Communicate known payloads to support the machine learning process

Abstract

Various aspects of the present disclosure generally relate to wireless communications. In some aspects, a user equipment may receive from a base station an indication of resource allocation for data communications having a known payload, the known payload including data associated with a machine learning process, and communicate with the base station based at least in part on the resource allocation. Numerous other aspects are provided.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This patent application claims priority to U.S. Provisional Patent Application No. 62 / 979,307, filed on February 20, 2020, entitled “COMMUNICATION OF A KNOWNPAYLOAD TO SUPPORT A MACHINE LEARNING PROCESS,” and U.S. Non-Provisional Patent Application No. 17 / 166,761, filed on February 3, 2021, entitled “COMMUNICATION OF A KNOWN PAYLOAD TO SUPPORT A MACHINE LEARNING PROCESS,” which are hereby expressly incorporated herein by reference.

[0003] public domain

[0004] Aspects of the present disclosure relate generally to wireless communications, and to techniques and apparatus for communicating known payloads to support machine learning processes.

[0005] background

[0006] Wireless communication systems are widely deployed to provide a variety of telecommunication services, such as telephony, video, data, messaging, and broadcasts. Typical wireless communication systems may employ multiple access technologies capable of supporting communication with multiple users by sharing available system resources (e.g., bandwidth, transmit power, etc.). Examples of such multiple access technologies include code division multiple access (CDMA) systems, time division multiple access (TDMA) systems, frequency division multiple access (FDMA) systems, orthogonal frequency division multiple access (OFDMA) systems, single-carrier frequency division multiple access (SC-FDMA) systems, time division synchronous code division multiple access (TD-SCDMA) systems, and long term evolution (LTE). LTE / LTE-Advanced is a set of enhancements to the Universal Mobile Telecommunications System (UMTS) mobile standard promulgated by the Third Generation Partnership Project (3GPP).

[0007] A wireless network may include several base stations (BSs) capable of supporting communications for several user equipment (UEs). UEs may communicate with a BS via downlinks and uplinks. The downlink (or forward link) refers to the communication link from the BS to the UE, while the uplink (or reverse link) refers to the communication link from the UE to the BS. As will be described in greater detail herein, a BS may be referred to as a Node B, gNB, access point (AP), radio head, transmit / receive point (TRP), new radio (NR) BS, 5G Node B, and so on.

[0008] The above multiple access technologies have been adopted in various telecommunication standards to provide a common protocol that enables different user equipment to communicate at city, country, region, and even global levels. The above multiple access technologies have been adopted in various telecommunication standards to provide a common protocol that enables different user equipment to communicate at city, country, region, and even global levels. NR is designed to better support mobile broadband Internet access by using orthogonal frequency division multiplexing (OFDM) (CP-OFDM) with a cyclic prefix (CP) on the downlink (DL), using CP-OFDM and / or SC-FDM (e.g., also known as discrete Fourier transform spread OFDM (DFT-s-OFDM)) on the uplink (UL), and supporting beamforming, multiple-input multiple-output (MIMO) antenna technology, and carrier aggregation to improve spectrum efficiency, reduce costs, improve services, utilize new spectrum, and better integrate with other open standards. As the demand for mobile broadband access continues to grow, further improvements to LTE, NR, and other radio access technologies are still useful.

[0009] Overview

[0010] In some aspects, a user equipment (UE) for wireless communication may include a memory and one or more processors operatively coupled to the memory. The memory and the one or more processors may be configured to: receive, from a base station, an indication of resource allocation for data communication having a known payload including data associated with a machine learning process; and communicate with the base station based at least in part on the resource allocation.

[0011] In some aspects, a base station for wireless communication may include a memory and one or more processors operatively coupled to the memory. The memory and the one or more processors may be configured to: transmit to a UE an indication of resource allocation for data communication having a known payload including data associated with a machine learning process; and communicate with the UE based at least in part on the resource allocation.

[0012] In some aspects, a wireless communication method performed by a UE may include: receiving an indication of a resource allocation for data communication having a known payload including data associated with a machine learning process from a base station; and communicating with the base station based at least in part on the resource allocation.

[0013] In some aspects, a wireless communication method performed by a base station may include: transmitting an indication of a resource allocation for data communication having a known payload including data associated with a machine learning process to a UE; and communicating with the UE based at least in part on the resource allocation.

[0014] In some aspects, a non-transitory computer-readable medium may store one or more instructions for wireless communication. The one or more instructions, when executed by one or more processors of a UE, may cause the one or more processors to: receive an indication of a resource allocation for data communication having a known payload, the known payload including data associated with a machine learning process, from a base station; and communicate with the base station based at least in part on the resource allocation.

[0015] In some aspects, a non-transitory computer-readable medium may store one or more instructions for wireless communication. The one or more instructions, when executed by one or more processors of a base station, may cause the one or more processors to: transmit to a UE an indication of a resource allocation for data communication having a known payload, the known payload including data associated with a machine learning process; and communicate with the UE based at least in part on the resource allocation.

[0016] In some aspects, an apparatus for wireless communication may include: means for receiving, from a base station, an indication of a resource allocation for data communication having a known payload comprising data associated with a machine learning process; and means for communicating with the base station based at least in part on the resource allocation.

[0017] In some aspects, an apparatus for wireless communication may include: means for transmitting to a UE an indication of a resource allocation for data communication having a known payload, the known payload including data associated with a machine learning process; and means for communicating with the UE based at least in part on the resource allocation.

[0018] Aspects generally include methods, apparatus, systems, computer program products, non-transitory computer-readable media, user equipment, base stations, wireless communication devices, and / or processing systems as substantially described herein with reference to and as illustrated in the figures, description, and appendices.

[0019] The foregoing has broadly outlined the features and technical advantages of examples according to the present disclosure in an effort to make the following detailed description better understood. Additional features and advantages will be described hereinafter. The concepts and specific examples disclosed can be readily used as a basis for modifying or designing other structures for implementing the same purposes as the present disclosure. Such equivalent constructions do not depart from the scope of the appended claims. The characteristics of the concepts disclosed herein, both in terms of their organization and method of operation, as well as the associated advantages, will be better understood by considering the following description in conjunction with the accompanying drawings. Each of the figures is provided for illustration and description purposes and is not intended to define limitations on the claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to understand in detail the features of the present disclosure set forth above, a more particular description of the content briefly summarized above may be obtained with reference to various aspects, some of which are illustrated in the accompanying drawings. It should be noted, however, that the accompanying drawings illustrate only certain typical aspects of the present disclosure and are not to be considered limiting of its scope, as the description may admit to other equally effective aspects. The same reference numerals in different drawings may identify the same or similar elements.

[0022] Figure 1 is a diagram illustrating an example of a wireless network in accordance with various aspects of the present disclosure.

[0023] Figure 2 is a diagram illustrating an example of a base station and a user equipment (UE) in communication in a wireless network according to various aspects of the present disclosure.

[0024] Figure 3 is a diagram illustrating an example of communicating a known payload to support a machine learning process in accordance with various aspects of the present disclosure.

[0025] Figure 4 is a diagram illustrating an example associated with communicating a known payload to support a machine learning process according to the present disclosure.

[0026] Figure 5 is a diagram illustrating example processes performed, for example, by a UE, according to various aspects of the present disclosure.

[0027] Figure 6 is a diagram illustrating example processes performed, for example, by a base station, according to various aspects of the present disclosure.

[0028] Detailed description

[0029] The various aspects of the present disclosure are described more fully below with reference to the accompanying drawings. However, the present disclosure can be implemented in many different forms and should not be interpreted as being limited to any specific structure or function given throughout the present disclosure. On the contrary, these aspects are provided to make the present disclosure thorough and complete, and they will fully convey the scope of the present disclosure to those skilled in the art. Based on the teachings of this article, those skilled in the art will appreciate that the scope of the present disclosure is intended to cover any aspect of the present disclosure disclosed herein, whether it is implemented independently of any other aspect of the present disclosure or implemented in combination. For example, any number of aspects set forth herein can be used to implement a device or practice method. In addition, the scope of the present disclosure is intended to cover such devices or methods that are practiced using a supplement to the various aspects of the present disclosure set forth herein or other other structures, functionality, or structure and functionality. It should be understood that any aspect of the present disclosure disclosed herein can be implemented by one or more elements of the claims.

[0030] Several aspects of telecommunications systems will now be presented with reference to various devices and techniques. These devices and techniques are described in the following detailed description and illustrated in the accompanying drawings by various blocks, modules, components, circuits, steps, processes, algorithms, etc. (collectively, "elements"). These elements may be implemented using hardware, software, or a combination thereof. Whether such elements are implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system.

[0031] It should be noted that although various aspects may be described herein using terminology generally associated with 5G or NR radio access technologies (RATs), various aspects of the present disclosure may be applied to other RATs, such as 3G RATs, 4G RATs, and / or RATs beyond 5G (e.g., 6G).

