among the N data packets, determining the feature and capability combination to which the i-th data packet belongs according to at least one feature of the feature set of the i-th data packet and the capabilities of the communication system; determining the configuration information of the i-th data packet according to the feature and capability combination to which the i-th data packet belongs, and the corresponding relationship between the feature and capability combination and the configuration information is predefined, and i is a positive integer less than or equal to N.

[0163] Exemplarily, one or more features covered by the feature set (for example, one or more of spectral efficiency requirements, transmission delay requirements, reliability requirements, capacity requirements, energy efficiency requirements, service quality requirements), and possible values of the signal domain capabilities of the communication system are divided into T feature and capability combinations according to their value ranges. Each feature and capability combination corresponds to a set of configuration information (including information domain configuration information and resource domain configuration information). If the feature set of the i-th data packet and the signal domain capabilities of the communication system belong to the j-th feature and capability combination, the configuration information of the i-th data packet is determined as the configuration information corresponding to the j-th feature and capability combination, where j = 1, …, T.

[0164] Exemplarily, one or more features in the feature set (for example, one or more of spectral efficiency requirements, transmission delay requirements, reliability requirements, capacity requirements, energy efficiency requirements, service quality requirements), and possible values of the resource domain capabilities of the communication system are divided into T feature and capability combinations according to their value ranges. Each feature and capability combination corresponds to a set of configuration information (including information domain configuration information and resource domain configuration information). If the feature set of the i-th data packet and the resource domain capabilities of the communication system belong to the j-th feature and capability combination, the configuration information of the i-th data packet is determined as the configuration information corresponding to the j-th feature and capability combination, where j = 1, …, T.

[0165] Exemplarily, one or more features in the feature set (for example, one or more of spectral efficiency requirements, transmission delay requirements, reliability requirements, capacity requirements, energy efficiency requirements, service quality requirements), the signal domain capabilities of the communication system, and possible values of the resource domain capabilities of the communication system are divided into T feature and capability combinations according to their value ranges. Each feature and capability combination corresponds to a set of configuration information (including information domain configuration information and resource domain configuration information). If the feature set of the i-th data packet, the signal domain capabilities of the communication system, and the resource domain capabilities of the communication system belong to the j-th feature and capability combination, the configuration information of the i-th data packet is determined as the configuration information corresponding to the j-th feature and capability combination, where j = 1, …, T.

[0166] S104. Process the N data packets according to the M configuration information of the N data packets and intelligent technologies.

[0167] In some embodiments, a digital twin wireless communication system that simulates the application domain, control domain, and information domain is generated. In the digital twin wireless communication system, the N data packets are simulatedly transmitted according to the M configuration information of the N data packets. In this way, through the digital twin wireless communication system, the data packet transmission situations under different configurations can be quickly simulated, and then the data packet transmission configuration and scheduling strategy can be optimized.

[0168] In some embodiments, for the i-th data packet among N data packets, a digital twin wireless communication system corresponding to the i-th data packet is generated according to the configuration information corresponding to the i-th data packet, and the transmission of the i-th data packet is simulated in the digital twin wireless communication system, where i = 1, …, N.

[0169] In some embodiments, for generating the digital twin wireless communication system corresponding to the i-th data packet according to the configuration information corresponding to the i-th data packet, the i-th data packet is transmitted in the digital twin wireless communication system, where i = 1, …, N.

[0170] In some embodiments, a digital twin wireless communication system is generated according to the capabilities of the communication system, and the transmission of N data packets is simulated in the digital twin wireless communication system according to M configuration information of the N data packets. Wherein, the capabilities of the communication system include the resource domain capabilities and / or signal domain capabilities of the communication system.

[0171] In some embodiments, the process of simulating the transmission of N data packets according to M configuration information of the N data packets in the digital twin wireless communication system is as follows: for the i-th data packet among the N data packets, according to the configuration information of the i-th data packet, resource domain information for transmitting the i-th data packet is configured in the digital twin wireless communication system, such as configuring at least one of the following resources for transmitting the i-th data packet: time domain resources, frequency domain resources, spatial domain resources, code domain resources, computing power resources, storage resources, index set of the first node used, index set of the second node used. According to the configuration information of the i-th data packet, signal domain information for transmitting the i-th data packet is configured in the digital twin wireless communication system, such as at least one of the carrier frequency used for transmitting the i-th data packet, the mode of carrier aggregation, the value of modulation and coding scheme, the configuration of DMRS, the configuration of CSI-RS, the multi-antenna mode, the information processing method, etc. And the i-th data packet is transmitted according to the transmission resources and signal processing algorithms determined by the configured resource domain information and signal domain information. Here, i = 1, …, N.

