Method and apparatus for nonlinearity compensation in wireless communication system

Abstract

The present disclosure relates to a 5G or 6G communication system for supporting higher data transfer rates than a 4G communication system, such as LTE. According to an embodiment of the present disclosure, provided is a method performed by a base station of a wireless communication system. The method comprises the steps of: transmitting a nonlinearity measurement request message; transmitting at least one of a pilot signal and data; receiving, on the basis of at least one of the pilot signal and the data, a nonlinearity measurement report message including information about nonlinearity measurement results; and determining a supportable modulation and coding scheme (MCS) level on the basis of the information about the nonlinearity measurement results.

Description

Method and device for compensating nonlinearity in wireless communication systems

[0001] The present disclosure relates to a wireless communication system. More specifically, the present disclosure relates to a method and device for measuring and compensating for nonlinearity occurring when a base station transmits a signal.

[0002] To meet the growing demand for wireless data traffic following the commercialization of 4G (4th generation) communication systems, efforts are being made to develop 5G (5th generation) communication systems, or pre-5G communication systems. For this reason, 5G communication systems, or pre-5G communication systems, are also referred to as "Beyond 4G Network" communication systems or "Post-LTE" systems.

[0003] To achieve high data rates, 5G communication systems are being considered for implementation in ultra-high frequency (mmWave) bands (e.g., the 60 GHz band). To mitigate radio path loss and increase the transmission range of radio waves in ultra-high frequency bands, beamforming, massive MIMO (massive MIMO), full-dimensional MIMO (FD-MIMO), array antennas, analog beamforming, and large-scale antenna technologies are being discussed in 5G communication systems. In addition, to improve the network of the system, technologies such as evolved small cells, advanced small cells, cloud Radio Access Network (cloud RAN), ultra-dense networks, device-to-device communication (D2D), wireless backhaul, moving networks, cooperative communication, CoMP (Coordinated Multi-Points), and interference cancellation are being developed in 5G communication systems.In addition, advanced coding modulation (ACM) methods such as hybrid FSK and QAM modulation (FQAM) and sliding window superposition coding (SWSC), as well as advanced access technologies such as Filter Bank Multi Carrier (FBMC), Non-Orthogonal Multiple Access (NOMA), and Sparse Code Multiple Access (SCMA) are being developed in 5G systems.

[0004] Meanwhile, 5G communication systems must be able to freely reflect the diverse needs of users and service providers, requiring services that simultaneously satisfy these requirements. Services being considered for 5G communication systems include enhanced Mobile Broadband (eMBB), massive Machine Type Communication (mMTC), and Ultra-Reliable Low-Latency Communication (URLLC).

[0005] eMBB aims to provide data transmission rates that are significantly higher than those supported by existing LTE, LTE-A, or LTE-Pro. For example, in a 5G communication system, eMBB must be able to support a peak data rate of 20 Gbps in the downlink and a peak data rate of 10 Gbps in the uplink from the perspective of a single base station. Furthermore, 5G communication systems must provide not only the peak data rate but also the increased user-perceived data rate for terminals. To meet these requirements, improvements in various transmission and reception technologies, including improved multi-antenna transmission technologies, are required. Furthermore, while current LTE transmits signals using a maximum transmission bandwidth of 20 MHz in the 2 GHz band, 5G communication systems can meet the data transmission rates required by 5G communication systems by utilizing a wider frequency bandwidth than 20 MHz in the 3-6 GHz or higher 6 GHz band.

[0006] At the same time, mMTC is being considered to support application services such as the Internet of Things (IoT) in 5G communication systems. To efficiently provide the Internet of Things, mMTC requires support for connection of a large number of terminals within a cell, improved terminal coverage, improved battery life, and reduced terminal costs. The Internet of Things provides communication functions by attaching various sensors and various devices, so a large number of terminals (e.g., 1,000,000 terminals / km) are required within a cell. 2) must be able to support. In addition, terminals supporting mMTC are likely to be located in shadow areas that cells cannot cover, such as basements of buildings, due to the nature of the service, and therefore require wider coverage than other services provided by 5G communication systems. Terminals supporting mMTC must be composed of low-cost terminals, and since it is difficult to frequently replace the terminal's battery, a very long battery life time, such as 10 to 15 years, is required.

[0007] Finally, URLLC refers to cellular-based wireless communication services used for specific mission-critical purposes. Examples include remote control of robots or machinery, industrial automation, unmanned aerial vehicles (UAVs), remote health care, and emergency alerts. Therefore, URLLC communications must offer extremely low latency and high reliability. For example, services supporting URLLC must meet air interface latency requirements of less than 0.5 milliseconds and a packet error rate of less than 10-5. Therefore, for services supporting URLLC, 5G communication systems must provide a shorter Transmit Time Interval (TTI) than other services, while simultaneously allocating extensive resources in the frequency band to ensure communication link reliability.

[0008] Looking back at the evolution of wireless communication over successive generations, technologies have primarily been developed for human-facing services such as voice, multimedia, and data. With the commercialization of 5G (5th-generation) communication systems, an explosive increase in connected devices is expected to be connected to communication networks. Examples of networked objects include vehicles, robots, drones, home appliances, displays, smart sensors installed in various infrastructures, construction equipment, and factory equipment. Mobile devices are also expected to evolve into diverse form factors, such as augmented reality glasses, virtual reality headsets, and holographic devices. In the 6th-generation (6G) era, efforts are being made to develop improved 6G communication systems to connect hundreds of billions of devices and objects and provide diverse services. For this reason, 6G communication systems are often referred to as "Beyond 5G."

[0009] The 6G communication system, expected to be realized around 2030, will have a maximum transmission speed of terabytes per second (1,000 gigabits per second) and a wireless latency of 100 microseconds (μsec). This means that compared to 5G, the transmission speed in a 6G communication system will be 50 times faster, while the wireless latency will be reduced to one-tenth.

[0010] To achieve these high data rates and ultra-low latency, 6G communication systems are being considered for implementation in terahertz bands (e.g., from 95 gigahertz (GHz) to 3 terahertz (THz)). In the terahertz band, compared to the millimeter wave (mmWave) band introduced in 5G, the importance of technologies that can guarantee signal reach, or coverage, is expected to increase. Key technologies for ensuring coverage include radio frequency (RF) components, antennas, new waveforms that are superior to OFDM (orthogonal frequency division multiplexing) in terms of coverage, beamforming, and multi-antenna transmission technologies such as MIMO, FD-MIMO, array antennas, and large-scale antennas. In addition, new technologies such as metamaterial-based lenses and antennas, high-dimensional spatial multiplexing technology using orbital angular momentum (OAM), and reconfigurable intelligent surfaces (RIS) are being discussed to improve the coverage of terahertz band signals.

[0011] In addition, in order to improve frequency efficiency and system network, 6G communication systems are being developed with full duplex technology that allows uplink (UL) and downlink (DL) to utilize the same frequency resources at the same time; network technology that integrates satellites and high-altitude platform stations (HAPS); network structure innovation technology that supports mobile base stations and enables optimization and automation of network operation; dynamic spectrum sharing technology through collision avoidance based on spectrum usage prediction; AI-based communication technology that utilizes artificial intelligence (AI) from the design stage and internalizes end-to-end AI support functions to realize system optimization; and next-generation distributed computing technology that realizes services with complexity that exceeds the limits of terminal computing capabilities by utilizing ultra-high-performance communication and computing resources (mobile edge computing (MEC), cloud, etc.). In addition, efforts are being made to further strengthen connectivity between devices, further optimize networks, promote softwareization of network entities, and increase the openness of wireless communications through the design of new protocols to be used in 6G communication systems, the implementation of hardware-based security environments, the development of mechanisms for the safe use of data, and the development of technologies for maintaining privacy.

[0012] Research and development of these 6G communication systems are expected to enable a new level of hyper-connected experience through the hyper-connectivity of 6G communication systems, which encompass not only connections between things but also connections between people and things. Specifically, 6G communication systems are expected to enable services such as truly immersive extended reality (XR), high-fidelity mobile holograms, and digital replicas. Furthermore, services such as remote surgery, industrial automation, and emergency response, which are provided through 6G communication systems through enhanced security and reliability, will be applied in diverse fields such as industry, medicine, automobiles, and home appliances.

[0013] Satisfying these diverse services requires a wide bandwidth. This has led to research into previously unused high bandwidths, leading to research in mmWave and THz for 5G and future 6G communication systems. However, ultra-high frequency bands suffer from severe path loss, resulting in limited coverage. This issue necessitates the installation of too many base stations, resulting in significant initial capital expenditures (CAPEX).

[0014] Various technologies have been proposed to address the aforementioned coverage issues. One such method involves utilizing a power amplifier (PA) to transmit at higher output power. However, in the high-power range of the PA, nonlinearities that distort the phase and amplitude of the transmitted signal appear. Therefore, additional technologies are required to compensate for this nonlinearity in order to utilize the PA at high power levels.

[0015] To utilize a PA at high output, a representative technique is digital pre-distortion (DPD) at the transmitter. DPD predicts the PA's distortion in advance and distorts the transmitted signal before passing it to the PA. Therefore, accurately predicting the PA's nonlinearity is crucial. However, because the PA's nonlinearity tends to change over time and with the surrounding environment, the DPD algorithm requires time to update the coefficients used when such changes are detected.

[0016] Meanwhile, the Internet is evolving from a human-centric network where humans create and consume information to an IoT network where information is exchanged and processed between distributed components, such as objects. The Internet of Everything (IoE) is also emerging, combining IoT technologies with big data processing technologies, such as those connected to cloud servers. To implement the IoT, technological elements such as sensing technologies, wireless and wired communication and network infrastructure, service interface technologies, and security technologies are required. Recently, research is being conducted on technologies such as sensor networks, machine-to-machine (M2M) communication, and MTC for connecting objects. In the IoT environment, intelligent IoT services can be provided that collect and analyze data generated from connected objects to create new value in human lives. The IoT can be applied to areas such as smart homes, smart buildings, smart cities, smart or connected cars, smart grids, healthcare, smart appliances, and advanced medical services through the convergence and integration of existing Information Technology (IT) technologies with various industries.

[0017] As described above, with the development of mobile communication systems, a variety of services can be provided, and thus, the need for an efficient method to compensate for the nonlinearity of PA has emerged as a means of improving data reception performance and increasing coverage.

