ABSTRACT
Abstract
A method of calibrating an array antenna in a wireless communication system includes a first step of transmitting a radio signal through a first antenna and a second antenna determined among a plurality of antennas included in the array antenna, a second step of measuring the radio signal through a specific coupling antenna of a plurality of coupling antennas adjacent to the plurality of antennas, a third step of estimating an error of the second antenna based on a result of the measurement of the radio signal, and a fourth step of calibrating the second antenna based on the error.
Description
BACKGROUND OF THE INVENTION
Field of the Invention
The present disclosure relates to a method and apparatus for calibrating an antenna array in a wireless communication system.
Related Art
A mobile communication system was developed to provide a voice service while ensuring the activity of a user. However, the area of the mobile communication system has extended up to data services in addition to voice. Due to a current explosive increase in traffic, there is a shortage of resources. Accordingly, there is a need for a more advanced mobile communication system because users demand higher speed services.
Requirements for a next-generation mobile communication system need to able to support the accommodation of explosive data traffic, a dramatic increase in the data rate per user, the accommodation of a significant increase in the number of connected devices, very low end-to-end latency, and high-energy efficiency. To this end, various technologies, such as dual connectivity, massive multiple input multiple output (MIMO), in-band full duplex, non-orthogonal multiple access (NOMA), the support of a super wideband, and device networking, are researched.
SUMMARY OF THE INVENTION
The present disclosure proposes a method of calibrating an array antenna.
In a conventional technology, the phase and gain error of an array antenna were estimated through a down-conversion mixer. However, the down-conversion mixer has a high cost and a high design level of difficulty.
There was proposed a technology for estimating phase and gain errors based on a channel environment estimated in a reception stage. However, the corresponding technology has a problem in that the accuracy of channel estimation may be degraded and has a critical point I that an effect of calibration is very small in terms of the phase calibration of an antenna if the volume of an array antenna is large because phase calibration is performed based on one phase shifter.
Accordingly, the present disclosure proposes a method and apparatus for calibrating an array antenna, which can solve the aforementioned problems of the conventional technology.
Technical problems to be solved by the present disclosure are not limited by the above-mentioned technical problems, and other technical problems which are not mentioned above can be clearly understood from the following description by those skilled in the art to which the present disclosure pertains.
In an embodiment, a method of calibrating an array antenna in a wireless communication system includes a first step of transmitting a radio signal through a first antenna and a second antenna determined among a plurality of antennas included in the array antenna, a second step of measuring the radio signal through a specific coupling antenna of a plurality of coupling antennas adjacent to the plurality of antennas, a third step of estimating an error of the second antenna based on a result of the measurement of the radio signal, and a fourth step of calibrating the second antenna based on the error.
The first step to the fourth step are repeatedly performed until the calibration of the plurality of antennas is completed. The first antenna is a reference antenna or the second antenna on which the calibration has already been performed. The second antenna is an antenna which is adjacent to the first antenna and on which the calibration has not been performed.
The radio signal may be transmitted based on a pre-configured adjustment value, and the result of the measurement may be based on an output of a power detector coupled to the specific coupling antenna.
The radio signal may be repeatedly transmitted by a specific number of times.
The pre-configured adjustment value may be changed whenever the radio signal is transmitted.
The pre-configured adjustment value may be related to at least one of a phase of the radio signal or a gain of the radio signal.
The pre-configured adjustment value may include a first adjustment value related to the first antenna and a second adjustment value related to the second antenna.
The first antenna and the second antenna may be determined among antennas related to a first location in the array antenna, and the first location may be based on a row or column of the array antenna.
Based on the completion of the calibration of the antennas related to the first location, the first antenna may be determined as any one of the antennas related to the first location, and the second antenna may be determined among antennas related to a second location.
The second location may be based on a row or column adjacent to the first location.
The plurality of coupling antennas may be disposed in one row or one column parallel to a specific row or specific column of the array antenna, respectively, and the specific coupling antenna may be one of coupling antennas belonging to a row or column parallel to the first location.
In another embodiment, an apparatus for calibrating an array antenna in a wireless communication system includes an array antenna, one or more transceivers configured to transmit or receive a radio signal through the array antenna, a plurality of coupling antennas configured to measure the radio signal, a plurality of power detectors coupled to the plurality of coupling antennas, one or more processors configured to control the apparatus, and one or more memories operatively coupled to the one or more processors and configured to store instructions for performing operations when a calibration of the array antenna is executed by the one or more processors.
The operations include a first step of transmitting a radio signal through a first antenna and a second antenna determined among a plurality of antennas included in the array antenna, a second step of measuring the radio signal through a specific coupling antenna of a plurality of coupling antennas adjacent to the plurality of antennas, a third step of estimating an error of the second antenna based on a result of the measurement of the radio signal, and a fourth step of calibrating the second antenna based on the error.
The first step to the fourth step are repeatedly performed until a calibration of the plurality of antennas is completed, the first antenna is a reference antenna or the second antenna on which the calibration has already been performed, and the second antenna is an antenna which is adjacent to the first antenna and on which the calibration has not been performed.
The radio signal may be transmitted based on a pre-configured adjustment value, and the result of the measurement may be based on an output of a power detector coupled to the specific coupling antenna.
The radio signal may be repeatedly transmitted by a specific number of times.
The pre-configured adjustment value may be changed whenever the radio signal is transmitted.
The pre-configured adjustment value may be related to at least one of a phase of the radio signal or a gain of the radio signal.
The pre-configured adjustment value may include a first adjustment value related to the first antenna and a second adjustment value related to the second antenna.
The first antenna and the second antenna may be determined among antennas related to a first location in the array antenna, and the first location may be based on a row or column of the array antenna.
Based on the completion of the calibration of the antennas related to the first location, the first antenna may be determined as any one of the antennas related to the first location, and the second antenna may be determined among antennas related to a second location.
