Model-based predictive interference management

Abstract

Apparatus, methods, and systems for model-based predictive interference management are disclosed. One method includes receiving modeling information corresponding to a device, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning component. The method includes determining a predictive inter-cell interference management strategy for the device based on the modeling information. The method also includes providing the device with the expected inter-cell interference management strategy.

Description

Technical Field

[0001] The topics disclosed in this paper generally relate to wireless communication, and more specifically to model-based predictive interference management. Background Technology

[0002] The following abbreviations are defined herein, and at least some of them are referenced in the following descriptions: Third Generation Partnership Project (“3GPP”), Fifth Generation (“5G”), 5G System (“5GS”), QoS for NR V2X Communication (“5QI / PQI”), Authentication, Authorization and Accounting (“AAA”), Positive Acknowledgment (“ACK”), Artificial Intelligence (“AI”), Application Function (“AF”), Authentication and Key Protocol (“AKA”), Aggregation Level (“AL”), Access and Mobility Management Function (“AMF”), Angle of Arrival (“AoA”), Angle of Departure (“AoD”), Access Point (“AP”), Application Programming Interface (“API”), Application Server (“AS”), Application Service Provider (“ASP”), Autonomous Uplink (“AUL”), Authentication Server Function (“AUSF”), Authentication Token (“AUTN”) Background Data (“BD”), Background Data Transmission (“BDT”), Beam Fault Detection (“BFD”), Beam Fault Recovery (“BFR”), Backhaul (“BH”), Binary Phase Shift Keying (“BPSK”), Base Station (“BS”), Buffer Status Report (“BSR”), Bandwidth (“BW”), Bandwidth Portion (“BWP”), Cloud-Resource Access Network (“C-RAN”), Cell RNTI (“C-RNTI”), Carrier Aggregation (“CA”), Channel Access Priority Class (“CAPC”), Coordinated Beamforming (“CB”), Contention-Based Random Access (“CBRA”), Idle Channel Assessment (“CCA”) Common Control Channel (“CCCH”), Control Channel Element (“CCE”), Cyclic Delay Diversity (“CDD”), Code Division Multiple Access (“CDMA”), Control Element (“CE”), Contention-Free Random Access (“CFRA”), Configured License (“CG”), Closed Loop (“CL”), Connection Mobility Control (“CMC”), Coordinated Multipoint (“CoMP”), Channel Occupancy Time (“COT”), Cyclic Prefix (“CP”), Channel Quality Indicator (“CQI”), Cyclic Redundancy Check (“CRC”), Coordinated Scheduling (“CS”), Channel State Information (“CSI”), Channel State Information-Reference Signal (“CSI-RS”) Common Search Space (“CSS”), Control Resource Set (“CORESET”), Central Unit (“CU”), Device-to-Device (“D2D”), Discrete Fourier Transform Extended (“DFTS”), Downlink Control Information (“DCI”), Downlink Feedback Information (“DFI”), Downlink (“DL”), Demodulation Reference Signal (“DMRS”), Data Network Name (“DNN”), Dynamic Resource Allocation (“DRA”), Data Radio Bearer (“DRB”), Discontinuous Receive (“DRX”), Dedicated Short Range Communication (“DSRC”), Distributed Unit (“DU”), Downlink Pilot Time Slot (“DwPTS”).Evolved Universal Terrestrial Access Network (“E-UTRAN”), E2 Terminal (“E2T”), Enhanced Free Channel Assessment (“eCCA”), Enhanced Mobile Broadband (“eMBB”), Evolved Node B (“eNB”), Extensible Authentication Protocol (“EAP”), Enhanced Inter-Cell Interference Coordination (“eICIC”), Effective Isotropic Radiated Power (“EIRP”), European Telecommunications Standards Institute (“ETSI”), Frame-Based Equipment (“FBE”), Frequency Division Duplex (“FDD”), Frequency Division Multiplexing (“FDM”), Frequency Division Multiple Access (“FDMA”), Frequency Division Orthogonal Coverage Code (“FD-OCC”), Fractional Frequency Reuse (“FFR”), Further Enhanced Inter-Cell Interference Coordination (“FeICIC”), Frequency Range 1–6 GHz and / or 410 MHz to 7125 MHz (“FR1”), Frequency Range 2–24.25 GHz to 52.6 GHz GHz (“FR2”), General Geographic Area Description (“GAD”), Guaranteed Bit Rate (“GBR”), Group Leader (“GL”), 5G Node B or Next Generation Node B (“gNB”), Global Navigation Satellite System (“GNSS”), General Packet Radio Service (“GPRS”), Guard Period (“GP”), Global Positioning System (“GPS”), General Public Subscription Identifier (“GPSI”), Global System for Mobile Communications (“GSM”), Globally Unique Temporary UE Identifier (“GUTI”), Home AMF (“hAMF”), Hybrid Automatic Repeat Request (“HARQ”), Heterogeneous Networks (“HetNets”), High Interference Indicator (“HII”), Home Location Register (“HLR”), Handover (“HO”), Home PLMN (“HPLMN”), Home Subscriber Server (“HSS”), Hash Expected Response (“HXRES”), Inter-cell Interference Coordination (“ICIC”), Identifier or Identifier (“ID”), Information Element (“IE”), Industrial Internet of Things (“IIoT”), Interference Management (“IM”), International Mobile Equipment Identity (“IMEI”), International Mobile Subscriber Identity (“IMSI”), International Mobile Telecommunications (“IMT”), Internet of Things (“IoT”), Joint Receive (“JR”), Joint Transmit (“JT”), Key Management Function (“KMF”), Key Performance Indicators (“KPI”), Layer 1 (“L1”), Layer 2 (“L2”), Layer 3 (“L3”), Licensed Assisted Access (“LAA”), Local Area Data Network (“LADN”), Local Area Network (“LAN”), Load Balancing (“LB”), Load-Based Equipment (“LBE”), Listen Before Talk (“LBT”), Logical Channel (“LCH”), Logical Channel Group (“LCG”), Logical Channel Priority (“LCP”), Log-Likelihood Ratio (“LLR”), Long Term Evolution (“LTE”), LTE Advanced (“LTE-A”)Multiple Access (“MA”), Media Access Control (“MAC”), Multimedia Broadcast Multicast Service (“MBMS”), Maximum Bit Rate (“MBR”), Minimum Communication Range (“MCR”), Modulation and Coding Scheme (“MCS”), Master Information Block (“MIB”), Multimedia Internet Keying (“MIKEY”), Multiple Input Multiple Output (“MIMO”), Machine Learning (“ML”), Mobility Management (“MM”), Mobility Management Entity (“MME”), Mobile Network Operator (“MNO”), Mobile Initiation (“MO”), Massive MTC (“mMTC”), Maximum Power Reduction (“MPR”), Machine Type Communication (“MTC”), Multi-User Shared Access (“MUSA”), Non-Access Stratum (“NAS”), Narrowband (“NB”), Negative Acknowledgment (“NACK”) or (“NAK”), New Data Indicator (“NDI”), Network Entity (“NE”), Network Exposure Function (“NEF”), Network Function (“NF”), Next Generation (“NG”), NG 5G S-TMSI (“NG-5G-S-TMSI”), Non-Orthogonal Multiple Access (“NOMA”), New Radio (“NR”), Unlicensed NR (“NR-U”), Network Repository Function (“NRF”), Network Scheduling Mode (“NS Mode”) (e.g., Network Scheduling Mode for V2X Communication Resource Allocation—Mode-1 in NR V2X and Mode-3 in LTE V2X), Network Slice Instance (“NSI”), Network Slice Selection Assistance Information (“NSSAI”), Network Slice Selection Function (“NSSF”), Network Slice Selection Policy (“NSSP”), Operation, Management and Maintenance System or Operation and Maintenance Center (“OAM”), O-RAN CU Control Plane (“O-CU-CP”), O-RAN CU User Plane (“O-CU-CP”), O-RAN DU (“O-DU”), Orthogonal Frequency Division Multiplexing (“OFDM”), Overload Indicator (“OI”), Open Loop (“OL”), Open RAN (“O-RAN”), Other System Information (“OSI”), Power Angle Spectrum (“PAS”), Physical Broadcast Channel (“PBCH”), Power Control (“PC”), UE-to-UE Interface (“PC5”), Policy and Charging Control (“PCC”), Primary Cell (“PCell”), Policy Control Function (“PCF”), Physical Cell Identifier (“PCI”), Physical Downlink Control Channel (“PDCCH”), Packet Data Convergence Protocol (“PDCP”), Packet Data Network Gateway (“PGW”), Physical Downlink Shared Channel (“PDSCH”), Pattern Division Multiple Access (“PDMA”), Packet Data Unit (“PDU”), Physical Hybrid ARQ Indicator Channel (“PHICH”), Power Headroom (“PH”), Power Headroom Report (“PHR”), Physical Layer (“PHY”).Public Land Mobile Network (“PLMN”), PC5 QoS Class Identifier (“PQI”), Physical Random Access Channel (“PRACH”), Physical Resource Block (“PRB”), Proximity Service (“ProSe”), Location Reference Signal (“PRS”), Physical Sidelink Control Channel (“PSCCH”), Primary and Secondary Cell (“PSCell”), Physical Sidelink Feedback Control Channel (“PSFCH”), Physical Uplink Control Channel (“PUCCH”), Physical Uplink Shared Channel (“PUSCH”), QoS Class Identifier (“QCI”), Quasi-Co-location (“QCL”), Quality of Experience (“QoE”), Quality of Service (“QoS”), Quadrature Phase Shift Keying (“QPSK”), Registration Area (“RA”), RA RNTI (“RA-RNTI”), Radio Access Network (“RAN”), Radio Access Network – Control Plane (“RAN”) CP”), Random (“RAND”), Radio Access Network – User Plane (“RANUP”), Radio Access Technology (“RAT”), Serving RAT (“RAT-1”) (regarding Uu service), Other RAT (“RAT-2”) (regarding Uu no service), Radio Licensing Control (“RAC”), Random Access Procedure (“RACH”), Random Access Preamble Identifier (“RAPID”), Random Access Response (“RAR”), Resource Block (“RB”), Resource Block Assignment (“RBA”), Radio Bearer Control (“RBC”), Resource Element Group (“REG”), Radio Access Network Intelligent Controller (“RIC”), Radio Link Control (“RLC”), RLC Acknowledgment Mode (“RLC-AM”), RLC Unacknowledgment Mode / Transparent Mode (“RLC-UM / TM”), Radio Link Failure (“RLF”), Radio Link Monitoring (“RLM”), Radio Network Temporary Identifier (“RNTI”), Relative Narrowband TX Power (“RNTP”), Reference Signal (“RS”), Residual Minimum System Information (“RMSI”), Radio Resource Control (“RRC”), Radio Resource Management (“RRM”), Resource Extended Multiple Access (“RSMA”), Received Reference Signal Power (“RSRP”), Received Signal Strength Indicator (“RSSI”), Real-Time (“RT”), Round-Trip Time (“RTT”), Receive (“RX”), Sparse Code Multiple Access (“SCMA”), Scheduling Request (“SR”), Sounding Reference Signal (“SRS”), Single Carrier Frequency Division Multiple Access (“SC-FDMA”), Secondary Cell (“SCell”), Secondary Cell Group (“SCG”), Shared Channel (“SCH”), Sidelink Control Information (“SCI”), Subcarrier Spacing (“SCS”), Software Defined Networking (“SDN”), Serving Data Unit (“SDU”), Security Anchor Function (“SEAF”).Sidelink Feedback Content Information (“SFCI”), Soft Frequency Reuse (“SFR”), Serving Gateway (“SGW”), System Information Block (“SIB”), System Information Block Type 1 (“SIB1”), System Information Block Type 2 (“SIB2”), Subscriber Identifier / Identifier Module (“SIM”), Signal-to-Interference-plus-Noise Ratio (“SINR”), Sidelink (“SL”), Service Level Agreement (“SLA”), Sidelink Synchronization Signal (“SLSS”), Session Management (“SM”), Session Management Function (“SMF”), Ad Hoc Network (“SON”), Specific Cell (“SpCell”), Single Network Slice Selection Auxiliary Information (“S-NSSAI”), Scheduling Request (“SR”), Signaling Radio Bearer (“SRB”), Shortened TMSI (“S-TMSI”), Shortened TTI (“sTTI”), Synchronization Signal (“SS”), Sidelink CSI RS (“S-CSI”) RS”, Side Link PRS (“S-PRS”), Side Link SSB (“S-SSB”), Synchronization Signal Block (“SSB”), Subscription Hidden Identifier (“SUCI”), Scheduled User Equipment (“SUE”), Supplemental Uplink (“SUL”), Subscriber Permanent Identifier (“SUPI”), Tracking Area (“TA”), TA Identifier (“TAI”), TA Update (“TAU”), Timing Calibration Timer (“TAT”), Transport Block (“TB”), Transport Block Size (“TBS”), Time Division Duplex (“TDD”) Time Division Multiplexing (“TDM”), Time Division Orthogonal Cover Code (“TD-OCC”), Temporary Mobile Subscriber Identifier (“TMSI”), Time of Flight (“ToF”), Transmit Power Control (“TPC”), Transmit Receive Point (“TRP”), Transmission Time Interval (“TTI”), Transmission (“TX”), Uplink Control Information (“UCI”), Unified Data Management Function (“UDM”), Ultra Dense Network (“UDN”), Unified Data Repository (“UDR”), User Entity / Equipment (Mobile Terminal) (“UE”) (e.g., V2X) UE), UE Autonomous Mode (UE autonomously selects V2X communication resources—e.g., Mode 2 in NR V2X and Mode 4 in LTE V2X. UE autonomous selection may or may not be based on resource sensing operations), Uplink (“UL”), UL SCH (“UL-SCH”), Universal Mobile Telecommunications System (“UMTS”), User Plane (“UP”), UP Function (“UPF”), Uplink Pilot Slot (“UpPTS”), Ultra-Reliable Low-Latency Communication (“URLLC”), UE Routing Policy (“URSP”), Vehicle-to-Vehicle (“V2V”), Vehicle-to-Everything (“V2X”), V2X UE (e.g., a UE capable of vehicular communication using 3GPP protocols), Access AMF (“vAMF”).V2X encryption key (“VEK”), V2X group key (“VGK”), V2X MIKEY key (“VMK”), access NSSF (“vNSSF”), access PLMN (“VPLMN”), V2X service key (“VTK”), wide area network (“WAN”), and global microwave access interoperability (“WiMAX”).

