Systems and methods for traffic flow shaping

Abstract

Systems and methods for traffic flow shaping may include a user equipment (UE) that determines a respective set of statistical parameters for a plurality of traffic flows for communication with a base station. The plurality of traffic flows may correspond to applications supported by the UE. The UE may send one or more messages in UE assistance information (UAI) signaling indicating statistical parameters for the plurality of traffic flows to the base station.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of and priority to U.S. Application No. 63 / 531,917, filed on August 10, 2023, and U.S. Application No. 18 / 767,541, filed on July 9, 2024, the contents of which are incorporated herein by reference in their entirety. Technical Field

[0003] The present disclosure generally relates to wireless communications between multiple devices, including but not limited to systems and methods for traffic flow shaping. Background Art

[0004] Augmented reality (AR), virtual reality (VR), and mixed reality (MR) are becoming more common, with these technologies supported on a wider range of platforms and devices. Some AR / VR / MR devices can communicate with other devices in the environment via various cellular connections or links. Summary of the invention

[0005] In one aspect, the present disclosure relates to a method. The method may include: determining, by a user equipment (UE), a corresponding set of statistical parameters for communicating with a base station for a plurality of service flows corresponding to applications supported by the UE. The method may include: sending, by the UE to the base station, one or more messages indicating the statistical parameters of the plurality of service flows in UE assistance information (UAI) signaling.

[0006] In some embodiments, the multiple service flows include the following service flows: the service flows are grouped together into multiple groups of service flows according to at least one of service characteristics or transmission conditions for sending services on the service flows included in one group. In some embodiments, the service characteristics include at least one of the following: service type, data rate, data burstiness, or data periodicity; and the transmission conditions include at least one of the following: delay conditions, packet loss conditions, power consumption conditions, or jitter conditions. In some embodiments, the UE determines the statistical parameters according to the type of application supported by the UE. In some embodiments, the statistical parameters of multiple service flows of a first application supported by the UE are different from the statistical parameters of multiple service flows of a second application supported by the UE.

[0007] In some embodiments, the multiple service flows include one or more service flows of the first group, and one or more service flows of the second group. In some embodiments, the statistical parameters of the first group are different from the statistical parameters of the second group. In some embodiments, the first group of statistical parameters is determined for the first group of service flows in the multiple service flows, and the second group of statistical parameters is determined for the second group of service flows in the multiple service flows. In some embodiments, the statistical parameters include at least one of the following: periodicity, jitter range, preferred connection mode discontinuous reception periodicity, preferred uplink configuration authorization offset, forward error correction parameters, or preferred packet data convergence protocol (PDCP) duplication configuration parameters. In some embodiments, the first group of statistical parameters of the first group of service flows in the multiple service flows include corresponding periodicity, corresponding jitter range, and preferred connection mode discontinuous reception periodicity; the second group of statistical parameters of the second group of service flows in the multiple service flows include corresponding periodicity, corresponding jitter range, and preferred uplink configuration authorization offset; and the third group of statistical parameters of the third group of service flows in the multiple service flows include forward error correction parameters and preferred packet data convergence protocol (PDCP) duplication configuration parameters.

[0008] In another aspect, the present disclosure relates to a wireless communication device, the wireless communication device comprising a wireless transceiver and one or more processors, the one or more processors being configured to: determine a corresponding set of statistical parameters for communicating with a base station corresponding to a plurality of service flows. The plurality of service flows may correspond to applications supported by the wireless communication device. The one or more processors may be configured to: send one or more messages indicating the statistical parameters of the plurality of service flows in user equipment (UE) auxiliary information (UAI) signaling to the base station via the wireless transceiver.

[0009] In some embodiments, the multiple service flows include the following service flows: the service flows are grouped together into multiple groups of service flows according to at least one of service characteristics or transmission conditions for sending services on the service flows included in one group. In some embodiments, the service characteristics include at least one of the following: service type, data rate, data burstiness, or data periodicity; and the transmission conditions include at least one of the following: delay conditions, packet loss conditions, power consumption conditions, or jitter conditions. In some embodiments, the one or more processors determine the statistical parameters according to the type of application supported by the wireless communication device. In some embodiments, the statistical parameters of multiple service flows of a first application supported by the wireless communication device are different from the statistical parameters of multiple service flows of a second application supported by the wireless communication device.

[0010] In some embodiments, the multiple service flows include one or more service flows of a first group, and one or more service flows of a second group. In some embodiments, the statistical parameters of the first group are different from the statistical parameters of the second group. In some embodiments, the first group of statistical parameters is determined for a first group of service flows in the multiple service flows, and the second group of statistical parameters is determined for a second group of service flows in the multiple service flows. In some embodiments, the statistical parameters include one or more of the following: periodicity, jitter range, preferred connection mode discontinuous reception periodicity, preferred uplink configuration authorization offset, one or more forward error correction parameters, or one or more preferred packet data convergence protocol (PDCP) repetition configuration parameters.

[0011] In another aspect, the present disclosure relates to a base station, the base station comprising a wireless transceiver and one or more processors, the one or more processors being configured to: receive one or more messages indicating statistical parameters of multiple service flows in UE assistance information (UAI) signaling from a user equipment (UE) via the wireless transceiver. The statistical parameters can be used for communication between the UE and the base station, and the multiple service flows correspond to applications supported by the UE. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The accompanying drawings are not intended to be drawn to scale. Like reference numbers and names in the various drawings indicate like elements. For clarity, not every component is labeled in every drawing.

[0013] Figure 1 is a schematic diagram of an example wireless communication system according to an example implementation of the present disclosure.

[0014] Figure 2 is a schematic diagram of a console and a head wearable display for presenting augmented reality or virtual reality according to an example embodiment of the present disclosure.

[0015] Figure 3 is a schematic diagram of a head wearable display according to an exemplary embodiment of the present disclosure.

[0016] Figure 4 is a block diagram of a computing environment according to an example implementation of the present disclosure.

[0017] Figure 5 is a block diagram of a system for traffic shaping according to an example embodiment of the present disclosure.

[0018] Figure 6 is a process flow illustrating an example of determining statistical parameters of a traffic flow according to an example implementation of the present disclosure.

[0019] Figure 7 is a flow chart illustrating an example method of traffic shaping according to an example implementation of the present disclosure. DETAILED DESCRIPTION

[0020] Before turning to the drawings that show certain embodiments in detail, it should be understood that the present disclosure is not limited to the details or methods set forth in the specification or shown in the drawings. It should also be understood that the terminology used herein is for descriptive purposes only and should not be considered as limiting.

[0021] Referring generally to the accompanying drawings, the systems and methods described herein relate to traffic shaping between a user equipment (UE) and a base station. UE assistance information (UAI) may include a mechanism by which the UE can notify the base station or the network of information (e.g., status information) so that the network can allocate resources to the UE accordingly. For extended reality (XR) (e.g., augmented reality, virtual reality, etc.) applications or services, the traffic flows associated with these services may have unique characteristics and transmission specifications or attributes (e.g., statistical parameters). Such characteristics may include data rate, burstiness, periodicity, and such transmission attributes may include latency, packet loss, power consumption, etc. In various embodiments, uplink (UL) traffic may be a bottleneck that may cause traffic congestion, increased latency, packet discards, etc.

[0022] According to the systems and methods described herein, the UE may map XR UL statistical parameters of the UL service to a set of UAI parameters of the UAI signaling and send the UAI signaling to the base station. The base station may then allocate resources to the UE based on the UAI signaling. For example, the UE may identify or determine a UL service flow to be used for a given application or resource to be executed / supported by the UE on the UE. The UE may determine one or more classifications / categories of UL service flows. The UE may determine a set of statistical information / attributes / parameters of the service flows related to these service flows. The UE may report the set of statistical parameters to the base station as part of the UAI signaling. The base station may allocate resources to the UE (e.g., to a specific service flow) based on the UAI signaling. Such implementation methods and embodiments may improve the efficiency of resource allocation by the base station, limit latency, and provide better support for XR applications or resources.

[0023] Figure 1An example wireless communication system 100 is shown. The wireless communication system 100 may include a base station 110 (also referred to as a "wireless communication node 110" or "station 110") and one or more user equipment (UE) 120 (also referred to as a "wireless communication device 120" or "terminal device 120"). The base station 110 and the UE 120 may communicate via wireless communication links 130A, 130B, 130N. The wireless communication link 130 may be a cellular communication link that complies with third generation mobile communication technology (3G), fourth generation mobile communication technology (4G), fifth generation mobile communication technology (5G), or other cellular communication protocols or Wi-Fi communication protocols. In one example, the wireless communication link 130 supports, employs, or is based on orthogonal frequency division multiple access (OFDMA). In one aspect, the UE 120 is located within a geographical boundary relative to the base station 110 and may communicate with or through the base station 110. In some embodiments, the wireless communication system 100 includes more than one wireless communication link. Figure 1 More components, fewer components, or including components shown in Figure 1 For example, the wireless communication system 100 may include components other than Figure 1 One or more additional base stations 110 other than the base station 110 shown in FIG.

