Method and apparatus for data collection based on logging duration

Abstract

A method and apparatus for data collection based on logging duration are provided. A wireless device receives a configuration for data logging, wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval. The wireless device performs data logging based on the logging duration, wherein the logging duration is configured within the logging interval.

Description

METHOD AND APPARATUS FOR DATA COLLECTION BASED ON LOGGING DURATION

[0001] The present disclosure relates to a method and apparatus for data collection based on logging duration.

[0002] 3rd generation partnership project (3GPP) long-term evolution (LTE) is a technology for enabling high-speed packet communications. Many schemes have been proposed for the LTE objective including those that aim to reduce user and provider costs, improve service quality, and expand and improve coverage and system capacity. The 3GPP LTE requires reduced cost per bit, increased service availability, flexible use of a frequency band, a simple structure, an open interface, and adequate power consumption of a terminal as an upper-level requirement.

[0003] Work has started in international telecommunication union (ITU) and 3GPP to develop requirements and specifications for new radio (NR) systems. 3GPP has to identify and develop the technology components needed for successfully standardizing the new RAT timely satisfying both the urgent market needs, and the more long-term requirements set forth by the ITU radio communication sector (ITU-R) international mobile telecommunications (IMT)-2020 process. Further, the NR should be able to use any spectrum band ranging at least up to 100 GHz that may be made available for wireless communications even in a more distant future.

[0004] The NR targets a single technical framework addressing all usage scenarios, requirements and deployment scenarios including enhanced mobile broadband (eMBB), massive machine-type-communications (mMTC), ultra-reliable and low latency communications (URLLC), etc. The NR shall be inherently forward compatible.

[0005] When AI / ML models are trained within the network, the UE may need to frequently send assistant data to enhance model performance through data collection. For example, in Release 19, use cases such as beam management and CSI prediction require data collection via CSI reporting for AI / ML model training, inference, and monitoring. In such cases, additional CSI reports may be necessary to support these models, leading to more frequent reporting compared to non-AIML operations.

[0006] To address these challenges, at least for model training purpose, RRC logging has been proposed. By utilizing logging and transmission mechanisms, RRC logging can help reduce the frequency of data transmissions, thus minimizing power consumption and signalling overhead while maintaining AI / ML model performance.

[0007] However, if the measurement or logging period is too short to collect detailed data, it may lead to issues such as increased UE power consumption and memory overload. The additional burden of continuous measurement and logging can be significant, given the UE's limited power and memory resources.

[0008] To mitigate this, extending the measurement / logging period can be considered. However, in such cases, it becomes difficult to capture detailed information for a specific time interval, making it challenging to analyze or understand critical patterns or changes that occur within that period, potentially resulting in meaningless measurement / logging data.

[0009] Thus, studies for data collection based on logging duration are required.

[0010] In an aspect, a method is provided. The method comprises: receiving, by a wireless device, a configuration for data logging, wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval; and performing, by the wireless device, data logging based on the logging duration, wherein the logging duration is configured within the logging interval.

[0011] In another aspect, an apparatus for implementing the above method is provided.

[0012] The present disclosure can have various advantageous effects.

[0013] According to some embodiments of the present disclosure, a wireless device could efficiently perform data collection based on logging duration.

[0014] For example, by controlling the logging interval to a short value, interpretation for a specific period can be improved, while limiting the logging operation during the logging duration can reduce the power consumption of the UE.

[0015] For example, the wireless device may perform data collection only during the logging duration within the logging interval. Therefore, the wireless device can save unnecessary resources.

[0016] According to some embodiments of the present disclosure, the wireless communication system could provide an efficient solution for data collection based on logging duration.

[0017] Advantageous effects which can be obtained through specific embodiments of the present disclosure are not limited to the advantageous effects listed above. For example, there may be a variety of technical effects that a person having ordinary skill in the related art can understand and / or derive from the present disclosure. Accordingly, the specific effects of the present disclosure are not limited to those explicitly described herein, but may include various effects that may be understood or derived from the technical features of the present disclosure.

[0018] FIG. 1 shows an example of a communication system to which implementations of the present disclosure is applied.

[0019] FIG. 2 shows an example of wireless devices to which implementations of the present disclosure is applied.

[0020] FIG. 3 shows an example of a wireless device to which implementations of the present disclosure is applied.

[0021] FIG. 4 shows another example of wireless devices to which implementations of the present disclosure is applied.

[0022] FIG. 5 shows an example of UE to which implementations of the present disclosure is applied.

[0023] FIGS. 6 and 7 show an example of protocol stacks in a 3GPP based wireless communication system to which implementations of the present disclosure is applied.

[0024] FIG. 8 shows a frame structure in a 3GPP based wireless communication system to which implementations of the present disclosure is applied.

[0025] FIG. 9 shows a data flow example in the 3GPP NR system to which implementations of the present disclosure is applied.

[0026] FIG. 10 shows an example of functional framework for AI / ML for NR Air Interface.

[0027] FIG. 11 shows an example of measurement reporting procedure.

[0028] FIG. 12 shows an example of location measurement indication.

[0029] FIG. 13 shows an example of logged measurement configuration.

[0030] FIG. 14 shows an example of UE information procedure.

[0031] FIG. 15 shows an example for data collection.

[0032] FIG. 16 shows an example of a method for data collection based on logging duration.

[0033] FIG. 17 shows an example of a method for logging with partial time domain within reporting interval.

[0034] FIG. 18 shows an example of a method for logging with periodic reporting with logging interval.

[0035] FIG. 19 shows an example of a method for logging with periodic reporting without logging interval.

[0036] FIG. 20 shows an example of a method for logging with partial time domain within reporting interval.

[0037] FIG. 21 shows an example of a method for logging with periodic reporting without logging interval.

[0038] FIG. 22 shows an example for data collection based on logging duration.

[0039] The following techniques, apparatuses, and systems may be applied to a variety of wireless multiple access systems. Examples of the multiple access systems include a code division multiple access (CDMA) system, a frequency division multiple access (FDMA) system, a time division multiple access (TDMA) system, an orthogonal frequency division multiple access (OFDMA) system, a single carrier frequency division multiple access (SC-FDMA) system, and a multicarrier frequency division multiple access (MC-FDMA) system. CDMA may be embodied through radio technology such as universal terrestrial radio access (UTRA) or CDMA2000. TDMA may be embodied through radio technology such as global system for mobile communications (GSM), general packet radio service (GPRS), or enhanced data rates for GSM evolution (EDGE). OFDMA may be embodied through radio technology such as institute of electrical and electronics engineers (IEEE) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, or evolved UTRA (E-UTRA). UTRA is a part of a universal mobile telecommunications system (UMTS). 3rd generation partnership project (3GPP) long term evolution (LTE) is a part of evolved UMTS (E-UMTS) using E-UTRA. 3GPP LTE employs OFDMA in DL and SC-FDMA in UL. LTE-advanced (LTE-A) is an evolved version of 3GPP LTE.

[0040] For convenience of description, implementations of the present disclosure are mainly described in regards to a 3GPP based wireless communication system. However, the technical features of the present disclosure are not limited thereto. For example, although the following detailed description is given based on a mobile communication system corresponding to a 3GPP based wireless communication system, aspects of the present disclosure that are not limited to 3GPP based wireless communication system are applicable to other mobile communication systems.

[0041] For terms and technologies which are not specifically described among the terms of and technologies employed in the present disclosure, the wireless communication standard documents published before the present disclosure may be referenced.

[0042] In the present disclosure, "A or B" may mean "only A", "only B", or "both A and B". In other words, "A or B" in the present disclosure may be interpreted as "A and / or B". For example, "A, B or C" in the present disclosure may mean "only A", "only B", "only C", or "any combination of A, B and C".

[0043] In the present disclosure, slash ( / ) or comma (,) may mean "and / or". For example, "A / B" may mean "A and / or B". Accordingly, "A / B" may mean "only A", "only B", or "both A and B". For example, "A, B, C" may mean "A, B or C".

[0044] In the present disclosure, "at least one of A and B" may mean "only A", "only B" or "both A and B". In addition, the expression "at least one of A or B" or "at least one of A and / or B" in the present disclosure may be interpreted as same as "at least one of A and B".

[0045] In addition, in the present disclosure, "at least one of A, B and C" may mean "only A", "only B", "only C", or "any combination of A, B and C". In addition, "at least one of A, B or C" or "at least one of A, B and / or C" may mean "at least one of A, B and C".

[0046] Also, parentheses used in the present disclosure may mean "for example". In detail, when it is shown as "control information (PDCCH)", "PDCCH" may be proposed as an example of "control information". In other words, "control information" in the present disclosure is not limited to "PDCCH", and "PDCCH" may be proposed as an example of "control information". In addition, even when shown as "control information (i.e., PDCCH)", "PDCCH" may be proposed as an example of "control information".

[0047] Technical features that are separately described in one drawing in the present disclosure may be implemented separately or simultaneously.

[0048] Although not limited thereto, various descriptions, functions, procedures, suggestions, methods and / or operational flowcharts of the present disclosure disclosed herein can be applied to various fields requiring wireless communication and / or connection (e.g., 5G) between devices.

[0049] Hereinafter, the present disclosure will be described in more detail with reference to drawings. The same reference numerals in the following drawings and / or descriptions may refer to the same and / or corresponding hardware blocks, software blocks, and / or functional blocks unless otherwise indicated.

[0050] FIG. 1 shows an example of a communication system to which implementations of the present disclosure is applied.

[0051] The 5G usage scenarios shown in FIG. 1 are only exemplary, and the technical features of the present disclosure can be applied to other 5G usage scenarios which are not shown in FIG. 1.

[0052] Three main requirement categories for 5G include (1) a category of enhanced mobile broadband (eMBB), (2) a category of massive machine type communication (mMTC), and (3) a category of ultra-reliable and low latency communications (URLLC).

[0053] Partial use cases may require a plurality of categories for optimization and other use cases may focus only upon one key performance indicator (KPI). 5G supports such various use cases using a flexible and reliable method.

[0054] eMBB far surpasses basic mobile Internet access and covers abundant bidirectional work and media and entertainment applications in cloud and augmented reality. Data is one of 5G core motive forces and, in a 5G era, a dedicated voice service may not be provided for the first time. In 5G, it is expected that voice will be simply processed as an application program using data connection provided by a communication system. Main causes for increased traffic volume are due to an increase in the size of content and an increase in the number of applications requiring high data transmission rate. A streaming service (of audio and video), conversational video, and mobile Internet access will be more widely used as more devices are connected to the Internet. These many application programs require connectivity of an always turned-on state in order to push real-time information and alarm for users. Cloud storage and applications are rapidly increasing in a mobile communication platform and may be applied to both work and entertainment. The cloud storage is a special use case which accelerates growth of uplink data transmission rate. 5G is also used for remote work of cloud. When a tactile interface is used, 5G demands much lower end-to-end latency to maintain user good experience. Entertainment, for example, cloud gaming and video streaming, is another core element which increases demand for mobile broadband capability. Entertainment is essential for a smartphone and a tablet in any place including high mobility environments such as a train, a vehicle, and an airplane. Other use cases are augmented reality for entertainment and information search. In this case, the augmented reality requires very low latency and instantaneous data volume.

[0055] In addition, one of the most expected 5G use cases relates a function capable of smoothly connecting embedded sensors in all fields, i.e., mMTC. It is expected that the number of potential Internet-of-things (IoT) devices will reach 204 hundred million up to the year of 2020. An industrial IoT is one of categories of performing a main role enabling a smart city, asset tracking, smart utility, agriculture, and security infrastructure through 5G.

[0056] URLLC includes a new service that will change industry through remote control of main infrastructure and an ultra-reliable / available low-latency link such as a self-driving vehicle. A level of reliability and latency is essential to control a smart grid, automatize industry, achieve robotics, and control and adjust a drone.

[0057] 5G is a means of providing streaming evaluated as a few hundred megabits per second to gigabits per second and may complement fiber-to-the-home (FTTH) and cable-based broadband (or DOCSIS). Such fast speed is needed to deliver TV in resolution of 4K or more (6K, 8K, and more), as well as virtual reality and augmented reality. Virtual reality (VR) and augmented reality (AR) applications include almost immersive sports games. A specific application program may require a special network configuration. For example, for VR games, gaming companies need to incorporate a core server into an edge network server of a network operator in order to minimize latency.

[0058] Automotive is expected to be a new important motivated force in 5G together with many use cases for mobile communication for vehicles. For example, entertainment for passengers requires high simultaneous capacity and mobile broadband with high mobility. This is because future users continue to expect connection of high quality regardless of their locations and speeds. Another use case of an automotive field is an AR dashboard. The AR dashboard causes a driver to identify an object in the dark in addition to an object seen from a front window and displays a distance from the object and a movement of the object by overlapping information talking to the driver. In the future, a wireless module enables communication between vehicles, information exchange between a vehicle and supporting infrastructure, and information exchange between a vehicle and other connected devices (e.g., devices accompanied by a pedestrian). A safety system guides alternative courses of a behavior so that a driver may drive more safely drive, thereby lowering the danger of an accident. The next stage will be a remotely controlled or self-driven vehicle. This requires very high reliability and very fast communication between different self-driven vehicles and between a vehicle and infrastructure. In the future, a self-driven vehicle will perform all driving activities and a driver will focus only upon abnormal traffic that the vehicle cannot identify. Technical requirements of a self-driven vehicle demand ultra-low latency and ultra-high reliability so that traffic safety is increased to a level that cannot be achieved by human being.

[0059] A smart city and a smart home / building mentioned as a smart society will be embedded in a high-density wireless sensor network. A distributed network of an intelligent sensor will identify conditions for costs and energy-efficient maintenance of a city or a home. Similar configurations may be performed for respective households. All of temperature sensors, window and heating controllers, burglar alarms, and home appliances are wirelessly connected. Many of these sensors are typically low in data transmission rate, power, and cost. However, real-time HD video may be demanded by a specific type of device to perform monitoring.

[0060] Consumption and distribution of energy including heat or gas is distributed at a higher level so that automated control of the distribution sensor network is demanded. The smart grid collects information and connects the sensors to each other using digital information and communication technology so as to act according to the collected information. Since this information may include behaviors of a supply company and a consumer, the smart grid may improve distribution of fuels such as electricity by a method having efficiency, reliability, economic feasibility, production sustainability, and automation. The smart grid may also be regarded as another sensor network having low latency.

[0061] Mission critical application (e.g., e-health) is one of 5G use scenarios. A health part contains many application programs capable of enjoying benefit of mobile communication. A communication system may support remote treatment that provides clinical treatment in a faraway place. Remote treatment may aid in reducing a barrier against distance and improve access to medical services that cannot be continuously available in a faraway rural area. Remote treatment is also used to perform important treatment and save lives in an emergency situation. The wireless sensor network based on mobile communication may provide remote monitoring and sensors for parameters such as heart rate and blood pressure.

[0062] Wireless and mobile communication gradually becomes important in the field of an industrial application. Wiring is high in installation and maintenance cost. Therefore, a possibility of replacing a cable with reconstructible wireless links is an attractive opportunity in many industrial fields. However, in order to achieve this replacement, it is necessary for wireless connection to be established with latency, reliability, and capacity similar to those of the cable and management of wireless connection needs to be simplified. Low latency and a very low error probability are new requirements when connection to 5G is needed.

[0063] Logistics and freight tracking are important use cases for mobile communication that enables inventory and package tracking anywhere using a location-based information system. The use cases of logistics and freight typically demand low data rate but require location information with a wide range and reliability.