[0003] Interference may occur in some wireless communication networks. Summary of the Invention

[0004] A model-based predictive interference management method is disclosed. Apparatus and systems also perform the functions of this method. One embodiment of the method includes receiving modeling information corresponding to a device, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model. In some embodiments, the method includes determining a predictive inter-cell interference management strategy for the device based on the modeling information. In some embodiments, the method includes providing the predictive inter-cell interference management strategy to the device.

[0005] An apparatus for model-based predictive interference management includes a receiver that receives modeling information corresponding to a device, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model. In various embodiments, the apparatus includes a processor that: determines a predictive inter-cell interference management strategy for the device based on the modeling information; and provides the predictive inter-cell interference management strategy to the device.

[0006] Another embodiment of the method for model-based predictive interference management includes receiving at least one monitoring report from a device. In some embodiments, the method includes determining a monitoring event report based on a subscription and at least one monitoring report. In some embodiments, the method includes providing the monitoring event report to an application.

[0007] Another apparatus for model-based predictive interference management includes a receiver that receives at least one monitoring report from the device. In various embodiments, the apparatus includes a processor that: determines a monitoring event report based on the subscription and at least one monitoring report; and provides the monitoring event report to an application.

[0008] Another embodiment of the method for model-based predictive interference management includes sending at least one monitoring report. In some embodiments, the method includes receiving information corresponding to a predictive inter-cell interference management strategy in response to sending at least one monitoring report.

[0009] Another apparatus for model-based predictive interference management includes a transmitter that sends at least one monitoring report. In some embodiments, the apparatus includes a receiver that receives information corresponding to a predictive inter-cell interference management strategy in response to the transmission of at least one monitoring report.

[0010] Another embodiment of the method for model-based predictive interference management includes sending an initial configuration. In various embodiments, the method includes receiving a request for modeling information in response to sending the initial configuration. In some embodiments, the method includes sending modeling information in response to receiving the request, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model.

[0011] Another apparatus for model-based predictive interference management includes a transmitter that sends an initial configuration. In some embodiments, the apparatus includes a receiver that receives a request for modeling information in response to sending the initial configuration; wherein the transmitter sends the modeling information in response to receiving the request, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model.

[0012] Further embodiments of the method for model-based predictive interference management include receiving a predictive resource management policy from at least one application. In various embodiments, the method includes determining at least one radio parameter corresponding to the predictive resource management policy. In some embodiments, the method includes transmitting at least one radio parameter to a device based on the predictive resource management policy.

[0013] A further apparatus for model-based predictive interference management includes a receiver that receives a predictive resource management policy from at least one application. In some embodiments, the apparatus includes a processor that determines at least one radio parameter corresponding to the predictive resource management policy. In various embodiments, the apparatus includes a transmitter that transmits at least one radio parameter to the device based on the predictive resource management policy. Attached Figure Description

[0014] A more detailed description of the embodiments briefly described above will be presented by referring to the specific embodiments illustrated in the accompanying drawings. It should be understood that these drawings depict only some embodiments and are not intended to be limiting of the scope; the embodiments will be described and explained with additional specificity and detail using the drawings, wherein:

[0015] Figure 1 This is a schematic block diagram illustrating one embodiment of a model-based predictive interference management wireless communication system;

[0016] Figure 2 This is a schematic block diagram illustrating one embodiment of a device that can be used for model-based predictive disturbance management;

[0017] Figure 3 This is a schematic block diagram illustrating one embodiment of a device that can be used for model-based predictive disturbance management;

[0018] Figure 4 This is a diagram illustrating one embodiment of a system for interference management;

[0019] Figure 5 This is a diagram illustrating another embodiment of a system for interference management;

[0020] Figure 6 This is a diagram illustrating one embodiment of communication used for interference management;

[0021] Figure 7 This is a diagram illustrating another embodiment of communication used for interference management;

[0022] Figure 8 This is a flowchart illustrating one embodiment of a model-based predictive disturbance management method;

[0023] Figure 9 This is a flowchart illustrating another embodiment of a model-based predictive disturbance management method;

[0024] Figure 10 This is a flowchart illustrating yet another embodiment of a model-based predictive disturbance management method;

[0025] Figure 11 This is a flowchart illustrating a further embodiment of a model-based predictive disturbance management method; and

[0026] Figure 12 This is a flowchart illustrating another embodiment of a model-based predictive disturbance management method. Detailed Implementation

[0027] As those skilled in the art will understand, aspects of the embodiments can be embodied as a system, apparatus, method, or program product. Therefore, embodiments can take the form of a completely hardware embodiment, a completely software embodiment (including firmware, resident software, microcode, etc.), or an embodiment combining software and hardware aspects, which may generally be referred to herein as a "circuit," "module," or "system." Furthermore, embodiments can take the form of a program product embodied in one or more computer-readable storage devices stored in machine-readable code, computer-readable code, and / or program code, hereinafter referred to as "code." The storage device can be tangible, non-transitory, and / or non-transferable. The storage device may not embody signals. In one embodiment, the storage device only uses signals for accessing the code.

[0028] Certain functional units described in this specification may be designated as modules to more specifically emphasize their implementation independence. For example, modules may be implemented as hardware circuits comprising custom-designed very large-scale integration (“VLSI”) circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. Modules may also be implemented in programmable hardware devices such as field-programmable gate arrays, programmable array logic, programmable logic devices, etc.

[0029] Modules can also be implemented in code and / or software to be executed by various types of processors. The identified code module can, for example, comprise one or more physical or logical blocks of executable code, which can, for example, be organized as objects, procedures, or functions. However, the executable files of the identified modules do not need to be physically located together and can include unrelated instructions stored in different locations, which, when logically combined, comprise the module and implement the stated purpose of the module.

[0030] In practice, a code module can be a single instruction or many instructions, and can even be distributed across several different code segments, different programs, and across several memory devices. Similarly, in this document, operational data can be identified and illustrated within a module, and can be represented in any suitable form and organized within any suitable type of data structure. Operational data can be collected as a single dataset or can be distributed across different locations, including different computer-readable storage devices. Where the module or part of a module is implemented in software, the software portion is stored on one or more computer-readable storage devices.

[0031] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable storage medium. A computer-readable storage medium may be a storage device for storing code. A storage device may be, for example, but not limited to, electronic, magnetic, optical, electromagnetic, infrared, holographic, micromechanical, or semiconductor systems, apparatuses, or devices, or any suitable combination thereof.

[0032] More specific examples of storage devices (a non-exhaustive list) will include the following: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (“RAM”), read-only memory (“ROM”), erasable programmable read-only memory (“EPROM” or flash memory), portable optical disc read-only memory (“CD-ROM”), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium can be any tangible medium capable of containing or storing programs for use by or in connection with an instruction execution system, apparatus, or device.

[0033] The code used to perform the operations of the embodiments can be any number of lines and can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Python, Ruby, Java, Smalltalk, and C++, and common procedural programming languages ​​such as the "C" programming language, and / or machine languages ​​such as assembly language. The code can be executed entirely on the user's computer, partially on the user's computer, or as a standalone software package on the user's computer, partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer via any type of network, including a local area network ("LAN") or a wide area network ("WAN"), or can be connected to an external computer (e.g., via the Internet through an Internet service provider).

[0034] Throughout this specification, references to "an embodiment," "embodiment," or similar language mean that a particular feature, structure, or characteristic described in connection with that embodiment is included in at least one embodiment. Therefore, unless explicitly stated otherwise, throughout this specification, the phrases "in an embodiment," "in an embodiment," and similar language may, but do not necessarily all refer to the same embodiment, but rather mean "one or more, but not all, embodiments." Unless explicitly stated otherwise, the terms "comprising," "including," "having," and variations thereof mean "including, but not limited to,". Unless explicitly stated otherwise, the list of enumerated items does not imply that any or all items are mutually exclusive. Unless explicitly stated otherwise, the terms "a," "an," and "the" also mean "one or more".

[0035] Furthermore, the features, structures, or characteristics of the described embodiments can be combined in any suitable manner. In the following description, numerous specific details are provided, such as examples of programming, software modules, user selection, network transactions, database queries, database structures, hardware modules, hardware circuits, hardware chips, etc., to provide a thorough understanding of the embodiments. However, those skilled in the art will recognize that embodiments can be practiced without one or more specific details, or by utilizing other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the embodiments.

[0036] The following description of aspects of embodiments is based on schematic flowcharts and / or schematic block diagrams of methods, apparatus, systems, and program products according to embodiments. It will be understood that each block of the schematic flowcharts and / or schematic block diagrams, and combinations of blocks in the schematic flowcharts and / or schematic block diagrams, can be implemented by code. The code can be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to generate machinery, such that instructions executable via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / operations specified in the blocks or blocks of the schematic flowcharts and / or schematic block diagrams.

[0037] The code can also be stored in a storage device that can instruct a computer, other programmable data processing device or other device to operate in a particular manner, such that the instructions stored in the storage device produce an article of art including instructions that implement the functions / operations specified in the boxes or some boxes of the schematic flowchart and / or schematic block diagram.

[0038] The code may also be loaded onto a computer, other programmable data processing apparatus or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer-implemented process, such that the code executing on the computer or other programmable apparatus provides for implementing the function / operation specified in the boxes or some boxes of the flowchart and / or block diagram.

[0039] The schematic flowcharts and / or schematic block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, system, method, and program products according to various embodiments. In this regard, each block in the schematic flowcharts and / or schematic block diagrams may represent a module, segment, or portion of code, which includes one or more executable instructions for implementing a specified logical function(s).

[0040] It should also be noted that in some alternative embodiments, the functions annotated in the boxes may not appear in the order indicated by the annotations in the figures. For example, depending on the functions involved, two boxes shown consecutively may actually be performed substantially simultaneously, or these boxes may sometimes be performed in reverse order. It is conceivable that other steps and methods are functionally, logically, or effectively equivalent to one or more boxes or portions thereof in the illustrated figures.

[0041] While various arrow and line types may be used in flowcharts and / or block diagrams, understanding them does not limit the scope of the corresponding embodiments. In fact, some arrows or other connectors may be used solely to indicate the logical flow of the depicted embodiments. For example, arrows may indicate waiting or monitoring periods of unspecified duration between enumerated steps in a depicted embodiment. It will also be noted that each block in the block diagrams and / or flowcharts, as well as combinations of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system performing a specific function or operation, or by a combination of dedicated hardware and code.

[0042] The description of the elements in each figure can be referenced to the elements in the preceding figures. Throughout all figures, the same reference numerals refer to the same elements, including alternative embodiments of the same elements.

[0043] Figure 1 An embodiment of a wireless communication system 100 for model-based predictive interference management is depicted. In one embodiment, the wireless communication system 100 includes a remote unit 102 and a network unit 104. Although Figure 1 A specific number of remote units 102 and network units 104 are depicted, but those skilled in the art will recognize that any number of remote units 102 and network units 104 can be included in the wireless communication system 100.

[0044] In one embodiment, remote unit 102 may include computing devices such as desktop computers, laptop computers, personal digital assistants (“PDAs”), tablet computers, smartphones, smart TVs (e.g., internet-connected televisions), set-top boxes, game consoles, security systems (including security cameras), in-vehicle computers, network devices (e.g., routers, switches, modems), aircraft, drones, etc. In some embodiments, remote unit 102 includes wearable devices such as smartwatches, fitness bands, optical head-mounted displays, etc. Furthermore, remote unit 102 may be referred to as a subscriber unit, mobile device, mobile station, user, terminal, mobile terminal, fixed terminal, subscriber station, UE, user terminal, device, or other terms used in the art. Remote unit 102 may communicate directly with one or more network units 104 via UL communication signals. In some embodiments, remote unit 102 may communicate directly with other remote units 102 via sidelink communication.