The plurality of coupling antennas may be disposed in one row or one column parallel to a specific row or specific column of the array antenna, respectively, and the specific coupling antenna may be one of coupling antennas belonging to a row or column parallel to the first location.
One or more non-transitory computer-readable media according to still another embodiment of the present disclosure store one or more commands.
One or more instructions executable by one or more processors are configured to enable an apparatus to perform a first step of transmitting a radio signal through a first antenna and a second antenna determined among a plurality of antennas included in the array antenna, a second step of measuring the radio signal through a specific coupling antenna of a plurality of coupling antennas adjacent to the plurality of antennas, a third step of estimating an error of the second antenna based on a result of the measurement of the radio signal, and a fourth step of calibrating the second antenna based on the error.
The first step to the fourth step are repeatedly performed until a calibration of the plurality of antennas is completed, the first antenna is a reference antenna or the second antenna on which the calibration has already been performed, and the second antenna is an antenna which is adjacent to the first antenna and on which the calibration has not been performed.
BRIEF DESCRIPTION OF THE DRAWINGS
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, exemplarily represent embodiments of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 illustrates physical channels and general signal transmission used in a 3GPP system.
FIG. 2 is a view showing an example of a communication structure providable in a 6G system applicable to the present disclosure.
FIG. 3 illustrates a structure of a perceptron to which the method proposed in the present specification can be applied.
FIG. 4 illustrates the structure of a multilayer perceptron to which the method proposed in the present specification can be applied.
FIG. 5 illustrates a structure of a deep neural network to which the method proposed in the present specification can be applied.
FIG. 6 illustrates the structure of a convolutional neural network to which the method proposed in the present specification can be applied.
FIG. 7 illustrates a filter operation in a convolutional neural network to which the method proposed in the present specification can be applied.
FIG. 8 illustrates a neural network structure in which a circular loop to which the method proposed in the present specification can be applied.
FIG. 9 illustrates an operation structure of a recurrent neural network to which the method proposed in the present specification can be applied.
FIG. 10 is a view showing an electromagnetic spectrum applicable to the present disclosure.
FIG. 11 is a view showing a THz communication method applicable to the present disclosure.
FIG. 12 is a view showing a THz wireless communication transceiver applicable to the present disclosure.
FIG. 13 is a view showing a THz signal generation method applicable to the present disclosure.
FIG. 14 is a view showing a wireless communication transceiver applicable to the present disclosure.
FIG. 15 is a view showing a transmitter structure applicable to the present disclosure.
FIG. 16 is a view showing a modulator structure applicable to the present disclosure.
FIG. 17 illustrates the structure of an apparatus for calibrating an array antenna according to an embodiment of the present disclosure.
FIG. 18 is a diagram for describing an operation performed in a group unit in the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 19 illustrates the structure of a system for calibrating an array antenna according to an embodiment of the present disclosure.
FIG. 20 is a diagram for describing the results of simulations of the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 21 is a graph illustrating the output of a power detector related to the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 22 is a diagram for describing an implementation method for the calibration of an antenna array according to a conventional technology.
FIG. 23 is a diagram for describing an implementation method for the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 24 is an example of a change of a first antenna and a second antenna in the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 25 is another example of a change of a first antenna and a second antenna in the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 26 is a diagram for describing the deployment and operation of coupling antennas in the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 27 is a diagram for describing the deployment of coupling antennas in the case of a subarray-based system according to an embodiment of the present disclosure.
FIG. 28 is a flowchart for describing a method of calibrating an array antenna in a wireless communication system according to an embodiment of the present disclosure.
FIG. 29 illustrates a communication system 1 applied to the present disclosure.</div
BACKGROUND OF THE INVENTION
Field of the Invention
The present disclosure relates to a method and apparatus for calibrating an antenna array in a wireless communication system.
Related Art
A mobile communication system was developed to provide a voice service while ensuring the activity of a user. However, the area of the mobile communication system has extended up to data services in addition to voice. Due to a current explosive increase in traffic, there is a shortage of resources. Accordingly, there is a need for a more advanced mobile communication system because users demand higher speed services.
Requirements for a next-generation mobile communication system need to able to support the accommodation of explosive data traffic, a dramatic increase in the data rate per user, the accommodation of a significant increase in the number of connected devices, very low end-to-end latency, and high-energy efficiency. To this end, various technologies, such as dual connectivity, massive multiple input multiple output (MIMO), in-band full duplex, non-orthogonal multiple access (NOMA), the support of a super wideband, and device networking, are researched.
SUMMARY OF THE INVENTION
The present disclosure proposes a method of calibrating an array antenna.
In a conventional technology, the phase and gain error of an array antenna were estimated through a down-conversion mixer. However, the down-conversion mixer has a high cost and a high design level of difficulty.
There was proposed a technology for estimating phase and gain errors based on a channel environment estimated in a reception stage. However, the corresponding technology has a problem in that the accuracy of channel estimation may be degraded and has a critical point I that an effect of calibration is very small in terms of the phase calibration of an antenna if the volume of an array antenna is large because phase calibration is performed based on one phase shifter.
Accordingly, the present disclosure proposes a method and apparatus for calibrating an array antenna, which can solve the aforementioned problems of the conventional technology.
Technical problems to be solved by the present disclosure are not limited by the above-mentioned technical problems, and other technical problems which are not mentioned above can be clearly understood from the following description by those skilled in the art to which the present disclosure pertains.
In an embodiment, a method of calibrating an array antenna in a wireless communication system includes a first step of transmitting a radio signal through a first antenna and a second antenna determined among a plurality of antennas included in the array antenna, a second step of measuring the radio signal through a specific coupling antenna of a plurality of coupling antennas adjacent to the plurality of antennas, a third step of estimating an error of the second antenna based on a result of the measurement of the radio signal, and a fourth step of calibrating the second antenna based on the error.
The first step to the fourth step are repeatedly performed until the calibration of the plurality of antennas is completed. The first antenna is a reference antenna or the second antenna on which the calibration has already been performed. The second antenna is an antenna which is adjacent to the first antenna and on which the calibration has not been performed.