[0018] According to one embodiment of the present disclosure, a method performed by a base station of a wireless communication system is provided. The method may include the steps of transmitting a nonlinearity measurement request message, transmitting at least one of a pilot signal and data, receiving a nonlinearity measurement report message including information on a nonlinearity measurement result based on at least one of the pilot signal and data, and determining a supportable modulation and coding scheme (MCS) level based on the information on the nonlinearity measurement result.

[0019] According to one embodiment of the present disclosure, a method performed by a terminal of a wireless communication system is provided. The method may include the steps of receiving a nonlinearity measurement request message, receiving at least one of a pilot signal and data, and transmitting a nonlinearity measurement report message including information on a nonlinearity measurement result based on at least one of the pilot signal and data. The information on the nonlinearity measurement result may be associated with an MCS level supported by a base station.

[0020] According to one embodiment of the present disclosure, a base station of a wireless communication system is provided. The base station may include a transceiver and a control unit. The control unit controls the transceiver to transmit a nonlinearity measurement request message, controls the transceiver to transmit at least one of a pilot signal and data, controls the transceiver to receive a nonlinearity measurement report message including information on a nonlinearity measurement result based on at least one of the pilot signal and data, and determines a supportable MCS level based on the information on the nonlinearity measurement result.

[0021] According to one embodiment of the present disclosure, a terminal of a wireless communication system is provided. The terminal may include a transceiver and a control unit. The control unit may control the transceiver to receive a nonlinearity measurement request message, control the transceiver to receive at least one of a pilot signal and data, and control the transceiver to transmit a nonlinearity measurement report message including information on a nonlinearity measurement result based on at least one of the pilot signal and data. The information on the nonlinearity measurement result may be associated with an MCS level that can be supported by a base station.

[0022] According to the present disclosure, the degree of nonlinearity occurring when a base station transmits a signal is measured with the help of a terminal, and the terminal selectively applies a nonlinearity compensation technique depending on the degree of nonlinearity, thereby more efficiently compensating for the nonlinearity of a PA.

[0023] The effects that can be obtained from the present disclosure are not limited to the effects mentioned above, and other effects that are not mentioned will be clearly understood by a person having ordinary skill in the art to which the present disclosure pertains from the description below.

[0024] FIG. 1 is a diagram illustrating a next-generation communication system according to one embodiment of the present disclosure.

[0025] FIG. 2 is a diagram illustrating signal distortion due to nonlinearity characteristics of a PA according to one embodiment of the present disclosure.

[0026] FIG. 3 is a diagram illustrating a DPD model according to one embodiment of the present disclosure.

[0027] FIG. 4 is a diagram illustrating a receiving path of a receiver including an AI-based nonlinearity compensation block according to one embodiment of the present disclosure.

[0028] FIG. 5 is a diagram illustrating an example of AI-based nonlinearity compensation according to one embodiment of the present disclosure.

[0029] FIG. 6 is a diagram illustrating a situation in which a DPD update is required in a base station including multiple antennas according to one embodiment of the present disclosure.

[0030] FIG. 7 is a sequence diagram illustrating a procedure for a terminal to measure nonlinearity at the request of a base station according to one embodiment of the present disclosure.

[0031] FIG. 8 is a sequence diagram illustrating a procedure for acquiring nonlinearity measurement-related capability information of a terminal upon initial connection according to one embodiment of the present disclosure.

[0032] FIG. 9 is a sequence diagram illustrating a procedure for compensating nonlinearity in a terminal when a nonlinearity problem occurs in a signal transmitted by a base station according to one embodiment of the present disclosure.

[0033] FIG. 10 is a diagram illustrating a processing time for performing a DPD update at a base station according to one embodiment of the present disclosure.

[0034] FIG. 11 is a diagram illustrating a procedure for a base station to designate a time for performing nonlinearity compensation on a terminal according to one embodiment of the present disclosure.

[0035] FIG. 12 is a diagram illustrating a procedure for updating a time at which a base station performs nonlinearity compensation on a terminal according to one embodiment of the present disclosure.

[0036] FIG. 13 is a sequence diagram illustrating a procedure for activating / deactivating signaling-based nonlinearity compensation according to one embodiment of the present disclosure.

[0037] FIG. 14 is a sequence diagram illustrating a procedure for activating / deactivating signaling-based nonlinearity compensation according to one embodiment of the present disclosure.

[0038] FIG. 15 is a sequence diagram illustrating a procedure for activating / deactivating signaling-based nonlinearity compensation according to one embodiment of the present disclosure.

[0039] FIG. 16 is a sequence diagram illustrating a procedure for activating / deactivating signaling-based nonlinearity compensation according to one embodiment of the present disclosure.

[0040] FIG. 17 is a flowchart illustrating the operation of a base station according to one embodiment of the present disclosure.

[0041] FIG. 18 is a flowchart illustrating the operation of a terminal according to one embodiment of the present disclosure.

[0042] FIG. 19 is a block diagram illustrating a terminal according to an embodiment of the present disclosure.

[0043] FIG. 20 is a block diagram illustrating a base station according to an embodiment of the present disclosure.

[0044] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the attached drawings.

[0045] In describing the embodiments, descriptions of technical contents that are well known in the technical field to which the present disclosure belongs and are not directly related to the present disclosure are omitted.

[0046] This is to convey the gist of the present disclosure more clearly without obscuring it by omitting unnecessary explanations.

[0047] For the same reason, some components in the attached drawings are exaggerated, omitted, or schematically depicted. Furthermore, the dimensions of each component do not entirely reflect its actual size. Identical or corresponding components in each drawing are assigned the same reference numbers.

[0048] The advantages and features of the present disclosure and the methods for achieving them will become apparent with reference to the embodiments described in detail below together with the accompanying drawings.

[0049] However, the present disclosure is not limited to the embodiments disclosed below and may be implemented in various different forms. These embodiments are provided only to complete the composition of the present disclosure and to fully inform those skilled in the art of the present disclosure of the scope of the invention, and the present disclosure is defined only by the scope of the claims. Like reference numerals refer to like elements throughout the specification.

[0050] At this time, it will be understood that each block of the processing flow diagrams and combinations of the flow diagrams can be performed by computer program instructions. These computer program instructions can be installed in a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing equipment, so that the instructions executed by the processor of the computer or other programmable data processing equipment create a means for performing the functions described in the flow diagram block(s). These computer program instructions can also be stored in a computer-available or computer-readable memory that can be directed to a computer or other programmable data processing equipment for implementation in a specific manner, so that the instructions stored in the computer-available or computer-readable memory can also produce a manufactured item that includes an instruction means for performing the functions described in the flow diagram block(s). Since the computer program instructions can also be installed on a computer or other programmable data processing device, a series of operational steps can be performed on the computer or other programmable data processing device to create a computer-executable process, and the instructions that cause the computer or other programmable data processing device to perform the steps for performing the functions described in the flowchart block(s) can also provide steps for performing the functions described in the flowchart block(s).

[0051] Additionally, each block may represent a module, segment, or portion of code that contains one or more executable instructions for performing a specific logical function(s). It should also be noted that in some alternative implementation examples, the functions described in the blocks may occur out of order. For example, two blocks depicted in succession may actually be executed substantially concurrently, or the blocks may sometimes be executed in reverse order, depending on their respective functions.

[0052] Here, the term '~ part' used in the present disclosure means a software or hardware component such as an FPGA or ASIC, and the '~ part' performs certain roles. However, the '~ part' is not limited to software or hardware. The '~ part' may be configured to be on an addressable storage medium, and may be configured to play one or more processors. Accordingly, as an example, the '~ part' includes components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided within the components and '~ parts' may be combined into a smaller number of components and '~ parts' or further separated into additional components and '~ parts'. Additionally, components and '~parts' may be implemented to regenerate one or more CPUs within a device or secure multimedia card.

[0053] For the convenience of the following explanation, some terms and names defined in the 3rd generation partnership project (3GPP) standards (standards for 5G, NR, LTE (Long term evolution), or similar systems) may be used. In addition, terms and names newly defined in the next-generation communication system to which the present disclosure can be applied (e.g., 6G, Beyond 5G systems) or used in existing communication systems may be used. The use of such terms is not limited to the terms and names of the present disclosure, and may be equally applied to systems that comply with other standards, and may be changed into other forms without departing from the technical spirit of the present disclosure.

[0054] Additionally, it will be understood that singular expressions such as “a” and “the above” include plural expressions unless they clearly indicate otherwise in one embodiment of the present disclosure.

[0055] Additionally, in one embodiment of the present disclosure, terms including ordinal numbers, such as "first" and "second," may be used to describe various components, but the components are not limited by these terms. These terms are used solely to distinguish one component from another. For example, without departing from the scope of the present disclosure, a first component could be referred to as a "second component," and similarly, a second component could also be referred to as a "first component."

[0056] Additionally, in one embodiment of the present disclosure, the term and / or includes a combination of a plurality of related described items or any one of a plurality of related described items.

[0057] In addition, the terms used in the embodiments of the present disclosure are only used to describe specific embodiments and are not intended to limit the present disclosure. The singular expression includes the plural expression unless the context clearly indicates otherwise. In this specification, it should be understood that the terms “comprise” or “have” are intended to specify the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, but do not exclude in advance the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0058] Additionally, in the present disclosure, expressions such as "more than" and "less than" are used to determine whether a specific condition is satisfied or fulfilled. However, this is merely a description to express an example and does not exclude descriptions of more than or less than. Conditions described as "more than" may be replaced with "more than," conditions described as "less than" may be replaced with "less than," and conditions described as "more than and less than" may be replaced with "more than and less than."

[0059] Before delving into the detailed description of this disclosure, examples of possible interpretations of some terms used herein are provided. However, it should be noted that the interpretations provided below are not limited to these examples.