[0064] Referring to FIG. 1, the communication system 1 includes wireless devices 100a to 100f, base stations (BSs) 200, and a network 300. Although FIG. 1 illustrates a 5G network as an example of the network of the communication system 1, the implementations of the present disclosure are not limited to the 5G system, and can be applied to the future communication system beyond the 5G system.

[0065] The BSs 200 and the network 300 may be implemented as wireless devices and a specific wireless device may operate as a BS / network node with respect to other wireless devices.

[0066] The wireless devices 100a to 100f represent devices performing communication using radio access technology (RAT) (e.g., 5G new RAT (NR)) or LTE) and may be referred to as communication / radio / 5G devices. The wireless devices 100a to 100f may include, without being limited to, a robot 100a, vehicles 100b-1 and 100b-2, an extended reality (XR) device 100c, a hand-held device 100d, a home appliance 100e, an IoT device 100f, and an artificial intelligence (AI) device / server 400. For example, the vehicles may include a vehicle having a wireless communication function, an autonomous driving vehicle, and a vehicle capable of performing communication between vehicles. The vehicles may include an unmanned aerial vehicle (UAV) (e.g., a drone). The XR device may include an AR / VR / Mixed Reality (MR) device and may be implemented in the form of a head-mounted device (HMD), a head-up display (HUD) mounted in a vehicle, a television, a smartphone, a computer, a wearable device, a home appliance device, a digital signage, a vehicle, a robot, etc. The hand-held device may include a smartphone, a smartpad, a wearable device (e.g., a smartwatch or a smartglasses), and a computer (e.g., a notebook). The home appliance may include a TV, a refrigerator, and a washing machine. The IoT device may include a sensor and a smartmeter.

[0067] In the present disclosure, the wireless devices 100a to 100f may be called user equipments (UEs). A UE may include, for example, a cellular phone, a smartphone, a laptop computer, a digital broadcast terminal, a personal digital assistant (PDA), a portable multimedia player (PMP), a navigation system, a slate personal computer (PC), a tablet PC, an ultrabook, a vehicle, a vehicle having an autonomous traveling function, a connected car, an UAV, an AI module, a robot, an AR device, a VR device, an MR device, a hologram device, a public safety device, an MTC device, an IoT device, a medical device, a FinTech device (or a financial device), a security device, a weather / environment device, a device related to a 5G service, or a device related to a fourth industrial revolution field.

[0068] The UAV may be, for example, an aircraft aviated by a wireless control signal without a human being onboard.

[0069] The VR device may include, for example, a device for implementing an object or a background of the virtual world. The AR device may include, for example, a device implemented by connecting an object or a background of the virtual world to an object or a background of the real world. The MR device may include, for example, a device implemented by merging an object or a background of the virtual world into an object or a background of the real world. The hologram device may include, for example, a device for implementing a stereoscopic image of 360 degrees by recording and reproducing stereoscopic information, using an interference phenomenon of light generated when two laser lights called holography meet.

[0070] The public safety device may include, for example, an image relay device or an image device that is wearable on the body of a user.

[0071] The MTC device and the IoT device may be, for example, devices that do not require direct human intervention or manipulation. For example, the MTC device and the IoT device may include smartmeters, vending machines, thermometers, smartbulbs, door locks, or various sensors.

[0072] The medical device may be, for example, a device used for the purpose of diagnosing, treating, relieving, curing, or preventing disease. For example, the medical device may be a device used for the purpose of diagnosing, treating, relieving, or correcting injury or impairment. For example, the medical device may be a device used for the purpose of inspecting, replacing, or modifying a structure or a function. For example, the medical device may be a device used for the purpose of adjusting pregnancy. For example, the medical device may include a device for treatment, a device for operation, a device for (in vitro) diagnosis, a hearing aid, or a device for procedure.

[0073] The security device may be, for example, a device installed to prevent a danger that may arise and to maintain safety. For example, the security device may be a camera, a closed-circuit TV (CCTV), a recorder, or a black box.

[0074] The FinTech device may be, for example, a device capable of providing a financial service such as mobile payment. For example, the FinTech device may include a payment device or a point of sales (POS) system.

[0075] The weather / environment device may include, for example, a device for monitoring or predicting a weather / environment.

[0076] The wireless devices 100a to 100f may be connected to the network 300 via the BSs 200. An AI technology may be applied to the wireless devices 100a to 100f and the wireless devices 100a to 100f may be connected to the AI server 400 via the network 300. The network 300 may be configured using a 3G network, a 4G (e.g., LTE) network, a 5G (e.g., NR) network, and a beyond-5G network. Although the wireless devices 100a to 100f may communicate with each other through the BSs 200 / network 300, the wireless devices 100a to 100f may perform direct communication (e.g., sidelink communication) with each other without passing through the BSs 200 / network 300. For example, the vehicles 100b-1 and 100b-2 may perform direct communication (e.g., vehicle-to-vehicle (V2V) / vehicle-to-everything (V2X) communication). The IoT device (e.g., a sensor) may perform direct communication with other IoT devices (e.g., sensors) or other wireless devices 100a to 100f.

[0077] Wireless communication / connections 150a, 150b and 150c may be established between the wireless devices 100a to 100f and / or between wireless device 100a to 100f and BS 200 and / or between BSs 200. Herein, the wireless communication / connections may be established through various RATs (e.g., 5G NR) such as uplink / downlink communication 150a, sidelink communication (or device-to-device (D2D) communication) 150b, inter-base station communication 150c (e.g., relay, integrated access and backhaul (IAB)), etc. The wireless devices 100a to 100f and the BSs 200 / the wireless devices 100a to 100f may transmit / receive radio signals to / from each other through the wireless communication / connections 150a, 150b and 150c. For example, the wireless communication / connections 150a, 150b and 150c may transmit / receive signals through various physical channels. To this end, at least a part of various configuration information configuring processes, various signal processing processes (e.g., channel encoding / decoding, modulation / demodulation, and resource mapping / de-mapping), and resource allocating processes, for transmitting / receiving radio signals, may be performed based on the various proposals of the present disclosure.

[0078] Here, the radio communication technologies implemented in the wireless devices in the present disclosure may include narrowband internet-of-things (NB-IoT) technology for low-power communication as well as LTE, NR and 6G. For example, NB-IoT technology may be an example of low power wide area network (LPWAN) technology, may be implemented in specifications such as LTE Cat NB1 and / or LTE Cat NB2, and may not be limited to the above-mentioned names. Additionally and / or alternatively, the radio communication technologies implemented in the wireless devices in the present disclosure may communicate based on LTE-M technology. For example, LTE-M technology may be an example of LPWAN technology and be called by various names such as enhanced machine type communication (eMTC). For example, LTE-M technology may be implemented in at least one of the various specifications, such as 1) LTE Cat 0, 2) LTE Cat M1, 3) LTE Cat M2, 4) LTE non-bandwidth limited (non-BL), 5) LTE-MTC, 6) LTE Machine Type Communication, and / or 7) LTE M, and may not be limited to the above-mentioned names. Additionally and / or alternatively, the radio communication technologies implemented in the wireless devices in the present disclosure may include at least one of ZigBee, Bluetooth, and / or LPWAN which take into account low-power communication, and may not be limited to the above-mentioned names. For example, ZigBee technology may generate personal area networks (PANs) associated with small / low-power digital communication based on various specifications such as IEEE 802.15.4 and may be called various names.

[0079] FIG. 2 shows an example of wireless devices to which implementations of the present disclosure is applied.

[0080] Referring to FIG. 2, a first wireless device 100 and a second wireless device 200 may transmit / receive radio signals to / from an external device through a variety of RATs (e.g., LTE and NR). In FIG. 2, {the first wireless device 100 and the second wireless device 200} may correspond to at least one of {the wireless device 100a to 100f and the BS 200}, {the wireless device 100a to 100f and the wireless device 100a to 100f} and / or {the BS 200 and the BS 200} of FIG. 1.

[0081] The first wireless device 100 may include one or more processors 102 and one or more memories 104 and additionally further include one or more transceivers 106 and / or one or more antennas 108. The processor(s) 102 may control the memory(s) 104 and / or the transceiver(s) 106 and may be configured to implement the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts described in the present disclosure. For example, the processor(s) 102 may process information within the memory(s) 104 to generate first information / signals and then transmit radio signals including the first information / signals through the transceiver(s) 106. The processor(s) 102 may receive radio signals including second information / signals through the transceiver(s) 106 and then store information obtained by processing the second information / signals in the memory(s) 104. The memory(s) 104 may be connected to the processor(s) 102 and may store a variety of information related to operations of the processor(s) 102. For example, the memory(s) 104 may store software code including commands for performing a part or the entirety of processes controlled by the processor(s) 102 or for performing the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts described in the present disclosure. Herein, the processor(s) 102 and the memory(s) 104 may be a part of a communication modem / circuit / chip designed to implement RAT (e.g., LTE or NR). The transceiver(s) 106 may be connected to the processor(s) 102 and transmit and / or receive radio signals through one or more antennas 108. Each of the transceiver(s) 106 may include a transmitter and / or a receiver. The transceiver(s) 106 may be interchangeably used with radio frequency (RF) unit(s). In the present disclosure, the first wireless device 100 may represent a communication modem / circuit / chip.

[0082] The second wireless device 200 may include one or more processors 202 and one or more memories 204 and additionally further include one or more transceivers 206 and / or one or more antennas 208. The processor(s) 202 may control the memory(s) 204 and / or the transceiver(s) 206 and may be configured to implement the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts described in the present disclosure. For example, the processor(s) 202 may process information within the memory(s) 204 to generate third information / signals and then transmit radio signals including the third information / signals through the transceiver(s) 206. The processor(s) 202 may receive radio signals including fourth information / signals through the transceiver(s) 106 and then store information obtained by processing the fourth information / signals in the memory(s) 204. The memory(s) 204 may be connected to the processor(s) 202 and may store a variety of information related to operations of the processor(s) 202. For example, the memory(s) 204 may store software code including commands for performing a part or the entirety of processes controlled by the processor(s) 202 or for performing the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts described in the present disclosure. Herein, the processor(s) 202 and the memory(s) 204 may be a part of a communication modem / circuit / chip designed to implement RAT (e.g., LTE or NR). The transceiver(s) 206 may be connected to the processor(s) 202 and transmit and / or receive radio signals through one or more antennas 208. Each of the transceiver(s) 206 may include a transmitter and / or a receiver. The transceiver(s) 206 may be interchangeably used with RF unit(s). In the present disclosure, the second wireless device 200 may represent a communication modem / circuit / chip.

[0083] Hereinafter, hardware elements of the wireless devices 100 and 200 will be described more specifically. One or more protocol layers may be implemented by, without being limited to, one or more processors 102 and 202. For example, the one or more processors 102 and 202 may implement one or more layers (e.g., functional layers such as physical (PHY) layer, media access control (MAC) layer, radio link control (RLC) layer, packet data convergence protocol (PDCP) layer, radio resource control (RRC) layer, and service data adaptation protocol (SDAP) layer). The one or more processors 102 and 202 may generate one or more protocol data units (PDUs) and / or one or more service data unit (SDUs) according to the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure. The one or more processors 102 and 202 may generate messages, control information, data, or information according to the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure. The one or more processors 102 and 202 may generate signals (e.g., baseband signals) including PDUs, SDUs, messages, control information, data, or information according to the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure and provide the generated signals to the one or more transceivers 106 and 206. The one or more processors 102 and 202 may receive the signals (e.g., baseband signals) from the one or more transceivers 106 and 206 and acquire the PDUs, SDUs, messages, control information, data, or information according to the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure.

[0084] The one or more processors 102 and 202 may be referred to as controllers, microcontrollers, microprocessors, or microcomputers. The one or more processors 102 and 202 may be implemented by hardware, firmware, software, or a combination thereof. As an example, one or more application specific integrated circuits (ASICs), one or more digital signal processors (DSPs), one or more digital signal processing devices (DSPDs), one or more programmable logic devices (PLDs), or one or more field programmable gate arrays (FPGAs) may be included in the one or more processors 102 and 202. descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure may be implemented using firmware or software and the firmware or software may be configured to include the modules, procedures, or functions. Firmware or software configured to perform the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure may be included in the one or more processors 102 and 202 or stored in the one or more memories 104 and 204 so as to be driven by the one or more processors 102 and 202. The descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure may be implemented using firmware or software in the form of code, commands, and / or a set of commands.

[0085] The one or more memories 104 and 204 may be connected to the one or more processors 102 and 202 and store various types of data, signals, messages, information, programs, code, instructions, and / or commands. The one or more memories 104 and 204 may be configured by read-only memories (ROMs), random access memories (RAMs), electrically erasable programmable read-only memories (EPROMs), flash memories, hard drives, registers, cash memories, computer-readable storage media, and / or combinations thereof. The one or more memories 104 and 204 may be located at the interior and / or exterior of the one or more processors 102 and 202. The one or more memories 104 and 204 may be connected to the one or more processors 102 and 202 through various technologies such as wired or wireless connection.

[0086] The one or more transceivers 106 and 206 may transmit user data, control information, and / or radio signals / channels, mentioned in the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure, to one or more other devices. The one or more transceivers 106 and 206 may receive user data, control information, and / or radio signals / channels, mentioned in the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure, from one or more other devices. For example, the one or more transceivers 106 and 206 may be connected to the one or more processors 102 and 202 and transmit and receive radio signals. For example, the one or more processors 102 and 202 may perform control so that the one or more transceivers 106 and 206 may transmit user data, control information, or radio signals to one or more other devices. The one or more processors 102 and 202 may perform control so that the one or more transceivers 106 and 206 may receive user data, control information, or radio signals from one or more other devices.

[0087] The one or more transceivers 106 and 206 may be connected to the one or more antennas 108 and 208 and the one or more transceivers 106 and 206 may be configured to transmit and receive user data, control information, and / or radio signals / channels, mentioned in the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure, through the one or more antennas 108 and 208. In the present disclosure, the one or more antennas may be a plurality of physical antennas or a plurality of logical antennas (e.g., antenna ports).

[0088] The one or more transceivers 106 and 206 may convert received radio signals / channels, etc., from RF band signals into baseband signals in order to process received user data, control information, radio signals / channels, etc., using the one or more processors 102 and 202. The one or more transceivers 106 and 206 may convert the user data, control information, radio signals / channels, etc., processed using the one or more processors 102 and 202 from the base band signals into the RF band signals. To this end, the one or more transceivers 106 and 206 may include (analog) oscillators and / or filters. For example, the transceivers 106 and 206 can up-convert OFDM baseband signals to a carrier frequency by their (analog) oscillators and / or filters under the control of the processors 102 and 202 and transmit the up-converted OFDM signals at the carrier frequency. The transceivers 106 and 206 may receive OFDM signals at a carrier frequency and down-convert the OFDM signals into OFDM baseband signals by their (analog) oscillators and / or filters under the control of the transceivers 102 and 202.

[0089] In the implementations of the present disclosure, a UE may operate as a transmitting device in uplink (UL) and as a receiving device in downlink (DL). In the implementations of the present disclosure, a BS may operate as a receiving device in UL and as a transmitting device in DL. Hereinafter, for convenience of description, it is mainly assumed that the first wireless device 100 acts as the UE, and the second wireless device 200 acts as the BS. For example, the processor(s) 102 connected to, mounted on or launched in the first wireless device 100 may be configured to perform the UE behavior according to an implementation of the present disclosure or control the transceiver(s) 106 to perform the UE behavior according to an implementation of the present disclosure. The processor(s) 202 connected to, mounted on or launched in the second wireless device 200 may be configured to perform the BS behavior according to an implementation of the present disclosure or control the transceiver(s) 206 to perform the BS behavior according to an implementation of the present disclosure.