[0045] Network unit 104 may be distributed across a geographical area. In some embodiments, network unit 104 may also be referred to as an access point, access terminal, base station, base station, node-B, eNB, gNB, home node-B, relay node, device, core network, air server, radio access node, AP, NR, network entity, AMF, UDM, UDR, UDM / UDR, PCF, RAN, NSSF, AS, NEF, key management server, KMF, middleware device, middleware entity, middleware function, NR, subscription management, subscription management function, conflict mitigation, conflict mitigation function, IM xAPP, near-RT RIC, non-RT RIC, service and / or management plane, near-RT TRIC framework function, or any other terminology used in the art and / or herein. Network unit 104 is typically part of a radio access network that includes one or more controllers communicatively coupled to one or more corresponding network units 104. The radio access network is typically communicatively coupled to one or more core networks, which may be coupled to other networks such as the Internet and the public switched telephone network. These and other components of the radio access and core network are not illustrated, but are generally well known to those skilled in the art.

[0046] In one implementation, the wireless communication system 100 conforms to the standardized NR protocol in 3GPP, wherein network unit 104 transmits over DL using an OFDM modulation scheme, and remote unit 102 transmits over UL using an SC-FDMA scheme or an OFDM scheme. However, more generally, the wireless communication system 100 may implement other open or proprietary communication protocols, such as WiMAX, IEEE 802.11 variants, GSM, GPRS, UMTS, LTE variants, CDMA2000, Bluetooth®, ZigBee, Sigfoxx, and other protocols. This disclosure is not intended to limit implementation to any particular wireless communication system architecture or protocol.

[0047] Network unit 104 can serve multiple remote units 102 within a service area, such as a cell or cell sector, via a wireless communication link. Network unit 104 transmits DL communication signals to serve the remote units 102 in the time, frequency, and / or spatial domains.

[0048] In various embodiments, network unit 104 may receive modeling information corresponding to a device, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model. In some embodiments, network unit 104 may determine a predictive inter-cell interference management strategy for the device based on the modeling information. In some embodiments, network unit 104 may provide the device with a predictive inter-cell interference management strategy. Therefore, network unit 104 can be used for model-based predictive interference management.

[0049] In some examples, network unit 104 may receive at least one monitoring report from a device. In various embodiments, network unit 104 may determine monitoring event reports based on subscriptions and at least one monitoring report. In some embodiments, network unit 104 may provide monitoring event reports to an application. Therefore, network unit 104 can be used for model-based predictive interference management.

[0050] In some embodiments, network unit 104 may send at least one monitoring report. In various embodiments, network unit 104 may receive information corresponding to a predicted inter-cell interference management strategy in response to sending at least one monitoring report. Therefore, network unit 104 can be used for model-based predicted interference management.

[0051] In various embodiments, network unit 104 may send an initial configuration. In some embodiments, network unit 104 may receive a request for modeling information in response to sending the initial configuration. In some embodiments, network unit 104 may send modeling information in response to receiving the request, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model. Therefore, network unit 104 can be used for model-based predictive interference management.

[0052] In some examples, network unit 104 may receive a predictive resource management policy from at least one application. In various embodiments, network unit 104 may determine at least one radio parameter corresponding to the predictive resource management policy. In some embodiments, network unit 104 may transmit at least one radio parameter based on the predictive resource management policy to a device. Therefore, network unit 104 can be used for model-based predictive interference management.

[0053] Figure 2An embodiment of a device 200 that can be used for model-based predictive interference management is depicted. Device 200 includes one embodiment of a remote unit 102. Furthermore, the remote unit 102 may include a processor 202, a memory 204, an input device 206, a display 208, a transmitter 210, and a receiver 212. In some embodiments, the input device 206 and the display 208 are combined into a single device, such as a touchscreen. In some embodiments, the remote unit 102 may not include any input device 206 and / or display 208. In various embodiments, the remote unit 102 may include one or more of the processor 202, memory 204, transmitter 210, and receiver 212, and may not include the input device 206 and / or display 208.

[0054] In one embodiment, processor 202 may include any known controller capable of executing computer-readable instructions and / or performing logical operations. For example, processor 202 may be a microcontroller, microprocessor, central processing unit (“CPU”), graphics processing unit (“GPU”), auxiliary processing unit, field-programmable gate array (“FPGA”), or similar programmable controller. In some embodiments, processor 202 executes instructions stored in memory 204 to perform the methods and routines described herein. Processor 202 is communicatively coupled to memory 204, input device 206, display 208, transmitter 210, and receiver 212.

[0055] In one embodiment, memory 204 is a computer-readable storage medium. In some embodiments, memory 204 includes volatile computer storage media. For example, memory 204 may include RAM, including dynamic RAM (“DRAM”), synchronous dynamic RAM (“SDRAM”), and / or static RAM (“SRAM”). In some embodiments, memory 204 includes non-volatile computer storage media. For example, memory 204 may include a hard disk drive, flash memory, or any other suitable non-volatile computer storage device. In some embodiments, memory 204 includes both volatile and non-volatile computer storage media. In some embodiments, memory 204 also stores program code and associated data, such as an operating system or other controller algorithms operating on remote unit 102.

[0056] In one embodiment, input device 206 may include any known computer input device, including a touchpad, button, keyboard, stylus, microphone, etc. In some embodiments, input device 206 may be integrated with display 208, for example, as a touchscreen or similar touch-sensitive display. In some embodiments, input device 206 includes a touchscreen, allowing text to be entered using a virtual keyboard displayed on the touchscreen and / or by handwriting on the touchscreen. In some embodiments, input device 206 includes two or more distinct devices such as a keyboard and a touch panel.

[0057] In one embodiment, display 208 may include any known electronically controllable display or display device. Display 208 may be designed to output visual, auditory, and / or tactile signals. In some embodiments, display 208 includes an electronic display capable of outputting visual data to a user. For example, display 208 may include, but is not limited to, LCD displays, LED displays, OLED displays, projectors, or similar display devices capable of outputting images, text, etc., to a user. As another non-limiting example, display 208 may include wearable displays such as smartwatches, smart glasses, head-up displays, etc. Furthermore, display 208 may be a component of a smartphone, personal digital assistant, television, desktop computer, laptop computer, personal computer, vehicle dashboard, etc.

[0058] In some embodiments, display 208 includes one or more speakers for generating sound. For example, display 208 may generate an audible alarm or notification (e.g., a buzzer or beep). In some embodiments, display 208 includes one or more haptic devices for generating vibration, motion, or other haptic feedback. In some embodiments, all or part of display 208 may be integrated with input device 206. For example, input device 206 and display 208 may form a touchscreen or similar touch-sensitive display. In other embodiments, display 208 may be positioned near input device 206.

[0059] In some embodiments, transmitter 210 may be used to transmit the information described herein and / or receiver 212 may be used to receive the information described herein.

[0060] Although only one transmitter 210 and one receiver 212 are illustrated, the remote unit 102 may have any suitable number of transmitters 210 and receivers 212. The transmitters 210 and 212 may be of any suitable type. In one embodiment, the transmitters 210 and 212 may be part of a transceiver. In some embodiments, the transmitter 210 may refer to sending or providing data via software communication (or transmission). In various embodiments, the receiver 212 may refer to receiving data via software communication or a software receiver.

[0061] Figure 3 An embodiment of a device 300 that can be used for model-based predictive interference management is depicted. Device 300 includes one embodiment of a network unit 104. Furthermore, network unit 104 may include a processor 302, a memory 304, an input device 306, a display 308, a transmitter 310, and a receiver 312. As will be understood, processor 302, memory 304, input device 306, display 308, transmitter 310, and receiver 312 may be substantially similar to processor 202, memory 204, input device 206, display 208, transmitter 210, and receiver 212 of remote unit 102, respectively.

[0062] In some embodiments, receiver 312 may receive modeling information corresponding to the device, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model. In various embodiments, processor 302 may: determine a predicted inter-cell interference management strategy for the device based on the modeling information; and provide the predicted inter-cell interference management strategy to the device.

[0063] In some embodiments, receiver 312 may receive at least one monitoring report from the device. In various embodiments, processor 302 may: determine a monitoring event report based on the subscription and at least one monitoring report; and provide the monitoring event report to the application.

[0064] In one embodiment, transmitter 310 may transmit at least one monitoring report. In some embodiments, receiver 312 may receive information corresponding to a predicted inter-cell interference management strategy in response to the transmission of at least one monitoring report.

[0065] In various embodiments, transmitter 310 may transmit an initial configuration. In some embodiments, receiver 312 may receive a request for modeling information in response to transmitting the initial configuration. In some embodiments, transmitter 310 may transmit modeling information in response to receiving a request, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model.

[0066] In some embodiments, receiver 312 may receive a predictive resource management policy from at least one application. In some embodiments, processor 302 may determine at least one radio parameter corresponding to the predictive resource management policy. In various embodiments, transmitter 310 may transmit at least one radio parameter based on the predictive resource management policy to a device.

[0067] Some of the embodiments described herein can be used to proactively minimize the impact of inter-cell interference in densely virtualized small cell co-channel deployments.

[0068] In some embodiments, such as in 5G RAN, UDN can pose interference challenges. In various embodiments, a variety of factors can influence how interference management is handled: the widespread use of beamforming; UL and / or DL ​​cross-interference for TDD; novel communication modes (e.g., self-backhaul, cellular-assisted D2D); and stringent application requirements (e.g., for latency-critical applications).

[0069] In some embodiments, RAN CP (e.g., RRM) functionality and UP for SDN can be separated, such as in 5G architectures. In such embodiments, interference management RRM functionality can be a key enabler for this separation to improve network flexibility and agility. However, challenges may exist that complicate complete separation (e.g., tight coupling of CP and UP in the RAN). For example, real-time scheduling (or fast RRM) functionality can be used according to TTI scheduling, while interference management (e.g., it can reside at an edge cloud platform) is applied in near real-time (e.g., 10-100ms). In this example, real-time scheduling decisions can be provided to the IM functionality to adapt to policies. In some embodiments, such as in virtualized cluster RAN systems, facilitating up-to-date IM decisions can be challenging due to timing and / or backhaul requirements.

[0070] In various embodiments, data analytics (e.g., diagnostics and / or prescriptive analysis) can be used to enhance the performance of interference mitigation techniques and allow decisions to be made at a semi-centralized entity without using real-time feedback from the involved RAN nodes. In such embodiments, the selection of UL power control parameters (e.g., fractional versus fully compensated power control) and / or temporal interference coordination for an optimal number of blank subframes can be performed. Predictive analytics can support decisions regarding configurations for initial parameter settings (e.g., considering potential load increases due to group mobility). Therefore, using data analytics can improve resource utilization efficiency and / or reduce the need for frequent parameter adjustments.

[0071] The various embodiments described herein can be examples of methods for minimizing inter-cell interference in clustered virtualized RAN deployments while preserving signaling load and / or low complexity.

[0072] In some embodiments, the RRM algorithm for cellular networks can be used to facilitate the efficient use of available radio resources and provide mechanisms that enable E-UTRAN and / or 5GS to meet radio resource-related requirements. In such embodiments, RRM can provide means of managing (e.g., assigning, reassigning, and / or releasing) radio resources for single and / or multi-cell systems.

[0073] In some embodiments, inter-cell interference management can be an RRM function that can reside at the BS or in a cloud platform for a cluster used by access nodes (e.g., C-RAN). Interference management can take different forms, such as: 1) interference cancellation and / or randomization (e.g., related to physical layer enhancements to cancel interference); 2) interference avoidance and / or coordination (e.g., ICIC, eICIC, and / or FeICIC); and / or 3) interference cooperation (e.g., coordinated multi-point TX and / or RX).

[0074] As can be understood, if the virtualization of radio resource management allows RRM functions to be placed in different entities, such as centralized RRM, distributed RRM, and semi-centralized RRM, then different implementations of the RRM algorithm can exist.

[0075] In centralized RRM, RRM functions operate together across entities used by multiple access nodes in a group. This provides fast and simple interaction between RRM functions; however, in HetNet, ideal backhaul can be used for some fast RRM functions (e.g., CoMP, DRA). Furthermore, signaling overhead can be very high in ultra-dense environments. Additionally, for 5G systems, various embodiments can use controllers for clusters of HetNet using cloud-based resource pooling and management (e.g., cloud-RAN, C-RAN). As can be understood, resource pooling and centralized resource management can provide high capacity gains. Nevertheless, this may require ideal backhaul and / or fronthaul, and DRA may be challenging in some environments where interference from other C-RAN clusters may exist.

[0076] In distributed RRM, such as those used in 3GPP LTE and / or LTE-A, the RRM functions reside at the eNB. The main RRM functions relate to DRA, ICIC, CMC, RAC, RBC, energy efficiency, and LB. In an LTE RRM architecture, interactions may occur between RRM functions. In one example, there may be cell turn-on and / or turn-off functions that may use inputs from resource constraints due to interference management, and there may be outputs that use handovers that may affect the CMC and LB. Because the main functions reside at the eNB, there may not be additional signaling specified in 3GPP for RRM interactions.

[0077] In semi-centralized RRM, the focus can be on centralized disturbance management and load balancing, as well as distributed fast RRM functionality. One challenge with semi-centralized RRM is the additional signaling and complexity that may arise from interactions across various RAN nodes.

[0078] O-RAN involves the virtualization of access domains and control functions (e.g., RRC and / or RRM) to the RIC, which may be quasi-co-located with gNBs or may be deployed for gNB clusters. As can be understood, RRM and / or RRC functions can be flexibly located at CUs and / or DUs or at dedicated RIC controllers (e.g., near RT RICs and non-RT RICs).