The radio signal may be transmitted based on a pre-configured adjustment value, and the result of the measurement may be based on an output of a power detector coupled to the specific coupling antenna.
The radio signal may be repeatedly transmitted by a specific number of times.
The pre-configured adjustment value may be changed whenever the radio signal is transmitted.
The pre-configured adjustment value may be related to at least one of a phase of the radio signal or a gain of the radio signal.
The pre-configured adjustment value may include a first adjustment value related to the first antenna and a second adjustment value related to the second antenna.
The first antenna and the second antenna may be determined among antennas related to a first location in the array antenna, and the first location may be based on a row or column of the array antenna.
Based on the completion of the calibration of the antennas related to the first location, the first antenna may be determined as any one of the antennas related to the first location, and the second antenna may be determined among antennas related to a second location.
The second location may be based on a row or column adjacent to the first location.
The plurality of coupling antennas may be disposed in one row or one column parallel to a specific row or specific column of the array antenna, respectively, and the specific coupling antenna may be one of coupling antennas belonging to a row or column parallel to the first location.
In another embodiment, an apparatus for calibrating an array antenna in a wireless communication system includes an array antenna, one or more transceivers configured to transmit or receive a radio signal through the array antenna, a plurality of coupling antennas configured to measure the radio signal, a plurality of power detectors coupled to the plurality of coupling antennas, one or more processors configured to control the apparatus, and one or more memories operatively coupled to the one or more processors and configured to store instructions for performing operations when a calibration of the array antenna is executed by the one or more processors.
The operations include a first step of transmitting a radio signal through a first antenna and a second antenna determined among a plurality of antennas included in the array antenna, a second step of measuring the radio signal through a specific coupling antenna of a plurality of coupling antennas adjacent to the plurality of antennas, a third step of estimating an error of the second antenna based on a result of the measurement of the radio signal, and a fourth step of calibrating the second antenna based on the error.
The first step to the fourth step are repeatedly performed until a calibration of the plurality of antennas is completed, the first antenna is a reference antenna or the second antenna on which the calibration has already been performed, and the second antenna is an antenna which is adjacent to the first antenna and on which the calibration has not been performed.
The radio signal may be transmitted based on a pre-configured adjustment value, and the result of the measurement may be based on an output of a power detector coupled to the specific coupling antenna.
The radio signal may be repeatedly transmitted by a specific number of times.
The pre-configured adjustment value may be changed whenever the radio signal is transmitted.
The pre-configured adjustment value may be related to at least one of a phase of the radio signal or a gain of the radio signal.
The pre-configured adjustment value may include a first adjustment value related to the first antenna and a second adjustment value related to the second antenna.
The first antenna and the second antenna may be determined among antennas related to a first location in the array antenna, and the first location may be based on a row or column of the array antenna.
Based on the completion of the calibration of the antennas related to the first location, the first antenna may be determined as any one of the antennas related to the first location, and the second antenna may be determined among antennas related to a second location.
The plurality of coupling antennas may be disposed in one row or one column parallel to a specific row or specific column of the array antenna, respectively, and the specific coupling antenna may be one of coupling antennas belonging to a row or column parallel to the first location.
One or more non-transitory computer-readable media according to still another embodiment of the present disclosure store one or more commands.
One or more instructions executable by one or more processors are configured to enable an apparatus to perform a first step of transmitting a radio signal through a first antenna and a second antenna determined among a plurality of antennas included in the array antenna, a second step of measuring the radio signal through a specific coupling antenna of a plurality of coupling antennas adjacent to the plurality of antennas, a third step of estimating an error of the second antenna based on a result of the measurement of the radio signal, and a fourth step of calibrating the second antenna based on the error.
The first step to the fourth step are repeatedly performed until a calibration of the plurality of antennas is completed, the first antenna is a reference antenna or the second antenna on which the calibration has already been performed, and the second antenna is an antenna which is adjacent to the first antenna and on which the calibration has not been performed.
BRIEF DESCRIPTION OF THE DRAWINGS
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, exemplarily represent embodiments of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 illustrates physical channels and general signal transmission used in a 3GPP system.
FIG. 2 is a view showing an example of a communication structure providable in a 6G system applicable to the present disclosure.
FIG. 3 illustrates a structure of a perceptron to which the method proposed in the present specification can be applied.
FIG. 4 illustrates the structure of a multilayer perceptron to which the method proposed in the present specification can be applied.
FIG. 5 illustrates a structure of a deep neural network to which the method proposed in the present specification can be applied.
FIG. 6 illustrates the structure of a convolutional neural network to which the method proposed in the present specification can be applied.
FIG. 7 illustrates a filter operation in a convolutional neural network to which the method proposed in the present specification can be applied.
FIG. 8 illustrates a neural network structure in which a circular loop to which the method proposed in the present specification can be applied.
FIG. 9 illustrates an operation structure of a recurrent neural network to which the method proposed in the present specification can be applied.
FIG. 10 is a view showing an electromagnetic spectrum applicable to the present disclosure.
FIG. 11 is a view showing a THz communication method applicable to the present disclosure.
FIG. 12 is a view showing a THz wireless communication transceiver applicable to the present disclosure.
FIG. 13 is a view showing a THz signal generation method applicable to the present disclosure.
FIG. 14 is a view showing a wireless communication transceiver applicable to the present disclosure.
FIG. 15 is a view showing a transmitter structure applicable to the present disclosure.
FIG. 16 is a view showing a modulator structure applicable to the present disclosure.
FIG. 17 illustrates the structure of an apparatus for calibrating an array antenna according to an embodiment of the present disclosure.
FIG. 18 is a diagram for describing an operation performed in a group unit in the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 19 illustrates the structure of a system for calibrating an array antenna according to an embodiment of the present disclosure.