[0090] In the present disclosure, a BS is also referred to as a node B (NB), an eNode B (eNB), or a gNB.

[0091] FIG. 3 shows an example of a wireless device to which implementations of the present disclosure is applied.

[0092] The wireless device may be implemented in various forms according to a use-case / service (refer to FIG. 1).

[0093] Referring to FIG. 3, wireless devices 100 and 200 may correspond to the wireless devices 100 and 200 of FIG. 2 and may be configured by various elements, components, units / portions, and / or modules. For example, each of the wireless devices 100 and 200 may include a communication unit 110, a control unit 120, a memory unit 130, and additional components 140. The communication unit 110 may include a communication circuit 112 and transceiver(s) 114. For example, the communication circuit 112 may include the one or more processors 102 and 202 of FIG. 2 and / or the one or more memories 104 and 204 of FIG. 2. For example, the transceiver(s) 114 may include the one or more transceivers 106 and 206 of FIG. 2 and / or the one or more antennas 108 and 208 of FIG. 2. The control unit 120 is electrically connected to the communication unit 110, the memory 130, and the additional components 140 and controls overall operation of each of the wireless devices 100 and 200. For example, the control unit 120 may control an electric / mechanical operation of each of the wireless devices 100 and 200 based on programs / code / commands / information stored in the memory unit 130. The control unit 120 may transmit the information stored in the memory unit 130 to the exterior (e.g., other communication devices) via the communication unit 110 through a wireless / wired interface or store, in the memory unit 130, information received through the wireless / wired interface from the exterior (e.g., other communication devices) via the communication unit 110.

[0094] The additional components 140 may be variously configured according to types of the wireless devices 100 and 200. For example, the additional components 140 may include at least one of a power unit / battery, input / output (I / O) unit (e.g., audio I / O port, video I / O port), a driving unit, and a computing unit. The wireless devices 100 and 200 may be implemented in the form of, without being limited to, the robot (100a of FIG. 1), the vehicles (100b-1 and 100b-2 of FIG. 1), the XR device (100c of FIG. 1), the hand-held device (100d of FIG. 1), the home appliance (100e of FIG. 1), the IoT device (100f of FIG. 1), a digital broadcast terminal, a hologram device, a public safety device, an MTC device, a medicine device, a FinTech device (or a finance device), a security device, a climate / environment device, the AI server / device (400 of FIG. 1), the BSs (200 of FIG. 1), a network node, etc. The wireless devices 100 and 200 may be used in a mobile or fixed place according to a use-example / service.

[0095] In FIG. 3, the entirety of the various elements, components, units / portions, and / or modules in the wireless devices 100 and 200 may be connected to each other through a wired interface or at least a part thereof may be wirelessly connected through the communication unit 110. For example, in each of the wireless devices 100 and 200, the control unit 120 and the communication unit 110 may be connected by wire and the control unit 120 and first units (e.g., 130 and 140) may be wirelessly connected through the communication unit 110. Each element, component, unit / portion, and / or module within the wireless devices 100 and 200 may further include one or more elements. For example, the control unit 120 may be configured by a set of one or more processors. As an example, the control unit 120 may be configured by a set of a communication control processor, an application processor (AP), an electronic control unit (ECU), a graphical processing unit, and a memory control processor. As another example, the memory 130 may be configured by a RAM, a DRAM, a ROM, a flash memory, a volatile memory, a non-volatile memory, and / or a combination thereof.

[0096] FIG. 4 shows another example of wireless devices to which implementations of the present disclosure is applied.

[0097] Referring to FIG. 4, wireless devices 100 and 200 may correspond to the wireless devices 100 and 200 of FIG. 2 and may be configured by various elements, components, units / portions, and / or modules.

[0098] The first wireless device 100 may include at least one transceiver, such as a transceiver 106, and at least one processing chip, such as a processing chip 101. The processing chip 101 may include at least one processor, such a processor 102, and at least one memory, such as a memory 104. The memory 104 may be operably connectable to the processor 102. The memory 104 may store various types of information and / or instructions. The memory 104 may store a software code 105 which implements instructions that, when executed by the processor 102, perform the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure. For example, the software code 105 may implement instructions that, when executed by the processor 102, perform the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure. For example, the software code 105 may control the processor 102 to perform one or more protocols. For example, the software code 105 may control the processor 102 may perform one or more layers of the radio interface protocol.

[0099] The second wireless device 200 may include at least one transceiver, such as a transceiver 206, and at least one processing chip, such as a processing chip 201. The processing chip 201 may include at least one processor, such a processor 202, and at least one memory, such as a memory 204. The memory 204 may be operably connectable to the processor 202. The memory 204 may store various types of information and / or instructions. The memory 204 may store a software code 205 which implements instructions that, when executed by the processor 202, perform the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure. For example, the software code 205 may implement instructions that, when executed by the processor 202, perform the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure. For example, the software code 205 may control the processor 202 to perform one or more protocols. For example, the software code 205 may control the processor 202 may perform one or more layers of the radio interface protocol.

[0100] FIG. 5 shows an example of UE to which implementations of the present disclosure is applied.

[0101] Referring to FIG. 5, a UE 100 may correspond to the first wireless device 100 of FIG. 2 and / or the first wireless device 100 of FIG. 4.

[0102] A UE 100 includes a processor 102, a memory 104, a transceiver 106, one or more antennas 108, a power management module 110, a battery 1112, a display 114, a keypad 116, a subscriber identification module (SIM) card 118, a speaker 120, and a microphone 122.

[0103] The processor 102 may be configured to implement the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure. The processor 102 may be configured to control one or more other components of the UE 100 to implement the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure. Layers of the radio interface protocol may be implemented in the processor 102. The processor 102 may include ASIC, other chipset, logic circuit and / or data processing device. The processor 102 may be an application processor. The processor 102 may include at least one of a digital signal processor (DSP), a central processing unit (CPU), a graphics processing unit (GPU), a modem (modulator and demodulator). An example of the processor 102 may be found in SNAPDRAGONTMseries of processors made by Qualcomm®, EXYNOSTMseries of processors made by Samsung®, A series of processors made by Apple®, HELIOTMseries of processors made by MediaTek®, ATOMTMseries of processors made by Intel®or a corresponding next generation processor.

[0104] The memory 104 is operatively coupled with the processor 102 and stores a variety of information to operate the processor 102. The memory 104 may include ROM, RAM, flash memory, memory card, storage medium and / or other storage device. When the embodiments are implemented in software, the techniques described herein can be implemented with modules (e.g., procedures, functions, etc.) that perform the descriptions, functions, procedures, suggestions, methods and / or operational flowcharts disclosed in the present disclosure. The modules can be stored in the memory 104 and executed by the processor 102. The memory 104 can be implemented within the processor 102 or external to the processor 102 in which case those can be communicatively coupled to the processor 102 via various means as is known in the art.

[0105] The transceiver 106 is operatively coupled with the processor 102, and transmits and / or receives a radio signal. The transceiver 106 includes a transmitter and a receiver. The transceiver 106 may include baseband circuitry to process radio frequency signals. The transceiver 106 controls the one or more antennas 108 to transmit and / or receive a radio signal.

[0106] The power management module 110 manages power for the processor 102 and / or the transceiver 106. The battery 112 supplies power to the power management module 110.

[0107] The display 114 outputs results processed by the processor 102. The keypad 116 receives inputs to be used by the processor 102. The keypad 16 may be shown on the display 114.

[0108] The SIM card 118 is an　integrated circuit　that is intended to　securely store the　international mobile subscriber identity　(IMSI) number and its related　key, which are used to identify and authenticate subscribers on　mobile telephony　devices (such as　mobile phones　and　computers). It is also possible to store contact information on many SIM cards.

[0109] The speaker 120 outputs sound-related results processed by the processor 102. The microphone 122 receives sound-related inputs to be used by the processor 102.

[0110] FIGS. 6 and 7 show an example of protocol stacks in a 3GPP based wireless communication system to which implementations of the present disclosure is applied.

[0111] In particular, FIG. 6 illustrates an example of a radio interface user plane protocol stack between a UE and a BS and FIG. 7 illustrates an example of a radio interface control plane protocol stack between a UE and a BS. The control plane refers to a path through which control messages used to manage call by a UE and a network are transported. The user plane refers to a path through which data generated in an application layer, for example, voice data or Internet packet data are transported. Referring to FIG. 6, the user plane protocol stack may be divided into Layer 1 (i.e., a PHY layer) and Layer 2. Referring to FIG. 7, the control plane protocol stack may be divided into Layer 1 (i.e., a PHY layer), Layer 2, Layer 3 (e.g., an RRC layer), and a non-access stratum (NAS) layer. Layer 1, Layer 2 and Layer 3 are referred to as an access stratum (AS).

[0112] In the 3GPP LTE system, the Layer 2 is split into the following sublayers: MAC, RLC, and PDCP. In the 3GPP NR system, the Layer 2 is split into the following sublayers: MAC, RLC, PDCP and SDAP. The PHY layer offers to the MAC sublayer transport channels, the MAC sublayer offers to the RLC sublayer logical channels, the RLC sublayer offers to the PDCP sublayer RLC channels, the PDCP sublayer offers to the SDAP sublayer radio bearers. The SDAP sublayer offers to 5G core network quality of service (QoS) flows.

[0113] In the 3GPP NR system, the main services and functions of the MAC sublayer include: mapping between logical channels and transport channels; multiplexing / de-multiplexing of MAC SDUs belonging to one or different logical channels into / from transport blocks (TB) delivered to / from the physical layer on transport channels; scheduling information reporting; error correction through hybrid automatic repeat request (HARQ) (one HARQ entity per cell in case of carrier aggregation (CA)); priority handling between UEs by means of dynamic scheduling; priority handling between logical channels of one UE by means of logical channel prioritization; padding. A single MAC entity may support multiple numerologies, transmission timings and cells. Mapping restrictions in logical channel prioritization control which numerology(ies), cell(s), and transmission timing(s) a logical channel can use.

[0114] Different kinds of data transfer services are offered by MAC. To accommodate different kinds of data transfer services, multiple types of logical channels are defined, i.e., each supporting transfer of a particular type of information. Each logical channel type is defined by what type of information is transferred. Logical channels are classified into two groups: control channels and traffic channels. Control channels are used for the transfer of control plane information only, and traffic channels are used for the transfer of user plane information only. Broadcast control channel (BCCH) is a downlink logical channel for broadcasting system control information, paging control channel (PCCH) is a downlink logical channel that transfers paging information, system information change notifications and indications of ongoing public warning service (PWS) broadcasts, common control channel (CCCH) is a logical channel for transmitting control information between UEs and network and used for UEs having no RRC connection with the network, and dedicated control channel (DCCH) is a point-to-point bi-directional logical channel that transmits dedicated control information between a UE and the network and used by UEs having an RRC connection. Dedicated traffic channel (DTCH) is a point-to-point logical channel, dedicated to one UE, for the transfer of user information. A DTCH can exist in both uplink and downlink. In downlink, the following connections between logical channels and transport channels exist: BCCH can be mapped to broadcast channel (BCH); BCCH can be mapped to downlink shared channel (DL-SCH); PCCH can be mapped to paging channel (PCH); CCCH can be mapped to DL-SCH; DCCH can be mapped to DL-SCH; and DTCH can be mapped to DL-SCH. In uplink, the following connections between logical channels and transport channels exist: CCCH can be mapped to uplink shared channel (UL-SCH); DCCH can be mapped to UL-SCH; and DTCH can be mapped to UL-SCH.

[0115] The RLC sublayer supports three transmission modes: transparent mode (TM), unacknowledged mode (UM), and acknowledged node (AM). The RLC configuration is per logical channel with no dependency on numerologies and / or transmission durations. In the 3GPP NR system, the main services and functions of the RLC sublayer depend on the transmission mode and include: transfer of upper layer PDUs; sequence numbering independent of the one in PDCP (UM and AM); error correction through ARQ (AM only); segmentation (AM and UM) and re-segmentation (AM only) of RLC SDUs; reassembly of SDU (AM and UM); duplicate detection (AM only); RLC SDU discard (AM and UM); RLC re-establishment; protocol error detection (AM only).

[0116] In the 3GPP NR system, the main services and functions of the PDCP sublayer for the user plane include: sequence numbering; header compression and decompression using robust header compression (ROHC); transfer of user data; reordering and duplicate detection; in-order delivery; PDCP PDU routing (in case of split bearers); retransmission of PDCP SDUs; ciphering, deciphering and integrity protection; PDCP SDU discard; PDCP re-establishment and data recovery for RLC AM; PDCP status reporting for RLC AM; duplication of PDCP PDUs and duplicate discard indication to lower layers. The main services and functions of the PDCP sublayer for the control plane include: sequence numbering; ciphering, deciphering and integrity protection; transfer of control plane data; reordering and duplicate detection; in-order delivery; duplication of PDCP PDUs and duplicate discard indication to lower layers.

[0117] In the 3GPP NR system, the main services and functions of SDAP include: mapping between a QoS flow and a data radio bearer; marking QoS flow ID (QFI) in both DL and UL packets. A single protocol entity of SDAP is configured for each individual PDU session.

[0118] In the 3GPP NR system, the main services and functions of the RRC sublayer include: broadcast of system information related to AS and NAS; paging initiated by 5GC or NG-RAN; establishment, maintenance and release of an RRC connection between the UE and NG-RAN; security functions including key management; establishment, configuration, maintenance and release of signaling radio bearers (SRBs) and data radio bearers (DRBs); mobility functions (including: handover and context transfer, UE cell selection and reselection and control of cell selection and reselection, inter-RAT mobility); QoS management functions; UE measurement reporting and control of the reporting; detection of and recovery from radio link failure; NAS message transfer to / from NAS from / to UE.

[0119] FIG. 8 shows a frame structure in a 3GPP based wireless communication system to which implementations of the present disclosure is applied.

[0120] The frame structure shown in FIG. 8 is purely exemplary and the number of subframes, the number of slots, and / or the number of symbols in a frame may be variously changed. In the 3GPP based wireless communication system, OFDM numerologies (e.g., subcarrier spacing (SCS), transmission time interval (TTI) duration) may be differently configured between a plurality of cells aggregated for one UE. For example, if a UE is configured with different SCSs for cells aggregated for the cell, an (absolute time) duration of a time resource (e.g., a subframe, a slot, or a TTI) including the same number of symbols may be different among the aggregated cells. Herein, symbols may include OFDM symbols (or CP-OFDM symbols), SC-FDMA symbols (or discrete Fourier transform-spread-OFDM (DFT-s-OFDM) symbols).

[0121] Referring to FIG. 8, downlink and uplink transmissions are organized into frames. Each frame has Tf= 10ms duration. Each frame is divided into two half-frames, where each of the half-frames has 5ms duration. Each half-frame consists of 5 subframes, where the duration Tsfper subframe is 1ms. Each subframe is divided into slots and the number of slots in a subframe depends on a subcarrier spacing. Each slot includes 14 or 12 OFDM symbols based on a cyclic prefix (CP). In a normal CP, each slot includes 14 OFDM symbols and, in an extended CP, each slot includes 12 OFDM symbols. The numerology is based on exponentially scalable subcarrier spacing △f = 2u*15 kHz.

