Adaptive inter-cell interference avoidance feedback decision window

Abstract

The described techniques generally relate to dynamically adapting parameter data (e.g., resizing and frequency) for inter-cell interference avoidance feedback and decision windows to obtain interference-related data from UEs. Interference-related data analyzed from the return window is used to recommend decisions to the ran node as to which radio resources should be avoided when scheduling UE-related communications to avoid inter-cell interference. A controller (e.g., an RIC) dynamically attempts to optimize the frequency and periodicity of inter-cell interference avoidance feedback and decision windows to be transmitted based on measurements and KPIs (e.g., UE traffic mode data and QoS requirements) from RAN nodes and performance capability data of the nodes. The node can accept window parameter data or reject requests for reprocessing by the controller.

Description

Cross-references to related applications

[0001] This application claims priority to U.S. nonprovisional patent application No. 18 / 313,413, filed May 8, 2023, entitled “ADAPTIVE INTERCELL INTERFERENCEAVOIDANCE FEEDBACK-DECISION WINDOW,” the entire contents of which are incorporated herein by reference. Background Technology

[0002] In wireless network communication, inter-cell interference occurs when neighboring cells transmit simultaneously. Generally, inter-cell interference can lead to low network key performance indicators (KPIs), such as low spectral efficiency and low Quality of Service (QoS). In fact, inter-cell interference reduces bandwidth efficiency and may violate the Quality of Service (QoS) requirements of user equipment (UE).

[0003] The impact of inter-cell interference depends on the location of the UE relative to its serving cell and the neighboring cells that are interfering. Therefore, inter-cell interference suppression techniques attempt to identify affected UEs and select spectrum resources that can be used by each cell to avoid inter-cell interference.

[0004] Inter-cell interference suppression techniques include empty beamforming, which uses "beamspaces" directed towards UEs served by neighboring cells to avoid interference. In the Alternate Subband Channel Quality Indicator (CQI) method, the UE reports the channel quality in each portion of the spectrum (e.g., each resource block group). The scheduler then selects the resource block group with the highest channel quality for each UE. However, the reported quality is averaged over a duration depending on the UE implementation, and distributing UE data transmission across multiple time slots can lead to overuse of control channels. In channel reuse methods, frequencies can be reused between different cells so that statically non-overlapping portions of the spectrum are allocated to neighboring cells. However, this leads to low spectral efficiency when traffic load is unevenly distributed across neighboring cells, and further, reconfiguring spectrum allocation for each cell can cause service interruptions for connected users.

[0005] The background above is intended to provide only a contextual overview of some current issues and is not intended to be exhaustive. Further contextual information may become more apparent when reviewing the detailed description below. Attached Figure Description

[0006] The techniques described herein are illustrated by way of example and are not limited to the accompanying drawings, in which the same reference numerals indicate similar elements, and in the accompanying drawings:

[0007] Figure 1 This is a block diagram of an example system / architecture including a controller, which is configured to detect interference patterns via an adaptive (dynamic) reporting window, based on various aspects and implementations disclosed in this subject matter.

[0008] Figure 2A and Figure 2B Examples of ultra-reliable low-latency (URLLC) communication for user equipment (UE) to adapt to dynamic inter-cell interference and avoid feedback decision windows, based on various aspects and implementations disclosed in this subject matter.

[0009] Figure 3A and Figure 3B Examples of non-URLLC communication of a UE to adapt to dynamic inter-cell interference and avoid feedback decision windows, based on various aspects and implementations disclosed in this subject matter.

[0010] Figure 4 This is a sequence / dataflow diagram of example operations performed by various network devices with respect to UE-based service data and network function (NF) infrastructure information in an adaptive interference avoidance feedback decision window, based on various aspects and implementations disclosed in this subject matter.

[0011] Figure 5 This is a sequence / dataflow diagram of example operations performed by various network devices to change adaptive interference avoidance feedback decision windows based on UE-based changes in service data, according to various aspects and implementations disclosed in this subject.

[0012] Figure 6 This is a sequence / dataflow diagram of example operations performed by various network devices to handle subscription request failures by changing the adaptive interference for the UE to avoid feedback decision window, based on various aspects and implementations disclosed in this subject.

[0013] Figure 7 This is a flowchart illustrating example operations performed by the controller when generating an adaptive interference avoidance feedback decision window for the UE, based on various aspects and implementations disclosed in this subject matter.

[0014] Figure 8 This is a flowchart of an example operation involving determining window parameter data for inter-cell interference avoidance feedback and decision windows based on operational data, according to various aspects and implementations disclosed in this subject matter, whereby the operational data includes business model data representing business models associated with user equipment.

[0015] Figure 9 and Figure 10This includes flowcharts illustrating example operations for changing parameter data for inter-cell interference avoidance feedback and decision windows once the user equipment's service model has changed, based on various aspects and implementations disclosed in this subject matter.

[0016] Figure 11 This is a flowchart illustrating example operations related to generating recommendation window parameter data to prioritize a first user device over a second user device, based on various aspects and implementations disclosed in this subject matter.

[0017] Figure 12 This is a block diagram representing an example computing environment in which aspects of the topics described herein can be included.

[0018] Figure 13 Example schematic block diagrams depict computing environments according to various aspects and implementations disclosed in this subject matter, the disclosed subject matter being able to interact with / utilize the computing environment at least in part. Detailed Implementation

[0019] The techniques described herein typically involve adapting the frequency and transmission interval of inter-cell interference avoidance feedback and decision (reporting) windows to user equipment service models / patterns and their quality of service (QoS) requirements (e.g., constraint data, such as latency). Generally, a centralized controller collects reporting windows containing UE data related to inter-cell interference, detects interference patterns within these reporting windows, and returns inter-cell interference avoidance data (e.g., a list of recommended preferred time slot utilizations used by the cell scheduler) to connected network nodes to silence transmissions on some radio resources during data bursts from neighboring cells.

[0020] Generally, as described herein, the interference avoidance feedback and decision (reporting) window for analyzing the collected data can have variable parameter data, including window size and / or window reporting frequency. The controller determines the parameter data for a given reporting window based on the operational data of each corresponding UE, including service mode data and QoS-related data. The controller can also consider the capability data of a given network node when determining the parameter data for the interference avoidance feedback and decision window. In the event of changing conditions (e.g., the UE has switched to a different service mode), the interference avoidance feedback and decision window adapts to the changing conditions; (this is in contrast to static windows, which have been found to be suboptimal for UEs with non-periodic interference and latency-sensitive applications, or static windows with small windows that cause additional CPU and memory utilization during high-load scenarios).