[0032] Figure 1 is a diagram illustrating an example of a wireless network 100 according to various aspects of the present disclosure. The wireless network 100 may be a 5G (NR) network and / or an LTE network, etc. or may include elements thereof. The wireless network 100 may include several base stations 110 (shown as BS 110a, BS 110b, BS 110c, and BS 110d) and other network entities. A base station (BS) is an entity that communicates with user equipment (UE) and may also be referred to as an NR BS, B node, gNB, 5G B node (NB), access point, transmit reception point (TRP), etc. Each BS may provide communication coverage for a specific geographic area. In 3GPP, the term "cell" may refer to the coverage area of ​​a BS and / or a BS subsystem serving that coverage area, depending on the context in which the term is used.

[0033] A BS may provide communication coverage for a macro cell, a pico cell, a femto cell, and / or another type of cell. A macro cell may cover a relatively large geographic area (e.g., several kilometers in radius) and may allow unrestricted access by UEs with service subscriptions. A pico cell may cover a relatively small geographic area and may allow unrestricted access by UEs with service subscriptions. A femto cell may cover a relatively small geographic area (e.g., a residence) and may allow restricted access by UEs associated with the femto cell (e.g., UEs in a closed subscriber group (CSG)). A BS for a macro cell may be referred to as a macro BS. A BS for a pico cell may be referred to as a pico BS. A BS for a femto cell may be referred to as a femto BS or a home BS. In Figure 1In the example shown in FIG, BS 110a may be a macro BS for macro cell 102a, BS 110b may be a pico BS for pico cell 102b, and BS 110c may be a femto BS for femto cell 102c. A BS may support one or more (e.g., three) cells. The terms "eNB," "base station," "NR BS," "gNB," "TRP," "AP," "Node B," "5G NB," and "cell" may be used interchangeably herein.

[0034] In some aspects, the cells may not necessarily be stationary, and the geographic area of ​​the cells may move depending on the location of the mobile BS. In some aspects, the BSs may be interconnected to each other and / or to one or more other BSs or network nodes (not shown) in the wireless network 100 via various types of backhaul interfaces, such as direct physical connections or virtual networks, using any suitable transport network.

[0035] The wireless network 100 may also include a relay station. A relay station is an entity that can receive transmissions of data from an upstream station (e.g., a BS or a UE) and send transmissions of the data to a downstream station (e.g., a UE or a BS). A relay station may also be a UE that can relay transmissions for other UEs. Figure 1 In the example shown in , relay BS 110d may communicate with macro BS 110a and UE 120d to facilitate communication between BS 110a and UE 120d. A relay BS may also be referred to as a relay station, relay base station, relay, etc.

[0036] The wireless network 100 may be a heterogeneous network including different types of BSs, such as macro BSs, pico BSs, femto BSs, relay BSs, etc. These different types of BSs may have different transmit power levels, different coverage areas, and different impacts on interference in the wireless network 100. For example, a macro BS may have a high transmit power level (e.g., 5 to 40 watts), while a pico BS, a femto BS, and a relay BS may have a lower transmit power level (e.g., 0.1 to 2 watts).

[0037] The network controller 130 may be coupled to a set of BSs and may provide coordination and control of these BSs. The network controller 130 may communicate with each BS via a backhaul. These BSs may also communicate with each other directly or indirectly via a wireless or wired backhaul.

[0038] UEs 120 (e.g., 120a, 120b, 120c) may be dispersed throughout the wireless network 100, and each UE may be stationary or mobile. A UE may also be referred to as an access terminal, terminal, mobile station, subscriber unit, station, etc. A UE may be a cellular phone (e.g., a smartphone), a personal digital assistant (PDA), a wireless modem, a wireless communication device, a handheld device, a laptop computer, a cordless phone, a wireless local loop (WLL) station, a tablet, a camera, a gaming device, a netbook, a smartbook, an ultrabook, a medical device or equipment, a biometric sensor / device, a wearable device (e.g., a smart watch, smart clothing, smart glasses, a smart wristband, smart jewelry (e.g., a smart ring, a smart bracelet)), an entertainment device (e.g., a music or video device, or a satellite radio), a vehicle component or sensor, a smart meter / sensor, industrial manufacturing equipment, a global positioning system device, or any other suitable device configured to communicate via a wireless or wired medium.

[0039] Some UEs may be considered machine type communication (MTC) UEs, or evolved or enhanced machine type communication (eMTC) UEs. MTC and eMTC UEs include, for example, robots, drones, remote devices, sensors, meters, monitors, and / or location tags that can communicate with a base station, another device (e.g., a remote device), or some other entity. A wireless node may provide connectivity to or to a network (e.g., a wide area network (such as the Internet) or a cellular network), for example, via a wired or wireless communication link. Some UEs may be considered Internet of Things (IoT) devices and / or may be implemented as NB-IoT (Narrowband Internet of Things) devices. Some UEs may be considered customer premises equipment (CPE). UE 120 may be included within a housing that houses components of UE 120, such as a processor component and / or a memory component. In some aspects, the processor component and the memory component may be coupled together. For example, the processor component (e.g., one or more processors) and the memory component (e.g., memory) may be operatively coupled, communicatively coupled, electronically coupled, and / or electrically coupled.

[0040] In general, any number of wireless networks may be deployed in a given geographic area. Each wireless network may support a specific RAT and may operate on one or more frequencies. A RAT may also be referred to as a radio technology, air interface, etc. A frequency may also be referred to as a carrier, frequency channel, etc. Each frequency may support a single RAT in a given geographic area to avoid interference between wireless networks of different RATs. In some cases, NR or 5G RAT networks may be deployed.

[0041] In some aspects, two or more UEs 120 (e.g., shown as UE 120a and UE 120e) may communicate directly (e.g., without using base station 110 as an intermediary) using one or more sidelink channels. For example, UE 120 may communicate using peer-to-peer (P2P) communication, device-to-device (D2D) communication, vehicle-to-everything (V2X) protocols (e.g., which may include vehicle-to-vehicle (V2V) protocols or vehicle-to-infrastructure (V2I) protocols), and / or mesh networks. In this scenario, UE 120 may perform scheduling operations, resource selection operations, and / or other operations described elsewhere herein as being performed by base station 110.

[0042] The devices of the wireless network 100 can communicate using an electromagnetic spectrum, which can be subdivided into various categories, frequency bands, channels, etc. based on frequency or wavelength. For example, the devices of the wireless network 100 can communicate using an operating band having a first frequency range (FR1) and / or can communicate using an operating band having a second frequency range (FR2), the first frequency range (FR1) can span from 410 MHz to 7.125 GHz, and the second frequency range (FR2) can span from 24.25 GHz to 52.6 GHz. Frequencies between FR1 and FR2 are sometimes referred to as mid-band frequencies. Although a portion of FR1 is greater than 6 GHz, FR1 is often referred to as a "sub-6 GHz" band. Similarly, although different from the extremely high frequency (EHF) band (30 GHz–300 GHz) identified as a "millimeter wave" band by the International Telecommunication Union (ITU), FR2 is often referred to as a "millimeter wave" band. Therefore, unless otherwise specifically stated, it should be understood that the terms "sub-6 GHz," etc., if used herein, may broadly refer to frequencies less than 6 GHz, frequencies within FR1, and / or mid-band frequencies (e.g., greater than 7.125 GHz). Similarly, unless otherwise specifically stated, it should be understood that the terms "millimeter wave," etc., if used herein, may broadly refer to frequencies within the EHF band, frequencies within FR2, and / or mid-band frequencies (e.g., less than 24.25 GHz). It is contemplated that the frequencies included in FR1 and FR2 may be modified, and that the techniques described herein are applicable to those modified frequency ranges.

[0043] As indicated above, Figure 1 are provided as examples. Other examples may differ from those described in Figure 1 Examples described.

[0044] Figure 2is a diagram illustrating an example 200 of a base station 110 and a UE 120 in communication in a wireless network 100 in accordance with various aspects of the present disclosure. The base station 110 may be equipped with T antennas 234a through 234t, and the UE 120 may be equipped with R antennas 252a through 252r, where in general T≥1 and R≥1.

[0045] At base station 110, transmit processor 220 may receive data for one or more UEs from data source 212, select one or more modulation and coding schemes (MCS) for each UE based at least in part on a channel quality indicator (CQI) received from the UE, process (e.g., encode and modulate) the data for each UE based at least in part on the MCS selected for the UE, and provide data symbols for all UEs. Transmit processor 220 may also process system information (e.g., for semi-static resource partitioning information (SRPI)) and control information (e.g., CQI requests, grants, and / or upper layer signaling) and provide overhead symbols and control symbols. Transmit processor 220 may also generate reference symbols for reference signals (e.g., cell-specific reference signal (CRS) or demodulation reference signal (DMRS)) and synchronization signals (e.g., primary synchronization signal (PSS) or secondary synchronization signal (SSS)). A transmit (TX) multiple-input, multiple-output (MIMO) processor 230 may perform spatial processing (e.g., precoding) on ​​data symbols, control symbols, overhead symbols, and / or reference symbols, as applicable, and may provide T output symbol streams to T modulators (MODs) 232a through 232t. Each modulator 232 may process a respective output symbol stream (e.g., for OFDM) to obtain an output sample stream. Each modulator 232 may further process (e.g., convert to analog, amplify, filter, and frequency upconvert) the output sample stream to obtain a downlink signal. The T downlink signals from modulators 232a through 232t may be transmitted via T antennas 234a through 234t, respectively.