FIG. 20 is a diagram for describing the results of simulations of the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 21 is a graph illustrating the output of a power detector related to the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 22 is a diagram for describing an implementation method for the calibration of an antenna array according to a conventional technology.
FIG. 23 is a diagram for describing an implementation method for the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 24 is an example of a change of a first antenna and a second antenna in the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 25 is another example of a change of a first antenna and a second antenna in the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 26 is a diagram for describing the deployment and operation of coupling antennas in the calibration of an antenna array according to an embodiment of the present disclosure.
FIG. 27 is a diagram for describing the deployment of coupling antennas in the case of a subarray-based system according to an embodiment of the present disclosure.
FIG. 28 is a flowchart for describing a method of calibrating an array antenna in a wireless communication system according to an embodiment of the present disclosure.
FIG. 29 illustrates a communication system 1 applied to the present disclosure.
FIG. 30 illustrates wireless devices applicable to the present disclosure.
FIG. 31 illustrates a signal process circuit for a transmission signal applied to the present disclosure.
FIG. 32 illustrates another example of a wireless device applied to the present disclosure.
FIG. 33 illustrates a hand-held device applied to the present disclosure.
DESCRIPTION OF EXEMPLARY EMBODIMENTS
Hereinafter, embodiments disclosed in the present specification will be described in detail with reference to the accompanying drawings, but the same or similar components are denoted by the same and similar reference numerals, and redundant descriptions thereof will be omitted. The suffixes âmoduleâ and âunitâ for components used in the following description are given or used interchangeably in consideration of only the ease of preparation of the specification, and do not have meanings or roles that are distinguished from each other by themselves. In addition, in describing the embodiments disclosed in the present specification, when it is determined that a detailed description of related known technologies may obscure the subject matter of the embodiments disclosed in the present specification, the detailed description thereof will be omitted. In addition, the accompanying drawings are for easy understanding of the embodiments disclosed in the present specification, and the technical idea disclosed in the present specification is not limited by the accompanying drawings, and all modifications included in the spirit and scope of the present invention, It should be understood to include equivalents or substitutes.
In the present disclosure, a base station has the meaning of a terminal node of a network over which the base station directly communicates with a terminal. In this document, a specific operation that is described to be performed by a base station may be performed by an upper node of the base station according to circumstances. That is, it is evident that in a network including a plurality of network nodes including a base station, various operations performed for communication with a terminal may be performed by the base station or other network nodes other than the base station. The base station (BS) may be substituted with another term, such as a fixed station, a Node B, an eNB (evolved-NodeB), a base transceiver system (BTS), an access point (AP), or generation NB (general NB, gNB). Furthermore, the terminal may be fixed or may have mobility and may be substituted with another term, such as user equipment (UE), a mobile station (MS), a user terminal (UT), a mobile subscriber station (MSS), a subscriber station (SS), an advanced mobile station (AMS), a wireless terminal (WT), a machine-type communication (MTC) device, a machine-to-Machine (M2M) device, or a device-to-device (D2D) device.
Hereinafter, downlink (DL) means communication from a base station to UE, and uplink (UL) means communication from UE to a base station. In DL, a transmitter may be part of a base station, and a receiver may be part of UE. In UL, a transmitter may be part of UE, and a receiver may be part of a base station.
Specific terms used in the following description have been provided to help understanding of the present disclosure, and the use of such specific terms may be changed in various forms without departing from the technical sprit of the present disclosure.
The following technologies may be used in a variety of wireless communication systems, such as code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), orthogonal frequency division multiple access (OFDMA), single carrier frequency division multiple access (SC-FDMA), and non-orthogonal multiple access (NOMA). CDMA may be implemented using a radio technology, such as universal terrestrial radio access (UTRA) or CDMA2000. TDMA may be implemented using a radio technology, such as global system for mobile communications (GSM)/general packet radio service (GPRS)/enhanced data rates for GSM evolution (EDGE). OFDMA may be implemented using a radio technology, such as Institute of electrical and electronics engineers (IEEE) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, or evolved UTRA (E-UTRA). UTRA is part of a universal mobile telecommunications system (UMTS). 3rd generation partnership project (3GPP) Long term evolution (LTE) is part of an evolved UMTS (E-UMTS) using evolved UMTS terrestrial radio access (E-UTRA), and it adopts OFDMA in downlink and adopts SC-FDMA in uplink. LTE-advanced (LTE-A) is the evolution of 3GPP LTE.
For clarity, the description is based on a 3GPP communication system (eg, LTE, NR, etc.), but the technical idea of the present invention is not limited thereto. LTE refers to the technology after 3GPP TS 36.xxx Release 8. In detail, LTE technology after 3GPP TS 36.xxx Release 10 is referred to as LTE-A, and LTE technology after 3GPP TS 36.xxx Release 13 is referred to as LTE-A pro. 3GPP NR refers to the technology after TS 38.xxx Release 15. 3GPP 6G may mean technology after TS Release 17 and/or Release 18. âxxxâ means standard document detail number. LTE/NR/6G may be collectively referred to as a 3GPP system. Background art, terms, abbreviations, and the like used in the description of the present invention may refer to matters described in standard documents published before the present invention. For example, you can refer to the following document:
3GPP LTE
36.211: Physical channels and modulation 36.212: Multiplexing and channel coding 36.213: Physical layer procedures 36.300: Overall description 36.331: Radio Resource Control (RRC)
3GPP NR
38.211: Physical channels and modulation 38.212: Multiplexing and channel coding 38.213: Physical layer procedures for control 38.214: Physical layer procedures for data 38.300: NR and NG-RAN Overall Description 38.331: Radio Resource Control (RRC) protocol specification
Physical Channel and Frame Structure
Physical Channels and General Signal Transmission
FIG. 1 illustrates physical channels and general signal transmission used in a 3GPP system. In a wireless communication system, a terminal receives information from a base station through a downlink (DL), and the terminal transmits information to the base station through an uplink (UL). The information transmitted and received by the base station and the terminal includes data and various control information, and various physical channels exist according to the type/use of information transmitted and received by them.