[0079] Figure 4 This is a diagram illustrating one embodiment of a system 400 for interference management. System 400 may operate using O-RAN and / or near-RT-RIC architectures.

[0080] As used in this article, non-RT RIC can refer to logical functions that enable non-real-time control and optimization of RAN elements and resources, including AI and / or ML workflows for model training and updates, and policy-based guidance for the application and / or features in near-RT RICs.

[0081] Furthermore, as used herein, near-RT RIC and framework functions can refer to logical functions that enable near real-time control and optimization of RAN elements and resources through fine-grained (e.g., UE-based, cell-based) data collection and actions via E2 interfaces. Near-RT RICs may include near-RT RIC foundation and / or framework functions that may include subscription management, conflict mitigation, and E2T.

[0082] Furthermore, as used herein, conflict management and / or mitigation functions can be part of a near-RT RIC and can be used to avoid conflicting control messages from different xAPPs. Based on the output of conflict mitigation, E2T can generate only one valid control message on a single E2 interface.

[0083] Additionally, as used in this article, the subscription management function can refer to the function of xAPP subscriptions controlling E2 nodes. The subscription management function can merge identical subscriptions from different xAPPs. Based on the output of the subscription management function, E2T can generate only a single message to send to the E2 node.

[0084] Additionally, as used herein, xApp can refer to an application designed to run on a near-RT RIC. An application may include one or more microservices, and, where applicable, may be identified as to which data it consumes and which data it provides. The application may be independent of the near-RT RIC and may be provided by a third party. E2 can enable direct association between xApp and RAN functions.

[0085] Furthermore, as used in this document, A1 (or O1) may refer to the interface between non-RT RIC and near-RT RIC to enable policy-driven guidance for near-RT RIC applications and / or functions, and may support AI and / or ML workflows.

[0086] Additionally, as used in this article, E2 can refer to the interface connecting the near-RT RIC and NR.

[0087] In addition, as used in this article, an E2 node can refer to a logical node that terminates the E2 interface (e.g., an NR node like an O-CU-CP, O-CU-UP, O-DU, or a virtualized eNB).

[0088] Furthermore, as used in this article, an open API can refer to a definition within the near-RT RIC and / or can be an interface between framework functionality and xAPP.

[0089] Figure 4 System 400 includes a service and / or management plane 402, a near-RT RIC 404, and an NR system 406. The service and / or management plane 402 communicates with the near-RT RIC 404 via an A1 interface 408. Furthermore, the near-RT RIC 404 communicates with the NR system 406 via an E2 interface 410. The service and / or management plane 402 includes a non-RT RIC 412 and a configuration 414. The configuration 414 may include policy, inventory, and / or design information.

[0090] The near-RT RIC 404 includes an A1T 416 (or O1T), which can be a logical node terminating the A1 interface 408. The near-RT RIC 404 also includes multiple xAPPs 418 that communicate with the A1T 416 via a first open API 420. The xAPPs 418 include a first xAPP 422, a second xAPP 424, a third xAPP 426, and a fourth xAPP 428. The near-RT RIC 404 also includes near-RT RIC framework functionality 430. Near-RT RIC framework functionality 430 communicates with the xAPPs 418 via a second open API 432. Additionally, near-RT RIC framework functionality 430 includes subscription management functionality 434, conflict mitigation functionality 436, and a database 438. The near-RT RIC 404 further includes an E2T 440, which can be a logical node terminating the E2 interface 410 and enables communication between components of the near-RT RIC 404 and NR 406.

[0091] This document describes various embodiments for configuring a set of RAN nodes, supported by trained service and mobility AI and / or ML models, to represent resource allocation strategies and / or inter-cell interference-aware resource allocation strategies on top of these resource allocation strategies. About Figure 5 An example is described.

[0092] Figure 5 This is a diagram illustrating another embodiment of a system 500 for interference management. System 500 includes a service and / or management plane 502, a near-RT RIC 504, and an NR system 506. The service and / or management plane 502 communicates with the near-RT RIC 504 via an A1 interface. Furthermore, the near-RT RIC 504 communicates with the NR system 506 via an E2 interface. The service and / or management plane 502 includes a non-RT RIC 508 and a configuration 510. The configuration 510 may include policy, inventory, and / or design information.

[0093] The near-RT RIC 504 includes an A1T 512 (or O1T), which can be a logical node terminating the A1 interface. The near-RT RIC 504 also includes multiple xAPPs 514 that communicate with the A1T 512 via an open API. These xAPPs 514 include a first xAPP 516, a second xAPP 518 (e.g., an IM xAPP), a third xAPP 520, and a fourth xAPP 522. The near-RT RIC 504 also includes near-RT RIC framework functionality 524. This near-RT RIC framework functionality 524 communicates with the xAPPs 514 via an open API. Additionally, the near-RT RIC framework functionality 524 includes subscription management functionality 526, conflict mitigation functionality 528, and a database 530. The near-RT RIC 504 further includes an E2T 532, which can be a logical node terminating the E2 interface and enables communication between the components of the near-RT RIC 504 and NR 506. System 500 may also include middleware entity 534 to facilitate communication between NR 506 and near-RT RIC 504.

[0094] In the first communication 536 from the service and / or management plane 502 to the second xAPP 518, the second xAPP 518 initially receives an IM configuration policy (e.g., initial configuration of the policy) from the service and / or management plane 502, including: a list of available IM metrics (e.g., ICIC, eICIC, CoMP 1, CoMP 2), thresholds and / or criteria for access and BH metrics to support the selection and / or updating of the IM policy, preferences, whether the policy can be enforced by the second xAPP 518, recommendations, coverage time and / or coverage area. The IM configuration policy can be vertical-specific (e.g., V2X, IIoT) or a general configuration for all verticals using RAN resources. If the same RAN node is controlled, this IM configuration policy can provide the necessary interactions within the xAPP for both intra-vertical and cross-vertical scenarios.

[0095] In the second communication 538 transmitted between the subscription management function 526 and the second xAPP 518, in response to receiving the IM configuration policy, the second xAPP 518 subscribes to receive UE monitoring events, RAN monitoring events and / or measurements for the set of cells indicated in the first communication 536.

[0096] In the third communication 540 sent from NR 506 to the second xAPP 518, the second xAPP 518 receives a trigger event based on the subscription received in the second communication 538 indicating that the UE performance metric and / or RAN performance metric has changed (e.g., resource overload, QoS degradation). This trigger event can be provided by NR 506 or directly by middleware entity 534 based on real-time radio measurements.

[0097] In a fourth communication 542 transmitted between the service and / or management plane 502 and the second xAPP 518, in response to receiving a trigger event, the second xAPP 518 requests and receives a trained AI model for service and / or mobility predictions for each cell or for one or more UEs within a set of cells indicated at the trigger event. Such service and / or mobility predictions may include the expected performance distribution of the RAN or selected UEs within a predefined time window (e.g., 10 ms to 1 s).

[0098] The second xAPP 518 determines an IM policy (e.g., to be enforced or to be used as a recommendation) for the set of cells as indicated by the triggering event. The criterion for selecting a particular IM policy is the predicted output, and it can be determined whether the expected metric is within a threshold as set in the first communication 536. A particular IM policy may be a policy that can be applied to a future given time window (e.g., for the next 1 second) based on the predicted output.

[0099] In the fifth communication 544 sent between the conflict mitigation function 528 and the second xAPP 518, the second xAPP 518 may verify and / or check the feasibility of the IM policy with the support of a common control function used to authorize the IM policy request.

[0100] In the sixth communication 546, from the second xAPP 518 to the NR 506, the second xAPP 518 sends the IM policy directly or via middleware entity 534 to the respective RAN node of the NR 506. If real-time radio parameters are required, the use of middleware entity 534 can relax the constraints of dynamic IM policies (e.g., CoMP) by converting the IM policy into precise radio parameters (e.g., RB silence). Middleware entity 534 may be part of the near-RT RIC 504 or may be deployed as a quasi-co-located agent with the CU and / or gNB.

[0101] Figure 6This diagram illustrates one embodiment of communication 600 for interference management. In this embodiment, an implementation oriented towards an O-RAN architecture is provided. In this architecture, external applications take the form of IM xAPP. The communication 600 includes communication between non-RT RIC 602 (e.g., a service and / or management plane, received by a near-RT RIC at A1 termination), IM xAPP 604 (e.g., an external application), conflict mitigation 606 (e.g., a conflict mitigation function, which may be located near the RT RIC), subscription management 608 (e.g., a subscription management function, which may be located near the RT RIC), and NR 610 (e.g., E2T, E2 nodes, CU, DU, RAN nodes). The communication 600 described herein may each include one or more messages.

[0102] In the first communication 612 from non-RT RIC 602 to IM xAPP 604, IM xAPP 604 may receive interference management policy messages (e.g., from non-RT RIC via A1T and via an open API between IM xAPP 604 and A1T). Interface management policy messages may include: cell ID; network slice ID; service type, application type, and / or application profile (e.g., these may be vertically related); a list of policy IDs (e.g., policy 1: ICIC scheme 1 (e.g., FFR); policy 2: ICIC scheme 2 (e.g., SFR); policy 3: eICIC scheme; policy 4: CoMP scheme 1 (e.g., CS, CB); policy 5: CoMP scheme 2 (e.g., coherent JT, coherent JR); policy 6: CoMP scheme 2 (e.g., incoherent JT, incoherent JR)); and per-policy thresholds (e.g., O-RAN cell computed load). O-CU load; O-DU load; RAN allowed latency; per-policy backhaul requirement; minimum and / or maximum UE density; radio resource load); interference management preferences include what is included (e.g., cell ID list; resource pool ID; policy preferences for the cell list (e.g., should, preferred, avoid, prohibit); policy priorities for the cell list (e.g., should, preferred, avoid, prohibit); enforcement flags (e.g., enforce policy or not enforce policy); time validity; coverage area; per-vertical parameters (e.g., priority, spectrum considerations, spectrum limits, isolation level, per-vertical small cell dedicated clusters in the same vertical xAPP); and / or cross-vertical parameters (e.g., priority, spectrum considerations, spectrum limits, isolation level, per-vertical (for all vertical) small cell clusters in the xAPP within the vertical).

[0103] In a second communication 614 transmitted between IM xAPP 604 and subscription management 608, IM xAPP 604 subscribes to the near-RT RIC from subscription management 608 to periodically receive RAN monitoring events, UE monitoring events, and / or measurements (e.g., RAN and / or UE). Subscription management 608 provides requests to the RAN node (e.g., this could be a combined request from more than one xAPP-like application). Such monitored events and / or measurements may include: radio resource utilization (e.g., DL and / or UL total PRB usage and / or distribution of usage, DL and / or UL PRB for data services); DRB-related measurements (e.g., the number of successfully established DRBs, DRB session activity time); CQI-related measurements (e.g., broadband CQI distribution); MCS-related measurements; QoS maintainability; KPI monitoring; RAN UE-wide KPI monitoring; latency DL and / or UL air interface average and distribution; NG-RAN handover success rate monitoring; number of requested handover resource allocations; and / or number of successful handover resource allocations.

[0104] NR 610 detects RAN or UE monitoring event 616.

[0105] In the third communication 618, transmitted from NR 610 to IM xAPP 604, RAN or UE monitoring events are received by IM xAPP 604 based on monitoring subscriptions subscribed in the second communication 614 (e.g., radio resource load > X% for cell 1). This event can be provided directly from the E2 node or via other frameworks such as E2T and / or near-RT RIC functionality. Information indicating RAN or UE monitoring events may include: cell ID; UE ID; network slice ID; resource ID; resource pool ID; UEQoE degradation indication; QoS degradation indication; high resource load indication; high RAN latency indication; low backhaul resource availability indication; QoS fluctuation indication; and / or radio link failure indication.

[0106] In the fourth communication 620 sent from IM xAPP 604 to nonRT RIC 602, IM xAPP 604 sends a request for modeling information (e.g., a traffic prediction model message and / or a mobility prediction model request message) to nonRT RIC 602 for all or selected UEs in a given area (e.g., cell edge, from point A to point B). If the monitoring event is a UE monitoring event, this can be applied to the model of the selected UE.

[0107] In the fifth communication 622, which is transmitted from the non-RT RIC 602 to the IM xAPP 604, the IM xAPP 604 receives modeling information (e.g., business prediction model reports and / or mobility prediction model reports of trained AI and / or ML models) from the non-RT RIC 602. In some embodiments, the fifth communication 622 may be transmitted from the non-RT RIC 602 to the IM xAPP 604, and in other embodiments, the modeling information may instead be stored in a near-RT RIC database and retrieved by the IM xAPP 604. Modeling information may include: expected RAN resource conditions (e.g., channel statistics distribution over the entire area with high and low points) within a time period (e.g., 10 ms to 1 sec, predefined, configured, pre-configured) based on configuration and / or prediction accuracy; expected radio BH resource conditions (e.g., channel statistics distribution of the involved BH links) within a time period based on configuration and / or prediction accuracy; expected UE mobility parameters, expected UE location information, and / or expected UE trajectories (e.g., anonymized) and / or prediction accuracy for UEs in a geographic area; expected performance metrics and / or prediction accuracy for UEs in a geographic area, and the expected distribution of any of the above within a time period; confidence level metrics for any of the above within a time period, and / or the expected sequence of inter-cell handovers for UEs in a geographic area.