[0046] At UE 120, antennas 252a through 252r may receive downlink signals from base station 110 and / or other base stations and may provide received signals to demodulators (DEMODs) 254a through 254r, respectively. Each demodulator 254 may condition (e.g., filter, amplify, downconvert, and digitize) the received signal to obtain input samples. Each demodulator 254 may further process the input samples (e.g., for OFDM) to obtain received symbols. A MIMO detector 256 may obtain received symbols from all R demodulators 254a through 254r, perform MIMO detection on the received symbols where applicable, and provide detected symbols. A receive processor 258 may process (e.g., demodulate and decode) the detected symbols, provide decoded data for UE 120 to a data sink 260, and provide decoded control information and system information to a controller / processor 280. The term "controller / processor" may refer to one or more controllers, one or more processors, or a combination thereof. The channel processor may determine a reference signal received power (RSRP) parameter, a received signal strength indicator (RSSI) parameter, a reference signal received quality (RSRQ) parameter, and / or a channel quality indicator (CQI) parameter, etc. In some aspects, one or more components of the UE 120 may be included in the housing 284.

[0047] The network controller 130 may include a communication unit 294, a controller / processor 290, and a memory 292. The network controller 130 may include, for example, one or more devices in a core network. The network controller 130 may communicate with the base station 110 via the communication unit 294.

[0048] The antennas (e.g., antennas 234a to 234t and / or antennas 252a to 252r) may include, or may be included within, one or more antenna panels, antenna groups, sets of antenna elements, and / or antenna arrays, etc. The antenna panels, antenna groups, sets of antenna elements, and / or antenna arrays may include one or more antenna elements. The antenna panels, antenna groups, sets of antenna elements, and / or antenna arrays may include coplanar sets of antenna elements and / or non-coplanar sets of antenna elements. The antenna panels, antenna groups, sets of antenna elements, and / or antenna arrays may include antenna elements within a single housing and / or antenna elements within multiple housings. The antenna panels, antenna groups, sets of antenna elements, and / or antenna arrays may include antenna elements coupled to one or more transmit and / or receive components (such as Figure 2 One or more antenna elements of one or more components).

[0049] On the uplink, at the UE 120, a transmit processor 264 may receive and process data from a data source 262 and control information (e.g., for reports including RSRP, RSSI, RSRQ, and / or CQI) from a controller / processor 280. The transmit processor 264 may also generate reference symbols for one or more reference signals. The symbols from the transmit processor 264 may be precoded by a TX MIMO processor 266, if applicable, further processed by modulators 254a through 254r (e.g., for DFT-s-OFDM or CP-OFDM), and transmitted to the base station 110. In some aspects, the modulator and demodulator (e.g., MOD / DEMOD 254) of the UE 120 may be included in a modem of the UE 120. In some aspects, the UE 120 comprises a transceiver. The transceiver may include any combination of antenna(s) 252, modulator and / or demodulator 254, MIMO detector 256, receive processor 258, transmit processor 264, and / or TX MIMO processor 266. The transceiver may be used by a processor (e.g., controller / processor 280) and memory 282 to perform aspects of any of the methods described herein, for example, as described with reference to Figure 3-5 described.

[0050] At base station 110, uplink signals from UE 120 and other UEs may be received by antenna 234, processed by demodulator 232, detected by MIMO detector 236 where applicable, and further processed by receive processor 238 to obtain decoded data and control information sent by UE 120. Receive processor 238 may provide the decoded data to data sink 239 and the decoded control information to controller / processor 240. Base station 110 may include a communication unit 244 and communicate with network controller 130 via communication unit 244. Base station 110 may include a scheduler 246 to schedule UE 120 for downlink and / or uplink communications. In some aspects, the modulator and demodulator (e.g., MOD / DEMOD 232) of base station 110 may be included in a modem of base station 110. In some aspects, base station 110 includes a transceiver. The transceiver may include any combination of antenna(s) 234, modulator and / or demodulator 232, MIMO detector 236, receive processor 238, transmit processor 220, and / or TX MIMO processor 230. The transceiver may be used by a processor (e.g., controller / processor 240) and memory 242 to perform aspects of any of the methods described herein, for example, as described with reference to Figure 3-5 described.

[0051] The controller / processor 240 of the base station 110, the controller / processor 280 of the UE 120, and / or Figure 2 Any other component(s) of the base station 110 may perform one or more techniques associated with the delivery of known payloads for supporting machine learning processes, as described in more detail elsewhere herein. For example, the controller / processor 240 of the base station 110, the controller / processor 280 of the UE 120, and / or Figure 2 Any other component(s) may perform or direct e.g. Figure 4 The process of 400 Figure 5 500, and / or operations of other processes as described herein. Memories 242 and 282 may store data and program codes for base station 110 and UE 120, respectively. In some aspects, memory 242 and / or memory 282 may include: a non-transitory computer-readable medium storing one or more instructions (e.g., code and / or program code) for wireless communication. For example, the one or more instructions, when executed (e.g., directly or after compilation, conversion, and / or interpretation) by one or more processors of base station 110 and / or UE 120, may cause the one or more processors, UE 120, and / or base station 110 to perform or direct, for example Figure 4 The process of 500 Figure 5 In some aspects, executing instructions may include running instructions, converting instructions, compiling instructions, and / or interpreting instructions, among other things.

[0052] In some aspects, UE 120 may include: means for receiving from a base station an indication of a resource allocation for data communication having a known payload including data associated with a machine learning process; means for communicating with the base station based at least in part on the resource allocation, etc. In some aspects, such means may include in conjunction with Figure 2 One or more components of the UE 120 are depicted, such as the controller / processor 280, transmit processor 264, TX MIMO processor 266, MOD 254, antenna 252, DEMOD 254, MIMO detector 256, receive processor 258, and so forth.

[0053] In some aspects, base station 110 may include: means for transmitting to a UE an indication of a resource allocation for data communication having a known payload including data associated with a machine learning process; means for communicating with the UE based at least in part on the resource allocation, etc. In some aspects, such means may include in conjunction with Figure 2One or more components of base station 110 are depicted, such as antenna 234, DEMOD 232, MIMO detector 236, receive processor 238, controller / processor 240, transmit processor 220, TX MIMO processor 230, MOD 232, antenna 234, and so forth.

[0054] although Figure 2 The blocks in FIG. 2 are illustrated as distinct components, but the functionality described above with respect to these blocks may be implemented in a single hardware, software, or combined component or various combinations of components. For example, the functionality described with respect to the transmit processor 264, the receive processor 258, and / or the TX MIMO processor 266 may be performed by or under the control of the controller / processor 280.

[0055] As indicated above, Figure 2 are provided as examples. Other examples may differ from those described in Figure 2 Examples described.

[0056] In some wireless networks, one or more network nodes may be configured to run a machine learning (ML) process. The ML process may be used to establish, enhance, and / or otherwise support functionality to be performed by one or more nodes. A machine learning model may be trained using a set of observations. The set of observations may be obtained and / or input from historical data (such as data collected during one or more processes described herein). For example, the set of observations may include data collected from transmissions of known payloads, as described elsewhere herein. In some implementations, the machine learning system may receive the set of observations (e.g., as input) from another network device (such as a UE or a base station).

[0057] A feature set may be derived from the set of observations. The feature set may include a set of variable types. Variable types may be referred to as features. A particular observation may include a set of variable values ​​corresponding to the set of variable types. The set of variable values ​​may vary from observation to observation. In some cases, different observations may be associated with different sets of variable values ​​(sometimes referred to as feature values). In some implementations, the machine learning system may determine the variable values ​​for a particular observation based on input received from a UE and / or base station. For example, the machine learning system may identify a feature set (e.g., one or more features and / or corresponding feature values) from structured data input to the machine learning system, such as by extracting data from a specific column of a table, extracting data from a specific field of a form, extracting data from a specific field of a message, extracting data received in a structured data format, etc. In some implementations, the machine learning system may determine the features (e.g., variable types) in the feature set based on input received from a UE and / or base station, such as by extracting or generating the names of columns, extracting or generating the names of fields of a form and / or message, extracting or generating the names based on a structured data format, etc. Additionally or alternatively, the machine learning system may receive input from an operator to determine the features and / or feature values. In some implementations, the machine learning system can perform natural language processing and / or another feature identification technique to extract features (e.g., variable types) and / or feature values ​​(e.g., variable values) from text (e.g., unstructured data) input to the machine learning system, such as by identifying keywords and / or values ​​associated with those keywords from the text.