[0024] In some embodiments, UE 120 may be a user device, such as a mobile phone, a smart phone, a personal digital assistant (PDA), a tablet computer, a laptop computer, a wearable computing device, etc. Each UE 120 may communicate with a base station 110 via a corresponding communication link 130. For example, UE 120 may send data to base station 110 via wireless communication link 130, and receive data from base station 110 via wireless communication link 130. Example data may include audio data, image data, text, etc. Communication or data transmission by UE 120 to base station 110 may be referred to as uplink communication. Communication or data reception by UE 120 from base station 110 may be referred to as downlink communication. In some embodiments, UE 120A includes a wireless interface 122, a processor 124, a memory device (also referred to as memory) 126, and one or more antennas 128. These components may be implemented as hardware, software, firmware, or a combination thereof. In some embodiments, UE 120A includes more than one embodiment. Figure 1 More components, fewer components, or including components shown in Figure 1For example, UE 120 may include an electronic display and / or input device. For example, UE 120 may include in addition to Figure 1 Additional antennas 128 and wireless interfaces 122 beyond the antennas 128 and wireless interfaces 122 shown in FIG.

[0025] Antenna 128 can be a component that receives radio frequency (RF) signals and / or sends RF signals through a wireless medium. The RF signal can be at a frequency between 200 megahertz (MHz) and 100 gigahertz (GHz). The RF signal can have a data packet, symbol or frame corresponding to the data used for communication. Antenna 128 can be a dipole antenna, a patch antenna, a loop antenna, or any suitable antenna for wireless communication. In one aspect, a single antenna 128 is used to both send and receive RF signals. In one aspect, different antennas 128 are used to send and receive RF signals. In one aspect, multiple antennas 128 are used to support multiple-input, multiple-out (MIMO) communications.

[0026] The wireless interface 122 includes or is implemented as a transceiver for sending and receiving RF signals through a wireless medium. The wireless interface 122 can communicate with the wireless interface 112 of the base station 110 through a wireless communication link 130A. In one configuration, the wireless interface 122 is coupled to one or more antennas 128. In one aspect, the wireless interface 122 can receive an RF signal at an RF frequency received by the antenna 128, and down-convert the RF signal to a baseband frequency (e.g., 0 GHz to 1 GHz). The wireless interface 122 can provide a down-converted signal to the processor 124. In one aspect, the wireless interface 122 can receive a baseband signal transmitted at a baseband frequency from the processor 124, and up-convert the baseband signal to generate an RF signal. The wireless interface 122 can send an RF signal through the antenna 128.

[0027] The processor 124 is a component for processing data. The processor 124 can be implemented as a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a logic circuit, etc. The processor 124 can obtain instructions from the memory device 126 and execute the instructions. In one aspect, the processor 124 can receive down-converted data at a baseband frequency from the wireless interface 122, and decode or process the down-converted data. For example, the processor 124 can generate audio data or image data based on the down-converted data, and present the audio indicated by the audio data and / or the image indicated by the image data to the user of the UE 120A. In one aspect, the processor 124 can generate or obtain data transmitted at a baseband frequency, and encode or process the data. For example, the processor 124 can encode or process image data or audio data at a baseband frequency, and provide the encoded or processed data to the wireless interface 122 for transmission.

[0028] The memory device 126 is a component that stores data. The memory device 126 can be implemented as a random access memory (RAM), a flash memory, a read only memory (ROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a register, a hard disk, a removable disk, a compact disc read-only memory (CD-ROM), or any device capable of storing data. The memory device 126 can be implemented as a non-transitory computer-readable medium that stores the following instructions: the instructions can be executed by the processor 124 to perform various functions of the UE 120A disclosed herein. In some embodiments, the memory device 126 and the processor 124 are integrated into a single component.

[0029] In some embodiments, each of UEs 120B ... 120N includes similar components of UE 120A for communicating with base station 110. Therefore, for the sake of brevity, detailed descriptions of repeated parts thereof are omitted herein.

[0030] In some embodiments, the base station 110 may be an evolved node B (eNB), a serving eNB, a target eNB, a femto station, or a pico station. The base station 110 may be communicatively coupled to another base station 110 or other communication device via a wireless communication link and / or a wired communication link. The base station 110 may receive data (or RF signals) from the UE 120 in an uplink communication. Additionally or alternatively, the base station 110 may provide data to another UE 120, another base station, or another communication device. Thus, the base station 110 allows communication between multiple UEs 120 associated with the base station 110, or allows communication between other multiple UEs associated with different base stations. In some embodiments, the base station 110 includes a wireless interface 112, a processor 114, a memory device (also referred to as a memory) 116, and one or more antennas 118. These components may be implemented as hardware, software, firmware, or a combination thereof. In some embodiments, the base station 110 includes more than one embodiment of the present invention. Figure 1 More components, fewer components, or including components shown in Figure 1 For example, base station 110 may include an electronic display and / or an input device. For example, base station 110 may include an electronic display and / or an input device. Figure 1 An additional antenna 118 and wireless interface 112 are provided in addition to the antenna 118 and wireless interface 112 shown in FIG.

[0031] Antenna 118 may be a component that receives radio frequency (RF) signals and / or transmits RF signals through a wireless medium. Antenna 118 may be a dipole antenna, a patch antenna, a loop antenna, or any suitable antenna for wireless communication. In one aspect, a single antenna 118 is used to both transmit and receive RF signals. In one aspect, different antennas 118 are utilized to transmit and receive RF signals. In one aspect, multiple antennas 128 are utilized to support multiple-input multiple-output (MIMO) communications.

[0032] The wireless interface 112 includes or is implemented as a transceiver for sending and receiving RF signals through a wireless medium. The wireless interface 112 can communicate with the wireless interface 122 of the UE 120 through a wireless communication link 130. In one configuration, the wireless interface 112 is coupled to one or more antennas 118. In one aspect, the wireless interface 112 can receive an RF signal at an RF frequency received by the antenna 118, and down-convert the RF signal to a baseband frequency (e.g., 0 GHz to 1 GHz). The wireless interface 112 can provide the processor 114 with a down-converted signal. In one aspect, the wireless interface 122 can receive a baseband signal transmitted at a baseband frequency from the processor 114, and up-convert the baseband signal to generate an RF signal. The wireless interface 112 can send an RF signal through the antenna 118.

[0033] Processor 114 is a component for processing data. Processor 114 can be implemented as FPGA, ASIC, logic circuit, etc. Processor 114 can obtain instructions from memory device 116 and execute the instructions. In one aspect, processor 114 can receive down-converted data at baseband frequency from wireless interface 112, and decode or process the down-converted data. For example, processor 114 can generate audio data or image data based on down-converted data. In one aspect, processor 114 can generate or obtain data for transmission at baseband frequency, and encode or process the data. For example, processor 114 can encode or process image data or audio data at baseband frequency, and provide encoded or processed data to wireless interface 112 for transmission. In one aspect, processor 114 can set, assign, schedule or allocate communication resources for different UE120. For example, processor 114 can set different modulation schemes, time slots, channels, frequency bands, etc. for each UE 120 to avoid interference. The processor 114 may generate data (or an uplink configuration grant (UL CG)) indicating the configuration of communication resources and provide the data (or UL CG) to the wireless interface 112 for transmission to the UE 120 .

[0034] The memory device 116 is a component that stores data. The memory device 116 may be implemented as a RAM, flash memory, ROM, EPROM, EEPROM, registers, a hard disk, a removable disk, a CD-ROM, or any device capable of storing data. The memory device 116 may be implemented as a non-transitory computer-readable medium that stores instructions that can be executed by the processor 114 to perform various functions of the base station 110 disclosed herein. In some embodiments, the memory device 116 and the processor 114 are integrated into a single component.

[0035] In some embodiments, the communication between the base station 110 and the UE 120 is based on one or more layers of the Open Systems Interconnection (OSI) model. The OSI model may include multiple layers, including: a physical layer; a medium access control (MAC) layer; a radio link control (RLC) layer; a packet data convergence protocol (PDCP) layer; a radio resource control (RRC) layer; a non-access stratum (NAS) layer or an Internet Protocol (IP) layer; and other layers.

