Apparatus, method, and storage medium for analyzing channel in wireless communication system

Abstract

This electronic device may comprise: at least one processor; and a memory that stores instructions. The instructions, when executed individually or collectively by the at least one processor, may instruct the electronic device to: generate first modified covariance information by generating covariance information of a channel for reception antennas on the basis of channel estimation using a reference signal obtained from another electronic device and setting, as a reference value, each of covariance components of the covariance information corresponding to a first component group determined on the basis of the magnitude of a covariance component from among component groups indicating correlation between the reception antennas; generate second modified covariance information by setting, as the reference value, each of covariance components of the first modified covariance information corresponding to a second component group different from the first component group from among the component groups; and transmit a signal to the other electronic device according to precoding information determined by using the second modified covariance information.

Description

Device, method, and storage medium for analyzing a channel in a wireless communication system

[0001] The present disclosure relates to a wireless communication system, and more particularly, to a device, method, and storage medium for analyzing a channel.

[0002] To improve signal transmission and reception performance, multiple antenna elements may be utilized. For example, the technologies utilized by the multiple antenna elements may include single-input multiple-output (SIMO) technology, multiple-input single-output (MISO) technology, and multiple-input multiple-output (MIMO) technology. The channel capacity of a wireless communication system utilizing the above technologies utilizing multiple antenna elements can be significantly improved compared to single-antenna technology.

[0003] The above information may be provided as background art to aid in understanding the present disclosure. No claim or determination is made as to whether any of the above is applicable as prior art related to the present disclosure.

[0004] An electronic device may include at least one processor comprising a processing circuit. The electronic device may include a memory comprising one or more storage media storing instructions. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to generate covariance information of a channel for receiving antennas based on a channel estimation using a reference signal acquired from another electronic device. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to generate first modified covariance information by setting each of the covariance components of the covariance information corresponding to a first component group determined based on the magnitude of the covariance component among the component groups representing a correlation between the receiving antennas to a reference value. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to generate second modified covariance information by setting each of the covariance components of the first modified covariance information corresponding to a second component group different from the first component group among the component groups to the reference value. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to transmit a signal to the other electronic device according to precoding information determined using the second modified covariance information.

[0005] A method performed by an electronic device may include generating covariance information of a channel for receiving antennas based on channel estimation using a reference signal acquired from another electronic device. The method may include generating first modified covariance information by setting each of the covariance components of the covariance information, which corresponds to a first component group determined based on a magnitude of the covariance component among component groups representing a correlation between the receiving antennas, to a reference value. The method may include generating second modified covariance information by setting each of the covariance components of the first modified covariance information, which corresponds to a second component group different from the first component group, to the reference value. The method may include transmitting a signal to the other electronic device according to precoding information determined using the second modified covariance information.

[0006] A non-transitory computer-readable storage medium may store one or more programs that, when individually or collectively executed by at least one processor of an electronic device, cause the electronic device to generate covariance information of a channel for receive antennas based on a channel estimation using a reference signal acquired from another electronic device. The non-transitory computer-readable storage medium may store one or more programs that, when individually or collectively executed by the at least one processor, cause the electronic device to generate first modified covariance information by setting each of the covariance components of the covariance information corresponding to a first component group determined based on a magnitude of the covariance component among the component groups representing a correlation between the receive antennas to a reference value. The non-transitory computer-readable storage medium may store one or more programs that, when individually or collectively executed by the at least one processor, cause second modified covariance information to be generated by setting each of the covariance components of the first modified covariance information corresponding to a second component group different from the first component group among the component groups to the reference value. The non-transitory computer-readable storage medium may store one or more programs that, when individually or collectively executed by the at least one processor, cause a signal to be transmitted to the other electronic device according to precoding information determined using the second modified covariance information.

[0007] Figure 1 illustrates an example of a wireless communication system.

[0008] Figure 2a illustrates an example of network entities according to distributed deployment.

[0009] Figure 2b illustrates an example of function splitting of network entities.

[0010] Figure 3 illustrates an example of a functional configuration of an electronic device.

[0011] Figure 4 illustrates an example of a MIMO (multiple input multiple output) transmitter and receiver.

[0012] Figure 5 is a diagram illustrating an example of SVD (singular value decomposition) for channel information in MIMO.

[0013] FIG. 6a illustrates an example of an operational flow for how an electronic device decomposes covariance information of a channel based on component groups.

[0014] Figure 6b illustrates examples of component groups corresponding to covariance components within the covariance information of a channel.

[0015] Figure 6c shows examples of component groups for the covariance matrix of a channel.

[0016] FIG. 7a illustrates an example of an operational flow for a method in which an electronic device decomposes covariance information of a channel based on a sequence of covariance components.

[0017] Figure 7b illustrates an example of covariance information of a channel decomposed according to a sequence of covariance components.

[0018] Figures 8a and 8b illustrate examples of graphs showing mean square error (MSE) according to the number of transmitting antennas.

[0019] FIG. 9 illustrates an example of an operational flow for a method in which an electronic device decomposes covariance information of a component group-based channel and transmits data.

[0020] The terms used in this disclosure are used only to describe specific embodiments and may not be intended to limit the scope of other embodiments. The singular expression may include plural expressions unless the context clearly indicates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by those of ordinary skill in the art described in this disclosure. Terms defined in general dictionaries among the terms used in this disclosure may be interpreted as having the same or similar meaning in the context of the relevant technology, and shall not be interpreted in an idealized or overly formal sense unless explicitly defined in this disclosure. In some cases, even if a term is defined in this disclosure, it cannot be interpreted to exclude embodiments of the present disclosure.

[0021] The various embodiments of the present disclosure described below illustrate a hardware-based approach as an example. However, since the various embodiments of the present disclosure include techniques utilizing both hardware and software, the various embodiments of the present disclosure do not exclude a software-based approach.

[0022] In the following description, terms referring to signals (e.g., packet, message, signal, information, signaling), terms referring to resources (e.g., symbol, slot, subframe, radio frame, subcarrier, RE (resource element), RB (resource block), BWP (bandwidth part), occasion), terms for operational states (e.g., step, operation, procedure), terms referring to data (e.g., packet, message, user stream, information, bit, symbol, codeword), terms referring to channels, terms referring to network entities (distributed unit (DU), radio unit (RU), central unit (CU), CU-CP (control plane), CU-UP (user plane), O-DU (O-RAN (open radio access network) DU), O-RU (O-RAN RU), O-CU (O-RAN CU), Terms such as O-CU-UP (O-RAN CU-CP), O-CU-CP (O-RAN CU-CP)), referring to components of the device, are examples for convenience of explanation. Therefore, the present disclosure is not limited to the terms described below, and other terms having equivalent technical meanings may be used. In addition, terms such as '... part', '... device', '... object', '... body', etc. used below may mean at least one shape structure or a unit that processes a function.

[0023] In addition, in the present disclosure, expressions such as "more than" or "less than" may be used to determine whether a specific condition is satisfied or fulfilled, but this is merely a description for expressing an example and does not exclude descriptions such as "more than" or "less than." A condition described as "more than" may be replaced with "more than," a condition described as "less than" may be replaced with "less than," and a condition described as "more than and less than" may be replaced with "more than and less than." In addition, hereinafter, "A" to "B" mean at least one of elements from A (including A) to B (including B). hereinafter, "C" and / or "D" mean at least one of "C" or "D," that is, including {"C", "D", "C" and "D"}.

[0024] Although this disclosure describes embodiments using terminology used in certain communication standards (e.g., 3rd Generation Partnership Project (3GPP)), this is merely an example for illustrative purposes. Embodiments of this disclosure can also be applied to other communication and broadcasting systems.

[0025] Figure 1 illustrates an example of a wireless communication system.

[0026] Referring to FIG. 1, FIG. 1 illustrates a base station (110) and a terminal (120) as some of the nodes utilizing a wireless channel in a wireless communication system. Although FIG. 1 illustrates only one base station, the wireless communication system may further include other base stations identical or similar to the base station (110).

[0027] The base station (110) is a network infrastructure that provides wireless access to the terminal (120). The base station (110) has coverage defined based on the distance at which a signal can be transmitted. In addition to the base station, the base station (110) may be referred to as an 'access point (AP)', 'eNodeB (eNB)', '5th generation node', 'next generation nodeB (gNB)', 'wireless point', 'transmission / reception point (TRP)', or other terms having equivalent technical meanings.