[0122] Table 1 shows the number of OFDM symbols per slot Nslotsymb, the number of slots per frameNframe,uslot, and the number of slots per subframe Nsubframe,uslotfor the normal CP, according to the subcarrier spacing △f = 2u*15 kHz.

[0123] uNslotsymbNframe,uslotNsubframe,uslot01410111420221440431480841416016

[0124] Table 2 shows the number of OFDM symbols per slot Nslotsymb, the number of slots per frameNframe,uslot, and the number of slots per subframe Nsubframe,uslotfor the extended CP, according to the subcarrier spacing △f = 2u*15 kHz.

[0125] uNslotsymbNframe,uslotNsubframe,uslot212404

[0126] A slot includes plural symbols (e.g., 14 or 12 symbols) in the time domain. For each numerology (e.g., subcarrier spacing) and carrier, a resource grid ofNsize,ugrid,x*NRBscsubcarriers andNsubframe,usymbOFDM symbols is defined, starting at common resource block (CRB)Nstart,ugridindicated by higher-layer signaling (e.g., RRC signaling), whereNsize,ugrid,xis the number of resource blocks (RBs) in the resource grid and the subscript x is DL for downlink and UL for uplink.NRBscis the number of subcarriers per RB. In the 3GPP based wireless communication system,NRBscis 12 generally. There is one resource grid for a given antenna portp, subcarrier spacing configurationu, and transmission direction (DL or UL). The carrier bandwidthNsize,ugridfor subcarrier spacing configurationuis given by the higher-layer parameter (e.g., RRC parameter). Each element in the resource grid for the antenna portpand the subcarrier spacing configurationuis referred to as a resource element (RE) and one complex symbol may be mapped to each RE. Each RE in the resource grid is uniquely identified by an indexkin the frequency domain and an indexlrepresenting a symbol location relative to a reference point in the time domain. In the 3GPP based wireless communication system, an RB is defined by 12 consecutive subcarriers in the frequency domain.

[0127] In the 3GPP NR system, RBs are classified into CRBs and physical resource blocks (PRBs). CRBs are numbered from 0 and upwards in the frequency domain for subcarrier spacing configurationu. The center of subcarrier 0 of CRB 0 for subcarrier spacing configurationucoincides with 'point A' which serves as a common reference point for resource block grids. In the 3GPP NR system, PRBs are defined within a bandwidth part (BWP) and numbered from 0 toNsizeBWP,i-1, where i is the number of the bandwidth part. The relation between the physical resource block nPRBin the bandwidth part i and the common resource block nCRBis as follows: nPRB= nCRB+NsizeBWP,i, whereNsizeBWP,iis the common resource block where bandwidth part starts relative to CRB 0. The BWP includes a plurality of consecutive RBs. A carrier may include a maximum of N (e.g., 5) BWPs. A UE may be configured with one or more BWPs on a given component carrier. Only one BWP among BWPs configured to the UE can active at a time. The active BWP defines the UE's operating bandwidth within the cell's operating bandwidth.

[0128] The NR frequency band may be defined as two types of frequency range, i.e., FR1 and FR2. The numerical value of the frequency range may be changed. For example, the frequency ranges of the two types (FR1 and FR2) may be as shown in Table 3 below. For ease of explanation, in the frequency ranges used in the NR system, FR1 may mean "sub 6 GHz range", FR2 may mean "above 6 GHz range," and may be referred to as millimeter wave (mmW).

[0129] Frequency Range designationCorresponding frequency rangeSubcarrier SpacingFR1450MHz - 6000MHz15, 30, 60kHzFR224250MHz - 52600MHz60, 120, 240kHz

[0130] As mentioned above, the numerical value of the frequency range of the NR system may be changed. For example, FR1 may include a frequency band of 410MHz to 7125MHz as shown in Table 4 below. That is, FR1 may include a frequency band of 6GHz (or 5850, 5900, 5925 MHz, etc.) or more. For example, a frequency band of 6 GHz (or 5850, 5900, 5925 MHz, etc.) or more included in FR1 may include an unlicensed band. Unlicensed bands may be used for a variety of purposes, for example for communication for vehicles (e.g., autonomous driving).

[0131] Frequency Range designationCorresponding frequency rangeSubcarrier SpacingFR1410MHz - 7125MHz15, 30, 60kHzFR224250MHz - 52600MHz60, 120, 240kHz

[0132] In the present disclosure, the term "cell" may refer to a geographic area to which one or more nodes provide a communication system, or refer to radio resources. A "cell" as a geographic area may be understood as coverage within which a node can provide service using a carrier and a "cell" as radio resources (e.g., time-frequency resources) is associated with bandwidth which is a frequency range configured by the carrier. The "cell" associated with the radio resources is defined by a combination of downlink resources and uplink resources, for example, a combination of a DL component carrier (CC) and a UL CC. The cell may be configured by downlink resources only, or may be configured by downlink resources and uplink resources. Since DL coverage, which is a range within which the node is capable of transmitting a valid signal, and UL coverage, which is a range within which the node is capable of receiving the valid signal from the UE, depends upon a carrier carrying the signal, the coverage of the node may be associated with coverage of the "cell" of radio resources used by the node. Accordingly, the term "cell" may be used to represent service coverage of the node sometimes, radio resources at other times, or a range that signals using the radio resources can reach with valid strength at other times.

[0133] In CA, two or more CCs are aggregated. A UE may simultaneously receive or transmit on one or multiple CCs depending on its capabilities. CA is supported for both contiguous and non-contiguous CCs. When CA is configured, the UE only has one RRC connection with the network. At RRC connection establishment / re-establishment / handover, one serving cell provides the NAS mobility information, and at RRC connection re-establishment / handover, one serving cell provides the security input. This cell is referred to as the primary cell (PCell). The PCell is a cell, operating on the primary frequency, in which the UE either performs the initial connection establishment procedure or initiates the connection re-establishment procedure. Depending on UE capabilities, secondary cells (SCells) can be configured to form together with the PCell a set of serving cells. An SCell is a cell providing additional radio resources on top of special cell (SpCell). The configured set of serving cells for a UE therefore always consists of one PCell and one or more SCells. For dual connectivity (DC) operation, the term SpCell refers to the PCell of the master cell group (MCG) or the primary SCell (PSCell) of the secondary cell group (SCG). An SpCell supports PUCCH transmission and contention-based random access, and is always activated. The MCG is a group of serving cells associated with a master node, comprised of the SpCell (PCell) and optionally one or more SCells. The SCG is the subset of serving cells associated with a secondary node, comprised of the PSCell and zero or more SCells, for a UE configured with DC. For a UE in RRC_CONNECTED not configured with CA / DC, there is only one serving cell comprised of the PCell. For a UE in RRC_CONNECTED configured with CA / DC, the term "serving cells" is used to denote the set of cells comprised of the SpCell(s) and all SCells. In DC, two MAC entities are configured in a UE: one for the MCG and one for the SCG.

[0134] FIG. 9 shows a data flow example in the 3GPP NR system to which implementations of the present disclosure is applied.

[0135] Referring to FIG. 9, "RB" denotes a radio bearer, and "H" denotes a header. Radio bearers are categorized into two groups: DRBs for user plane data and SRBs for control plane data. The MAC PDU is transmitted / received using radio resources through the PHY layer to / from an external device. The MAC PDU arrives to the PHY layer in the form of a transport block.

[0136] In the PHY layer, the uplink transport channels UL-SCH and RACH are mapped to their physical channels PUSCH and PRACH, respectively, and the downlink transport channels DL-SCH, BCH and PCH are mapped to PDSCH, PBCH and PDSCH, respectively. In the PHY layer, uplink control information (UCI) is mapped to PUCCH, and downlink control information (DCI) is mapped to PDCCH. A MAC PDU related to UL-SCH is transmitted by a UE via a PUSCH based on an UL grant, and a MAC PDU related to DL-SCH is transmitted by a BS via a PDSCH based on a DL assignment.

[0137] Hereinafter, technical features related to AI / ML are described.

[0138] The application of AI / ML to wireless communications has been thus far limited to implementation-based approaches, both, at the network and the UE sides. A study on enhancement for data collection for NR and ENDC (FS_NR_ENDC_data_collect) has examined thefunctional framework for RAN intelligence enabled by further enhancement of data collection through use cases, examples etc. and identify the potential standardization impacts on currentNG-RAN nodes and interfaces. In SA WG2 AI / ML related study, a network functionality NWDAF (Network Data Analytics Function) was introduced in Rel-15 and has been enhanced in Rel-16 and Rel-17.

[0139] In this study, we explore the benefits of augmenting the air-interface with features enabling improved support of AI / ML based algorithms for enhanced performance and / or reduced complexity / overhead. Enhanced performance here depends on the use cases under consideration and could be, e.g., improved throughput, robustness, accuracy or reliability, etc.

[0140] Through studying a few carefully selected use cases, assessing their performance in comparison with traditional methods and the associated potential specification impacts that enable their solutions, this SI will　lay the foundation for future air-interface use cases leveraging AI / ML techniques.

[0141] The goal is that sufficient use cases will be considered to enable the identification of a common AI / ML framework, including functional requirements of AI / ML architecture, which could be used in subsequent projects. The study should also identify areas where AI / ML could improve the performance of air-interface functions.

[0142] The study will serve identifying what is required for an adequate AI / ML model characterization and description establishing pertinent notation for discussions and subsequent evaluations. Various levels of collaboration between the gNB and UE are identified and considered.

[0143] Evaluations to exercise the attainable gains of AI / ML based techniques for the use cases under consideration will be carried out with the corresponding identification of KPIs with the goal to have a better understanding of the attainable gains and associated complexity requirements.

[0144] Finally, specification impact will be assessed in order to improve the overall understanding of what would be required to enable AI / ML techniques for the air-interface.

[0145] For the study on AI / ML for air-interface, the basic framework and principles agreed forFS_NR_ENDC_data_collect,as captured in section 4 of TR 37.817, should be taken into consideration for possible applicability.

[0146] Study the 3GPP framework for AI / ML for air-interface corresponding to each target use case regarding aspects such as performance, complexity, and potential specification impact.

[0147] Use cases to focus on:

[0148] 1> Initial set of use cases includes:

[0149] a) CSI feedback enhancement, e.g., overhead reduction, improved accuracy, prediction

[0150] b) Beam management, e.g., beam prediction in time,　and / or　spatial domain　for overhead and latency reduction, beam selection accuracy improvement

[0151] c) Positioning accuracy enhancements for different scenarios including, e.g., those with　heavy NLOS conditions

[0152] 2> Finalize representative sub use cases for each use case for characterization and baseline performance evaluations

[0153] a) The AI / ML approaches for the selected sub use cases need to be diverse enough to support various requirements on the gNB-UE collaboration levels

[0154] - the selection of use cases for this study solely targets the formulation of a framework to apply AI / ML to the air-interface for these and other use cases. The selection itself does not intend to provide any indication of the prospects of any future normative project.

[0155] AI / ML model, terminology and description to identify common and specific characteristics for framework investigations:

[0156] 3> Characterize the defining stages of AI / ML related algorithms and associated complexity:

[0157] a) Model generation, e.g., model training (including input / output, pre- / post-process, online / offline as applicable), model validation, model testing, as applicable

[0158] b) Inference operation, e.g., input / output, pre- / post-process, as applicable

[0159] 4> Identify various levels of collaboration between UE and gNB pertinent to the selected use cases, e.g.,

[0160] a) No collaboration: implementation-based only AI / ML algorithms without information exchange [for comparison purposes]

[0161] b) Various levels of UE / gNB collaboration targeting at separate or joint ML operation.

[0162] 5> Characterize lifecycle management of AI / ML model: e.g., model training, model deployment , model inference, model monitoring, model updating

[0163] 6> Dataset(s) for training, validation, testing, and inference

[0164] 7> Identify common notation and terminology for AI / ML related functions, procedures and interfaces

[0165] 8> Note: Consider the work done forFS_NR_ENDC_data_collectwhen appropriate

[0166] For the use cases under consideration:

[0167] - Evaluate performance benefits of AI / ML based algorithms for the agreed use cases in the final representative set:

[0168] a) Methodology based on statistical models (from TR 38.901 and TR 38.857 [positioning]), for link and system level simulations.

[0169] i. Extensions of 3GPP evaluation methodology for better suitability to AI / ML based techniques should be considered as needed.

[0170] ii. Whether field data are optionally needed to further assess the performance and robustness in real-world environments should be discussed as part of the study.

[0171] iii. Need for common assumptions in dataset construction for training, validation and test for the selected use cases.

[0172] iv. Consider adequate model training strategy, collaboration levels and associated implications

[0173] v. Consider agreed-upon base AI model(s) for calibration

[0174] vi. AI model description and training methodology used for evaluation should be reported for information and cross-checking purposes

[0175] b) KPIs: Determine the common KPIs and corresponding requirements for the AI / ML operations. Determine the use-case specific KPIs and benchmarks of the selected use-cases.

[0176] i. Performance, inference latency and computational complexity of AI / ML based algorithms should be compared to that of a state-of-the-art baseline

[0177] ii. Overhead, power consumption (including computational), memory storage, and hardware requirements (including for given processing delays) associated with enabling respective AI / ML scheme, as well as generalization capability should be considered.

[0178] - Assess potential specification impact, specifically for the agreed use cases in the final representative set and for a common framework:

[0179] c) PHY layer aspects, e.g., (RAN1)

[0180] i. Consider aspects related to, e.g., the potential specification of the AI Model lifecycle management, and dataset construction for training, validation and test for the selected use cases

[0181] ii. Use case and collaboration level specific specification impact, such as new signalling, means for training and validation data assistance, assistance information, measurement, and feedback

[0182] d) Protocol aspects, e.g., (RAN2) - RAN2 only starts the work after there is sufficient progress on the use case study in RAN1

[0183] i. Consider aspects related to, e.g., capability indication, configuration and control procedures (training / inference), and management of data and AI / ML model, per RAN1 input

[0184] ii. Collaboration level specific specification impact per use case

[0185] e) Interoperability and testability aspects, e.g., (RAN4) - RAN4 only starts the work after there is sufficient progress on use case study in RAN1 and RAN2

[0186] i. Requirements and testing frameworks to validate AI / ML based performance enhancements and ensuring that UE and gNB with AI / ML meet or exceed the existing minimum requirements if applicable

[0187] ii. Consider the need and implications for AI / ML processing capabilities definition

[0188] - specific AI / ML models are not expected to be specified and are left to implementation. User data privacy needs to be preserved.

[0189] - The study on AI / ML for air interface is based on the current RAN architecture and new interfaces shall not be introduced.

[0190] The application of AI / ML techniques to NR air interface has been studied in FS_NR_AIML_Air.

[0191] In this work item, we provide the normative support for the general framework for AI / ML for air interface, as well as, enable the recommended use cases in the preceding study. In addition, a number of study objectives in this project will tackle some outstanding issues identified during the study in an attempt to deepen the understanding in view of future normative work.

[0192] Functional framework details

[0193] This section introduces the functional framework for AI / ML for NR air interface illustrated in FIG. 10. The aim of this framework is to cover a general functional architecture addressing both model-ID-based LCM and functionality-based LCM. Therefore, some of the functions or data / information / instruction flows (i.e., the arrows) shown in the FIG. 10 might not always be relevant for a given LCM approach. As an illustrative example, consider a scenario where the network performs functionality-based LCM and where models are not identified in the network, while the UE concurrently performs model-level management (e.g., model selection / switching / (de)activation, etc쪋). In this hypothetical case, the "Model Training" or "Model Storage" functions with their respective procedures, may be regarded as irrelevant from the network's perspective.