[0058] The set of observations can be associated with a target variable type. The target variable type can represent a variable with a numerical value (e.g., an integer value, a floating point value, etc.), a variable with a numerical value that falls within a range of values ​​or contains some discrete possible values, a variable that can be selected from one of multiple options (e.g., one of multiple classes, classifications, labels, etc.), a variable with a Boolean value (e.g., 0 or 1, true or false, yes or no), etc. The target variable type can be associated with a target variable value, and the target variable value can vary depending on the observation. In some cases, different observations can be associated with different target variable values.

[0059] The target variable can represent the value that the machine learning model is being trained to predict, and the feature set can represent the variables that are input to the trained machine learning model to predict the value of the target variable. The set of observations can include the target variable value so that the machine learning model can be trained to identify patterns in the feature set that lead to the target variable value. The machine learning model trained to predict the target variable value can be referred to as a supervised learning model, a prediction model, etc. When the target variable type is associated with a continuous target variable value (e.g., a numeric range, etc.), the machine learning model can use regression techniques. When the target variable type is associated with a categorical target variable value (e.g., a category, a label, etc.), the machine learning model can use classification techniques.

[0060] In some implementations, a machine learning model can be trained on a set of observations that does not include a target variable (or includes the target variable but the machine learning model is not executed to predict the target variable). This can be referred to as an unsupervised learning model, an automatic data analysis model, an automatic signal extraction model, etc. In this case, the machine learning model can learn patterns from the set of observations without labeling or supervision, and can provide outputs indicative of such patterns, such as by identifying groups of related items within the set of observations using clustering and / or association.

[0061] In some aspects described herein, an ML process can be used to develop a neural network using supervised learning. A neural network can be a model comprising connected nodes arranged in layers. Weights and biases can be assigned to the connections. The weights influence the degree to which a given node activates nodes in the next layer. The bias is a threshold that can help eliminate activations that might otherwise produce false positives.

[0062] In some aspects, a neural network may be used to process received MIMO signals. The ML process may include the construction of algorithms and / or models and may be run on the UE, the BS, and / or jointly across the UE and BS (e.g., in the case of a distributed algorithm). While the neural network may be trained offline, the neural network may additionally or alternatively be configured to be trained using known wireless network transmissions as training data to fine-tune the model for network channel, noise, and / or other environmental characteristics.

[0063] A general neural network used as a MIMO demapper can be represented, for example, as y=Hx+n, where y is the received vector, x is the transmitted symbol vector, n is the noise vector, and finally H is the channel matrix. The neural network can be trained offline to determine (estimated symbols) and can benefit from fine-tuning using online training. The input to the neural network can be the received observations (y) and the estimated channel matrix (H), and the output can be the detected transmitted symbols. To perform online training, the neural network can be provided with the true value labels And training data in the form of transmissions with known payloads (e.g., data that the device knows or can regenerate by the device) can be sent to the device (e.g., UE and / or BS) on which the ML model is implemented. The received observations y and the estimated channel matrix (H) can be the inputs of the neural network, and the known payload can be the output (true value label). In this way, the device (UE or gNB) can perform further online training without decoding y to convert the decoded Serves as the ground truth labels for the neural network. Because the payload is known, the neural network can use the training data to learn how to interpret the codewords in the presence of channel characteristics, noise characteristics, etc.

[0064] Training data may include, for example, known reference signals; known payloads of physical downlink control channel (PDCCH) transmissions, physical uplink control channel (PUCCH) transmissions, physical downlink shared channel (PDSCH) transmissions, and physical uplink shared channel (PUSCH) transmissions; periodically repeated system information blocks; and typical unicast transmissions. Conventional data transmissions, such as those indicated above, can be considered known once decoded. However, this approach may require excessive memory and computational overhead. For example, received modulation symbols may need to be stored until decoding is complete.

[0065] In some aspects, techniques and apparatus are provided for communicating known payloads to support ML processes (e.g., processes for training neural networks). In some aspects, a UE may receive an indication of resource allocation from a base station (BS) for communicating data with known payloads and communicate with the BS based at least in part on the resource allocation. In this manner, both the UE and the BS may coordinate information about which transmissions will include known payloads, such that a receiving node (UE and / or BS) may receive the transmissions and process the data contained therein without decoding them (e.g., using the payload data for the ML process).

[0066] In some aspects, a known payload may be generated based on a scrambling seed configured using a radio resource control (RRC) message. The scrambling seed may generate bits for the encoding process so that the known payload transmission may be treated more like a reference signal than a data packet. In this way, a network node may be able to process the transmitted data without decoding the signal. In some aspects, the known payload may be transmitted using a dedicated logical channel that includes assigned priority rules and multiplexing restrictions so that the receiving network node may know that the transmission includes known payload data. In some aspects, for example, the transmission of the dedicated logical channel may be prohibited from being multiplexed with any other logical channel so that the known aspects of the data are not corrupted.

[0067] In some aspects, known payload transmissions can be assigned the lowest priority compared to other types of transmissions so that transmitting the payload to support the ML process does not disrupt regular network traffic flow. In some aspects, multiple dedicated logical channels for transmitting known payloads for the ML process can be defined and assigned priorities relative to each other (e.g., based on logical channel identifiers (IDs), etc.). In some aspects, a specification can prohibit the transmission of uplink control information (UCI) on PUSCH transmissions that include known payloads so that known payload transmissions are not obscured by UCI. In some aspects, exceptions can be made for known payload transmissions with the lowest priority in situations where the ML model is out of date or is exhibiting performance that fails to meet performance thresholds. In this way, known payload transmissions can be prioritized to the extent that these transmissions can contribute to maintaining regular network traffic flow.

[0068] Figure 3 is a diagram illustrating an example 300 for communicating a known payload to support a machine learning process in accordance with various aspects of the present disclosure. As shown, a BS 110 and a UE 120 may communicate with each other.

[0069] As shown by reference numeral 305, BS 110 may transmit and UE 120 may receive an indication of resource allocation for data communication having a known payload. The known payload may include data associated with a machine learning process, as described above. In some aspects, for example, a neural network associated with BS 110 and / or UE 120 may undergo an offline training phase to find weights and biases for the neural network. The neural network may be deployed in another environment (e.g., a wireless network) than the offline environment. The transmission of known data may be used to help BS 110 and / or UE 120 perform online training and refine the neural network parameters (weights and biases) to customize the neural network parameters for the specific environment in which BS 110 and UE 120 are deployed.

[0070] In some aspects, the indication of the resource allocation may be carried in at least one of a radio resource control (RRC) message, a downlink control information (DCI) communication, a medium access control (MAC) control element (CE), or a combination thereof. As shown by reference numeral 310, the UE 120 may communicate with the BS 110 based at least in part on the resource allocation. Communicating with the BS 110 may include transmitting a known payload to the base station and / or receiving a known payload from the BS 110.

[0071] In some aspects, resource allocations and corresponding communications may be configured according to various rules, specifications, etc., such that both BS 110 and UE 120 may know and / or agree upon the payload prior to communication, thereby enabling the receiving entity to process the payload data (e.g., use the payload data in an ML process) without decoding the transmission.

[0072] In some aspects, as indicated above, BS 110 may transmit an indication of the resource allocation in an RRC message. In some aspects, the RRC message may include an indication of a scrambling seed. In some aspects, the RRC message may include configuration of a scrambling seed generation process by which the UE may generate the scrambling seed. In some aspects, UE 120 may generate a known payload based at least in part on the scrambling seed. In some aspects, generating the known payload based at least in part on the scrambling seed may include using the scrambling seed to generate bits to be encoded.

[0073] In some aspects, the data communication may include uplink data communication, and the UE 120 may use a scrambling seed to generate one or more padding bits associated with a known payload. For example, in some aspects, padding bits may be used when the transport block size allocation is larger than the number of bits available. In uplink communications, if the padding is large enough to enable insertion of a buffer status report (BSR), then the BSR may be inserted (which may be referred to as a "padding-BSR"). In some aspects, a wireless communication standard, configuration, or dynamic indication may indicate that a known payload does not have padding (or does not have padding large enough for a BSR) or that a padding-BSR will not be used.

[0074] For example, UE 120 may generate padding bits using the same scrambling seed proposed for the known payload or set the padding bits to zero. Additionally or alternatively, as indicated above, some aspects include generating one or more padding bits associated with the known payload without including the buffer status report in the one or more padding bits.

[0075] In some aspects, as indicated above, BS 110 may transmit an indication of the resource allocation in a DCI. In some aspects, the DCI may include a radio network temporary identifier (RNTI) associated with a known payload. In some aspects, the DCI may include a DCI format associated with a known payload.

[0076] In some aspects, communication may include using a dedicated logical channel to transmit or receive a known payload. The dedicated logical channel may be subject to certain priority and / or multiplexing rules. In some aspects, for example, the dedicated logical channel will not be multiplexed with another logical channel. In some aspects, the dedicated logical channel will not be transmitted in a transport block that includes a media access control (MAC) control element.

