Network side model inference verification based on artificial intelligence

Abstract

A method of artificial intelligence (AI) based model inference validation implemented by a user equipment (UE). The method includes decoding, from a network, a one-time measurement configuration for AI based model validation; storing, at the UE, the one-time measurement configuration; performing, by the UE, one or more measurements based on the one-time measurement configuration; and encoding, for transmission to the network, the one or more measurements for validating one or more AI based models at the network.

Description

Technical Field

[0001] Embodiments of the present invention relate to wireless communication, including apparatus, systems, and methods for implementing network-side artificial intelligence-based model inference verification in cellular communication networks. Background Technology

[0002] The use of wireless communication systems is growing rapidly. In recent years, wireless devices, such as smartphones and tablets, have become increasingly complex and sophisticated. In addition to supporting telephone calls, many mobile devices now offer access to the Internet, email, text messaging, and navigation using the Global Positioning System (GPS), and are capable of operating complex applications that utilize these functionalities.

[0003] Long Term Evolution (LTE) has become the technology of choice for most wireless network operators worldwide, providing mobile broadband data and high-speed internet access to their user base. LTE was first proposed in 2004 and standardized for the first time in 2008. Since then, with the exponential growth in the use of wireless communication systems, the demand from wireless network operators to support higher capacity for a higher density of mobile broadband users has also increased. Research into new radio access technologies began in 2015, and in 2017, the first version of 5G New Radio (5G NR) was standardized.

[0004] 5G-NR (also known as NR for short) offers higher capacity for higher density mobile broadband users compared to LTE, while also supporting ultra-reliable and massive machine-type communication between devices, as well as lower latency and / or lower battery consumption. Additionally, NR allows for more flexible UE scheduling compared to current LTE. Therefore, ongoing development of 5G-NR is underway to take advantage of the potentially higher throughput at higher frequencies. Summary of the Invention

[0005] The implementation relates to wireless communication, and more specifically to apparatus, systems, and methods for a device for a user equipment (UE), the device including one or more processors coupled to a memory, the one or more processors being configured to: decode from a network a one-off measurement configuration for artificial intelligence (AI)-based model validation; have the UE perform one or more measurements based on the one-off measurement configuration; store the one-off measurement configuration at the UE; and encode the one or more measurements for validating the one or more AI-based models at the network for transmission to the network.

[0006] Other embodiments involve apparatus for a base station (e.g., a base station (base station)) including one or more processors coupled to a memory, the one or more processors being configured to: encode a one-off measurement configuration for artificial intelligence (AI)-based model validation for transmission to a user equipment (UE), wherein the UE is able to store the one-off measurement configuration at the UE and perform one or more measurements based on the one-off measurement configuration; and decode from the UE the one or more measurements for validating the one or more AI-based models at the network.

[0007] The technologies described herein can be implemented in and / or used with a variety of different types of devices, including but not limited to unmanned aerial vehicles (UAVs), unmanned controllers (UACs), base stations, access points, cellular phones, tablet computers, wearable computing devices, portable media players, and any of a variety of other computing devices.

[0008] The present invention is intended to provide a brief overview of some of the subjects described in this document. Therefore, it should be understood that the features described above are merely illustrative and should not be construed as narrowing the scope or substance of the subjects described herein in any way. Other features, aspects, and advantages of the subjects described herein will become apparent from the following detailed description, drawings, and claims. Attached Figure Description

[0009] A better understanding of the subject matter can be obtained by considering the following detailed description of various embodiments in conjunction with the accompanying drawings, in which: Figure 1A Example wireless communication systems according to some implementation schemes are illustrated.

[0010] Figure 1B Examples of base stations and access points communicating with user equipment (UE) devices according to some implementation schemes are illustrated.

[0011] Figure 2 Example block diagrams of base stations according to some implementation schemes are shown.

[0012] Figure 3 Example block diagrams of servers according to some implementation schemes are shown.

[0013] Figure 4 Exemplary block diagrams of a UE according to some implementation schemes are shown.

[0014] Figure 5 Exemplary block diagrams of cellular communication circuits according to some implementation schemes are shown.

[0015] Figure 6Examples of baseband processor architectures for UEs according to some implementation schemes are illustrated.

[0016] Figure 7 Example block diagrams illustrating the interface of a baseband circuit according to some implementation schemes are shown.

[0017] Figure 8 Examples of control plane protocol stacks based on some implementation schemes are shown.

[0018] Figure 9 An example timing diagram signaling is illustrated according to some implementation schemes for implementing AI-based model inference verification on the network side between a user equipment (UE) and a base station (e.g., a base station (base station)).

[0019] Figure 10 Example flowcharts illustrate methods for implementing network-side AI-based model inference verification at the user equipment (UE) according to some implementation schemes.

[0020] Figure 11 An example flowchart illustrates a method for implementing network-side AI-based model inference verification at a base station according to some implementation schemes.

[0021] Although the features described herein may be subject to various modifications and alternatives, specific embodiments thereof are shown by way of example in the accompanying drawings and described in detail herein. However, it should be understood that the drawings and their detailed description are not intended to limit one to the specific forms disclosed, but rather to cover all modifications, equivalents, and alternatives falling within the substance and scope of the subject matter as defined by the appended claims. Detailed Implementation

[0022] the term The following is a glossary of terms used in this disclosure: Memory media—any of various types of nontransitory memory devices or storage devices. The term "memory media" is intended to include mounting media, such as CD-ROMs, floppy disks, or magnetic tape devices; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory; magnetic media, such as hard disk drives or optical storage devices; registers or other similar types of memory elements, etc. Memory media may also include other types of nontransitory memory or combinations thereof. Furthermore, memory media may reside in a first computer system executing a program, or may reside in a different second computer system connected to the first computer system via a network such as the Internet. In the latter example, the second computer system may provide program instructions to the first computer for execution. The term "memory media" may include two or more memory media residing in different locations in different computer systems connected via, for example, a network. Memory media may store program instructions (e.g., embodied in a computer program) that can be executed by one or more processors.

[0023] Carrier media—such as memory media as described above, and physical transmission media such as buses, networks, and / or other physical transmission media that transmit signals such as electrical signals, electromagnetic signals, or digital signals.

[0024] Programmable hardware elements encompass a variety of hardware devices, which consist of multiple programmable functional blocks connected via programmable interconnects. Examples include FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), FPOAs (Field-Programmable Object Arrays), and CPLDs (Complex PLDs). Programmable functional blocks can range from fine-grained (combinational logic or lookup tables) to coarse-grained (arithmetic logic units or processor cores). Programmable hardware elements may also be referred to as "configurable logic units."

[0025] Computer system (or computer) — any of the various types of computing or processing systems, including personal computer systems (PCs), mainframe computer systems, workstations, network appliances, internet-connected appliances, personal digital assistants (PDAs), television systems, grid computing systems, or other devices or combinations thereof. In general, the term "computer system" can be broadly defined to encompass any device (or combination of devices) having at least one processor that executes instructions from a memory medium.

[0026] User equipment (UE) (or “UE device”) — any of various types of computer system devices that are mobile or portable and perform wireless communication. Examples of UE devices include mobile phones or smartphones (e.g., iPhone). ™Based on Android ™ Telephones), portable gaming devices (e.g., Nintendo DS) ™ PlayStation Portable ™ Gameboy Advance ™ iPhone ™ ), laptops, wearable devices (e.g., smartwatches, smart glasses), PDAs, portable internet devices, music players, data storage devices, other handheld devices, unmanned aerial vehicles (UAVs) (e.g., drones), UAV controllers (UACs), etc. Generally speaking, the term "UE" or "UE device" can be broadly defined to encompass any electronic device, computing device, and / or telecommunications device (or combination of devices) that is easily transportable by the user and capable of wireless communication.

[0027] Base station—The term “base station” has the full range of its common meaning and includes at least a wireless communication station that is installed in a fixed location and is used for communication as part of a wireless telephone system or radio system.

[0028] A processing element (or processor) is a component or combination of components capable of performing the functions of a device such as a user equipment or cellular network device. A processing element may include, for example: a processor and associated memory, portions or circuitry of individual processor cores, an entire processor core, a processor array, circuitry such as an ASIC (Application-Specific Integrated Circuit), programmable hardware components such as a Field-Programmable Gate Array (FPGA), and any combination thereof.

[0029] A channel is a medium used to transmit information from a transmitter to a receiver. It should be noted that because the characteristics of the term "channel" can vary depending on the wireless protocol, the term "channel" as used herein can be considered to be used in a standard manner consistent with the type of device to which the term is referenced. In some standards, channel bandwidth can be variable (e.g., depending on device capabilities, frequency band conditions, etc.). For example, LTE can support scalable channel bandwidths from 1.4 MHz to 20 MHz. 5G NR can support scalable channel bandwidths from 5 MHz to 100 MHz in Frequency Range 1 (FR1) and up to 400 MHz in FR2. In other radio access technologies, WLAN channels can be 22 MHz wide, while Bluetooth channels can be 1 MHz wide. Other protocols and standards may include different definitions of channels. Furthermore, some standards may define and use multiple types of channels, for example, different channels for uplink or downlink and / or different channels for different purposes such as data, control information, etc.

[0030] Frequency band—The term “frequency band” has the full range of its general meaning and includes at least a segment of spectrum (e.g., radio frequency spectrum) in which a channel is used or reserved for the same purpose.

[0031] Automatic—means that an action or operation is performed by a computer system (e.g., software executed by the computer system) or device (e.g., circuits, programmable hardware elements, ASICs, etc.) without requiring direct specification or execution of the action or operation through user input. Therefore, the term "automatically" is the opposite of an operation performed or specified manually by a user, where the user provides input to directly perform the operation. An automatic process can be initiated by user-provided input, but the subsequent actions performed "automatically" are not specified by the user; that is, they are not performed "manually," where the user specifies each action to be performed. For example, a user filling out a form by selecting each field and providing input specifying information (e.g., by typing information, selecting a checkbox, radio selection, etc.) is considered manually filling out the form, even though the computer system will update the form in response to the user's actions. The form can be automatically filled out by a computer system, where the computer system (e.g., software executed on the computer system) analyzes the fields of the form and fills out the form without any user input specifying answers for the fields. As indicated above, the user can invoke the automatic filling of the form but does not participate in the actual filling of the form (e.g., the user does not manually specify answers for the fields, but they are completed automatically). This manual provides various examples of operations that are automatically performed in response to actions taken by the user.

[0032] Approximately—means a value close to the correct or precise value. For example, approximately could mean a value within 1% to 10% of the precise (or expected) value. However, it should be noted that the actual threshold (or tolerance) can be application-dependent. For example, in some implementations, “approximately” may mean within 0.1% of a specified or expected value, while in various other implementations, the threshold may be, for example, 2%, 3%, 5%, etc., depending on the expectations or settings of the specific application.

[0033] Concurrency refers to the parallel execution or implementation of tasks, processes, or programs in a manner that at least partially overlaps. For example, concurrency can be achieved using “strong” or strict parallelism, where tasks are executed in parallel (at least partially) on corresponding computing elements; or using “weak parallelism,” where tasks are executed in an interleaved manner (e.g., by time multiplexing of execution threads).