[0194] The functions and data / information / instruction flows (i.e., the arrows) depicted in FIG. 10 are analysed for any standardization impact and its implications.

[0195] The functional framework and high-level procedures defined in this TR should not prevent from "thinking beyond" them during a normative phase if any use case requires so.

[0196] FIG. 10 shows an example of functional framework for AI / ML for NR Air Interface.

[0197] As seen in FIG. 10, the general framework consists of the following:

[0198] - Data Collection is a function that provides input data to the Model Training, Management, and Inference functions.

[0199] - Training Data: Data needed as input for the AI / ML Model Training function.

[0200] - Monitoring Data: Data needed as input for the Management of AI / ML models or AI / ML functionalities.

[0201] - Inference Data: Data needed as input for the AI / ML Inference function.

[0202] - Model Training is a function that performs AI / ML model training, validation, and testing which may generate model performance metrics which can be used as part of the model testing procedure. The Model Training function is also responsible for data preparation (e.g., data pre-processing and cleaning, formatting, and transformation) based on Training Data delivered by a Data Collection function, if required.

[0203] - Trained / Updated Model: In case of having a Model Storage function, this is used to deliver trained, validated, and tested AI / ML models to the Model Storage function, or to deliver an updated version of a model to the Model Storage function.

[0204] - Management is a function that oversees the operation (e.g., selection / (de)activation / switching / fallback) and monitoring (e.g., performance) of AI / ML models or AI / ML functionalities. This function is also responsible for making decisions to ensure the proper inference operation based on data received from the Data Collection function and the Inference function.

[0205] - Management Instruction: Information needed as input to manage the Inference function. Concerning information may include selection / (de)activation / switching of AI / ML models or AI / ML-based functionalities, fallback to non-AI / ML operation (i.e., not relying on inference process), etc쪋

[0206] - Model Transfer / Delivery Request: Used to request model(s) to the Model Storage function.

[0207] - Performance Feedback / Retraining Request: Information needed as input for the Model Training function, e.g., for model (re)training or updating purposes.

[0208] - Inference is a function that provides outputs from the process of applying AI / ML models or AI / ML functionalities, using the data that is provided by the Data Collection function (i.e., Inference Data) as an input. The Inference function is also responsible for data preparation (e.g., data pre-processing and cleaning, formatting, and transformation) based on Inference Data delivered by a Data Collection function, if required.

[0209] - Inference Output: Data used by the Management function to monitor the performance of AI / ML models or AI / ML functionalities.

[0210] - Model Storage is a function responsible for storing trained / updated models that can be used to perform the Inference function.

[0211] - The Model Storage function in FIG. 10 is only intended as a reference point (if any) when applicable for protocol terminations, model transfer / delivery, and related processes. It should be stressed that its purpose does not encompass restricting the actual storage locations of models. Therefore, the specification impact of all data / information / instruction flows (i.e., the arrows in FIG. 10) to / from this function should be studied case by case.

[0212] - Model Transfer / Delivery: Used to deliver an AI / ML model to the Inference function.

[0213] Beam management

[0214] Performance monitoring:

[0215] For the performance monitoring of BM-Case1 and BM-Case2:

[0216] - Performance metric(s) with the following alternatives:

[0217] - Alt.1: Beam prediction accuracy related KPIs, e.g., Top-K / 1 beam prediction accuracy

[0218] - Alt.2: Link quality related KPIs, e.g., throughput, L1-RSRP, L1-SINR, hypothetical BLER

[0219] - Alt.3: Performance metric based on input / output data distribution of AI / ML

[0220] - Alt.4: The L1-RSRP difference evaluated by comparing measured RSRP and predicted RSRP

[0221] - Benchmark / reference for the performance comparison, including:

[0222] - Alt.1: The best beam(s) obtained by measuring beams of a set indicated by gNB (e.g., Beams from Set A)

[0223] - Alt.4: Measurements of the predicted best beam(s)　corresponding to　model output (e.g., Comparison between actual L1-RSRP and predicted RSRP of predicted Top-1 / K Beams)

[0224] - Signalling / configuration / measurement / report for model monitoring, e.g., signalling aspects related to assistance information (if supported), Reference signals

[0225] For BM-Case1 and BM-Case2 with a UE-side AI / ML model:

[0226] - Type 1 performance monitoring:

[0227] - Configuration / Signalling from gNB to UE for measurement and / or reporting

[0228] - UE may have different operations

[0229] - Option 1 (NW-side performance monitoring): UE sends reporting to NW (e.g., for the calculation of performance metric at NW)

[0230] - Option 2 (UE-assisted performance monitoring): UE calculates performance metric(s), either reports it to NW or reports an event to NW based on the performance metric(s)

[0231] - Indication from NW for UE to do LCM operations

[0232] - Type 2 performance monitoring:

[0233] - Indication / request / report from UE to gNB for performance monitoring

[0234] - The indication / request / report may be not needed in some case(s)

[0235] - Configuration / Signalling from gNB to UE for performance monitoring measurement and / or reporting

[0236] - If it is for UE side model monitoring, UE makes decision(s) of model selection / activation / deactivation / switching / fallback operation

[0237] - Mechanism that facilitates the UE to detect whether the functionality / model is suitable or no longer suitable

[0238] For BM-Case1 and BM-Case2 with a NW-side AI / ML model

[0239] - Beam measurement and report for model monitoring

[0240] - UE reporting of beam measurement(s) based on a set of beams indicated by gNB.

[0241] - Signalling, e.g., RRC-based, L1-based.

[0242] - NW monitors the performance metric(s) and makes decision(s) of model selection / activation / deactivation / switching / fallback operation

[0243] - Note: Performance and UE complexity, power consumption should be considered.

[0244] Data collection:

[0245] At UE side for UE-side AI / ML model:

[0246] - UE reporting to NW supported / preferred configurations of DL RS transmission.

[0247] - Trigger / initiating data collection considering:

[0248] - Option 1: data collection initiated / triggered by configuration from NW.

[0249] - Option 2: request from UE for data collection.

[0250] - Signalling / configuration / measurement / report for data collection, e.g., signalling aspects related to assistance information (if supported), Reference signals, content / type of the collected data, configuration related to Set A and / or Set B, information on association / mapping of Set A and Set B

[0251] - Assistance information from Network to UE for UE data collection for categorizing the data for the purpose of differentiating characteristics of the data (if supported). The assistance information should preserve privacy / proprietary information.

[0252] At NW side for NW-side AI / ML model:

[0253] - Mechanism related to the reporting.

[0254] - Additional information for content of the reporting.

[0255] - Reporting overhead reduction.

[0256] - Signalling / configuration / measurement / report for data collection, e.g., signalling aspects related to assistance information (if supported), Reference signals.

[0257] Regarding data collection for NW-side AI / ML model regarding the contents of collected data:

[0258] - Opt.1: M1 L1-RSRPs (corresponding to M1 beams) with the indication of beams (beam pairs) based on the measurement corresponding to a beam set, where M1 can be larger than 4, if applicable.

[0259] - Opt.2: M2 L1-RSRPs (corresponding to M2 beams) based on the measurement corresponding to a beam set, where M2 can be larger than 4, if applicable.

[0260] - Opt.3: M3 beam (beam pair) indices based on the measurement corresponding to a beam set, where M3 can be larger than 4, if applicable.

[0261] Regarding data collection for NW-side AI / ML model of BM-Case1 and BM-Case2, the following approaches have been identified for overhead reduction:

[0262] - the omission / selection of collected data

[0263] - the compression of collected data

[0264] - For the different purposes of data collection, the overhead reduction mechanisms and corresponding specification impacts may be different.

[0265] - Support of any mechanism(s) (if necessary) for each LCM purpose and the potential spec impact (if any) are separate discussions

[0266] - UE complexity and power consumption should be considered

[0267] Regarding data collection for NW-side AI / ML model of BM-Case1 and BM-Case2, the following reporting signalling for beam-specific aspects maybe applicable:

[0268] - L1 signalling to report the collected data

[0269] - Higher-layer signalling to report the collected data

[0270] - At least not applicable to AI / ML model inference

[0271] - Higher layer signalling design is up to RAN2

[0272] - Whether each signalling applicable to each LCM purpose is a separate discussion

[0273] - The legacy signalling principle (e.g. RSRP reporting for L1) can be re-used

[0274] Model Inference related:

[0275] In order to facilitate the AI / ML model inference:

[0276] - Enhanced or new configurations / UE reporting / UE measurement, e.g., enhanced or new beam measurement and / or beam reporting

[0277] - Enhanced or new signalling for measurement configuration / triggering

[0278] - Signalling of assistance information (if applicable)

[0279] For BM-Case1 and BM-Case2 with a UE-side AI / ML model:

[0280] - Indication of the associated Set A from network to UE, e.g., association / mapping of beams within Set A and beams within Set B if applicable

[0281] - Beam indication from network for UE reception, which may or may not have additional specification impact (e.g., legacy mechanism may be reused), particularly:

[0282] - how to perform beam indication of beams in Set A not in Set B. Note: also applicable to NW-side AI / ML model. Note: At least for BM-Case1 with a UE-side AI / ML model, the legacy TCI state mechanism can be used to perform beam indication of beams

[0283] - For DL beam pair prediction, there is no consensus to support the reporting of the predicted Rx beam(s) (e.g., Rx beam ID, Rx beam angle information, etc) from the UE to the network.

[0284] - Predicted L1-RSRP(s) corresponding to the DL Tx beam(s) or beam pair(s)

[0285] - Whether / how to differentiate predicted L1-RSRP and measured L1-RSRP

[0286] - Confidence / probability information related to the output of AI / ML model inference (e.g., predicted beams)

[0287] For BM-Case1 and BM-Case2 with a NW-side AI / ML model:

[0288] - L1 beam reporting enhancement for AI / ML model inference:

[0289] - UE to report the measurement results of more than 4 beams in one reporting instance

[0290] - Other L1 reporting enhancements can be considered

[0291] For BM-Case1 with a UE-side AI / ML model:

[0292] - L1 signalling to report the following information of AI / ML model inference to NW:

[0293] - The beam(s) that is based on the output of AI / ML model inference.

[0294] For BM-Case2 with a UE-side AI / ML model:

[0295] - L1 signalling to report the following information of AI / ML model inference to NW:

[0296] - The beam(s) of N future time instance(s) that is based on the output of AI / ML model inference.

[0297] - Information about the timestamp corresponding the reported beam(s).

[0298] For BM-Case 2:

[0299] - Reporting information about measurements of multiple past time instances in one reporting instance. Notes: Only applicable to NW-side AI / ML model. The potential performance gains of measurement reporting should be justified by considering UCI payload overhead.

[0300] Assistance information:

[0301] Regarding the explicit assistance information from UE to network for NW-side AI / ML model, RAN1 has no consensus to support the following information

[0302] - UE location

[0303] - UE moving direction

[0304] - UE Rx beam shape / direction

[0305] Regarding the explicit assistance information from network to UE for UE-side AI / ML model, RAN1 has no consensus to support the following information

[0306] - NW-side beam shape information

[0307] - E.g., 3dB beamwidth, beam boresight directions, beam shape, Tx beam angle, etc.

[0308] - Other information (e.g., relative information) of Tx beam(s) preserving sensitive proprietary information is a separate discussion

[0309] - e.g., some information following the same principle of Rel-17 positioning agreement

[0310] For BM-Case1 and BM-Case2 with a UE-side AI / ML model, consistency / association of Set B beams and Set A beams across training and inference is beneficial from performance perspective.

[0311] - Whether specification impact is needed is a separate discussion.

[0312] Considerations for network-side data collection

[0313] A set of general data collection principles is expected to be considered for network-side model training. These include:

[0314] - UE to support data logging,

[0315] - UE to report the collected data periodically, event-based, and on-demand,

[0316] - The UE memory, processing power, energy consumption, signalling overhead should be considered.

[0317] Furthermore, and regarding the use cases in this study, the following is considered.

[0318] For CSI and beam management use cases, the training of network-side models can consider both gNB and OAM-centric data collection mechanisms. The gNB-centric data collection implies that the gNB can configure the UE to initiate / terminate the data collection procedure. The potential impact of L3 signalling for the reporting of collected data should be assessed.

[0319] On the other hand, OAM-centric data collection implies that the OAM provides the configuration (via the gNB) needed for the UE to initiate / terminate the data collection procedure. MDT framework can be considered to achieve this. The potential impact on MDT for RRC_CONNECTED state should be assessed.

[0320] For positioning use cases, when considering LMF-side inference, it is assumed that the LPP protocol should be applied to the data collected by UE and terminated at LMF, while the NRPPa protocol should be applied to the data collected by gNB and terminated at LMF. While for LMF-side performance monitoring, it is assumed that the LPP protocol should be applied to the data collected by UE and terminated at LMF, while the NRPPa protocol should be applied to the data collected by gNB and terminated at LMF.

[0321] Data collection forUE-side model training

[0322] The following proposals were discussed in RAN2:

[0323] 1. UE collects and directly transfers training data to the Over-The-Top (OTT) server;

[0324] 1a) OTT (TRansparent)

[0325] 1b) OTT (non-TRansparent)

[0326] 2. UE collects training data and transfers it to Core Network. Core Network transfers the training data to the OTT server.

[0327] 3. UE collects training data and transfers it to OAM. OAM transfers the needed data to the OTT server.

[0328] Hereinafter, technical features related to measurements are described. Sections of 3GPP TS 38.331 v18.3.0 may be referred.

[0329] The network may configure an RRC_CONNECTED UE to perform measurements. The network may configure the UE to report them in accordance with the measurement configuration or perform conditional reconfiguration evaluation in accordance with the conditional reconfiguration. The measurement configuration is provided by means of dedicated signalling i.e. using theRRCReconfigurationorRRCResume.

[0330] The network may configure the UE to perform the following types of measurements:

[0331] - NR measurements;

[0332] - Inter-RAT measurements of E-UTRA frequencies;

[0333] - Inter-RAT measurements of UTRA-FDD frequencies;

[0334] - NR sidelink measurements of L2 U2N Relay UEs.

[0335] The network may configure the UE to report the following measurement information based on SS / PBCH block(s):

[0336] - Measurement results per SS / PBCH block;

[0337] - Measurement results per cell based on SS / PBCH block(s);

[0338] - SS / PBCH block(s) indexes.

[0339] The network may configure the UE to report the following measurement information based on CSI-RS resources:

[0340] - Measurement results per CSI-RS resource;

[0341] - Measurement results per cell based on CSI-RS resource(s);

[0342] - CSI-RS resource measurement identifiers.

[0343] The network may configure the UE to perform the following types of measurements for NR sidelink and V2X sidelink:

[0344] - CBR measurements.

[0345] The network may configure the UE to report the following CLI measurement information based on SRS resources:

[0346] - Measurement results per SRS resource;

[0347] - SRS resource(s) indexes.

[0348] The network may configure the UE to report the following CLI measurement information based on CLI-RSSI resources:

[0349] - Measurement results per CLI-RSSI resource;

[0350] - CLI-RSSI resource(s) indexes.

[0351] The network may configure the UE to report the following Rx-Tx time difference measurement information based on CSI-RS for tracking or PRS:

[0352] - UE Rx-Tx time difference measurement result.