[0028] The terminal (120) is a device used by a user and communicates with the base station (110) via a wireless channel. The link from the base station (110) to the terminal (120) is referred to as a downlink (DL), and the link from the terminal (120) to the base station (110) is referred to as an uplink (UL). In addition, although not shown in FIG. 1, the terminal (120) and another terminal may communicate with each other via a wireless channel. In this case, the link between the terminal (120) and another terminal (device-to-device link, D2D) is referred to as a sidelink, and the sidelink may be used interchangeably with the PC5 interface. In some other embodiments, the terminal (120) may be operated without the involvement of a user. In one embodiment, the terminal (120) is a device that performs machine type communication (MTC) and may not be carried by the user. Additionally, according to one embodiment, the terminal (120) may be an NB (narrowband)-IoT (internet of things) device.

[0029] The terminal (120) may be referred to as a terminal, or other terms such as 'user equipment (UE),' 'customer premises equipment (CPE),' 'mobile station,' 'subscriber station,' 'remote terminal,' 'wireless terminal,' 'electronic device,' or 'user device,' or other terms having equivalent technical meanings.

[0030] The base station (110) and the terminal (120) can perform beamforming. The base station (110) and the terminal (120) can transmit and receive wireless signals in a relatively low frequency band (e.g., FR 1 (frequency range 1) of NR). In addition, the base station (110) and the terminal (120) can transmit and receive wireless signals in a relatively high frequency band (e.g., FR 2 (or, FR 2-1, FR 2-2, FR 2-3), FR 3 of NR), millimeter wave (mmWave) band (e.g., 28 GHz, 30 GHz, 38 GHz, 60 GHz)). To improve channel gain, the base station (110) and the terminal (120) can perform beamforming. Here, the beamforming can include transmission beamforming and reception beamforming. The base station (110) and the terminal (120) can impart directionality to the transmitted or received signal. To this end, the base station (110) and the terminal (120) can select serving beams through a beam search or beam management procedure. After the serving beams are selected, subsequent communication can be performed through resources that have a QCL relationship with the resource that transmitted the serving beams.

[0031] If large-scale characteristics of a channel carrying a symbol on a first antenna port can be inferred from a channel carrying a symbol on a second antenna port, the first antenna port and the second antenna port can be evaluated to have a QCL relationship. For example, the large-scale characteristics may include at least one of delay spread, Doppler spread, Doppler shift, average gain, average delay, and a spatial receiver parameter.

[0032] Although both the base station (110) and the terminal (120) are described as performing beamforming in FIG. 1, the embodiments of the present disclosure are not necessarily limited thereto. In some embodiments, the terminal may or may not perform beamforming. Furthermore, the base station may or may not perform beamforming. That is, either only one of the base station and the terminal may perform beamforming, or neither the base station nor the terminal may perform beamforming.

[0033] In the present disclosure, a beam refers to a spatial flow of a signal in a wireless channel, and is formed by one or more antennas (or antenna elements), and this forming process may be referred to as beamforming. Beamforming may include at least one of analog beamforming and digital beamforming (e.g., precoding). Reference signals transmitted based on beamforming may include, for example, a demodulation-reference signal (DM-RS), a channel state information-reference signal (CSI-RS), a synchronization signal / physical broadcast channel (SS / PBCH), and a sounding reference signal (SRS). In addition, as a configuration for each reference signal, an IE such as a CSI-RS resource or an SRS-resource may be used, and this configuration may include information associated with the beam. Information associated with a beam may mean whether the configuration (e.g., a CSI-RS resource) uses the same spatial domain filter as another configuration (e.g., another CSI-RS resource within the same CSI-RS resource set) or a different spatial domain filter, or whether it is quasi-co-located (QCL) with a reference signal, and if so, what type it is (e.g., QCL type A, B, C, D).

[0034] In communication systems with relatively large cell radius of base stations, each base station was installed to include the functions of a digital processing unit (or distributed unit (DU)) and a radio frequency (RF) processing unit (or radio unit (RU)). However, as higher frequency bands are used in 4G (4th generation) and / or subsequent communication systems (e.g., 5G) and the cell coverage of base stations becomes smaller, the number of base stations to cover a specific area has increased. The burden of installation costs on operators for installing base stations has also increased. In order to minimize the installation cost of base stations, a structure has been proposed in which the digital unit (DU) and radio unit (RU) (or massive multiple input multiple output unit (MMU)) of the base station are separated, one or more RUs are connected to one DU through a wired network, and one or more RUs are geographically distributed to cover a specific area. Below, the layout structure and expansion examples of base stations according to various embodiments of the present disclosure are described through FIG. 2a.

[0035] Figure 2a illustrates an example of network entities according to distributed deployment.

[0036] For example, the network entities may include a digital unit (DU) (210) and a radio unit (RU) (220) (or a massive multiple input multiple output (MMU) unit). For example, the network entities may be connected via a fronthaul. Unlike the backhaul between a base station and a core network, the fronthaul refers to entities (e.g., DU (210), RU (220)) between a wireless LAN and a base station. Although FIG. 2A illustrates an example of a fronthaul structure between a DU (210) and one RU (220), this is merely for convenience of explanation and the present disclosure is not limited thereto. In other words, embodiments of the present disclosure may also be applied to a fronthaul structure between one DU and multiple RUs. For example, embodiments of the present disclosure may be applied to a fronthaul structure between one DU and two RUs. Additionally, the embodiments of the present disclosure can also be applied to a fronthaul structure between one DU and three RUs.

[0037] Referring to FIG. 2A, a base station (110) may include a DU (210) and a RU (220). A fronthaul (215) between the DU (210) and the RU (220) may be operated via an Fx interface. For the operation of the fronthaul (215), an interface such as an enhanced common public radio interface (eCPRI) or radio over ethernet (ROE) may be used, for example. Depending on the implementation example, the DU (210) may be referred to as a baseband unit (BBU), a digital BBU, a baseband digital unit, a digital processing unit, a digital processing circuit, a baseband processing circuit, a baseband processing unit, and / or equivalent technical terms in addition to a DU (digital unit). According to an implementation example, the RU (220) may be referred to as a remote unit, a radio demote head (RRH), a radio processing circuit, a radio processing unit, an antenna-integrated radio, an air radio device, an air scale communication device, a radio device, a radio communication device, and / or equivalent technical terms in addition to the RU (radio unit). In addition, according to an implementation example, although a network entity connected to the DU (210) in the present disclosure is described as the RU (220), it is of course possible for an MMU (massive multiple input multiple output) unit) to be connected to and used with the DU (210) instead of the RU (220).

[0038] As communication technology advances, mobile data traffic increases, significantly increasing the bandwidth requirements for the fronthaul between the digital unit and the wireless unit. In a deployment such as a centralized / cloud radio access network (C-RAN), the DU (210) performs functions for the packet data convergence protocol (PDCP), radio link control (RLC), media access control (MAC), and physical (PHY) layer, and the RU (220) can be implemented to perform functions for the PHY layer in addition to the RF (radio frequency) function.

[0039] The DU (210) may be responsible for upper layer functions of a wireless network. For example, the DU (210) may perform functions of the MAC layer and a part of the PHY layer. Here, a part of the PHY layer refers to functions performed at a higher level among the functions of the PHY layer, and may include, for example, channel encoding (or channel decoding), scrambling (or descrambling), modulation (or demodulation), and layer mapping (or layer demapping). According to an embodiment, if the DU (210) complies with the O-RAN standard, it may be referred to as an O-DU (O-RAN DU). The DU (210) may be replaced with a first network entity for a base station (e.g., gNB) in embodiments of the present disclosure, if necessary.

[0040] The RU (220) may be responsible for lower layer functions of a wireless network. For example, the RU (220) may perform a part of the PHY layer, an RF function. Here, a part of the PHY layer refers to functions of the PHY layer that are performed at a relatively lower level than the DU (210), and may include, for example, iFFT transformation (or FFT transformation), CP insertion (CP removal), and digital beamforming. The RU (220) may be referred to as an 'access unit (AU)', an 'access point (AP)', a 'transmission / reception point (TRP)', a 'remote radio head (RRH)', a 'radio unit (RU)', or other terms having an equivalent technical meaning thereto. According to an embodiment, when the RU (220) complies with the O-RAN standard, it may be referred to as an O-RU (O-RAN RU). RU (220) may be replaced with a second network entity for a base station (e.g., gNB) in embodiments of the present disclosure as needed.

[0041] In FIG. 2A, the base station (110) is described as including a DU (210) and a RU (220), but the embodiments of the present disclosure are not limited thereto. The base station according to the embodiments may be implemented in a distributed deployment according to a centralized unit (CU) configured to perform functions of upper layers of an access network (e.g., packet data convergence protocol (PDCP), radio resource control (RRC)) and a distributed unit (DU) configured to perform functions of lower layers. For example, the digital unit (DU) (210) may be implemented by separating into a centralized unit (CU) and a distributed unit (DU). Between a core (e.g., 5G core (5GC) or next generation core (NGC)) network and a radio network (RAN), the base station may be implemented in a structure in which a centralized unit (CU), a distributed unit (DU), and a radio unit (RU) are arranged in that order. The interface between the CU (centralized unit) and the DU (distributed unit) can be referred to as the F1 interface.