[0036] Figure 2 is a block diagram of an example artificial reality system environment 200. In some embodiments, the artificial reality system environment 200 includes a HWD 250 worn by a user, and a console 210 that provides artificial reality (e.g., augmented reality, virtual reality, mixed reality) content to the HWD 250. Each of the HWD 250 and the console 210 may be a separate UE 120. The HWD 250 may be referred to as, include, or be a part of a head mounted display (HMD), a head mounted device (HMD), a head wearable device (HWD), a head worn display (HWD), or a head worn device (HWD). The HWD 250 may detect the position and / or orientation of the HWD 250, and the shape, position and / or orientation of the body / hand / face of the user, and provide the detected position and / or orientation of the HWD 250, and / or tracking information indicating the shape, position and / or orientation of the body / hand / face to the console 210. The console 210 may generate image data indicating an artificial reality image based on the following items, and send the image data to the HWD 250 for presentation. In some embodiments, the artificial reality system environment 200 includes more than Figure 2 More components, fewer components, or including components shown in Figure 2In some embodiments, the functionality of one or more components in the artificial reality system environment 200 may be distributed among the components in a manner different from that described herein. For example, some functions of the console 210 may be performed by the HWD 250. For example, some functions of the HWD 250 may be performed by the console 210. In some embodiments, the console 210 is integrated as part of the HWD 250.

[0037] In some embodiments, HWD 250 is an electronic component that can be worn by a user and can present or provide an artificial reality experience to the user. HWD 250 can render one or more images, videos, audio, or some combination thereof to provide an artificial reality experience to the user. In some embodiments, audio is presented via an external device (e.g., a speaker and / or headphones) that receives audio information from HWD 250, console 210, or both and presents audio based on the audio information. In some embodiments, HWD 250 includes a sensor 255, a wireless interface 265, a processor 270, an electronic display 275, a lens 280, and a compensator 285. These components can operate together to detect the position of HWD 250 and the gaze direction of the user wearing HWD 250, and render an image of a field of view corresponding to the detected position and / or orientation of HWD 250 within an artificial reality. In other embodiments, HWD 250 includes a sensor 255, a wireless interface 265, a processor 270, an electronic display 275, a lens 280, and a compensator 285. These components can operate together to detect the position of HWD 250 and the gaze direction of the user wearing HWD 250, and render an image of a field of view corresponding to the detected position and / or orientation of HWD 250 within an artificial reality. In other embodiments, HWD 250 includes a sensor 255, a wireless interface 265, a processor 270, an electronic display 275, a lens 280, and a compensator 285. Figure 2 More components, fewer components, or including components shown in Figure 2 The components shown in the figure are different components.

[0038] In some embodiments, sensor 255 includes an electronic component or a combination of an electronic component and a software component that detects the position and orientation of HWD 250. Examples of sensor 255 may include: one or more imaging sensors, one or more accelerometers, one or more gyroscopes, one or more magnetometers, or another suitable type of sensor that detects motion and / or position. For example, one or more accelerometers may measure translational motion (e.g., forward / backward, upward / downward, left / right), and one or more gyroscopes may measure rotational motion (e.g., pitch, yaw, roll). In some embodiments, sensor 255 detects translational motion and rotational motion, and determines the orientation and position of HWD 250. In one aspect, sensor 255 may detect translational motion and rotational motion relative to the previous orientation and position of HWD 250, and determines the new orientation and / or position of HWD 250 by accumulating or integrating the detected translational motion and / or rotational motion. For example, assuming that HWD 250 is facing a direction 25 degrees from a reference direction, sensor 255 may determine that HWD 250 is now facing or facing a direction 45 degrees from the reference direction in response to detecting that HWD 250 has turned 20 degrees. For another example, assuming that HWD 250 is located two feet away from a reference point in a first direction, sensor 255 may determine that HWD 250 is now located at the vector product of two feet in the first direction and three feet in the second direction in response to detecting that HWD 250 has moved three feet in the second direction.

[0039] In some embodiments, the sensor 255 includes an eye tracker. These eye trackers may include electronic components, or a combination of electronic components and software components, that determine the gaze direction of the user of the HWD 250. In some embodiments, the HWD 250, the console 210, or a combination thereof may generate image data for artificial reality in conjunction with the gaze direction of the user of the HWD 250. In some embodiments, the plurality of eye trackers include two eye trackers, each of which captures an image of a corresponding eye and determines the gaze direction of the eye. In one example, the eye tracker determines the angular rotation of the eye, the translation of the eye, the torsion change of the eye, and / or the change in the shape of the eye based on the captured eye image, and determines the relative gaze direction relative to the HWD 250 based on the determined angular rotation of the eye, the translation of the eye, and the torsion change of the eye. In one method, the eye tracker may illuminate or project a predetermined reference pattern or structured pattern on a portion of the eye, and capture an image of the eye to analyze the pattern projected on the portion of the eye to determine the relative gaze direction of the eye relative to the HWD 250. In some embodiments, the eye tracker determines the user's gaze direction in combination with the orientation of HWD 250 and the relative gaze direction relative to HWD 250. For example, assuming that HWD 250 is oriented in a direction 30 degrees from a reference direction, and the relative gaze direction of HWD 250 relative to HWD 250 is -10 degrees (or 350 degrees), the eye tracker can determine that the user's gaze direction is 20 degrees from the reference direction. In some embodiments, the user of HWD 250 can configure HWD 250 (e.g., via user settings) to enable or disable the eye tracker. In some embodiments, the user of HWD 250 is prompted to enable or disable the eye tracker.

[0040] In some embodiments, the wireless interface 265 includes electronic components, or a combination of electronic components and software components, that communicate with the console 210. The wireless interface 265 may be or correspond to the wireless interface 122. The wireless interface 265 may communicate with the wireless interface 215 of the console 210 via a wireless communication link via the base station 110. Through the communication link, the wireless interface 265 may transmit data indicating the determined position and / or orientation of the HWD 250 and / or the determined user gaze direction to the console 210. In addition, through the communication link, the wireless interface 265 may receive image data indicating or corresponding to an image to be rendered and additional data associated with the image from the console 210.

[0041] In some embodiments, the processor 270 includes an electronic component, or a combination of electronic components and software components, that generates one or more images for display (e.g., according to a change in the field of view of the space of the artificial reality). In some embodiments, the processor 270 is implemented as a part of the processor 124, or is communicatively coupled to the processor 124. In some embodiments, the processor 270 is implemented as a processor (or a graphical processing unit (GPU)) that executes multiple instructions to perform various functions described herein. The processor 270 can receive image data describing an artificial reality image to be rendered, and additional data associated with the image through the wireless interface 265, and the processor 270 can render the image for display through the electronic display 275. In some embodiments, the image data from the console 210 can be encoded, and the processor 270 can decode the image data to render the image. In some embodiments, the processor 270 receives object information and depth information located in the additional data from the console 210, the object information indicating a virtual object in the artificial reality space, and the depth information indicating the depth of the virtual object (or the distance from the HWD 250). In one aspect, the processor 270 may perform shading, reprojection, and / or blending based on the artificial reality image from the console 210, object information, depth information, and / or updated sensor measurements from the sensor 255 to update the artificial reality image to correspond to the updated position and / or orientation of the HWD 250. Assuming that the user turns his head after the initial sensor measurements, the processor 270 may generate a small portion (e.g., 10%) of the image corresponding to the updated field of view within the artificial reality based on the updated sensor measurements and append the portion to the image in the image data from the console 210 by reprojection, rather than reconstructing the entire image in response to the updated sensor measurements. The processor 270 may perform shading and / or blending on the additional edges. Thus, the processor 270 may generate an image of the artificial reality without reconstructing the image of the artificial reality based on the updated sensor measurements.

[0042] In some embodiments, the electronic display 275 is an electronic component that displays an image. The electronic display 275 may be, for example, a liquid crystal display or an organic light emitting diode display. The electronic display 275 may be a transparent display that allows the user to see through. In some embodiments, when the user wears the HWD 250, the electronic display 275 is located near the user's eyes (e.g., less than 3 inches). In one aspect, the electronic display 275 emits light or projects light toward the user's eyes according to the image generated by the processor 270.

[0043] In some embodiments, lens 280 is a mechanical component that changes the light received from electronic display 275. Lens 280 can magnify the light from electronic display 275 and correct the optical errors associated with the light. Lens 280 can be a Fresnel lens, a convex lens, a concave lens, a filter, or any suitable optical component that changes the light from electronic display 275. Although electronic display 275 is very close to both eyes, light from electronic display 275 can still pass through lens 280 to the pupil so that the user can see the image displayed by electronic display 275.

[0044] In some embodiments, compensator 285 includes electronic components, or a combination of electronic components and software components, that perform compensation to compensate for any distortion or aberration. In one aspect, lens 280 introduces optical aberrations (e.g., chromatic aberration), pincushion distortion, barrel distortion, etc. Compensator 285 can determine compensation (e.g., pre-distortion) to be applied to the image to be rendered from processor 270 to compensate for the distortion caused by lens 280, and apply the determined compensation to the image from processor 270. Compensator 285 can provide the pre-distorted image to electronic display 275.