[0077] In some aspects, BS 110 and / or UE 120 may transmit a known payload based on a priority associated with a dedicated logical channel. The priority associated with a dedicated logical channel may be configured relative to a priority associated with one or more other dedicated logical channels. In some aspects, the priority associated with a dedicated logical channel may be lower than a priority associated with user data communications. User data may be carried on uplink and / or downlink channels.

[0078] In some aspects, a transmitting entity (UE 110 and / or BS 110) may determine that a machine learning model associated with a machine learning process is out of date or is exhibiting performance that fails to meet a performance threshold. The transmitting entity may transmit the known payload according to a priority associated with a dedicated logical channel, wherein the priority associated with the dedicated logical channel is higher relative to a priority associated with at least one other communication based at least in part on the determination that the machine learning model associated with the machine learning process is out of date or is exhibiting performance that fails to meet a performance threshold.

[0079] In some aspects, a transmitting and / or receiving entity may detect a conflict between a communication associated with a dedicated logical channel and another communication. The transmitting and / or receiving entity may, based at least in part on detecting the conflict, abandon the communication associated with the dedicated logical channel for a time period associated with the other communication. In some aspects, the indication of resource allocation may indicate that only dedicated semi-persistent scheduling grants are to be mapped to the dedicated logical channel. In some aspects, the indication of resource allocation may indicate that only configured grants are to be mapped to the dedicated logical channel.

[0080] As indicated above, Figure 3 are provided as examples. Other examples may differ from those described in Figure 3 Examples described.

[0081] Figure 4 is a diagram illustrating an example 400 associated with transmitting a known payload to support a machine learning process according to the present disclosure. Figure 4 As shown in , BS 110 and UE 120 may communicate with each other.

[0082] As indicated by reference numeral 405, BS 110 may transmit and UE 120 may receive a scrambling seed configuration. The scrambling seed configuration may be transmitted using an RRC message. In some aspects, the RRC message may include an indication of the scrambling seed. In some aspects, the RRC message may include a configuration of a scrambling seed generation process by which the UE may generate the scrambling seed. In some aspects, UE 120 may generate a known payload based at least in part on the scrambling seed. In some aspects, generating the known payload based at least in part on the scrambling seed may include using the scrambling seed to generate bits to be encoded.

[0083] UE 120 may transmit, and BS 110 may receive, a request for data, as indicated by reference numeral 410. For example, UE 120 may determine that a neural network hosted by UE 120 is outdated and should be updated through training. UE 120 may transmit the request for data based at least in part on this determination.

[0084] As shown by reference numeral 415, BS 110 may transmit, and UE 120 may receive, an indication of resource allocation for data communications having a known payload, as described above in conjunction with Figure 3 As shown by reference numeral 420, BS 110 may transmit and UE 120 may receive data communications including a known payload. UE 120 may use the data communications to update the neural network through a training process.

[0085] In some aspects, the data transmission may be an uplink transmission instead of a downlink data transmission. For example, BS 110 may determine that a neural network maintained at BS 110 is outdated. BS 110 may transmit a resource allocation to UE 120 based at least in part on this determination without first sending a data request.

[0086] As indicated above, Figure 4 are provided as examples. Other examples may differ from those described in Figure 4 Examples described.

[0087] Figure 5 is a diagram illustrating an example process 500, performed, for example, by a UE, in accordance with various aspects of the present disclosure. Example process 500 is an example in which a UE (eg, UE 120, etc.) performs operations associated with communicating a known payload to support an ML process.

[0088] like Figure 5As shown in , in some aspects, process 500 may include receiving, from a base station, an indication of resource allocation for data communications having a known payload that includes data associated with a machine learning process (block 510). For example, a UE (e.g., using receive processor 258, controller / processor 280, memory 282, etc.) may receive, from a base station, an indication of resource allocation for data communications having a known payload that includes data associated with a machine learning process, as described above.

[0089] like Figure 5 As further shown in FIG5 , in some aspects, process 500 may include communicating with a base station based at least in part on the resource allocation (block 520). For example, the UE (e.g., using receive processor 258, transmit processor 264, controller / processor 280, memory 282, etc.) may communicate with the base station based at least in part on the resource allocation, as described above.

[0090] Process 500 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere herein.

[0091] In a first aspect, receiving an indication of a resource allocation includes receiving at least one of a radio resource control message, a medium access control (MAC) control element, or a downlink control information communication.

[0092] In a second aspect, alone or in combination with the first aspect, process 500 includes receiving an indication of a scrambling seed from the base station; and generating a known payload based at least in part on the scrambling seed, wherein communicating with the base station includes transmitting the known payload to the base station or receiving the known payload from the base station.

[0093] In a third aspect, alone or in combination with the second aspect, the scrambling seed is carried in a radio resource control message.

[0094] In a fourth aspect, alone or in combination with one or more of the second to third aspects, generating the known payload based at least in part on the scrambling seed comprises using the scrambling seed to generate bits to be encoded.

[0095] In a fifth aspect, alone or in combination with one or more of the second to fourth aspects, the data communication comprises uplink data communication, the method further comprising using the scrambling seed to generate one or more padding bits associated with the known payload.

[0096] In a sixth aspect, either alone or in combination with one or more of the first to fifth aspects, the data communication comprises uplink data communication, the method further comprising generating one or more padding bits associated with the known payload, the one or more padding bits each having a value of zero.

[0097] In a seventh aspect, either alone or in combination with one or more of the first to fifth aspects, the data communication includes uplink data communication, and process 500 further includes generating one or more padding bits associated with a known payload without including a buffer status report in the one or more padding bits.

[0098] In an eighth aspect, alone or in combination with one or more of the first to seventh aspects, communicating with the base station includes using a dedicated logical channel to transmit or receive a known payload.

[0099] In a ninth aspect, alone or in combination with the eighth aspect, the dedicated logical channel shall not be multiplexed with another logical channel.

[0100] In a tenth aspect, alone or in combination with one or more of the eighth to ninth aspects, uplink control information (UCI) shall not be carried by a physical uplink shared channel (PUSCH) communication including the known payload.

[0101] In an eleventh aspect, alone or in combination with one or more of the eighth to tenth aspects, dedicated logical channels shall not be transmitted in a transport block including a medium access control (MAC) control element.

[0102] In a twelfth aspect, alone or in combination with one or more of aspects eight to eleven, process 500 includes transmitting a known payload based on a priority associated with a dedicated logical channel, wherein the priority associated with the dedicated logical channel is configured relative to a priority associated with another dedicated logical channel.

[0103] In a thirteenth aspect, alone or in combination with one or more of aspects eight to twelfth, process 500 includes transmitting a known payload based on a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is lower than the priority associated with the user data communication.

[0104] In a fourteenth aspect, alone or in combination with one or more of aspects eight to thirteen, process 500 includes transmitting a known payload based on a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is lower than the priority associated with the reference signal.

[0105] In a fifteenth aspect, alone or in combination with one or more of aspects eight to fourteen, process 500 includes determining that a machine learning model associated with the machine learning process is outdated or is exhibiting performance that fails to meet a performance threshold; and transmitting a known payload according to a priority associated with a dedicated logical channel, wherein the priority associated with the dedicated logical channel is higher relative to a priority associated with at least one other communication based at least in part on determining that the machine learning model associated with the machine learning process is outdated or is exhibiting performance that fails to meet a performance threshold.

[0106] In the sixteenth aspect, alone or in combination with one or more of aspects eight to fifteen, process 500 includes detecting a conflict between the communication associated with the dedicated logical channel and another communication; and abandoning the communication associated with the dedicated logical channel for a time period associated with the other communication based at least in part on detecting the conflict.

[0107] In a seventeenth aspect, alone or in combination with one or more of the eighth to sixteenth aspects, the indication of the resource allocation indicates a dedicated semi-persistent scheduling grant to which only dedicated logical channels are to be mapped.

[0108] In an eighteenth aspect, alone or in combination with one or more of the eighth to seventeenth aspects, the indication of the resource allocation indicates that only dedicated logical channels are to be mapped onto the configured grants.

[0109] In the nineteenth aspect, alone or in combination with one or more of the first to eighteenth aspects, the indication of the resource allocation indicates at least one of the periodic functionality of the dedicated logical channel, the semi-persistent functionality of the dedicated logical channel, the aperiodic functionality of the dedicated logical channel, or a combination thereof.

[0110] In the twentieth aspect, alone or in combination with one or more of the first to nineteenth aspects,

[0111] Receiving an indication of the resource allocation includes receiving downlink control information (DCI) including a radio network temporary identifier associated with the known payload.

[0112] In a twenty-first aspect, alone or in combination with one or more of the first to twentieth aspects, receiving an indication of the resource allocation comprises receiving a DCI comprising a new DCI format associated with the known payload.

[0113] In aspect twenty-second, alone or in combination with one or more of aspects one to twenty-first, the data communication includes downlink data communication, and the process 500 further includes: receiving the downlink data communication; and processing the downlink data communication without decoding the downlink data communication to extract data associated with the machine learning process.