[0108] IM xAPP 604 determines a new IM policy for the affected RAN node 624. This can be a predefined policy based on thresholds from the first communication 612 and / or prediction information from the fifth communication 622. The determination can take into account predicted performance metrics (e.g., prediction accuracy as well) and can also check whether these metrics meet the thresholds set from the first communication 612. IM xAPP 604 can select an IM policy that will result in a higher preference and / or priority for performance optimization based on IM policy preferences from the first communication 612 (e.g., CoMP is a higher priority than ICIC).

[0109] In the sixth communication 626, sent from IM xAPP 604 to conflict mitigation 606, IM xAPP 604 sends an updated IM policy request message to conflict mitigation 606. The updated IM policy request message may include: cell ID; network slice ID; CU ID; DU ID; current policy ID; new policy ID; enforcement flag; time validity; and / or coverage area.

[0110] In the seventh communication 628, which is sent from the conflict mitigation 606 to the IM xAPP 604, the IM xAPP 604 receives a response (e.g., ACK, NACK) from the conflict mitigation 606.

[0111] In the eighth communication 630 from IM xAPP 604 to NR 610, IM xAPP 604, based on successful ACK reception, provides the affected RAN nodes with a new IM policy using an updated IM policy message. The updated IM policy message includes: cell ID; network slice ID; CU ID; DU ID; current policy ID; new policy ID; enforcement flag; time validity; coverage area; and / or per-IM policy parameters (e.g., OI, HII, RNTP, ABS pattern information, CoMP coordination area, CoMP scheme, and resource constraints (e.g., in the time, frequency, and / or spatial domains)).

[0112] Figure 7 This is a diagram illustrating another embodiment of a communication 700 for interference management. In this embodiment, an implementation oriented towards an O-RAN architecture is provided. In this architecture, the external application takes the form of an IM xAPP, and middleware functionality is used. The use of middleware functionality can reduce and / or alleviate potentially high loads on the IM xAPP (e.g., if the xAPP receives all radio-related measurements and / or events and may be aware of low-level real-time configuration). As described herein, the middleware functionality can be deployed as a near-RT RIC function or as a quasi-co-located proxy on the RAN side and can: receive UE and / or RAN monitoring reports and can translate them into IM xAPP-aware behaviors and / or events (e.g., high load indications, RAN UE KPIs reaching low thresholds) – this can be used in embodiments where UE-related measurements may not be exposed to the xAPP, but only abstract events can be provided to the xAPP as updated control messages; and receive requested updated IM policies and translate them into precise radio parameters to be used based on real-time radio conditions – this may enable the IMXAPP to be aware only of the high-level policies to be applied, rather than the radio parameters that need to be updated.

[0113] Communication 700 includes communication between non-RT RIC 702 (e.g., service and / or management plane, received by a near RT RIC at the A1 termination), IM xAPP 704 (e.g., external application), conflict mitigation 706 (e.g., conflict mitigation function, which may be located near the RT RIC), subscription pipe 710 (e.g., middleware entity), and NR 712 (e.g., E2T, E2 node, CU, DU, RAN node). Each of the communication 700 described herein may include one or more messages.

[0114] In the first communication 714 from the non-RT RIC 702 to the IM xAPP 704, the IM xAPP 704 may receive interference management policy messages (e.g., from the non-RT RIC via A1T and via the open API between the IM xAPP 704 and the IM xAPP 704). Interface management policy messages may include: cell ID; network slice ID; service type, application type, and / or application profile (e.g., these may be vertically related); a list of policy IDs (e.g., policy 1: ICIC scheme 1 (e.g., FFR); policy 2: ICIC scheme 2 (e.g., SFR); policy 3: eICIC scheme; policy 4: CoMP scheme 1 (e.g., CS, CB); policy 5: CoMP scheme 2 (e.g., coherent JT, coherent JR); policy 6: CoMP scheme 2 (e.g., incoherent JT, incoherent JR)); per-policy thresholds (e.g., O-RAN cell computation load; O-CU load; O-DU load; RAN allowance). Allowed latency; backhaul requirements for each policy; minimum and / or maximum UE density; radio resource load); interference management preferences include what is indicated (e.g., cell ID list; resource pool ID; policy preferences for the cell list (e.g., should, preferred, avoid, prohibit); policy priorities for the cell list (e.g., will, preferred, avoid, prohibit); enforcement flags (e.g., enforce policy or not enforce policy); use of middleware flags (e.g., use or not use); middleware ID; middleware address; time validity; coverage area; per-vertical parameters (e.g., priority, spectrum considerations, spectrum limits, isolation level, per-vertical small cell dedicated clusters in the same vertical xAPP); and / or cross-vertical parameters (e.g., priority, spectrum considerations, spectrum limits, isolation level, per-vertical (for all vertical) small cell clusters in the vertical xAPP).

[0115] In the second communication 716 sent between IM xAPP 704 and subscription management 708, IM xAPP 704 subscribes to the near RT RIC from subscription management 708 to periodically receive RAN monitoring events, UE monitoring events, and / or measurements (e.g., RAN and / or UE). Subscription management 708 provides requests to the RAN node (e.g., this could be a merge request from more than one xAPP-like application). Monitoring and / or measurement of such events may include: radio resource utilization (e.g., total PRB usage and / or distribution of usage for DL ​​and / or UL, DL and / or UL PRBs for data services); DRB-related measurements (e.g., the number of successfully established DRBs, the session activity time of DRBs); CQI-related measurements (e.g., broadband CQI distribution); MCS-related measurements; QoS maintainability; KPI monitoring; RAN UEs with KPI monitoring across the board; average and distribution of delays on DL and / or UL air interfaces; NG-RAN handover success rate monitoring; the number of requested handover resource allocations; the number of successful handover resource allocations; and / or the configuration of middleware IDs and triggering events (e.g., which may be per vertical application or for all vertical applications).

[0116] In an optional third communication 718 sent between subscription management 708 and middleware 710, subscription management 708 may provide middleware 710 with a request for events and / or other information related to the subscription corresponding to the second communication 716.

[0117] In the fourth communication 720, which is transmitted from NR 712 to middleware 710, middleware 710 receives a monitoring report from NR 712. This monitoring report may include: cell ID; UE ID; network slice ID; resource ID; resource pool ID; UE QoE degradation indication; QoS degradation indication; high resource load indication; high RAN latency indication; low backhaul resource availability indication; QoS fluctuation indication; and / or radio link failure indication.

[0118] Middleware 710 can transform monitoring reports 722 into monitoring events based on subscription information and real-time analytics.

[0119] In the fifth communication 724 sent from middleware 710 to IM xAPP 704, if conditions are met (e.g., based on thresholds from the first communication 714 and / or monitoring subscriptions), middleware 710 sends a monitoring event report message to IM xAPP 704. This report message may include: cell ID; UE ID; network slice ID; resource ID; resource pool ID; UE QoE degradation indication; QoS degradation indication; high resource load indication; high RAN latency indication; low backhaul resource availability indication; QoS fluctuation indication; bandwidth adaptation requirement, radio resource adaptation requirement, service shifting requirement, and / or radio link failure indication.

[0120] In the sixth communication 726 sent from IM xAPP 704 to nonRT RIC 702, IM xAPP 704 sends a request for modeling information (e.g., a traffic prediction model message and / or a mobility prediction model request message) to nonRT RIC 702 for all or selected UEs in a given area (e.g., cell edge, from point A to point B). If the monitoring event is a UE monitoring event, this can be applied to the model of the selected UE.

[0121] In the seventh communication 728, which is transmitted from the non-RT RIC 702 to the IM xAPP 704, the IM xAPP 704 receives modeling information (e.g., business prediction model reports and / or mobility prediction model reports of trained AI and / or ML models) from the non-RT RIC 702. In some embodiments, the seventh communication 728 may be transmitted from the non-RT RIC 702 to the IM xAPP 704, and in other embodiments, the modeling information may instead be stored in a near-RT RIC database and retrieved by the IM xAPP 704. Modeling information may include: expected RAN resource conditions (e.g., channel statistics distribution over the entire area with high and low points) within a time period (e.g., 10 ms to 1 sec, predefined, configured, pre-configured) based on configuration and / or prediction accuracy; expected radio BH resource conditions (e.g., channel statistics distribution of the involved BH links) within a time period based on configuration and / or prediction accuracy; expected UE mobility parameters, expected UE location information, and / or expected UE trajectories (e.g., anonymized) and / or prediction accuracy for UEs in a geographic area; expected performance metrics and / or prediction accuracy for UEs in a geographic area, and the expected distribution of any of the above within a time period; confidence level metrics for any of the above within a time period, and / or the expected sequence of inter-cell handovers for UEs in a geographic area.

[0122] IM xAPP 704 determines a new IM policy for the affected RAN node 730. This can be a predefined policy based on thresholds from the first communication 714 and / or prediction information from the seventh communication 728. This determination can take into account prediction performance metrics (e.g., prediction accuracy as well) and can also check whether these metrics meet the thresholds set from the first communication 714. IM xAPP 704 can select an IM policy that will result in a higher preference and / or priority for performance optimization based on IM policy preferences from the first communication 714 (e.g., CoMP is a higher priority than ICIC).

[0123] In the eighth communication 732, sent from IM xAPP 704 to conflict mitigation 706, IM xAPP 704 sends an updated IM policy request message to conflict mitigation 706. The updated IM policy request message may include: cell ID; network slice ID; CU ID; DU ID; current policy ID; new policy ID; enforcement flag; time validity; and / or coverage area.

[0124] In the ninth communication 734, which is sent from the conflict mitigation 706 to the IM xAPP 704, the IM xAPP 704 receives a response (e.g., ACK, NACK) from the conflict mitigation 706.

[0125] In the tenth communication 736, from IM xAPP 704 to middleware 710, IM xAPP 704, based on the successful receipt of the ACK, provides a new IM policy to middleware 710 with an updated IM policy message. The updated IM policy message includes: cell ID; network slice ID; CU ID; DU ID; current policy ID; new policy ID; enforcement flag; time validity; coverage area; and / or per-IM policy parameters (e.g., OI, HII, RNTP, ABS pattern information, CoMP coordination area, CoMP scheme, resource limits (e.g., in the time, frequency, and / or spatial domains)).

[0126] The middleware 710 checks the real-time radio resource conditions of the RAN nodes involved (738) and derives the policy parameters to be provided to the RAN nodes.

[0127] In the eleventh communication 740, which is transmitted from middleware 710 to NR 712, middleware 710 sends the IM policy parameters of the application message to NR 712. The IM policy parameters of the application message may include: cell ID; UE ID; resource ID; resource pool ID; and / or per-IM policy parameters (e.g., OI, HII, RNTP, ABS pattern information, CoMP coordination area, CoMP scheme, and resource limits (e.g., in the time, frequency, and / or spatial domains)).

[0128] Figure 8 This is a flowchart illustrating one embodiment of a model-based predictive interference management method 800. In some embodiments, method 800 is executed by a device, such as network unit 104. In some embodiments, method 800 may be executed by a processor that executes program code, such as a microcontroller, microprocessor, CPU, GPU, auxiliary processing unit, FPGA, etc.

[0129] In various embodiments, method 800 includes receiving 802 modeling information corresponding to a device, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model. In some embodiments, method 800 includes determining 804 a predicted inter-cell interference management strategy for the device based on the modeling information. In some embodiments, method 800 includes providing the predicted inter-cell interference management strategy to device 806.

[0130] In some embodiments, method 800 further includes receiving an initial configuration before determining the predicted inter-cell interference management measurement. In some embodiments, the initial configuration is sent from a serving entity, a management entity, or a combination thereof. In various embodiments, the initial configuration includes a cell identifier, a network slice identifier, a service type, an application type, a profile, a list of policy identifiers, per-policy metrics, per-policy thresholds, interference management preferences, an enforcement flag, a middleware flag, a middleware identifier, a time validity indicator, a geographic region, vertical-specific parameters, cross-vertical parameters, or some combination thereof.

[0131] In one embodiment, the initial configuration is configured per vertical customer. In some embodiments, method 800 further includes obtaining monitoring event reports related to the device. In some embodiments, a predicted inter-cell interference management strategy is determined in response to obtaining the monitoring event reports.

[0132] In various embodiments, monitoring event reports include cell identifiers, user equipment identifiers, network slice identifiers, resource identifiers, resource pool identifiers, user equipment quality of experience degradation indicators, user equipment service quality degradation indicators, high resource load indicators, high radio access network latency indicators, low backhaul resource availability indicators, service quality fluctuation indicators, radio link failure indicators, or combinations thereof. In one embodiment, method 800 further includes subscribing to radio access network nodes, subscribing to functions, or combinations thereof for receiving monitoring event reports. In some embodiments, the device includes at least one network element, at least one user equipment, or a combination thereof.