[0045] In some embodiments, the console 210 is an electronic component or a combination of an electronic component and a software component that provides content to be rendered to the HWD 250. In one aspect, the console 210 includes a wireless interface 215 and a processor 230. These components can be run together to determine the visual field of the artificial reality corresponding to the position of the HWD 250 and the gaze direction of the user of the HWD 250 (e.g., the user's field of view (FOV)), and can generate image data indicating the artificial reality image corresponding to the determined visual field. In addition, these components can be run together to generate additional data associated with the image. Additional data can be information associated with presenting or rendering artificial reality in addition to the artificial reality image. Examples of additional data include hand model data, mapping information (or simultaneous localization and mapping (SLAM) data) for converting the position and orientation of the HWD 250 in the physical space to the virtual space, eye tracking data, motion vector information, depth information, edge information, object information, etc. The console 210 may provide image data and additional data to the HWD 250 for use in presenting artificial reality. Figure 2 More components, fewer components, or including components shown in Figure 2 In some embodiments, console 210 is integrated as a part of HWD 250.

[0046] In some embodiments, the wireless interface 215 is an electronic component, or a combination of an electronic component and a software component, that communicates with the HWD 250. The wireless interface 215 may be or correspond to the wireless interface 122. The wireless interface 215 may be a corresponding component of the wireless interface 265 to communicate via a communication link (e.g., a wireless communication link). The wireless interface 215 may receive data from the HWD 250 via the communication link, the data indicating the determined position and / or orientation of the HWD 250, and / or the determined user gaze direction. In addition, via the communication link, the wireless interface 215 may transmit image data describing the image to be rendered and additional data associated with the image of the artificial reality to the HWD 250.

[0047] The processor 230 may include or correspond to a component that generates content to be rendered based on the position and / or orientation of the HWD 250. In some embodiments, the processor 230 is implemented as a part of the processor 124 or is communicatively coupled to the processor 124. In some embodiments, the processor 230 may be combined with the gaze direction of the user of the HWD 250. In one aspect, the processor 230 determines the view of the artificial reality based on the position and / or orientation of the HWD 250. For example, the processor 230 maps the position of the HWD 250 in the physical space to a position within the artificial reality space, and determines the view of the artificial reality space along the direction corresponding to the mapped orientation from the position in the mapped artificial reality space. The processor 230 may generate image data of an image describing the view of the determined artificial reality space, and transmit the image data to the HWD 250 via the wireless interface 215. In some embodiments, the processor 230 may generate additional data associated with the image (the additional data may include motion vector information, depth information, edge information, object information, hand model data, etc.), and transmit the additional data together with the image data to the HWD 250 through the wireless interface 215. The processor 230 may encode the image data describing the image, and may transmit the encoded data to the HWD 250. In some embodiments, the processor 230 generates image data periodically (e.g., every 11 milliseconds (ms)) and provides the image data to the HWD 250.

[0048] In one aspect, the process of detecting the position of the HWD 250 and the gaze direction of the user wearing the HWD 250 and rendering the image to the user should be performed within one frame time (e.g., 11ms or 16ms). The delay between the movement of the user wearing the HWD 250 and the image displayed corresponding to the user's movement may cause jitter, which may cause motion sickness and may reduce the user experience. In one aspect, the HWD 250 and the console 210 can prioritize the communication of AR / VR so that the delay between the movement of the user wearing the HWD 250 and the image displayed corresponding to the user's movement can be presented within one frame time (e.g., 11ms or 16ms) to provide a seamless experience.

[0049] Figure 3 2 is a schematic diagram of HWD 250 according to an exemplary embodiment. In some embodiments, HWD 250 includes a front rigid body 305 and a belt 310. Front rigid body 305 includes: electronic display 275 ( Figure 3 Not shown), lens 280 ( Figure 3 ), sensor 255, wireless interface 265, and processor 270. Figure 3 In the illustrated embodiment, the wireless interface 265, processor 270, and sensor 255 are located within the front rigid body 305 and may not be visible to the outside. Figure 3 For example, the wireless interface 265, the processor 270 and / or the sensor 255 may be located in a different configuration than that shown in FIG. Figure 3 The positions shown in the figure are different positions.

[0050] Various operations described herein can be implemented on a computer system. Figure 4 A block diagram of a representative computing system 414 that can be used to implement the present disclosure is shown. In some embodiments, the base station 110, UE 120, console 210, HWD 250 can be implemented by the computing system 414. The computing system 414 can be implemented, for example, as a consumer device, such as a smartphone, other mobile phones, tablet computers, wearable computing devices (e.g., smart watches, glasses, head wearable displays), desktop computers, laptop computers; or can be implemented using distributed computing devices. The computing system 414 can be implemented to provide VR experience, AR experience, MR experience. In some embodiments, the computing system 414 may include traditional computer components, such as a processor unit 416, a storage device 418, a network interface 420, a user input device 422, and a user output device 424.

[0051] The network interface 420 can provide a connection to a wide area network (e.g., the Internet) to which a wide area network (WAN) interface of the remote server system is also connected. The network interface 420 can include a wired interface (e.g., Ethernet) and / or a wireless interface that implements various radio frequency (RF) data communication standards, such as Wi-Fi, Bluetooth, or cellular data network standards (e.g., 3G, 4G, 5G, 60GHz, Long Term Evolution (LTE), etc.).

[0052] The network interface 420 may include a transceiver to allow the computing system 414 to send data to a remote device using a transmitter and to receive data from a remote device using a receiver. The transceiver may be configured to support such transmission / reception: the transmission / reception supports industrial standards for implementing two-way communication. An antenna may be attached to the transceiver housing and electrically coupled to the transceiver. Additionally or alternatively, a multi-antenna array may be electrically coupled to the transceiver so that multiple beams pointing in different directions can facilitate sending and / or receiving data.

[0053] The transmitter may be configured to wirelessly transmit a frame, time slot, or symbol generated by the processor unit 416. Similarly, the receiver may be configured to receive a frame, time slot, or symbol, and the processor unit 416 may be configured to process the frame. For example, the processor unit 416 may be configured to determine the type of frame and process the frame and / or fields of the frame accordingly.

[0054] User input device 422 may include any device (or devices) via which a user may provide signals to computing system 414; computing system 414 may interpret these signals as indicating a particular user request or information. User input device 422 may include any or all of the following: a keyboard; a touch pad; a touch screen; a mouse or other pointing device; a scroll wheel; a click wheel; a dial; a button; a switch; a keypad; a microphone; and a sensor (e.g., a motion sensor, an eye tracking sensor, etc.), etc.

[0055] User output device 424 may include any device via which computing system 414 can provide information to a user. For example, user output device 424 may include a display for displaying images generated by computing system 414 or delivered to computing system 314. The display may be combined with various image generation technologies and supporting electronic devices (e.g., digital-to-analog converters or analog-to-digital converters, or signal processors, etc.), such as liquid crystal displays (LCDs), light-emitting diodes (LEDs) including organic light-emitting diodes (OLEDs), projection systems, or cathode ray tubes (CRTs), etc. Devices that act as both input devices and output devices, such as touch screens, may be used. User output device 424 may be provided in addition to or in place of a display. Examples include indicator lights, speakers, tactile "display" devices, and printers, etc.

[0056] Some embodiments include electronic components storing computer program instructions in computer-readable storage media (e.g., non-transient computer-readable media), such as microprocessors, storage devices, and memory. Many of the multiple features described in this specification may be implemented as a process: the process is specified as a set of program instructions encoded on a computer-readable storage medium. These program instructions, when executed by one or more processors, cause the processor to perform the various operations indicated in these program instructions. Examples of program instructions or computer codes include machine codes and files, which are generated, for example, by a compiler, and the files include high-level codes executed by a computer, electronic component, or microprocessor using an interpreter. Through suitable programming, the processor unit 416 can provide various functions for the computing system 414, including any of the following: functions described herein as being executed by a server or client, or other functions associated with a message management service.

[0057] It will be understood that computing system 414 is illustrative and various variations and modifications may be made. The computer system used in conjunction with the present disclosure may have other capabilities not explicitly described herein. In addition, although computing system 414 is described with reference to specific blocks, it should be understood that these blocks are defined for the convenience of description and are not intended to imply a specific physical arrangement structure of component parts. For example, different blocks may be located in the same facility, in the same server rack, or on the same motherboard. In addition, these blocks do not have to correspond to physically different components. Each block may be configured to perform various operations, such as by programming a processor or providing an appropriate and suitable control circuit, and various blocks may or may not be reconfigurable, depending on how to obtain the initial configuration. Embodiments of the present disclosure may be implemented in a variety of devices, including electronic devices implemented using any combination of circuits and software.