[0060] In the present disclosure, a terminal (or communication terminal) is an entity that communicates with a base station or another terminal, and may be referred to as a node, UE (User equipment), NG UE (Next generation UE), MS (Mobile station), device, or terminal. In addition, the terminal may include at least one of a smartphone, a tablet PC, a mobile phone, a video phone, an e-book reader, a desktop PC, a laptop PC, a netbook computer, a PDA, a PMP (Portable multimedia player), an MP3 player, a medical device, a camera, or a wearable device. In addition, the terminal may include at least one of a television, a DVD (Digital video disk) player, an audio player, a refrigerator, an air conditioner, a vacuum cleaner, an oven, a microwave oven, a washing machine, an air purifier, a set-top box, a home automation control panel, a security control panel, a media box, a game console, an electronic dictionary, an electronic key, a camcorder, or an electronic picture frame.In addition, the terminal may include at least one of various medical devices (e.g., various portable medical measuring devices (such as blood glucose meters, heart rate monitors, blood pressure monitors, or body temperature monitors), magnetic resonance angiography (MRA), magnetic resonance imaging (MRI), computed tomography (CT), cameras, or ultrasound machines), navigation devices, global navigation satellite systems (GNSS), event data recorders (EDR), flight data recorders (FDR), automotive infotainment devices, electronic equipment for ships (such as marine navigation devices, gyrocompasses, etc.), avionics, security devices, head units for vehicles, industrial or home robots, drones, ATMs for financial institutions, POSs (Point of Sales) for stores, or Internet of Things devices (such as light bulbs, various sensors, sprinkler devices, fire alarms, thermostats, streetlights, toasters, exercise equipment, hot water tanks, heaters, boilers, etc.). Additionally, the terminal may include various types of multimedia systems capable of performing communication functions. Meanwhile, the present disclosure is not limited to the above description, and the terminal may also be referred to by terms having the same or similar meaning.

[0061] In addition, in the present disclosure, the base station communicates with the terminal and is an entity that performs resource allocation of the terminal, and may have various forms and may be referred to as a BS (Base Station), a NodeB (NB), an NG RAN (Next generation radio access network), an AP (Access Point), a TRP (Transmission and Reception Point), a satellite base station, a wireless access unit, a base station controller, or a node on a network. Alternatively, it may be referred to as a CU (Central Unit) or a DU (Distributed Unit) depending on functional separation. Meanwhile, the present disclosure is not limited thereto, and the base station may be referred to by a term having the same or similar meaning.

[0062] In addition, in the present disclosure, control information may be referred to as a control message, control signaling, or MAC (Medium access control)-CE (Control element), DCI (Downlink control information), UCI (Uplink control information), or RRC (Radio resource control) message depending on the context, and the present disclosure is not limited thereto, and may also be referred to by terms having the same or similar meaning.

[0063] Additionally, in the present disclosure, the transmitting end may be referred to as a transmitter or a first device, and may mean a terminal in the case of uplink, and a base station in the case of downlink.

[0064] Additionally, in the present disclosure, the receiving end may be referred to as a receiver or a second device, and may mean a base station in the case of uplink, and a terminal in the case of downlink.

[0065] FIG. 1 is a diagram illustrating a next-generation communication system according to one embodiment of the present disclosure.

[0066] Referring to Figure 1, a next-generation communication system may be comprised of a next-generation base station (1-10) and a next-generation core network (CN) (1-05). A next-generation terminal (1-15) may access an external network through the next-generation base station (1-10) and the next-generation core network (1-05).

[0067] In Fig. 1, the next-generation base station (1-10) may perform a role corresponding to an eNB of an existing LTE communication system or an NR base station (gNB) of an NR communication system. Alternatively, in embodiments of the present disclosure, the next-generation base station (1-10) may refer to an LTE base station or an NR base station. The next-generation base station (1-10) may be connected to a terminal (1-15) via a wireless channel and may provide a communication service superior to that of an existing Node B. The next-generation core network (1-05) may perform a role corresponding to an NR core network of an NR communication system. In addition, the next-generation communication system to which the present disclosure may be applied may be interoperable with an existing LTE communication system or an NR communication system. When interoperable with an LTE communication system, the next-generation base station may be connected to an MME (mobility management entity) (1-25) via a network interface, and the MME may be connected to an eNB (1-30), which is an existing LTE base station. Alternatively, when interworking with an NR communication system, it may be connected to an NR core network (1-25) via a network interface, and the NR core network (1-25) may be connected to an NR base station (1-30). Meanwhile, the next-generation communication system to which the present disclosure may be applied is not limited to that illustrated in FIG. 1. The above-described next-generation communication system may be implemented through base stations, terminals, and core networks having various forms, and the present disclosure may also be applied in such cases.

[0068] In the communication system of the present disclosure, a signal can be transmitted by increasing the transmission power through a PA at the transmitter for purposes such as increasing coverage. However, there is a problem that signal distortion occurs due to the nonlinear characteristics of the PA. This will be described in detail below with reference to FIG. 2.

[0069] FIG. 2 is a diagram illustrating signal distortion due to nonlinearity characteristics of a PA according to one embodiment of the present disclosure.

[0070] Referring to Fig. 2, in a region where the power of the signal input to the PA (input power) is small (small signal region), as the input power (PAin) increases, the power of the signal output from the PA (output power, PAout) increases in proportion to the power gain value (G) of the PA, which exhibits linearity. However, in a region where the input power of the PA is high, the power of the signal output from the PA (PAout) is not amplified by the power gain value (G), and nonlinearity occurs in which the phase or amplitude is distorted.

[0071] In this way, due to the nonlinearity in which the phase and intensity of the signal are distorted in the high-power region, the Error Vector Magnitude (EVM) of the transmitted data symbol may increase and the data reception performance may deteriorate. Meanwhile, in order to avoid the signal distortion problem caused by the nonlinearity of the PA, a method of limiting the operating range of the PA to a linear section by applying an output back-off has also been proposed. However, although the output back-off method can reduce the EVM of the transmitted symbol, it can cause coverage loss because the transmitted output is limited as a result.

[0072] FIG. 3 is a diagram illustrating a DPD model according to one embodiment of the present disclosure.

[0073] In next-generation communication systems such as 6G, a method of utilizing the high-power range of the PA as it is and compensating for nonlinearity in advance by utilizing DPD at the transmitter end has been considered.

[0074] Referring to Figure 3, is the original input signal before DPD is applied, silver This is a signal that has passed through DPD, silver This is the amplified signal through the PA. is used as the input of the DPD model by multiplying by 1 / G, which is the reciprocal of the gain value (G) of the PA, and the output of the DPD model is can be expressed as . Here, the estimation error is If defined as above, is represented in vector format for N sample blocks. About, The coefficients of the DPD model can be derived so that the value is minimized.

[0075] As an example of the above DPD model, the GMP (general memory polynomial) model can be expressed as shown in the following mathematical expression 1.

[0076] [Mathematical Formula 1]

[0077]

[0078] Here, a specific time instance About is the output value of the GMP model, silver The input signal of the GMP model is delayed by the sample, , and are the coefficients that must be determined. , , , , , , , and are preset integer values ​​that determine the order, complexity, and memory depth of the GMP model.

[0079] However, the scope of the present disclosure is not limited to the above-described GMP model, and various other models may be used.

[0080] FIG. 4 is a diagram illustrating a receiving path of a receiver including an AI-based nonlinearity compensation block according to one embodiment of the present disclosure.

[0081] Referring to FIG. 4, the signal reception path of the receiver may include an LNA (low noise amplifier) ​​block, an ADC (analog to digital converter) block, a Sync block, a CP (cyclic prefix) removal and FFT (fast Fourier transform) block, a Pre-EQ (pre-equalization) block, an IFFT (inverse fast Fourier transform) block, a TD-ESN (time domain based echo state network) block, an FFT (fast Fourier transform) block, a demodulation block, and a channel decoding block. Here, a set of the IFFT block, the TD-ESN block, and the FFT block may be referred to as an AI-based non-linearity compensator (AI-NC).

[0082] The specific operation of each block is described below. The LNA block can amplify the received RF signal. The ADC block can convert the analog signal to a digital signal. The Sync block can perform signal synchronization. The CP removal and FFT block can remove the CP and convert the time domain signal to a frequency domain signal through FFT. The Pre-EQ block can perform channel estimation and channel equalization based on the frequency domain signal. Afterwards, the IFFT block can convert the signal with channel EQ applied to it into a time domain signal through IFFT. The TD-ESN block can perform nonlinearity compensation on the time domain signal. For example, the TD-ESN block can obtain nonlinearity information indicating signal distortion caused by the nonlinearity of the PA used in the transmitter, and perform nonlinearity compensation on the time domain signal based on the nonlinearity information.

[0083] For example, the TD-ESN block can perform AI-based nonlinearity compensation. The TD-ESN block can train the AI ​​model by inputting the pilot portion of the signal with channel EQ applied to the AI ​​model and optimizing the objective function (e.g., minimizing the loss function or maximizing the utility function) for the difference between the output from the AI ​​model (the value predicted by the pilot received by the receiver) and the transmission pattern of the pilot provided by the transmitter to the receiver. In other words, the TD-ESN block can train the AI ​​model by inputting a pilot distorted due to the nonlinearity of the PA into the AI ​​model and optimizing the value predicted by the AI ​​model to be close to the transmission pattern of the corresponding pilot. Thereafter, the TD-ESN block can obtain data with the PA nonlinearity compensated for (i.e., data with the distortion due to the nonlinearity of the PA removed) as the output value of the AI ​​model by inputting the data portion of the signal with channel EQ applied to the trained AI model. Here, the AI ​​model can be implemented by AI-related algorithms including ESN (echo state network).

[0084] The signal compensated for the nonlinearity of the PA can be converted into a frequency domain signal through the FFT block, and the modulated symbol can be demodulated and decoded through the demodulation block and channel decoding block to restore the original input data stream.

[0085] Meanwhile, some of the blocks illustrated in FIG. 4 may be omitted, and one block may perform the functions of another block. Furthermore, each component illustrated in FIG. 4 may be implemented using only hardware or a combination of hardware and software / firmware. For example, at least some of the components illustrated in FIG. 4 may be implemented using software, while other components may be implemented using configurable hardware or a combination of software and configurable hardware. For example, the FFT block and the IFFT block may be implemented using configurable software algorithms. Furthermore, although the FFT and IFFT have been described as being used, this is merely an example and does not limit the scope of the present disclosure. Accordingly, other types of transforms, such as the Discrete Fourier Transform (DFT) and the Inverse Discrete Fourier Transform (IDFT), may be used.

[0086] FIG. 5 is a diagram illustrating an example of AI-based nonlinearity compensation according to one embodiment of the present disclosure.