When the terminal is powered on or newly enters a cell, the terminal performs an initial cell search operation such as synchronizing with the base station (S 101 ). To this end, the UE receives a Primary Synchronization Signal (PSS) and a Secondary Synchronization Signal (SSS) from the base station to synchronize with the base station and obtain information such as cell ID. Thereafter, the terminal may receive a physical broadcast channel (PBCH) from the base station to obtain intra-cell broadcast information. Meanwhile, the UE may receive a downlink reference signal (DL RS) in the initial cell search step to check a downlink channel state.
After completing the initial cell search, the UE receives a physical downlink control channel (PDCCH) and a physical downlink shared channel (PDSCH) according to the information carried on the PDCCH, thereby receiving a more specific system Information can be obtained (S 102 ).
On the other hand, when accessing the base station for the first time or when there is no radio resource for signal transmission, the terminal may perform a random access procedure (RACH) for the base station (S 103 to S 106 ). To this end, the UE transmits a specific sequence as a preamble through a physical random access channel (PRACH) (S 103 and S 105 ), and a response message to the preamble through a PDCCH and a corresponding PDSCH (RAR (Random Access Response) message) In the case of contention-based RACH, a contention resolution procedure may be additionally performed (S 106 ).
After performing the above-described procedure, the UE receives PDCCH/PDSCH (S 107 ) and physical uplink shared channel (PUSCH)/physical uplink control channel as a general uplink/downlink signal transmission procedure. (Physical Uplink Control Channel; PUCCH) transmission (S 108 ) can be performed. In particular, the terminal may receive downlink control information (DCI) through the PDCCH. Here, the DCI includes control information such as resource allocation information for the terminal, and different formats may be applied according to the purpose of use.
On the other hand, control information transmitted by the terminal to the base station through uplink or received by the terminal from the base station is a downlink/uplink ACK/NACK signal, a channel quality indicator (CQI), a precoding matrix index (PMI), and (Rank Indicator) may be included. The terminal may transmit control information such as CQI/PMI/RI described above through PUSCH and/or PUCCH.
Structure of Uplink and Downlink Channels
Downlink Channel Structure
The base station transmits a related signal to the terminal through a downlink channel to be described later, and the terminal receives a related signal from the base station through a downlink channel to be described later.
(1) Physical Downlink Shared Channel (PDSCH)
PDSCH carries downlink data (eg, DL-shared channel transport block, DL-SCH TB), and includes Quadrature Phase Shift Keying (QPSK), Quadrature Amplitude Modulation (QAM), 64 QAM, 256 QAM, etc. The modulation method is applied. A codeword is generated by encoding TB. The PDSCH can carry multiple codewords. Scrambling and modulation mapping are performed for each codeword, and modulation symbols generated from each codeword are mapped to one or more layers (Layer mapping). Each layer is mapped to a resource together with a demodulation reference signal (DMRS) to generate an OFDM symbol signal, and is transmitted through a corresponding antenna port.
(2) Physical Downlink Control Channel (PDCCH)
The PDCCH carries downlink control information (DCI) and a QPSK modulation method is applied. One PDCCH is composed of 1, 2, 4, 8, 16 Control Channel Elements (CCEs) according to the Aggregation Level (AL). One CCE consists of 6 REGs (Resource Element Group). One REG is defined by one OFDM symbol and one (P)RB.
The UE acquires DCI transmitted through the PDCCH by performing decoding (aka, blind decoding) on the set of PDCCH candidates. The set of PDCCH candidates decoded by the UE is defined as a PDCCH search space set. The search space set may be a common search space or a UE-specific search space. The UE may acquire DCI by monitoring PDCCH candidates in one or more search space sets set by MIB or higher layer signaling.
Uplink Channel Structure
The terminal transmits a related signal to the base station through an uplink channel to be described later, and the base station receives a related signal from the terminal through an uplink channel to be described later.
(1) Physical uplink shared channel (PUSCH)
PUSCH carries uplink data (eg, UL-shared channel transport block, UL-SCH TB) and/or uplink control information (UCI), and CP-OFDM (Cyclic Prefix-Orthogonal Frequency Division Multiplexing) waveform (waveform), DFT-s-OFDM (Discrete Fourier Transform-spread-Orthogonal Frequency Division Multiplexing) is transmitted based on the waveform. When the PUSCH is transmitted based on the DFT-s-OFDM waveform, the UE transmits the PUSCH by applying transform precoding. For example, when transform precoding is not possible (eg, transform precoding is disabled), the UE transmits a PUSCH based on the CP-OFDM waveform, and when transform precoding is possible (eg, transform precoding is enabled), the UE is CP-OFDM. PUSCH may be transmitted based on a waveform or a DFT-s-OFDM waveform. PUSCH transmission is dynamically scheduled by the UL grant in the DCI or is semi-static based on higher layer (e.g., RRC) signaling (and/or Layer 1 (L1) signaling (e.g., PDCCH)). Can be scheduled (configured grant). PUSCH transmission may be performed based on a codebook or a non-codebook.
(2) Physical Uplink Control Channel (PUCCH)
The PUCCH carries uplink control information, HARQ-ACK, and/or scheduling request (SR), and may be divided into a plurality of PUCCHs according to the PUCCH transmission length.
6G System General
A 6G (wireless communication) system has purposes such as (i) very high data rate per device, (ii) a very large number of connected devices, (iii) global connectivity, (iv) very low latency, (v) decrease in energy consumption of battery-free IoT devices, (vi) ultra-reliable connectivity, and (vii) connected intelligence with machine learning capacity. The vision of the 6G system may include four aspects such as âintelligent connectivityâ, âdeep connectivityâ, âholographic connectivityâ and âubiquitous connectivityâ, and the 6G system may satisfy the requirements shown in Table 1 below. That is, Table 1 shows the requirements of the 6G system.