[0172] In some embodiments, for each of the N data packets, it is determined whether the transmission of the data packet in the digital twin wireless communication system meets the transmission requirements. In one example, determining whether the transmission of the i-th data packet meets the transmission requirements means whether the i-th data packet meets at least one of the characteristics in the characteristic set corresponding to the i-th data packet after the transmission is completed. For example, whether it meets one or more of the spectral efficiency requirements, transmission delay requirements, reliability requirements, capacity requirements, energy efficiency requirements, service quality requirements of the i-th data packet. As for how many characteristics need to be met, it can be preset or agreed in advance. Here, i = 1, …, N.

[0173] If any one of the N data packets meets the transmission requirements during the transmission of the data packets in the digital twin wireless communication system, determine the M configuration information of the N data packets as the final M configuration information;

[0174] If at least one of the N data packets does not meet the transmission requirements during the transmission in the digital twin wireless communication system, determine and update the M configuration information of the N data packets according to the M feature sets corresponding to the N data packets in the control domain;

[0175] Perform the above operations until the transmission of the N data packets in the digital twin wireless communication system all meets the transmission requirements.

[0176] In this way, when any one of the N data packets meets the transmission requirements during the transmission in the digital twin wireless communication system, determining the final M configuration information of the N data packets can improve the accuracy of determining the configuration information of the N data packets, so that the wireless communication system can better transmit the N data packets based on the final M configuration information later, improving the comprehensive performance of the communication system.

[0177] In some embodiments, after simulating the transmission of the N data packets according to the M configuration information of the N data packets in the digital twin wireless communication system and determining the final M configuration information of the N data packets when each data packet meets the transmission requirements, the wireless communication system determines the transmission resources of the N data packets according to the M configuration information of the N data packets and transmits the N data packets on the transmission resources.

[0178] In some embodiments, the wireless communication system determines the transmission resources corresponding to the i-th data packet according to the configuration information of the i-th data packet and transmits the i-th data packet on the transmission resources, where i is a non-negative integer less than or equal to N.

[0179] In some embodiments, the wireless communication system sends the M configuration information of the N data packets to the second node through the first node; or directly sends the M configuration information of the N data packets to the second node.

[0180] Exemplarily, taking the first node as the base station and the second node as the terminal as an example, the wireless communication system sends the M configuration information of the N data packets to the corresponding base station, and the base station then sends the M configuration information of the N data packets to the corresponding terminal. Or directly send the M configuration information of the N data packets to the corresponding terminal.

[0181] In some embodiments, the wireless communication system includes an information controller located in at least one of the following: a base station, a core network, a third-party server. The information controller is configured to execute the method described in any of the above embodiments or examples. The present disclosure places no limitation on the number of base stations and third-party servers. For example, the information controller may be located in one or more base stations, and / or in one or more core network elements, and / or in one or more independent third-party servers. The information controller may also have other names, such as a centralized controller, an intelligent domain, which is not limited in the present disclosure.

[0182] The following are some embodiments for illustrating the process of actually transmitting the i-th data packet in the wireless communication system, where i is a non-negative integer less than or equal to N.

[0183] In some embodiments, for the i-th data packet, according to the configuration information of the i-th data packet, resource domain information for transmitting the i-th data packet is configured in the wireless communication system, such as configuring at least one of the following resources for transmitting the i-th data packet: time-domain resources, frequency-domain resources, space-domain resources, code-domain resources, computing power resources, storage resources, the index set of the first nodes used, the index set of the second nodes used. According to the configuration information of the i-th data packet, signal domain information for transmitting the i-th data packet is configured in the wireless communication system, such as at least one of the carrier frequency used for transmitting the i-th data packet, the mode of carrier aggregation, the value of the modulation and coding scheme, the configuration of DMRS, the configuration of CSI-RS, the multi-antenna mode used, the information processing method used, etc. And according to the configured resource domain information and signal domain information, the i-th data packet is transmitted, where i = 1,..., N.

[0184] In one example, for one of the N data packets, in the resource domain and signal domain configurations of the wireless communication system corresponding to this data packet, the first communication node includes K1 base stations for joint transmission, and it is coherent joint transmission, using K2 data streams, and the bandwidth is allocated K3 sub-bands. Then, the K1 base stations are used to transmit the data packet in a coherent joint transmission manner in the K3 sub-bands, where K1, K2, and K3 are positive integers greater than 1.

[0185] In one example, for one of the N data packets, its reliability requirement is greater than 99.99%, and the transmission delay is less than 1 ms. To meet this reliability requirement and transmission delay requirement, in the resource domain and signal domain configuration of the wireless communication system, K1 data streams are allocated to this data packet, and K2 sub-bands are allocated. Among these sub-bands, the sub-bands are divided into two sub-band groups, and frequency-domain repeated transmission is performed for each sub-band group. That is, the content transmitted by the two sub-band groups is the same to improve reliability. And in the channel coding scheme, QAM with a code rate of 1 / 2 is selected to improve reliability, where K1 and K2 are positive integers greater than 1.