[0087] As described above, the transmitter transmits a signal by amplifying the transmission power through the PA, and the receiver can receive the signal and apply channel EQ. However, as illustrated in FIG. 5A, there is distortion in the phase or amplitude of the signal to which the channel EQ is applied due to the nonlinearity of the PA. Therefore, the receiver can perform nonlinearity compensation on the signal to which the channel EQ is applied. The receiver can input the pilot (e.g., DMRS) portion of the signal to which the channel EQ is applied into an AI model, and train the AI ​​model so that the value predicted by the AI ​​model has a small error with the pilot's transmission pattern (i.e., a signal predefined between the transmitter and receiver and before the transmitter uses the PA). Thereafter, the receiver can input the data portion of the signal to which the channel EQ is applied into the AI ​​model, and obtain data with the nonlinearity compensated.

[0088] Referring to Figure 5B, it can be seen that the signal with the PA nonlinearity compensated is more similar to the signal before the PA is used at the transmitter than the signal with only channel EQ applied. Therefore, data reception performance can be improved by compensating for the PA nonlinearity at the receiver.

[0089] Meanwhile, DPD requires a step to adjust the DPD algorithm coefficients by predicting the PA's nonlinearity based on past information. Therefore, in environments where the PA's nonlinearity significantly changes, the predicted DPD algorithm coefficients can become inaccurate. This can increase transmission signal distortion and degrade EVM performance.

[0090] To detect changes in the PA nonlinearity, the base station can sample the signal passed through the PA to determine whether the DPD is functioning properly. If the DPD is determined to be not functioning properly, the DPD algorithm can be changed, or the coefficients within the same DPD algorithm can be changed. In order to obtain the coefficients of a new DPD algorithm, a delay may occur proportional to the number of coefficients used in the algorithm, and during this delay, the quality of the transmitted signal after passing through the PA may be lower than usual. When the quality of the transmitted signal is degraded as described above, if a modulation signal with a high modulation order (e.g., 1024-QAM, 4096-QAM, or higher) is also used, such as in 6G communication systems, the signal transmitted by the base station must satisfy the EVM requirements for each modulation order. However, there is a problem that it is difficult for the base station to determine on its own whether the EVM requirements are satisfied in a situation where the quality of the transmitted signal is degraded. Therefore, in the conventional technology, when a high modulation order modulation signal is used in a situation like the above, the modulation order is sequentially lowered after repeated transmission failures.

[0091] In this disclosure, we aim to solve problems that may arise in the above conventional technology from two major viewpoints.

[0092] The first is to accurately determine the maximum modulation order that the base station can use when the quality of the transmitted signal deteriorates at the base station's PA, thereby preventing unnecessary transmission failures. The second is to activate an additional nonlinearity compensation process at the terminal when the quality of the transmitted signal deteriorates at the base station's PA, thereby improving the signal quality at the receiving end.

[0093] FIG. 6 is a diagram illustrating a situation in which a DPD update is required in a base station including multiple antennas according to one embodiment of the present disclosure.

[0094] Referring to FIG. 6, the base station (1-10) may use a multiple antenna structure capable of supporting a Massive MIMO (Multiple-Input Multiple-Output) transmission / reception technique, and multiple PAs may exist to support this.

[0095] The base station (1-10) can detect that a nonlinearity problem has occurred in some of the multiple PAs and thus requires a DPD update. However, as explained above, the base station (1-10) may have difficulty estimating the extent to which such nonlinearity problem affects the reception performance of the receiving end (i.e., the terminal (1-15)).

[0096] Accordingly, the base station (1-10) requests a nonlinearity measurement from the terminal (1-15), receives the measurement results, and based on the results, adjusts the MCS (modulation and coding scheme) level that can be supported while updating the DPD. More specific operations are described in FIG. 7 below.

[0097] FIG. 7 is a sequence diagram illustrating a procedure for a terminal to measure nonlinearity at the request of a base station according to one embodiment of the present disclosure.

[0098] At step S700, the base station (1-10) can identify that a DPD update is required for the PA(s). For example, in a transmitter with n PAs, if the PA characteristics of PAs a, b, and c change, the coefficients of the DPD blocks supporting the corresponding PAs may not have been updated yet, or the nonlinearity of the PAs may be less well controlled than before due to a specific cause.

[0099] In step S702, the base station (1-10) can set a supportable MCS level appropriate for the current situation based on predetermined rules. For example, the base station (1-10) can set the maximum supportable MCS level based on past information, or, in situations where past information does not exist, can set the maximum supportable MCS level based on the number of PAs requiring DPD updates. For example, the maximum supportable MCS level based on the number of PAs requiring DPD updates can be determined as shown in [Table 1] below.

[0100] Number of PAs requiring DPD updates Maximum supported MCS levels 04096 QAM 1, 2, 31024 QAM and above 256 QAM

[0101] At step S704, the base station (1-10) may transmit a message (e.g., NL Measurement Request) requesting nonlinearity measurement to the terminal (1-15). Meanwhile, in a cell environment where multiple terminals exist, the base station (1-10) may select the terminal(s) for which to request nonlinearity (NL) measurement. For example, the base station (1-10) may select the terminal(s) based on one or a combination of the following methods.

[0102] 1) Round robin extraction

[0103] 2) Random sampling

[0104] 3) Extract the current DL data by sorting it in order of the largest number.

[0105] 4) Extraction using round robin method from terminals where DL data currently exists

[0106] 5) Randomly select terminals that currently have DL data.

[0107] 6) Sort and extract the current channel status in order of best to worst.

[0108] 7) Round robin extraction from terminals whose current channel status is above a certain level

[0109] 8) Randomly select terminals whose current channel status is above a certain level.

[0110] Here, methods 1)-2) have the advantage of not increasing the complexity of the base station. Methods 3)-5) have the advantage of eliminating the need for the base station to allocate and transmit additional data and pilot signals for NL measurements if terminals with existing DL data are selected. Methods 6)-8) have the advantage of providing more accurate nonlinearity measurement results, as terminals with good channel conditions are relatively advantageous in nonlinearity measurements.

[0111] At step S706, the terminal (1-15) can transmit a response (e.g., NL Measurement Acknowledgment) to the message requesting the nonlinearity measurement to the base station (1-10).

[0112] At step S708, the base station (1-10) may transmit a pilot signal and / or data to the terminal (1-15). For example, if there is no DL data to transmit to the current terminal (1-15), separate data and / or pilot signals defined in advance for NL measurement may be transmitted. The separate data and / or pilot signals for this purpose may be defined as follows.

[0113] 1) Data and / or pilot signals having globally unique sequences or time-frequency resources are defined in the system, and the base station can always transmit the same data and / or pilot signals when requesting NL measurement without additional signal exchange with the terminal.

[0114] 2) When each terminal connects to the base station, the base station checks capability information on whether the terminal is capable of NL measurement, and if it is determined that the terminal is capable of NL measurement, the base station can set information on cell-specific data and / or pilot signals.

[0115] 3) When each terminal connects to the base station, the base station checks capability information on whether the terminal is capable of NL measurement, and if it is determined that the terminal is capable of NL measurement, the base station can set information on UE-specific data and / or pilot signals.

[0116] 4) A formula for forming globally unique data and / or pilot signals is defined in the system, and when each terminal connects to the base station, the base station can transmit key parameters (e.g., sequence number, etc.) of the formula to the terminal.

[0117] 5) A formula for forming globally unique data and / or pilot signals is defined in the system, and when the base station requests NL measurement from a terminal, the key parameters (e.g., sequence number, etc.) of the formula can be transmitted to the terminal.

[0118] Alternatively, if the algorithm for NL measurement of the terminal does not require separate data, only the pilot signal defined by one of the above methods may be transmitted without data transmission. Alternatively, the data may be dummy data for NL measurement, in which case the base station may notify the terminal of this during the data scheduling phase.

[0119] Meanwhile, in situations where the base station already has data to send to the terminal, NL measurements can be requested using the existing data without using additional data and / or pilot signals. In this case, the base station can instruct the terminal on which data to request NL measurements, as follows:

[0120] 1) Request NL measurements for all data transmissions that occur.

[0121] 2) Request NL measurement only for data transmission corresponding to specific time and frequency information.

[0122] 3) Request using a separate directive when scheduling only for data transmission that requires measurement.

[0123] At step S710, the terminal (1-15) can perform nonlinearity measurement using the received data and / or pilot signal. Nonlinearity may be measured during the nonlinearity compensation process as described with respect to FIG. 4 described above, or may be measured separately, unrelated to nonlinearity compensation.

[0124] For NL measurement, the terminal may require a separate processing step beyond the existing data reception process. To this end, during the terminal's connection to the base station, the terminal may transmit information to the base station regarding processing delay times for NL measurement, additional battery usage, and other information during the terminal's capability verification process. More detailed operations for this will be described later in the description of Figure 8.

[0125] Alternatively, during the transmission of messages regarding NL measurements, the base station may request the terminal via a query message, or exchange the information at the terminal's request. Based on this information, the base station can use it to determine whether to request NL measurements from the terminal by verifying whether the terminal's additional NL measurements satisfy requirements such as delay time or reliability of existing data.

[0126] At step S712, the terminal (1-15) may transmit a message (e.g., NL Measurement Report) reporting the NL measurement results to the base station (1-10). For example, the message reporting the NL measurement results may include at least one of the following information or a combination thereof.

[0127] 1) Information that directly expresses the degree of nonlinearity in a manner preset by the base station and terminal.

[0128] 2) Information that indirectly expresses the degree of nonlinearity using specific performance metrics such as the current EVM.

[0129] 3) Maximum MCS level that can be supported as determined by the terminal

[0130] In step S714, the base station (1-10) can use the NL measurement result reported from the terminal (1-15) or additionally the NL measurement result reported from other terminal(s) to set the maximum MCS level that can be currently supported. For example, the base station (1-10) can use an algorithm that maps indirect information such as the degree of nonlinearity and EVM reported by the terminal (1-15) to the maximum MCS level that can be supported. In addition, the base station (1-10) can modify specific parameters of the algorithm based on the data transmission result that occurs later (e.g., statistical information of ACK / NACK, etc.). The base station (1-10) and the terminal (1-15) can perform data transmission and reception based on the determined maximum MCS level that can be supported.

[0131] At step S716, the base station (1-10) can identify that the DPD update for the PA(s) has been completed. Even after all DPD updates have been completed, the base station (1-10) can store the NL measurement report information received from the terminal and reuse it in the future when a DPD update is required again.