[0042] A centralized unit (CU) may be connected to one or more distributed units (DUs) and may be responsible for functions at a higher layer than the distributed units (DUs). For example, the CU may be responsible for functions at the radio resource control (RRC) and packet data convergence protocol (PDCP) layers, while the DU and RU may be responsible for functions at lower layers. The DU may perform some functions (high PHY) of the radio link control (RLC), media access control (MAC), and physical (PHY) layers, while the RU may be responsible for the remaining functions (low PHY) of the PHY layer. In addition, for example, a digital unit (DU) may be included in a distributed unit (DU) depending on the implementation of a distributed deployment of the base station. Hereinafter, unless otherwise defined, the operations of DU (digital unit) and RU are described, but various embodiments of the present disclosure can be applied to both a base station arrangement including a CU and an arrangement in which a DU is directly connected to a core network (i.e., a base station in which the CU and DU are integrated into a single entity (e.g., an NG-RAN node)).

[0043] Fig. 2b illustrates an example of functional splitting of network entities. The network entities of Fig. 2b may include DU (210) and RU (220) of Fig. 2a.

[0044] As wireless communication technology develops (e.g., introduction of 5G (5th generation) communication system (or, NR (new radio) communication system), the frequency band used has increased further. As the cell radius of the base station has become very small, the number of RUs that need to be installed has also increased further. In addition, in 5G communication system, the amount of data transmitted has increased by a large amount, up to ten times, so the transmission capacity of the wired network transmitted to the fronthaul has increased significantly. Due to the factors described above, the installation cost of the wired network in the 5G communication system may increase significantly. Therefore, in order to lower the transmission capacity of the wired network and reduce the installation cost of the wired network, 'function split' can be used to lower the transmission capacity of the fronthaul by transferring some of the functions of the modem of the DU to the RU. Although described as RU below, the function split described below can be equally applied not only to the RU but also to the relationship between the MMU and the DU.

[0045] To reduce the burden on the DU, the role of the RU, which is traditionally solely responsible for RF functions, can be expanded to include some physical layer functions. As the RU performs higher-layer functions, its throughput increases, which can increase transmission bandwidth in the fronthaul while reducing latency requirements due to response processing. However, as the RU performs higher-layer functions, virtualization gains decrease, and the RU's size, weight, and cost increase. Considering the trade-offs between the advantages and disadvantages described above, implementing an optimal functional separation is required.

[0046] Referring to Figure 2b, the functional separation in the physical layer below the MAC layer is illustrated. For the downlink (DL) that transmits signals to a terminal through a wireless network, the base station can sequentially perform channel encoding / scrambling, modulation, layer mapping, antenna mapping, RE mapping, digital beamforming (e.g., precoding), iFFT transform / CP insertion, and RF transform. For the uplink (UL) that receives signals from a terminal through a wireless network, the base station can sequentially perform RF transform, FFT transform / CP removal, digital beamforming (pre-combining), RE demapping, channel estimation, layer demapping, demodulation, and decoding / descrambling. The separation of uplink and downlink functions can be defined in various types depending on the needs of vendors, discussions in standards, etc., according to the above-mentioned trade-offs.

[0047] In the first functional separation (255), the RU performs the RF function, and the DU performs the PHY function. The first functional separation is one in which the PHY function is not substantially implemented in the RU, and may be referred to as Option 8, for example. In the second functional separation (260), the RU performs iFFT conversion / CP insertion in the DL and FFT conversion / CP removal in the UL of the PHY function, and the DU performs the remaining PHY functions. As an example, the second functional separation (260) may be referred to as Option 7-1. In the third functional separation (270a), the RU performs iFFT conversion / CP insertion in the DL and FFT conversion / CP removal and digital beamforming in the UL of the PHY function, and the DU performs the remaining PHY functions. As an example, the third functional separation (270a) may be referred to as Option 7-2x Category A. In the fourth functional separation (270b), the RU performs up to digital beamforming in both the DL and UL, and the DU performs upper PHY functions after the digital beamforming. For example, the fourth functional separation (270b) may be referred to as Option 7-2x Category B. In the fifth functional separation (275), the RU performs up to RE mapping (or RE demapping) in both the DL and UL, and the DU performs upper PHY functions after RE mapping (or RE demapping). For example, the fifth functional separation (275) may be referred to as Option 7-2. In the sixth functional separation (280), the RU performs up to modulation (or demodulation) in both the DL and UL, and the DU performs upper PHY functions after modulation (or demodulation). For example, the sixth functional separation (280) may be referred to as Option 7-3. In the seventh functional separation (290), the RU performs encoding / scrambling (or decoding / descrambling) in both the DL and UL, and the DU performs subsequent upper PHY functions up to modulation (or demodulation). For example, the seventh functional separation (290) may be referred to as Option 6.

[0048] In one embodiment, when a large amount of signal processing is expected, such as in the FR 1 MMU, functional separation at a relatively high layer (e.g., the fourth functional separation (270b)) may be required to reduce fronthaul capacity. In addition, functional separation at too high a layer (e.g., the sixth functional separation (280)) may complicate the control interface and cause a burden on the implementation of the RU due to the inclusion of a large number of PHY processing blocks within the RU. Therefore, appropriate functional separation may be required depending on the arrangement and implementation method of the DU and the RU.

[0049] In one embodiment, if the precoding of data received from the DU cannot be processed (i.e., if the precoding capability of the RU is limited), the third functional separation (270a) or a lower functional separation (e.g., the second functional separation (260)) may be applied. Conversely, if the DU has the capability to process the precoding of data received from the DU, the fourth functional separation (270b) or a higher functional separation (e.g., the sixth functional separation (280)) may be applied.

[0050] The O-RAN standard distinguishes the types of O-RUs depending on whether the precoding function is located at the interface of the O-DU or the O-RU interface. For example, the RU may perform operations according to the functional separation of the third functional separation (270a) (which may be referred to as category A (CAT-A)) or the fourth functional separation (270b) (which may be referred to as category B (CAT-B)) for performing beamforming processing. In other words, an O-RU that does not perform precoding (i.e., has low complexity) may be referred to as a CAT-A O-RU. An O-RU that performs precoding may be referred to as a CAT-B O-RU. In addition, for example, channel estimation may be performed in the O-RU instead of the O-DU. To improve uplink performance, the O-RU may also operate according to the sixth functional separation (280) (Option 7-3).

[0051] Hereinafter, the term "upper-PHY" refers to the physical layer processing performed in the DU of the fronthaul interface. For example, the upper-PHY may include FEC encoding / decoding, scrambling, and modulation / demodulation. The term "lower-PHY" refers to the physical layer processing performed in the RU of the fronthaul interface. For example, the lower-PHY may include FFT / iFFT, digital beamforming, PRACH (physical random access channel) extraction and filtering. However, the above-described criteria do not exclude embodiments through other functional separations. The functional configuration, signaling, or operation of FIGS. 6a, 6b, 6c to 11 described below may be applied not only to the third functional separation (270a), the fourth functional separation (270b), but also to other functional separations (e.g., the sixth functional separation (280)). For example, channel estimation may be performed in the O-RU instead of the O-DU. To improve uplink performance, the O-RU may operate according to the sixth functional separation (280) (Option 7-3).

[0052] Figure 3 illustrates an example of a functional configuration of an electronic device.

[0053] The configuration of the electronic device (300) illustrated in FIG. 3 can be understood as a configuration of a base station (110), a terminal (120), a DU (210), or an RU (220) (or an MMU). Terms such as "...unit" and "...unit" used hereinafter mean a unit that processes at least one function or operation, and this can be implemented by hardware, software, or a combination of hardware and software.

[0054] Referring to FIG. 3, the electronic device (300) may include a transceiver (310), a memory (320), and a processor (330). However, the present disclosure is not limited thereto. For example, the electronic device (300) may not include at least some of the components illustrated in FIG. 3, or may further include components not illustrated in FIG. 3. For example, the electronic device (300) may not include the transceiver (310).

[0055] The transceiver (310) can perform functions for transmitting and receiving signals in a wired communication environment. The transceiver (310) can include a wired interface for controlling direct connections between devices via a transmission medium (e.g., copper wire, optical fiber). For example, the transceiver (310) can transmit electrical signals to other devices via copper wire, or perform conversion between electrical signals and optical signals.

[0056] The transceiver (310) may perform functions for transmitting and receiving signals in a wireless communication environment. For example, the transceiver (310) may perform a conversion function between baseband signals and bit streams according to the physical layer specifications of the system. For example, when transmitting data, the transceiver (310) encodes and modulates the transmitted bit stream to generate complex-valued symbols. Furthermore, when receiving data, the transceiver (310) demodulates and decodes the baseband signal to restore the received bit stream. Furthermore, the transceiver (310) may include multiple transmission and reception paths.