TABLE 1
Per device peak data rate
â1 Tbps
E2E latency
â1 ms
Maximum spectral efficiency
100 bps/Hz
Mobility support
Up to 1000 km/hr
Satellite integration
Fully
AI
Fully
Autonomous vehicle
Fully
XR
Fully
Haptic Communication
Fully
At this time, the 6G system may have key factors such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), massive machine type communications (mMTC), AI integrated communication, tactile Internet, high throughput, high network capacity, high energy efficiency, low backhaul and access network congestion and enhanced data security.
FIG. 2 is a view showing an example of a communication structure providable in a 6G system applicable to the present disclosure.
Referring to FIG. 15 , the 6G system will have 50 times higher simultaneous wireless communication connectivity than a 5G wireless communication system. URLLC, which is the key feature of 5G, will become more important technology by providing end-to-end latency less than 1 ms in 6G communication. At this time, the 6G system may have much better volumetric spectrum efficiency unlike frequently used domain spectrum efficiency. The 6G system may provide advanced battery technology for energy harvesting and very long battery life and thus mobile devices may not need to be separately charged in the 6G system. In addition, in 6G, new network characteristics may be as follows.
Satellites integrated network: To provide a global mobile group, 6G will be integrated with satellite. Integrating terrestrial waves, satellites and public networks as one wireless communication system may be very important for 6G. Connected intelligence: Unlike the wireless communication systems of previous generations, 6G is innovative and wireless evolution may be updated from âconnected thingsâ to âconnected intelligenceâ. AI may be applied in each step (or each signal processing procedure which will be described below) of a communication procedure. Seamless integration of wireless information and energy transfer: A 6G wireless network may transfer power in order to charge the batteries of devices such as smartphones and sensors. Therefore, wireless information and energy transfer (WIET) will be integrated. Ubiquitous super 3-dimemtion connectivity: Access to networks and core network functions of drones and very low earth orbit satellites will establish super 3D connection in 6G ubiquitous.
In the new network characteristics of 6G, several general requirements may be as follows.
Small cell networks: The idea of a small cell network was introduced in order to improve received signal quality as a result of throughput, energy efficiency and spectrum efficiency improvement in a cellular system. As a result, the small cell network is an essential feature for 5G and beyond 5G (5 GB) communication systems. Accordingly, the 6G communication system also employs the characteristics of the small cell network. Ultra-dense heterogeneous network: Ultra-dense heterogeneous networks will be another important characteristic of the 6G communication system. A multi-tier network composed of heterogeneous networks improves overall QoS and reduce costs. High-capacity backhaul: Backhaul connection is characterized by a high-capacity backhaul network in order to support high-capacity traffic. A high-speed optical fiber and free space optical (FSO) system may be a possible solution for this problem. Radar technology integrated with mobile technology: High-precision localization (or location-based service) through communication is one of the functions of the 6G wireless communication system. Accordingly, the radar system will be integrated with the 6G network. Softwarization and virtualization: Softwarization and virtualization are two important functions which are the bases of a design process in a 5 GB network in order to ensure flexibility, reconfigurability and programmability.
Core implementation technology of 6G system
Artificial Intelligence (AI)
Technology which is most important in the 6G system and will be newly introduced is AI. AI was not involved in the 4G system. A 5G system will support partial or very limited AI. However, the 6G system will support AI for full automation. Advance in machine learning will create a more intelligent network for real-time communication in 6G. When AI is introduced to communication, real-time data transmission may be simplified and improved. AI may determine a method of performing complicated target tasks using countless analysis. That is, AI may increase efficiency and reduce processing delay.
Time-consuming tasks such as handover, network selection or resource scheduling may be immediately performed by using AI. AI may play an important role even in M2M, machine-to-human and human-to-machine communication. In addition, AI may be rapid communication in a brain computer interface (BCI). An AI based communication system may be supported by meta materials, intelligent structures, intelligent networks, intelligent devices, intelligent recognition radios, self-maintaining wireless networks and machine learning.
Recently, attempts have been made to integrate AI with a wireless communication system in the application layer or the network layer, but deep learning have been focused on the wireless resource management and allocation field. However, such studies are gradually developed to the MAC layer and the physical layer, and, particularly, attempts to combine deep learning in the physical layer with wireless transmission are emerging. AI-based physical layer transmission means applying a signal processing and communication mechanism based on an AI driver rather than a traditional communication framework in a fundamental signal processing and communication mechanism. For example, channel coding and decoding based on deep learning, signal estimation and detection based on deep learning, multiple input multiple output (MIMO) mechanisms based on deep learning, resource scheduling and allocation based on AI, etc. may be included.
Machine learning may be used for channel estimation and channel tracking and may be used for power allocation, interference cancellation, etc. in the physical layer of DL. In addition, machine learning may be used for antenna selection, power control, symbol detection, etc. in the MIMO system.
However, application of a deep neutral network (DNN) for transmission in the physical layer may have the following problems.
Deep learning-based AI algorithms require a lot of training data in order to optimize training parameters. However, due to limitations in acquiring data in a specific channel environment as training data, a lot of training data is used offline. Static training for training data in a specific channel environment may cause a contradiction between the diversity and dynamic characteristics of a radio channel.
In addition, currently, deep learning mainly targets real signals. However, the signals of the physical layer of wireless communication are complex signals. For matching of the characteristics of a wireless communication signal, studies on a neural network for detecting a complex domain signal are further required.
Hereinafter, machine learning will be described in greater detail.
Machine learning refers to a series of operations to train a machine in order to create a machine which can perform tasks which cannot be performed or are difficult to be performed by people. Machine learning requires data and learning models. In machine learning, data learning methods may be roughly divided into three methods, that is, supervised learning, unsupervised learning and reinforcement learning.
Neural network learning is to minimize output error. Neural network learning refers to a process of repeatedly inputting training data to a neural network, calculating the error of the output and target of the neural network for the training data, backpropagating the error of the neural network from the output layer of the neural network to an input layer in order to reduce the error and updating the weight of each node of the neural network.