[0114] although Figure 5 Example blocks of process 500 are shown, but in some aspects, process 500 may include Figure 5 5. In some embodiments, the process 500 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in FIG. Additionally or alternatively, two or more blocks of process 500 may be executed in parallel.

[0115] Figure 6 is a diagram illustrating an example process 600, performed, for example, by a base station, in accordance with various aspects of the present disclosure. Example process 600 is an example of operations in which a base station (e.g., base station 110, etc.) performs operations associated with communicating a known payload to support a machine learning process.

[0116] like Figure 6 As shown in , in some aspects, process 600 may include transmitting to a UE an indication of resource allocation for data communications having a known payload that includes data associated with a machine learning process (block 610). For example, a base station (e.g., using transmit processor 220, controller / processor 240, memory 242, etc.) may transmit to a UE an indication of resource allocation for data communications having a known payload that includes data associated with a machine learning process, as described above.

[0117] like Figure 6 As further shown in FIG6 , in some aspects, process 600 may include communicating with the UE based at least in part on the resource allocation (block 620). For example, the base station (e.g., using transmit processor 220, receive processor 238, controller / processor 240, memory 242, etc.) may communicate with the UE based at least in part on the resource allocation, as described above.

[0118] Process 600 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere herein.

[0119] In a first aspect, transmitting the indication of the resource allocation includes transmitting at least one of a radio resource control message, a MAC-CE, or a downlink control information communication.

[0120] In a second aspect, alone or in combination with the first aspect, process 600 includes transmitting an indication of a scrambling seed to the UE; and receiving the known payload from the UE, wherein the known payload is based at least in part on the scrambling seed.

[0121] In a third aspect, alone or in combination with the second aspect, the scrambling seed is carried in a radio resource control message.

[0122] In a fourth aspect, alone or in combination with one or more of the first to third aspects, the data communication comprises downlink data communication, and the process 600 further comprises using the scrambling seed to generate one or more padding bits associated with the known payload.

[0123] In a fifth aspect, either alone or in combination with one or more of the first to fourth aspects, the data communication comprises downlink data communication, the process 600 further comprising generating one or more padding bits associated with the known payload, the one or more padding bits each having a value of zero.

[0124] In a sixth aspect, alone or in combination with one or more of the first to fifth aspects, communicating with the UE includes using a dedicated logical channel to transmit or receive a known payload.

[0125] In a seventh aspect, alone or in combination with the sixth aspect, the dedicated logical channel shall not be multiplexed with another logical channel.

[0126] In an eighth aspect, alone or in combination with one or more of the first to seventh aspects, dedicated logical channels shall not be transmitted in transport blocks including medium access control (MAC) control elements.

[0127] In a ninth aspect, alone or in combination with the eighth aspect, process 600 includes transmitting a known payload according to a priority associated with a dedicated logical channel, wherein the priority associated with the dedicated logical channel is configured relative to a priority associated with another dedicated logical channel.

[0128] In a tenth aspect, either alone or in combination with one or more of the eighth to ninth aspects, the process 600 includes transmitting a known payload based on a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is lower relative to a priority associated with user data communications.

[0129] In an eleventh aspect, alone or in combination with one or more of aspects eight to ten, process 600 includes transmitting a known payload based on a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is lower than the priority associated with the reference signal.

[0130] In a twelfth aspect, alone or in combination with one or more of the eighth to eleventh aspects, process 600 includes determining that a machine learning model associated with the machine learning process is outdated or is exhibiting performance that fails to meet a performance threshold; and transmitting a known payload according to a priority associated with a dedicated logical channel, wherein the priority associated with the dedicated logical channel is higher relative to a priority associated with at least one other communication based at least in part on determining that the machine learning model associated with the machine learning process is outdated or is exhibiting performance that fails to meet the performance threshold.

[0131] In the thirteenth aspect, alone or in combination with one or more of aspects eight to twelfth, process 600 includes detecting a conflict between the communication associated with the dedicated logical channel and another communication; and abandoning the communication associated with the dedicated logical channel for a time period associated with the other communication based at least in part on detecting the conflict.

[0132] In a fourteenth aspect, alone or in combination with one or more of the eighth to thirteenth aspects, the indication of the resource allocation indicates a dedicated semi-persistent scheduling grant onto which only dedicated logical channels are to be mapped.

[0133] In a fifteenth aspect, alone or in combination with one or more of the eighth to fourteenth aspects, the indication of the resource allocation indicates that only dedicated logical channels are to be mapped onto the configured grants.

[0134] In the sixteenth aspect, alone or in combination with one or more of the eighth to fifteenth aspects, the indication of the resource allocation indicates at least one of the periodic functionality of the dedicated logical channel, the semi-persistent functionality of the dedicated logical channel, the aperiodic functionality of the dedicated logical channel, or a combination thereof.

[0135] In a seventeenth aspect, alone or in combination with one or more of the eighth to sixteenth aspects, transmitting an indication of the resource allocation comprises transmitting a DCI comprising a radio network temporary identifier associated with the known payload.

[0136] In an eighteenth aspect, alone or in combination with one or more of the eighth to seventeenth aspects, transmitting an indication of the resource allocation comprises transmitting a DCI comprising a new DCI format associated with the known payload.

[0137] In a nineteenth aspect, alone or in combination with one or more of aspects one to eighteen, the data communication includes uplink data communication, and the method further includes: receiving the uplink data communication; and processing the uplink data communication without decoding the uplink data communication to extract data associated with the machine learning process.

[0138] although Figure 6 Example blocks of process 600 are shown, but in some aspects, process 600 may include Figure 6 6. In some embodiments, the process 600 may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in FIG. Additionally or alternatively, two or more blocks of process 600 may be executed in parallel.

[0139] The following provides an overview of some aspects of the disclosure:

[0140] Aspect 1: A wireless communication method performed by a user equipment (UE), comprising: receiving an indication of resource allocation for data communication having a known payload, the known payload including data associated with a machine learning process, from a base station; and communicating with the base station based at least in part on the resource allocation.

[0141] Aspect 2: The method of aspect 1, wherein receiving an indication of resource allocation comprises receiving at least one of a radio resource control message, a medium access control (MAC) control element, or a downlink control information communication.

[0142] Aspect 3: The method of any one of Aspects 1 or 2, further comprising: receiving an indication of a scrambling seed from the base station; and generating a known payload based at least in part on the scrambling seed, wherein communicating with the base station comprises transmitting the known payload to the base station or receiving the known payload from the base station.

[0143] Aspect 4: The method of aspect 3, wherein the scrambling seed is carried in a radio resource control message.

[0144] Aspect 5: The method of any of Aspects 3 or 4, wherein generating the known payload based at least in part on the scrambling seed comprises using the scrambling seed to generate bits to be encoded.

[0145] Aspect 6: The method of any of aspects 3-5, wherein the data communication comprises uplink data communication, the method further comprising using the scrambling seed to generate one or more padding bits associated with the known payload.

[0146] Aspect 7: The method of any one of Aspects 1-5, wherein the data communication comprises uplink data communication, the method further comprising generating one or more padding bits associated with the known payload, wherein the one or more padding bits each have a value of zero.

[0147] Aspect 8: The method of any one of Aspects 1-5, wherein the data communication comprises uplink data communication, the method further comprising generating one or more padding bits associated with a known payload without including a buffer status report in the one or more padding bits.

[0148] Aspect 9: The method of any one of aspects 1-8, wherein communicating with the base station comprises using a dedicated logical channel to transmit or receive a known payload.

[0149] Aspect 10: The method of aspect 9, wherein the dedicated logical channel will not be multiplexed with another logical channel.

[0150] Aspect 11: The method of any one of Aspects 9 or 10, wherein uplink control information (UCI) will not be carried by a physical uplink shared channel (PUSCH) communication including the known payload.

[0151] Aspect 12: The method of any of aspects 9-11, wherein the dedicated logical channel is not to be transmitted in a transport block including a medium access control (MAC) control element.

[0152] Aspect 13: The method of any of aspects 9-12, further comprising transmitting the known payload according to a priority associated with a dedicated logical channel, wherein the priority associated with the dedicated logical channel is configured relative to a priority associated with another dedicated logical channel.

[0153] Aspect 14: The method of any of aspects 9-13, further comprising transmitting the known payload according to a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is lower relative to a priority associated with user data communications.

[0154] Aspect 15: The method of any one of aspects 9-14, further comprising transmitting the known payload according to a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is lower relative to a priority associated with the reference signal.

[0155] Aspect 16: The method of any of Aspects 9-15, further comprising: determining that a machine learning model associated with the machine learning process is outdated or is exhibiting performance that fails to meet a performance threshold; and transmitting a known payload according to a priority associated with a dedicated logical channel, wherein the priority associated with the dedicated logical channel is higher relative to a priority associated with at least one other communication based at least in part on determining that the machine learning model associated with the machine learning process is outdated or is exhibiting performance that fails to meet a performance threshold.