[0132] For example, the base station (1-10) may store the NL measurement results reported from the terminal in a situation where a DPD update is required for PAs a, b, and c. Later, when a situation arises where a DPD update is required for PAs d, e, and f, the base station (1-10) may assume that the NL level is the same or similar to the previous one, since the same number of PAs require DPD updates. Alternatively, if a problem occurs in a different number of PAs, such as PAs d, e, f, and g, the NL level may be assumed to be greater by the difference in the number of PAs requiring DPD updates (e.g., 1) compared to the previously measured NL level, and may utilize this in the step of initially setting the maximum MCS level that can be supported in step S702.

[0133] Meanwhile, in the above-described embodiment, it is explained assuming that the base station (1-10) has identified that a DPD update is required due to a specific cause, but the base station (1-10) can perform the above-described operations to check the degree of nonlinearity of the current PA even in a situation where there is no problem with the PA, and step S700 can be omitted.

[0134] Through this, the base station (1-10) can check the current degree of PA nonlinearity and decide whether to perform coefficient update of the DPD algorithm based on the information received from the terminal (1-15). Alternatively, the base station (1-10) can also check whether the PA performance has been permanently degraded due to aging effects, etc. based on the above information. Through this, the results reported by the terminal (1-15) can be utilized in processes such as changing the default value of the maximum supportable MCS level.

[0135] FIG. 8 is a sequence diagram illustrating a procedure for acquiring nonlinearity measurement-related capability information of a terminal upon initial connection according to one embodiment of the present disclosure.

[0136] Referring to FIG. 8, at step S800, the base station (1-15) and the terminal (1-10) can perform an initial access procedure. For example, the terminal (1-10) can search for a synchronization signal block (SSB) to synchronize the downlink and obtain system information required for initial access through a master information block (MIB) and a system information block (SIB). Thereafter, the terminal (1-10) can perform a random access procedure based on the obtained system information to complete the RRC setup.

[0137] At step S802, the base station (1-10) may transmit a message (e.g., NL Capability Request) requesting nonlinearity measurement-related capability information to the terminal (1-15). Alternatively, a message (UE Capability Enquiry) requesting previously defined terminal capability information may be transmitted.

[0138] At step S804, the terminal (1-15) may transmit a message (e.g., NL Capability Response) containing capability information related to nonlinearity measurement to the base station (1-10). Alternatively, a message (UE Capability Information) containing previously defined terminal capability information may be transmitted.

[0139] The above message may contain at least one or a combination of the following information:

[0140] - Information on whether the terminal supports NL measurement function

[0141] - If separate data and / or pilot signal transmission is required for NL measurement, terminal capability parameters required to define the data and / or pilot signal.

[0142] - Information about the overhead required for the terminal to perform NL measurements (e.g., processing delay time for NL measurements, additional battery usage, etc.)

[0143] Based on the above-described information, the base station (1-10) can generate configuration information for NL measurement. In addition, the base station (1-10) can utilize capability information of the terminal (1-10) to determine whether the terminal (1-15) supports the NL measurement function, generate separate data and / or pilot signals for NL measurement, or determine whether to request NL measurement from the terminal (1-10).

[0144] FIG. 9 is a sequence diagram illustrating a procedure for compensating nonlinearity in a terminal when a nonlinearity problem occurs in a signal transmitted by a base station according to one embodiment of the present disclosure.

[0145] Referring to FIG. 9, a method of requesting non-linearity compensation (NC) to a terminal (1-15) when there is a problem with non-linearity in a signal transmitted after the PA stage of a base station (1-10) is illustrated.

[0146] For example, the base station (1-10) can determine the degree of distortion or nonlinearity of the signal by sampling the signal transmitted after the PA stage and comparing it with the signal before the DPD stage. At this time, assuming that the difference between the signal before the DPD stage and the signal after the PA stage is e, a situation in which the e value is smaller than a specific threshold (th) is defined as a situation in which there is no problem with nonlinearity, and a situation in which the e value is larger than a specific threshold (th) is defined as a situation in which there is a problem with nonlinearity, so that the base station (1-10) can determine whether a problem has occurred in the nonlinearity compensation of the PA.

[0147] For example, at step S900, the base station (1-10) can identify that there is no problem with the nonlinearity compensation in the PA. At step S902, the base station (1-10) can transmit data to the terminal (1-15). At step S904, the terminal (1-15) can receive data without performing nonlinearity compensation.

[0148] Meanwhile, at step S906, the base station (1-10) can identify that a problem has occurred in the nonlinearity compensation of the PA. At step S908, the base station (1-10) can transmit information or a message requesting nonlinearity compensation along with data to the terminal (1-15). At step S910, the terminal (1-15) can receive data by compensating for nonlinearity at the request of the base station (1-10).

[0149] The specific procedure for the base station (1-10) to transmit information or a message requesting nonlinearity compensation to the terminal (1-15) will be described in more detail in the description of FIGS. 11 to 14 below.

[0150] FIG. 10 is a diagram illustrating a processing time for performing a DPD update at a base station according to one embodiment of the present disclosure.

[0151] Referring to Fig. 10, the base station (1-10) can transmit a signal by compensating (removing) nonlinearity in advance using DPD. Meanwhile, the base station (1-10) can attempt a DPD update (or a DPD algorithm coefficient update) if it detects a problem or change in PA nonlinearity at a specific point in time. However, it takes a certain amount of time (T) for the base station (1-10) to perform a DPD update. update ) may require processing time, and signals with nonlinearities may be transmitted during that period. In addition, T update can increase in proportion to the number of coefficients of the DPD algorithm. Therefore, the problem of PA nonlinearity is difficult to solve at the transmitter (base station) during the DPD algorithm coefficient update, and during that period, the receiver (terminal) can receive the signal by performing an additional nonlinearity compensation (NC) process.

[0152] FIG. 11 is a diagram illustrating a procedure for a base station to designate a time for performing nonlinearity compensation on a terminal according to one embodiment of the present disclosure.

[0153] Referring to Fig. 11, when a nonlinearity problem occurs in a signal transmitted after the PA stage of the base station (1-10), a method is illustrated in which the base station (1-10) requests nonlinearity compensation (NC) from the terminal (1-15) and specifies a time (T_NC) for performing NC. For a method of performing NC at the receiving end (i.e., the terminal), reference may be made to the description of Fig. 4 described above.

[0154] At step S1100, the base station (1-10) can identify a nonlinearity problem. For example, as described in FIG. 9, the base station (1-10) can determine that a situation in which the difference between the signal before the DPD stage and the signal after the PA stage, assuming e, is greater than a specific threshold value (th), is a nonlinearity problem.

[0155] In step S1102, the base station (1-10) may transmit a message (e.g., NC Activation) to the terminal (1-15) requesting that the receiving end perform nonlinearity compensation. As described in Fig. 10, if a nonlinearity problem occurs in the base station (1-10), the problem may be resolved within a specific period (T update ) is likely to occur continuously during the period. Therefore, the base station (1-10) performs nonlinearity compensation on the above message at a time (T NC ) may include information about the time (T) at which nonlinearity compensation is performed. NC ) can be set according to any of the following.

[0156] 1) Predefined default values ​​in the system (e.g. T NC = 3 seconds)

[0157] 2) The time taken for the past n DPD coefficient updates (T update ) average value

[0158] 3) Time taken for the past n DPD coefficient updates (T update ) the maximum value

[0159] 4) The time taken to update the DPD coefficients for the same number of PAs that have had the current problem n times in the past (T update ) average value

[0160] 5) The time taken to update the DPD coefficients for the same number of PAs that have had the current problem n times in the past (T update ) the maximum value

[0161] 6) Time taken for the previous DPD coefficient update (T update )

[0162] 7) The time taken to update the DPD coefficients for the same number of PAs that had the previous current problem (T update )

[0163] In addition, the time (T) for performing the above nonlinearity compensation NC ) can be set in absolute time units (e.g., sec, msec), and / or in slot units, and / or in symbol units.

[0164] The terminal (1-15) that received the message requesting the above nonlinearity compensation starts the timer T NC can start driving.

[0165] In step S1104, the terminal (1-15) may transmit a response message (e.g., NC Activation Acknowledgement) to the message requesting the nonlinearity compensation to the base station (1-10). The terminal (1-15) may transmit the timer T NC The drive may start after step S1104.

[0166] At step S1106, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD is not applied.

[0167] At step S1108, the terminal (1-15) can receive data transmitted from the base station (1-10). At this time, the timer T NC If the terminal (1-15) is in operation, the terminal (1-15) can receive the above data by compensating for nonlinearity.

[0168] At step S1110, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD has been applied as the DPD coefficient update of the base station (1-10) is completed.

[0169] At step S1112, the terminal (1-15) can receive data transmitted from the base station (1-10). At this time, the timer T NC If has expired, the terminal (1-15) can receive the above data without nonlinearity compensation.

[0170] FIG. 12 is a diagram illustrating a procedure for updating a time at which a base station performs nonlinearity compensation on a terminal according to one embodiment of the present disclosure.

[0171] Referring to Figure 12, the time (T) at which the base station (1-10) performs nonlinearity compensation to the terminal (1-15) NC ) was specified, but an example of updating (resetting) T_NC is shown due to reasons such as delay in processing time for updating DPD coefficients.

[0172] The operations from step S1200 to step S1208 can be performed similarly to the operations from step S1100 to step S1108 of FIG. 11.

[0173] At step S1210, the time to perform nonlinearity compensation (T NC ) to update the message (e.g. T NC Update) can be transmitted. The terminal (1-15) that receives the above message sends T NC can start driving. Terminal (1-15) is currently running T NC In parallel with T NC It can be operated and the T that was currently running NC Stop and T NC You can start over again.

[0174] Additionally, the above message contains a new T NC The value of may be included separately. The new T NC The value of T is previously set NC It may be the same as or different from the value of . If the above message contains a separate T NCIf the value of is not included, the terminal (1-15) is set to the previously set T NC Assume that the value is equal to or the default value of T NC can be operated.

[0175] At step S1212, the terminal (1-15) performs the nonlinearity compensation at a time (T NC ) response message to a message to update (e.g. T NC Update Acknowledgement) can be transmitted to the base station (1-10). The terminal (1-15) can then send a new timer T NC Driving may also start after step S1212.