[0034] The legacy system—the 3rd Generation Partnership Project (3GPP)—develops specifications that define 3GPP technologies. 3GPP specifications cover cellular telecommunications technologies, including radio access, core network, and service capabilities, providing a complete system description for mobile telecommunications. 3GPP uses a system of parallel “releases,” which provide developers with a stable platform for implementing features at a given point and then allow for the addition of new functionality in subsequent releases. Release 17 was released in 2022. At the time of this disclosure, Release 18 (Rel-18) is due for release on June 22, 2024, as its specifications are largely finalized. Therefore, specific implementations and concepts compatible with Rel-18 or earlier releases are sometimes referred to herein as “legacy releases.” One or more implementations of this disclosure may be adopted in future releases (e.g., Release 19).

[0035] Various components can be described as being "configured" to perform one or more tasks. In this context, "configured" is a broad expression generally meaning "having a structure" that performs one or more tasks during operation. Therefore, a component can be configured to perform a task even when it is not currently performing one (e.g., a set of electrical conductors can be configured to electrically connect one module to another, even when the two modules are not connected). In some contexts, "configured" can be a broad expression generally meaning "having a circuit" that performs one or more tasks during operation. Therefore, a component can be configured to perform a task even when it is not currently switched on. Typically, the circuit forming the structure corresponding to "configured" can include hardware circuitry.

[0036] For ease of description, various components may be described as performing one or more tasks. Such descriptions should be interpreted as including the phrase "configured to". Statements describing a component as configured to perform one or more tasks are explicitly intended not to invoke the interpretation of 35 USC § 112(f) for that component.

[0037] The example implementation can be further understood by referring to the following description and related figures, wherein the same elements have the same reference numerals. The example implementation relates to implementing network-side AI-based model inference verification.

[0038] Example implementations are described in relation to communication between a base station and a user equipment (UE). However, references to the base station or UE are provided for illustrative purposes only. The example implementations can be used with any electronic component that can establish a connection to the network and is configured with hardware, software, and / or firmware to support network-side AI-based model inference verification. Therefore, the base station or UE described herein is used to represent any suitable type of electronic component.

[0039] An example implementation is also described regarding a fifth-generation (5G) new radio (NR) network that can be configured to control UE-side performance monitoring. However, the reference to the 5G NR network is provided for illustrative purposes only. The example implementation can be used with any suitable type of network.

[0040] As described, the mechanism of the illustrated implementation provides a user equipment (UE) including one or more processors coupled to memory, which can be configured to: encode a UE capability report for transmission to a base station; determine a confidence level based on the predicted RLF using one or more AI-based models for predicting radio link failures (RLFs); compare the predicted RLF confidence level with a confidence threshold; and encode an RLF prediction report indicating that the predicted RLF confidence level is greater than the confidence threshold for transmission to the base station.

[0041] Throughout this specification, various information elements (IEs) are referred to by specific names. It should be understood that these names are merely examples, and the IEs carrying the information referenced throughout this specification may be referenced by various entities under other names.

[0042] Figure 1A and Figure 1B Communication system Figure 1A A simplified example wireless communication system according to some implementation schemes is illustrated. It should be noted that... Figure 1A The system described herein is merely one example of a possible system, and the features of this disclosure can be implemented in any of a variety of systems as needed.

[0043] As shown in the figure, the example wireless communication system includes a base station 102A, which communicates with one or more user equipments 106A, 106B to 106N, etc., via a transmission medium. Each user equipment may be referred to herein as a "user equipment" (UE). Therefore, user equipment 106 is referred to as a UE or UE device.

[0044] Base station (BS) 102A may be a transceiver base station (BTS) or a cell site (“cellular base station”), and may include hardware that enables wireless communication with UE 106A to UE 106N.

[0045] The communication area (or coverage area) of a base station may be referred to as a "cell". Base station 102A and UE 106 can be configured to communicate via a transmission medium using any of a variety of Radio Access Technologies (RATs), also known as wireless communication technologies or telecommunications standards, such as GSM, UMTS (associated with air interfaces such as WCDMA or TD-SCDMA), LTE, LTE-Advanced (LTE-A), 5G New Radio (5G NR), HSPA, 3GPP2 CDMA2000 (e.g., 1xRTT, 1xEV-DO, HRPD, eHRPD), etc. Note that if base station 102A is implemented in the context of LTE (also known as Evolved Universal Terrestrial Radio Access Network (E-UTRAN), its alternative location may be referred to as an "eNodeB" or "eNB". Note that if base station 102A is implemented in the context of 5G NR, its alternative location may be referred to as a "gNodeB" or "base station".

[0046] As shown in the figure, base station 102A can also be configured to communicate with network 100 (e.g., in various possibilities, the core network of a cellular service provider, telecommunications networks such as the Public Switched Telephone Network (PSTN), and / or the Internet). Therefore, base station 102A facilitates communication between user equipments and / or between user equipments and network 100. Specifically, cellular base station 102A can provide UE 106 with various telecommunications capabilities, such as voice, SMS, and / or data services.

[0047] Base station 102A and other similar base stations (such as base stations 102B, ..., 102N) operating according to the same or different cellular communication standards can therefore be provided as a network of cells that can provide continuous or nearly continuous overlapping services to UE 106A-106N and similar devices over a geographical area via one or more cellular communication standards.

[0048] Therefore, although base station 102A can act as such Figure 1A The illustrated UE 106A-N is a "serving cell," but each UE 106 may also be able to receive signals (and possibly within its communication range) from one or more other cells (which may be provided by base stations 102B-N and / or any other base stations), which may be referred to as "neighboring cells." Such cells may also facilitate communication between user equipments and / or between user equipments and network 100. These cells may include "macro" cells, "micro" cells, "pecimen" cells, and / or any other cells of various other granularities providing a service area size. For example, Figure 1A The illustrated base station 102A-B could be a macro cell, while base station 102N could be a micro cell. Other configurations are also possible.

[0049] In some implementations, base station 102A may be a next-generation base station, such as a 5G New Radio (5G NR) base station or "base station". In some implementations, the base station may be connected to a legacy evolved packet core (EPC) network and / or to an NR core (NRC) network. Furthermore, the base station cell may include one or more transition and receive points (TRPs). Additionally, a UE capable of operating according to 5G NR may be connected to one or more TRPs within one or more base stations.

[0050] It should be noted that UE 106 may be able to communicate using multiple wireless communication standards. For example, UE 106 may be configured to communicate using wireless networking (e.g., Wi-Fi) and / or peer-to-peer wireless communication protocols (e.g., Bluetooth, Wi-Fi peer-to-peer, etc.) other than at least one cellular communication protocol (e.g., GSM, UMTS (associated with, for example, WCDMA or TD-SCDMA air interfaces), LTE, LTE-A, 5G NR, HSPA, 3GPP2 CDMA2000 (e.g., 1xRTT, 1xEV-DO, HRPD, eHRPD, etc.)). If desired, UE 106 may also be configured, or alternatively, to communicate using one or more Global Navigation Satellite Systems (GNSS, such as GPS or GLONASS), one or more mobile television broadcasting standards (e.g., ATSC-M / H or DVB-H) and / or any other wireless communication protocol. Other combinations of wireless communication standards (including more than two wireless communication standards) are also possible.

[0051] Figure 1B User equipment 106 (e.g., one of devices 106A to 106N) communicating with base station 102 and access point 112 according to some embodiments is illustrated. UE 106 can be a device with cellular and non-cellular communication capabilities (e.g., Bluetooth, Wi-Fi, etc.), such as a mobile phone, handheld device, computer or tablet computer, or virtually any type of wireless device.

[0052] UE 106 may include a processor configured to execute program instructions stored in memory. UE 106 may execute any method implementation of the method implementations described herein by executing such stored instructions. Alternatively or additionally, UE 106 may include programmable hardware elements, such as a field-programmable gate array (FPGA) configured to perform any of the method implementations described herein or any portion thereof.

[0053] UE 106 may include one or more antennas for communicating using one or more wireless communication protocols or technologies. In some embodiments, UE 106 may be configured to communicate using, for example, CDMA2000 (1xRTT / 1xEV-DO / HRPD / eHRPD), LTE / Advanced LTE, or 5G NR using a single shared radio component and / or GSM, LTE, Advanced LTE, or 5G NR using a single shared radio component. The shared radio component may be coupled to a single antenna or to multiple antennas (e.g., for MIMO) for performing wireless communication. Generally, the radio component may include any combination of baseband processor, analog RF signal processing circuitry (e.g., including filters, mixers, oscillators, amplifiers, etc.) or digital processing circuitry (e.g., for digital modulation and other digital processing). Similarly, the radio component may use the aforementioned hardware to implement one or more receive chains and transmit chains. For example, UE 106 may share one or more portions of the receive chain and / or transmit chain among multiple wireless communication technologies (such as those discussed above).

[0054] In some implementations, UE 106 may include independent transmit and / or receive chains (e.g., including independent antennas and other radio components) for each wireless communication protocol configured to communicate therewith. As another possibility, UE 106 may include one or more radio components shared among multiple wireless communication protocols, as well as one or more radio components uniquely used by a single wireless communication protocol. For example, UE 106 may include shared radio components for communicating using LTE or 5G NR (or LTE or 1xRTT, or LTE or GSM), and separate radio components for communicating using each of Wi-Fi and Bluetooth. Other configurations are also possible.

[0055] Figure 2 Block diagram of a base station Figure 2 Example block diagrams of base station 102 according to some implementation schemes are shown. It should be noted that... Figure 2 The base station shown is merely one example of a possible base station. As illustrated, base station 102 may include processor 204, which executes program instructions for base station 102. Processor 204 may also be coupled to memory management unit (MMU) 240, which may be configured to receive addresses from processor 204 and translate those addresses into locations in memory (e.g., memory 260 and read-only memory (ROM) 250) or into other circuitry or devices.

[0056] Base station 102 may include at least one network port 270. Network port 270 may be configured to couple to a telephone network and provide access rights as described above in Figures 1a, 1b, and... Figure 2 The telephone network described herein includes multiple devices, such as UE device 106.

[0057] Network port 270 (or an additional network port) may also be configured, or alternatively configured, to couple to a cellular network, such as the core network of a cellular service provider. The core network may provide mobility-related services and / or other services to multiple devices, such as UE device 106. In some cases, network port 270 may be coupled to a telephone network via the core network, and / or the core network may provide a telephone network (e.g., in other UE devices served by a cellular service provider).

[0058] In some implementations, base station 102 may be a next-generation base station, such as a 5G New Radio (5G NR) base station, or simply a "base station". In such implementations, base station 102 may be connected to a legacy evolved packet core (EPC) network and / or to an NR core (NRC) network. Furthermore, base station 102 may be considered a 5G NR cell and may include one or more transition and receive points (TRPs). Additionally, a UE capable of operating according to 5G NR may connect to one or more TRPs within one or more base stations.

[0059] Base station 102 may include at least one antenna 234, and may include multiple antennas. At least one antenna 234 may be configured to operate as a wireless transceiver and may also be configured to communicate with UE device 106 via radio component 230. Antenna 234 communicates with radio component 230 via communication link 232. Communication link 232 may be a receive link, a transmit link, or both. Radio component 230 may be configured to communicate via various wireless communication standards, including but not limited to 5G NR, LTE, LTE-A, GSM, UMTS, CDMA2000, Wi-Fi, etc.