[0133] In some embodiments, the modeling information includes: a first expectation of radio access network resource conditions within a predefined time period; a second expectation of radio backhaul resource conditions within a predefined time period; a third expectation of user equipment mobility parameters, user equipment location information, or combinations thereof, for user equipment in a geographic area; a fourth expectation of performance metrics for user equipment in a geographic area; the expected distribution of the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; a confidence level metric for the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; the expected probability density function over radio access network resources, backhaul resources, or combinations thereof; the expectation of inter-cell handover sequences for user equipment in a geographic area; or combinations thereof. In various embodiments, the predicted inter-cell interference management strategy is provided to the middleware entity. In one embodiment, the predicted inter-cell interference management policy includes a cell identifier, application identifier, user equipment group identifier, network slice identifier, central unit identifier, distributed unit identifier, current policy identifier, new policy identifier, current service redirection policy identifier (this identifier can be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), new service redirection policy identifier (this can be a service redirection policy updated based on the predicted inter-cell interference management policy), confidence level parameter, enforcement flag, time validity indicator, area indicator, overload indicator, high interference indicator, relative narrowband transmit power, near-blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource constraints, or some combination thereof.

[0134] In some embodiments, method 800 further includes requesting verification of the predicted inter-cell interference management strategy from the conflict mitigation function and receiving a verification response from the conflict mitigation function. In some embodiments, communication is sent and received using an open application programming interface (API). In various embodiments, the A1 interface is used for communication with a service entity, a management entity, or a combination thereof.

[0135] In one embodiment, the E2 interface is used for communication with new radio equipment. In some embodiments, predictive inter-cell interference management strategies are provided to the device via application exposure functionality.

[0136] Figure 9 This is a flowchart illustrating another embodiment of a method 900 for model-based predictive interference management. In some embodiments, method 900 is executed by a device, such as network unit 104. In some embodiments, method 900 may be executed by a processor that executes program code, such as a microcontroller, microprocessor, CPU, GPU, auxiliary processing unit, FPGA, etc.

[0137] In various embodiments, method 900 includes receiving at least one monitoring report from device 902. In some embodiments, method 900 includes determining 904 a monitoring event report based on subscriptions and at least one monitoring report. In some embodiments, method 900 includes providing the monitoring event report to application 906.

[0138] In some embodiments, method 900 further includes: receiving a predicted inter-cell interference management policy from an application; determining at least one radio parameter corresponding to the predicted inter-cell interference management policy; and transmitting at least one radio parameter to a device based on the predicted inter-cell interference management policy. In some embodiments, the predicted inter-cell interference management policy includes a cell identifier, an application identifier, a user equipment group identifier, a network slice identifier, a central unit identifier, a distributed unit identifier, a current policy identifier, a new policy identifier, a current service redirection policy identifier (this identifier may be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), a new service redirection policy identifier (this may be a service redirection policy updated based on the predicted inter-cell interference management policy), a confidence level parameter, an enforcement flag, a time validity indicator, a zone indicator, or some combination thereof. In various embodiments, at least one radio parameter includes overload indication, high interference indication, relatively narrowband transmit power, nearly blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource constraints, parameters for service transition policy updates (handover request indication, source cell identifier, target cell identifier, frequency selection indication, radio access technology selection indication, radio interface selection indication, distributed unit selection indication, central unit selection indication) or some combination thereof.

[0139] In one embodiment, the predicted inter-cell interference management strategy is provided to the device via an application exposure function. In some embodiments, method 900 further includes receiving a subscription request for a subscription from the application. In some embodiments, the monitoring event report includes cell identifier, user equipment identifier, network slice identifier, resource identifier, resource pool identifier, user equipment experience quality degradation indicator, user equipment service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, bandwidth adaptation requirement, radio resource adaptation requirement, service shift requirement, or some combination thereof.

[0140] Figure 10This is a flowchart illustrating yet another embodiment of a model-based predictive interference management method 1000. In some embodiments, method 1000 is executed by a device, such as network unit 104. In some embodiments, method 1000 may be executed by a processor that executes program code, such as a microcontroller, microprocessor, CPU, GPU, auxiliary processing unit, FPGA, etc.

[0141] In various embodiments, method 1000 includes sending 1002 at least one monitoring report. In some embodiments, method 1000 includes receiving information 1004 corresponding to a predicted inter-cell interference management strategy in response to sending at least one monitoring report.

[0142] In some embodiments, at least one monitoring report includes a monitoring event report, which includes a cell identifier, user equipment identifier, network slice identifier, resource identifier, resource pool identifier, user equipment experience quality degradation indicator, user equipment service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, bandwidth adaptation requirement, radio resource adaptation requirement, service shift requirement, or some combination thereof.

[0143] In some embodiments, the predicted inter-cell interference management policy includes a cell identifier, application identifier, user equipment group identifier, network slice identifier, central unit identifier, distributed unit identifier, current policy identifier, new policy identifier, current service redirection policy identifier (this identifier can be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), new service redirection policy identifier (this can be a service redirection policy updated based on the predicted inter-cell interference management policy), confidence level parameter, enforcement flag, time validity indicator, area indicator, overload indicator, high interference indicator, relative narrowband transmit power, near-blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource limit, or some combination thereof. In one embodiment, information corresponding to the predicted inter-cell interference management policy is received from a middleware entity or application.

[0144] Figure 11 This is a flowchart illustrating a further embodiment of a method 1100 for model-based predictive interference management. In some embodiments, method 1100 is performed by a device, such as network unit 104. In some embodiments, method 1100 may be performed by a processor that executes program code, such as a microcontroller, microprocessor, CPU, GPU, auxiliary processing unit, FPGA, etc.

[0145] In various embodiments, method 1100 includes sending 1102 an initial configuration. In some embodiments, method 1100 includes receiving 1104 a request for modeling information in response to sending the initial configuration. In some embodiments, method 1100 includes sending modeling information 1106 in response to receiving the request, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model.

[0146] In some embodiments, the initial configuration is sent to the application. In some embodiments, the initial configuration is sent from a service entity, a management entity, or a combination thereof. In various embodiments, the initial configuration includes a cell identifier, a network slice identifier, a service type, an application type, a profile, a list of policy identifiers, per-policy metrics, per-policy thresholds, interference management preferences, enforcement flags, middleware flags, middleware identifiers, time validity indicators, geographic regions, vertical-specific parameters, cross-vertical parameters, or some combination thereof.

[0147] In one embodiment, the initial configuration is configured according to vertical clients. In some embodiments, the modeling information includes: a first expectation of radio access network resource conditions within a predefined time period; a second expectation of radio backhaul resource conditions within a predefined time period; a third expectation of user equipment mobility parameters, user equipment location information, or combinations thereof, for user equipment in a geographic area; a fourth expectation of performance metrics for user equipment in a geographic area; the expected distribution of the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; a confidence level metric of the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; the expected probability density function of radio access network resources, backhaul resources, or combinations thereof; the expectation of inter-cell handover sequences for user equipment in a geographic area; or combinations thereof.

[0148] Figure 12 This is a flowchart illustrating another embodiment of a model-based predictive interference management method 1200. In some embodiments, method 1200 is executed by a device, such as network unit 104. In some embodiments, method 1200 may be executed by a processor that executes program code, such as a microcontroller, microprocessor, CPU, GPU, auxiliary processing unit, FPGA, etc.

[0149] In various embodiments, method 1200 includes receiving a predictive resource management policy from at least one application 1202. In various embodiments, method 1200 includes determining at least one radio parameter corresponding to the predictive resource management policy at 1204. In some embodiments, method 1200 includes transmitting at least one radio parameter to device 1206 based on the predictive resource management policy.

[0150] In some embodiments, the predictive resource management policy includes an application identifier, a user equipment group identifier, a cell identifier, a network slice identifier, a central unit identifier, a distributed unit identifier, a current inter-cell interference management policy identifier, a new inter-cell interference policy identifier, a current service redirection policy identifier (this identifier may be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), a new service redirection policy identifier (this may be a service redirection policy updated based on the predictive inter-cell interference management policy), a confidence level parameter, an enforcement flag, a time validity indicator, a region indicator, or a combination thereof. In some embodiments, at least one radio parameter includes an overload indicator, a high interference indicator, a relative narrowband transmit power, near-blank subframe pattern information, a coordinated multipoint coordination area, a coordinated multipoint scheme, resource constraints, parameters for the updated service redirection policy (handover request indicator, source cell identifier, target cell identifier, frequency selection indicator, radio access technology selection indicator, radio interface selection indicator, distributed unit selection indicator, central unit selection indicator) or a combination thereof.

[0151] In various embodiments, predictive resource management policies are provided to the device via application exposure functionality. In one embodiment, the device includes at least one network element, at least one user equipment, or a combination thereof. In some embodiments, at least one radio parameter is further determined based on at least one predefined rule corresponding to an application type, service type, or a combination thereof.

[0152] In some embodiments, predefined rules include key performance indicators, service type identifiers, application type identifiers, radio access network identifiers, network slice profiles, service profiles, quality of service objectives (guaranteed traffic bit rate, maximum traffic bit rate, priority level, packet delay budget parameter, reliability parameter, packet error rate parameter), quality of experience objectives (quality of experience score, initial buffer parameter, delay events, delay ratio, average opinion score), priority identifiers, application quality of service to network quality of service mapping information, or some combination thereof.

[0153] In various embodiments, method 1200 further includes: receiving at least one monitoring report from a device; determining a monitoring event report based on the subscription and the at least one monitoring report; and sending the monitoring event report to an application. In one embodiment, method 1200 further includes receiving a subscription request for the subscription from the application.

[0154] In some embodiments, the monitoring report includes user equipment quality of service parameters, user equipment experience quality parameters, radio resource quality parameters, computed radio access network resource load parameters, central unit load, distributed unit load, channel state information, radio resource management measurements, radio link monitoring measurements, received signal strength indicators, reference signal received power parameters, handover fault monitoring parameters, or some combinations thereof.

[0155] In some embodiments, the monitoring report further includes backhaul radio resource quality parameters, backhaul channel state information, backhaul radio resource management measurements, backhaul radio link monitoring measurements, backhaul topology parameters, backhaul type parameters, or combinations thereof. In various embodiments, monitoring event reports are determined based on offline user equipment analysis, online user equipment analysis, radio resource quality analysis, or combinations thereof.

[0156] In one embodiment, the monitoring event report includes cell identifier, user equipment identifier, network slice identifier, resource identifier, resource pool identifier, user equipment experience quality degradation indicator, user equipment service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, bandwidth adaptation requirement, radio resource adaptation requirement, service shift requirement, or some combination thereof.

[0157] In one embodiment, a method includes: receiving modeling information corresponding to a device, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model; determining a predictive inter-cell interference management strategy for the device based on the modeling information; and providing the predictive inter-cell interference management strategy to the device.

[0158] In some embodiments, the method further includes receiving an initial configuration before determining a predicted inter-cell interference management strategy.

[0159] In some embodiments, the initial configuration is sent from a service entity, a management entity, or a combination thereof.

[0160] In various embodiments, the initial configuration includes a cell identifier, network slice identifier, service type, application type, profile, list of policy identifiers, per-policy metric, per-policy threshold, interference management preference, enforcement flag, middleware flag, middleware identifier, time validity indicator, geographic region, vertical-specific parameter, cross-vertical parameter, or some combination thereof.

[0161] In one embodiment, the initial configuration is configured according to a vertical client.

[0162] In some embodiments, the method further includes obtaining monitoring event reports related to the device.

[0163] In some embodiments, the predictive inter-cell interference management strategy is determined in response to receiving a monitoring event report.

[0164] In various embodiments, the monitoring event report includes cell identifier, user equipment identifier, network slice identifier, resource identifier, resource pool identifier, user equipment quality of experience degradation indicator, user equipment service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, or some combination thereof.

[0165] In one embodiment, the method further includes subscribing to a radio access network node, subscribing to a function, or a combination thereof, for receiving monitoring event reports.

[0166] In some embodiments, the device includes at least one network element, at least one user equipment, or a combination thereof.

[0167] In some embodiments, the modeling information includes: a first expectation of radio access network resource conditions within a predefined time period; a second expectation of radio backhaul resource conditions within a predefined time period; a third expectation of user equipment mobility parameters, user equipment location information, or combinations thereof for user equipment in a geographic area; a fourth expectation of performance metrics for user equipment in a geographic area; the expected distribution of the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; a confidence level metric for the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; the expected probability density function for radio access network resources, backhaul resources, or combinations thereof; the expectation of inter-cell handover sequences for user equipment in a geographic area; or combinations thereof.

[0168] In various embodiments, the predicted inter-cell interference management strategy is provided to the middleware entity.

[0169] In one embodiment, the predicted inter-cell interference management policy includes a cell identifier, application identifier, user equipment group identifier, network slice identifier, central unit identifier, distributed unit identifier, current policy identifier, new policy identifier, current service redirection policy identifier (this identifier can be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), new service redirection policy identifier (this can be a service redirection policy updated based on the predicted inter-cell interference management policy), confidence level parameter, enforcement flag, time validity indicator, area indicator, overload indicator, high interference indicator, relative narrowband transmit power, near-blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource constraints, or some combination thereof.

[0170] In some embodiments, the method further includes requesting verification of the predicted inter-cell interference management strategy from the conflict mitigation function and receiving a verification response from the conflict mitigation function.

[0171] In some embodiments, open application programming interfaces (APIs) are used to send and receive communications.

[0172] In various embodiments, the A1 interface is used for communication with service entities, management entities, or a combination thereof.