[0021] It should be understood that any examples in this document are non-limiting. As an example, the technology is generally described herein in an O-RAN (Open Radio Access Network) environment; however, this is merely an example, and the technology can be implemented in similar environments. In fact, the technology is often described as being able to operate according to any 5G, next-generation communication technology, or existing communication technology. Therefore, any embodiments, aspects, concepts, structures, functions, or examples described herein are non-limiting, and the technology can be used in various ways that generally provide benefits and advantages in data storage and computation. It should also be noted that terms such as “optimized” or “best” as used herein only indicate a goal moving towards a better state, and do not necessarily mean achieving an ideal result.

[0022] Throughout this specification, references to "an embodiment," "an embodiment," "an implementation," "implementation," etc., mean that a particular feature, structure, or characteristic described in connection with that embodiment / implementation is included in at least one embodiment / implementation. Therefore, such phrases as "in one embodiment," "in an implementation," etc., appearing throughout this specification do not necessarily all refer to the same embodiment / implementation. Furthermore, in one or more embodiments / implementations, a particular feature, structure, or characteristic may be combined in any suitable manner.

[0023] One or more embodiments of the subject matter disclosed will now be described more fully below with reference to the accompanying drawings, in which example components, diagrams, and / or operations are illustrated. In the following description, several specific details are set forth for purposes of explanation in order to provide a thorough understanding of various embodiments. However, this subject matter disclosure may be embodied in many different forms and should not be construed as limited to the examples set forth herein.

[0024] Figure 1 An example system / architecture 100 including a controller 102 is shown, which, among other operations, provides an inter-cell interference avoidance service that, generally, silences transmissions on some radio resources during data bursts from neighboring cells. Figure 1 In one example implementation described herein (where the system is O-RAN compatible), controller 102 (e.g., RAN Intelligent Controller (RIC)) is coupled to service management and orchestration (SMO) component 104 via an O1 interface, which handles the orchestration, management, and automation aspects of RAN elements.

[0025] Controller 102 includes: an interface processor 106 that allows controller 102 to receive data from cooperating cells represented by RAN 108 and its network nodes, together with a data repository 110 (e.g., a database) that stores the data received through interface processor 106. Such data includes, but is not limited to, key performance indicators and allocation data related to previous reporting windows.

[0026] As described herein, example controller 102 runs application 112, including a user equipment (UE) service classification module 114, which detects UE operation data 116 (for the UE's service model / mode, collectively referred to as 134) coupled to controller 102 via RAN 120 and is capable of classifying each UE's use case type (e.g., identified by its packet arrival interval rate as Ultra Reliable Low Latency Communication (URLLC) vs. Mobile Broadband (MBB) vs. Machine Type Communication (MTC) applications). Interference detection module 118 of controller 102 collects (box 120) UE measurement results / data in interference avoidance feedback and decision window data 122 and detects which UEs are suffering interference based on these measurements.

[0027] More specifically, the interference pattern identification module 124 (e.g., based on negative acknowledgments (NACK) from the same UE) identifies interference-related patterns in the interference avoidance feedback and decision window data 124. For UEs requiring reporting window changes as described herein (e.g., the UE has changed its service type), the interference pattern identification module 124 (or other components of the controller 102) issues a subscription request to the appropriate node in the RAN 108 using adjusted window parameter data 126 (such as including window reporting frequencies as described herein).

[0028] Example RAN network node components are also shown as part of RAN 108. These components include centralized unit (DU) nodes and distributed unit (DU) nodes suitable for 4G and 5G technologies, supporting MBB, URLLC, and MTC applications. More specifically, Figure 1 The example system illustrates a controller 102 coupled to a RAN 108 with three cells via an E2 interface (e.g., in an O-RAN compatible scenario), each cell comprising corresponding distributed units 130(1) to 130(3) and centralized units 132(1) to 132(3). It should be understood that although three DU / CU network elements are shown in this example, it should be understood that the controller 102 is capable of being coupled to any actual number of elements. Figure 1 Radio units (RUs) not explicitly shown in the text also exist as part of the network elements of RAN 108.

[0029] Figure 1 The diagram also shows user equipment (UE) devices 134(1) to 134(2) communicating via RAN node 120. n Such UE devices 134(1) to 134( n The device can be one of any number (e.g., URLLC) of devices, including but not limited to medical-related devices, vehicles, sensors, small measuring devices, etc., which can move at relatively high speeds, for example, on drones, mobile robots, etc. The non-limiting terms “user equipment” or “UE” can refer to any type of device capable of communicating with network nodes (RAN 120) in cellular or mobile communication systems / architectures 100. UE devices 134(1) to 134( n Non-limiting examples of UE devices include target devices, device-to-device (D2D) UEs, machine-type UEs or UEs capable of machine-to-machine (M2M) communication, personal digital assistants (PDAs), tablet computers, mobile terminals, smartphones, laptop-mounted devices (LMEs), Universal Serial Bus (USB) dongles enabled for mobile communications, computers with mobility capabilities, mobile devices such as cellular phones, laptop computers with laptop-mounted embedded devices (LEEs, such as mobile broadband adapters), tablet computers with mobile broadband adapters, wearable devices, virtual reality (VR) devices, head-up display (HUD) devices, smart cars, machine-type communication (MTC) devices, augmented reality head-mounted displays, etc. UE devices 134(1) to 134( n One or more UE devices in a UE device may also include wireless communication IoT devices.

[0030] Generally, controller 102 is configured to estimate inter-cell interference on things that can be at a small time granularity (e.g., a single transmission time interval (TTI)), and controller 102 can provide inter-cell interference avoidance data 136, such as a time recommendation for preferred time slots, which the scheduler at the cell of RAN 108 (e.g., the scheduler at the network node) can use to avoid inter-cell interference. Controller 102 can utilize sporadic traffic from neighboring cells at the network node, and controller 102 can identify time slots with peak traffic demand for over-the-air transmission. Controller 102 can guide the resource scheduler at the network node to avoid transmitting data over-the-air to some UEs during periods that may experience high inter-cell interference.

[0031] Furthermore, controller 102 can rely on data with multiple granularities, including TTI-level information and / or aggregated network performance metrics. TTI-level information allows controller 102 to have a clear view of neighboring cell traffic and the resulting interference patterns, enabling controller 102 to construct an accurate list of preferred time slots. Controller 102 does not require additional reconfiguration of the UE or cell / network nodes, thereby reducing signaling overhead and service interruptions.

[0032] Controller 102 (and the scheduler at the network node) can consider UE 134(1) to 134( n The controller 102 (and / or the node scheduler) can determine the QoS level of the UE and select a time recommendation, including preferred time slots to avoid QoS violations when processing UE traffic with strict delay requirements. For example, the controller 102 (and / or the node scheduler) can assess the risk of a QoS violation (e.g., a packet exceeds its delay budget due to delaying transmission to a preferred time slot) and can compare that risk with the risk of immediately sending the packet in a non-preferred time slot (resulting in packet drop due to high interference).