[0060] Base station 102 can be configured to perform wireless communication using multiple wireless communication standards. In some instances, base station 102 may include multiple radio components that enable base station 102 to communicate according to multiple wireless communication technologies. For example, as one possibility, base station 102 may include an LTE radio component for performing communication according to LTE and a 5G NR radio component for performing communication according to 5G NR. In this case, base station 102 may be able to operate as both an LTE base station and a 5G NR base station. As another possibility, base station 102 may include a multimode radio component capable of performing communication according to any of multiple wireless communication technologies (e.g., 5G NR and Wi-Fi, LTE and Wi-Fi, LTE and UMTS, LTE and CDMA2000, UMTS and GSM, etc.).

[0061] As further described herein, BS 102 may include hardware and software components for implementing or supporting specific implementations of the features described herein. The processor 204 of base station 102 may be configured, for example, to implement or support some or all of the methods described herein by executing program instructions stored on a memory medium (e.g., a non-transitory computer-readable memory medium). Alternatively, processor 204 may be configured as a programmable hardware element such as a FPGA (Field-Programmable Gate Array), or as an ASIC (Application-Specific Integrated Circuit), or a combination thereof. Alternatively (or further), in conjunction with one or more of other components 230, 232, 234, 240, 250, 260, 270, the processor 204 of BS 102 may be configured to implement or support some or all of the features described herein.

[0062] Furthermore, as described herein, processor 204 may comprise one or more processing elements. In other words, one or more processing elements may be included in processor 204. Therefore, processor 204 may include one or more integrated circuits (ICs) configured to perform the functions of processor 204. Additionally, each integrated circuit may include circuitry (e.g., a first circuit, a second circuit, etc.) configured to perform the functions of processor 204.

[0063] Furthermore, as described herein, radio component 230 may comprise one or more processing elements. In other words, one or more processing elements may be included in radio component 230. Therefore, radio component 230 may include one or more integrated circuits (ICs) configured to perform the functions of radio component 230. Additionally, each integrated circuit may include circuitry (e.g., a first circuit, a second circuit, etc.) configured to perform the functions of radio component 230.

[0064] Figure 3 Server block diagram Figure 3 Example block diagrams of server 104 according to some implementation schemes are shown. Note that... Figure 3 The server shown is merely one example of a possible server. As illustrated, server 104 may include processor 344 capable of executing program instructions for server 104. Processor 344 may also be coupled to memory management unit (MMU) 374, which may be configured to receive addresses from processor 344 and translate those addresses into locations in memory (e.g., memory 364 and read-only memory (ROM) 354) or into other circuitry or devices.

[0065] Server 104 can be configured to provide network access functionality to multiple devices, such as base station 102 and UE device 106, for example, as further described herein.

[0066] In some implementations, server 104 may be part of a radio access network, such as a 5G New Radio (5G NR) access network. In some implementations, server 104 may be connected to a legacy evolved packet core (EPC) network and / or to an NR core (NRC) network.

[0067] As described herein, server 104 may include hardware and software components for implementing or supporting the implementation of the features described herein. Processor 344 of server 104 may be configured, for example, to implement or support some or all of the methods described herein by executing program instructions stored on a memory medium (e.g., a non-transitory computer-readable storage medium). Alternatively, processor 344 may be configured as a programmable hardware element such as a FPGA (Field-Programmable Gate Array), or as an ASIC (Application-Specific Integrated Circuit), or a combination thereof. Alternatively (or further), in conjunction with one or more of other components 354, 364, and / or 374, processor 344 of server 104 may be configured to implement or support some or all of the features described herein.

[0068] Furthermore, as described herein, processor 344 may comprise one or more processing elements. In other words, one or more processing elements may be included in processor 344. Therefore, processor 344 may include one or more integrated circuits (ICs) configured to perform the functions of processor 344. Additionally, each integrated circuit may include circuitry (e.g., a first circuit, a second circuit, etc.) configured to perform the functions of processor 344.

[0069] Figure 4 User Equipment Block Diagram Figure 4A simplified block diagram of a communication device 106 according to some implementation schemes is shown. Note that... Figure 4 The block diagram of the communication device is merely one example of possible communication devices. According to implementations, communication device 106 may be a user equipment (UE) device, a mobile device or mobile station, a wireless device or wireless station, a desktop computer or computing device, a mobile computing device (e.g., a laptop computer, notebook computer, or portable computing device), a tablet computer, an unmanned aerial vehicle (UAV), a UAV controller (UAC), and / or a combination of devices, as well as other devices. As shown, communication device 106 may include a set of components 400 configured to perform core functions. For example, this set of components may be implemented as a system-on-a-chip (SOC), which may include portions for various purposes. Alternatively, the set of components 400 may be implemented as individual components or groups of components for various purposes. The set of components 400 may be (e.g., communicatively; directly or indirectly) coupled to various other circuitry of communication device 106.

[0070] For example, communication device 106 may include various types of memory (e.g., including NAND flash memory 410), input / output interfaces such as connector I / F 420 (e.g., for connection to a computer system; docking station; charging station; input devices such as microphone, camera, keyboard; output devices such as speaker; etc.), a display 460 that may be integrated with or external to the communication device 106, and cellular communication circuitry 430 such as for 5G NR, LTE, GSM, etc., and short- to medium-range wireless communication circuitry 429 (e.g., Bluetooth). ™ (and WLAN circuitry). In some embodiments, communication device 106 may include wired communication circuitry (not shown), such as, for example, a network interface card for Ethernet.

[0071] Cellular communication circuitry 430 may be coupled (e.g., communicatively; directly or indirectly) to one or more antennas, such as antennas 435 and 436 as shown. Short-to-medium-range wireless communication circuitry 429 may also be coupled (e.g., communicatively; directly or indirectly) to one or more antennas, such as antennas 437 and 438 as shown. Alternatively, short-to-medium-range wireless communication circuitry 429 may be coupled (e.g., communicatively; directly or indirectly) to antennas 435 and 436 in addition to or instead of being coupled to antennas 437 and 438. Short-to-medium-range wireless communication circuitry 429 and / or cellular communication circuitry 430 may include multiple receive chains and / or multiple transmit chains for receiving and / or transmitting multiple spatial streams, such as in a multiple-input multiple-output (MIMO) configuration.

[0072] In some embodiments, as further described below, the cellular communication circuit 430 may include dedicated receive chains for multiple RATs (including and / or coupled to (e.g., communicatively; directly or indirectly) dedicated processors and / or radio components) (e.g., a first receive chain for LTE and a second receive chain for 5G NR). Furthermore, in some embodiments, the cellular communication circuit 430 may include a single transmit chain that can be switched between radio components dedicated to a specific RAT. For example, a first radio component may be dedicated to a first RAT, such as LTE, and may communicate with a dedicated receive chain and a transmit chain shared with additional radio components, such as a second radio component that may be dedicated to a second RAT (e.g., 5G NR) and may communicate with a dedicated receive chain and a shared transmit chain.

[0073] The communication device 106 may also include one or more user interface elements and / or be configured to be used with one or more user interface elements. The user interface elements may include any of a variety of elements, such as a display 460 (which may be a touch screen display), a keyboard (which may be a discrete keyboard or may be implemented as part of a touch screen display), a mouse, a microphone and / or a speaker, one or more cameras, one or more buttons, and / or any of a variety of other elements capable of providing information to the user and / or receiving or interpreting user input.

[0074] The communication device 106 may also include one or more smart cards 445 with SIM (Subscriber Identity Module) functionality, such as one or more UICC (Universal Integrated Circuit Card) cards 445. It should be noted that the term "SIM" or "SIM entity" is intended to include any of various types of SIM implementations or SIM functions, such as one or more UICC cards 445, one or more eUICCs, one or more eSIMs, removable or embedded, etc. In some embodiments, the UE 106 may include at least two SIMs. Each SIM may execute one or more SIM applications and / or otherwise implement SIM functionality. Thus, each SIM may be a single smart card that can be embedded, for example, soldered to a circuit board in the UE 106, or each SIM 410 may be implemented as a removable smart card. Therefore, a SIM may be one or more removable smart cards (such as UICC cards, sometimes referred to as "SIM cards"), and / or SIM 410 may be one or more embedded cards (such as embedded UICCs (eUICCs), sometimes referred to as "eSIMs" or "eSIM cards"). In some implementations (such as when the SIM includes an eUICC), one or more SIMs within the SIM can implement embedded SIM (eSIM) functionality; in such implementations, a single SIM within the SIM can execute multiple SIM applications. Each SIM may include components such as a processor and / or memory; instructions for performing SIM / eSIM functionality may be stored in memory and executed by the processor. In some implementations, UE 106 may include, as needed, a combination of removable smart cards and fixed / non-removable smart cards (such as one or more eUICC cards implementing eSIM functionality). For example, UE 106 may include two embedded SIMs, two removable SIMs, or a combination of one embedded SIM and one removable SIM. Various other SIM configurations are also envisioned.

[0075] As described above, in some implementations, UE 106 may include two or more SIMs. Including two or more SIMs in UE 106 allows UE 106 to support two different phone numbers and allows UE 106 to communicate on two or more corresponding networks. For example, the first SIM may support a first RAT (such as LTE), and the second SIM 106 may support a second RAT (such as 5G NR). Other specific implementations and RATs are also possible. In some implementations, when UE 106 includes two SIMs, UE 106 may support Dual SIM Dual Standby (DSDA) functionality. DSDA functionality allows UE 106 to connect to two networks simultaneously (and use two different RATs), or allows two connections supported by two different SIMs using the same or different RATs to be maintained simultaneously on the same or different networks. DSDA functionality also allows UE 106 to receive voice calls or data traffic simultaneously on either phone number. In some implementations, voice calls may be packet-switched communications. In other words, voice calls can be received using LTE-based Voice (VoLTE) technology and / or NR-based Voice (VoNR) technology. In some implementations, UE 106 may support Dual SIM Dual Standby (DSDS) functionality. DSDS functionality allows either of the two SIMs in UE 106 to remain in standby while awaiting a voice call and / or data connection. In DSDS, when a call / data connection is established on one SIM, the other SIM is no longer active. In some implementations, DSDx functionality (DSDA or DSDS functionality) can be implemented using a single SIM (e.g., eUICC) that performs multiple SIM applications for different carriers and / or RATs.

[0076] As shown in the figure, the SOC 400 may include a processor 402 and display circuitry 404. The processor executes program instructions for the communication device 106, and the display circuitry performs graphics processing and provides display signals to the display 460. The processor 402 may also be coupled to a memory management unit (MMU) 440 (which may be configured to receive addresses from the processor 402 and translate those addresses into locations in memory (e.g., memory 406, read-only memory (ROM) 450, NAND flash memory 410)) and / or coupled to other circuitry or devices (such as display circuitry 404, short-to-medium range wireless communication circuitry 429, cellular communication circuitry 430, connector I / F 420, and / or display 460). The MMU 440 may be configured to perform memory protection and page table translation or setup. In some embodiments, the MMU 440 may be included as part of the processor 402.