[0353] The measurement configuration includes the following parameters:

[0354] 1. Measurement objects:A list of objects on which the UE shall perform the measurements.

[0355] - For intra-frequency and inter-frequency measurements a measurement object indicates the frequency / time location and subcarrier spacing of reference signals to be measured. Associated with this measurement object, the network may configure a list of cell specific offsets, a list of 'exclude-listed' cells and a list of 'allow-listed' cells. Exclude-listed cells are not applicable in event evaluation or measurement reporting. Allow-listed cells are the only ones applicable in event evaluation or measurement reporting.

[0356] - ThemeasObjectIdof the MO which corresponds to each serving cell is indicated byservingCellMOwithin the serving cell configuration.

[0357] - For inter-RAT E-UTRA measurements a measurement object is a single E-UTRA carrier frequency. Associated with this E-UTRA carrier frequency, the network can configure a list of cell specific offsets and a list of 'exclude-listed' cells. Exclude-listed cells are not applicable in event evaluation or measurement reporting.

[0358] - For inter-RAT UTRA-FDD measurements a measurement object is a set of cells on a single UTRA-FDD carrier frequency.

[0359] - For NR sidelink measurements of L2 U2N Relay UEs, a measurement object is a single NR sidelink frequency to be measured.

[0360] - For CBR measurement of NR sidelink communication, a measurement object is a set of transmission resource pool(s) on a single carrier frequency for NR sidelink communication.

[0361] - For CBR measurement of NR sidelink discovery, a measurement object is a set of discovery dedicated resource pool(s) or transmission resource pool(s) also used for NR sidelink discovery on a single carrier frequency for NR sidelink discovery.

[0362] - For CLI measurements a measurement object indicates the frequency / time location of SRS resources and / or CLI-RSSI resources, and subcarrier spacing of SRS resources to be measured.

[0363] 2. Reporting configurations:A list of reporting configurations where there can be one or multiple reporting configurations per measurement object. Each measurement reporting configuration consists of the following:

[0364] - Reporting criterion: The criterion that triggers the UE to send a measurement report. This can either be periodical or a single event description.

[0365] - RS type: The RS that the UE uses for beam and cell measurement results (SS / PBCH block or CSI-RS).

[0366] - Reporting format: The quantities per cell and per beam that the UE includes in the measurement report (e.g. RSRP) and other associated information such as the maximum number of cells and the maximum number beams per cell to report.

[0367] In case of conditional reconfiguration, each configuration consists of the following:

[0368] - Execution criteria: The criteria the UE uses for conditional reconfiguration execution.

[0369] - RS type: The RS that the UE uses for obtaining beam and cell measurement results (SS / PBCH block-based or CSI-RS-based), used for evaluating conditional reconfiguration execution condition.

[0370] 3. Measurement identities:For measurement reporting, a list of measurement identities where each measurement identity links one measurement object with one reporting configuration. By configuring multiple measurement identities, it is possible to link more than one measurement object to the same reporting configuration, as well as to link more than one reporting configuration to the same measurement object. The measurement identity is also included in the measurement report that triggered the reporting, serving as a reference to the network. For conditional reconfiguration triggering, one measurement identity links to exactly one conditional reconfiguration trigger configuration. And up to 2 measurement identities can be linked to one conditional reconfiguration execution condition.

[0371] 4. Quantity configurations:The quantity configuration defines the measurement filtering configuration used for all event evaluation and related reporting, and for periodical reporting of that measurement. For NR measurements, the network may configure up to 2 quantity configurations with a reference in the NR measurement object to the configuration that is to be used. In each configuration, different filter coefficients can be configured for different measurement quantities, for different RS types, and for measurements per cell and per beam.

[0372] 5. Measurement gaps:Periods that the UE may use to perform measurements.

[0373] A UE in RRC_CONNECTED maintains a measurement object list, a reporting configuration list, and a measurement identities list according to signalling and procedures in this specification. The measurement object list possibly includes NR measurement object(s), CLI measurement object(s), inter-RAT objects, and L2 U2N Relay objects. Similarly, the reporting configuration list includes NR, inter-RAT, and L2 U2N Relay reporting configurations. Any measurement object can be linked to any reporting configuration of the same RAT type. Some reporting configurations may not be linked to a measurement object. Likewise, some measurement objects may not be linked to a reporting configuration.

[0374] The measurement procedures distinguish the following types of cells:

[0375] 1. The NR serving cell(s) - these are the SpCell and one or more SCells.

[0376] 2. Listed cells - these are cells listed within the measurement object(s).

[0377] 3. Detected cells - these are cells that are not listed within the measurement object(s) but are detected by the UE on the SSB frequency(ies) and subcarrier spacing(s) indicated by the measurement object(s).

[0378] For NR measurement object(s), the UE measures and reports on the serving cell(s) / serving Relay UE (for L2 U2N Remote UE), listed cells and / or detected cells. For inter-RAT measurements object(s) of E-UTRA, the UE measures and reports on listed cells and detected cells and, for RSSI and channel occupancy measurements, the UE measures and reports on the configured resources on the indicated frequency. For inter-RAT measurements object(s) of UTRA-FDD, the UE measures and reports on listed cells. For CLI measurement object(s), the UE measures and reports on configured measurement resources (i.e. SRS resources and / or CLI-RSSI resources). For L2 U2N Relay object(s), the UE measures and reports on the serving NR cell(s), as well as the discovered L2 U2N Relay UEs.

[0379] Whenever the procedural specification, other than contained in clause 5.5.2, refers to a field it concerns a field included in theVarMeasConfigunless explicitly stated otherwise i.e. only the measurement configuration procedure covers the direct UE action related to the receivedmeasConfig.

[0380] In NR-DC, the UE may receive two independentmeasConfig:

[0381] - ameasConfig, associated with MCG, that is included in theRRCReconfigurationmessage received via SRB1; and

[0382] - ameasConfig, associated with SCG, that is included in theRRCReconfigurationmessage received via SRB3, or, alternatively, included within aRRCReconfigurationmessage embedded in aRRCReconfigurationmessage received via SRB1.

[0383] In this case, the UE maintains two independentVarMeasConfigandVarMeasReportList, one associated with eachmeasConfig, and independently performs all the procedures for eachmeasConfigand the associatedVarMeasConfigandVarMeasReportList, unless explicitly stated otherwise.

[0384] The configurations related to CBR measurements are only included in themeasConfigassociated with MCG.

[0385] The configurations related to Rx-Tx time difference measurement are only included in themeasConfigassociated with MCG.

[0386] Measurement configuration

[0387] The network applies the procedure as follows:

[0388] - to ensure that, whenever the UE has ameasConfigassociated with a CG, it includes ameasObjectfor the SpCell and for each NR SCell of the CG to be measured;

[0389] - to configure at most one measurement identity across all CGs using a reporting configuration with thereportTypeset toreportCGI;

[0390] - to configure at most one measurement identity per the node hosting PDCP entity using a reporting configuration with theul-DelayValueConfig;

[0391] - to configure at most one measurement identity per the node hosting PDCP entity using a reporting configuration with theul-ExcessDelayConfig;

[0392] - to ensure that, in themeasConfigassociated with a CG:

[0393] - for all SSB based measurements there is at most one measurement object with the samessbFrequency;

[0394] -ansmtc1included in any measurement object with the samessbFrequencyhas the same value and that ansmtc2included in any measurement object with the samessbFrequencyhas the same value and that ansmtc3listincluded in any measurement object with the samessbFrequencyhas the same value and that ansmtc4listincluded in any measurement object with the samessbFrequencyhas the same value;

[0395] - to ensure that all measurement objects configured in this specification with the samessbFrequencyhave the samessbSubcarrierSpacing;

[0396] - to ensure that, if a measurement object associated with the MCG has the samessbFrequencyas a measurement object associated with the SCG:

[0397] - for thatssbFrequency, the measurement window according to thesmtc1configured by the MCG includes the measurement window according to thesmtc1configured by the SCG, or vice-versa, with an accuracy of the maximum receive timing difference.

[0398] - if both measurement objects are used for RSSI measurements, bits inmeasurementSlotsin both objects corresponding to the same slot are set to the same value. Also, theendSymbolis the same in both objects.

[0399] - to ensure that, if a measurement object has the samessbFrequencyas a measurement object:

[0400] - for thatssbFrequency, the measurement window according to thesmtcincludes the measurement window according to thesmtc1, or vice-versa, with an accuracy of the maximum receive timing difference.

[0401] - if both measurement objects are used for RSSI measurements, bits inmeasurementSlotsin both objects corresponding to the same slot are set to the same value. Also, theendSymbolis the same in both objects.

[0402] - when the UE is in NE-DC, NR-DC, or NR standalone, to configure at most one measurement identity across all CGs using a reporting configuration with thereportTypeset toreportSFTD;

[0403] For CSI-RS resources, the network applies the procedure as follows:

[0404] - to ensure that all CSI-RS resources configured in each measurement object have the same center frequency, (startPRB+floor(nrofPRBs / 2))

[0405] - to ensure that the total number of CSI-RS resources configured in each measurement object does not exceed the maximum number.

[0406] Quantity configuration

[0407] The UE shall:

[0408] 1> for each RAT for which the receivedquantityConfigincludes parameter(s):

[0409] 2> set the corresponding parameter(s) inquantityConfigwithinVarMeasConfigto the value of the receivedquantityConfigparameter(s);

[0410] 1> for eachmeasIdincluded in themeasIdListwithinVarMeasConfig:

[0411] 2> remove the measurement reporting entry for thismeasIdfrom theVarMeasReportList, if included;

[0412] 2> stop the periodical reporting timer or timer T321 or timer T322, whichever one is running, and reset the associated information (e.g.timeToTrigger) for thismeasId.

[0413] Reference signal measurement timing configuration

[0414] The UE shall setup the first SS / PBCH block measurement timing configuration (SMTC) in accordance with the receivedperiodicityAndOffsetparameter (providingPeriodicityandOffsetvalue for the following condition) in thesmtc1configuration. The first subframe of each SMTC occasion occurs at an SFN and subframe of the NR SpCell meeting the following condition:

[0415] SFN modT= (FLOOR (Offset / 10));

[0416] if thePeriodicityis larger thansf5:

[0417] subframe =Offsetmod 10;

[0418] else:

[0419] subframe =Offsetor (Offset+5);

[0420] withT= CEIL(Periodicity / 10).

[0421] Ifsmtc2is present, for cells indicated in thepci-Listparameter insmtc2in the sameMeasObjectNR, the UE shall setup an additional SS / PBCH block measurement timing configuration (SMTC) in accordance with the receivedperiodicityparameter in thesmtc2configuration and use theOffset(derived from parameterperiodicityAndOffset) anddurationparameter from thesmtc1configuration. The first subframe of each SMTC occasion occurs at an SFN and subframe of the NR SpCell meeting the above condition.

[0422] Ifsmtc2-LPis present, for cells indicated in thepci-Listparameter insmtc2-LPin the same frequency (for intra frequency cell reselection) or different frequency (for inter frequency cell reselection), the UE shall setup an additional SS / PBCH block measurement timing configuration (SMTC) in accordance with the receivedperiodicityparameter in thesmtc2-LPconfiguration and use theOffset(derived from parameterperiodicityAndOffset) anddurationparameter from thesmtcconfiguration for that frequency. The first subframe of each SMTC occasion occurs at an SFN and subframe of the NR SpCell or serving cell (for cell reselection) meeting the above condition.

[0423] Ifsmtc3listis present, for cells indicated in thepci-Listparameter in eachSSB-MTC3element of the list in the sameMeasObjectNR, the IAB-MT shall setup an additional SS block measurement timing configuration in accordance with the receivedperiodicityAndOffsetparameter (using same condition assmtc1to identify the SFN and the subframe for SMTC occasion) in each SSB-MTC3 configuration and use the duration andssb-ToMeasureparameters from each SSB-MTC3 configuration.

[0424] Ifsmtc4listis present, for cells indicated in thepci-Listparameter in eachSSB-MTC4element of the list in the sameMeasObjectNR, the UE shall setup an additional SS / PBCH block measurement timing configuration (SMTC) in accordance with the receivedOffsetparameter in thesmtc4configuration and use theperiodicity(derived from parameterperiodicityAndOffset) anddurationparameter from thesmtc1configuration. The first subframe of each SMTC occasion occurs at an SFN and subframe of the NR SpCell meeting the above condition.

[0425] On the indicatedssbFrequency, the UE shall not consider SS / PBCH block transmission in subframes outside the SMTC occasion for RRM measurements based on SS / PBCH blocks and for RRM measurements based on CSI-RS except for SFTD measurement.

[0426] Performing measurements

[0427] An RRC_CONNECTED UE shall derive cell measurement results by measuring one or multiple beams associated per cell as configured by the network. For all cell measurement results, except for RSSI, and CLI measurement results in RRC_CONNECTED, the UE applies the layer 3 filtering, before using the measured results for evaluation of reporting criteria, measurement reporting or the criteria to trigger conditional reconfiguration execution. For cell measurements, the network can configure RSRP, RSRQ, SINR, RSCP or EcN0 as trigger quantity. For CLI measurements, the network can configure SRS-RSRP or CLI-RSSI as trigger quantity. For cell and beam measurements, reporting quantities can be any combination of quantities (i.e. only RSRP; only RSRQ; only SINR; RSRP and RSRQ; RSRP and SINR; RSRQ and SINR; RSRP, RSRQ and SINR; only RSCP; only EcN0; RSCP and EcN0), irrespective of the trigger quantity, and for CLI measurements, reporting quantities can be either SRS-RSRP or CLI-RSSI. For conditional reconfiguration execution, the network can configure up to 2 quantities, both using same RS type. The UE does not apply the layer 3 filtering to derive the CBR measurements. The UE does not apply the layer 3 filtering to derive the Rx-Tx time difference measurements.

[0428] The network may also configure the UE to report measurement information per beam (which can either be measurement results per beam with respective beam identifier(s) or only beam identifier(s)). If beam measurement information is configured to be included in measurement reports, the UE applies the layer 3 beam filtering. On the other hand, the exact L1 filtering of beam measurements used to derive cell measurement results is implementation dependent.

[0429] Hereinafter, examples of events are described.

[0430] Event A1 (Serving becomes better than threshold)

[0431] Event A2 (Serving becomes worse than threshold)

[0432] Event A3 (Neighbour becomes offset better than SpCell)

[0433] Event A4 (Neighbour becomes better than threshold)

[0434] Event A5 (SpCell becomes worse than threshold1 and neighbour becomes better than threshold2)

[0435] Event A6 (Neighbour becomes offset better than SCell)

[0436] Event B1 (Inter RAT neighbour becomes better than threshold)

[0437] Event B2 (PCell becomes worse than threshold1 and inter RAT neighbour becomes better than threshold2)

[0438] Event I1 (Interference becomes higher than threshold)

[0439] Event C1 (The NR sidelink channel busy ratio is above a threshold)

[0440] Event C2 (The NR sidelink channel busy ratio is below a threshold)

[0441] Event D1 (Distance between UE and referenceLocation1 is above threshold1 and distance between UE and referenceLocation2 is below threshold2)

[0442] CondEvent T1 (Time measured at UE is within a duration from threshold)

[0443] Event X1 (Serving L2 U2N Relay UE becomes worse than threshold1 and NR Cell becomes better than threshold2)

[0444] Event X2 (Serving L2 U2N Relay UE becomes worse than threshold)

[0445] Event Y1 (PCell becomes worse than threshold1 and candidate L2 U2N Relay UE becomes better than threshold2)

[0446] Event Y2 (Candidate L2 U2N Relay UE becomes better than threshold)

[0447] FIG. 11 shows an example of measurement reporting procedure.