[0033] Turning to example implementations of the techniques described herein, Figure 2A and Figure 2B A concept for a dynamic inter-cell interference avoidance feedback decision window 230 is illustrated for example URLLC use cases, such as autonomous vehicles, drones, etc., with high reliability and low latency requirements. In this example, the feedback decision window 230 is frequently sent to the controller 102; for example, the feedback decision window 230 is reported by the E2 node 208 (CU / DU / RU) every 100 milliseconds (ms) and has a relatively small decision window size, for example, 100 time slots. Figure 2B The window can include hybrid Automatic Repeat Request (HARQ) feedback, such as acknowledgment (ACK) and NACK data received from the UE at the serving cell via the Physical Uplink Control Channel (PUCCH) or Physical Uplink Scheduling Channel (PUSCH). The HARQ feedback list can indicate whether downlink data transmitted on the Physical Downlink Scheduling Channel (PDSCH) has been correctly decoded. Other data can be transmitted instead of HARQ feedback, such as KPI data, PRB (Physical Resource Block) utilization data, SINR (Signal-to-Interference-plus-Noise Ratio) data, Automatic Neighbor Relationship (ANR) data, etc. Machine learning models can be trained in a non-real-time RIC on RSRP (Reference Signal Received Power), RSRQ (Reference Signal Received Quality), and MCS (Modulation and Coding Scheme) data generated from simulation and drive tests; the trained model can then be passed to a near real-time RIC for runtime inference of interference and potential time slots to be utilized.

[0034] Generally speaking, such as Figure 2A As shown, the smaller the decision window size, the heavier the data transmission load becomes, in order to ensure faster (e.g., 300 ms in total) identification of interference patterns. Figure 2B As shown, after three decision window transmissions totaling 300 milliseconds, the 100-slot reporting window 230 exhibits interference pattern 232 detected by the controller 102. Figure 2B In the example, interference was detected in slots 2 and 3, which were depicted by shaded blocks (as opposed to unshaded blocks) in each of the three reports. Interference was also detected in slot 6 of the second report; however, this was not detected as part of the cyclic pattern.

[0035] Figure 3A and Figure 3B The example illustrates a dynamic inter-cell interference avoidance feedback decision window in a non-URLLC use case. For instance, video streams do not have the same latency requirements as any URLLC use case, thus enabling controller 102 to reduce the heavy load of frequent transmissions to support a larger decision window. Figure 3A and Figure 3B As shown in the example, the feedback decision window is sent to controller 102 less frequently; for example, this feedback decision window is reported by E2 RAN node 320 (CU / DU / RU) every 1000 ms (i.e., one second) and has a relatively large decision window size, for example, 1000 time slots. Figure 3B This results in significantly less reporting / reporting overhead between the E2 node and controller 102; however, pattern identification is more efficient than... Figure 2A and Figure 2B The URLLC use case example (300 ms time frame) is slightly slower (within a longer 1000 ms time frame). In fact, as... Figure 3B As shown, the 1000-slot report window 330 has interference patterns detected by the controller 102 in 322(a) and 332(b) after a decision window (report) transmission that takes a total of 1000 milliseconds.

[0036] although Figure 2A , Figure 2B , Figure 3A and Figure 3B The examples above illustrate some typical use cases, but it should be understood that other use cases are also possible. For instance, a UE in a video streaming application use case with normal buffering and a set of QoS constraints may be unacceptable for another video streaming application (such as a live video conference or event with stricter QoS constraints). Therefore, for the latter case (e.g., every 500 ms), it is possible to increase the window return frequency, rather than targeting... Figure 2A and Figure 2B The former use case increases every 1000 ms, but it is not necessarily the same as... Figure 3A and Figure 3B The rate is as high as that of URLLC use cases (every 100 ms). It is easy to understand that it is possible to assign a reporting window much less frequently to user devices that scroll through text data (such as social media / text messages / emails).

[0037] Figure 4 An example sequence and data flow diagram of the dynamic feedback window adjustment procedure for a single UE 436 are shown; this procedure is performed for each UE coupled to a given RAN E2 node (e.g., RAN node 408). Figure 4 In this configuration, SMO 104 configures the initial performance capabilities and QoS requirements of RAN node 408, as indicated by the arrow marked as one (1). Based on this configuration, RAN node 408 sends a number of downlink data transmissions (arrow two (2)) to UE 436, after which UE 436 sends back channel quality feedback data (arrow three (3)).

[0038] The system can determine an initial feedback and decision window for each UE based on current QoS requirements and service patterns (e.g., packet arrival interval rate). As described herein, the feedback and decision window parameter data are subsequently dynamically adapted based on time-varying services, new services for the UE, or changes in network capabilities (e.g., due to slicing or load variations). Adaptation is triggered by the controller or RAN node. This can be based on capability exchanges with the RAN node, QoS reconfiguration by the operator / SMO, or the absence / delay of inter-cell interference decisions.

[0039] RAN E2 node 408 collects information on UE services and network function infrastructure key performance indicators (KPIs) (arrow four (4)) and sends the corresponding data (arrow five (5)) to controller 102 (RIC application). Controller 102 identifies the service model of UE 436 (arrow six (6)) and the infrastructure capabilities of RAN node 408 (arrow seven (7)). Controller 102 then adjusts the dynamic window parameter data as needed to suit the needs of the UE service use cases and the utilization of the RAN node's performance capabilities. In this example, controller 102 sends subscription requests to RAN node 408 using the adjusted parameter data (e.g., window reporting frequency and / or size), as indicated by arrow eight (8). RAN node 408 reports the HARQ window at the adjusted frequency, as indicated by arrow nine (9).

[0040] As indicated by arrow 10 (10), RAN node 408 also reports network function infrastructure data and QoS capability data to SMO 104. As needed, in this example indicated by arrow 11 (11), SMO 104 updates the RAN node's performance capability data and QoS capability data.

[0041] Figure 5 It shows the basis from Figure 4 Continuing, an example of dynamic window parameter data change triggered by a change in UE service mode is shown by arrow twelve (12). As before, RAN node 408 sends a number of downlink data transmissions (arrow thirteen (13)) to UE 436, after which UE 436 sends back channel quality feedback data (arrow fourteen (14)).

[0042] As indicated by arrow 15 (10), RAN node 408 sends the collected UE service information to controller 102 (RIC application). Based on the collected UE service information, controller 102 (UE service classification 114, Figure 1 The UE service type is indicated by arrow sixteen (16).

[0043] In this example, based on the changed UE service type, controller 102 sends a subscription request to RAN node 408 using new parameter data (e.g., window reporting frequency and / or size), as indicated by arrow seventeen (17). RAN node 420 reports the HARQ window at the new frequency, as indicated by arrow eighteen (18). Thus, when the UE switches to another use case and the service has changed, the controller identifies the service change and adjusts the dynamic window to align with the new service type through the pattern reported by RAN node 408.