[0077] As described herein, communication device 106 may include hardware and software components for implementing the features described above to communicate a scheduling profile for power saving to the network. For example, processor 402 of communication device 106 may be configured to implement some or all of the features described herein by executing program instructions stored on a memory medium (e.g., a non-transitory computer-readable storage medium). Alternatively (or in addition), processor 402 may be configured as a programmable hardware element such as a FPGA (Field-Programmable Gate Array) or as an ASIC (Application-Specific Integrated Circuit). Alternatively (or in addition), in conjunction with one or more of other components 400, 404, 406, 410, 420, 429, 430, 440, 445, 450, 460, processor 402 of communication device 106 may be configured to implement some or all of the features described herein.

[0078] Furthermore, as described herein, processor 402 may include one or more processing elements. Therefore, processor 402 may include one or more integrated circuits (ICs) configured to perform the functions of processor 402. Additionally, each integrated circuit may include circuitry (e.g., a first circuit, a second circuit, etc.) configured to perform the functions of processor 402.

[0079] Additionally, as described herein, the cellular communication circuit 430 and the short-to-medium-range wireless communication circuit 429 may each include one or more processing elements. In other words, one or more processing elements may be included in the cellular communication circuit 430, and similarly, one or more processing elements may be included in the short-to-medium-range wireless communication circuit 429. Therefore, the cellular communication circuit 430 may include one or more integrated circuits (ICs) configured to perform the functions of the cellular communication circuit 430. Furthermore, each integrated circuit may include circuitry (e.g., a first circuit, a second circuit, etc.) configured to perform the functions of the cellular communication circuit 430. Similarly, the short-to-medium-range wireless communication circuit 429 may include one or more ICs configured to perform the functions of the short-to-medium-range wireless communication circuit 429. Furthermore, each integrated circuit may include circuitry (e.g., a first circuit, a second circuit, etc.) configured to perform the functions of the short-to-medium-range wireless communication circuit 429.

[0080] Figure 5 Block diagram of cellular communication circuit Figure 5 Exemplary simplified block diagrams of cellular communication circuits according to some implementation schemes are shown. It should be noted that... Figure 5The block diagram of the cellular communication circuit is merely one example of a possible cellular communication circuit. According to the implementation, the cellular communication circuit 530 (which may be the cellular communication circuit 430) may be included in a communication device such as the communication device 106 described above. As noted above, among other devices, the communication device 106 may be a user equipment (UE) device, a mobile device or mobile station, a wireless device or wireless station, a desktop computer or computing device, a mobile computing device (e.g., a laptop computer, notebook computer, or portable computing device), a tablet computer, and / or a combination of these devices.

[0081] The cellular communication circuit 530 may (e.g., communicatively; directly or indirectly) be coupled to one or more antennas, such as ( Figure 4 Antennas 435a-b and 436 are shown in the diagram. In some embodiments, cellular communication circuitry 530 may include dedicated receive chains for various RATs (including and / or coupled to (e.g., communicatively ground; directly or indirectly) dedicated processors and / or radio components) (e.g., a first receive chain for LTE and a second receive chain for 5G NR). For example, as... Figure 5 As shown, the cellular communication circuit 530 may include a modem 510 and a modem 520. The modem 510 may be configured for communication according to a first RAT (e.g., such as LTE or LTE-A), and the modem 520 may be configured for communication according to a second RAT (e.g., such as 5G NR).

[0082] As shown, modem 510 may include one or more processors 512 and memory 516 communicating with processors 512. Modem 510 may communicate with radio frequency (RF) front end 535. RF front end 535 may include circuitry for transmitting and receiving radio signals. For example, RF front end 535 may include receiver circuitry (RX) 532 and transmitter circuitry (TX) 534. In some embodiments, receiver circuitry 532 may communicate with downlink (DL) front end 550, which may include circuitry for receiving radio signals via antenna 335a.

[0083] Similarly, modem 520 may include one or more processors 522 and memory 526 communicating with processor 522. Modem 520 may communicate with RF front end 540. RF front end 540 may include circuitry for transmitting and receiving radio signals. For example, RF front end 540 may include receiving circuitry 542 and transmitting circuitry 544. In some embodiments, receiving circuitry 542 may communicate with DL front end 560, which may include circuitry for receiving radio signals via antenna 335b.

[0084] In some implementations, switch 570 may couple transmitting circuitry 534 to uplink (UL) front-end 572. Additionally, switch 570 may couple transmitting circuitry 544 to UL front-end 572. UL front-end 572 may include circuitry for transmitting radio signals via antenna 336. Therefore, when cellular communication circuitry 530 receives an instruction to transmit according to a first RAT (e.g., supported by modem 510), switch 570 may be switched to a first state allowing modem 510 to transmit signals according to the first RAT (e.g., via a transmission chain including transmitting circuitry 534 and UL front-end 572). Similarly, when cellular communication circuitry 530 receives an instruction to transmit according to a second RAT (e.g., supported by modem 520), switch 570 may be switched to a second state allowing modem 520 to transmit signals according to the second RAT (e.g., via a transmission chain including transmitting circuitry 544 and UL front-end 572).

[0085] As described herein, modem 510 may include hardware and software components for implementing the features described above or for UL data used in time-division multiplexing NSANR operation, as well as various other techniques described herein. For example, processor 512 may be configured to implement some or all of the features described herein by executing program instructions stored on a memory medium (e.g., a non-transitory computer-readable storage medium). Alternatively (or in addition), processor 512 may be configured as a programmable hardware element such as a FPGA (Field-Programmable Gate Array) or as an ASIC (Application-Specific Integrated Circuit). Alternatively (or in addition), processor 512 may be configured to implement some or all of the features described herein by combining one or more of other components 530, 532, 534, 535, 550, 570, 572, 335a, 335b, and 336.

[0086] Furthermore, as described herein, processor 512 may include one or more processing elements. Therefore, processor 512 may include one or more integrated circuits (ICs) configured to perform the functions of processor 512. Additionally, each integrated circuit may include circuitry (e.g., a first circuit, a second circuit, etc.) configured to perform the functions of processor 512.

[0087] For example, by executing program instructions stored on a memory medium (e.g., a non-transitory computer-readable memory medium), processor 522 may be configured to implement some or all of the features described herein. Alternatively (or in addition), processor 522 may be configured as a programmable hardware element such as a FPGA (Field-Programmable Gate Array) or as an ASIC (Application-Specific Integrated Circuit). Alternatively (or in addition), in conjunction with one or more of other components 540, 542, 544, 550, 570, 572, 335a, 335b, and 336, processor 522 may be configured to implement some or all of the features described herein.

[0088] Furthermore, as described herein, processor 522 may include one or more processing elements. Therefore, processor 522 may include one or more integrated circuits (ICs) configured to perform the functions of processor 522. Additionally, each integrated circuit may include circuitry (e.g., a first circuit, a second circuit, etc.) configured to perform the functions of processor 522.

[0089] Figure 6 Block diagram of the baseband processor architecture for UE Figure 6 Example components of device 600 according to some implementation schemes are illustrated. It should be noted that... Figure 6 The device described is merely one example of a possible system, and the features of this disclosure can be implemented in any type of UE as needed.

[0090] In some embodiments, device 600 may include application circuitry 602, baseband circuitry 604, radio frequency (RF) circuitry 606, front-end module (FEM) circuitry 608, one or more antennas 610, and power management circuitry (PMC) 612 (at least coupled together as shown). Components of the illustrated device 600 may be included in UE 106 or RAN node 102A. In some embodiments, device 600 may include fewer components (e.g., the RAN node may not utilize application circuitry 602, but instead include a processor / controller to process IP data received from the EPC). In some embodiments, device 600 may include additional components such as, for example, memory / storage devices, displays, cameras, sensors, or input / output (I / O) interfaces. In other embodiments, the components described below may be included in more than one device (e.g., the circuitry may be individually included in more than one device for a cloud-RAN (C-RAN) specific implementation).

[0091] Application circuitry 602 may include one or more application processors. For example, application circuitry 602 may include circuitry such as, but not limited to, one or more single-core or multi-core processors. The one or more processors may include any combination of general-purpose processors and special-purpose processors (e.g., graphics processors, application processors, etc.). These processors may be coupled to or may include memory / storage devices and may be configured to execute instructions stored in the memory / storage device to enable various applications or operating systems to run on device 600. In some embodiments, the processor of application circuitry 602 may process IP data packets received from the EPC.

[0092] Baseband circuitry 604 may include circuitry such as, but not limited to, one or more single-core or multi-core processors. Baseband circuitry 604 may include one or more baseband processors or control logic components to process baseband signals received from the receive signal path of RF circuitry 606 and generate baseband signals for the transmit signal path of RF circuitry 606. Baseband processing circuitry 604 may interact with application circuitry 602 to generate and process baseband signals and control the operation of RF circuitry 606. For example, in some embodiments, baseband circuitry 604 may include a third-generation (3G) baseband processor 604A, a fourth-generation (4G) baseband processor 604B, a fifth-generation (5G) baseband processor 604C, or other existing, under development, or future generations of baseband processors 604D (e.g., second-generation (2G), sixth-generation (6G), etc.). Baseband circuitry 604 (e.g., one or more of baseband processors 604A-D) may process various radio control functions that enable communication with one or more radio networks via RF circuitry 606. In other embodiments, some or all of the functions of the baseband processors 604A-D may be included in modules stored in memory 604G and executed via a central processing unit (CPU) 604E. Radio control functions may include, but are not limited to, signal modulation / demodulation, encoding / decoding, and radio frequency shifting. In some embodiments, the modulation / demodulation circuitry of the baseband circuitry 604 may include Fast Fourier Transform (FFT), pre-decoding, or constellation mapping / demapping functionality. In some embodiments, the encoding / decoding circuitry of the baseband circuitry 604 may include convolution, tail-biting convolution, turbo, Viterbi, or low-density parity-check (LDPC) encoder / decoder functionality. Implementations of the modulation / demodulation and encoder / decoder functions are not limited to these examples, and other suitable functions may be included in other embodiments.

[0093] In some embodiments, the baseband circuitry 604 may include one or more audio digital signal processors (“DSPs”) 604F. The audio DSP 604F may include elements for compression / decompression and echo cancellation, and in other embodiments may include other suitable processing elements. In some embodiments, components of the baseband circuitry may be suitably combined in a single chip, a single chipset, or disposed on the same circuit board. In some embodiments, some or all of the components of the baseband circuitry 604 and the application circuitry 602 may be implemented together, for example, on a system-on-a-chip (SOC).

[0094] In some implementations, baseband circuit 604 can provide communication compatible with one or more radio technologies. For example, in some implementations, baseband circuit 604 can support communication with the Evolved Universal Terrestrial Radio Access Network (EUTRAN) or other Wireless Metropolitan Area Networks (WMAN), Wireless Local Area Networks (WLAN), or Wireless Personal Area Networks (WPAN). Implementations in which baseband circuit 604 is configured to support radio communication with more than one radio protocol may be referred to as multimode baseband circuits.