[0186] In one example, for one of the N data packets, its reliability requirement is greater than 99.99%, and the transmission delay is less than 10 ms. To meet this reliability requirement and transmission delay requirement, in the resource domain and signal domain configuration of the wireless communication system, K1 data streams are allocated to this data packet, and K2 sub-bands are allocated. Since its delay requirement is relatively large, it can be transmitted in K3 time slots. To provide reliability, repeated transmission can be performed in K3 different time slots. That is, the content transmitted in multiple different time slots is the same to improve reliability. And in the channel coding scheme, QAM with a code rate of 1 / 2 is selected to improve reliability, where K1, K2, and K3 are positive integers greater than 1.

[0187] In one example, for one of the N data packets, its energy efficiency requirement is that the energy consumption per bit is less than a bit / joule, or the radio frequency transmission power of each base station is less than b watts, where a or b is a positive real number and can be less than 1 / 4 of the existing 5G communication system. In the resource domain and signal domain configuration of the wireless communication system, K1 data streams are allocated to this data packet, and K2 sub-bands are allocated. The allocated multi-antenna technology is distributed MIMO without cells (where without cells can also be referred to as without a honeycomb, or cell free). According to the location information of the user, the K3 base stations closest to this user, or the K3 base stations with the minimum path loss, or the K3 references with the minimum reference signal receiving power (RSRP) are found to transmit data for it. By selecting the base station closest to the user to serve it, the transmission power can be reduced. To achieve the purpose of saving energy consumption, K1, K2, and K3 are integers greater than or equal to 1.

[0188] In one example, for one of the N data packets, in the resource domain and signal domain configurations of the wireless communication system corresponding to this data packet, the first communication node includes one base station, K1 data streams are used, and K2 sub-bands are allocated for the bandwidth. Due to obstructions, the signal to interference plus noise ratio (SINR) is relatively small. To improve its spectral efficiency, a reconfigurable intelligent surface (RIS) that can cover this user is selected. Then, the one base station and the RIS are used to transmit the data packet in the K2 sub-bands, where K1 and K2 are integers greater than or equal to 1.

[0189] In one example, for one of the N data packets, in the resource domain and signal domain configurations of the wireless communication system corresponding to this data packet, the first communication node includes one base station, K1 data streams are used, and K2 sub-bands are allocated for the bandwidth. However, since this user supports at most two data streams, it is difficult to meet the spectral efficiency requirements. However, it supports multi-node joint reception (such as virtual MIMO). To improve its spectral efficiency, the wireless communication system configures K3 cooperative terminals for the terminal corresponding to this data packet. The K3 cooperative terminals and the terminal corresponding to the data packet receive the K1 data streams sent by the base station in the form of virtual MIMO. Here, K1, K2, and K3 are positive integers greater than 1.

[0190] In one example, for one data packet out of N data packets, the wireless communication system is configured to jointly receive (or referred to as virtual MIMO) the data packet using a group of terminals. Here, the group of terminals includes K terminals, where K is a positive integer greater than 1. Among them, this data packet is to be transmitted to the first terminal in the group of terminals. Subsequently, the first terminal is referred to as the primary terminal, and the other terminals are referred to as assisting terminals. To enable the base station to better configure resource domain information and signal domain information, the primary terminal needs to feedback the following channel state information through high-layer signaling and / or physical layer signaling: the rank RI1 supported by a single node, the rank RI2 supported by multi-node joint reception, the precoding matrix indicator PMI1 corresponding to a single node, the precoding matrix indicator PMI2 corresponding to multi-node joint reception, the channel quality indicator CQI1 corresponding to a single node, and the channel quality indicator CQI2 corresponding to multiple joint receptions. Here, RI1, PMI1, and CQI1 are the channel rank, precoding matrix indicator, and channel quality indicator corresponding to the channel when only the primary terminal receives. RI2, PMI2, and CQI2 are the channel rank, precoding matrix indicator, and channel quality indicator corresponding to the channel when jointly receiving with at least one assisting terminal. During joint reception, it is also necessary to feedback the number of terminals for joint reception and the channel rank corresponding to each terminal. In some examples, the primary terminal also needs to feedback the number of reference signal resource ports it expects the base station to configure and / or the processing delay. In one example, the processing delay includes Z and Z’, where Z is the interval from the last symbol of the physical downlink control channel (PDCCH) transmitted by the base station to the first symbol of the physical uplink shared channel (PUSCH) used to carry CSI, and Z’ is the interval from the last symbol of the channel state information reference signal transmitted by the base station for calculating CSI to the first symbol of the PUSCH used to carry CSI. In one example, it is necessary to redefine the table of Z and Z’. In one example, a fixed offset value is added to the table based on the existing 5G NR technology table.