[0044] Figure 6 Another example is shown, where RAN node 408 (e.g., DU) rejects a subscription request, for example, due to infrastructure limitations and / or QoS requirements. Note that... Figure 6 The arrows marked in the middle, one (1) through eight (8), reflect the previous references in this paper. Figure 4 The arrows described will not be described again for the sake of brevity.

[0045] In this example, RAN node 408 rejects subscription requests from the controller at the adjusted reporting frequency. Figure 6 Arrow nine (9) (different from) Figure 4This indicates that a subscription failure response has been sent (e.g., due to disruption of network functionality or QoS requirements, it cannot be supported by RAN node 408). The failure response can include data indicating the reason for the rejection and / or what adjusted reporting parameter data is an acceptable recommendation for RAN node 408. For example, the RAN node may be unable to keep up with the frequency of reporting feedback and may request a different frequency, e.g., 500 ms instead of 100 ms.

[0046] Based on the information received in the failure response, such as by Figure 6 As indicated by arrow 10 (10), controller 102 readjusts the dynamic window parameter data (e.g., size and frequency) and sends the readjusted subscription request at arrow 11 (11) to RAN node 408. In this example, the readjusted subscription request is successful, and RAN node 408 sends a subscription success response to the controller at arrow 12 (12).

[0047] Figure 6 Arrows thirteen (13) to fifteen (15) are similar Figure 4 Arrows nine (9) to eleven (11). Therefore, as Figure 6 As shown, RAN node 408 reports the HARQ window at the adjusted frequency, as indicated by arrow thirteen (13). As indicated by arrow fourteen (14), RAN node 408 reports network function infrastructure data and QoS capability data to SMO 104. As needed, in this example indicated by arrow fifteen (15), SMO 104 updates the RAN node's performance capability data and QoS capability data.

[0048] Figure 7 This is a flowchart illustrating example operations of a controller (e.g., controller 102) regarding data collection, service classification, UE prioritization, and generating dynamic windows for sending subscription requests to network nodes. As shown at operation 702, the controller performs data collection, thereby collecting network-related data, including but not limited to the processing power of network functions (e.g., CPU utilization), the link capacity of network functions (e.g., controller and DU), and packet latency on the E2 interface. The controller also collects UE-related data, including but not limited to QoS requirement / constraint data, service mode data, and UE time slice data for each UE.

[0049] As indicated by operation 704, UE service mode and time slice data are used to identify UE service types. At operation 706, each UE's service type and QoS requirement data are used to prioritize UEs relative to each other (e.g., URLLC over enhanced mobile broadband) based on recommended window parameter data (e.g., window size and / or window reporting frequency).

[0050] As illustrated in operations 708, 718, and 720, the controller iterates through a priority-sorted list of UEs to generate a recommended dynamic window, for example, based on service mode type and QoS requirements. At operation 712, if the initial recommended window does not meet network function (node) requirements, the controller adjusts the window at operation 714, iterating back as needed until the network function (node) requirements are met. Once the window meets the network function (node) requirements, the final window (parameter data) is set for transmission as part of the subscription stream for the corresponding UE. This facilitates balancing the limited resources of a given node.

[0051] although Figure 7 It is not explicitly stated in the document, such as Figures 4 to 6 As shown, the final window (window parameter data) for the UE is sent to their corresponding network nodes. This can be done as follows: Figures 4 to 6 The example is a UE / node, or a part of a batch request for multiple UE windows for a given node.

[0052] One or more aspects can be embodied in network devices and / or systems, such as Figure 8 The example operations, as illustrated in the examples, can include, for example, a memory storing computer-executable components and / or operations, and a processor executing the computer-executable components and / or operations stored in the memory. The example operations can include operation 802, which represents determining window parameter data for an inter-cell interference avoidance feedback and decision window for a user equipment based on operational data, including service mode data representing a service mode associated with the user equipment. Example operation 804 represents conveying the window parameter data to a network node. Example operation 806 represents receiving report data representing interference mode data from a network node based on the window parameter data, the interference mode data representing an interference mode applicable to the user equipment. Example operation 808 represents determining inter-cell interference avoidance data based on the report data, which can be used to facilitate the selection of network resources for communication regarding the user equipment. Example operation 810 represents conveying the inter-cell interference avoidance data to a network node.

[0053] The window parameter data may include at least one of the following: window report frequency data indicating the frequency at which report data is received; or window report size data indicating the size of the report data.

[0054] Operational data can also include service quality-related data, which represents the service quality specifications applicable to user equipment.

[0055] Operational data can also include performance capability data representing the performance capabilities of network nodes.

[0056] The performance capability data of a network node may include at least one of the following: network function infrastructure capability data representing the network function infrastructure capability; or network function link capacity data representing the network function link capability.

[0057] The window parameter data can be first window parameter data for the first inter-cell interference avoidance feedback and decision window, the operation data can be first operation data, the service mode data can be first service data representing a first service mode associated with the user equipment, and the additional operation can include: determining, based on information returned by the network node, that the first operation data has changed to second operation data that is different from the first operation data, the second operation data including second service mode data representing a second service mode associated with the user equipment, the second service mode data being different from the first service mode data; determining, based on the second operation data, second window parameter data for the second inter-cell interference avoidance feedback and decision window, wherein the second window parameter data is different from the first window parameter data and can be used to facilitate further selection of network resources for further communication regarding the user equipment; and conveying the second window parameter data to the network node.

[0058] Other operations may include: receiving communication from the network node indicating that the second window parameter data is not supported by the network node in response to the transmission of the second window parameter data; determining third window parameter data for the third feedback and decision window in response to the communication; and transmitting the third window parameter data to the network node.

[0059] The communication can include information related to window parameter data, and determining the third window parameter data can include: information related to processing window parameter data.

[0060] The network device may include a radio access network intelligent controller, and communicating window parameter data to the network node may include sending a subscription request from the radio access network intelligent controller to the network node.

[0061] A network node can include at least one of the following: a centralized unit, a distributed unit, or a radio unit.

[0062] The reported data can correspond to at least one of the following: hybrid automatic repeat request information of user equipment; or reference signal reception quality information of user equipment.

[0063] Service pattern data can include packet arrival interval rate (PAR) data, which represents the packet arrival interval rate suitable for communication with user equipment.

[0064] exist Figure 9 and Figure 10The term "indicates" refers to one or more instance aspects, such as those corresponding to instance operations of a method. Figure 9 Example operation 902 indicates that a system including a processor obtains first operational data from a network node coupled to a user equipment. The first operational data includes first service mode data and first quality of service constraint data for the user equipment. Example operation 904 indicates that the system determines first window parameter data for an inter-cell interference avoidance feedback and decision window based on the first operational data. Example operation 906 indicates that the system communicates the first window parameter data to the network node. Example operation 908 indicates that, based on the first window parameter data, the system receives first report data from the network node representing first interference mode data for the user equipment. Example operation 910 indicates that, based on the first report data, the system determines inter-cell interference avoidance data for the first cell. Figure 10 Example operation 1002 indicates that the first inter-cell interference avoidance data is transmitted to the network node. Example operation 1004 indicates that, based on information returned by the network node, it is determined that the first operation data has been changed to second operation data, which is different from the first operation data. The second operation data includes second service mode data of the user equipment, which is different from the first service mode data. Example operation 1006 indicates that the system determines second window parameter data for the second inter-cell interference avoidance feedback and decision window based on the second operation data, wherein the second window parameter data is different from the first window parameter data. Example operation 1008 indicates that the system transmits the second window parameter data to the network node.