[0057] The transceiver (310) transmits and receives signals as described above. Accordingly, all or part of the transceiver (310) may be referred to as a "communication unit," a "transmitter," a "receiver," or a "transmitter-receiver unit." Furthermore, in the following description, transmission and reception performed via a wireless channel are used to mean that the transceiver (310) performs the processing described above.

[0058] Although not illustrated in FIG. 3, the transceiver (310) may further include a backhaul transceiver for connection to the core network or other base stations. The backhaul transceiver provides an interface for communicating with other nodes within the network. That is, the backhaul transceiver converts a bit stream transmitted from the base station to other nodes, such as other access nodes, other base stations, upper nodes, the core network, etc., into a physical signal, and converts a physical signal received from other nodes into a bit stream.

[0059] The memory (320) stores data such as basic programs, application programs, and setting information for the operation of the electronic device (300). The memory (320) may be referred to as a storage unit. The memory (320) may be composed of volatile memory, nonvolatile memory, or a combination of volatile memory and nonvolatile memory. In addition, the memory (320) provides stored data upon request from the processor (330).

[0060] For example, the processor (330) may include various processing circuits and / or multiple processors. For example, the term "processor" as used herein, including in the claims, may include various processing circuits including at least one processor, one or more of which may be configured to individually and / or collectively perform the various functions described below in a distributed manner. As used herein, when "processor," "at least one processor," and "one or more processors" are described as being configured to perform various functions, these terms encompass, for example, and without limitation, situations where one processor performs some of the recited functions and other processor(s) perform other parts of the recited functions, and also situations where one processor may perform all of the recited functions. Additionally, the at least one processor may include a combination of processors that perform the various functions enumerated / disclosed, for example, in a distributed manner. At least one processor may execute program instructions to achieve or perform the various functions.

[0061] The processor (330) controls the overall operations of the electronic device (300). The processor (380) may be referred to as a control unit. For example, the processor (330) transmits and receives signals via the transceiver (310) (or via a backhaul communication unit). In addition, the processor (330) records and reads data from the memory (320). In addition, the processor (330) may perform the functions of a protocol stack required by a communication standard. Although only the processor (330) is illustrated in FIG. 3, the electronic device (300) may include two or more processors according to other implementation examples.

[0062] The configuration of the electronic device (300) illustrated in FIG. 3 is only an example, and examples of the electronic device (300) performing the embodiments of the present disclosure are not limited to the configuration illustrated in FIG. 3. In some embodiments, some configurations may be added, deleted, or changed. For example, if the electronic device (300) is an RU, the electronic device (300) may further include a fronthaul transceiver. For example, the fronthaul transceiver may transmit and receive signals on a fronthaul interface. For example, the fronthaul transceiver may receive a management plane (M-plane) message. For example, the fronthaul transceiver may receive a management plane (S-plane) message. For example, the fronthaul transceiver may receive a control plane (C-plane) message. For example, the fronthaul transceiver may transmit a user plane (U-plane) message. For example, the fronthaul transceiver can receive user plane messages.

[0063] Figure 4 illustrates an example of a MIMO (multiple input multiple output) transmitter and receiver.

[0064] Referring to FIG. 4, a communication system (400) for supporting MIMO (e.g., a wired and wireless communication system, or a broadcasting system) may include a transmitter (410) and a receiver (420) as part of electronic devices or nodes that utilize a channel (430) (e.g., a wired or wireless channel, or a combined wired and wireless channel). In the present disclosure, the transmitter (410) and the receiver (420) may be referred to as a transmitter or a receiver, respectively.

[0065] Each of the transmitter (410) and the receiver (420) of FIG. 4 may be included in the electronic device (300). For example, if the transmitter (410) is included in the terminal (120) of FIG. 1, the receiver (420) may be included in the base station (110) of FIG. 1. For example, if the transmitter (410) is included in the terminal (120) of FIG. 1, the receiver (420) may be included in the DU (210) (or, RU (220), DU (210), and RU (220)) of FIG. 2A. However, the embodiments of the present disclosure are not limited thereto. For example, if the transmitter (410) is included in the base station (110) of FIG. 1, the receiver (420) may be included in the terminal (120) of FIG. 1.

[0066] According to one embodiment, the transmitter (410) and the receiver (420) may be included in different electronic devices depending on the link formed between the communication nodes. For example, the transmitter (410) may be a base station (110), and the receiver (420) may be a terminal (120). Furthermore, the receiver (420) may be a base station (110), and the transmitter (410) may be a terminal (120). For example, the transmitter (410) or the receiver (420) may be included in a base station (110) that includes a digital unit (DU) (e.g., DU (210) of FIG. 2A) and a radio unit (RU) (e.g., RU (220) of FIG. 2A). For example, at least some of the signal processing operations of the transmitter (410) or the receiver (420) may be performed in the DU of the base station (110).

[0067] Hereinafter, the entity transmitting the signal is described as a transmitter (410), and the entity receiving the signal is described as a receiver (420). However, these are merely functional expressions for explaining the signal processing process and are not to be construed as limiting a specific embodiment. For convenience of explanation, FIG. 4 exemplifies a communication system (400) in which the transmitter (410) and the receiver (420) are implemented as different electronic devices or nodes. However, the transmitter (410) and the receiver (420) may be included within a single electronic device.

[0068] According to one embodiment, the transmitter (410) can perform conversion between a baseband signal and a bit stream according to the physical layer specification of the system. For example, the transmitter (410) can generate a codeword by encoding information bits based on at least one channel encoder (411). The transmitter (410) can generate complex symbols based on the encoded codeword through a modulator (412). The transmitter (410) can process a reference signal known to the transmitter (410) together with the complex symbols through a resource mapping and multiplexer (413). For example, the transmitter (410) may perform time / space / frequency resource mapping on the complex symbols and the reference signal, and multiplex them using an orthogonal frequency division multiple access (OFDM) / discrete Fourier transform-spread-OFDM (DFT-s-OFDM) / code division multiple access (CDMA) method, etc. The transmitter (410) may transmit a signal processed through a transmission front end (414). For example, in a communication system (400) supporting MIMO, the transmission front end (414) of the transmitter (410) may include a plurality of transmission antennas. However, the present disclosure is not limited thereto. For example, in a communication system (400) supporting SIMO, the transmission front end (414) of the transmitter (410) may include one transmission antenna.For example, the transmitter (410) may up-convert a baseband signal to an RF (radio frequency) signal and then transmit the RF signal through an antenna. As the transmitted RF signal passes through the channel (430), it may be affected by damage or gain reduction due to background noise, interference, fading, etc.

[0069] According to one embodiment, the receiver (420) may receive an RF signal transmitted from the transmitter (410) and passing through a channel (430) through the reception front end (421). For example, in a communication system (400) supporting MIMO, the reception front end (421) of the receiver (420) may include a plurality of reception antennas. For example, the RF signal may be received through an antenna after passing through the channel (430). The RF signal may be down-converted into a baseband signal. The receiver (420) may process the baseband signal through a resource demapping and demultiplexer (422). For example, the receiver (420) may demultiplex and demap the baseband signal to distinguish it into a reference signal and a data signal. The baseband signal may be referred to as a reception signal received by the receiver (420). The reference signal and the data signal identified by demultiplexing and dephasing from the above-described reception signal may be referred to as a reception reference signal and a reception data signal, respectively. The receiving end (420) may estimate a channel (430) from the reference signal through a channel estimator (423). The receiving end (420) may perform equalization through a channel equalizer (424) based on information about the channel estimation and the data signal. The receiving end (420) may estimate or restore the transmitted bit string by demodulating and decoding through a demodulator (425) and a channel decoder (426).

[0070] In wireless communication systems, MIMO (or MIMO system) may refer to a communication technology in which a transmitter (e.g., a transmitter (410) of FIG. 4) and a receiver (e.g., a receiver (420) of FIG. 4) each utilize multiple antennas. The capacity of a MIMO system may increase in proportion to the number of antennas. In addition, massive MIMO can effectively eliminate interference between multiple users by performing beamforming using multiple antennas.

[0071] The above beamforming (or transmit / receive beamforming) can be utilized to perform effective data transmission. For efficient beamforming, a decomposition method (or matrix decomposition method, matrix decomposition algorithm) for information about the channel (or channel matrix, channel information matrix) between the transmitter and the receiver can be considered. For example, the decomposition method can include eigenvalue decomposition (EVD) or singular value decomposition (SVD) decomposition. However, although the exemplified decomposition methods provide relatively excellent transmission performance, they may require a high amount of computation. Therefore, the development of a matrix decomposition method that considers the trade-off is required.