[0448] The purpose of this procedure is to transfer measurement results from the UE to the network. The UE shall initiate this procedure only after successful AS security activation.

[0449] FIG. 12 shows an example of location measurement indication.

[0450] The purpose of this procedure is to indicate to the network that the UE is going to start / stop location related measurements towards E-UTRA or NR (eutra-RSTD,nr-RSTD,nr-UE-RxTxTimeDiff,nr-PRS-RSRP) which require measurement gaps or start / stop detection of subframe and slot timing towards E-UTRA (eutra-FineTimingDetection)which requires measurement gaps. UE shall initiate this procedure only after successful AS security activation.

[0451] Hereinafter, technical features related to logged measurements are described.

[0452] FIG. 13 shows an example of logged measurement configuration.

[0453] The purpose of this procedure is to configure the UE to perform logging of measurement results while in RRC_IDLE and RRC_INACTIVE. The procedure applies to logged measurements capable UEs that are in RRC_CONNECTED.

[0454] NG-RAN may retrieve stored logged measurement information by means of the UE information procedure.

[0455] NG-RAN initiates the logged measurement configuration procedure to UE in RRC_CONNECTED by sending theLoggedMeasurementConfigurationmessage.

[0456] Upon receiving theLoggedMeasurementConfigurationmessage the UE shall:

[0457] 1> discard the logged measurement configuration as well as the logged measurement information;

[0458] 1> store the receivedloggingDuration,reportTypeandareaConfiguration, if included, inVarLogMeasConfig;

[0459] 1> if theLoggedMeasurementConfigurationmessage includesplmn-IdentityList:

[0460] 2> setplmn-IdentityListinVarLogMeasReportto include the RPLMN as well as the PLMNs included inplmn-IdentityList;

[0461] 1> else:

[0462] 2> setplmn-IdentityListinVarLogMeasReportto include the RPLMN;

[0463] 1> store the receivedabsoluteTimeInfo,traceReference,traceRecordingSessionRef, andtce-IdinVarLogMeasReport;

[0464] 1> store the receivedbt-NameList, if included, inVarLogMeasConfig;

[0465] 1> store the receivedwlan-NameList, if included, inVarLogMeasConfig;

[0466] 1> store the receivedsensor-NameList, if included, inVarLogMeasConfig;

[0467] 1> start timer T330 with the timer value set to theloggingDuration;

[0468] 1> store the receivedsigLoggedMeasType,if included, inVarLogMeasReport;

[0469] 1> store the receivedearlyMeasIndication,if included, inVarLogMeasConfig;

[0470] Measurements logging

[0471] This procedure specifies the logging of available measurements by a UE in RRC_IDLE and RRC_INACTIVE that has a logged measurement configuration. The actual process of logging within the UE, takes place in RRC IDLE state could continue in RRC INACTIVE state or vice versa.

[0472] FIG. 14 shows an example of UE information procedure.

[0473] The UE information procedure is used by the network to request the UE to report information.

[0474] The network initiates the procedure by sending theUEInformationRequestmessage. The network should initiate this procedure only after successful security activation.

[0475] Meanwhile, when AI / ML models are trained within the network, the UE may need to frequently send assistant data to enhance model performance through data collection. For example, in Release 19, use cases such as beam management and CSI prediction require data collection via CSI reporting for AI / ML model training, inference, and monitoring. In such cases, additional CSI reports may be necessary to support these models, leading to more frequent reporting compared to non-AIML operations.

[0476] FIG. 15 shows an example for data collection.

[0477] To address these challenges, at least for model training purpose, RRC logging has been proposed. By utilizing logging and transmission mechanisms, RRC logging can help reduce the frequency of data transmissions, thus minimizing power consumption and signalling overhead while maintaining AI / ML model performance.

[0478] However, if the measurement or logging period is too short to collect detailed data, it may lead to issues such as increased UE power consumption and memory overload. The additional burden of continuous measurement and logging can be significant, given the UE's limited power and memory resources.

[0479] To mitigate this, extending the measurement / logging period can be considered. However, in such cases, it becomes difficult to capture detailed information for a specific time interval, making it challenging to analyze or understand critical patterns or changes that occur within that period, potentially resulting in meaningless measurement / logging data.

[0480] Thus, studies for data collection based on logging duration are required.

[0481] Hereinafter, a method for data collection based on logging duration, according to some embodiments of the present disclosure, will be described with reference to the following drawings.

[0482] The following drawings are created to explain specific embodiments of the present disclosure. The names of the specific devices or the names of the specific signals / messages / fields shown in the drawings are provided by way of example, and thus the technical features of the present disclosure are not limited to the specific names used in the following drawings. Herein, a wireless device may be referred to as a user equipment (UE).

[0483] FIG. 16 shows an example of a method for data collection based on logging duration.

[0484] In particular, FIG. 16 shows an example of a method performed by a wireless device in a wireless communication system.

[0485] In step S1601, the wireless device may receive a configuration for data logging.

[0486] For example, the configuration may include (i) information related to a logging duration and (ii) information related to a logging interval.

[0487] In step S1602, the wireless device may perform data logging based on the logging duration.

[0488] The logging duration may be configured within the logging interval.

[0489] For example, the logging duration may be equal to or shorter than the logging interval.

[0490] For example, the logging interval may be a reporting interval.

[0491] For example, the logging duration may be configured within every logging interval.

[0492] For example, the wireless device may skip data logging outside the logging duration.

[0493] For example, the wireless device may transmit a reporting message including logged information upon expiration of the logging interval.

[0494] For example, the wireless device may initiate a new logging interval upon expiration of the logging interval.

[0495] For example, the configuration for data logging may include (i) at least one measurement object, (ii) at least one reporting configuration, and (iii) at least one measurement identity.

[0496] For example, the wireless device may receive a reporting configuration including (i) information related to a reporting interval, (ii) information related to a reporting amount, and (iii) information related to at least one reporting condition.

[0497] For example, the wireless device may log layer 1 (L1) measurement results based on the logging duration.

[0498] For example, the data logging may include logging (i) measurement results, (ii) a measurement identity related to the measurement results, and (iii) time information related to the measurement results.

[0499] For example, the logged information may include (1) reference signal configuration related Id (e.g., Index # of trigger state, Resource Id / Resource set Id / Resource config Id / Report config Id, etc), (2) beam index (e.g., CSI-RS / SSB id, top M beam ids with highest RSRP, K beam ids larger than a threshold or within a threshold, etc), (3) L1 measurement results (e.g., RSRP, SINR, RSRP difference (e.g., difference between predicted and actual RSRP, difference between predicted RSRPs in different time instance), quantized value, normalized value, etc), (4) PMI (Precoding Matrix Indicator), (5) CQI (Channel Quality indicator), (6) RI (Rank indicator), (7) LI (Layer indicator), (8) Time information, (9) Location information(e.g., altitude / latitude / longitude, speed(e.g., vertical / horizon), vector / direction / angle, polygon type location, etc), (10) Cell information (e.g., PCI, TAC, PLMN, etc), (11) L3 measurement results (e.g., RSRP, RSRQ, SINR, etc), and / or (12) System KPI results (e.g., BLER, throughput, nack / ack related information, connection failure related information (e.g., RLF, BF, HOF, Rach failure).

[0500] For example, the data logging may be based on layer 1 measurements for the at least one reference signal.

[0501] According to some embodiments of the present disclosure, the wireless device may be in communication with at least one of a user equipment, a network, or an autonomous vehicle other than the wireless device.

[0502] Hereinafter, some embodiments of a method for logging with partial time domain within reporting interval are provided.

[0503] The UE may log data over a specific duration within reporting interval, i.e., no logging is performed outside of the specific duration interval. Once the reporting interval is reached, the UE may report the logged data may re-start the timer of the specific duration for logging for the next reporting interval. By controlling the logging interval to a short value, interpretation for a specific period can be improved, while limiting the logging operation during the logging duration can reduce the power consumption of the UE.

[0504] To this end, the network may configure logging duration. The logging duration may start when measurement configuration is configured / activated, when the next report interval begins, or upon arriving a time offset from the moment the next report interval begins, or the measurement configuration is configured / activated.

[0505] FIG. 17 shows an example of a method for logging with partial time domain within reporting interval.

[0506] Configuration

[0507] The logging configuration may be further divided into three sub-parts: Measurement Object, Logging (if necessary) and Reporting configuration, and Measurement ID configuration.

[0508] - Measurement Object: Measurement object configuration may include measurement / logging object such as beam (reference signals, SSB, etc) specific / cell specific object.

[0509] - Report configuration:

[0510] > Logging configuration may be included in report configuration. Alternatively, it can be configured in measurement object configuration.

[0511] >> Logging interval: It may indicate the periodicity for logging measurement results.

[0512] >> Logging duration: It may indicate the periodicity for logging within a reporting interval.

[0513] >>> It may be configured with unit of time, such as unit of milliseconds, seconds, minutes, etc

[0514] >>> It may be configured with offset value

[0515] >>> It may be configured with time value such as the logging starting / stop time

[0516] > Reporting configuration may be included in report configuration.

[0517] >> Reporting interval: It may indicate the periodicity for reporting (logged) measurement results.

[0518] >> Reporting amount: It may indicate the number of measurement reports

[0519] >> Reporting condition:

[0520] >>> Radio quality threshold such as A1-A6 events

[0521] >>> Count threshold to trigger reports

[0522] - Measurement Identification

[0523] > Each measurement Id is linked with measurement object and report configuration.

[0524] > Alternatively, logging / reporting related configuration may be applied to more than one measurement object

[0525] In order to log L1 measurement results, the UE may be configured with L1 related reporting configuration. L1 related reporting configuration may associated with measurement object in measurement configuration for logging.

[0526] - Triggering State:

[0527] > aperiodicTriggerStateList: Contains trigger states for dynamically selecting one or more aperiodic and semi-persistent reporting configurations and / or triggering one or more aperiodic CSI-RS resource sets for channel and / or interference measurement

[0528] > semiPersistentOnPUSCH-TriggerStateList : It is used to configure the UE with list of trigger states for semi-persistent reporting of channel state information on L1.

[0529] - Report and Resource Configuration

[0530] > csi-ReportConfigToAddModList: It is used to configure a periodic or semi-persistent report sent on PUCCH on the cell in which theCSI-ReportConfigis included, or to configure a semi-persistent or aperiodic report sent on PUSCH triggered by DCI received on the cell in which theCSI-ReportConfigis included

[0531] > csi-ResourceConfigToAddModList: IECSI-ResourceConfigdefines a group of one or moreNZP-CSI-RS-ResourceSet,CSI-IM-ResourceSetand / orCSI-SSB-ResourceSet.

[0532] - Physical Layer configuration

[0533] > nzp-CSI-RS-ResourceSetToAddModList: references to NZP CSI-RS resources used for beam measurement and reporting in a CSI-RS resource set

[0534] > csi-IM-ResourceSetToAddModList: references to CSI-IM resources used for CSI measurement and reporting in a CSI-RS resource set

[0535] > csi-SSB-ResourceSetToAddModList: references to SSB resources used for CSI measurement and reporting in a CSI-RS resource set

[0536] Performing Measurement

[0537] The UE may perform measurement for measurement object in measurement configuration and may derive measurement results related information.

[0538] The measurement results related information may include:

[0539] - Measurement Id related to measurement results; and / or

[0540] - Reference signal configuration related Id (e.g., Index # of trigger state, Resource Id / Resource set Id / Resource config Id / Report config Id, etc); and / or

[0541] - Beam index (e.g., CSI-RS / SSB id, top M beam ids with highest RSRP, K beam ids larger than a threshold or within a threshold, etc); and / or

[0542] - L1 measurement results (e.g., RSRP, SINR, RSRP difference (e.g., difference between predicted and actual RSRP, difference between predicted RSRPs in different time instance), quantized value, normalized value, etc); and / or

[0543] - PMI (Precoding Matrix Indicator); and / or

[0544] - CQI (Channel Quality indicator); and / or

[0545] - RI (Rank indicator); and / or

[0546] - LI (Layer indicator); and / or

[0547] - Time information; and / or

[0548] - Location information(e.g., altitude / latitude / longitude, speed(e.g., vertical / horizon), vector / direction / angle, polygon type location, etc); and / or

[0549] - Cell information (e.g., PCI, TAC, PLMN, etc); and / or

[0550] - L3 measurement results ( e.g., RSRP, RSRQ, SINR, etc); and / or

[0551] - System KPI results (e.g., BLER, throughput, nack / ack related information, connection failure related information (e.g., RLF, BF, HOF, Rach failure)

[0552] Logging mechanism

[0553] The UE may log the measurement results related information at each logging interval.

[0554] - Logging interval may start when measurement configuration is configured / activated, when previous logging interval is expired, when next reporting interval begins, or upon logging the measurement results

[0555] - If the logging interval is not configured, the UE may log L1 measurement results related information when the UE measures the beam(s).

[0556] - Alternatively, the UE may not perform measurement during the interval in which it does not perform logging, i.e., during the interval in which it waits for the logging interval to expire.

[0557] FIG. 18 shows an example of a method for logging with periodic reporting with logging interval.

[0558] FIG. 19 shows an example of a method for logging with periodic reporting without logging interval.

[0559] If logging duration is configured, the UE may perform logging operation during logging duration.

[0560] - Logging duration may start as followings:

[0561] > When measurement configuration is configured / activated, or

[0562] > When the next report interval begins, or

[0563] > When the UE logs the first data within current reporting interval, or

[0564] > After a time offset from the moment the next report interval begins, or when the measurement configuration is configured / activated, or

[0565] > When previous logging data is removed, or

[0566] > Upon the triggering / sending of the previous report,

[0567] FIG. 20 shows an example of a method for logging with partial time domain within reporting interval.

[0568] <Selective logging case>

[0569] The UE may log measurement results related information depending on a condition (selective logging)

[0570] - For example, if the current value of a specific content of the measurement result related information does not differ from the previous measurement result by a threshold value, the UE may not log the current result.

[0571] - For example, if the current value of a specific content of the measurement result related information does not satisfy condition, e.g., a threshold value, the UE may not log the current results.

[0572] - For example, if the current environment does not satisfy a condition, e.g., UE's speed, UE's (3D) area, etc, the UE may not log the current results.

[0573] < logging stop case>

[0574] The UE may stop logging in following cases:

[0575] - When the UE has internal problem (e.g., UE's memory become full, UE's low power state); and / or

[0576] - When the amount of logged data (logged L1 measurement result related information) has reached maximum size of reporting container. Alternatively, the UE may remove old data and continue logging.; and / or

[0577] - When the UE's report based on reporting interval / report amount is finished. Additionally, in this case, the UE may remove the logging / reporting configuration for the beam(s) related to the reporting.; and / or

[0578] - When the UE's logging duration is expired; and / or

[0579] - When the UE's logging stop time has arrived; and / or

[0580] - When the UE reports the logged data as many times as the number of reports set in the reporting amount

[0581] - In sections where logging is not performed, the UE may not perform measurement.

[0582] Reporting mechanism

[0583] The UE may report logged data according to report interval and / or report amount.

[0584] - When report interval is expired, the UE may report logged data.