[0065] The additional operations may include: the system receiving communication from the network node indicating that the second window parameter data is not supported by the network node in response to the transmission of the second window parameter data; the system determining third window parameter data for the third feedback and decision window in response to the communication; and the system transmitting the third window parameter data to the network node. The communication may include information related to the window parameter data, and determining the third window parameter data may include: processing information related to the window parameter data.

[0066] Other operations may include: the system receiving second report data representing second interference mode data about the user equipment from the network node based on second window parameter data; the system determining second inter-cell interference avoidance data based on the second report data; and the system transmitting the second inter-cell interference avoidance data to the network node.

[0067] Figure 11This document outlines various example operations corresponding to machine-readable media, including executable instructions that, when executed by a processor, facilitate operations. Example operation 1102 represents obtaining first operation data for a first user equipment, the first operation data including first service data of the first user equipment. Example operation 1104 represents obtaining second operation data for a second user equipment, the second operation data including second service data of the second user equipment. Example operation 1106 represents prioritizing the first user equipment over the second user equipment based on the first and second operation data. Example operation 1108 represents generating first recommended window parameter data for the first user equipment regarding inter-cell interference avoidance feedback and decision windows, based on the first operation data. Example operation 1110 represents conveying the first window parameter data to a network node. Example operation 1112 represents generating second recommended window parameter data for the second user equipment regarding inter-cell interference avoidance feedback and decision windows, based on the second operation data. Example operation 1114 represents conveying the second window parameter data to a network node.

[0068] Other operations may include: obtaining third operational data of the first user equipment, the third operational data including third service data of the first user equipment; generating third recommended window parameter data about the first user equipment for inter-cell interference avoidance feedback and decision window based on the third operational data; and transmitting the third window parameter data to the network node.

[0069] The additional operations may include: receiving communication from the network node indicating that the second window parameter data is not supported by the network node in response to transmitting the second window parameter data; generating third recommended window parameter data for the second user equipment regarding the third inter-cell interference avoidance feedback and decision window based on the second operation data in response to the communication; and transmitting the third window parameter data to the network node.

[0070] Generating second recommended window parameter data can include: determining first candidate window parameter data for the second recommended window parameter data; evaluating whether the first candidate window parameter data conforms to network capability data in a first evaluation; determining, based on the first evaluation, that the first candidate window parameter data does not conform to network capability data; in response to determining that the first candidate window parameter data does not conform to network capability data, determining second candidate window parameter data for the second recommended window parameter data; evaluating whether the second candidate window parameter data conforms to network capability data in a second evaluation; determining, based on the second evaluation, that the second first candidate window parameter data conforms to network capability data; and in response to determining that the first candidate window parameter data conforms to network capability data, selecting the second candidate window parameter data as the second window parameter data to be conveyed to network nodes.

[0071] As can be seen, the techniques described in this paper facilitate adaptive feedback and decision window sizing and frequency adjustment based on various dynamic data, such as UE service pattern data. The Controller (RIC) attempts to dynamically optimize the frequency and TTI range of the inter-cell interference to be transmitted to avoid feedback and decision windows. This decision made by the RIC is based on the continuous (nearly continuous) collection of measurements and KPIs from the RAN E2 node via the E2 interface connecting the RIC and the RAN E2 node (i.e., DU). For each UE, the RIC examines and identifies criteria, including the UE service pattern identified by its packet arrival interval rate and / or UE QoS requirements (e.g., latency). For each RAN E2 node, the RIC collects performance capability reports against capability criteria, including network function infrastructure processing capacity and network function link capacity.

[0072] In one or more example implementations, once the RIC identifies the optimal feedback window frequency and size, it uses this information to send a subscription request to the E2 node via the E2 interface. The E2 node can accept the subscription and adjust its feedback window transmission accordingly or reject the request; if rejected, the RIC will reprocess the decision based on the returned response.

[0073] Using the reported UE data returned in the window, in addition to dynamically adapting the size and periodicity of the feedback window, the RIC can also output a mute decision for each UE based on service type (e.g., periodic vs. non-periodic), network function processing capacity, and QoS requirements.

[0074] Figure 12 This is a schematic block diagram of a computing environment 1200 with which the disclosed subject can interact. System 1200 includes one or more remote components 1210. The remote components 1210 can be hardware and / or software (e.g., threads, processes, computing devices). In some embodiments, the remote components 1210 can be a distributed computer system connected to a local autoscaling component and / or a program using the resources of the distributed computer system via a communication framework 1240. The communication framework 1240 can include wired network devices, wireless network devices, mobile devices, wearable devices, radio access network devices, gateway devices, femtocellular devices, servers, etc.

[0075] System 1200 also includes one or more local components 1220. The local components 1220 can be hardware and / or software (e.g., threads, processes, computing devices). In some embodiments, the local components 1220 can include autoscaling components and / or programs that communicate / use remote resources 1210, which are connected to a remotely located distributed computing system via a communication framework 1240.

[0076] One possible communication between the (multiple) remote components 1210 and the (multiple) local components 1220 could be in the form of data packets adapted for transmission between two or more computer processes. Another possible communication between the (multiple) remote components 1210 and the (multiple) local components 1220 could be in the form of circuit-switched data transmitted between two or more computer processes in a radio time slot. System 1200 includes a communication framework 1240 that can be used to facilitate communication between the (multiple) remote components 1210 and the (multiple) local components 1220, and can include an air interface, such as the Uu interface of a UMTS network, via a Long Term Evolution (LTE) network, etc. The (multiple) remote components 1210 can be operatively connected to one or more remote data repositories 1250, such as hard disk drives, solid-state drives, SIM cards, device memory, etc., and the one or more remote data repositories 1250 can be used to store information on the (multiple) remote component 1210 side of the communication framework 1240. Similarly, the local components 1220 can be operatively connected to one or more local data repositories 1230, which can be used to store information on the local component 1220 side of the communication framework 1240.

[0077] To provide additional context for the various embodiments described herein Figure 13 The following discussion is intended to provide a brief overview of a suitable computing environment 1300 in which various embodiments of the embodiments described herein can be implemented. While the embodiments have been described above in the general context of computer-executable instructions capable of running on one or more computers, those skilled in the art will recognize that these embodiments can also be implemented in combination with other program modules and / or as a combination of hardware and software.