[0176] At step S1214, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD is not applied.

[0177] At step S1216, the terminal (1-15) can receive data transmitted from the base station (1-10). At this time, the timer T driven at step S1202 / S1204 NC Even if the timer T has expired, a new timer is started at step S1210 / S1212. NC If the terminal (1-15) is in operation, the terminal (1-15) can receive the above data by compensating for nonlinearity.

[0178] FIG. 13 is a sequence diagram illustrating a procedure for activating / deactivating signaling-based nonlinearity compensation according to one embodiment of the present disclosure.

[0179] Referring to FIG. 13, a method of activating and deactivating the nonlinearity compensation (NC) function of a terminal (1-15) through explicit signaling of a base station (1-10) is illustrated.

[0180] At step S1300, the base station (1-10) can identify a problem with nonlinearity. For example, as described in FIG. 9, the base station (1-10) can determine that a situation in which the difference between the signal before the DPD stage and the signal after the PA stage, assuming e, is greater than a specific threshold value (th), is a situation in which a problem with nonlinearity exists.

[0181] At step S1302, the base station (1-10) can transmit a message (e.g., NC Activation) requesting activation of a nonlinearity compensation operation at the receiving end to the terminal (1-15).

[0182] At step S1304, the terminal (1-15) can transmit a response message (e.g., NC Activation Acknowledgement) to the message requesting activation of the nonlinearity compensation operation to the base station (1-10).

[0183] A terminal (1-15) that receives the above NC Activation or transmits the NC Activation Acknowledgement can activate nonlinearity compensation operation.

[0184] At step S1306, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD is not applied.

[0185] At step S1308, the terminal (1-15) can receive data transmitted from the base station (1-10). At this time, the terminal (1-15) with the nonlinearity compensation operation activated can receive the data by compensating for nonlinearity.

[0186] At step S1310, the base station (1-10) may transmit a message (e.g., NC Deactivation) to the terminal (1-15) requesting deactivation of the nonlinearity compensation operation. The message may be transmitted based on the determination that the nonlinearity problem no longer occurs at the base station (1-10) or that the DPD update has been completed.

[0187] At step S1312, the terminal (1-15) can transmit a response message (e.g., NC Deactivation Acknowledgement) to the message requesting deactivation of the nonlinearity compensation operation to the base station (1-10).

[0188] A terminal (1-15) that receives the above NC Deactivation or transmits the above NC Deactivation Acknowledgement can deactivate the nonlinearity compensation operation.

[0189] At step S1312, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD has been applied as the DPD coefficient update of the base station (1-10) is completed.

[0190] At step S1314, the terminal (1-15) can receive data transmitted from the base station (1-10). At this time, the terminal (1-15) with the nonlinearity compensation operation disabled can receive the data without nonlinearity compensation.

[0191] FIG. 14 is a sequence diagram illustrating a procedure for activating / deactivating signaling-based nonlinearity compensation according to one embodiment of the present disclosure.

[0192] Referring to FIG. 14, a method is illustrated in which a base station (1-10) and a terminal (1-15) exchange explicit signaling to activate and deactivate the nonlinearity compensation (NC) function of the terminal (1-15). However, in FIG. 14, the terminal continuously checks the degree of nonlinearity in the data signal transmitted by the base station, and can request the base station to deactivate the nonlinearity compensation operation when the nonlinearity is determined to be low.

[0193] At step S1400, the base station (1-10) can identify a nonlinearity problem. For example, as described in FIG. 9, the base station (1-10) can determine that a situation in which the difference between the signal before the DPD stage and the signal after the PA stage, assuming e, is greater than a specific threshold value (th), is a nonlinearity problem.

[0194] At step S1402, the base station (1-10) can transmit a message (e.g., NC Activation) requesting activation of a nonlinearity compensation operation at the receiving end to the terminal (1-15).

[0195] At step S1404, the terminal (1-15) can transmit a response message (e.g., NC Activation Acknowledgement) to the message requesting activation of the nonlinearity compensation operation to the base station (1-10).

[0196] A terminal (1-15) that receives the above NC Activation or transmits the NC Activation Acknowledgement can activate nonlinearity compensation operation.

[0197] At step S1406, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD is not applied.

[0198] At step S1408, the terminal (1-15) can receive data transmitted from the base station (1-10). At this time, the terminal (1-15) with the nonlinearity compensation operation activated can receive the data by compensating for the nonlinearity. If a certain level of high nonlinearity is detected in the data, the terminal (1-15) can continue to activate the nonlinearity compensation operation.

[0199] At step S1410, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD has been applied as the DPD coefficient update of the base station (1-10) is completed, or a signal to which DPD has not been applied.

[0200] At step S1412, the terminal (1-15) can receive data transmitted from the base station (1-10). At this time, the terminal (1-15) with the nonlinearity compensation operation activated can receive the data by compensating for the nonlinearity. Unlike step S1408, if a low nonlinearity below a certain level is detected in the data, the terminal (1-15) can decide to deactivate the nonlinearity compensation operation.

[0201] At step S1414, the terminal (1-15) that has decided to deactivate the nonlinearity compensation operation may transmit a message (e.g., NC Deactivation Request) requesting deactivation of the nonlinearity compensation operation to the base station (1-10). In another embodiment, the terminal (1-15) may deactivate the NC function on its own without sending a separate message (e.g., NC Deactivation Request) to the base station (1-10).

[0202] At step S1416, the base station (1-15) can transmit a response message (e.g., NC Deactivation Request Acknowledgement) to the message requesting deactivation of the nonlinearity compensation operation to the terminal (1-15).

[0203] A terminal (1-15) that transmits the NC Deactivation Request or receives the NC Deactivation Request Acknowledgement can deactivate the nonlinearity compensation operation.

[0204] At step S1418, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD has been applied as the DPD coefficient update of the base station (1-10) is completed.

[0205] At step S1420, the terminal (1-15) can receive data transmitted from the base station (1-10). At this time, the terminal (1-15) with the nonlinearity compensation operation disabled can receive the data without nonlinearity compensation.

[0206] FIG. 15 is a sequence diagram illustrating a procedure for activating / deactivating signaling-based nonlinearity compensation according to one embodiment of the present disclosure.

[0207] Referring to FIG. 15, a method is illustrated in which a nonlinearity compensation (NC) operation is activated by a proactive nonlinearity measurement of a terminal (1-15) and NC is deactivated by a base station (1-10).

[0208] At step S1500, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD is not applied.

[0209] At step S1502, the terminal (1-15) can measure the nonlinearity of data transmitted from the base station (1-10). The nonlinearity may be measured during the nonlinearity compensation process as described with respect to FIG. 4 described above, or may be measured separately, unrelated to the nonlinearity compensation. If the nonlinearity is determined to be high, the terminal (1-15) may decide to activate the nonlinearity compensation operation.

[0210] At step S1504, the terminal (1-15) can transmit a message (e.g., NC Activation Request or DPD Update Request) requesting activation of a nonlinearity compensation operation at the receiving end and / or a DPD update at the transmitting end.

[0211] At step S1506, the base station (1-10) can transmit a response message (e.g., NC Activation Request Acknowledgement or DPD Update Request Acknowledgement) to the terminal (1-15) for a message requesting activation of the nonlinearity compensation operation or a message requesting a DPD update.

[0212] A terminal (1-15) that transmits the above NC Activation / DPD Update Request or receives the above NC Activation / DPD Update Request Acknowledgement can activate a nonlinearity compensation operation.

[0213] At step S1508, the base station (1-10) that received the NC Activation / DPD Update Request or transmitted the NC Activation / DPD Update Request Acknowledgement can start DPD update (or DPD algorithm coefficient update).

[0214] At step S1510, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD is not applied.

[0215] At step S1512, the terminal (1-15) can receive data transmitted from the base station (1-10). At this time, the terminal (1-15) with the nonlinearity compensation operation activated can receive the data by compensating for nonlinearity.

[0216] At step S1514, the base station (1-10) can identify that the DPD update is completed (terminated).

[0217] At step S1516, the base station (1-10) where the DPD update is completed can transmit a message (e.g., NC Deactivation) requesting deactivation of the nonlinearity compensation operation to the terminal (1-15).

[0218] At step S1518, the terminal (1-10) can transmit a response message (e.g., NC Deactivation Acknowledgement) to the message requesting deactivation of the nonlinearity compensation operation to the base station (1-10).

[0219] A terminal (1-15) that receives the above NC Deactivation or transmits the above NC Deactivation Acknowledgement can deactivate the nonlinearity compensation operation.

[0220] At step S1520, the terminal (1-15) with the nonlinearity compensation operation disabled can then receive data from the base station (1-10) without nonlinearity compensation.

[0221] FIG. 16 is a sequence diagram illustrating a procedure for activating / deactivating signaling-based nonlinearity compensation according to one embodiment of the present disclosure.

[0222] Referring to FIG. 16, there is shown how the nonlinearity compensation (NC) operation is activated and deactivated by the proactive nonlinearity measurement of the terminal (1-15).

[0223] At step S1600, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD is not applied.

[0224] At step S1602, the terminal (1-15) can measure the nonlinearity of data transmitted from the base station (1-10). The nonlinearity may be measured during the nonlinearity compensation process as described with respect to FIG. 4 described above, or may be measured separately, independent of the nonlinearity compensation. If the nonlinearity is determined to be high, the terminal (1-15) may decide to activate the nonlinearity compensation operation.

[0225] At step S1604, the terminal (1-15) can transmit a message (e.g., NC Activation Request or DPD Update Request) requesting activation of a nonlinearity compensation operation at the receiving end and / or a DPD update at the transmitting end.

[0226] At step S1606, the base station (1-10) can transmit a response message (e.g., NC Activation Request Acknowledgement or DPD Update Request Acknowledgement) to the terminal (1-15) for a message requesting activation of the nonlinearity compensation operation or a message requesting a DPD update.

[0227] A terminal (1-15) that transmits the NC Activation / DPD Update Request or receives the NC Activation / DPD Update Request Acknowledgement can activate a nonlinearity compensation operation. In addition, a base station (1-10) that receives the NC Activation / DPD Update Request or transmits the NC Activation / DPD Update Request Acknowledgement can initiate a DPD update (or a DPD algorithm coefficient update).