[0058] Reference now Figure 5 Depicted is a system 500 for traffic shaping according to an example embodiment of the present disclosure. The system 500 may include a wireless communication device 502 that is communicatively coupled to a wireless communication node 504. As described in more detail below, the wireless communication device 502 may be configured to determine statistical parameters 506 for a plurality of traffic flows 508 for communicating with the wireless communication node 504, wherein the traffic flows 508 may correspond to resources, services, or applications supported by the wireless communication device 502. The wireless communication device 502 may be configured to transmit, send, provide, or otherwise communicate one or more messages indicating the statistical parameters 506 of the plurality of traffic flows 508 to the wireless communication node 504. For example, the wireless communication device 502 may be configured to send one or more messages in one or more user equipment (UE) assistance information (UAI) signaling to the wireless communication node 504. The wireless communication node 504 may be configured to use the UAI signaling (e.g., indicating the statistical parameters 506 of the plurality of traffic flows 508) to allocate resources to the wireless communication device 502.

[0059] The wireless communication device 502 may be the same as or similar to the UE 120, and the wireless communication node 504 may be the same as or similar to the base station 110, both of which are referred to above. Figures 1 to 4For example, the wireless communication device 502 and the wireless communication node 504 may include processors 124, 114, similar to the processors described above, respectively, and memories 126, 116, similar to the memories described above, respectively. In addition, the wireless communication device 502 may include a wireless transceiver 512, and the wireless communication node 504 may include a wireless transceiver 514, the wireless transceivers 512, 514 include wireless interfaces 122, 112, respectively, and include one or more antennas 128, one or more antennas 118, respectively. The wireless transceivers 512, 514 may facilitate, support, or provide wireless communication between the wireless communication device 502 and the wireless communication node 504.

[0060] In various embodiments, the wireless communication device 502 and the wireless communication node 504 may exchange (e.g., send and / or receive) data that supports or otherwise corresponds to one or more applications, one or more resources, or one or more services executed on or supported by the wireless communication device 502. For example, the wireless communication device 502 may be configured to exchange data with the wireless communication node 504 that corresponds to an extended reality (XR) application / resource / service executed on or supported by the wireless communication device 502. Such data may include uplink data / traffic (e.g., traffic sent from the wireless communication device 502 to the wireless communication node 504) for transmission or provision to an endpoint (e.g., a resource server, another wireless communication device 502). Such data may also include downlink data / traffic (e.g., traffic received by the wireless communication node 504 for transmission to the wireless communication device 502).

[0061] In various embodiments, uplink traffic may be sent via separate traffic flows 508 (e.g., flows 508 corresponding to or otherwise including specific types of traffic, such as video traffic, audio traffic, gesture traffic, control traffic, and model traffic, etc.). For example, a connection between a wireless communication device 502 and a wireless communication node 504 may include multiple traffic flows 508(1) to 508(N), such as a traffic flow 508 for audio traffic, a traffic flow 508 for video traffic, a traffic flow 508 for gesture traffic, a traffic flow 508 for control traffic, and a traffic flow 508 for model (e.g., avatar model) traffic, etc. For a given resource / service / application, the traffic flows 508 may have different traffic characteristics or transmission conditions based on the type of information / data being exchanged or included in the traffic. For example, audio traffic and video traffic may be more periodic (e.g., at a certain frequency or refresh rate) and may involve greater power requirements. As another example, gesture services and control services may be more sensitive to latency because delays in receiving such services may reduce the user experience due to lags. As yet another example, model services may be more sensitive to dropped packets. As described in more detail below, the wireless communication device 502 may be configured to determine statistical parameters 506 for a service flow 508, wherein these statistical parameters correspond to the services of the service flow 508. The wireless communication device 502 may be configured to generate UAI signaling, which is used to indicate the statistical parameters to the wireless communication node 504, so that the wireless communication node 504 can optimize / allocate the resources of the connection based on such statistical parameters (e.g., provide more bandwidth for power-sensitive service flows 508, increase throughput for delay-sensitive service flows 508, etc.).

[0062] The wireless communication device 502 and the wireless communication node 504 may include processing engines 516 and 518, respectively. The processing engines 516 and 518 may be or include any device, component, element or hardware designed or configured to perform various functions of the corresponding device. For example, the wireless communication device 502 may include an application (application, app) execution engine 520, a traffic shaping engine 522, a traffic fusion engine 524 and a signal generator 526. The wireless communication node 504 may include a signal processing engine 528 and a resource allocation engine 530. Although these one or more processing engines 516 and 518 are shown and described, it should be noted that the present disclosure is not limited to these specific one or more processing engines 516 and 518. For example, additional or alternative processing engines 516 and 518 may be implemented by the corresponding device. Similarly, one or more processing engines 516 and 518 may be divided into multiple processing engines 516 and 518, or two or more processing engines 516 and 518 may be combined into a single processing engine 516 and 518. Additionally, some processing engines 516, 518 may execute locally while other processing engines 516, 518 may execute remotely.

[0063] The wireless communication device 502 may include an app execution engine 520. The app execution engine 520 may be configured to support, execute, provision, or otherwise provide resources, services, or applications (collectively, "apps") on the wireless communication device 502. For example, the app execution engine 520 may be configured to execute programs or machine-readable instructions to provide apps to end users of the wireless communication device 502 (e.g., using various hardware of the wireless communication device 502, such as a display, one or more speakers, one or more sensors, and one or more input and output devices, etc.). The app execution engine 520 may be configured to support or provide different types of apps. For example, the app execution engine 520 may be configured to provide XR apps (e.g., augmented reality apps or virtual reality apps), mobile communication apps (e.g., audio call apps or video call apps, messaging apps), and gaming apps, etc.

[0064] Apps supported by the app execution engine 520 can use or utilize a wireless communication link or channel between the wireless communication device 502 and the wireless communication node 504 to exchange data with an endpoint. For example, an audio call app or a video call app can use a wireless communication channel to exchange audio data / video data between devices corresponding to each user participating in the audio call / video call. In addition, depending on the type of app, some apps can use or utilize wireless communication channels to exchange different types of data, which may involve or require different quality of service (QoS) metrics or attributes. For example, some business types may be more sensitive to power than other business types, some business types may be more sensitive to latency than other business types, and / or some business types may be more sensitive to reliability than other business types. In addition, depending on the type of app, some business types may have different QoS attributes. For example, for an audio call app or a video call app, a business type (e.g., audio business) may be latency sensitive, but for an XR app, the business type may be power sensitive.

[0065] In various embodiments, the wireless communication link or channel may support or include multiple service flows 508 for each type of service used by the app. For example, the wireless communication channel may include service flows 508 for each type of service, such as service flows 508(1) for audio services or video services, service flows 508(2) for gesture services or control services, and service flows 508(N) for model services, etc. Each service flow 508 may be or include service flows (or data packets) that carry / include / correspond to the same type of service. As described in more detail below, the wireless communication node 504 may be configured to allocate one or more resources to the service flow 508 based on or according to the requirements / specifications / attributes / parameters 506 of the service flow 508, which may be indicated in one or more UE assistance information (UAI) messages or signaling.

[0066] The wireless communication device 502 may include a traffic shaping engine 522. The traffic shaping engine 522 may be configured to determine, detect, or otherwise identify each of the plurality of traffic flows 508 to be used by the app execution engine 520 to support the app. In some embodiments, the traffic shaping engine 522 may be configured to identify each of the plurality of traffic flows 508 by cross-referencing the app or the app type of the app with a database or data structure to identify or determine the specific traffic flow 508 to be used by the app. In some embodiments, the traffic shaping engine 522 may be configured to identify each of the plurality of traffic flows 508 based on a request / response / negotiation of a wireless communication link between the wireless communication device 502 and the wireless communication node 504 (e.g., based on the requested traffic flow 508). In some embodiments, the traffic shaping engine 522 may be configured to identify each of the plurality of traffic flows based on source Internet Protocol (IP) and destination IP addresses, port numbers, protocol types, application signatures, etc.

[0067] The traffic shaping engine 522 may be configured to classify and / or shape the plurality of traffic flows 508. In some embodiments, the traffic shaping engine 522 may be configured to classify the plurality of traffic flows 508 by grouping the plurality of traffic flows 508 together based on or according to traffic characteristics or transmission conditions. For example, the traffic shaping engine 522 may be configured to classify the plurality of traffic flows 508 by assigning each of the plurality of traffic flows 508 to a specific group based on the following items: traffic type; target data rate / maximum data rate / minimum data rate, etc.; burstiness; periodicity; latency; packet loss; power consumption; and jitter, etc. In some embodiments, the traffic shaping engine 522 may be configured to group the plurality of traffic flows 508 together based on the type of traffic that shares the same traffic characteristics or transmission conditions. For example, for an XR app, the traffic shaping engine 522 may be configured to group the video traffic flow 508 and the audio traffic flow 508 together into the same category (e.g., a power optimization category) based on the video traffic and the audio traffic that use more transmission power (e.g., due to power sensitivity relative to other types of traffic). As another example, the traffic shaping engine 522 can be configured to group the gesture traffic flow 508 and the control traffic flow 508 together into the same category (e.g., a latency optimization category) based on the gesture traffic and the control traffic being more sensitive to latency and delay than other types of traffic. As yet another example, the traffic shaping engine 522 can be configured to group the model traffic flow 508 and the voice over IP (VoIP) traffic flow 508 together into the same category (e.g., a reliability optimization category) based on the model traffic and the voice over IP (VoIP) traffic being more sensitive to packet drops or reliability than other types of traffic.