[0173] In one embodiment, the E2 interface is used for communication with new wireless devices.

[0174] In some embodiments, the predicted inter-cell interference management strategy is provided to the device via an application exposure function.

[0175] In one embodiment, an apparatus includes: a receiver that receives modeling information corresponding to a device, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model; and a processor that: determines a predictive inter-cell interference management strategy for the device based on the modeling information; and provides the predictive inter-cell interference management strategy to the device.

[0176] In some embodiments, the receiver receives the initial configuration before determining the predicted inter-cell interference management strategy.

[0177] In some embodiments, the initial configuration is sent from a service entity, a management entity, or a combination thereof.

[0178] In various embodiments, the initial configuration includes a cell identifier, network slice identifier, service type, application type, profile, list of policy identifiers, per-policy metric, per-policy threshold, interference management preference, enforcement flag, middleware flag, middleware identifier, time validity indicator, geographic region, vertical-specific parameter, cross-vertical parameter, or some combination thereof.

[0179] In one embodiment, the initial configuration is configured according to a vertical client.

[0180] In some embodiments, the receiver receives reports of monitoring events related to the device.

[0181] In some embodiments, the predictive inter-cell interference management strategy is determined in response to receiving a monitoring event report.

[0182] In various embodiments, the monitoring event report includes cell identifier, user equipment identifier, network slice identifier, resource identifier, resource pool identifier, user equipment quality of experience degradation indicator, user equipment service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, or some combination thereof.

[0183] In one embodiment, the processor subscribes to radio access network nodes, subscription functions, or a combination thereof for receiving monitoring event reports.

[0184] In some embodiments, the device includes at least one network element, at least one user equipment, or a combination thereof.

[0185] In some embodiments, the modeling information includes: a first expectation of radio access network resource conditions within a predefined time period; a second expectation of radio backhaul resource conditions within a predefined time period; a third expectation of user equipment mobility parameters, user equipment location information, or combinations thereof for user equipment in a geographic area; a fourth expectation of performance metrics for user equipment in a geographic area; the expected distribution of the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; a confidence level metric for the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; the expected probability density function for radio access network resources, backhaul resources, or combinations thereof; the expectation of inter-cell handover sequences for user equipment in a geographic area; or combinations thereof.

[0186] In various embodiments, the predicted inter-cell interference management strategy is provided to the middleware entity.

[0187] In one embodiment, the predicted inter-cell interference management policy includes a cell identifier, application identifier, user equipment group identifier, network slice identifier, central unit identifier, distributed unit identifier, current policy identifier, new policy identifier, current service redirection policy identifier (this identifier can be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), new service redirection policy identifier (this can be a service redirection policy updated based on the predicted inter-cell interference management policy), confidence level parameter, enforcement flag, time validity indicator, area indicator, overload indicator, high interference indicator, relative narrowband transmit power, near-blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource constraints, or some combination thereof.

[0188] In some embodiments, the receiver requests verification of the predicted inter-cell interference management strategy from the conflict mitigation function and receives a verification response from the conflict mitigation function.

[0189] In some embodiments, communication is sent and received using an open application programming interface (API).

[0190] In various embodiments, the A1 interface is used for communication with service entities, management entities, or a combination thereof.

[0191] In one embodiment, the E2 interface is used for communication with new wireless devices.

[0192] In some embodiments, the predicted inter-cell interference management strategy is provided to the device via an application exposure function.

[0193] In one embodiment, a method includes: receiving at least one monitoring report from a device; determining a monitoring event report based on a subscription and the at least one monitoring report; and providing the monitoring event report to an application.

[0194] In some embodiments, the method further includes: receiving a predicted inter-cell interference management policy from an application; determining at least one radio parameter corresponding to the predicted inter-cell interference management policy; and transmitting at least one radio parameter to a device based on the predicted inter-cell interference management policy.

[0195] In some embodiments, the predicted inter-cell interference management policy includes a cell identifier, an application identifier, a user equipment group identifier, a network slice identifier, a central unit identifier, a distributed unit identifier, a current policy identifier, a new policy identifier, a current service redirection policy identifier (this identifier may be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), a new service redirection policy identifier (this may be a service redirection policy updated based on the predicted inter-cell interference management policy), a confidence level parameter, an enforcement flag, a time validity indicator, a region indicator, or some combination thereof.

[0196] In various embodiments, at least one radio parameter includes overload indication, high interference indication, relatively narrowband transmit power, nearly blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, parameters for service transition policy updates (handover request indication, source cell identifier, target cell identifier, frequency selection indication, radio access technology selection indication, radio interface selection indication, distributed unit selection indication, central unit selection indication) or some combination thereof.

[0197] In one embodiment, the predicted inter-cell interference management strategy is provided to the device via an application exposure function.

[0198] In some embodiments, the method further includes receiving a subscription request for the subscription from the application.

[0199] In some embodiments, the monitoring event report includes cell identifier, user equipment identifier, network slice identifier, resource identifier, resource pool identifier, user equipment experience quality degradation indicator, user equipment service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, or some combination thereof.

[0200] In one embodiment, an apparatus includes: a receiver that receives at least one monitoring report from a device; and a processor that: determines a monitoring event report based on a subscription and the at least one monitoring report; and provides the monitoring event report to an application.

[0201] In some embodiments, the apparatus further includes a transmitter, wherein: the receiver receives a predicted inter-cell interference management policy from an application; the processor determines at least one radio reference corresponding to the predicted inter-cell interference management policy; and the transmitter transmits at least one radio parameter to the apparatus based on the predicted inter-cell interference management policy.

[0202] In some embodiments, the predicted inter-cell interference management policy includes a cell identifier, an application identifier, a user equipment group identifier, a network slice identifier, a central unit identifier, a distributed unit identifier, a current policy identifier, a new policy identifier, a current service redirection policy identifier (this identifier may be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), a new service redirection policy identifier (this may be a service redirection policy updated based on the predicted inter-cell interference management policy), a confidence level parameter, an enforcement flag, a time validity indicator, a region indicator, or some combination thereof.

[0203] In various embodiments, at least one radio parameter includes overload indication, high interference indication, relatively narrowband transmit power, nearly blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource constraints, parameters for service transition policy updates (handover request indication, source cell identifier, target cell identifier, frequency selection indication, radio access technology selection indication, radio interface selection indication, distributed unit selection indication, central unit selection indication) or some combination thereof.

[0204] In one embodiment, the predicted inter-cell interference management strategy is provided to the device via an application exposure function.

[0205] In some embodiments, the receiver receives a subscription request for the subscription from the application.

[0206] In some embodiments, the monitoring event report includes cell identifier, user equipment identifier, network slice identifier, resource identifier, resource pool identifier, user equipment experience quality degradation indicator, user equipment service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, bandwidth adaptation requirement, radio resource adaptation requirement, service shift requirement, or some combination thereof.

[0207] In one embodiment, a method includes: sending at least one monitoring report; and receiving information corresponding to a predicted inter-cell interference management strategy in response to sending at least one monitoring report.

[0208] In some embodiments, at least one monitoring report includes a monitoring event report, which includes a cell identifier, user equipment identifier, network slice identifier, resource identifier, resource pool identifier, user equipment experience quality degradation indicator, user equipment service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, bandwidth adaptation requirement, radio resource adaptation requirement, service shift requirement, or some combination thereof.

[0209] In some embodiments, the predicted inter-cell interference management policy includes a cell identifier, application identifier, user equipment group identifier, network slice identifier, central unit identifier, distributed unit identifier, current policy identifier, new policy identifier, current service redirection policy identifier (this identifier may be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), new service redirection policy identifier (this may be a service redirection policy updated based on the predicted inter-cell interference management policy), confidence level parameter, enforcement flag, time validity indicator, area indicator, overload indicator, high interference indicator, relative narrowband transmit power, near-blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource limit, or some combination thereof.

[0210] In various embodiments, at least one monitoring report is sent to a middleware entity or application.

[0211] In one embodiment, information corresponding to the predicted inter-cell interference management strategy is received from a middleware entity or application.

[0212] In one embodiment, an apparatus includes: a transmitter that transmits at least one monitoring report; and a receiver that receives information corresponding to a predicted inter-cell interference management strategy in response to the transmission of at least one monitoring report.

[0213] In some embodiments, at least one monitoring report includes a monitoring event report, which includes a cell identifier, user equipment identifier, network slice identifier, resource identifier, resource pool identifier, user equipment experience quality degradation indicator, user equipment service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, bandwidth adaptation requirement, radio resource adaptation requirement, service shift requirement, or some combination thereof.

[0214] In some embodiments, the predicted inter-cell interference management policy includes a cell identifier, application identifier, user equipment group identifier, network slice identifier, central unit identifier, distributed unit identifier, current policy identifier, new policy identifier, current service redirection policy identifier (this identifier may be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), new service redirection policy identifier (this may be a service redirection policy updated based on the predicted inter-cell interference management policy), confidence level parameter, enforcement flag, time validity indicator, area indicator, overload indicator, high interference indicator, relative narrowband transmit power, near-blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource limit, or some combination thereof.

[0215] In various embodiments, at least one monitoring report is sent to a middleware entity or application.

[0216] In one embodiment, information corresponding to the predicted inter-cell interference management strategy is received from a middleware entity or application.

[0217] In one embodiment, a method includes: sending an initial configuration; receiving a request for modeling information in response to sending the initial configuration; and sending the modeling information in response to receiving the request, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model.

[0218] In some embodiments, the initial configuration is sent to the application.

[0219] In some embodiments, the initial configuration is sent from a service entity, a management entity, or a combination thereof.

[0220] In various embodiments, the initial configuration includes a cell identifier, network slice identifier, service type, application type, profile, list of policy identifiers, per-policy metric, per-policy threshold, interference management preference, enforcement flag, middleware flag, middleware identifier, time validity indicator, geographic region, vertical-specific parameter, cross-vertical parameter, or some combination thereof.

[0221] In one embodiment, the initial configuration is configured according to a vertical client.

[0222] In some embodiments, the modeling information includes: a first expectation of radio access network resource conditions within a predefined time period; a second expectation of radio backhaul resource conditions within a predefined time period; a third expectation of user equipment mobility parameters, user equipment location information, or combinations thereof for user equipment in a geographic area; a fourth expectation of performance metrics for user equipment in a geographic area; the expected distribution of the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; a confidence level metric for the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; the expected probability density function for radio access network resources, backhaul resources, or combinations thereof; the expectation of inter-cell handover sequences for user equipment in a geographic area; or combinations thereof.

[0223] In one embodiment, an apparatus includes: a transmitter that transmits an initial configuration; and a receiver that receives a request for modeling information in response to transmitting the initial configuration; wherein the transmitter transmits the modeling information in response to receiving the request, wherein the modeling information includes service parameters, radio parameters, mobility parameters, or combinations thereof, and the modeling information includes at least one machine learning model.

[0224] In some embodiments, the initial configuration is sent to the application.

[0225] In some embodiments, the initial configuration is sent from a service entity, a management entity, or a combination thereof.

[0226] In various embodiments, the initial configuration includes a cell identifier, network slice identifier, service type, application type, profile, list of policy identifiers, per-policy metric, per-policy threshold, interference management preference, enforcement flag, middleware flag, middleware identifier, time validity indicator, geographic region, vertical-specific parameter, cross-vertical parameter, or some combination thereof.

[0227] In one embodiment, the initial configuration is configured according to a vertical client.

[0228] In some embodiments, the modeling information includes: a first expectation of radio access network resource conditions within a predefined time period; a second expectation of radio backhaul resource conditions within a predefined time period; a third expectation of user equipment mobility parameters, user equipment location information, or combinations thereof for user equipment in a geographic area; a fourth expectation of performance metrics for user equipment in a geographic area; the expected distribution of the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; a confidence level metric for the first, second, third, and fourth expectations, or combinations thereof, over a predefined time period; the expected probability density function for radio access network resources, backhaul resources, or combinations thereof; the expectation of inter-cell handover sequences for user equipment in a geographic area; or combinations thereof.

[0229] In one embodiment, a method includes: receiving a predictive resource management policy from at least one application; determining at least one radio parameter corresponding to the predictive resource management policy; and transmitting at least one radio parameter to a device based on the predictive resource management policy.

[0230] In some embodiments, the predictive resource management policy includes an application identifier, a user equipment group identifier, a cell identifier, a network slice identifier, a central unit identifier, a distributed unit identifier, a current inter-cell interference management policy identifier, a new inter-cell interference policy identifier, a current service redirection policy identifier (this identifier may be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), a new service redirection policy identifier (this may be a service redirection policy updated based on the predictive inter-cell interference management policy), a confidence level parameter, an enforcement flag, a time validity indicator, a region indicator, or some combination thereof.

[0231] In some embodiments, at least one radio parameter includes overload indication, high interference indication, relatively narrowband transmit power, nearly blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource constraints, parameters for service transition policy updates (handover request indication, source cell identifier, target cell identifier, frequency selection indication, radio access technology selection indication, radio interface selection indication, distributed unit selection indication, central unit selection indication) or some combinations thereof.

[0232] In various embodiments, predictive resource management strategies are provided to the device via application exposure functionality.

[0233] In one embodiment, the device includes at least one network unit, at least one user equipment, or a combination thereof.