[0072] Hereinafter, the Jacobi rotation (or Jacobi algorithm) exemplified in the present disclosure is a matrix decomposition method that satisfies both complexity and performance. For example, when the Jacobi algorithm is applied to the decomposition of a matrix to obtain eigenvalues ​​(or singular values), since the Jacobi algorithm has high generality, the Jacobi algorithm can be used even after preprocessing is applied to the matrix. For example, the preprocessing may include a bi-diagonal transformation as a method for processing the matrix. The matrix decomposition method including the Jacobi algorithm may include an operation of removing off-diagonal components (or entries) within the matrix to obtain a diagonal matrix for eigenvalue decomposition or singular value decomposition.

[0073] Hereinafter, the present disclosure proposes a matrix decomposition method based on the Jacobian algorithm used for matrix decomposition. Accordingly, the present disclosure can satisfy system requirements and improve system efficiency by selecting a matrix decomposition method based on the processing capacity for digital signals.

[0074] Hereinafter, in the present disclosure, the following mathematical symbols may be used.

[0075]

[0076]

[0077]

[0078] Figure 5 is a diagram illustrating an example of SVD (singular value decomposition) for channel information in MIMO.

[0079] FIG. 5 illustrates an example of SVD for channel information between a transmitter (510) and a receiver (520) in a MIMO system (500). For example, the MIMO system (500) of FIG. 5 may be an example of the communication system (400) of FIG. 4. For example, the transmitter (510) of FIG. 5 may be an example of the transmitter (410) of FIG. 4. For example, the receiver (520) of FIG. 5 may be an example of the receiver (420) of FIG. 4.

[0080]

[0081]

[0082]

[0083]

[0084]

[0085]

[0086]

[0087]

[0088]

[0089]

[0090]

[0091]

[0092]

[0093]

[0094]

[0095]

[0096]

[0097] The Jacobian algorithm can vary in performance and complexity depending on how it determines the off-diagonal elements of the matrix to which Jacobian rotation is applied (or the covariance elements of the covariance matrix). For example, the GO Jacobian algorithm can diagonalize matrices faster than other Jacobian algorithms because it changes the largest off-diagonal element to a reference value (e.g., 0) for each rotation. Therefore, the GO Jacobian algorithm can have the highest performance. However, the GO Jacobian algorithm may require additional computation because it must find the largest off-diagonal element for each rotation. For example, the Circular Jacobian algorithm and the Parallel Jacobian algorithm can omit the operation (or computation) of finding the order among the off-diagonal elements of the matrix to which Jacobian rotation is applied. However, the Circular Jacobian algorithm and the Parallel Jacobian algorithm can diagonalize matrices more slowly than the GO Jacobian algorithm. Hereinafter, the present disclosure proposes a Jacobian algorithm that can improve the trade-off between performance and complexity.

[0098]

[0099]

[0100]

[0101]

[0102]

[0103] Hereinafter, the device, method, and storage medium according to the present disclosure can determine off-diagonal components to be subjected to Jacobian rotation by selecting a group from among groups corresponding to covariance components of covariance information. For example, when the covariance information is a covariance matrix, the covariance components may represent off-diagonal components. For example, the groups may be referred to as component groups. In addition, the device, method, and storage medium according to the present disclosure can determine off-diagonal components to be subjected to Jacobian rotation based on a noise power parameter according to the order (or sequence) in which the Jacobian rotation is to be applied to the covariance components. Accordingly, the device, method, and storage medium according to the present disclosure can reduce the amount of computation (or computational complexity) and improve (or increase) performance (or diagonalization performance).

[0104] Figure 6a illustrates an example of an operational flow for a method for an electronic device to decompose covariance information of a channel based on component groups. Figure 6b illustrates examples of component groups corresponding to covariance components within the covariance information of a channel. Figure 6c illustrates examples of component groups for a covariance matrix of a channel.

[0105] At least some of the methods of FIG. 6A may be performed by the electronic device (300) of FIG. 3. For example, at least some of the methods may be controlled by the processor (330) of the electronic device (300). In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0106] In operation (600), according to one embodiment, the electronic device (300) may obtain a reference signal. For example, the electronic device (300) may obtain reception signals including the reference signal. For example, the electronic device (300) (or receiver) (e.g., a massive multiple input multiple output unit (MMU) of FIG. 2A) may directly receive the reception signals from an external electronic device (or transmitter) via reception antennas. Alternatively, for example, the electronic device (300) (e.g., a DU (210) of FIG. 2A) may receive the reception signals from another electronic device (e.g., a RU (220) of FIG. 2A) that has received the reception signals from the external electronic device via the reception antennas. The reception signals may include the reference signal and a data signal. For example, the reference signal may include an uplink reference signal (e.g., a sounding reference signal (SRS)) or a downlink reference signal (e.g., a channel state information-reference signal (CSI-RS)). However, the present disclosure is not limited thereto.

[0107] In operation (605), according to one embodiment, the electronic device (300) may perform channel estimation for the reference signal. For example, the electronic device (300) may generate channel information by performing the channel estimation for the reference signal. For example, the channel information may be channel estimation information or channel may be referred to as. For example, the channel information may be related to the transmitting antennas (or the number of transmitting antennas) used to transmit the reference signal and the receiving antennas (or the number of receiving antennas) used to receive the reference signal.

[0108]

[0109] In operation (615), according to one embodiment, the electronic device (300) may determine component groups representing correlations between the receiving antennas. For example, the component groups may correspond to covariance components (or off-diagonal components) of the covariance information of the channel. For example, each of the component groups may be mapped (or matched, defined, related) to covariance components of the covariance information. The covariance components of each of the component groups may represent correlations between the receiving antennas. The relationship between the component groups and the covariance components may be referenced in FIG. 6B.

[0110] Referring to FIG. 6B, examples (650) of component groups for covariance information when the number of receiving antennas is 4 and examples (660) of component groups for covariance information when the number of receiving antennas is 8 are illustrated. For example, in FIG. 6B, Gn (n = 1, 2, 3, 4, 5, 6, 7) may represent an index of a component group (or groups), and p and q may represent positions (e.g., p rows, q columns) (or positions of covariance components) within the covariance information. In the examples (650, 660) of FIG. 6B, covariance components corresponding to the component groups may represent upper triangular components since the covariance information is a symmetric matrix.

[0111] Referring to example (650), For the covariance information having (size), three component groups (651, 652, 653) may be defined. For example, each of the component groups (651, 652, 653) may correspond to (or match) two covariance components. The first component group (651) may correspond to a covariance component (651a) located at (1, 2) and a covariance component (651b) located at (3, 4). For example, the size of the covariance information may be associated with receive antennas. The four receive antennas of example (650) may include a first receive antenna, a second receive antenna, a third receive antenna, and a fourth receive antenna. For example, the first receive antenna may be associated with a first row and a first column of the covariance information. For example, the second receiving antenna may be associated with the second row and second column of the covariance information. For example, the third receiving antenna may be associated with the third row and third column of the covariance information. For example, the fourth receiving antenna may be associated with the fourth row and fourth column of the covariance information.

[0112] Each of the covariance components (651a, 651b) corresponding to the first component group (651) may be associated with a pair of two antennas. For example, the pair may be referred to as a pair of receive antennas. For example, the covariance component (651a) may be associated with a first receive antenna and a second receive antenna. The magnitude of the covariance component (651a) may represent a correlation value between the first receive antenna and the second receive antenna. For example, the covariance component (651b) may be associated with a third receive antenna and a fourth receive antenna. The magnitude of the covariance component (651b) may represent a correlation value between the third receive antenna and the fourth receive antenna. Referring to the above, the covariance components (651a, 651b) corresponding to the first component group (651) may be associated with different receive antennas. The covariance components (651a, 651b) corresponding to the first component group (651) may represent covariance components to which Jacobi rotation can be applied simultaneously (or in parallel). In other words, the first component group (651) may represent a set of covariance components to which Jacobi rotation can be applied simultaneously (or in parallel).

[0113] In the above example, the content of the first component group (651) is described, but the present disclosure is not limited thereto. For example, the content of the first component group (651) can be substantially equally applied to the second component group (652) and the third component group (653). For example, the second component group (652) can correspond to a covariance component located at (1, 3) and a covariance component located at (2, 4). In this case, the covariance component located at (1, 3) can represent a correlation between the first receiving antenna and the third receiving antenna. An example of covariance information related to the example (650) of FIG. 6b can be referenced in FIG. 6c.