[0191] In one example, when the wireless communication system is not configured for multi-node joint reception, the terminal also needs to feedback the number of reference signal resource ports it expects the base station to configure and / or the processing delay. Here, the definitions of Z and Z’ are as described in the previous embodiments and will not be elaborated here. The base station receives at least one of the number of reference signal resource ports, processing delay, etc. feedback by the terminal to better determine and configure signal domain configuration information and / or resource domain configuration information.

[0192] In some examples, before the wireless communication system determines the M configuration information of the N data packets according to the M feature sets corresponding to the N data packets in the control domain, it further includes receiving feedback parameters transmitted by a communication node, where the feedback parameters of the communication node include at least one of the following: the rank RI1 supported by a single node, the rank RI2 supported by multi-node joint reception, the precoding matrix indicator PMI1 corresponding to a single node, the precoding matrix indicator PMI2 corresponding to multi-node joint reception, the channel quality indicator CQI1 corresponding to a single node, the channel quality indicator CQI2 corresponding to multi-node joint reception, the expected number of reference signal ports to be configured, the expected processing delay Z and the expected processing delay Z', the bias of the processing delay Z, the bias of the processing delay Z', and the table index of the processing delay.

[0193] In some examples, the wireless communication system determines the M configuration information of the N data packets in the control domain according to the M feature sets corresponding to the N data packets and at least one of the received feedback parameters of the communication node. For example, in one example, it determines whether to configure multi-node joint reception according to the size relationship between the rank RI1 supported by a single node and the rank RI2 supported by multi-node joint reception in the feedback parameters. For example, if RI1 is less than RI2, multi-node joint reception is configured; otherwise, single-node reception is configured. For example, in one example, it determines whether to configure multi-node joint reception according to the size relationship between the capacity of CQI1 corresponding to a single node and the capacity of CQI2 corresponding to multi-node joint reception in the feedback parameters. For example, if the capacity corresponding to CQI1 is less than the capacity corresponding to CQI2, multi-node joint reception is configured; otherwise, single-node reception is configured. For example, in one example, it determines whether to use an artificial intelligence-based processing method according to the size of the processing delay Z or Z'. When Z and Z' meet the processing delay of the artificial intelligence model, the artificial intelligence-based method can be configured to process the signal; otherwise, a non-artificial intelligence-based method is configured to process the signal. For example, in one example, it determines whether to configure multi-node joint reception according to the size of the processing delay Z or Z'. When Z and Z' meet the processing delay of multi-node joint reception, multi-node joint reception can be configured; otherwise, single-node reception is configured.

[0194] Based on this, N data packets generated by the application domain are obtained; according to the N data packets, M feature sets corresponding to the N data packets are determined, and the feature sets include at least one of the following features: spectrum efficiency requirement, transmission delay requirement, reliability requirement, capacity requirement, energy efficiency requirement, quality of service requirement; in the control domain, according to the M feature sets corresponding to the N data packets, M configuration information of the N data packets is determined, and the configuration information includes signal domain configuration information and resource domain configuration information. The N data packets are processed according to the M configuration information of the N data packets and intelligent technologies. Thus, intelligent multi-domain (application domain, control domain, signal domain, resource domain) efficient collaborative management is realized, ensuring that each data packet can obtain an optimal or near-optimal processing path and resource allocation, and improving the comprehensive performance of the mobile communication network.

[0195] The above mainly introduces the solution of the embodiments of the present disclosure from the perspective of methods. The following also shows an information processing device for intelligent multi-domain efficient collaboration, which is used to execute the information processing method for intelligent multi-domain efficient collaboration in any of the above embodiments and its possible implementation manners. It can be understood that, in order to implement the information processing method for intelligent multi-domain efficient collaboration, the information processing device for intelligent multi-domain efficient collaboration includes corresponding hardware structures and / or software modules for executing each function; those skilled in the art should easily realize that, combined with the algorithm steps of each example described in the embodiments of the present disclosure, the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraint conditions of the technical solution. Professional technicians can use different methods to implement the described function for each specific application, but such implementation should not be considered to exceed the scope of the present disclosure.

[0196] The embodiments of the present disclosure can divide the information processing device for intelligent multi-domain efficient collaboration into functional modules according to the above method embodiments. For example, each functional module can be divided corresponding to each function, or two or more functions can be integrated into one functional module. The above integrated module can be implemented in the form of hardware or software. It should be noted that the division of modules in the embodiments of the present disclosure is illustrative, only a logical function division, and there can be other division methods in actual implementation. The following takes the example of dividing each functional module corresponding to each function for illustration.

[0197] Figure 4 FIG. 10 is a schematic structural diagram of an information processing device for intelligent multi-domain efficient collaboration provided by an embodiment of the present disclosure, which is applied to a wireless communication system. The information processing device 400 for intelligent multi-domain efficient collaboration includes: an acquisition module 401, a first determination module 402, a second determination module 403, a processing module 404, and a communication module 405.