[0078] Typically, program modules include routines, programs, components, data structures, etc., which perform specific tasks or implement specific abstract data types. Furthermore, those skilled in the art will understand that the method can be practiced using other computer system configurations, including single-processor or multi-processor computer systems, minicomputers, mainframes, Internet of Things (IoT) devices, distributed computing systems, and personal computers, handheld computing devices, microprocessor-based or programmable consumer electronics, each of which can be operatively coupled to one or more associated devices.

[0079] The embodiments described herein can also be practiced in a distributed computing environment, where certain tasks are performed by remote processing devices linked via a communication network. In a distributed computing environment, program modules can reside on both local and remote memory storage devices.

[0080] Computing devices typically include various media, which can include computer-readable storage media, machine-readable storage media, and / or communication media, these two terms being used differently herein as follows. A computer-readable storage medium or a machine-readable storage medium can be any available storage medium accessible by a computer, and includes both volatile and non-volatile media, and both removable and non-removable media. By way of example and not limitation, a computer-readable storage medium or a machine-readable storage medium can be implemented in conjunction with any method or technique used for storing information, such as computer-readable or machine-readable instructions, program modules, structured data, or unstructured data.

[0081] Computer-readable storage media can include, but is not limited to, random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, optical disc read-only memory (CD-ROM), digital versatile disc (DVD), Blu-ray disc (BD) or other optical disc storage devices, cassette tape, magnetic tape, disk storage devices or other magnetic storage devices, solid-state drives or other solid-state storage devices, or other tangible and / or non-transitory media that can be used to store desired information. For this purpose, the terms “tangible” or “non-transitory” used herein, when applied to storage devices, memories, or computer-readable media, should be understood to exclude only the propagation of transient signals themselves as a modifier, and do not waive the rights to all standard storage devices, memories, or computer-readable media that do not only propagate transient signals themselves.

[0082] A computer-readable storage medium can be accessed by one or more local or remote computing devices, for example via access requests, queries or other data retrieval protocols, for various operations on the information stored in the medium.

[0083] Communication media typically embody computer-readable instructions, data structures, program modules, or other structured or unstructured data in the form of data signals such as modulated data signals (e.g., carrier waves or other transmission mechanisms), and include any information delivery or transmission medium. The terms "modulated data signal" or "signal" refer to a signal having one or more characteristics set or altered in such a manner as encoding information in one or more signals. By way of example and not limitation, communication media include: wired media, such as wired networks or direct-line connections; and wireless media, such as acoustic media, RF media, infrared media, and other wireless media.

[0084] Refer again Figure 13 An example environment 1300 for implementing various embodiments of the aspects described herein includes a computer 1302, which includes a processing unit 1304, system memory 1306, and a system bus 1308. The system bus 1308 couples system components, including but not limited to system memory 1306, to the processing unit 1304. The processing unit 1304 can be any commercially available processor among a variety of commercially available processors. Dual microprocessors and other multiprocessor architectures can also be used as the processing unit 1304.

[0085] System bus 1308 can be any of several types of bus architectures, which can also interconnect to memory buses (with or without memory controllers), peripheral buses, and local buses using any commercially available bus architecture. System memory 1306 includes ROM 1310 and RAM 1312. The Basic Input / Output System (BIOS) can be stored in non-volatile memory such as ROM, erasable programmable read-only memory (EPROM), or EEPROM, containing basic routines that facilitate, for example, the transfer of information between components within computer 1302 during startup. RAM 1312 can also include high-speed RAM, such as static RAM for caching data.

[0086] Computer 1302 also includes an internal hard disk drive (HDD) 1314 (e.g., EIDE, SATA) and is capable of including one or more external storage devices 1316 (e.g., floppy disk drive (FDD) 1316, memory stick or flash drive reader, memory card reader, etc.). Although the internal HDD 1314 is illustrated as being located within computer 1302, the internal HDD 1314 can also be configured for external use in a suitable rack (not shown). Additionally, although not shown in environment 1300, solid-state drives (SSDs) can be used in addition to or in place of HDD 1314.

[0087] Other internal or external storage devices may include at least one other storage device 1320 having storage medium 1322 (e.g., solid-state storage device, non-volatile memory device, and / or optical disc drive capable of reading from or writing to removable media such as CD-ROM, DVD, BD, etc.). External storage device 1316 may be facilitated by a network virtual machine. HDD 1314, (multiple) external storage devices 1316, and storage devices (e.g., drives) 1320 may be connected to system bus 1308 via HDD interface 1324, external storage interface 1326, and drive interface 1328, respectively.

[0088] The drive and its associated computer-readable storage medium provide a non-volatile storage device for data, data structures, computer-executable instructions, etc. For computer 1302, the drive and storage medium accommodate the storage of any data in a suitable digital format. Although the above description of computer-readable storage media refers to a corresponding type of storage device, those skilled in the art will understand that other types of computer-readable storage media, whether currently existing or developed in the future, can be used in the example operating environment, and further, any such storage medium can contain computer-executable instructions for performing the methods described herein.

[0089] Multiple program modules can be stored in the drive and RAM 1312, including the operating system 1330, one or more application programs 1332, other program modules 1334, and program data 1336. All or part of the operating system, applications, modules, and / or data can also be cached in RAM 1312. The systems and methods described herein can be implemented using a variety of commercially available operating systems or combinations of operating systems.

[0090] Computer 1302 may optionally include emulation technology. For example, a hypervisor (not shown) or other intermediary may emulate the hardware environment used for operating system 1330, and the emulated hardware may optionally be compatible with... Figure 13 The hardware illustrated is different. In this embodiment, the operating system 1330 can be included as one of a plurality of virtual machines (VMs) hosted at the computer 1302. Furthermore, the operating system 1330 can provide a runtime environment, such as the Java Runtime Environment or the .NET Framework, to the application 1332. The runtime environment is a consistent execution environment that allows the application 1332 to run on any operating system that includes that runtime environment. Similarly, the operating system 1330 can support containers, and the application 1332 can be in the form of a container, which is a lightweight, standalone, executable software package that includes, for example, code, runtime, system tools, system libraries, and application-specific settings.

[0091] Furthermore, computer 1302 can be enabled using security modules such as Trusted Processing Modules (TPMs). For example, using a TPM, the next boot component is hashed at the boot component time, and the process waits for the result to match a security value before loading the next boot component. This process can occur at any layer of the code execution stack of computer 1302, for example, at the application execution level or the operating system (OS) kernel level, thereby achieving security at any code execution level.