Supervised learning may use training data labeled with a correct answer and the unsupervised learning may use training data which is not labeled with a correct answer. That is, for example, in case of supervised learning for data classification, training data may be labeled with a category. The labeled training data may be input to the neural network, and the output (category) of the neural network may be compared with the label of the training data, thereby calculating the error. The calculated error is backpropagated from the neural network backward (that is, from the output layer to the input layer), and the connection weight of each node of each layer of the neural network may be updated according to backpropagation. Change in updated connection weight of each node may be determined according to the learning rate. Calculation of the neural network for input data and backpropagation of the error may configure a learning cycle (epoch). The learning data is differently applicable according to the number of repetitions of the learning cycle of the neural network. For example, in the early phase of learning of the neural network, a high learning rate may be used to increase efficiency such that the neural network rapidly ensures a certain level of performance and, in the late phase of learning, a low learning rate may be used to increase accuracy.
The learning method may vary according to the feature of data. For example, for the purpose of accurately predicting data transmitted from a transmitter in a receiver in a communication system, learning may be performed using supervised learning rather than unsupervised learning or reinforcement learning.
The learning model corresponds to the human brain and may be regarded as the most basic linear model. However, a paradigm of machine learning using a neural network structure having high complexity, such as artificial neural networks, as a learning model is referred to as deep learning.
Neural network cores used as a learning method may roughly include a deep neural network (DNN) method, a convolutional deep neural network (CNN) method and a recurrent Boltzmman machine (RNN) method. Such a learning model is applicable.
An artificial neural network is an example of connecting several perceptrons.
FIG. 3 illustrates a structure of a perceptron to which the method proposed in the present specification can be applied.
Referring to FIG. 3 , when an input vector x=(x1,x2, . . . ,xd) is input, each component is multiplied by a weight (W1,W2, . . . ,Wd), and all the results are summed. After that, the entire process of applying the activation function Ï(·) is called a perceptron. The huge artificial neural network structure may extend the simplified perceptron structure shown in FIG. 3 to apply input vectors to different multidimensional perceptrons. For convenience of explanation, an input value or an output value is referred to as a node.
Meanwhile, the perceptron structure illustrated in FIG. 3 may be described as being composed of a total of three layers based on an input value and an output value. An artificial neural network in which H (d+1) dimensional perceptrons exist between the 1st layer and the 2nd layer, and K (H+1) dimensional perceptrons exist between the 2nd layer and the 3rd layer, as shown in FIG. 4 .
FIG. 4 illustrates the structure of a multilayer perceptron to which the method proposed in the present specification can be applied.
The layer where the input vector is located is called an input layer, the layer where the final output value is located is called the output layer, and all layers located between the input layer and the output layer are called a hidden layer. In the example of FIG. 4 , three layers are disclosed, but since the number of layers of the artificial neural network is counted excluding the input layer, it can be viewed as a total of two layers. The artificial neural network is constructed by connecting the perceptrons of the basic blocks in two dimensions.
The above-described input layer, hidden layer, and output layer can be jointly applied in various artificial neural network structures such as CNN and RNN to be described later as well as multilayer perceptrons. The greater the number of hidden layers, the deeper the artificial neural network is, and the machine learning paradigm that uses the deep enough artificial neural network as a learning model is called Deep Learning. In addition, the artificial neural network used for deep learning is called a deep neural network (DNN).
FIG. 5 illustrates a structure of a deep neural network to which the method proposed in the present specification can be applied.
The deep neural network shown in FIG. 5 is a multilayer perceptron composed of eight hidden layers+output layers. The multilayer perceptron structure is expressed as a fully-connected neural network. In a fully connected neural network, a connection relationship does not exist between nodes located on the same layer, and a connection relationship exists only between nodes located on adjacent layers. DNN has a fully connected neural network structure and is composed of a combination of multiple hidden layers and activation functions, so it can be usefully applied to understand the correlation characteristics between input and output. Here, the correlation characteristic may mean a joint probability of input/output.
âOn the other hand, depending on how the plurality of perceptrons are connected to each other, various artificial neural network structures different from the aforementioned DNN can be formed.
In a DNN, nodes located inside one layer are arranged in a one-dimensional vertical direction. However, in FIG. 6 , it may be assumed that w nodes are arranged in two dimensions, and h nodes are arranged in a two-dimensional manner (convolutional neural network structure of FIG. 6 ). In this case, since a weight is added per connection in the connection process from one input node to the hidden layer, a total of hÃw weights must be considered. Since there are hÃw nodes in the input layer, a total of h2w2 weights are required between two adjacent layers.
FIG. 6 illustrates the structure of a convolutional neural network to which the method proposed in the present specification can be applied.
The convolutional neural network of FIG. 6 has a problem in that the number of weights increases exponentially according to the number of connections, so instead of considering the connection of all modes between adjacent layers, it is assumed that a filter having a small size exists. Thus, as shown in FIG. 7 , weighted sum and activation function calculations are performed on a portion where the filters overlap.
One filter has a weight corresponding to the number as much as the size, and learning of the weight may be performed so that a certain feature on an image can be extracted and output as a factor. In FIG. 7 , a filter having a size of 3Ã3 is applied to the upper leftmost 3Ã3 area of the input layer, and an output value obtained by performing a weighted sum and activation function operation for a corresponding node is stored in z22.
While scanning the input layer, the filter performs weighted summation and activation function calculation while moving horizontally and vertically by a predetermined interval, and places the output value at the position of the current filter. This method of operation is similar to the convolution operation on images in the field of computer vision, so a deep neural network with this structure is called a convolutional neural network (CNN), and a hidden layer generated as a result of the convolution operation. Is referred to as a convolutional layer. In addition, a neural network in which a plurality of convolutional layers exists is referred to as a deep convolutional neural network (DCNN).
FIG. 7 illustrates a filter operation in a convolutional neural network to which the method proposed in the present specification can be applied.