[0068] In various embodiments, the traffic shaping engine 522 can be configured to group traffic flows 508 based on specific apps that are using or utilizing the wireless communication channel or link. For example, different traffic flows 508 can be grouped differently based on specific applications / resources / services executed on or supported by the wireless communication device 502 (e.g., via the app execution engine 520). As an example, the audio traffic flow of a gaming app can be assigned to a power-sensitive classification, but the audio traffic flow of a VoIP app can be assigned to a latency-sensitive classification. In this regard, the traffic shaping engine 522 can be configured to group traffic flows 508 based on apps or app types of apps. In addition, by grouping traffic flows 508 differently based on app / app type, the traffic convergence engine 524 can be configured to determine, identify, configure, or otherwise select different traffic attributes / requirements / configurations / parameters of the traffic flows 508 based on the specific categories to which the traffic flows 508 are assigned.

[0069] For each classification, the traffic shaping engine 522 can be configured to shape or combine similar flows within the category / classification. For example, the traffic shaping engine 522 can be configured to combine multiple flows 508 of a category into a single flow 508 based on flows 508 that share the same characteristics / requirements / specifications / parameters / attributes. In some embodiments, the traffic shaping engine 522 can be configured to apply one or more shaping policies to traffic flows 508 based on current network conditions, app support requirements, and congestion levels, etc. For example, these shaping policies can include / implement / trigger / utilize rate limiting, priority assignment, queue management, etc.

[0070] The wireless communication device 502 may include a traffic convergence engine 524. The traffic convergence engine 524 may be designed or configured to identify, select, configure, or otherwise determine (e.g., determined by the traffic shaping engine 522) one or more statistical parameters 506 for each category of traffic flow 508. The statistical parameters 506 may be or include QoS metrics / configurations / requirements, such as, but not limited to, QoS requirements related to traffic characteristics or transmission conditions used to classify such traffic flow 508. For example, the statistical parameters 506 may include periodicity (e.g., minimum / maximum / average), jitter range, connected mode discontinuous reception (CDRX) periodicity, preferred uplink configuration grant offset, forward error correction (FEC) parameters, and preferred packet data convergence protocol (PDCP) repetition configuration, etc.

[0071] In some embodiments, the business fusion engine 524 can be configured to determine the statistical parameters 506 based on the classification to which the business flow 508 is assigned. For example, the business fusion engine 524 can be configured to determine that the statistical parameters 506 of each business flow 508 assigned to a specific classification are the same as other business flows 508 within the same classification, and can determine that the statistical parameters 506 of other business flows 508 assigned to different classifications are different. In some embodiments, the business fusion engine 524 can be configured to assign different types of statistical parameters 506 to business flows 508 of different classifications. For example, the type of statistical parameters 506 can be related to the specific requirements / configuration of the classification of the business flow, etc. Some non-limiting examples of the types of statistical parameters 506 that can be assigned to business flows 508 of corresponding classifications, and business flows 508 of related types that can be assigned to corresponding classifications are provided in Table 1 below.

[0072]

[0073] Table 1. Example statistical parameters for one or more traffic flows per classification

[0074] refer to Figure 6 Depicted is a process flow 600 illustrating an example implementation according to an example implementation of the present disclosure in which a traffic shaping engine 522 and a traffic fusion engine 524 may collaborate to determine a statistical parameter 506 of a traffic flow 508. Figure 6 As shown, the traffic shaping engine 522 can be configured to identify or otherwise determine each of the plurality of traffic flows 508 to be used or supported by the app execution engine 520 when providing the app to the end user of the wireless communication device 502. Figure 6 In the example shown, the traffic shaping engine 522 can identify four traffic flows 508(1)-508(4) that are to be used in association with the supporting app. These traffic flows 508(1)-508(4) can be collectively referred to as “original” traffic flows 508.

[0075] The traffic shaping engine 522 may be configured to identify, determine, select, classify, or otherwise group each of the plurality of traffic flows 508 into a classification 602. In some embodiments, the traffic shaping engine 522 may be configured to group the plurality of traffic flows 508 into a classification 602 based on or in accordance with the traffic to be sent on the traffic flow 508 and the traffic characteristics or transmission conditions of the app executed or provided by the app execution engine 520. The traffic shaping engine 522 may be configured to group the traffic flows 508 based on the following items: traffic type, data rate of the traffic, data burstiness, data periodicity, maximum allowable delay, maximum packet loss rate, minimum power, and maximum jitter, etc. Figure 6 In the example shown, the traffic shaping engine 522 can be configured to group the first traffic flow 508(1) and the third traffic flow 508(3) into one classification (CL) 602(1) (e.g., a power optimization classification), group the second traffic flow 508(2) into another classification 602(2) (e.g., a delay sensitive classification), and group the fourth traffic flow 508(4) into yet another classification 602(3) (e.g., a reliability sensitive classification). In some embodiments, the traffic shaping engine 522 can be configured to assign various shaping values ​​to the traffic flows 508 based on the corresponding classifications. For example, the traffic shaping engine 522 can be configured to group similar traffic types together based on their similarity and correlation, and can shape traffic by reshaping two or more traffic flows 508 into a single traffic flow (e.g., forming one traffic flow 508 based on the first traffic flow 508(1) and the third traffic flow 508(3)).

[0076] The traffic fusion engine 524 may be configured to receive the identified traffic flows 508 and corresponding classifications 602 from the traffic shaping engine 522. The traffic fusion engine 524 may be configured to define, select, configure, identify, or otherwise determine one or more statistical parameters 506 for each of the plurality of traffic flows 508. In some embodiments, the traffic fusion engine 524 may be configured to determine the statistical parameters 506 based on a particular classification to which the traffic flows 508 are assigned by the traffic shaping engine 522. For example, the traffic fusion engine 524 may be configured to determine the statistical parameters 506 using a lookup table in a data structure or database (e.g., similar to Table 1) based on the classification to which the traffic flows 508 are assigned. In this regard, the traffic fusion engine 524 may be configured to determine the statistical parameters 506 for the traffic flows 508 based on the classification.

[0077] Return to reference Figure 5, the wireless communication device 502 may include a signal generator 526. The signal generator 526 may be designed or configured to generate, configure, establish, or otherwise provide one or more messages, one or more communications, or one or more signals that may indicate, identify, or otherwise provide statistical parameters 506 of a traffic flow 508. In some embodiments, the signal generator 526 may be configured to provide a signal for each traffic flow in the plurality of traffic flows 508, the signal identifying the statistical parameters 506 of the corresponding traffic flow 508. In some embodiments, the signal generator 526 may be configured to provide a signal for each class / classification of traffic flow 508, wherein the signal indicates the statistical parameters 506 corresponding to the traffic flow 508 assigned to the corresponding classification. In some embodiments, the signal generator 526 may be configured to provide a signal for a wireless communication link or channel, wherein the signal identifies the statistical parameters 506 of each traffic flow / traffic flow classification in the plurality of traffic flows 508.

[0078] In some embodiments, the signal generator 526 may be configured to generate one or more signals as UE assistance information (UAI) signaling 510. Figure 5 As shown, UAI signaling 510 may include, for example, an identifier associated with one or more specific flows 508 and corresponding statistical parameters (labeled as "SP") 506. UAI signaling 510 may include: statistical parameters 506 of service flows 508, and other information that may be included in UAI signaling 510 (such as (but not limited to) device capabilities, measurement result reports, location information, power / battery status information, usage patterns, etc.). In some embodiments, statistical parameters 506 may be included in a configuration request of UAI signaling 510.

[0079] The wireless communication device 502 may be configured to transmit, convey, send, or otherwise provide one or more signals (e.g., UAI signaling 510) to the wireless communication node 504 via the respective transceivers 512, 514. The wireless communication node 504 may include a signal processing engine 528 and a resource allocation engine 530. The signal processing engine 528 may be designed or configured to parse, inspect, analyze, or otherwise identify various information included in the signaling, such as statistical parameters 506 of the identified traffic flow 508. The resource allocation engine 530 may be designed or configured to configure, select, define, or otherwise allocate network resources for the wireless communication link based on the statistical parameters 506. The signal processing engine 528 may be configured to identify the statistical parameters 506 of the traffic flows 508 received from the plurality of UEs 502, and the resource allocation engine 530 may allocate resources to different communication links related to the respective UEs 502. In various embodiments, the resource allocation engine 530 can be configured to allocate resources by increasing the bandwidth of power-optimized service flows 508 (e.g., to increase power availability for signaling via these corresponding service flows), by increasing the periodicity of latency-optimized service flows 508 (e.g., to increase the frequency with which data / information / packets can be sent to the wireless communication node 504 for transmission to an endpoint), etc.