[0228] At step S1608, the base station (1-10) can transmit data to the terminal (1-15). Here, the data may be a signal to which DPD has been applied as the DPD coefficient update of the base station (1-10) is completed, or may be a signal to which DPD has not been applied.

[0229] At step S1610, the terminal (1-15) can receive data transmitted from the base station (1-10). At this time, the terminal (1-15) with the nonlinearity compensation operation activated can receive the data by compensating for the nonlinearity. If the terminal (1-15) measures the nonlinearity of the data transmitted by the base station and detects a low nonlinearity below a certain level, the terminal (1-15) can decide to deactivate the nonlinearity compensation operation.

[0230] At step S1612, a terminal (1-15) that has decided to deactivate the nonlinearity compensation operation can transmit a message requesting deactivation of the nonlinearity compensation operation (e.g., NC Deactivation Request) to the base station (1-10).

[0231] At step S1614, the base station (1-15) can transmit a response message (e.g., NC Deactivation Request Acknowledgement) to the message requesting deactivation of the nonlinearity compensation operation to the terminal (1-15).

[0232] A terminal (1-15) that transmits the NC Deactivation Request or receives the NC Deactivation Request Acknowledgement can deactivate the nonlinearity compensation operation.

[0233] At step S1618, the terminal (1-15) with the nonlinearity compensation operation disabled can then receive data from the base station (1-10) without nonlinearity compensation.

[0234] FIG. 17 is a flowchart illustrating the operation of a base station according to one embodiment of the present disclosure.

[0235] Referring to FIG. 17, the operations performed by the base stations (1-10) of FIGS. 1 to 16 described above are illustrated.

[0236] In step S1700, the base station may transmit a nonlinearity measurement request message. For example, the base station may transmit the message based on identifying that a DPD update is required for the PA(s), or may transmit the message to determine the degree of nonlinearity of the current PA(s). For example, the base station may determine an MCS level according to the number of PAs requiring a DPD update based on a predetermined rule. For example, the base station may determine one or more terminals to request nonlinearity measurement based on at least one of a round robin method, a random selection method, data to be transmitted, or current channel conditions, and transmit the nonlinearity measurement request message to the one or more terminals.

[0237] In step S1704, the base station may transmit a pilot signal and / or data. For example, the pilot signal and / or data may be transmitted based on a predefined sequence or predefined time-frequency resources, may be transmitted based on cell-specific or terminal-specific information, or may be transmitted based on a predefined formula.

[0238] In step S1706, the base station may receive a nonlinearity measurement report message. For example, the nonlinearity measurement report message may include information on a nonlinearity measurement result based on the pilot signal and / or data. For example, the information on the nonlinearity measurement result may include at least one of information directly indicating the degree of nonlinearity, information on a performance measurement metric according to the degree of nonlinearity, and information on the maximum supportable MCS level determined by the terminal.

[0239] In step S1708, the base station may select a supportable MCS level. For example, if the information regarding the nonlinearity measurement results includes information regarding the performance measurement metric, the base station may determine the supportable MCS level mapped to the performance measurement metric, and adjust the supportable MCS level based on the results of subsequent data transmission.

[0240] FIG. 18 is a flowchart illustrating the operation of a terminal according to one embodiment of the present disclosure.

[0241] Referring to FIG. 18, the operations performed by the terminals (1-15) of FIGS. 1 to 16 described above are illustrated.

[0242] At step S1800, the terminal may receive a nonlinearity measurement request message. For example, the message may be transmitted based on the base station identifying that a DPD update is required for the PA(s), or may be transmitted for the base station to determine the degree of nonlinearity of the current PA(s). For example, even before receiving the nonlinearity measurement request message, the base station may determine an MCS level according to the number of PAs requiring DPD updates based on a predetermined rule. For example, the terminal may be selected by the base station to request nonlinearity measurement based on at least one of a round robin method, a random selection method, data to be transmitted, or current channel conditions.

[0243] In step S1804, the terminal may receive a pilot signal and / or data. For example, the pilot signal and / or data may be received based on a predefined sequence or predefined time-frequency resources, based on cell-specific or terminal-specific information, or based on a predefined formula.

[0244] At step S1806, the terminal may measure nonlinearity. For example, the terminal may measure nonlinearity for the pilot signal and / or data. The nonlinearity may be measured during the nonlinearity compensation process, as described with respect to FIG. 4 above, or may be measured separately, independent of nonlinearity compensation.

[0245] In step S1808, the terminal may transmit a nonlinearity measurement report message. For example, the nonlinearity measurement report message may include information on a nonlinearity measurement result based on the pilot signal and / or data. For example, the information on the nonlinearity measurement result may include at least one of information directly indicating the degree of nonlinearity, information on a performance measurement metric according to the degree of nonlinearity, and information on a maximum supportable MCS level determined by the terminal. For example, the information on the nonlinearity measurement result may be associated with an MCS level supportable by the base station. For example, if the information on the nonlinearity measurement result includes information on the performance measurement metric, the base station may determine the supportable MCS level mapped to the performance measurement metric, and adjust the supportable MCS level based on a subsequent data transmission result.

[0246] FIG. 19 is a block diagram illustrating a terminal according to an embodiment of the present disclosure.

[0247] Referring to FIG. 19, the terminal (1900) may correspond to the terminal (1-15) illustrated in FIGS. 1 to 18. The terminal (1900) may include a transceiver (1901), a control unit (processor) (1902), and a storage unit (memory) (1903). According to an embodiment of the present disclosure, the transceiver (1901), the control unit (1902), and the storage unit (1903) of the terminal (1900) may operate. However, the components of the terminal (1900) according to one embodiment are not limited to the above-described example. According to other embodiments, the terminal (1900) may include more or fewer components than the components described above. In addition, in certain cases, the transceiver (1901), the control unit (1902), and the storage unit (1903) may be implemented in the form of a single chip.

[0248] The transceiver (1901) may, according to another embodiment, be composed of a transmitter and a receiver. The transceiver (1901) may transmit and receive signals with a base station. The signals may include control information and data. To this end, the transceiver (1901) may be composed of an RF transmitter that up-converts and amplifies the frequency of a transmitted signal, and an RF receiver that low-noise amplifies and down-converts the frequency of a received signal. In addition, the transceiver (1901) may receive a signal through a wireless channel and output it to the control unit (1902), and transmit the signal output from the control unit (1902) through the wireless channel.

[0249] The control unit (1902) can control a series of processes that the terminal (1900) can operate according to the above-described embodiment of the present disclosure. For this purpose, the control unit (1902) can include at least one processor. For example, the control unit (1902) can include a communication processor (CP) that performs control for communication and an application processor (AP) that controls upper layers such as application programs. For example, the control unit (1902) can control the transceiver unit (1901) to receive a nonlinearity measurement request message, control the transceiver unit (1901) to receive at least one of a pilot signal or data, and control the transceiver unit (1901) to transmit a nonlinearity measurement report message that includes information on a nonlinearity measurement result based on at least one of the pilot signal or data.

[0250] The storage unit (1903) can store control information or data included in a signal obtained from the terminal (1900), and can have an area for storing data required for controlling the control unit (1902) and data generated during control by the control unit (1902).

[0251] Additionally, the terminal (1900) may include an AI device (not shown) capable of performing at least some of the AI ​​processing. The AI ​​device may include an AI processor, memory, and / or a communication unit.

[0252] For example, the control unit (1902) may operate as an AI processor or perform at least a part of the functions of an AI processor. The AI ​​processor may learn a neural network using a program stored in a memory. Here, the neural network may be designed to simulate the structure of a human brain on a computer and may include a plurality of network nodes having weights that simulate neurons of a human neural network. The plurality of network modes may exchange data according to their respective connection relationships so as to simulate the synaptic activity of neurons that exchange signals through synapses. Here, the neural network may include a deep learning model developed from a neural network model. In the deep learning model, the plurality of network nodes may be located in different layers and exchange data according to convolutional connection relationships.

[0253] Meanwhile, the AI ​​processor may include a data learning unit that trains a neural network for data classification / recognition. The data learning unit can classify data to be used for learning and acquire data to be learned. The data learning unit can train a deep learning model by applying the acquired learning data to the deep learning model. For example, the deep learning model can be trained through supervised learning or unsupervised learning. Furthermore, the data learning unit can train the deep learning model through reinforcement learning using feedback on whether the results of the situational judgment based on learning are correct. The deep learning model can be trained based on the data of the input layer and the output layer.

[0254] The data learning unit may be manufactured in the form of at least one hardware chip and mounted on an AI device. For example, the data learning unit may be manufactured in the form of a dedicated hardware chip for artificial intelligence (AI), or may be manufactured as part of a general-purpose processor (CPU) or a graphics processor (GPU) and mounted on an AI device. Furthermore, the data learning unit may be implemented as a software module. When implemented as a software module (or a program module including instructions), the software module may be stored on a non-transitory computer-readable recording medium that can be read by a computer. In this case, at least one software module may be provided by an operating system (OS) or an application.

[0255] For example, the storage unit (1903) may include memory of the AI ​​device. The memory may store various programs and data required for the operation of the AI ​​device. The memory is accessed by the AI ​​processor, and data may be read, recorded, modified, deleted, updated, etc. by the AI ​​processor. For example, the data learning unit may store a learned model associated with the input / output relationship information of the PA in the memory.

[0256] For example, the communication unit of the AI ​​device may be included in the transceiver unit (1901).

[0257] FIG. 20 is a block diagram illustrating a base station according to an embodiment of the present disclosure.

[0258] Referring to FIG. 20, the base station (2000) may correspond to the base stations (1-10) illustrated in FIGS. 1 to 18. The base station (2000) may include a transceiver (2001), a control unit (processor) (2002), and a storage unit (memory) (2003). According to an embodiment of the present disclosure, the transceiver (2001), the control unit (2002), and the storage unit (2003) of the base station (2000) may operate. However, the components of the base station (2000) according to one embodiment are not limited to the above-described example. According to other embodiments, the base station (2000) may include more or fewer components than the components described above. In addition, in certain cases, the transceiver (2001), the control unit (2002), and the storage unit (2003) may be implemented in the form of a single chip.