[0234] In some embodiments, at least one radio parameter is further determined based on at least one predefined rule corresponding to an application type, service type, or a combination thereof.

[0235] In some embodiments, predefined rules include key performance indicators, service type identifiers, application type identifiers, radio access network identifiers, network slice profiles, service profiles, quality of service objectives (guaranteed traffic bit rate, maximum traffic bit rate, priority level, packet delay budget parameter, reliability parameter, packet error rate parameter), quality of experience objectives (quality of experience score, initial buffer parameter, delay events, delay ratio, average opinion score), priority identifiers, application quality of service to network quality of service mapping information, or some combination thereof.

[0236] In various embodiments, the method further includes: receiving at least one monitoring report from a device; determining a monitoring event report based on the subscription and the at least one monitoring report; and sending the monitoring event report to an application.

[0237] In one embodiment, the method further includes receiving a subscription request for the subscription from the application.

[0238] In some embodiments, the monitoring report includes user equipment quality of service parameters, user equipment experience quality parameters, radio resource quality parameters, computed radio access network resource load parameters, central unit load, distributed unit load, channel state information, radio resource management measurements, radio link monitoring measurements, received signal strength indicators, reference signal received power parameters, handover fault monitoring parameters, or some combinations thereof.

[0239] In some embodiments, the monitoring report may further include backhaul radio resource quality parameters, backhaul channel state information, backhaul radio resource management measurements, backhaul radio link monitoring measurements, backhaul topology parameters, backhaul type parameters, or combinations thereof.

[0240] In various embodiments, monitoring event reporting is determined based on offline user equipment analysis, online user equipment analysis, radio resource quality analysis, or some combination thereof.

[0241] In one embodiment, the monitoring event report includes cell identifier, user equipment identifier, network slice identifier, resource identifier, resource pool identifier, user equipment experience quality degradation indicator, user equipment service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, bandwidth adaptation requirement, radio resource adaptation requirement, service shift requirement, or some combination thereof.

[0242] In one embodiment, an apparatus includes: a receiver that receives a predictive resource management policy from at least one application; a processor that determines at least one radio parameter corresponding to the predictive resource management policy; and a transmitter that transmits at least one radio parameter to the apparatus based on the predictive resource management policy.

[0243] In some embodiments, the predictive resource management policy includes an application identifier, a user equipment group identifier, a cell identifier, a network slice identifier, a central unit identifier, a distributed unit identifier, a current inter-cell interference management policy identifier, a new inter-cell interference policy identifier, a current service redirection policy identifier (this identifier may be mapped to one of the following policies for one or more user equipments: 1) intra-frequency gNB selection, 2) inter-frequency gNB selection, 3) central unit selection, 4) distributed unit selection, 5) dual connectivity operation selection), a new service redirection policy identifier (this may be a service redirection policy updated based on the predictive inter-cell interference management policy), a confidence level parameter, an enforcement flag, a time validity indicator, a region indicator, or some combination thereof.

[0244] In some embodiments, at least one radio parameter includes overload indication, high interference indication, relatively narrowband transmit power, nearly blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource constraints, parameters for service transition policy updates (handover request indication, source cell identifier, target cell identifier, frequency selection indication, radio access technology selection indication, radio interface selection indication, distributed unit selection indication, central unit selection indication) or some combinations thereof.

[0245] In various embodiments, predictive resource management strategies are provided to the device via application exposure functionality.

[0246] In one embodiment, the device includes at least one network unit, at least one user equipment, or a combination thereof.

[0247] In some embodiments, at least one radio parameter is further determined based on at least one predefined rule corresponding to an application type, service type, or a combination thereof.

[0248] In some embodiments, predefined rules include key performance indicators, service type identifiers, application type identifiers, radio access network identifiers, network slice profiles, service profiles, quality of service objectives (guaranteed traffic bit rate, maximum traffic bit rate, priority level, packet delay budget parameter, reliability parameter, packet error rate parameter), quality of experience objectives (quality of experience score, initial buffer parameter, delay events, delay ratio, average opinion score), priority identifiers, application quality of service to network quality of service mapping information, or some combination thereof.

[0249] In various embodiments: the receiver receives at least one monitoring report from the device; the processor determines a monitoring event report based on the subscription and the at least one monitoring report; and the transmitter sends the monitoring event report to the application.

[0250] In one embodiment, the receiver receives a subscription request for the subscription from the application.

[0251] In some embodiments, the monitoring report includes user equipment quality of service parameters, user equipment experience quality parameters, radio resource quality parameters, computed radio access network resource load parameters, central unit load, distributed unit load, channel state information, radio resource management measurements, radio link monitoring measurements, received signal strength indicators, reference signal received power parameters, handover fault monitoring parameters, or some combinations thereof.

[0252] In some embodiments, the monitoring report may further include backhaul radio resource quality parameters, backhaul channel state information, backhaul radio resource management measurements, backhaul radio link monitoring measurements, backhaul topology parameters, backhaul type parameters, or combinations thereof.

[0253] In various embodiments, monitoring event reporting is determined based on offline user equipment analysis, online user equipment analysis, radio resource quality analysis, or some combination thereof.

[0254] In one embodiment, the monitoring event report includes cell identifier, user equipment identifier, network slice identifier, resource identifier, resource pool identifier, user equipment experience quality degradation indicator, user equipment service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, bandwidth adaptation requirement, radio resource adaptation requirement, service shift requirement, or some combination thereof.

[0255] The embodiments may be practiced in other specific forms. The described embodiments are to be regarded in all respects as illustrative rather than restrictive. Therefore, the scope of the invention is indicated by the appended claims rather than the foregoing description. All modifications within the meaning and equivalent scope of the claims are covered within their scope.

Claims

1. A method performed by a network function, the method comprising: Receive the initial inter-cell interference management policy corresponding to the equipment from the Radio Access Network (RAN) Intelligent Controller (RIC); Modeling information is received from the RIC, wherein the modeling information corresponds to the device and includes one or more of UE service parameters, UE radio parameters, and UE mobility parameters, and wherein the modeling information further includes at least one trained machine learning model, one or more of the following: a first expectation of radio access network resource conditions within a predefined time period, a second expectation of radio backhaul resource conditions within the predefined time period, an expectation of UE mobility parameters and UE location information of the UE in a geographic area, or a third expectation of both, and a fourth expectation of the performance metric of the UE in the geographic area; Based on the modeling information and the initial inter-cell interference management strategy, a predictive inter-cell interference management strategy is determined for the device. as well as The predicted inter-cell interference management strategy is provided to the device.

2. The method of claim 1, wherein, The predicted inter-cell interference management strategy is sent from the service entity, the management entity, or both.

3. The method of claim 1, wherein, The initial inter-cell interference management policy includes one or more of the following: cell identifier, network slice identifier, service type, application type, profile, policy identifier list, per-policy metric, per-policy threshold, interference management preference, enforcement flag, middleware flag, middleware identifier, time validity indicator, geographic region, vertical specific parameter, and cross-vertical parameter.

4. The method of claim 1, further comprising obtaining monitoring event reports related to the device.

5. The method of claim 4, wherein, The predicted inter-cell interference management strategy is determined in response to receiving the monitoring event report.

6. The method of claim 4, wherein, The monitoring event report includes cell identifier (ID), UE identifier, network slice ID, resource ID, resource pool ID, UE experience quality degradation indicator, UE service quality degradation indicator, high resource load indicator, high radio access network latency indicator, low backhaul resource availability indicator, service quality fluctuation indicator, radio link failure indicator, bandwidth adaptation requirement, radio resource adaptation requirement, service redirection requirement, or a combination thereof.

7. The method of claim 4, further comprising subscribing to a RAN node, subscribing to a function, or both, for receiving the monitoring event report.

8. The method of claim 1, wherein, The device includes at least one network element, at least one UE, or a combination thereof.

9. The method of claim 1, wherein, The modeling information includes one or more of the following: The expected distribution of the first expectation, the second expectation, the third expectation, the fourth expectation, or a combination thereof over the predefined time period; A confidence level measure of the first expectation, the second expectation, the third expectation, the fourth expectation, or a combination thereof over the predefined time period; The expected probability density function over radio access network resources, backhaul resources, or both; or The expected inter-cell handover sequence of the UE in the geographical region.

10. The method according to claim 1, wherein, The predicted inter-cell interference management strategy includes one or more of the following: cell identifier (ID), application ID, UE group ID, network slice ID, central unit (CU) ID, distributed unit (DU) ID, current policy ID, new policy ID, current service redirection policy ID, new service redirection policy ID, confidence level parameter, enforcement flag, time validity indicator, area indicator, overload indicator, high interference indicator, relative narrowband transmit power, near-blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource limitation, or a combination thereof.

11. The method of claim 1, further comprising: The system requests verification of the predicted inter-cell interference management strategy from the conflict mitigation function and receives a verification response from the conflict mitigation function.

12. The method according to claim 1, wherein, Use open application programming interfaces (APIs) to send and receive communications.

13. The method according to claim 1, wherein, Inter-cell interference management strategies are provided to the device via application exposure functionality.

14. A method performed by a network function, the method comprising: Send at least one monitoring report corresponding to the interference management device; as well as In response to sending the at least one monitoring report, information corresponding to a predicted inter-cell interference management strategy is received, wherein the predicted inter-cell interference management strategy is determined based on modeling information, the at least one monitoring report, and an initial inter-cell interference management strategy, and the modeling information includes one or more of the following: a first expectation of radio access network resource conditions within a predefined time period, a second expectation of radio backhaul resource conditions within the predefined time period, expectations of UE mobility parameters and UE location information of the UE in the geographic area, or a third expectation of both, and a fourth expectation of performance metrics of the UE in the geographic area.

15. The method according to claim 14, wherein, The at least one monitoring report includes a detection event report, comprising one or more of the following: cell identifier (ID), UE identifier, network slice ID, resource ID, resource pool ID, UE experience quality degradation indication, UE service quality degradation indication, high resource load indication, high radio access network latency indication, low backhaul resource availability indication, service quality fluctuation indication, radio link failure indication, bandwidth adaptation requirement, radio resource adaptation requirement, service shift requirement, or a combination thereof.

16. The method of claim 14, wherein, The predicted inter-cell interference management strategy includes one or more of the following: cell identifier (ID), application ID, UE group ID, network slice ID, central unit (CU) ID, distributed unit (DU) ID, current policy ID, new policy ID, current service redirection policy ID, new service redirection policy ID, confidence level parameter, enforcement flag, time validity indicator, area indicator, overload indicator, high interference indicator, relative narrowband transmit power, near-blank subframe pattern information, coordinated multipoint coordination area, coordinated multipoint scheme, resource limitation, or a combination thereof.

17. A method performed by a network function, the method comprising: The service entity, management entity, or both send the initial inter-cell interference management policy corresponding to the device from the Radio Access Network (RAN) Intelligent Controller (RIC) to the application; In response to the initial inter-cell interference management policy being sent from the application, a request for modeling information is received; as well as In response to receiving the request, the modeling information is sent, wherein the modeling information includes one or more of the following: user equipment (UE) service parameters, UE radio parameters, or UE mobility parameters, and the modeling information includes at least one trained machine learning model, and the modeling information includes one or more of the following: a first expectation of radio access network resource conditions within a predefined time period, a second expectation of radio backhaul resource conditions within the predefined time period, an expectation of UE mobility parameters of the UE in the geographic area, an expectation of UE location information, or a third expectation of both, and a fourth expectation of performance metrics of the UE in the geographic area.

18. The method according to claim 17, wherein, The initial inter-cell interference management policy includes one or more of the following: cell identifier, network slice identifier, service type, application type, profile, policy identifier list, per-policy metric, per-policy threshold, interference management preference, enforcement flag, middleware flag, middleware identifier, time validity indicator, geographic region, vertical specific parameter, and cross-vertical parameter.

19. The method of claim 17, wherein, The modeling information includes: The expected distribution of the first expectation, the second expectation, the third expectation, the fourth expectation, or a combination thereof over the predefined time period; A confidence level measure of the first expectation, the second expectation, the third expectation, the fourth expectation, or a combination thereof over the predefined time period; The expected probability density function over radio access network resources, backhaul resources, or combinations thereof; The expected inter-cell handover sequence of the UE in the geographical region; or Its combination.

20. An apparatus for performing network functions, the apparatus comprising: At least one memory; as well as At least one processor, coupled to the at least one memory, and configured to cause the device to: Receive the initial inter-cell interference management policy corresponding to the equipment from the Radio Access Network (RAN) Intelligent Controller (RIC); Modeling information is received from the RIC and User Equipment (UE) / RAN monitoring equipment, wherein the modeling information corresponds to the equipment and includes one or more of UE service parameters, UE radio parameters, and UE mobility parameters, and wherein the modeling information further includes at least one trained machine learning model, one or more of the following: a first expectation of radio access network resource conditions within a predefined time period, a second expectation of radio backhaul resource conditions within the predefined time period, an expectation of UE mobility parameters of the UE in a geographic area, an expectation of UE location information, or a third expectation of both, and a fourth expectation of the performance metric of the UE in the geographic area; Based on the modeling information and the initial inter-cell interference management strategy, a predictive inter-cell interference management strategy is determined for the device. as well as The predicted inter-cell interference management strategy is provided to the device.

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