[0095] RF circuit 606 enables communication with a wireless network via a non-solid medium using modulated electromagnetic radiation. In various embodiments, RF circuit 606 may include switches, filters, amplifiers, etc., to facilitate communication with the wireless network. RF circuit 606 may include a receive signal path that includes circuitry for down-converting the RF signal received from FEM circuit 608 and providing a baseband signal to baseband circuit 604. RF circuit 606 may also include a transmit signal path that includes circuitry for up-converting the baseband signal provided by baseband circuit 604 and providing an RF output signal for transmission to FEM circuit 608.

[0096] In some embodiments, the receive signal path of RF circuit 606 may include mixer circuit 606a, amplifier circuit 606b, and filter circuit 606c. In some embodiments, the transmit signal path of RF circuit 606 may include filter circuit 606c and mixer circuit 606a. RF circuit 606 may also include synthesizer circuit 606d for synthesizing frequencies used by mixer circuit 606a in both the receive and transmit signal paths. In some embodiments, mixer circuit 606a in the receive signal path may be configured to down-convert the RF signal received from FEM circuit 608 based on the synthesized frequency provided by synthesizer circuit 606d. Amplifier circuit 606b may be configured to amplify the down-converted signal, and filter circuit 606c may be a low-pass filter (LPF) or band-pass filter (BPF) configured to remove unwanted signals from the down-converted signal to generate an output baseband signal. The output baseband signal may be provided to baseband circuit 604 for further processing. In some implementations, these output baseband signals may be zero-frequency baseband signals, but this is not necessary. In some implementations, the mixer circuit 606a in the receiving signal path may include a passive mixer, but the scope of the implementations is not limited in this respect.

[0097] In some implementations, the mixer circuit 606a of the transmit signal path may be configured to up-convert the input baseband signal based on the synthesis frequency provided by the synthesizer circuit 606d to generate an RF output signal for the FEM circuit 608. The baseband signal may be provided by the baseband circuit 604 and may be filtered by the filter circuit 606c.

[0098] In some embodiments, the mixer circuit 606a for the receive signal path and the mixer circuit 606a for the transmit signal path may include two or more mixers and may be arranged for quadrature downconversion and quadrature upconversion, respectively. In some embodiments, the mixer circuit 606a for the receive signal path and the mixer circuit 606a for the transmit signal path may include two or more mixers and may be arranged for image rejection (e.g., Hartley image rejection). In some embodiments, the mixer circuit 606a for the receive signal path and the mixer circuit 606a for the transmit signal path may be arranged for direct downconversion and direct upconversion, respectively. In some embodiments, the mixer circuit 606a for the receive signal path and the mixer circuit 606a for the transmit signal path may be configured for superheterodyne operation.

[0099] In some embodiments, the output baseband signal and the input baseband signal may be analog baseband signals, but the scope of the embodiments is not limited in this respect. In some alternative embodiments, the output baseband signal and the input baseband signal may be digital baseband signals. In these alternative embodiments, RF circuit 606 may include analog-to-digital converter (ADC) and digital-to-analog converter (DAC) circuitry, and baseband circuit 604 may include a digital baseband interface for communicating with RF circuit 606.

[0100] In some dual-mode implementations, separate radio IC circuits may be provided to process signals for each spectrum, but the scope of the implementation is not limited in this respect.

[0101] In some implementations, synthesizer circuit 606d may be a fractional-N synthesizer or a fractional-N / N+1 synthesizer, but the scope of implementations is not limited in this respect, as other types of frequency synthesizers may also be suitable. For example, synthesizer circuit 606d may be a Δ-∑ synthesizer, a frequency multiplier, or a synthesizer including a phase-locked loop with a frequency divider.

[0102] Synthesizer circuit 606d can be configured to synthesize an output frequency based on a frequency input and a divider control input for use by mixer circuit 606a of RF circuit 606. In some embodiments, synthesizer circuit 606d may be a fractional N / N+1 synthesizer.

[0103] In some implementations, the frequency input may be provided by a voltage-controlled oscillator (VCO), but this is not necessary. The divider control input may be provided by the baseband circuitry 604 or the application processor 602 according to the desired output frequency. In some implementations, the divider control input (e.g., N) may be determined from a lookup table based on the channel indicated by the application processor 602.

[0104] The synthesizer circuit 606d of the RF circuit 606 may include a frequency divider, a delay-locked loop (DLL), a multiplexer, and a phase accumulator. In some embodiments, the frequency divider may be a dual-mode divider (DMD), and the phase accumulator may be a digital phase accumulator (DPA). In some embodiments, the DMD may be configured to divide the input signal by N or N+1 (e.g., based on carry) to provide a fractional division ratio. In some example embodiments, the DLL may include a cascaded, tunable delay element, a phase detector, a charge pump, and a set of D-type flip-flops. In these embodiments, the delay elements may be configured to divide the VCO cycle into Nd equal phase groups, where Nd is the number of delay elements in the delay line. Thus, the DLL provides negative feedback to help ensure that the total delay through the delay line is one VCO cycle.

[0105] In some embodiments, synthesizer circuitry 606d may be configured to generate a carrier frequency as the output frequency, while in other embodiments, the output frequency may be a multiple of the carrier frequency (e.g., twice the carrier frequency, four times the carrier frequency) and used in conjunction with quadrature generator and frequency divider circuitry to generate multiple signals having multiple different phases relative to each other at the carrier frequency. In some embodiments, the output frequency may be the LO frequency (fLO). In some embodiments, RF circuitry 606 may include an IQ / polarity converter.

[0106] FEM circuit 608 may include a receive signal path, which may include circuitry configured to operate on RF signals received from one or more antennas 610, amplify the received signals, and provide an amplified version of the received signals to RF circuit 606 for further processing. FEM circuit 608 may also include a transmit signal path, which may include circuitry configured to amplify transmit signals provided by RF circuit 606 for transmission by one or more of the one or more antennas 610. In various embodiments, amplification via the transmit or receive signal path may be performed only in RF circuit 606, only in FEM 608, or in both RF circuit 606 and FEM 608.

[0107] In some embodiments, FEM circuit 608 may include a TX / RX switch for switching between transmit and receive mode operation. The FEM circuit may include a receive signal path and a transmit signal path. The receive signal path of the FEM circuit may include an LNA for amplifying the received RF signal and providing the amplified received RF signal as an output (e.g., provided to RF circuit 606). The transmit signal path of FEM circuit 608 may include a power amplifier (PA) for amplifying (e.g., provided by RF circuit 606) the input RF signal; and one or more filters for generating an RF signal for subsequent transmission (e.g., through one or more antennas in one or more antennas 610).

[0108] In some implementations, the PMC 612 manages the power supplied to the baseband circuitry 604. Specifically, the PMC 612 controls power selection, voltage scaling, battery charging, or DC-DC conversion. The PMC 612 is typically included when the device 600 can be battery powered, for example, when the device is included in a UE. The PMC 612 can improve power conversion efficiency while providing the desired specific implementation size and thermal characteristics.

[0109] Although Figure 6A PMC 612 is shown coupled only to the baseband circuit 604, but in other embodiments, the PMC 612 may be coupled additionally or alternatively to other components such as, but not limited to, the application circuit 602, the RF circuit 606, or the FEM 608, and perform similar power management operations for these other components.

[0110] In some implementations, the PMC 612 may control or otherwise become part of various power-saving mechanisms of the device 600. For example, if the device 600 is in the Radio Resource Control_Connected (RRC_Connected) state, where the device is still connected to the RAN node because it expects to receive traffic immediately, it may enter a state called Discontinuous Receive Mode (DRX) after a period of inactivity. During this state, the device 600 may power down for short intervals, thereby saving power.

[0111] If there is no data traffic activity during the extended period, device 600 can transition to the RRC_Idle state, in which the device disconnects from the network and does not perform operations such as channel quality feedback or handover. Device 600 enters a very low power state and performs paging, in which the device periodically wakes up again to listen to the network, and then powers off again. Device 600 may be unable to receive data in this state, and to receive data, it will transition back to the RRC_Connected state.

[0112] An additional power-saving mode renders the device unusable for a period exceeding the paging interval (from seconds to hours). During this time, the device is completely unconnected to the network and may be completely powered off. Any data transmitted during this period will incur significant latency, which is assumed to be acceptable.

[0113] The processor of application circuit 602 and the processor of baseband circuit 604 can be used to execute elements of one or more instances of the protocol stack. For example, the processor of baseband circuit 604 can be used individually or in combination to perform layer 3, layer 2, or layer 1 functions, while the processor of application circuit 604 can utilize data received from these layers (e.g., packet data) and further perform layer 4 functions (e.g., transmit communication protocol (TCP) and user datagram protocol (UDP) layers). As mentioned herein, layer 3 (L3) may include the Radio Resource Control (RRC) layer, which will be described in further detail below. As mentioned herein, layer 2 (L2) may include the Media Access Control (MAC) layer, the Radio Link Control (RLC) layer, and the Packet Data Convergence Protocol (PDCP) layer, which will be described in further detail below. As mentioned herein, layer 1 (L1) may include the physical (PHY) layer of the UE / RAN node, which will be described in further detail below. Therefore, baseband circuit 604 can be used to encode messages for transmission between the UE and the base station, or to decode messages received between the UE and the base station.

[0114] Figure 7 Block diagram of the baseband circuit interface Figure 7 Example interfaces of baseband circuits according to some implementation schemes are illustrated. Note that... Figure 7 The baseband circuit is merely one example of a possible circuit, and the features of this disclosure can be implemented in any of various systems as needed.

[0115] As discussed above, Figure 6 The baseband circuit 604 may include processors 604A-604E and a memory 604G utilized by the processors. Each of the processors 604A-604E may respectively include a memory interface 704A-704E for transferring / receiving data to / from the memory 604G.

[0116] The baseband circuit 604 may further include: one or more interfaces for communicatively coupling to other circuits / devices, such as a memory interface 712 (e.g., an interface for transferring data to / receiving data from a memory external to the baseband circuit 604); and an application circuit interface 714 (e.g., for...). Figure 6 The application circuit 602 is an interface for transmitting data / receiving data from the application circuit; the RF circuit interface 716 (e.g., for transmitting data to / from the application circuit) Figure 6 RF circuit 606 is an interface for transmitting / receiving data from / from the RF circuit; wireless hardware connectivity interface 718 (e.g., for connecting to / from near field communication (NFC) components, Bluetooth). ® Components (e.g., Bluetooth) ® Low power consumption, Wi-Fi ®Interfaces for transmitting / receiving data from components and other communication components); and power management interface 720 (e.g., an interface for transmitting or receiving power or control signals to / from the PMC 612).

[0117] Figure 8 Control plane protocol stack Figure 8 This is an example of a control plane protocol stack according to some implementation schemes. In this implementation scheme, control plane 800 is shown as a communication protocol stack between UE 106a (or alternatively, UE 106b), RAN node 102A (or alternatively, RAN node 102B) and Mobility Management Entity (MME) 621.

[0118] PHY layer 801 can transmit or receive information used by MAC layer 802 through one or more air interfaces. PHY layer 801 can further perform link adaptive or adaptive modulation and decoding (AMC), power control, cell search (e.g., for initial synchronization and handover purposes), and other measurements used by higher layers (such as RRC layer 805). PHY layer 801 can also further perform: error detection of the transport channel, forward error correction (FEC) decoding / decoding of the transport channel, modulation / demodulation of the physical channel, interleaving, rate matching, mapping to the physical channel, and multiple-input multiple-output (MIMO) antenna processing.