[0198] Among them, an obtaining module 401 is configured to obtain N data packets generated by an application domain;

[0199] A first determining module 402 is configured to determine M feature sets corresponding to the N data packets according to the N data packets, and the feature sets include at least one of the following features: spectrum efficiency requirement, transmission delay requirement, reliability requirement, capacity requirement, energy efficiency requirement, quality of service requirement;

[0200] A second determining module 403 is further configured to determine M configuration information of the N data packets in a control domain according to the M feature sets corresponding to the N data packets, and the configuration information includes signal domain configuration information and resource domain configuration information;

[0201] A processing module 404 is further configured to process the N data packets according to the M configuration information of the N data packets and an intelligent technology, where N and M are positive integers.

[0202] In some embodiments, the N data packets correspond to K different application domain services, and the application domain services include at least one of the following: game service, voice service, long video service, short video service, picture service, payment service, positioning service, chat service, web page service, high-definition video, virtual reality, augmented reality, mixed reality, perception service, where K is a positive integer and K is less than or equal to N.

[0203] In some embodiments, the signal domain configuration information at least includes one of the following: carrier frequency, carrier aggregation mode, modulation mode, demodulation reference signal configuration information, channel state information reference signal configuration information, multiplexing mode, multi-antenna mode, information processing mode.

[0204] In some embodiments, the resource domain configuration information at least includes one of the following: time domain resource configuration information, frequency domain resource configuration information, space domain resource configuration information, code domain resource configuration information, computing power resource configuration information, storage resource configuration information, a first node set, a second node set.

[0205] In some embodiments, the first determining module 402 is specifically configured to:

[0206] Determine M feature sets corresponding to the N data packets according to the feature parameters of each data packet in the N data packets, and the feature parameters include at least one of the following: quality of service of the data packet, size of the data packet, generation frequency of the data packet.

[0207] In some embodiments, the first determining module 402 is specifically configured to:

[0208] Input the characteristic parameters of each of the N data packets into an artificial intelligence model to obtain M feature sets corresponding to the N data packets. Some layers of the artificial intelligence model include at least one of the following: at least one residual block, at least one dense block, at least one long short-term memory network, at least one encoder, and at least one decoder.

[0209] In some embodiments, the first determination module 402 is specifically configured to:

[0210] In the case where the number of feature sets corresponding to the N data packets is greater than N, perform a merging operation on the multiple feature sets according to the similarity distances between the feature sets corresponding to the N data packets until the number of feature sets is less than or equal to N, to obtain M feature sets.

[0211] In some embodiments, the second determination module 403 is specifically configured to:

[0212] In the case where M is equal to N, determine the configuration information of the i-th data packet according to the feature set of the i-th data packet, where i is a non-negative integer less than or equal to M.

[0213] In some embodiments, the second determination module 403 is specifically configured to:

[0214] Input the feature set of the i-th data packet into the artificial intelligence model to obtain the configuration information of the i-th data packet.

[0215] In some embodiments, the second determination module 403 is specifically configured to:

[0216] Determine the feature combination to which the feature set of the i-th data packet belongs according to at least one feature in the feature set of the i-th data packet;

[0217] Determine the configuration information of the i-th data packet according to the feature combination, and the corresponding relationship between the feature combination and the configuration information of the data packet is predefined.

[0218] In some embodiments, the second determination module 403 is specifically configured to:

[0219] Determine M configuration information of the N data packets according to the M feature sets corresponding to the N data packets and the capabilities of the communication system; wherein, the capabilities of the communication system include at least one of the following: the signal domain capabilities of the communication system, the resource domain capabilities of the communication system.

[0220] In some embodiments, the signal domain capabilities of the communication system include at least one of the following: whether the first node supports joint transmission, the type of joint transmission supported by the first node, whether the first node supports distributed precoding, the maximum number of data streams transmitted by the first node, whether the first node supports repeated transmission, the type of repeated transmission supported by the first node, whether the second node supports multi-node joint reception, whether the second node supports repeated transmission, the modulation method supported, whether high-frequency beamforming is supported, the bandwidth size supported, whether artificial intelligence is supported, and the type of artificial intelligence model.

[0221] In some embodiments, the resource domain capabilities of the communication system include at least one of the following: computing power resource capabilities, storage resource capabilities; wherein, the computing power resource capabilities include at least one of the following: the number of graphics processors supported, the number of central processing units supported, the type of graphics processor supported, the type of central processing unit supported, the remaining computing power resource size, the data types and precisions supported by the hardware; the storage resource capabilities include one of the following: the memory size, the number of registers, the video memory size of the graphics processor, the remaining storage resource size.

[0222] In some embodiments, the second determination module 403 is specifically configured to:

[0223] Input the M feature sets of the N data packets and the capabilities of the communication system into the artificial intelligence model to obtain the M configuration information of the N data packets.