[0156] Aspect 17: The method of any one of Aspects 9-16, further comprising: detecting a conflict between the communication associated with the dedicated logical channel and another communication; and abandoning the communication associated with the dedicated logical channel within a time period associated with the other communication based at least in part on detecting the conflict.

[0157] Aspect 18: The method of any of aspects 9-17, wherein the indication of the resource allocation indicates that only dedicated logical channels are to be mapped onto dedicated semi-persistent scheduling grants.

[0158] Aspect 19: The method of any of aspects 9-17, wherein the indication of the resource allocation indicates configured grants onto which only dedicated logical channels are to be mapped.

[0159] Aspect 20: The method of any one of Aspects 1-19, wherein the indication of the resource allocation indicates at least one of periodic functionality of the dedicated logical channel, semi-persistent functionality of the dedicated logical channel, aperiodic functionality of the dedicated logical channel, or a combination thereof.

[0160] Aspect 21: The method of any of aspects 1-20, wherein receiving an indication of the resource allocation comprises receiving downlink control information (DCI), the DCI comprising a radio network temporary identifier associated with the known payload.

[0161] Aspect 22: The method of any of aspects 1-21, wherein receiving an indication of the resource allocation comprises receiving downlink control information (DCI), the DCI comprising a new DCI format associated with the known payload.

[0162] Aspect 23: A method as in any of Aspects 1-22, wherein the data communication includes downlink data communication, the method further comprising: receiving the downlink data communication; and processing the downlink data communication to extract data associated with the machine learning process without decoding the downlink data communication.

[0163] Aspect 24: A wireless communication method performed by a base station, comprising: transmitting to a user equipment (UE) an indication of a resource allocation for data communication having a known payload, the known payload including data associated with a machine learning process; and communicating with the UE based at least in part on the resource allocation.

[0164] Aspect 25: The method of aspect 24, wherein receiving an indication of a resource allocation comprises receiving at least one of a radio resource control message, a medium access control (MAC) control element, or a downlink control information communication.

[0165] Aspect 26: The method of any one of Aspects 24 or 25, further comprising: transmitting an indication of a scrambling seed to the UE; and receiving the known payload from the UE, wherein the known payload is based at least in part on the scrambling seed.

[0166] Aspect 27: The method of Aspect 26, wherein the scrambling seed is carried in a radio resource control message.

[0167] Aspect 28: The method of aspect 24, wherein the data communication comprises downlink data communication, the method further comprising using the scrambling seed to generate one or more padding bits associated with the known payload.

[0168] Aspect 29: The method of any of Aspects 24-28, wherein the data communication comprises downlink data communication, the method further comprising generating one or more padding bits associated with the known payload, wherein the one or more padding bits each have a value of zero.

[0169] Aspect 30: The method of any one of aspects 24-29, wherein communicating with the UE comprises using a dedicated logical channel to transmit or receive a known payload.

[0170] Aspect 31: The method of aspect 30, wherein the dedicated logical channel will not be multiplexed with another logical channel.

[0171] Aspect 32: The method of any of Aspects 30 or 31, wherein the dedicated logical channel is not to be transmitted in a transport block including a medium access control (MAC) control element.

[0172] Aspect 33: The method of any of aspects 30-32, further comprising transmitting the known payload according to a priority associated with a dedicated logical channel, wherein the priority associated with the dedicated logical channel is configured relative to a priority associated with another dedicated logical channel.

[0173] Aspect 34: The method of any one of aspects 30-33, further comprising transmitting the known payload according to a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is lower relative to a priority associated with user data communications.

[0174] Aspect 35: The method of any one of aspects 30-34, further comprising transmitting the known payload according to a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is lower relative to a priority associated with the reference signal.

[0175] Aspect 36: The method of any of Aspects 30-35, further comprising: determining that a machine learning model associated with the machine learning process is outdated or is exhibiting performance that fails to meet a performance threshold; and transmitting a known payload according to a priority associated with a dedicated logical channel, wherein the priority associated with the dedicated logical channel is higher relative to a priority associated with at least one other communication based at least in part on determining that the machine learning model associated with the machine learning process is outdated or is exhibiting performance that fails to meet a performance threshold.

[0176] Aspect 37: The method of any one of Aspects 30-36, further comprising: detecting a conflict between the communication associated with the dedicated logical channel and another communication; and abandoning the communication associated with the dedicated logical channel within a time period associated with the other communication based at least in part on detecting the conflict.

[0177] Aspect 38: The method of any of aspects 30-37, wherein the indication of the resource allocation indicates that only dedicated logical channels are to be mapped onto dedicated semi-persistent scheduling grants.

[0178] Aspect 39: The method of any of aspects 30-38, wherein the indication of the resource allocation indicates that only dedicated logical channels are to be mapped onto the configured grants.

[0179] Aspect 40: The method of any one of Aspects 30-39, wherein the indication of the resource allocation indicates at least one of periodic functionality of the dedicated logical channel, semi-persistent functionality of the dedicated logical channel, aperiodic functionality of the dedicated logical channel, or a combination thereof.

[0180] Aspect 41: The method of any of Aspects 30-40, wherein transmitting the indication of the resource allocation comprises transmitting downlink control information (DCI), the DCI comprising a radio network temporary identifier associated with the known payload.

[0181] Aspect 42: The method of any of aspects 30-41, wherein transmitting an indication of the resource allocation comprises transmitting downlink control information (DCI), the DCI comprising a new DCI format associated with the known payload.

[0182] Aspect 43: A method as in any of Aspects 24-42, wherein the data communication includes uplink data communication, the method further comprising: receiving the uplink data communication; and processing the uplink data communication to extract data associated with the machine learning process without decoding the uplink data communication.

[0183] Aspect 44: An apparatus for wireless communication at a device, comprising: a processor; a memory coupled to the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform a method as in one or more aspects of aspects 1-23.

[0184] Aspect 45: An apparatus for wireless communication, comprising a memory and one or more processors coupled to the memory, the memory and the one or more processors configured to perform the method of one or more aspects of aspects 1-23.

[0185] Aspect 46: An apparatus for wireless communication, comprising at least one means for performing the method of one or more of aspects 1-23.

[0186] Aspect 47: A non-transitory computer-readable medium storing code for wireless communication, the code comprising instructions executable by a processor to perform the method of one or more aspects of aspects 1-23.

[0187] Aspect 48: A non-transitory computer-readable medium storing an instruction set for wireless communication, the instruction set comprising one or more instructions that, when executed by one or more processors of a device, cause the device to perform the method of one or more aspects of aspects 1-23.

[0188] Aspect 49: An apparatus for wireless communication at a device, comprising: a processor; a memory coupled to the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform a method as in one or more aspects of Aspects 24-43.

[0189] Aspect 50: A device for wireless communication, comprising a memory and one or more processors coupled to the memory, the memory and the one or more processors configured to perform the method of one or more aspects of aspects 24-43.

[0190] Aspect 51: An apparatus for wireless communication, comprising at least one means for performing the method of one or more aspects of aspects 24-43.

[0191] Aspect 52: A non-transitory computer-readable medium storing code for wireless communication, the code comprising instructions executable by a processor to perform the method of one or more aspects of aspects 24-43.

[0192] Aspect 53: A non-transitory computer-readable medium storing an instruction set for wireless communication, the instruction set comprising one or more instructions that, when executed by one or more processors of a device, cause the device to perform the method of one or more aspects of aspects 24-43.

[0193] The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit the aspects to the precise form disclosed. Modifications and variations may be made in light of the above disclosure or may be acquired from practice of the aspects.

[0194] Further disclosure is included in the Appendix. This Appendix is ​​provided by way of example only and should be considered a part of this specification. Definitions, illustrations, or other descriptions in the Appendix do not supersede or override similar information contained in the Detailed Description or Figures. Furthermore, definitions, illustrations, or other descriptions in the Detailed Description or Figures do not supersede or override similar information contained in the Appendix. Furthermore, this Appendix is ​​not intended to limit the disclosure of possible aspects.

[0195] As used herein, the term "component" is intended to be broadly interpreted as a combination of hardware and / or hardware and software. "Software" should be broadly interpreted as meaning an instruction, an instruction set, a code, a code segment, a program code, a program, a subroutine, a software module, an application, a software application, a software package, a routine, a subroutine, an object, an executable, a thread of execution, a procedure, and / or a function, etc., whether it is described in software, firmware, middleware, microcode, hardware description language or other terms. As used herein, a processor is implemented with hardware and / or a combination of hardware and software. It will be apparent that the systems and / or methods described herein can be implemented in different forms of hardware and / or a combination of hardware and software. The actual dedicated control hardware or software code used to implement these systems and / or methods does not limit various aspects. Thus, the operation and behavior of these systems and / or methods are described herein without reference to specific software code - it is understood that software and hardware can be designed to implement these systems and / or methods based at least in part on the description herein.

[0196] As used herein, satisfying a threshold may refer to a value being greater than a threshold, greater than or equal to a threshold, less than a threshold, less than or equal to a threshold, equal to a threshold, not equal to a threshold, etc., depending on the context.