[0092] Users can input commands and information into computer 1302 via one or more wired / wireless input devices (e.g., keyboard 1338, touchscreen 1340, and pointing devices such as mouse 1342). Other input devices (not shown) may include microphones, infrared (IR) remote controls, radio frequency (RF) remote controls or other remote controls, joysticks, virtual reality controllers and / or virtual reality headsets, gamepads, styluses, image input devices (e.g., cameras), gesture sensor input devices, visual motion sensor input devices, emotion or face detection devices, biometric input devices (e.g., fingerprint or iris scanners), etc. These and other input devices are typically connected to processing unit 1304 via input device interface 1344, which can be coupled to system bus 1308, but can also be connected via other interfaces (e.g., parallel ports, IEEE 1394 serial ports, game ports, USB ports, IR interfaces, BLUETOOTH® interfaces, etc.).

[0093] Monitor 1346 or other types of display devices can also be connected to system bus 1308 via an interface such as video adapter 1348. In addition to monitor 1346, the computer typically includes other peripheral output devices (not shown), such as speakers, printers, etc.

[0094] Computer 1302 is capable of operating in a networked environment using logical connections to one or more remote computers (such as remote computers 1350, etc.) via wired and / or wireless communications. Remote computers 1350 can be workstations, server computers, routers, personal computers, portable computers, microprocessor-based entertainment devices, peer-to-peer devices, or other public network nodes, and typically include many or all of the elements described relative to computer 1302, but for simplicity, only memory / storage device 1352 is illustrated. The depicted logical connections include wired / wireless connections to a local area network (LAN) 1354 and / or a larger network (e.g., a wide area network (WAN) 1356). Such LAN and WAN network environments are common in offices and corporations and facilitate enterprise-wide computer networks, such as intranets, all of which can connect to global communications networks, such as the Internet.

[0095] When used in a LAN network environment, computer 1302 can connect to local area network 1354 via a wired and / or wireless communication network interface or adapter 1358. Adapter 1358 facilitates wired or wireless communication to LAN 1354, which can also include a wireless access point (AP) configured thereon for communicating with adapter 1358 in wireless mode.

[0096] When used in a WAN network environment, computer 1302 may include modem 1360, or may be connected to a communication server on WAN 1356 via other means (such as via the Internet) for establishing communication over WAN 1356. Modem 1360 (which may be an internal or external device and a wired or wireless device) may be connected to system bus 1308 via input device interface 1344. In a networked environment, program modules or portions thereof depicted relative to computer 1302 may be stored in remote memory / storage device 1352. It should be understood that the network connection shown is an example, and other means for establishing communication links between computers may be used.

[0097] When used in a LAN or WAN network environment, computer 1302 can access cloud storage systems or other network-based storage systems, in addition to or in place of external storage device 1316 as described above. Typically, the connection between computer 1302 and the cloud storage system can be established (e.g., via adapter 1358 or modem 1360) through LAN 1354 or WAN 1356. When computer 1302 is connected to an associated cloud storage system, external storage interface 1326 can manage the storage devices provided by the cloud storage system with the help of adapter 1358 and / or modem 1360, just as it manages other types of external storage devices. For example, external storage interface 1326 can be configured to provide access to cloud storage sources as if these sources were physically connected to computer 1302.

[0098] Computer 1302 is operable to communicate with any wireless device or entity operatively configured for wireless communication (e.g., printers, scanners, desktop and / or portable computers, portable data assistants, communication satellites, any device or location associated with a wirelessly detectable tag (e.g., phone booths, newsstands, shelves, etc.) and telephones). This can include Wi-Fi and BLUETOOTH® wireless technologies. Therefore, communication can be a predefined structure like a conventional network, or simply self-organizing communication between at least two devices.

[0099] The above description of the illustrative embodiments disclosed in this subject matter, including the content described in the abstract, is not intended to be exhaustive or to limit the disclosed embodiments to the precise form disclosed. While specific embodiments and examples have been described herein for illustrative purposes, those skilled in the art will recognize that various modifications are possible within the scope of such embodiments and examples.

[0100] In this regard, while the disclosed subject matter has been described in conjunction with various embodiments and corresponding drawings, it should be understood where applicable that other similar embodiments can be used, or modifications and additions can be made to the described embodiments to perform the same, similar, alternative, or substitute functions of the disclosed subject matter without departing from the disclosed subject matter. Therefore, the disclosed subject matter should not be limited to any single embodiment described herein, but should be interpreted in accordance with the breadth and scope of the appended claims.

[0101] As used in this subject matter specification, the term "processor" can refer to virtually any computing processing unit or device, including, but not limited to: a single-core processor; a single processor with software multithreading capabilities; a multi-core processor; a multi-core processor with software multithreading capabilities; a multi-core processor utilizing hardware multithreading technology; a parallel platform; and a parallel platform with distributed shared memory. Additionally, a processor can refer to an integrated circuit, an application-specific integrated circuit, a digital signal processor, a field-programmable gate array, a programmable logic controller, a complex programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. Processors can utilize nanoscale architectures, such as, but not limited to, molecular and quantum dot-based transistors, switches, and gates, to optimize space utilization or enhance the performance of user devices. Processors can also be implemented as a combination of computing processing units.

[0102] As used herein, the terms “component,” “system,” “platform,” “layer,” “selector,” “interface,” etc., are intended to refer to a computer-related entity or an entity associated with an operating device having one or more specific functionalities, wherein the entity can be hardware, a combination of hardware and software, software, or software in execution. As an example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or a computer. By way of illustration and not limitation, both an application running on a server and the server itself can be components. One or more components can reside within a process and / or an execution thread, and components can reside on a single computer and / or be distributed across two or more computers. Furthermore, these components can execute from various computer-readable media on which various data structures are stored. These components can communicate via local and / or remote processes, such as based on signals having one or more data packets (e.g., data from a component that interacts with a local system, another component in a distributed system, and / or other systems across a network (such as the Internet). As another example, a component can be a device having specific functionality provided by a mechanical part operated by an electrical or electronic circuit system, the device being operated by a software or firmware application executed by a processor, wherein the processor is internal or external to the device and executes at least a portion of the software or firmware application. As yet another example, a component can be a device that provides specific functionality through an electronic component without mechanical parts, the electronic component including a processor that executes software or firmware that at least partially endows the electronic component with functionality.

[0103] Furthermore, the term "or" is intended to mean an inclusive "or," not an exclusive "or." That is, unless otherwise specified, it is clear from the context that "X takes A or B" is intended to mean any natural inclusive permutation. In other words, if X takes A; X takes B; or X takes both A and B, then "X takes A or B" is satisfied in any of the foregoing instances.

[0104] While the embodiments are susceptible to various modifications and alternative constructions, some of the illustrated implementations are shown in the accompanying drawings and have been described in detail above. However, it should be understood that the various embodiments are not intended to be limited to the specific forms disclosed, but rather, the invention is intended to cover all modifications, alternative constructions, and equivalents falling within its spirit and scope.

[0105] In addition to the various embodiments described herein, it should be understood that other similar embodiments can be used, or modifications and additions can be made to the described embodiments(s) to perform the same or equivalent functions of the corresponding embodiments(s) ...