[0224] In some embodiments, the second determination module 403 is specifically configured to at least one of the following:

[0225] Input the M feature sets of the N data packets and the signal domain capabilities of the communication system into the first artificial intelligence model to obtain the M configuration information of the N data packets;

[0226] Input the M feature sets of the N data packets and the resource domain capabilities of the communication system into the second artificial intelligence model to obtain the M configuration information of the N data packets;

[0227] Input the M feature sets of the N data packets, the signal domain capabilities of the communication system, and the resource domain capabilities of the communication system into the third artificial intelligence model to obtain the M configuration information of the N data packets.

[0228] In some embodiments, the second determination module 403 is specifically configured to:

[0229] For the i-th data packet among the N data packets, determine the feature and capability combination to which the i-th data packet belongs according to at least one feature of the feature set of the i-th data packet and the capabilities of the communication system;

[0230] Determine the configuration information of the i-th data packet according to the combination of features and capabilities to which the i-th data packet belongs, where the corresponding relationship between the combination of features and capabilities and the configuration information is predefined, and i is a positive integer less than or equal to N.

[0231] In some embodiments, the processing module 404 is specifically configured to:

[0232] Generate a digital twin wireless communication system that simulates the application domain, control domain, and information domain, and simulate the transmission of N data packets according to the M configuration information of the N data packets in the digital twin wireless communication system;

[0233] Determine whether the transmission of each of the N data packets in the digital twin wireless communication system meets the transmission requirements;

[0234] If the transmission of all N data packets in the digital twin wireless communication system meets the transmission requirements, determine the M configuration information of the N data packets as the final M configuration information;

[0235] If the transmission of at least one of the N data packets in the digital twin wireless communication system does not meet the transmission requirements, then in the control domain, determine and update the M configuration information of the N data packets according to the M feature sets corresponding to the N data packets;

[0236] Execute the above operations until the transmission of all N data packets in the digital twin wireless communication system meets the transmission requirements.

[0237] In some embodiments, the processing module 404 is specifically configured to:

[0238] Determine the transmission resources of the N data packets according to the M configuration information of the N data packets, and transmit the N data packets on the transmission resources.

[0239] In some embodiments, the communication module 405 is specifically configured to:

[0240] Send the M configuration information of the N data packets to the second node through the first node; or,

[0241] Send the M configuration information of the N data packets directly to the second node.

[0242] In some embodiments, the wireless communication system includes an information controller, and the information controller is located in at least one of the following: base station, core network, third-party server, and the information controller is used to execute the method described in any of the above embodiments or examples.

[0243] For a more detailed description of the above-mentioned acquisition module 401, the first determination module 402, the second determination module 403, the processing module 404, and the communication module 405, as well as a more detailed description of each technical feature therein, and a description of the beneficial effects, etc., reference can be made to the corresponding method embodiment part above, which will not be elaborated here.

[0244] It should be noted that Figure 4 the modules in can also be referred to as units. For example, the communication module can be referred to as a communication unit. Additionally, in Figure 4 the illustrated embodiment, the names of the various modules may not be the names shown in the figure. For example, the communication module can also be referred to as a sending module or a receiving module.

[0245] Figure 4 If each unit or module in is implemented in the form of a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present disclosure, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods of the various embodiments of the present disclosure. The storage media storing the computer software product include: various media such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs that can store program codes.

[0246] In the case of implementing the functions of the above-mentioned integrated modules in the form of hardware, the embodiments of the present disclosure also provide a possible structure of a communication device. This communication device is used to execute the intelligent multi-domain efficient collaborative information processing method provided by the embodiments of the present disclosure. As Figure 5 shown, the communication device 500 includes: a communication interface 503, a processor 502, and a bus 504. Optionally, the communication device may further include a memory 501.

[0247] The processor 502 can be a device that implements or executes various exemplary logical blocks, modules, and circuits described in connection with the embodiments of the present disclosure. The processor 502 can be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array, or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute various exemplary logical blocks, modules, and circuits described in connection with the embodiments of the present disclosure. The processor 502 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0248] The communication interface 503 is used to connect to other devices through a communication network. The communication network can be an Ethernet, a wireless access network, a wireless local area network (WLAN), etc.

[0249] The memory 501 can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM), or other type of dynamic storage device that can store information and instructions. It can also be an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium, or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0250] As a possible implementation, the memory 501 can exist independently of the processor 502. The memory 501 can be connected to the processor 502 through a bus 504 for storing instructions or program code. When the processor 502 calls and executes the instructions or program code stored in the memory 501, it can implement the intelligent multi-domain efficient collaborative information processing method provided by the embodiments of the present disclosure.

[0251] In another possible implementation, the memory 501 can also be integrated with the processor 502.