[0197] Although specific feature combinations are described in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of various aspects. In fact, many of these features can be combined in a manner not specifically described in the claims and / or not disclosed in the specification. Although each dependent claim listed below can be directly subordinate to only one claim, the disclosure of various aspects includes that each dependent claim is combined with each other claim in this group of claims. As used herein, the phrase quoting "at least one of" a column of items refers to any combination of these items, including single members. As an example, "at least one of a, b or c" is intended to encompass: a, b, c, ab, ac, bc, and abc, as well as any combination with multiple identical elements (e.g., aa, aaa, aab, aac, abb, acc, bb, bbb, bbc, cc, and ccc, or any other sorting of a, b and c).

[0198] The elements, actions or instructions used herein should not be interpreted as key or necessary unless explicitly described as such. Moreover, as used herein, the articles "one" and "a" are intended to include one or more projects and can be used interchangeably with "one or more". Furthermore, as used herein, the article "the" is intended to include one or more projects cited in conjunction with the article "the", and can be used interchangeably with "one or more". Furthermore, as used herein, the terms "set (set, group)" and "group" are intended to include one or more projects (for example, related items, non-related items, or a combination of related items and non-related items), and can be used interchangeably with "one or more". In the case of being intended to have only one project, the phrase "only one" or similar language is used. Moreover, as used herein, the terms "having", "containing", "comprising" etc. are intended to be open terms. Furthermore, the phrase "based on" is intended to mean "at least partially based on", unless otherwise explicitly stated. Furthermore, as used herein, the term "or" when used in a sequence is intended to be inclusive and can be used interchangeably with "and / or" unless expressly stated otherwise (e.g., when used in conjunction with "either of" or "only one of").

Claims

1. A user equipment (UE) for wireless communication, comprising: Memory; as well as one or more processors coupled to the memory, the one or more processors configured to: receiving, from a network node, an indication of resource allocation for data communications having a known payload including data associated with a machine learning process; and The known payload is transmitted or received with the network node using a dedicated logical channel based at least in part on the resource allocation, wherein the dedicated logical channel adheres to assigned priority rules and / or multiplexing restrictions.

2. The UE of claim 1 , wherein the one or more processors, when receiving the indication of the resource allocation, are configured to receive at least one of a radio resource control message, a medium access control (MAC) control element, or a downlink control information communication.

3. The UE of claim 1 , wherein the one or more processors are further configured to: receiving an indication of a scrambling seed from the network node; and generating the known payload based at least in part on the scrambling seed, Wherein, when transmitting or receiving the known payload, the one or more processors are configured to transmit the known payload to the network node or receive the known payload from the network node.

4. The UE of claim 3, wherein the one or more processors, when generating the known payload based at least in part on the scrambling seed, are configured to use the scrambling seed to generate bits to be encoded.

5. The UE of claim 3, wherein the data communication comprises an uplink data communication, and wherein the one or more processors are further configured to use the scrambling seed to generate one or more padding bits associated with the known payload.

6. The UE of claim 1 , wherein the data communication comprises uplink data communication, and wherein the one or more processors are further configured to generate one or more padding bits associated with the known payload, wherein the one or more padding bits each have a value of zero.

7. The UE of claim 1 , wherein the data communication comprises uplink data communication, and wherein the one or more processors are further configured to generate one or more padding bits associated with the known payload without including a buffer status report in the one or more padding bits.

8. The UE of claim 1, wherein the dedicated logical channel will not be multiplexed with another logical channel.

9. The UE of claim 1 , wherein uplink control information (UCI) will not be carried by a physical uplink shared channel (PUSCH) communication including the known payload, and wherein the dedicated logical channel will not be transmitted in a transport block including a medium access control (MAC) control element.

10. The UE of claim 1 , wherein the one or more processors are further configured to transmit the known payload according to a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is configured relative to a priority associated with another dedicated logical channel.

11. The UE of claim 1 , wherein the one or more processors are further configured to transmit the known payload according to a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is lower relative to a priority associated with at least one of: user data communication, or a reference signal.

12. The UE of claim 1 , wherein the one or more processors are further configured to: determining that a machine learning model associated with the machine learning process is outdated or is exhibiting performance that fails to meet a performance threshold; and The known payload is transmitted according to a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is higher relative to a priority associated with at least one other communication based at least in part on a determination that the machine learning model associated with the machine learning process is out of date or is exhibiting performance that fails to meet the performance threshold.

13. The UE of claim 1 , wherein the one or more processors are further configured to: detecting a collision between the communication associated with the dedicated logical channel and another communication; and Based at least in part on detecting the collision, the communication associated with the dedicated logical channel is abandoned for a time period associated with the other communication.

14. The UE of claim 1 , wherein the indication of the resource allocation indicates at least one of: a dedicated semi-persistent scheduling grant to which only the dedicated logical channel will be mapped, or Only the dedicated logical channels will have configured grants mapped onto them.

15. The UE of claim 1, wherein the indication of the resource allocation indicates at least one of periodic functionality of the dedicated logical channel, semi-persistent functionality of the dedicated logical channel, aperiodic functionality of the dedicated logical channel, or a combination thereof.

16. The UE of claim 1 , wherein the one or more processors, upon receiving the indication of the resource allocation, are configured to receive downlink control information (DCI), the DCI comprising at least one of: a radio network temporary identifier associated with said known payload, or A new DCI format associated with the known payload.

17. The UE of claim 1 , wherein the data communication comprises a downlink data communication, and wherein the one or more processors are further configured to: receiving the downlink data communication; and The downlink data communications are processed without decoding the downlink data communications to extract the data associated with the machine learning process.

18. A network node for wireless communication, comprising: Memory; as well as one or more processors coupled to the memory, the one or more processors configured to: transmitting an indication of an allocation of resources for data communications having a known payload including data associated with a machine learning process; and The known payload is transmitted or received with a user equipment (UE) using a dedicated logical channel based at least in part on the resource allocation, wherein the dedicated logical channel adheres to assigned priority rules and / or multiplexing restrictions.

19. The network node of claim 18, wherein the one or more processors are further configured to: transmitting an indication of a scrambled seed; and The known payload is received, wherein the known payload is based at least in part on the scrambling seed.

20. The network node of claim 19, wherein the data communication comprises downlink data communication, and wherein the one or more processors are further configured to: using the scrambling seed to generate one or more padding bits associated with the known payload, or Set one or more padding bits to zero.

21. The network node of claim 18, wherein the dedicated logical channel is not to be multiplexed with another logical channel, and wherein the dedicated logical channel is not to be transmitted in a transport block including a medium access control (MAC) control element.

22. The network node of claim 18, wherein the one or more processors are further configured to transmit the known payload according to a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is configured relative to a priority associated with another dedicated logical channel.

23. The network node of claim 18, wherein the one or more processors are further configured to transmit the known payload according to a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is lower relative to a priority associated with at least one of: user data communications, or a reference signal.

24. The network node of claim 18, wherein the one or more processors are further configured to: determining that a machine learning model associated with the machine learning process is outdated or is exhibiting performance that fails to meet a performance threshold; and The known payload is transmitted according to a priority associated with the dedicated logical channel, wherein the priority associated with the dedicated logical channel is higher relative to a priority associated with at least one other communication based at least in part on a determination that the machine learning model associated with the machine learning process is out of date or is exhibiting performance that fails to meet the performance threshold.

25. The network node of claim 18, wherein the one or more processors are further configured to: detecting a collision between the communication associated with the dedicated logical channel and another communication; and Based at least in part on detecting the collision, the communication associated with the dedicated logical channel is abandoned for a time period associated with the other communication.

26. The network node of claim 18, wherein the one or more processors, when transmitting the indication of the resource allocation, are configured to transmit downlink control information (DCI), the DCI comprising at least one of: a radio network temporary identifier associated with said known payload, or A new DCI format associated with the known payload.

27. The network node of claim 18, wherein the data communication comprises uplink data communication, and wherein the one or more processors are further configured to: receiving the uplink data communication; and The uplink data communications are processed without decoding the uplink data communications to extract the data associated with the machine learning process.

28. A wireless communication method performed by a user equipment (UE), comprising: receiving, from a network node, an indication of resource allocation for data communications having a known payload, the known payload including data associated with a machine learning process; as well as The known payload is transmitted or received with the network node using a dedicated logical channel based at least in part on the resource allocation, wherein the dedicated logical channel adheres to assigned priority rules and / or multiplexing restrictions.

29. The method of claim 28, wherein receiving the indication of the resource allocation comprises receiving at least one of a radio resource control message, a medium access control (MAC) control element, or a downlink control information communication.

30. A wireless communication method performed by a network node, comprising: transmitting an indication of an allocation of resources for data communications having a known payload, the known payload including data associated with a machine learning process; as well as The known payload is transmitted or received with a user equipment (UE) using a dedicated logical channel based at least in part on the resource allocation, wherein the dedicated logical channel adheres to assigned priority rules and / or multiplexing restrictions.

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