[0119] MAC layer 802 can perform the following: mapping between logical channels and transport channels, multiplexing MAC service data units (SDUs) from one or more logical channels onto a transport block (TB) to be delivered to the PHY via the transport channel, demultiplexing MAC SDUs from a transport block (TB) delivered from the PHY via the transport channel onto one or more logical channels, multiplexing MAC SDUs onto a TB, scheduling information reporting, error correction via Hybrid Automatic Repeat Request (HARQ), and logical channel prioritization.

[0120] RLC layer 803 can operate in multiple modes, including Transparent Mode (TM), Unacknowledged Mode (UM), and Acknowledged Mode (AM). RLC layer 803 can perform the transmission of higher-layer protocol data units (PDUs), error correction for AM data duplication via Automatic Repeat Request (ARQ), and concatenation, segmentation, and reassembly of RLC SDUs for UM and AM data transmission. RLC layer 803 can also re-segment RLC data PDUs used for AM data transmission, reorder RLC data PDUs used for UM and AM data transmission, detect duplicate data used for UM and AM data transmission, discard RLC SDUs used for UM and AM data transmission, detect protocol errors used for AM data transmission, and perform RLC re-establishment.

[0121] PDCP layer 804 can perform header compression and decompression of IP data, maintain PDCP sequence numbers (SNs), perform sequential delivery of upper-layer PDUs during lower-layer re-establishment, eliminate duplication of lower-layer SDUs during lower-layer re-establishment for radio bearers mapped on RLC AM, encrypt and decrypt control plane data, perform integrity protection and integrity verification of control plane data, control timer-based data discarding, and perform security operations (e.g., encryption, decryption, integrity protection, integrity verification, etc.).

[0122] The main services and functions of RRC layer 805 may include broadcasting system information (e.g., included in the Master Information Block (MIB) or System Information Block (SIB) related to the Non-Access Stratum (NAS), broadcasting system information related to the Access Stratum (AS), paging, establishment, maintenance, and release of RRC connections between the UE and E-UTRAN (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release), establishment, configuration, maintenance, and release of point-to-point radio bearers, security functions including key management, mobility between Radio Access Technologies (RATs), and measurement configuration for UE measurement reporting. The MIB and SIB may include one or more Information Elements (IEs), each of which may include a separate data field or data structure.

[0123] UE 601 and RAN node 102A can use the Uu interface (e.g., the LTE-Uu interface) to exchange control plane data via a protocol stack including PHY layer 801, MAC layer 802, RLC layer 803, PDCP layer 804 and RRC layer 805.

[0124] The Non-Access Layer (NAS) protocol 806 forms the highest layer of the control plane between UE 601 and MME 621. NAS protocol 806 supports the mobility and session management processes of UE 601 to establish and maintain IP connectivity between UE 601 and P-GW 623.

[0125] The S1 Application Protocol (S1-AP) layer 815 supports the functions of the S1 interface and includes the Basic Procedure (EP). The EP is the interaction unit between RAN node 102A and CN 100. S1-AP layer services can include two sets: UE-associated services and non-UE-associated services. These services perform functions including, but not limited to: E-UTRAN Radio Access Bearer (E-RAB) management, UE capability indication, mobility, NAS signaling transmission, RAN Information Management (RIM), and configuration transmission.

[0126] The Flow Control Transmission Protocol (SCTP) layer (optionally referred to as the SCTP / IP layer) 814 may be based in part on the IP protocol supported by the IP layer 813 to ensure reliable delivery of signaling messages between the RAN node 102A and the MME 621. The L2 layer 812 and the L1 layer 811 may refer to the communication links (e.g., wired or wireless) used by the RAN node and the MME to exchange information.

[0127] RAN node 102A and MME 621 can use the S1-MME interface to exchange control plane data through a protocol stack including L1 layer 811, L2 layer 812, IP layer 813, SCTP layer 814 and S1-AP layer 815.

[0128] AI / ML model development The development of AI / ML models can be divided into four main phases: training, simulation (validation), deployment, and inference. The following paragraphs briefly describe the main tasks involved in each phase.

[0129] Training Phase: In this phase, the AI ​​model is trained on the dataset. This involves feeding the model input data and corresponding correct output labels, allowing the model to learn patterns and relationships within the data. Training typically involves optimization algorithms used to tune the model's parameters to minimize error.

[0130] Simulation Phase: In the simulation phase, the trained model is extensively tested to ensure it performs well on data it has never seen before. This phase involves using a validation dataset to evaluate the model's performance metrics, such as accuracy, precision, and recall. Simulation helps identify any issues with the model's generalization and performance before deployment.

[0131] Deployment Phase: Once the model has been trained and successfully simulated, it is ready for deployment. Deployment involves integrating the model into a production environment where it can predict or classify new, unseen data. This may involve creating an application programming interface (API) or integrating the model into the applications or systems that will use it.

[0132] Inference Phase: In this phase, the deployed model is used to make predictions or classifications on real-world data referred to in this paper as a “scenario.” A scenario typically refers to a specific situation or problem domain in which an AI / ML model is applied or evaluated. Scenarios help to construct the context in which the AI / ML model is deployed. The AI / ML model takes the input data, processes it, and produces an output called inference, such as the predicted beam RSRP (auxiliary) or predicted beam ID.

[0133] AI / ML model monitoring Monitoring and evaluation: Monitoring entities (such as UE 106, base station 102 or network 1020) can continuously monitor various factors, such as data characteristics, system performance metrics or environmental conditions.

[0134] Decision specification: Based on the monitored factors, the monitoring entity decides whether to switch to a different machine learning model that is more suitable for the current conditions or task, use transfer learning to fine-tune the current model to better match the environmental conditions, or indicate that it is necessary to revert to a non-AI-based positioning.

[0135] AI model switching refers to the process of dynamically selecting or switching between different machine learning models or algorithms based on certain conditions or criteria. This approach is typically used in adaptive systems where the best model for a specific task may change over time or in different contexts. AI model switching can include the following.

[0136] Model selection: The monitored entity selects the most appropriate model from a set of predefined models or algorithms. This selection can be based on factors such as accuracy, efficiency, or robustness.

[0137] Model fine-tuning: Once a model is selected, it can be further trained on task-specific datasets. This is called fine-tuning. Fine-tuning a pre-trained model reduces the initial training load while ensuring the model is trained for the specific task it will be used for. This allows the model to be trained more generally for multiple specific tasks. Fine-tuning a pre-trained model can be optional, depending on how different the initial training is from the model's final use.

[0138] Adaptation: Once a new model is selected and optionally fine-tuned, the monitored entity adapts its operation to use the newly selected model for prediction or decision-making.

[0139] Case Studies of New Solutions in 3GPP Release 18 It should be understood that the accuracy of inferences made by AI / ML models is limited by the accuracy of the monitored factors, such as data characteristics, system performance metrics, or environmental conditions.

[0140] This disclosure provides novel and non-obvious technical solutions applicable to research cases identified above. For example, this disclosure provides information on (1) how to obtain measurements for validating network AI / ML model inference data while minimizing UE measurement performance and reporting. It should be understood that the technical solutions provided herein may be incorporated into future specifications, including 3GPP Release 19.

[0141] AI / ML-based handover failure and radio link failure prediction Wireless communication systems provide mobility by enabling user equipment (UEs) to move between cells via a process known as handover. Handover occurs when a mobile UE switches from one cell to another neighboring cell. Mechanisms have been established to help ensure a smooth transition between cells. NR supports different types of handover not supported in previous 4G LTE specifications. The basic handover in NR is based on LTE handover mechanisms, in which the network controls UE mobility based on UE measurement reports. These measurement reports typically involve Layer 3 (L3) measurements of neighboring cells and reports from the UE to the eNB.

[0142] It should be noted that 5G NR implements various advanced capabilities compared to LTE, and one existing process that can benefit from leveraging these enhancements of 5G technology is the Radio Link Failure (RLF) mechanism. RLF refers to a situation where radio link quality deteriorates below a certain threshold, causing a communication interruption between the User Equipment (UE) and the serving base station. The current RLF process has some limitations because it only reacts to failures after they have occurred, rather than proactively preventing them. The process also relies on a limited set of reference signal measurements that may not fully capture emerging radio link problems. Additionally, downlink and uplink signals are evaluated independently, even though they are often correlated in indicating radio link conditions.

[0143] These gaps highlight the use cases where advanced algorithms, such as artificial intelligence (AI) and machine learning (ML), combined with coordination between the UE and next-generation NodeBs (base stations), can provide more predictive identification of the risk of impending radio link failures. By intelligently fusing multiple radio link indicators and legacy measurements, AI / ML can potentially predict failures in advance, allowing mitigation actions (such as handover) to prevent deterioration, rather than simply reacting to RLF events. As 5G networks continue to evolve, achieving such predictive failure management can further improve reliability mechanisms.

[0144] Figure 9 : A timing graph used to implement network-side model inference verification based on artificial intelligence (AI).

[0145] In cellular systems, AI-based mobility involves the network using artificial intelligence (AI) models to estimate measurement events and configure UEs to perform fewer measurements. However, since the network's measurement predictions may be less accurate than the actual measurements taken by the UE, using these network-based event predictions to trigger mobility actions can lead to more frequent handover (HO) failures. Therefore, validation of network predictions is needed. Consequently, a mechanism is required to validate network-side AI / ML-based predictions to maintain reliable mobility performance for UEs operating within the network.

[0146] Therefore, the mechanism of the illustrated implementation provides a measurement query that can be transmitted from the network to the UE. In doing so, the network queries the UE for measurements at the UE, such as, for example, the network requesting the UE to confirm that the measurements are within a threshold predicted by the network.

[0147] Existing measurement frameworks, such as "ReportMount" with "eventTriggered" as the reportType and set to 1, can be used to support AI / ML model validation. However, this approach, as a legacy "one-off" type of measurement, may be inefficient for network-side AI / ML model validation if the network might request additional "on-the-fly" measurements (which would require new measurement configurations and thus result in excessive signaling overhead).

[0148] Therefore, the mechanism of the illustrated implementation provides an additional variant of "one-off" measurement, in which the network provides a measurement configuration once and transmits the one-off measurement configuration for AI-based model validation to the UE. The network can then trigger the UE to perform various measurements using the one-off measurement configuration as needed. In one example, a new ReportConfig element (in addition to periodic elements and event-triggered elements) is provided, which can be referred to as one-off (e.g., one-off measurement configuration).

[0149] When a UE receives a MeasConfig message from the network via this type of report, it may immediately perform a measurement and store the measurement configuration if instructed, which is the opposite of the old-fashioned "one-off" approach where the measurement configuration is deleted at the UE after the measurement is performed.

[0150] Subsequently, such one-off measurements can be triggered at the UE using Radio Resource Control (RRC) messages, Media Access Control (MAC) control elements (CE), and / or Downlink Control Information (DCI). However, the UE does not release the measurement configuration after performing the one-off measurement. When the measurement configuration is no longer needed, legacy signaling can be used to release the one-off measurement configuration.