[0252] The bus 504 can be an extended industry standard architecture (EISA) bus, etc. The bus 504 can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 5 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0253] Some embodiments of the present disclosure provide a computer-readable storage medium (e.g., a non-transitory computer-readable storage medium) storing computer program instructions, which, when running on a computer, cause the computer to execute the information processing method for intelligent multi-domain efficient collaboration as described in any one of the above embodiments.

[0254] In an exemplary embodiment, the computer may be the above-mentioned information processing device for intelligent multi-domain efficient collaboration, and the present disclosure places no limitation on the specific form of the computer.

[0255] In some examples, the above computer-readable storage medium may include, but is not limited to: magnetic storage devices (e.g., hard disks, floppy disks, or magnetic tapes, etc.), optical discs (e.g., compact disks (CD), digital versatile disks (DVD), etc.), smart cards, and flash memory devices (e.g., erasable programmable read-only memories (EPROM), cards, sticks, or key drives, etc.). The various computer-readable storage media described in the present disclosure may represent one or more devices and / or other machine-readable storage media for storing information. The term "machine-readable storage medium" may include, but is not limited to, wireless channels and various other media capable of storing, containing, and / or carrying instructions and / or data.

[0256] The embodiments of the present disclosure provide a computer program product containing instructions, which, when running on a computer, cause the computer to execute the information processing method for intelligent multi-domain efficient collaboration as described in any one of the above embodiments.

[0257] As described above, the above are only the specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present disclosure should be covered by the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the protection scope of the claims.

Claims

1. An intelligent multi-domain efficient collaborative information processing method, characterized in that: Applied to a wireless communication system, the method comprises: Get N data packets generated by the application domain; Determine, according to the N data packets, M feature sets corresponding to the N data packets, where the feature sets include at least one of the following features: spectrum efficiency requirement, transmission delay requirement, reliability requirement, capacity requirement, energy efficiency requirement, and quality of service requirement; Determine, in the control domain, M configuration information of the N data packets according to the M feature sets corresponding to the N data packets, wherein the configuration information includes signal domain configuration information and resource domain configuration information; The N data packets are processed according to the M configuration information of the N data packets and intelligent technology, where N and M are positive integers.

2. The method according to claim 1, characterized in that The N data packets correspond to K different application domain services, and the application domain services include at least one of the following: game services, voice services, long video services, short video services, picture services, payment services, positioning services, chat services, web services, high-definition video, virtual reality, augmented reality, mixed reality, and perception services, where K is a positive integer and K is less than or equal to N.

3. The method according to claim 1, characterized in that The signal domain configuration information includes at least one of the following: carrier frequency, carrier aggregation mode, modulation mode, demodulation reference signal configuration information, channel state information reference signal configuration information, multiplexing mode, multi-antenna mode, and information processing mode.

4. The method according to claim 1, characterized in that: The resource domain configuration information includes at least one of the following: time domain resource configuration information, frequency domain resource configuration information, space domain resource configuration information, code domain resource configuration information, computing power resource configuration information, storage resource configuration information, sending node set, and receiving node set.

5. The method according to claim 1, characterized in that The determining, according to the N data packets, M feature sets corresponding to the N data packets comprises: According to the characteristic parameters of each of the N data packets, M feature sets corresponding to the N data packets are determined, and the characteristic parameters include at least one of the following: service quality of the data packet, size of the data packet, and generation frequency of the data packet.

6. The method according to claim 5, characterized in that The determining, according to the characteristic parameters of each data packet in the N data packets, M feature sets corresponding to the N data packets comprises: The characteristic parameters of each of the N data packets are input into an artificial intelligence model to obtain M feature sets corresponding to the N data packets, and some layers of the artificial intelligence model include at least one of the following: at least one residual block, at least one dense block, at least one long short-term memory network, at least one encoder, and at least one decoder.

7. The method according to claim 1, characterized in that The determining, according to the N data packets, M feature sets corresponding to the N data packets comprises: When the number of feature sets corresponding to the N data packets is greater than N, a plurality of the feature sets are merged according to similarity distances between the feature sets corresponding to the N data packets until the number of the feature sets is less than or equal to N, thereby obtaining M feature sets.

8. The method according to claim 1, characterized in that: The determining, according to the M feature sets corresponding to the N data packets, the M configuration information of the N data packets comprises: When M is equal to N, the configuration information of the ith data packet is determined according to the feature set of the ith data packet, where i is a non-negative integer less than or equal to M.

9. The method according to claim 8, characterized in that The determining, according to the feature set of the i-th data packet, the configuration information of the i-th data packet comprises: The feature set of the i-th data packet is input into an artificial intelligence model to obtain configuration information of the i-th data packet.

10. The method according to claim 8, characterized in that The determining, according to the feature set of the i-th data packet, the configuration information of the i-th data packet comprises: Determine, according to at least one feature in the feature set of the i-th data packet, the feature combination to which the feature set of the i-th data packet belongs; According to the feature combination of the i-th data packet, the configuration information of the i-th data packet is determined, and the corresponding relationship between the feature combination and the configuration information is predefined.