[0585] > The report interval may start when measurement configuration is configured / activated, when DCI / MAC CE for aperiodic / semi-persistent reporting (or activation of aperiodic / semi-persistent CSI-RS) is received, when reporting specific DCI / MAC CE is received, or when previous reporting interval is expired (if the number of reporting does not exceed report amount),

[0586] - If report amount is configured, the UE may report logged data the number of times set in report amount

[0587] FIG. 21 shows an example of a method for logging with periodic reporting without logging interval.

[0588] The UE may report logged data according to report condition, if configured

[0589] - If the radio quality related threshold is configured, the UE may send the data when the UE's radio quality is satisfied with radio quality related threshold.

[0590] - If the Count threshold is configured, the UE may count the number of logged data.

[0591] > UE may count the number of logged data per measurement Id; or UE may count the number of logged data for all configured measurement Id,

[0592] >> Alternative 1. If the number of logged data for each measurement Id is more than count threshold, the UE may send a report with logged data

[0593] >> Alternative 2. If the number of logged data for multiple measurement Id is more than count threshold, the UE may send a report with logged data

[0594] >> Alternatively, the UE may send an indication indicating that there are logged data. In this case, the network may retrieve the logged data by using additional procedure, e.g., UE information Request / Response procedure.

[0595] FIG. 22 shows an example for data collection based on logging duration.

[0596] In particular, FIG. 22 shows an example of a method performed by a wireless device in a wireless communication system.

[0597] In step S2201, the wireless device may receive a configuration for logged measurement reporting. The configuration may comprise a logging duration and a report interval of logged result.

[0598] In step S2202, the wireless device may obtain CSI result.

[0599] In step S2203, the wireless device may log the obtained CSI result during the logging duration. The logging duration may be equal to or shorter than the report interval.

[0600] In step S2204, the wireless device may report the logged CSI results based on the reporting interval.

[0601] For example, the wireless device may start a reporting timer related to the report interval, after receiving the configuration for logged measurement reporting.

[0602] For example, the wireless device may report the logged CSI results if a reporting timer related to the report interval expires.

[0603] For example, the wireless device may restart the reporting timer, upon reporting the logged CSI results.

[0604] For example, the wireless device may start a logging timer related to the logging duration, while the reporting timer is running.

[0605] For example, the wireless device may log the CSI results, while the logging timer is running.

[0606] For example, the wireless device may restart the logging timer, based on restarting of the reporting timer.

[0607] Some of the detailed steps shown in the examples of FIGS. 16-22 may not be essential steps and may be omitted. In addition to the steps shown in FIGS. 16-22, other steps may be added, and the order of the steps may vary. Some of the above steps may have their own technical meaning.

[0608] Hereinafter, an apparatus for data collection based on logging duration, according to some embodiments of the present disclosure, will be described. Herein, the apparatus may be a wireless device (100 or 200) in FIGS. 2, 3, and 5.

[0609] For example, a wireless device may perform the methods described above. The detailed description overlapping with the above-described contents could be simplified or omitted.

[0610] Referring to FIG. 5, a wireless device 100 may include a processor 102, a memory 104, and a transceiver 106.

[0611] According to some embodiments of the present disclosure, the processor 102 may be configured to be coupled operably with the memory 104 and the transceiver 106.

[0612] The processor 102 may be adapted to perform operations. The operations comprise: receiving a configuration for data logging, wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval; and performing data logging based on the logging duration, wherein the logging duration is configured within the logging interval.

[0613] For example, the logging duration is equal to or shorter than the logging interval.

[0614] For example, the logging interval is a reporting interval.

[0615] For example, the logging duration is configured within every logging interval.

[0616] For example, the operations further comprise: skipping data logging outside the logging duration.

[0617] For example, the operations further comprise: transmitting a reporting message including logged information upon expiration of the logging interval.

[0618] For example, the operations further comprise: initiating a new logging interval upon expiration of the logging interval.

[0619] For example, the configuration for data logging further includes (i) at least one measurement object, (ii) at least one reporting configuration, and (iii) at least one measurement identity.

[0620] For example, the operations further comprise: receiving a reporting configuration including (i) information related to a reporting interval, (ii) information related to a reporting amount, and (iii) information related to at least one reporting condition.

[0621] For example, the operations further comprise: logging layer 1 (L1) measurement results based on the logging duration.

[0622] For example, the data logging includes logging (i) measurement results, (ii) a measurement identity related to the measurement results, and (iii) time information related to the measurement results.

[0623] For example, the data logging is based on layer 1 measurements for the at least one reference signal.

[0624] For example, the processor 102 may be configured to control the transceiver 106 to be in communication with at least one of a user equipment, a network, or an autonomous vehicle other than the wireless device.

[0625] Hereinafter, a processor for a wireless device for data collection based on logging duration, according to some embodiments of the present disclosure, will be described.

[0626] The processor may be configured to control the wireless device to perform operations. The operations comprise: receiving a configuration for data logging, wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval; and performing data logging based on the logging duration, wherein the logging duration is configured within the logging interval.

[0627] For example, the logging duration is equal to or shorter than the logging interval.

[0628] For example, the logging interval is a reporting interval.

[0629] For example, the logging duration is configured within every logging interval.

[0630] For example, the operations further comprise: skipping data logging outside the logging duration.

[0631] For example, the operations further comprise: transmitting a reporting message including logged information upon expiration of the logging interval.

[0632] For example, the operations further comprise: initiating a new logging interval upon expiration of the logging interval.

[0633] For example, the configuration for data logging further includes (i) at least one measurement object, (ii) at least one reporting configuration, and (iii) at least one measurement identity.

[0634] For example, the operations further comprise: receiving a reporting configuration including (i) information related to a reporting interval, (ii) information related to a reporting amount, and (iii) information related to at least one reporting condition.

[0635] For example, the operations further comprise: logging layer 1 (L1) measurement results based on the logging duration.

[0636] For example, the data logging includes logging (i) measurement results, (ii) a measurement identity related to the measurement results, and (iii) time information related to the measurement results.

[0637] For example, the data logging is based on layer 1 measurements for the at least one reference signal.

[0638] For example, the processor may be configured to control the wireless device to be in communication with at least one of a user equipment, a network, or an autonomous vehicle other than the wireless device.

[0639] Hereinafter, a non-transitory computer-readable medium has stored thereon a plurality of instructions for data collection based on logging duration, according to some embodiments of the present disclosure, will be described.

[0640] According to some embodiment of the present disclosure, the technical features of the present disclosure could be embodied directly in hardware, in a software executed by a processor, or in a combination of the two. For example, a method performed by a wireless device in a wireless communication may be implemented in hardware, software, firmware, or any combination thereof. For example, a software may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other storage medium.

[0641] Some example of storage medium is coupled to the processor such that the processor can read information from the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. For other example, the processor and the storage medium may reside as discrete components.

[0642] The computer-readable medium may include a tangible and non-transitory computer-readable storage medium.

[0643] For example, non-transitory computer-readable media may include random access memory (RAM) such as synchronous dynamic random access memory (SDRAM), read-only memory (ROM), non-volatile random access memory (NVRAM), electrically erasable programmable read-only memory (EEPROM), FLASH memory, magnetic or optical data storage media, or any other medium that can be used to store instructions or data structures. Non-transitory computer-readable media may also include combinations of the above.

[0644] In addition, the method described herein may be realized at least in part by a computer-readable communication medium that carries or communicates code in the form of instructions or data structures and that can be accessed, read, and / or executed by a computer.

[0645] According to some embodiment of the present disclosure, a non-transitory computer-readable medium has stored thereon a plurality of instructions. The stored plurality of instructions may be executed by a processor of a wireless device.

[0646] The stored plurality of instructions may cause the wireless device to perform operations. The operations comprise: receiving a configuration for data logging, wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval; and performing data logging based on the logging duration, wherein the logging duration is configured within the logging interval.

[0647] For example, the logging duration is equal to or shorter than the logging interval.

[0648] For example, the logging interval is a reporting interval.

[0649] For example, the logging duration is configured within every logging interval.

[0650] For example, the operations further comprise: skipping data logging outside the logging duration.

[0651] For example, the operations further comprise: transmitting a reporting message including logged information upon expiration of the logging interval.

[0652] For example, the operations further comprise: initiating a new logging interval upon expiration of the logging interval.

[0653] For example, the configuration for data logging further includes (i) at least one measurement object, (ii) at least one reporting configuration, and (iii) at least one measurement identity.

[0654] For example, the operations further comprise: receiving a reporting configuration including (i) information related to a reporting interval, (ii) information related to a reporting amount, and (iii) information related to at least one reporting condition.

[0655] For example, the operations further comprise: logging layer 1 (L1) measurement results based on the logging duration.

[0656] For example, the data logging includes logging (i) measurement results, (ii) a measurement identity related to the measurement results, and (iii) time information related to the measurement results.

[0657] For example, the data logging is based on layer 1 measurements for the at least one reference signal.

[0658] According to some embodiments of the present disclosure, the stored plurality of instructions may cause the wireless device to be in communication with at least one of a user equipment, a network, or an autonomous vehicle other than the wireless device.

[0659] Hereinafter, a method performed by a base station (BS) for data collection based on logging duration, according to some embodiments of the present disclosure, will be described.

[0660] The method comprises: transmitting, by a base station to a wireless device, a configuration for data logging, wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval, wherein the wireless device performs data logging based on the logging duration, and wherein the logging duration is configured within the logging interval.

[0661] Hereinafter, a base station (BS) for data collection based on logging duration, according to some embodiments of the present disclosure, will be described.

[0662] The BS may include a transceiver, a memory, and a processor operatively coupled to the transceiver and the memory.

[0663] The processor may be configured to perform operations. The operations comprise: transmitting, to a wireless device, a configuration for data logging, wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval, wherein the wireless device performs data logging based on the logging duration, and wherein the logging duration is configured within the logging interval.

[0664] The present disclosure can have various advantageous effects.

[0665] According to some embodiments of the present disclosure, a wireless device could efficiently perform data collection based on logging duration.

[0666] For example, by controlling the logging interval to a short value, interpretation for a specific period can be improved, while limiting the logging operation during the logging duration can reduce the power consumption of the UE.

[0667] For example, the wireless device may perform data collection only during the logging duration within the logging interval. Therefore, the wireless device can save unnecessary resources.

[0668] According to some embodiments of the present disclosure, the wireless communication system could provide an efficient solution for data collection based on logging duration.

[0669] Advantageous effects which can be obtained through specific embodiments of the present disclosure are not limited to the advantageous effects listed above. For example, there may be a variety of technical effects that a person having ordinary skill in the related art can understand and / or derive from the present disclosure. Accordingly, the specific effects of the present disclosure are not limited to those explicitly described herein, but may include various effects that may be understood or derived from the technical features of the present disclosure.

[0670] Claims in the present disclosure can be combined in a various way. For instance, technical features in method claims of the present disclosure can be combined to be implemented or performed in an apparatus, and technical features in apparatus claims can be combined to be implemented or performed in a method. Further, technical features in method claim(s) and apparatus claim(s) can be combined to be implemented or performed in an apparatus. Further, technical features in method claim(s) and apparatus claim(s) can be combined to be implemented or performed in a method. Other implementations are within the scope of the following claims.

Claims

1.A method, comprising:receiving, by a wireless device, a configuration for data logging,wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval; andperforming, by the wireless device, data logging based on the logging duration,wherein the logging duration is configured within the logging interval.2.The method of claim 1,wherein the logging duration is equal to or shorter than the logging interval.3.The method of claim 1,wherein the logging interval is a reporting interval.4.The method of claim 1,wherein the logging duration is configured within every logging interval.5.The method of claim 1, wherein the method further comprising:skipping, by the wireless device, data logging outside the logging duration.6.The method of claim 1, wherein the method further comprising:transmitting, by the wireless device, a reporting message including logged information upon expiration of the logging interval.7.The method of claim 1, wherein the method further comprising:initiating, by the wireless device, a new logging interval upon expiration of the logging interval.8.The method of claim 1,wherein the configuration for data logging further includes (i) at least one measurement object, (ii) at least one reporting configuration, and (iii) at least one measurement identity.9.The method of claim 1, wherein the method further comprising:receiving, by the wireless device, a reporting configuration including (i) information related to a reporting interval, (ii) information related to a reporting amount, and (iii) information related to at least one reporting condition.10.The method of claim 1, wherein the method further comprising:logging, by the wireless device, layer 1 (L1) measurement results based on the logging duration.11.The method of claim 1,wherein the data logging includes logging (i) measurement results, (ii) a measurement identity related to the measurement results, and (iii) time information related to the measurement results.12.The method of claim 1,wherein the data logging is based on layer 1 measurements for the at least one reference signal.13.The method of claim 1,wherein the wireless device is in communication with at least one of a user equipment, a network, or an autonomous vehicle other than the wireless device.14.A wireless device, comprising:a transceiver;a memory; andat least one processor operatively coupled to the transceiver and the memory, and adapted to perform operations, the operations comprising:receiving a configuration for data logging,wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval; andperforming data logging based on the logging duration,wherein the logging duration is configured within the logging interval.15.The wireless device of claim 14,wherein the logging duration is equal to or shorter than the logging interval.16.The wireless device of claim 14,wherein the logging interval is a reporting interval.17.The wireless device of claim 14,wherein the logging duration is configured within every logging interval.18.The wireless device of claim 14, wherein the operations further comprising:skipping data logging outside the logging duration.19.The wireless device of claim 14, wherein the operations further comprising:transmitting a reporting message including logged information upon expiration of the logging interval.20.The wireless device of claim 14, wherein the operations further comprising:initiating a new logging interval upon expiration of the logging interval.21.The wireless device of claim 14,wherein the configuration for data logging further includes (i) at least one measurement object, (ii) at least one reporting configuration, and (iii) at least one measurement identity.22.The wireless device of claim 14, wherein the operations further comprising:receiving a reporting configuration including (i) information related to a reporting interval, (ii) information related to a reporting amount, and (iii) information related to at least one reporting condition.23.The wireless device of claim 14, wherein the operations further comprising:logging layer 1 (L1) measurement results based on the logging duration.24.The wireless device of claim 14,wherein the data logging includes logging (i) measurement results, (ii) a measurement identity related to the measurement results, and (iii) time information related to the measurement results.25.The wireless device of claim 14,wherein the data logging is based on layer 1 measurements for the at least one reference signal.26.The wireless device of claim 14,wherein the wireless device is in communication with at least one of a user equipment, a network, or an autonomous vehicle other than the wireless device.27.A processor for a wireless device in a wireless communication system, wherein the processor is configured to control the wireless device to perform operations comprising:receiving a configuration for data logging,wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval; andperforming data logging based on the logging duration,wherein the logging duration is configured within the logging interval.28.A non-transitory computer-readable medium having stored thereon a plurality of instructions, which, when executed by a processor of a wireless device, cause the wireless device to perform operations, the operations comprises,receiving a configuration for data logging,wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval; andperforming data logging based on the logging duration,wherein the logging duration is configured within the logging interval.29.A method, comprising,transmitting, by a base station to a wireless device, a configuration for data logging,wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval,wherein the wireless device performs data logging based on the logging duration, andwherein the logging duration is configured within the logging interval.30.A base station, comprising:a transceiver;a memory; anda processor operatively coupled to the transceiver and the memory, and adapted to perform operations, the operations comprising:transmitting, to a wireless device, a configuration for data logging,wherein the configuration includes (i) information related to a logging duration and (ii) information related to a logging interval,wherein the wireless device performs data logging based on the logging duration, andwherein the logging duration is configured within the logging interval.

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