[0114] Referring to Fig. 6c, An example of covariance information (670) having variance components (or diagonal components) (671) and off-diagonal components is illustrated. The covariance information (670) may include variance components (or diagonal components) (671) and off-diagonal components. For example, the off-diagonal components of the covariance information (670) may include upper triangular components (e.g., a 12 , a 13 , a 14 , a 23 , a 24 , a 34 ) and lower triangular components (e.g. a 21 , a 31 , a 41 , a 32 , a 42 , a 43 ) may be included. Since the covariance information (670) is a symmetric matrix, each of the upper triangular components may have the same value as each of the corresponding lower triangular components.

[0115] For example, the covariance information (670) may correspond to three component groups (681, 682, 683). For example, the first component group (681) may correspond to the covariance component (681a) (or off-diagonal component) of (1, 2) and the covariance component (681b) of (3, 4). For example, the second component group (682) may correspond to the covariance component (682a) (or off-diagonal component) of (1, 3) and the covariance component (682b) of (2, 4). For example, the third component group (683) may correspond to the covariance component (683a) (or off-diagonal component) of (1, 4) and the covariance component (683b) of (2, 3).

[0116] Referring again to example (660) of Fig. 6b, For the above covariance information, seven component groups (661, 662, 663, 664, 665, 666, 667) can be defined. For example, each of the component groups (661, 662, 663, 664, 665, 666, 667) can correspond to (or be matched with) four covariance components. The first component group (661) can correspond to a covariance component (661a) located at (1, 2), a covariance component (661b) located at (3, 4), a covariance component (661c) located at (5, 6), and a covariance component (661d) located at (7, 8).

[0117] Each of the covariance components (661a, 661b, 661c, 661d) corresponding to the first component group (661) may be associated with a pair of two antennas. For example, the pair may be referred to as a pair of receive antennas. For example, covariance component (661a) may be associated with a first receive antenna and a second receive antenna. The magnitude of covariance component (661a) may represent a correlation value between the first receive antenna and the second receive antenna. For example, covariance component (651b) may be associated with a third receive antenna and a fourth receive antenna. The magnitude of covariance component (661b) may represent a correlation value between the third receive antenna and the fourth receive antenna. For example, covariance component (661c) may be associated with a fifth receive antenna and a sixth receive antenna. The size of the covariance component (661c) may represent the correlation value between the fifth and sixth receiving antennas. For example, the covariance component (661d) may be related to the seventh and eighth receiving antennas. The size of the covariance component (661d) may represent the correlation value between the seventh and eighth receiving antennas.

[0118] Referring to the above, the covariance components (661a, 661b, 661c, 661d) corresponding to the first component group (661) may be associated with different receiving antennas. The covariance components (661a, 661b, 661c, 661d) corresponding to the first component group (661) may represent covariance components to which Jacobi rotations can be applied simultaneously (or in parallel). In other words, the first component group (661) may represent a set of covariance components to which Jacobi rotations can be applied simultaneously (or in parallel).

[0119] In Fig. 6b, it is assumed that the size (P) of each component group is N / 2, and the number (G) of component groups is L / P=N-1. The size (P) of each component group may represent the number of covariance components corresponding to each component group. However, the present disclosure is not limited thereto. For example, the maximum value of the size (P) may be N / 2. For example, when the size (P) changes from N / 2 to N / 4, the number (G) of component groups may increase.

[0120] Referring back to FIG. 6A, in operation (620), according to one embodiment, the electronic device (300) may determine a component group based on the magnitude of a covariance component among the component groups. For example, the electronic device (300) may determine a component group to which Jacobi rotation will be applied among the component groups based on the magnitude (or absolute value) of the covariance component. A method for determining the component group based on the magnitude of the covariance component may include a first method for determining the component group by using the sum of the magnitudes of each of the covariance components of the component group, and a second method for determining a component group corresponding to (or mapped to) a covariance component having the largest magnitude among the covariance components. Specific details regarding the methods are described below.

[0121] With respect to the first method, according to one embodiment, the electronic device (300) may determine, among the component groups, a component group in which the sum of the magnitudes of each of the covariance components corresponding to the component group has a maximum value. For example, the sum of the magnitudes of each of the covariance components corresponding to the component group may be referred to as the sum of the component group. The following mathematical equation may be referred to as a method for determining the component group to which the Jacobian rotation based on the sum of the component groups will be applied.

[0122]

[0123]

[0124] According to one embodiment, the electronic device (300) may sequentially or in parallel apply Jacobian rotation to covariance components corresponding to the determined component group. The electronic device (300) may set each of the covariance components corresponding to the component group as a reference value. For example, the electronic device (300) may sequentially set (or change, modify) each of the covariance components corresponding to the component group as a reference value. For example, the electronic device (300) may set (or change, modify) the covariance components corresponding to the component group as the reference value in parallel.

[0125]

[0126]

[0127] With respect to the second method, according to one embodiment, the electronic device (300) may determine a component group corresponding to (or mapped to) a covariance component having the largest magnitude among the covariance components of the covariance information. For example, a method for determining a component group to which a Jacobian rotation will be applied based on a covariance component having the largest value among the covariance components may refer to the following mathematical equation.

[0128]

[0129]

[0130] According to one embodiment, the electronic device (300) may sequentially or in parallel apply Jacobian rotation to covariance components corresponding to the determined component group. The electronic device (300) may set each of the covariance components corresponding to the component group to the reference value. For example, the electronic device (300) may sequentially set (or change, modify) each of the covariance components corresponding to the component group to the reference value. For example, the electronic device (300) may set (or change, modify) the covariance components corresponding to the component group to the reference value in parallel.

[0131]

[0132]

[0133] In operation (625), according to one embodiment, the electronic device (300) may generate modified covariance information by performing a transformation on covariance components of the covariance information corresponding to the determined component group. For example, the electronic device (300) may set each of the covariance components of the covariance information corresponding to the determined component group to the reference value. For example, the electronic device (300) may apply Jacobian rotation to the covariance components of the covariance information corresponding to the determined component group in parallel or sequentially. For example, the electronic device (300) may generate the modified covariance information changed from the covariance information by setting each of the covariance components of the covariance information corresponding to the determined component group to the reference value. For example, the above-mentioned modified covariance information may represent a covariance matrix in which covariance components corresponding to the determined component group among all covariance components included in the above-mentioned covariance information are changed to the reference value.

[0134] In operation (630), according to one embodiment, the electronic device (300) may determine whether a transformation has been performed on all component groups. For example, the electronic device (300) may determine whether a transformation (or Jacobi rotation) has been performed on all of the component groups defined for the covariance information. For example, if three component groups are defined for the covariance information, the electronic device (300) may determine whether the transformation has been performed on all of the three component groups.

[0135] In operation (630), the electronic device (300) may perform operation (640) if transformations have been performed for all component groups. Alternatively, in operation (630), the electronic device (300) may perform operation (635) if transformations have not been performed for at least one component group.

[0136] In operation (635), according to one embodiment, the electronic device (300) may determine a new component group based on the magnitude of the covariance component. For example, the electronic device (300) may determine the new component group from among at least one component group for which no transformation has been performed among the component groups. For example, determining the new component group may be performed based on Equation 5 or Equation 6, as in operation (620). Thereafter, in operation (625) that is performed again, the electronic device (300) may generate new modified covariance information by performing a transformation on the determined new component group. The new modified covariance information may be generated from the modified covariance information by setting covariance components of the modified covariance information corresponding to the new component group to the reference value.

[0137] In operation (640), according to one embodiment, the electronic device (300) may determine precoding information using the modified covariance information. For example, the electronic device (300) may calculate the precoding information using the modified covariance information generated in operation (625). In one example, the modified covariance information may be a diagonal matrix. For example, the precoding information may include a reception matrix applied when the reference signal is received through the reception antennas. For example, the electronic device (300) may use the reception matrix as a precoding matrix in order to transmit a signal using the reception antennas. However, the present disclosure is not limited thereto. For example, the electronic device (300) may also generate the precoding information (or precoding matrix) modified from the reception matrix based on channel information (or channel matrix) in order to transmit a signal.

[0138] In operation (645), according to one embodiment, the electronic device (300) may transmit a signal according to the precoding information. For example, the electronic device (300) may transmit the signal to the external electronic device that transmitted the reference signal according to the precoding information.

[0139] Figure 7a illustrates an example of an operational flow for a method in which an electronic device decomposes covariance information of a channel based on a sequence of covariance components. Figure 7b illustrates an example of covariance information of a channel decomposed according to a sequence of covariance components.

[0140] At least some of the methods of FIG. 7A may be performed by the electronic device (300) of FIG. 3 . For example, at least some of the methods may be controlled by the processor (330) of the electronic device (300). In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0141] In operation (700), according to one embodiment, the electronic device (300) can determine sequences representing an order between covariance components of covariance information.