[0151] Therefore, compared to a one-off measurement in which the network transmits a measurement configuration to the UE, and the UE performs the measurement once and then discards the configuration, an enhanced one-off measurement configuration is provided to support network-side AI / ML model validation through more efficient communication of measurements made by the UE that can be used to train AI / ML models at the network.

[0152] In summary, the measurement configuration is transmitted from the network to the UE only once, and the UE performs the measurement immediately upon triggering. Furthermore, the UE stores the one-time measurement configuration for future use, rather than discarding it after the measurement is collected. In this way, the network can trigger immediate measurements performed by the UE multiple times as needed and using the same stored one-time measurement configuration, without transmitting the measurement configuration each time a measurement is needed or performed. This can be accomplished using various signaling methods, such as RRC messages, MAC CE, or DCI. At a later time, when the one-time measurement configuration is no longer needed, legacy signaling from the network can be used to release the one-time measurement configuration.

[0153] Measurement objects (MOs) can be used to transmit measurement configurations from the network to the UE. Regardless of the protocol used, trigger messages can carry a measurement object identifier (ID). Alternatively, if only one such measurement object is supported, the trigger message may not need to carry the MO ID.

[0154] Trigger messages may also include additional content. For example, a trigger message may include: - Information used to further restrict / filter the requested results (e.g., cell list, reference signal type); - The time and location (precise time or boundary) of the measurements performed by the UE. - reportAmount (this will override the reportAmount in the measurement configuration); and - The delay (between consecutive measurements), if reportAmount is provided; Alternatively, instead of reportAmount, a signal can be sent to notify the reporting time (start and stop).

[0155] Instead of triggering, activation / deactivation can be used as follows. Measurement objects and events can be configured as in the legacy configuration; however, they are marked as inactive. The network can activate measurement objects (using RRC / MAC / DCI). The network can deactivate measurement objects.

[0156] In another example, the mechanism of the illustrated implementation provides network command verification. For example, if the handover (HO) is triggered by a network-side AI / ML model-predicted event (as opposed to a UE-reported measurement event), the RRCReconfiguration message may also contain information about the predicted event that triggered it, including at least: 1) predicted target cell measurements, and / or 2) predicted serving cell measurements.

[0157] The RRCReconfiguration message may include a threshold for each predicted measurement. Before handover, it enables the UE to perform measurements to ensure that the difference between the predicted measurement and the actual / real measurement is defined by a threshold signaled by the network. If the difference between the predicted measurement and the actual / real measurement is less than the threshold, the UE performs a HO (House of Origin). If the difference between the predicted measurement and the actual / real measurement is greater than the threshold, the UE does not perform the HO and the UE indicates that the HO is rejected in the RRCReconfigurationComplete message. Alternatively, actual measurements may be included directly, or the UE may indicate their availability so that the network can acquire them when needed.

[0158] While HO is provided as an example, the mechanisms of various implementations can be generalized to any network RRC message. In one example, for each RRC message, the network may include a set of conditions, such as serving cell and neighboring cell measurements, which are typically based on predictions from network-side AI / ML models. The UE can verify these conditions and execute the HO command based on their satisfaction. Depending on the configuration, the UE must satisfy one or more of the conditions to execute the command. The UE can notify the network whether the command is accepted or rejected. If the conditions are not met, the UE provides a reason value and, if requested, provides the measurements.

[0159] The exact timing of when to perform a measurement can be left to the specific implementation of the UE. For example, the UE can perform measurements periodically and use the most recently available measurement results for verification. The network can specify a time threshold to indicate how “long” a measurement can be performed. That is, the network can indicate a time threshold to indicate the maximum age of measurements that can be used for verification. In one aspect, RRC commands (in addition to HO) can include MobilityFromNRCommand, PSCell Add, and PSCell Change messages.

[0160] It should be noted that while one or more solutions may be considered as part of AI-based model analysis, the proposed signaling can be used in conjunction with other operations. Furthermore, all types of measurements can be considered, such as cell-level, beam-level, serving cell, neighboring cell, and secondary cell measurements.

[0161] In another example, to optimize network command verification, when a handover is refused, the UE can indicate the difference between the predicted and actual measurements to the network, instead of directly providing the actual measurements. This can help reduce the amount of information that needs to be sent.

[0162] In another optimization, instead of immediately rejecting the handover if the validity conditions are not met, the UE can consider the handover command valid for a specified time period. This "validity period" can be signaled in the RRCReconfiguration message. Essentially, this transforms the HO command into a conditional handover (CHO) for a specific duration. Furthermore, the HO command itself can directly include the time and location for meeting the validity conditions. This allows for more precise control over when and where the UE should verify network predictions and execute the HO.

[0163] To further explain, Figure 9 Example timing diagram signaling between user equipment (UE) and a network (e.g., via a base station) for implementing artificial intelligence (AI)-based model inference verification, according to some implementation schemes, is illustrated. Furthermore, Figure 9 An example illustration of UE 106 communicating with base station 102 is provided. In various implementations, some of the signaling shown may be executed concurrently in a different order than that shown, or may be omitted. Additional signaling may also be executed as needed. As shown in the figure, the signaling may be implemented in the following example implementation.

[0164] Figure 9 The signaling shown can be used in conjunction with any of the systems, methods, and / or devices. In various embodiments, some of the signaling shown may be executed concurrently in a different order than that shown, or may be omitted. Additional signaling may also be executed as needed. As shown in the figure, the signaling can be implemented in one of the following example embodiments.

[0165] Signaling may begin with the network (e.g., base station 102) sending a 902 message to the UE (such as UE 106) for a one-time measurement configuration for AI-based model 920 (e.g., an AI / ML model) verification. In one aspect, the one-time measurement configuration includes a new ReportConfig element. This new ReportConfig element enables the UE to perform one or more measurements “n” times based on the one-time measurement configuration, where n is a positive integer. In another example, the UE may store / save the one-time measurement configuration at the UE for subsequent measurements performed based on the one-time measurement configuration in response to receiving one or more triggers from the network.

[0166] The UE can perform one or more measurements based on a one-time measurement configuration.

[0167] The UE may (e.g., via base station 102) transmit 906 to the network for verifying one or more measurements of one or more AI-based models 920 at base station 102 or network 1020. In one aspect, the measurements may be included in a measurement report.

[0168] The signaling may also include a base station (such as base station 102) transmitting a trigger 908 for performing one or more immediate measurements based on a one-time measurement configuration. The trigger may be transmitted to the UE via a Radio Resource Control (RRC) message, a Media Access Control (MAC) control element (CE), or a Downlink Control Information (DCI). Furthermore, the trigger may include information for restricting or filtering one or more measurements, the time and location for performing one or more measurements, the reporting amount, the delay between consecutive measurements, and the reporting time.

[0169] Furthermore, in response to receiving one or more triggers from network 1020, UE 106 may perform subsequent measurements based on a one-time measurement configuration. UE may (e.g., via base station 102) transmit one or more measurements in a measurement report to the network for verifying one or more AI-based models at the network.

[0170] Additionally, signaling may include UE monitoring 914 of the performance of one or more AI-based models 913. Furthermore, signaling may include base station 102 or network 1020 monitoring 916 of the performance of one or more AI-based models 920.

[0171] Figure 10 : A flowchart of a method for implementing network-side AI-based model inference verification at the UE.

[0172] Figure 10 An example flowchart illustrates a method 1000 for implementing network-side AI-based model inference verification at the UE according to some implementation schemes.

[0173] Figure 10 The methods shown can also be used in conjunction with any of the systems, methods, or apparatuses illustrated in the figures, as well as other devices. In various embodiments, some of the method elements shown may be performed concurrently in a different order than those shown, or may be omitted. Additional method elements may also be performed as needed.

[0174] According to one implementation, method 1000 for implementing network-side artificial intelligence (AI)-based model inference verification includes decoding a one-off measurement configuration for AI-based model verification from the network, as shown in box 1010. Method 1000 also includes having a UE perform one or more measurements based on the one-off measurement configuration, as shown in box 1012. Method 1000 further includes storing the one-off measurement configuration at the UE, as shown in box 1014. Method 1000 also includes encoding one or more measurements for verifying one or more AI-based models at the network for transmission to the network, as shown in box 1016.

[0175] In some implementations, method 1000 further includes decoding from the network a handover command comprising predicted target cell measurements and predicted serving cell measurements based on one or more AI-based models, wherein the handover command is an RRCReconfiguration RRC message and RRC is Radio Resource Control; comparing the predicted target cell measurements and predicted serving cell measurements with actual measurements; and sending a handover completion message, based on the comparison indicating compliance with the handover command, to the network, wherein the handover completion message is an RRCReconfigurationComplete message.

[0176] In some implementations, method 1000 also includes decoding from the network to perform one or more immediate measurements based on a one-time measurement configuration.

[0177] In some implementations, the one-time measurement configuration includes a new ReportConfig element. In some implementations, the new ReportConfig element enables the UE to perform one or more measurements for the nth time based on the one-time measurement configuration.

[0178] In some implementations, method 1000 also includes releasing a one-time measurement configuration based on signaling transmitted over the network.

[0179] In some implementations, method 1000 further includes decoding one or more triggers received from the network via Radio Resource Control (RRC) messages, Media Access Control (MAC) control elements (CE), or Downlink Control Information (DCI).

[0180] In some implementations, method 1000 further includes storing a one-time measurement configuration for performing subsequent measurements based on the one-time measurement configuration in response to receiving one or more triggers from the network.

[0181] In some implementations, one or more triggers include a measurement object identifier. In some implementations, one or more triggers include one or more of the following: information for limiting or filtering one or more measurements, the time and location for performing one or more measurements, the reporting quantity, the delay between consecutive measurements, and the reporting time.

[0182] In some implementations, method 1000 also includes decoding from the network one or more measurement objects and events configured to be inactive.

[0183] In some implementations, method 1000 further includes activating or deactivating one or more measurement objects based on indications received via Radio Resource Control (RRC) messages, Media Access Control (MAC) control elements (CE), or Downlink Control Information (DCI).

[0184] In some implementations, the handover order also includes thresholds for each of the predicted target cell measurements and the predicted serving cell measurements.

[0185] In some implementations, method 1000 further includes executing a handover command when the difference between the predicted measurement and the actual measurement is less than a threshold.

[0186] In some implementations, method 1000 further includes ignoring the handover command when the difference between the predicted measurement and the actual measurement is greater than a threshold; and indicating in the handover completion message that the handover was ignored.

[0187] In some implementations, the handover completion message includes one or more of the actual measurements and an indication of the availability of the actual measurements.

[0188] In some implementations, method 1000 further includes decoding a network radio resource control (RRC) message from the network, the network radio resource control (RRC) message including conditions predicted based on one or more AI-based models, wherein the network RRC message is generalized to any RRC message.

[0189] In some implementations, method 1000 further includes verifying one or more conditions included in the network RRC message; and executing a command associated with the network RRC message based on the verification of the one or more conditions.

[0190] In some implementations, method 1000 also includes notifying whether a network command is accepted; and providing a cause value and the actual measurement when one or more conditions are not verified.

[0191] In some implementations, the handover completion message includes the difference between the predicted measurement and the actual measurement when the handover order is rejected.

[0192] In some implementations, method 1000 also includes determining that the transfer order is valid for a certain period of time.