Claims

1. Network equipment, including: processor; as well as Memory storing executable instructions that, when executed by the processor, improve the performance of operations including: Based on operational data, window parameter data for avoiding feedback and decision windows for inter-cell interference is determined for user equipment, wherein the operational data includes business model data representing the business model associated with the user equipment; The window parameter data is transmitted to the network node; Based on the window parameter data, report data representing interference mode data is received from the network node, the interference mode data representing an interference mode applicable to the user equipment; Based on the reported data, inter-cell interference avoidance data is determined, which can be used to facilitate the selection of network resources for communication with respect to the user equipment; and Inter-cell interference avoidance data is transmitted to the network node.

2. The network device according to claim 1, wherein the window parameter data includes at least one of the following: window reporting frequency data indicating the frequency at which the reception of the report data occurs; or window reporting size data indicating the size applicable to the report data.

3. The network device according to claim 1, wherein the operation data further includes quality of service related data, the quality of service related data representing the quality of service specifications applicable to the user equipment.

4. The network device according to claim 1, wherein the operation data further includes performance capability data representing the performance capabilities of the network node.

5. The network device according to claim 4, wherein the performance capability data of the network node includes at least one of the following: network function infrastructure capability data representing network function infrastructure capability; or network function link capacity data representing network function link capability.

6. The network device according to claim 1, wherein the window parameter data is first window parameter data for the first inter-cell interference avoidance feedback and decision window, wherein the operation data is first operation data, wherein the service mode data is first service data representing a first service mode associated with the user equipment, and wherein the operation further includes: Based on the information returned by the network node, it is determined that the first operation data has been changed to second operation data that is different from the first operation data. The second operation data includes second service mode data that represents a second service mode associated with the user equipment, and the second service mode data is different from the first service mode data. Based on the second operational data, second window parameter data is determined for the second inter-cell interference avoidance feedback and decision window, wherein the second window parameter data differs from the first window parameter data and the second window parameter data can be used to facilitate further selection of the network resources for further communication with respect to the user equipment; and The second window parameter data is transmitted to the network node.

7. The network device according to claim 6, wherein the operation further includes: In response to the communication of the second window parameter data, receive from the network node a communication indicating that the second window parameter data is not supported by the network node; In response to the communication, third window parameter data for the third feedback and decision window are determined; and The third window parameter data is transmitted to the network node.

8. The network device of claim 6, wherein the communication includes window parameter data related information, and wherein the determination of the third window parameter data includes: Process the window parameter data and related information.

9. The network device of claim 1, wherein the network device includes a radio access network intelligent controller, and wherein conveying the window parameter data to the network node comprises: The subscription request is sent from the radio access network intelligent controller to the network node.

10. The network device of claim 1, wherein the network node comprises at least one of the following: a centralized unit, a distributed unit, or a radio unit.

11. The network device of claim 1, wherein the reported data corresponds to at least one of the following: the user equipment's hybrid automatic repeat request information; or the user equipment's reference signal reception quality information.

12. The network device of claim 1, wherein the service mode data includes packet arrival interval rate data, the packet arrival interval rate data representing a packet arrival interval rate suitable for communication with the user equipment.

13. A method comprising: The system, including a processor, obtains first operational data from a network node coupled to a user equipment, the first operational data including first service mode data and first quality of service constraint data of the user equipment. The system determines the first window parameter data for inter-cell interference avoidance feedback and decision window based on the first operation data; The system transmits the first window parameter data to the network node; Based on the first window parameter data, the system receives first report data from the network node representing first interference mode data about the user equipment; Based on the first reported data, the system determines the first inter-cell interference avoidance data; The interference-avoidance data in the first cell is transmitted to the network node; Based on the information returned by the network node, it is determined that the first operation data has been changed to second operation data that is different from the first operation data. The second operation data includes the second service mode data of the user equipment, which is different from the first service mode data. The system determines second window parameter data for inter-cell interference avoidance feedback and decision window based on the second operation data, wherein the second window parameter data is different from the first window parameter data; as well as The system transmits the second window parameter data to the network node.

14. The method of claim 13, further comprising: The system receives communication from the network node indicating that the second window parameter data is not supported by the network node in response to conveying the second window parameter data. In response to the communication, the system determines third window parameter data for the third feedback and decision window, and The system transmits the third window parameter data to the network node.

15. The method of claim 14, wherein the communication includes window parameter data related information, and wherein the determination of the third window parameter data includes: Process the window parameter data and related information.

16. The method of claim 13, further comprising: The system receives second report data from the network node based on the second window parameter data. The second report data represents second interference mode data regarding the user equipment. The system determines the second inter-cell interference avoidance data based on the second reported data, and The system transmits the second inter-cell interference avoidance data to the network node.

17. A non-transitory machine-readable medium comprising executable instructions that, when executed by a processor, improve the performance of operations, said operations including: Obtain first operation data of the first user equipment, wherein the first operation data includes first service data of the first user equipment; Obtain second operational data from the second user equipment, the second operational data including second service data of the second user equipment; Based on the first operation data and the second operation data, the first user equipment is given priority over the second user equipment; Based on the first operation data, generate first recommended window parameter data for the first user equipment regarding interference avoidance feedback and decision window in the first cell; The first window parameter data is transmitted to the network node; Based on the second operation data, generate second recommendation window parameter data for the second user equipment regarding the second inter-cell interference avoidance feedback and decision window; as well as The second window parameter data is transmitted to the network node.

18. The non-transitory machine-readable medium of claim 17, wherein the operation further comprises: Obtain third operation data of the first user equipment, wherein the third operation data includes third service data of the first user equipment; Based on the third operation data, generate third recommendation window parameter data for the first user equipment regarding the third inter-cell interference avoidance feedback and decision window; And to transmit the third window parameter data to the network node.

19. The non-transitory machine-readable medium of claim 17, wherein the operation further comprises: In response to the communication of the second window parameter data, receive from the network node a communication indicating that the second window parameter data is not supported by the network node; In response to the communication, third recommendation window parameter data for the second user equipment regarding the third inter-cell interference avoidance feedback and decision window is generated based on the second operation data; And to transmit the third window parameter data to the network node.

20. The non-transitory machine-readable medium of claim 17, wherein the generation of the second recommendation window parameter data comprises: Determine the first candidate window parameter data for the second recommended window parameter data. In the first evaluation, it is assessed whether the parameter data of the first candidate window conforms to the network capability data. Based on the first evaluation, it is determined that the parameter data of the first candidate window does not conform to the network capability data. In response to determining that the first candidate window parameter data does not conform to the network capability data, second candidate window parameter data is determined for the second recommended window parameter data. In the second evaluation, it is assessed whether the parameter data of the second candidate window conforms to the network capability data. Based on the second evaluation, it is determined that the parameter data of the second first candidate window conforms to the network capability data, and In response to determining that the first candidate window parameter data conforms to the network capability data, the second candidate window parameter data is selected as the second window parameter data for communication to the network node.

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