[0142] For example, the covariance information may include covariance information of a channel for receiving antennas generated from channel information, such as in operation (610) of FIG. 6A. Alternatively, the covariance information may be modified covariance information obtained by transforming covariance components of the covariance information corresponding to the determined component group in operation (625) of FIG. 6A. In other words, the covariance information of operation (700) may include covariance information that has not been preprocessed (e.g., covariance information generated in operation (610) of FIG. 6A) or covariance information that has been preprocessed (e.g., modified covariance information generated in operation (625) of FIG. 6A). For example, the preprocessing may include a Jacobian algorithm or another type of matrix transformation (e.g., bi-diagonalization transformation).

[0143] In one embodiment, each of the sequences may indicate an order in which Jacobian rotations are to be applied between the covariance components of the covariance information. For example, if there are L covariance components, the number of sequences may be L!.

[0144] In operation (705), according to one embodiment, the electronic device (300) may perform a transformation of the covariance components according to each of the sequences. For example, the electronic device (300) may set the covariance components to the reference value according to the order indicated by each of the sequences. For specific details regarding operation (700) and operation (705), reference may be made to FIG. 7B.

[0145] Referring to FIG. 7b, examples (751, 752, 753, 754) of a method for performing transformation of the covariance components of the covariance information according to a specific sequence among the sequences are illustrated. In the examples (751, 752, 753, 754) of FIG. 7b, the covariance information It may be a covariance matrix having. For example, the covariance information may include three covariance components (761, 762, 763) (or off-diagonal components) that are not the reference value among the upper triangular components. For example, the covariance components (761, 762, 763) are a 13 , a 24 , and a 34 may include.

[0146] According to one embodiment, the number of sequences may be determined based on the number of covariance components (761, 762, 763). In the example of Fig. 7b, the number of sequences may be 6. For example, the sequences may be [a 13 , a 24 , a 34 ] The first sequence, [a], which indicates the order 13 , a 34, a 24 ] the second sequence indicating the order, [a 24 , a 13 , a 34 ] The third sequence, [a], which indicates the order 24 , a 34, a 13 ] The fourth sequence, [a], which indicates the order 34, a 13 , a 24 ] the fifth sequence indicating the order, and [a 34, a 24 , a 13 ] may include a sixth sequence indicating the order. For example, the sequences may indicate the order in which Jacobi rotations are applied. For example, when three Jacobi rotations are applied to the covariance information according to the second sequence, a 13 After the first Jacobian rotation is performed on a 34 A second Jacobian rotation is performed on a , and finally a 23 A third Jacobian rotation can be performed on it.

[0147] In example (752), according to the first Jacobian rotation on the covariance information, the covariance component (761)(a 13 ) can be set (or changed, modified) to the reference value (771). According to the first Jacobian rotation, the covariance component (763) (a 34 ) may change in magnitude, but may not change to a reference value. According to the first Jacobian rotation, the covariance component (762)(a 24 ) can be maintained in size. Covariance component (762)(a 24 ) is the covariance component (761)(a 13 ) may be associated with different receiving antennas (e.g., row 1, column 1, row 3, column 3).

[0148] In example (753), according to the second Jacobian rotation on the covariance information on which the first Jacobian rotation was performed, the covariance component (763) (a 34 ) can be set (or changed, modified) to the reference value (772). According to the second Jacobian rotation, the covariance component (762) (a 24 ) may change in size, but may not change to a reference value. After this, in example (754), according to the third Jacobian rotation on the covariance information on which the second Jacobian rotation was performed, the covariance component (762) (a 24 ) can be set (or changed, modified) to the reference value (773).

[0149] Referring to examples (751, 752, 753, 754), the covariance information may have covariance components of the covariance information set to a reference value (or changed, modified) according to a specific sequence (e.g., the second sequence). In the example, conversion according to one sequence is illustrated, but the present disclosure is not limited thereto. For example, conversion according to each of the first sequence, the third sequence, the fourth sequence, the fifth sequence, and the sixth sequence of the covariance information of FIG. 7b may be performed.

[0150] Referring back to FIG. 7A, in operation (710), the electronic device (300) may calculate parameters related to effective channel information and noise power. For example, the electronic device (300) may calculate parameters related to the effective channel information and noise power for each sequence. For example, the electronic device (300) may calculate a parameter according to a sequence. For example, the parameter may be referred to as a noise power parameter. For example, the parameter may include a sum-rate or a signal-to-noise ratio (SNR).

[0151] In operation (715), the electronic device (300) may determine a sequence among the sequences based on the size of the parameter. For example, the sequence having the maximum size of the parameter among the sequences may be determined. The method for determining the sequence based on the size of the parameter may include a method based on the sum-transmission rate and a method based on the SNR. The method based on the sum-transmission rate may refer to the following mathematical equation.

[0152]

[0153]

[0154] The method based on the above SNR can be referred to the following mathematical formula.

[0155]

[0156]

[0157] According to one embodiment, the electronic device (300) may determine, based on the mathematical expression 7 or 8, a sequence having a maximum magnitude of a value representing the sum-transfer rate among the sequences or a sequence having a maximum magnitude of a value representing the SNR among the sequences. For example, the electronic device (300) may determine a parameter having a maximum magnitude among the parameters for the sequences, and determine a sequence corresponding to the parameter having the maximum magnitude among the sequences.

[0158] In operation (720), according to one embodiment, the electronic device (300) may generate modified covariance information by performing a transformation on the covariance components of the covariance information according to the determined sequence. For example, the electronic device (300) may set each of the covariance components of the covariance information to the reference value according to the sequence determined in operation (715). The electronic device (300) may generate the modified covariance information changed from the covariance information by setting each of the covariance components of the covariance information to the reference value. In one example, the modified covariance information may be a diagonal matrix. However, the present disclosure is not limited thereto. For example, the modified covariance information may also be a non-diagonal matrix including some non-diagonal components.

[0159] In operation (725), according to one embodiment, the electronic device (300) may determine precoding information using the modified covariance information. For example, the electronic device (300) may calculate the precoding information using the modified covariance information generated in operation (720). In one example, the modified covariance information may be a diagonal matrix. For example, the precoding information may include a reception matrix applied when the reference signal is received through the reception antennas. For example, the electronic device (300) may use the reception matrix as a precoding matrix in order to transmit a signal using the reception antennas. However, the present disclosure is not limited thereto. For example, the electronic device (300) may also generate the precoding information (or precoding matrix) modified from the reception matrix based on channel information (or channel matrix) in order to transmit a signal.

[0160] In operation (730), according to one embodiment, the electronic device (300) may transmit a signal according to the precoding information. For example, the electronic device (300) may transmit the signal to the external electronic device that transmitted the reference signal according to the precoding information.

[0161] Referring to the above, in operation (700), it is described that the electronic device (300) determines the sequences regardless of the number of covariance components that are different from the reference value of the covariance information, but the present disclosure is not limited thereto. According to one embodiment, the electronic device (300) may determine the sequences in operation (710) if the number of covariance components having a value different from the reference value among all covariance components of the covariance information is less than the reference number. For example, the electronic device (300) may determine the sequences for covariance components that are not the reference value if the number of covariance components that are not the reference value is less than the reference number. This may be because the complexity of determining the sequences and performing an operation accordingly increases as the number of covariance components increases.

[0162] Figures 8a and 8b illustrate examples of graphs showing mean square error (MSE) according to the number of transmitting antennas.

[0163] Figures 8a and 8b illustrate graphs (800, 850) depicting MSE according to the number of transmit antennas for matrix decomposition methods. The horizontal axis of the graphs (800, 850) represents log2(M) for the number of transmit antennas (M), and the vertical axis represents MSE (unit: decibel (dB)). For example, the MSE can be calculated based on the following mathematical equation.

[0164]

[0165]

[0166] The graph (800) assumes that the number of receiving antennas (N) is 4, the number of covariance components (L) of a matrix to which the Jacobian algorithm is to be applied (e.g., covariance information of a channel or a covariance matrix of a channel) is 6, and the number of Jacobian rotations (T=2*L) is 12. The graph (800) may include a first line (811) representing the first method based on mathematical expression 5, a second line (812) representing the second method based on mathematical expression 6, a third line (820) representing the GO Jacobian algorithm, a fourth line (830) representing the cyclic Jacobian algorithm, and a fifth line (840) representing the parallel (or parallel) Jacobian algorithm.

[0167] Referring to the graph (800), the first line (811) and the second line (812) may have relatively low MSE values ​​compared to the fourth line (830) and the fifth line (840). For example, the first line (811) may have a value of about -40 dB depending on the number (M) of transmit antennas. For example, the second line (812) may have a value of about -42 dB depending on the number (M) of transmit antennas. Referring to the graph (800), the first method and the second method may have relatively high performance compared to the cyclic Jacobian algorithm and the parallel Jacobian algorithm. For example, the third line (820) may have a value of about -45 dB depending on the number (M) of transmit antennas. When comparing MSEs, the GO Jacobian algorithm may have the highest performance.