In the convolutional layer, the number of weights may be reduced by calculating a weighted sum by including only nodes located in a region covered by the filter in the node where the current filter is located. Due to this, one filter can be used to focus on features for the local area. Accordingly, the CNN can be effectively applied to image data processing in which the physical distance in the 2D area is
CLAIMS
Claims ( 20 )
What is claimed is:
1. A method of calibrating an array antenna, the method performed by an apparatus for calibrating an array antenna in a wireless communication system comprising:
a first step of transmitting a radio signal through a first antenna and a second antenna determined among a plurality of antennas included in the array antenna;
a second step of measuring the radio signal through a specific coupling antenna of a plurality of coupling antennas adjacent to the plurality of antennas;
a third step of estimating an error of the second antenna based on a result of the measurement of the radio signal; and
a fourth step of calibrating the second antenna based on the error,
wherein the first step to the fourth step are repeatedly performed until a calibration of the plurality of antennas is completed,
wherein the first antenna is a reference antenna or the second antenna on which the calibration has already been performed, and
wherein the second antenna is an antenna which is adjacent to the first antenna and on which the calibration has not been performed.
2. The method of claim 1 ,
wherein the radio signal is transmitted based on a pre-configured adjustment value, and
wherein the result of the measurement is based on an output of a power detector coupled to the specific coupling antenna.
3. The method of claim 2 ,
wherein the radio signal is repeatedly transmitted by a specific number of times.
4. The method of claim 3 ,
wherein the pre-configured adjustment value is changed whenever the radio signal is transmitted.
5. The method of claim 4 ,
wherein the pre-configured adjustment value is related to at least one of a phase of the radio signal or a gain of the radio signal.
6. The method of claim 5 ,
wherein the pre-configured adjustment value includes a first adjustment value related to the first antenna and a second adjustment value related to the second antenna.
7. The method of claim 1 ,
wherein the first antenna and the second antenna are determined among antennas related to a first location in the array antenna, and
wherein the first location is based on a row or column of the array antenna.
8. The method of claim 7 ,
wherein based on a completion of the calibration of the antennas related to the first location, the first antenna is determined as any one of the antennas related to the first location, and the second antenna is determined among antennas related to a second location.
9. The method of claim 8 ,
wherein the second location is based on a row or column adjacent to the first location.
10. The method of claim 7 ,
wherein the plurality of coupling antennas is disposed in one row or one column parallel to a specific row or specific column of the array antenna, respectively, and
wherein the specific coupling antenna is one of coupling antennas belonging to a row or column parallel to the first location.
11. An apparatus for calibrating an array antenna in a wireless communication system, the apparatus comprising:
an array antenna;
one or more transceivers configured to transmit or receive a radio signal through the array antenna;
a plurality of coupling antennas configured to measure the radio signal;
a plurality of power detectors coupled to the plurality of coupling antennas;
one or more processors configured to control the apparatus; and
one or more memories operatively coupled to the one or more processors and configured to store instructions for performing operations when a calibration of the array antenna is executed by the one or more processors,
wherein the operations include:
a first step of transmitting a radio signal through a first antenna and a second antenna determined among a plurality of antennas included in the array antenna;
a second step of measuring the radio signal through a specific coupling antenna of a plurality of coupling antennas adjacent to the plurality of antennas;
a third step of estimating an error of the second antenna based on a result of the measurement of the radio signal; and
a fourth step of calibrating the second antenna based on the error,
wherein the first step to the fourth step are repeatedly performed until a calibration of the plurality of antennas is completed,
wherein the first antenna is a reference antenna or the second antenna on which the calibration has already been performed, and
wherein the second antenna is an antenna which is adjacent to the first antenna and on which the calibration has not been performed.
12. The apparatus of claim 11 ,
wherein the radio signal is transmitted based on a pre-configured adjustment value, and
wherein the result of the measurement is based on an output of a power detector coupled to the specific coupling antenna, among the plurality of power detectors.
13. The apparatus of claim 12 ,
wherein the radio signal is repeatedly transmitted by a specific number of times.
14. The apparatus of claim 13 ,
wherein the pre-configured adjustment value is changed whenever the radio signal is transmitted.
15. The apparatus of claim 14 ,
wherein the pre-configured adjustment value is related to at least one of a phase of the radio signal or a gain of the radio signal.
16. The apparatus of claim 15 ,
wherein the pre-configured adjustment value includes a first adjustment value related to the first antenna and a second adjustment value related to the second antenna.
17. The apparatus of claim 11 ,
wherein the first antenna and the second antenna are determined among antennas related to a first location in the array antenna, and
wherein the first location is based on a row or column of the array antenna.
18. The apparatus of claim 17 ,
wherein based on a completion of the calibration of the antennas related to the first location, the first antenna is determined as any one of the antennas related to the first location, and the second antenna is determined among antennas related to a second location.
19. The apparatus of claim 17 ,
wherein the plurality of coupling antennas is disposed in one row or one column parallel to a specific row or specific column of the array antenna, respectively, and
wherein the specific coupling antenna is one of coupling antennas belonging to a row or column parallel to the first location.
20. One or more non-transitory computer-readable media storing one or more commands, wherein one or more commands executable by one or more processors are configured to enable an apparatus to perform:
a first step of transmitting a radio signal through a first antenna and a second antenna determined among a plurality of antennas included in the array antenna;
a second step of measuring the radio signal through a specific coupling antenna of a plurality of coupling antennas adjacent to the plurality of antennas;
a third step of estimating an error of the second antenna based on a result of the measurement of the radio signal; and
a fourth step of calibrating the second antenna based on the error,
wherein the first step to the fourth step are repeatedly performed until a calibration of the plurality of antennas is completed,
wherein the first antenna is a reference antenna or the second antenna on which the calibration has already been performed, and
wherein the second antenna is an antenna which is adjacent to the first antenna and on which the calibration has not been performed.
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