11. The method according to claim 1, characterized in that: The determining, according to the M feature sets corresponding to the N data packets, the M configuration information of the N data packets comprises: The M configuration information of the N data packets are determined according to the M feature sets corresponding to the N data packets and the capability of the communication system; wherein the capability of the communication system includes at least one of the following: the signal domain capability of the communication system, and the resource domain capability of the communication system.

12. The method according to claim 11, characterized in that The signal domain capabilities of the communication system include at least one of the following: whether the first node supports joint transmission, the type of joint transmission supported by the first node, whether the first node supports distributed precoding, the maximum number of data streams transmitted by the first node, whether the first node supports repeated transmission, the type of repeated transmission supported by the first node, whether the second node supports multi-node joint reception, whether the second node supports repeated transmission, supported modulation methods, whether high-frequency beamforming is supported, supported bandwidth size, whether artificial intelligence is supported, and the model type of artificial intelligence.

13. The method according to claim 11, characterized in that The resource domain capabilities of the communication system include at least one of the following: computing power resource capabilities and storage resource capabilities; wherein the computing power resource capabilities include at least one of the following: the number of graphics processors supported, the number of central processing units supported, the types of graphics processors supported, the types of central processing units supported, the remaining computing power resource size, the data types and precision supported by the hardware; the storage resource capabilities include one of the following: memory size, the number of registers, the video memory size of the graphics processor, and the size of the remaining storage resources.

14. The method according to claim 11, characterized in that The determining the M configuration information of the N data packets according to the M feature sets corresponding to the N data packets and the capability of the communication system includes: The M feature sets of the N data packets and the capability of the communication system are input into an artificial intelligence model to obtain M configuration information of the N data packets.

15. The method according to claim 14, characterized in that The step of inputting the M feature sets of the N data packets and the capability of the communication system into an artificial intelligence model to obtain the M configuration information of the N data packets includes at least one of the following: Inputting the M feature sets of the N data packets and the signal domain capability of the communication system into a first artificial intelligence model to obtain M configuration information of the N data packets; Inputting the M feature sets of the N data packets and the resource domain capability of the communication system into a second artificial intelligence model to obtain M configuration information of the N data packets; The M feature sets of the N data packets, the signal domain capability of the communication system, and the resource domain capability of the communication system are input into a third artificial intelligence model to obtain M configuration information of the N data packets.

16. The method according to claim 11, characterized in that The determining the M configuration information of the N data packets according to the M feature sets corresponding to the N data packets and the capability of the communication system includes: For an i-th data packet of the N data packets, determining a feature and capability combination to which the i-th data packet belongs according to at least one feature of a feature set of the i-th data packet and a capability of the communication system; According to the feature and capability combination to which the i-th data packet belongs, the configuration information of the i-th data packet is determined, the correspondence between the feature and capability combination and the configuration information is predefined, and i is a positive integer less than or equal to N.

17. The method according to claim 1, characterized in that The processing of the N data packets according to the M configuration information of the N data packets and the intelligent technology includes: Generate a digital twin wireless communication system simulating the application domain, the control domain and the information domain, and simulate the transmission of the N data packets according to the M configuration information of the N data packets in the digital twin wireless communication system; Determine whether transmission of each of the N data packets in the digital twin wireless communication system meets transmission requirements; If the transmission of the N data packets in the digital twin wireless communication system meets the transmission requirements, determine that the M configuration information of the N data packets are the final M configuration information; If the transmission of at least one of the N data packets in the digital twin wireless communication system does not meet the transmission requirements, then determining and updating the M configuration information of the N data packets in the control domain according to the M feature sets corresponding to the N data packets; The above operations are performed until the transmission of the N data packets in the digital twin wireless communication system meets the transmission requirements.

18. The method according to claim 1, characterized in that The processing of the N data packets according to the M configuration information of the N data packets and the intelligent technology includes: According to the M configuration information of the N data packets, transmission resources of the N data packets are determined, and the N data packets are transmitted on the transmission resources.

19. The method according to claim 1, characterized in that The method further comprises: Sending the M configuration information of the N data packets to the second node through the first node; or, The M configuration information of the N data packets are directly sent to the second node.

20. A wireless communication system, characterized in that: The wireless communication system includes an information controller, which is located in at least one of the following: a base station, a core network, and a third-party server. The information controller is used to execute the method as described in any one of claims 1 to 19.

21. A communication device, characterized in that: include: Memory and processor; Memory and processor coupling; The memory is used to store instructions executable by the processor; When the processor executes the instructions, the method according to any one of claims 1 to 19 is performed.

22. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are executed on a communication device, the communication device is caused to execute the method according to any one of claims 1 to 19.

23. A computer program product, characterized in that When the computer program product is executed, the method according to any one of claims 1 to 19 is implemented.

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