[0080] refer to Figure 7 Depicted is a flowchart illustrating an example method 700 of traffic shaping according to an example implementation of the present disclosure. The method 700 may be referred to above. Figures 1 to 6 The present invention is performed by the devices, components, elements and hardware described in the present invention, such as wireless communication devices (or UEs) 502 and / or wireless communication nodes (or base stations) 504. As a brief overview, in step 705, UE 502 can identify applications. In step 710, UE 502 can determine traffic flows. In step 715, UE 502 can determine statistical parameters of traffic flows, which step 715 can include step 720, in which UE 502 identifies traffic flow classifications; and step 725, in which UE 502 determines statistical parameters for each classification. In step 730, UE 502 can send one or more messages to base station 504. In step 735, base station 504 can receive the one or more messages from UE 502. In step 740, base station 504 can allocate resources.

[0081] In step 705, UE 502 may identify an application. In some embodiments, UE 502 may identify an application being executed, run by UE 502, an application provided by UE 502 or otherwise provided to a terminal user of UE 502. UE 502 may identify the application in response to the deployment of the application. In step 710, UE 502 may determine a service flow. In some embodiments, UE 502 may determine a service flow to be used by the application identified in step 705. In some embodiments, UE 502 may determine a service flow to be used by the application to exchange data related to the application with an endpoint (e.g., another UE 502, an application server, etc.). UE 502 may determine a service flow to carry the application service of the application. In other words, UE 502 may determine a service flow corresponding to an application supported by UE 502 (e.g., an application determined in step 705). Service flows may include, for example, audio service flows, video service flows, gesture service flows, control service flows, model service flows, etc. UE 502 may determine service flows based on applications, based on the type of applications, etc. For example, UE 502 may determine a traffic flow based on requested resources or traffic flows as part of a negotiation with base station 504. As another example, UE 502 may determine a traffic flow based on an application signature associated with an application. As yet another example, UE 502 may determine a traffic flow based on a requested service or capability used by an application.

[0082] In step 715, UE 502 may determine statistical parameters for the traffic flow. In some embodiments, UE 502 may determine a corresponding set of statistical parameters for communicating with base station 504 for the corresponding traffic flow determined in step 710. The statistical parameters may be or include periodicity, jitter range, preferred connection mode discontinuous reception periodicity, preferred uplink configuration grant offset, forward error correction parameters, and / or preferred packet data convergence protocol (PDCP) repetition configuration parameters, several non-limiting attributes are listed here. In some embodiments, UE 502 determines the statistical parameters according to the type of application supported by UE 502. For example, UE 502 may determine different statistical parameters for different types or one or more applications supported by UE 502. In other words, in various instances, the statistical parameters of the traffic flow of the first application supported by UE 502 may be different from the statistical parameters of the same traffic flow of different applications supported by UE 502. Therefore, this embodiment may provide optimized statistical parameters according to the specific application supported by UE 502.

[0083] In some embodiments, determining the statistical parameters (at step 715) may include the UE 502 identifying a traffic flow classification (at step 720). For example, the UE 502 may group multiple traffic flows together into one or more categories based on various traffic characteristics and / or transmission conditions to send traffic on corresponding traffic flows. Traffic characteristics may include, for example, traffic type, data rate, data burstiness, and / or data periodicity. Transmission conditions may include, for example, latency conditions, packet loss conditions, power consumption conditions, and / or jitter conditions. The UE 502 may assign each traffic flow to a corresponding classification based on various one or more combinations of traffic characteristics and / or transmission conditions. Therefore, the one or more classifications may include multiple groups of one or more traffic flows assigned to corresponding classifications. In other words, the UE 502 may identify or determine multiple groups of one or more traffic flows (e.g., which are assigned to corresponding classifications). In various embodiments, the UE 502 may perform traffic shaping on the classified traffic flows. Such traffic shaping may include assigning priority, rate limiting, queue management, and other settings or configurations to the classification of the traffic flow.

[0084] In some embodiments, determining the statistical parameters (at step 715) may include UE 502 determining the statistical parameters for each category (at step 725). In some embodiments, UE 502 may determine different statistical parameters for each grouping or classification of multiple service flows. In other words, UE 502 may allocate / configure / determine a first set of statistical parameters for a first grouping or classification service flow, and may determine a second set of statistical parameters for a second grouping or classification service flow (e.g., where the first set of statistical parameters is different from the second set of statistical parameters). In some embodiments, UE 502 may determine different types of statistical parameters for service flows of different groups / classifications. For example, UE 502 may determine a first set of statistical parameters for a first grouping / classification / group service flow, a second set of statistical parameters for a second grouping / classification / group service flow, and a third set of statistical parameters for a third grouping / classification / group service flow. For example, in the case where the first group of service flows corresponds to a power optimization classification, the first set of statistical parameters may be or include periodicity, jitter range, and / or preferred connection mode discontinuous reception periodicity. As another example, in the case where the second group of service flows corresponds to the delay optimization classification, the second group of statistical parameters may be or include periodicity, jitter range and / or preferred uplink configuration authorization offset. As yet another example, in the case where the third group of service flows corresponds to the reliability optimization classification, the third group of statistical parameters may be or include forward error correction parameters and / or preferred packet data convergence protocol (PDCP) repetition configuration parameters.

[0085] In step 730, UE 502 may send one or more messages to base station 504. In some embodiments, UE 502 may send one or more messages indicating statistical parameters of multiple traffic flows to base station 504. The UE may send the one or more messages in UE Assistance Information (UAI) signaling. In some embodiments, UE 502 may send the one or more messages in UAI signaling before communicating on a wireless communication channel / link. UE 502 may send the one or more messages as part of negotiating a wireless communication channel / link. In some embodiments, UE 502 may send the one or more messages in response to deploying an app (e.g., after steps 705 to 725). In some embodiments, UE 502 may send the one or more messages after a wireless communication channel / link has been established / while communication is ongoing (e.g., as an update to previously provided UAI signaling).

[0086] In step 735, the base station 504 may receive the one or more messages from the UE 502. In some embodiments, the base station 504 may receive the one or more messages included in the UAI signaling from the UE 502. The base station 504 may receive the one or more messages as part of the session negotiation and signaling, as part of the session renegotiation, etc. In step 740, the base station 504 may allocate resources. In some embodiments, the base station 504 may allocate resources for the wireless communication channel / link based on the UAI signaling. For example, the base station 504 may allocate resources (e.g., bandwidth, periodicity, error correction, etc.) for the wireless communication channel / link based on the statistical parameters identified or included in the UAI signaling. In some embodiments, the base station may allocate resources to each service flow based on the statistical parameters corresponding to the service flow (e.g., as reflected in the UAI signaling).

[0087] Now that some illustrative embodiments have been described, it is apparent that the foregoing, which has been presented by way of example, is illustrative and not restrictive. Specifically, although many of the examples presented herein relate to specific combinations of method actions or system elements, these actions and these elements may be combined in other ways to achieve the same purpose. The actions, elements, and features discussed in conjunction with one embodiment are not intended to be excluded from similar roles in other embodiments.

[0088] The hardware and multiple data processing components for implementing the various processes, operations, illustrative logic, logic blocks, modules and circuits described in conjunction with the multiple embodiments disclosed herein can be implemented or executed using the following components designed to perform the functions described herein: a general-purpose single-chip processor or a general-purpose multi-chip processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic, a discrete hardware component, or any combination thereof. A general-purpose processor may be a microprocessor, or may be any conventional processor, controller, microcontroller or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a combination of multiple microprocessors, a combination of one or more microprocessors and a DSP core, or any other such configuration. In some embodiments, specific processes and methods may be performed by circuits dedicated to a given function. A memory (e.g., a memory, a memory unit, a storage device, etc.) may include one or more devices (e.g., RAM, ROM, flash memory, hard disk storage, etc.) for storing data and / or computer code for completing or facilitating the various processes, various layers and various modules described in this disclosure. The memory may be or may include volatile memory or non-volatile memory, and may include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described in the present disclosure. According to an exemplary embodiment, the memory is communicatively connected to the processor via the processing circuit and includes computer code for executing (e.g., by the processing circuit and / or the processor) one or more processes described herein.

[0089] The present disclosure contemplates methods, systems, and program products on any machine-readable medium for completing various operations. The various embodiments of the present disclosure may be implemented using existing computer processors, or by a dedicated computer processor for a suitable system combined for this or other purposes, or by a hard-wired system. The various embodiments within the scope of the present disclosure include program products, which include machine-readable media for carrying or storing machine-executable instructions or data structures thereon. Such machine-readable media may be any available medium that can be accessed by a general-purpose computer or a special-purpose computer or other machine with a processor. As an example, such machine-readable media may include RAM, ROM, EPROM, EEPROM, or other optical disk storage, disk storage, or other magnetic storage device, or any other medium that can be used to carry or store program codes in the form of desired machine-executable instructions or data structures, and can be accessed by a general-purpose computer or a special-purpose computer or other machine with a processor. The above combinations are also included in the scope of machine-readable media. Machine-executable instructions include, for example, instructions and data that cause a general-purpose computer, a special-purpose computer, or a special-purpose processing machine to perform a specific function or group of functions.