[0193] In some implementations, the handover order includes the time and location that must be met for the predicted measurements.

[0194] In some implementations, the network RRC message is one or more of a handover command, a mobility command from a new radio (NR), a primary / secondary cell (PSCell) add command, and a PSCell change command. In some implementations, one or more conditions include one or more of serving cell measurements, neighboring cell measurements, secondary cell measurements, and beam level measurements.

[0195] In some implementations, method 1000 also includes periodically performing one or more measurements; and using the latest available measurement results to verify one or more conditions.

[0196] In some implementations, the network RRC message includes a time threshold, and one or more measurements within the time threshold are used to verify one or more conditions.

[0197] In some embodiments, an apparatus is disclosed that is configured to cause a user equipment (UE) to perform any operation of method 1100.

[0198] Figure 11 : A flowchart of a method for network-side model inference verification based on artificial intelligence, implemented by a base station.

[0199] Figure 11 An example flowchart is provided for a method 1100 for implementing network-side AI-based model inference verification at a base station according to some implementation schemes.

[0200] Figure 11 The methods shown can also be used in conjunction with any of the systems, methods, or apparatuses illustrated in the figures, as well as other devices. In various embodiments, some of the method elements shown may be performed concurrently in a different order than those shown, or may be omitted. Additional method elements may also be performed as needed.

[0201] According to one implementation, method 1100 for implementing network-side AI-based model inference verification includes encoding a one-off measurement configuration for AI-based model verification and sending it to a user equipment (UE), as shown in box 1110. Method 1100 also includes encoding a trigger for performing one or more measurements based on the one-off measurement configuration and sending it to the UE, as shown in box 1112. Method 1100 further includes decoding from the UE one or more measurements performed by the UE based on the one-off measurement configuration, as shown in box 1114. Method 1100 also includes using one or more measurements received from the UE by a base station to verify one or more AI-based models, as shown in box 1116.

[0202] In some implementations, method 1100 further includes encoding a handover command, comprising predicted target cell measurements and predicted serving cell measurements based on one or more AI-based models, for transmission to the UE, wherein the handover command is an RRCReconfiguration RRC message and RRC is Radio Resource Control, to enable the UE to compare the predicted target cell measurements and predicted serving cell measurements with actual measurements.

[0203] In some implementations, method 1100 further includes decoding from the UE a handover completion message based on a comparison indication that the handover command is followed, wherein the handover completion message is an RRCReconfigurationComplete message.

[0204] In some embodiments, an apparatus is disclosed that is configured to cause a base station to perform any operation of method 1100.

[0205] In some embodiments, a computer program product is disclosed that includes computer instructions that, when executed by one or more processors, perform any of the operations described with respect to method 1200.

[0206] In some embodiments, a computer program product is disclosed that includes computer instructions that, when executed by one or more processors, perform any of the operations described with respect to method 1200.

[0207] Embodiments of this disclosure may be implemented in any of a variety of forms. For example, some embodiments may be implemented as computer-implemented methods, computer-readable storage media, or computer systems. Other embodiments may be implemented using one or more custom-designed hardware devices such as ASICs. Other embodiments may be implemented using one or more programmable hardware elements such as FPGAs.

[0208] In some embodiments, a non-transitory computer-readable storage medium may be configured to store program instructions and / or data, wherein, if executed by a computer system, the program instructions cause the computer system to perform a method, such as any method embodiment of the method embodiments described herein, or any combination of method embodiments described herein, or any subset or combination of any such subset of any method embodiments described herein.

[0209] In some implementations, the device (e.g., UE 106) may be configured to include a processor (or a set of processors) and a memory medium, wherein the memory medium stores program instructions, and the processor is configured to read from and execute the program instructions from the memory medium, wherein the program instructions are executable to implement any of the various method implementations described herein (or any combination of method implementations described herein, or any subset of any method implementations described herein, or any combination of such subsets). The device may be implemented in any of the various forms.

[0210] By interpreting each message / signal X received by the user equipment (UE) in the downlink as a message / signal X sent by the base station, and interpreting each message / signal Y sent by the UE in the uplink as a message / signal Y received by the base station, any of the methods described herein for operating the UE can serve as the basis for a corresponding method for operating the base station.

[0211] Although the above embodiments have been described in considerable detail, many variations and modifications will become apparent to those skilled in the art once the above disclosure is fully understood. It is intended that the following claims be construed as encompassing all such variations and modifications.

Claims

1. A method for AI-based model inference verification of a network-side artificial intelligence (AI) model implemented by a user equipment (UE) in a wireless communication system, the method comprising: At the UE, a one-time measurement configuration for AI-based model validation is decoded from the network. The UE performs one or more measurements based on the one-time measurement configuration; The one-time measurement configuration is stored at the UE; as well as The one or more measurements used to validate the one or more AI-based models at the network are encoded and sent to the network.

2. The method of claim 1, further comprising decoding one or more triggers from the network to perform the one or more measurements based on a stored one-time measurement configuration.

3. The method of claim 1, wherein the one-time measurement configuration includes identifying the measurement as a one-time new ReportConfig measurement type, and the UE is configured to store the measurement configuration based on the one-time ReportConfig type.

4. The method of claim 3, wherein the new ReportConfig type enables the UE to perform the one or more measurements n times based on the one-time measurement configuration, where n is a positive integer.

5. The method of claim 1, further comprising releasing the one-time measurement configuration according to signaling transmitted by the network.

6. The method of claim 2, wherein the one or more triggers are received at the UE via one or more of a Radio Resource Control (RRC) message, a Media Access Control (MAC) control element (CE), or a Downlink Control Information (DCI).

7. The method of claim 6, further comprising storing the one-time measurement configuration for performing subsequent measurements based on the one-time measurement configuration in response to receiving the one or more triggers from the network.

8. The method of claim 2, wherein the one or more triggers include a measurement object identifier for identifying the one-time measurement configuration.

9. The method of claim 2, wherein the one or more triggers include one or more of the following: information for limiting or filtering the one or more measurements, time and location for performing the one or more measurements, reporting quantity, delay between consecutive measurements, and reporting time.

10. The method of claim 1, further comprising decoding from the network one or more measurement objects and events configured to be inactive.

11. The method of claim 10, further comprising activating or deactivating the one or more measurement objects based on an indication received via a Radio Resource Control (RRC) message, a Media Access Control (MAC) control element (CE), or a Downlink Control Information (DCI).

12. The method according to claim 1, further comprising: Decoding from the network includes a Radio Resource Control (RRC) handover command based on one or more of the network-side AI-based models, namely, a predicted target cell measurement or a predicted serving cell measurement, wherein the handover command is an RRCReconfiguration message; The predicted target cell measurement and the predicted serving cell measurement are compared with the actual measurements performed at the UE; as well as A handover completion message is sent to the network, the handover completion message indicating when the handover command is followed at the UE based on a comparison of the predicted target cell measurement or the predicted serving cell measurement with the actual measurement, wherein the handover completion message is an RRCReconfigurationComplete message.

13. The method of claim 12, wherein the handover command further includes a threshold for one or more of each of the predicted target cell measurement or the predicted serving cell measurement.

14. The method of claim 13, further comprising executing the handover command when the difference between the predicted measurement and the actual measurement is less than a threshold.

15. The method of claim 14, further comprising: The handover command is ignored when the difference between the predicted measurement and the actual measurement is greater than the threshold. as well as The handover completion message indicates that the handover was ignored.

16. The method of claim 15, wherein the handover completion message includes one or more of the actual measurements and an indication of the availability of the actual measurements.

17. The method of claim 12, further comprising decoding a radio resource control (RRC) message from the network, the RRC message including a command for the UE and conditions associated with the command based on predictions of the one or more AI-based models.

18. The method of claim 17, further comprising: Verify one or more conditions of the prediction based on the one or more AI-based models included in the network RRC message by comparing the one or more conditions with one or more measurements performed at the UE to verify that the one or more conditions are within the threshold level of the one or more measurements; as well as The command is executed at the UE associated with the network RRC message based on verification of one or more of the conditions.

19. The method of claim 18, further comprising: The network is notified when the command is accepted at the UE or when the command is not accepted at the UE; as well as If one or more of the conditions are not verified, provide a cause value and one or more of the measurements.

20. The method of claim 12, wherein the handover completion message includes the difference between the predicted measurement and the one or more measurements when the handover command is rejected.

21. The method of claim 12, further comprising determining that the handover order is valid within a selected time period.

22. The method of claim 21, wherein the handover command includes the time and location to be satisfied by the predicted measurement.

23. The method of claim 17, wherein the network RRC message is one or more of a handover command, a mobility command from a new radio (NR), a primary / secondary cell (PSCell) add command, or a PSCell change command.

24. The method of claim 18, wherein the one or more conditions include one or more of serving cell measurement, neighboring cell measurement, secondary cell measurement, or beam level measurement.

25. The method of claim 18, further comprising: Perform the one or more measurements periodically; or Use the latest available measurement results at the UE to verify one or more of the conditions.

26. The method of claim 18, wherein the network RRC message includes a time threshold, and wherein the one or more measurements within the time threshold are used to verify the one or more conditions.

27. An apparatus configured to cause a user equipment (UE) to perform any of the methods described according to claims 1 to 26.

28. A baseband processor configured to cause a user equipment (UE) to perform one or more of the methods according to claims 1 to 26.

29. An apparatus for a user equipment (UE), the apparatus comprising: One or more processors, said one or more processors coupled to memory, said one or more processors being configured to: Decode a one-off measurement configuration from the network for artificial intelligence (AI)-based model validation; The UE performs one or more measurements based on the one-time measurement configuration; The one-time measurement configuration is stored at the UE; as well as The one or more measurements used to validate the one or more AI-based models at the network are encoded and sent to the network.

30. An apparatus for a base station, the apparatus comprising: One or more processors, said one or more processors coupled to memory, said one or more processors being configured to: A one-off measurement configuration for AI-based model validation of one or more AI-based models at the network is encoded and sent to a user equipment (UE), thereby enabling the UE to store the one-off measurement configuration; A trigger that enables the UE to perform one or more measurements based on a stored one-time measurement configuration is encoded and sent to the UE; Decode from the UE one or more measurements performed by the UE based on the one-time measurement configuration; as well as One or more AI-based models at the network are validated using the one or more measurements received from the UE.

31. The apparatus of claim 30, further comprising the one or more processors coupled to the memory, the one or more processors being configured to: Encoding a Radio Resource Control (RRC) handover command, comprising one or more of the predicted target cell measurements or predicted serving cell measurements based on one or more AI-based models, for transmission to the UE, thereby enabling the UE to compare the predicted target cell measurement or the predicted serving cell measurement with the one or more measurements performed at the UE; and The UE decodes an RRC handover completion message, which indicates when to follow the handover command based on a comparison of the predicted target cell measurement and the predicted serving cell measurement with one or more measurements performed at the UE, wherein the handover completion message is an RRCReconfigurationComplete message.

32. The apparatus of claim 30, further comprising encoding a trigger for performing the one or more measurements based on a stored one-time measurement configuration for transmission to the UE.

33. A computer program product comprising computer instructions that, when executed by one or more processors, perform any of the operations described herein.

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