[0259] The transceiver (2001) may, according to another embodiment, be composed of a transmitter and a receiver. The transceiver (2001) may transmit and receive signals with a terminal. The signals may include control information and data. To this end, the transceiver (2001) may be composed of an RF transmitter that up-converts and amplifies the frequency of a transmitted signal, and an RF receiver that low-noise amplifies and down-converts the frequency of a received signal. In addition, the transceiver (2001) may receive a signal through a wireless channel and output it to the control unit (2002), and transmit a signal output from the control unit (2002) through the wireless channel.

[0260] The control unit (2002) can control a series of processes so that the base station (2000) can operate according to the above-described embodiment of the present disclosure. For this purpose, the control unit (2002) can include at least one processor. For example, the control unit (2002) can include an AP that controls upper layers such as a CP that performs control for communication and an application program. For example, the control unit (2002) can control the transceiver (2001) to transmit a nonlinearity measurement request message, control the transceiver (2001) to transmit at least one of a pilot signal or data, control the transceiver (2001) to receive a nonlinearity measurement report message that includes information on a nonlinearity measurement result based on at least one of the pilot signal or data, and determine a supportable modulation and coding scheme (MCS) level based on the information on the nonlinearity measurement result.

[0261] The storage unit (2003) can store control information, data determined by the base station (2000) or control information, data received from a terminal, and can have an area for storing data required for control of the control unit (2002) and data generated during control by the control unit (2002).

[0262] Additionally, the base station (2000) may include an AI device (not shown) capable of performing at least some of the AI ​​processing. The AI ​​device may include an AI processor, memory, and / or a communication unit.

[0263] For example, the control unit (2002) may operate as an AI processor or perform at least a part of the functions of an AI processor. The AI ​​processor may learn a neural network using a program stored in a memory. Here, the neural network may be designed to simulate the structure of a human brain on a computer and may include a plurality of network nodes having weights that simulate neurons of a human neural network. The plurality of network modes may exchange data according to their respective connection relationships so as to simulate the synaptic activity of neurons that exchange signals through synapses. Here, the neural network may include a deep learning model developed from a neural network model. In the deep learning model, the plurality of network nodes may be located in different layers and may exchange data according to convolutional connection relationships.

[0264] Meanwhile, the AI ​​processor may include a data learning unit that trains a neural network for data classification / recognition. The data learning unit can classify data to be used for learning and acquire learning data. The data learning unit can train a deep learning model by applying the acquired learning data to the deep learning model. For example, the deep learning model can be trained through supervised or unsupervised learning. Furthermore, the data learning unit can train the deep learning model through reinforcement learning using feedback on whether the results of situational judgment according to learning are correct. For example, the data learning unit can classify a received pilot portion as input layer data and classify it as output layer data by applying a size scaling factor to a previously known pilot portion. The deep learning model can be trained based on the data of the input layer and the output layer. Furthermore, inference can be performed based on the trained model by using the data portion of the received signal as the input layer.

[0265] The data learning unit may be manufactured in the form of at least one hardware chip and mounted on an AI device. For example, the data learning unit may be manufactured in the form of a dedicated hardware chip for artificial intelligence (AI), or may be manufactured as part of a general-purpose processor (CPU) or graphics processing unit (GPU) and mounted on an AI device. Furthermore, the data learning unit may be implemented as a software module. If implemented as a software module (or a program module including instructions), the software module may be stored on a computer-readable, non-transitory, readable recording medium. In this case, at least one software module may be provided by an operating system (OS) or an application.

[0266] For example, the storage unit (2003) may include the memory of the AI ​​device. The memory may store various programs and data necessary for the operation of the AI ​​device. The memory is accessed by the AI ​​processor, and data may be read, recorded, modified, deleted, updated, etc. by the AI ​​processor. For example, the data learning unit may store a learned model associated with the input / output relationship information of the PA in the memory.

[0267] For example, the communication unit of the AI ​​device may be included in the transceiver unit (2001).

[0268] The methods proposed in this disclosure may be implemented by combining some or all of the contents included in each embodiment within a scope that does not harm the essence of the invention.

[0269] The embodiments disclosed in this specification and drawings are merely specific examples to facilitate easy explanation of the technical content of the present invention and aid in understanding of the present disclosure, and are not intended to limit the scope of the present disclosure. That is, it will be apparent to those skilled in the art to which the present disclosure pertains that other modifications based on the technical concepts of the present disclosure are possible.

[0270] Furthermore, the present specification and drawings disclose preferred embodiments of the present disclosure, and although specific terms have been used, they are used in a general sense only to easily explain the technical contents of the present disclosure and to assist in the understanding of the invention, and are not intended to limit the scope of the present disclosure. It will be apparent to those skilled in the art to which the present disclosure pertains that other modified examples based on the technical idea of ​​the present disclosure are possible in addition to the embodiments disclosed herein.

Claims

1. A method performed by a base station of a wireless communication system, A step of transmitting a nonlinearity measurement request message; A step of transmitting at least one of a pilot signal or data; A step of receiving a nonlinearity measurement report message including information about a nonlinearity measurement result based on at least one of the pilot signal or data; and A method comprising the step of determining a supportable modulation and coding scheme (MCS) level based on information about the nonlinearity measurement results.

2. In paragraph 1, a step of identifying that an update of a digital pre-distortion (DPD) model for one or more power amplifiers (PAs) of the base station is required prior to transmitting the nonlinearity measurement request message; and A method further comprising the step of determining a maximum supportable MCS level based on a number of said one or more PAs, based on a predetermined rule.

3. In paragraph 1, The step of transmitting the above nonlinearity measurement request message is: A step of determining one or more terminals to request nonlinearity measurement based on at least one of a round robin method, a random selection method, data to be transmitted, or current channel conditions; and A method characterized by comprising the step of transmitting the nonlinearity measurement request message to the one or more terminals.

4. In paragraph 1, At least one of the above pilot signals or data, Transmitted based on a predefined sequence or predefined time-frequency resources, transmitted based on cell-specific or terminal-specific information, or transmitted based on a predefined formula, Information on the above nonlinearity measurement results, Contains at least one of information directly indicating the degree of nonlinearity, information on a performance metric according to the degree of nonlinearity, and information on the maximum MCS level that can be supported as determined by the terminal. The step of determining which MCS level can be supported is: When the information on the nonlinearity measurement result includes information on the performance measurement metric, a step of determining the supportable MCS level mapped to the performance measurement metric; and A method characterized by including a step of adjusting the supportable MCS level according to the results of subsequent data transmission.

5. In paragraph 1, A step of transmitting a message requesting capability information related to nonlinearity measurement; and A method further comprising the step of receiving a message including at least one of information on whether a nonlinearity measurement capability is supported, a terminal capability parameter related to at least one of the pilot signal or data, or information on overhead required for nonlinearity measurement.

6. In a method performed by a terminal of a wireless communication system, A step of receiving a nonlinearity measurement request message; A step of receiving at least one of a pilot signal or data; Comprising a step of transmitting a nonlinearity measurement report message including information about a nonlinearity measurement result based on at least one of the pilot signal or data, A method characterized in that information on the above nonlinearity measurement results is associated with a modulation and coding scheme (MCS) level that can be supported by the base station.

7. In paragraph 6, At least one of the above pilot signals or data, A method characterized in that it is received based on a predefined sequence or a predefined time-frequency resource, or based on information set cell-specifically or terminal-specifically, or based on a predefined formula.

8. In paragraph 6, Information on the above nonlinearity measurement results, A method characterized by including at least one of information directly indicating the degree of nonlinearity, information on a performance metric according to the degree of nonlinearity, and information on a maximum supportable MCS level determined by a terminal.

9. In a base station of a wireless communication system, Transmitter and receiver; and A base station comprising a control unit that controls the transceiver to transmit a nonlinearity measurement request message, controls the transceiver to transmit at least one of a pilot signal or data, controls the transceiver to receive a nonlinearity measurement report message including information on a nonlinearity measurement result based on at least one of the pilot signal or data, and determines a supportable modulation and coding scheme (MCS) level based on the information on the nonlinearity measurement result.

10. In paragraph 9, The above control unit, Prior to transmitting the nonlinearity measurement request message, identifying that an update of a digital pre-distortion (DPD) model for one or more power amplifiers (PAs) of the base station is required, A base station characterized in that it determines the maximum supportable MCS level according to the number of said one or more PAs based on a predetermined rule.

11. In paragraph 9, The above control unit, Determine one or more terminals to request nonlinearity measurements based on at least one of a round robin method, a random selection method, data to be transmitted, or current channel conditions, A base station characterized by controlling the transceiver to transmit the nonlinearity measurement request message to the one or more terminals.

12. In paragraph 9, At least one of the above pilot signals or data, Transmitted based on a predefined sequence or predefined time-frequency resources, transmitted based on cell-specific or terminal-specific information, or transmitted based on a predefined formula, Information on the above nonlinearity measurement results, Contains at least one of information directly indicating the degree of nonlinearity, information on a performance metric according to the degree of nonlinearity, and information on the maximum MCS level that can be supported as determined by the terminal. The above control unit, If the information about the above nonlinearity measurement result includes information about the above performance measurement metric, the supportable MCS level mapped to the above performance measurement metric is determined, A base station characterized in that it adjusts the supportable MCS level according to the result of subsequent data transmission.

13. In paragraph 9, The above control unit, Controlling the transceiver to transmit a message requesting capability information related to nonlinearity measurement, A base station characterized in that it controls the transceiver to receive a message including at least one of information on whether a nonlinearity measurement function is supported, a terminal capability parameter related to at least one of the pilot signal or data, or information on overhead required for nonlinearity measurement.

14. In the terminal of a wireless communication system, Transmitter and receiver; and A control unit for controlling the transceiver to receive a nonlinearity measurement request message, controlling the transceiver to receive at least one of a pilot signal or data, and controlling the transceiver to transmit a nonlinearity measurement report message including information on a nonlinearity measurement result based on at least one of the pilot signal or data, A terminal characterized in that the information on the above nonlinearity measurement result is associated with a modulation and coding scheme (MCS) level that can be supported by the base station.

15. In paragraph 14, At least one of the above pilot signals or data, Received based on a predefined sequence or predefined time-frequency resources, or received based on cell-specific or terminal-specific information, or received based on a predefined formula, Information on the above nonlinearity measurement results, A terminal characterized by including at least one of information directly indicating the degree of nonlinearity, information on a performance metric according to the degree of nonlinearity, and information on a maximum supportable MCS level determined by the terminal.

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