[0090] The words and terms used herein are for descriptive purposes and should not be considered limiting. The use of "comprising," "including," "having," "containing," "involving," "characterized by," "characterized by," and variations thereof herein is meant to encompass the items listed thereafter, their equivalents and additional items, and to include alternative embodiments consisting exclusively of the items listed thereafter. In one embodiment, the systems and methods described herein include one, each combination of more than one of the described elements, acts, or components, or all of them.

[0091] Any reference to an embodiment or element or action of the system and method mentioned in the singular herein may also encompass an embodiment including a plurality of these elements, and any plural reference to any embodiment or element or action herein may also encompass an embodiment including only a single element. References in the singular or plural form are not intended to limit the currently disclosed systems or methods, their components, actions or elements to a single or multiple configurations. References to any action or element based on any information, action or element may include an embodiment in which the action or element is based at least in part on any information, action or element.

[0092] Any embodiment disclosed herein may be combined with any other embodiment or example, and references to "an embodiment," "some embodiments," "an embodiment," etc. are not necessarily mutually exclusive, but are intended to indicate that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment or example. These terms as used herein do not necessarily all refer to the same embodiment. Any embodiment may be combined, inclusively or exclusively, with any other embodiment in any manner consistent with the various aspects and embodiments disclosed herein.

[0093] Where technical features in the drawings, detailed description or any claims are followed by reference numerals, these reference numerals have been included to increase the intelligibility of the drawings, detailed description and claims. Therefore, these reference numerals or their absence do not have any limiting effect on the scope of any claim element.

[0094] Without departing from the features of the present invention, the systems and methods described herein may be implemented in other specific forms. Unless otherwise expressly noted, references to "approximately," "about," "substantially," or other degree terms include changes of plus or minus 10% (+ / -10%) from a given measurement, unit, or range. The coupled elements may be electrically coupled, mechanically coupled, or physically coupled to each other directly or through intermediate elements. Therefore, the scope of the systems and methods described herein is indicated by the appended claims rather than the preceding description, and changes within the meaning and scope of the equivalents of the claims are included therein.

[0095] The term "coupled" and variations thereof include two members being directly or indirectly connected to one another. Such connection may be constant (e.g., permanent or fixed) or movable (e.g., removable or releasable). Such connection may be achieved by the two members being directly coupled to one another or coupled to one another, by the two members being coupled to one another using a separate intermediate member, and by any additional intermediate member being coupled to one another, or by the two members being coupled to one another using an intermediate member that is integrally formed as a single, unitary body with one of the two members. If "coupled" or variations thereof are modified by additional terms (e.g., directly coupled), the general definition of "coupled" provided above is modified by the plain language meaning of the additional terms (e.g., "directly coupled" means that the two members are connected without any separate intermediate member), resulting in a narrower definition than the general definition of "coupled" provided above. Such coupling may be mechanical, electrical, or fluidic.

[0096] References to "or" may be interpreted as inclusive, such that any term described using "or" may mean single, more than one, and any one of all described terms. References to "at least one of 'A' and 'B'" may include only 'A', only 'B', and both 'A' and 'B'. Such references used in conjunction with "including" or other public terms may include additional items.

[0097] Without departing substantially from the teachings and advantages of the subject matter disclosed herein, modifications may be made to the elements and actions described, such as changes in the size, dimensions, structure, shape and proportion of the various elements, parameter values, mounting arrangement structures, use of materials, colors, orientations. For example, an element shown as being integrally formed may be composed of multiple parts or elements, the positions of these elements may be reversed or otherwise changed, and the nature or number or position of discrete elements may be altered or varied. Other substitutions, modifications, changes and omissions may also be made to the design, operating conditions and arrangements of the disclosed elements and operations without departing from the scope of the present disclosure.

[0098] References herein to the positions of elements (e.g., "top," "bottom," "above," "below") are only used to describe the orientation of the various elements in the drawings. According to other example embodiments, the orientation of the various elements may be different, and such variations are intended to be encompassed by the present disclosure.

Claims

1. A method comprising: Determining, by a user equipment UE, a corresponding set of statistical parameters for communicating with a base station for a plurality of service flows, the plurality of service flows corresponding to applications supported by the UE; as well as The UE sends one or more messages indicating the statistical parameters of the multiple service flows in UE auxiliary information UAI signaling to the base station.

2. The method according to claim 1, wherein: The plurality of service flows include service flows that are grouped together into a plurality of groups of service flows according to at least one of service characteristics or transmission conditions for transmitting services on the service flows included in one group.

3. The method according to claim 2, wherein: The service characteristics include at least one of the following: service type, data rate, data burstiness or data periodicity; and wherein the transmission conditions include at least one of the following: delay condition, packet loss condition, power consumption condition or jitter condition.

4. The method according to claim 1, wherein: The UE determines the statistical parameter according to a type of the application supported by the UE.

5. The method according to claim 4, wherein: Statistical parameters of multiple service flows of a first application supported by the UE are different from statistical parameters of multiple service flows of a second application supported by the UE.

6. The method according to claim 1, wherein: The plurality of service flows include one or more service flows of a first group and one or more service flows of a second group.

7. The method according to claim 6, wherein: The statistical parameters of the first group are different from the statistical parameters of the second group.

8. The method according to claim 1, wherein: A first set of statistical parameters is determined for a first set of traffic flows in the plurality of traffic flows, and wherein a second set of statistical parameters is determined for a second set of traffic flows in the plurality of traffic flows.

9. The method according to claim 1, wherein: The statistical parameters include at least one of the following: periodicity, jitter range, preferred connected mode discontinuous reception periodicity, preferred uplink configuration grant offset, one or more forward error correction parameters, or one or more preferred packet data convergence protocol PDCP repetition configuration parameters.

10. The method according to claim 1, wherein: The first group of statistical parameters of the first group of service flows in the plurality of service flows comprises a corresponding periodicity, a corresponding jitter range and a preferred connection mode discontinuous reception periodicity, A second set of statistical parameters of a second set of service flows in the plurality of service flows comprises a corresponding periodicity, a corresponding jitter range, and a preferred uplink configuration authorization offset, and The third group of statistical parameters of the third group of service flows among the multiple service flows includes one or more forward error correction parameters and one or more preferred packet data convergence protocol PDCP repetition configuration parameters.

11. A wireless communication device, comprising: Wireless transceiver; as well as One or more processors configured to: determining a respective set of statistical parameters for a plurality of traffic flows for communicating with a base station, the plurality of traffic flows corresponding to applications supported by the wireless communication device; as well as One or more messages indicating the statistical parameters of the multiple service flows in User Equipment (UE) Assistant Information (UAI) signaling are sent to the base station via the wireless transceiver.

12. The wireless communication device according to claim 11, wherein: The plurality of service flows include service flows that are grouped together into a plurality of groups of service flows according to at least one of service characteristics or transmission conditions for transmitting services on the service flows included in one group.

13. The wireless communication device according to claim 12, wherein: The service characteristics include at least one of the following: service type, data rate, data burstiness or data periodicity; and wherein the transmission conditions include at least one of the following: delay condition, packet loss condition, power consumption condition or jitter condition.

14. The wireless communication device according to claim 1, wherein: The one or more processors determine the statistical parameter based on a type of the application supported by the wireless communication device.

15. The wireless communication device according to claim 14, wherein: Statistical parameters of a plurality of service flows of a first application supported by the wireless communication device are different from statistical parameters of a plurality of service flows of a second application supported by the wireless communication device.

16. The wireless communication device according to claim 11, wherein: The plurality of service flows include one or more service flows of a first group and one or more service flows of a second group.

17. The wireless communication device according to claim 16, wherein: The statistical parameters of the first group are different from the statistical parameters of the second group.

18. The wireless communication device according to claim 11, wherein: A first set of statistical parameters is determined for a first set of traffic flows in the plurality of traffic flows, and wherein a second set of statistical parameters is determined for a second set of traffic flows in the plurality of traffic flows.

19. The wireless communication device according to claim 11, wherein: The statistical parameters include at least one of the following: periodicity, jitter range, preferred connected mode discontinuous reception periodicity, preferred uplink configuration grant offset, one or more forward error correction parameters, or one or more preferred packet data convergence protocol PDCP repetition configuration parameters.

20. A base station, comprising: Wireless transceiver; as well as One or more processors configured to: receiving, via the wireless transceiver, one or more messages indicating statistical parameters of a plurality of service flows in UE assistance information UAI signaling from a user equipment UE, The statistical parameters are used for communication between the UE and the base station, and the multiple service flows correspond to applications supported by the UE.

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