[0168] Graph (850) assumes that the number of receiving antennas (N) is 8, the number of covariance components (L) of the matrix to which the Jacobian algorithm is applied (e.g., covariance information of the channel or covariance matrix of the channel) is 27, and the number of Jacobian rotations (T=3*L) is 81. The graph (850) may include a first line (861a) representing the first method based on mathematical expression 5 when the size (P) of the component group is the first size, a second line (861b) representing the first method based on mathematical expression 5 when the size (P) of the component group is the second size, a third line (862a) representing the second method based on mathematical expression 6 when the size (P) of the component group is the first size, a fourth line (862b) representing the second method based on mathematical expression 6 when the size (P) of the component group is the second size, a fifth line (870) representing the GO Jacobian algorithm, a sixth line (880) representing the cyclic Jacobian algorithm, and a seventh line (890) representing the parallel Jacobian algorithm. For example, the first size may be greater than the second size. For example, the first size may be 4 and the second size may be 2. However, the present disclosure is not limited thereto.

[0169] Referring to the graph (850), the first line (861a), the second line (861b), the third line (862a), and the fourth line (862b) may have relatively low MSE values ​​compared to the sixth line (880) and the seventh line (890). For example, the first line (861a) may have a value of about -55 dB, depending on the number (M) of transmit antennas. For example, the second line (861b) may have a value of about -65 dB, depending on the number (M) of transmit antennas. For example, the third line (862a) may have a value of about -52 dB, depending on the number (M) of transmit antennas. For example, the fourth line (862b) may have a value of about -55 to about -65 dB, depending on the number (M) of transmit antennas. Referring to the first line (861a), the second line (861b), the third line (862a), and the fourth line (862b), the smaller the size (P) of the component group, the higher the performance. This may be because the smaller the size (P) of the component group, the more frequently Jacobian rotations are performed.

[0170] Referring to graph (850), the first and second methods can exhibit relatively high performance compared to the cyclic Jacobian algorithm and the parallel Jacobian algorithm. For example, the fifth line (870) can have a value of approximately -95 dB, depending on the number of transmit antennas (M). When comparing MSEs, the GO Jacobian algorithm can exhibit the highest performance.

[0171] The computational amount (or computational complexity) of the matrix decomposition methods, not the performance of the matrix decomposition methods exemplified in FIGS. 8a and 8b, can be exemplified as in the table below.

[0172]

[0173] The above table may represent a case where the computational amount of the GO Jacobi algorithm is assumed to be 100. For example, the computational amount according to the first method and the second method may be reduced by up to 2 / N compared to the computational amount of the GO Jacobi algorithm. Referring to the above, the first method and the second method according to the present disclosure may have a lower computational amount than the GO Jacobi algorithm and may have higher performance than the cyclic Jacobi algorithm and the parallel (or parallel) Jacobi algorithm. The first method and the second method according to the present disclosure may improve the performance of the Jacobi algorithm by using a relatively simple sorting operation within a limited number of iterations (or number of Jacobi rotations). In addition, the first method and the second method according to the present disclosure may flexibly satisfy the trade-off between performance and complexity required in various scenarios by adjusting the size of the component group. When comparing the first method and the second method, the first method has relatively high performance in terms of MSE performance, and the second method may be relatively easy in terms of implementation.

[0174] FIG. 9 illustrates an example of an operational flow for a method in which an electronic device decomposes covariance information of a component group-based channel and transmits data.

[0175] At least some of the methods of FIG. 9 may be performed by the electronic device (300) of FIG. 3. For example, at least some of the methods may be controlled by the processor (330) of the electronic device (300). In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0176] According to one embodiment, in operation (910), the electronic device (300) may generate channel covariance information for the receiving antennas based on channel estimation using a reference signal. For example, the electronic device (300) may generate the channel covariance information based on the channel estimation using the reference signal obtained from another electronic device.

[0177] According to one embodiment, the electronic device (300) can perform the channel estimation for the reference signal. For example, the electronic device (300) can generate channel information by performing the channel estimation for the reference signal. For example, the channel information may be channel estimation information or channel may be referred to as. For example, the channel information may be related to the transmitting antennas (or the number of transmitting antennas) used to transmit the reference signal and the receiving antennas (or the number of receiving antennas) used to receive the reference signal.

[0178]

[0179] According to one embodiment, in operation (920), the electronic device (300) may generate first modified covariance information by setting each of the covariance components of the covariance information, which corresponds to a first component group determined based on the magnitude of the covariance component among the component groups representing the correlation between the receiving antennas, to a reference value. Hereinafter, for convenience of explanation, among all covariance components of the covariance information, the covariance components corresponding to the first component group may be referred to as first covariance components.

[0180] According to one embodiment, the electronic device (300) may determine the component groups representing the correlation between the receiving antennas. For example, the component groups may correspond to covariance components (or off-diagonal components) of the covariance information of the channel. For example, each of the component groups may be mapped (or matched, defined, related) to covariance components of the covariance information. The covariance components of each of the component groups may represent the correlation between the receiving antennas. An example of the relationship between the component groups and the covariance components may be referred to FIG. 6B.

[0181] According to one embodiment, the electronic device (300) may determine the first component group based on the magnitude of a covariance component among the component groups. For example, the electronic device (300) may determine the first component group to which Jacobi rotation will be applied among the component groups based on the magnitude (or absolute value) of the covariance component. A method for determining the first component group based on the magnitude of the covariance component may include the first method of determining the component group by using the sum of the magnitudes of each of the covariance components of the component group, and the second method of determining a component group corresponding to (or mapped to) a covariance component having the largest magnitude among the covariance components. For specific details regarding the methods, reference may be made to FIG. 6B.

[0182] According to one embodiment, the electronic device (300) can generate the first modified covariance information by performing a transformation on the first covariance components of the covariance information corresponding to the determined first component group. For example, the electronic device (300) can set each of the first covariance components of the covariance information corresponding to the first component group to the reference value. For example, the electronic device (300) can apply Jacobian rotation on the first covariance components of the covariance information corresponding to the first component group in parallel or sequentially. For example, the electronic device (300) can generate the first modified covariance information changed from the covariance information by setting each of the first covariance components of the covariance information corresponding to the first component group to the reference value. For example, the first modified covariance information may represent a covariance matrix in which the first covariance components corresponding to the first component group among all covariance components included in the covariance information are changed to the reference value.

[0183] According to one embodiment, in operation (930), the electronic device (300) may generate second modified covariance information by setting each of the covariance components of the first modified covariance information, which corresponds to a second component group different from the first component group among the component groups, to the reference value. Hereinafter, for convenience of explanation, the covariance components corresponding to the second component group among all covariance components of the first modified covariance information may be referred to as second covariance components. For example, the electronic device (300) may determine the second component group based on the magnitude of the covariance component among the remaining component groups excluding the first component group among the component groups. For example, the second component group may be determined by applying the first method or the second method to the remaining component groups. For example, after determining the second component group, the electronic device (300) can set each of the second covariance components of the first modified covariance information corresponding to the second component group to the reference value.

[0184] Referring to the above, the electronic device (300) may perform a transformation on the second component group based on the first modified covariance information changed from the covariance information by performing a transformation on the first component group. The electronic device (300) may generate the second modified covariance information changed from the first modified covariance information by performing a transformation on the second component group.

[0185] According to one embodiment, in operation (940), the electronic device (300) may transmit a signal according to precoding information determined using the second modified covariance information. For example, the electronic device (300) may transmit a signal to the other electronic device according to the precoding information determined using the second modified covariance information. In one example, the second modified covariance information may be a diagonal matrix. However, the present disclosure is not limited thereto. For example, when a reference precision based on a sum-transmission rate is satisfied, the electronic device (300) may determine the precoding information using the second modified covariance information including some off-diagonal components, and transmit the signal according to the determined precoding information.

[0186] For example, the precoding information may include a reception matrix that is applied when the reference signal is received through the reception antennas. For example, the electronic device (300) may use the reception matrix as a precoding matrix to transmit a signal using the reception antennas. However, the present disclosure is not limited thereto. For example, the electronic device (300) may also generate the precoding information (or precoding matrix) modified from the reception matrix based on channel information (or channel matrix) to transmit a signal.

[0187] Referring to FIGS. 1 to 9, the device, method, and storage medium according to the present disclosure can determine off-diagonal components to be subjected to Jacobian rotation by selecting a group from among groups corresponding to covariance components of covariance information. For example, when the covariance information is a covariance matrix, the covariance components may represent off-diagonal components. For example, the groups may be referred to as component groups. In addition, the device, method, and storage medium according to the present disclosure can determine off-diagonal components to be subjected to Jacobian rotation based on a noise power parameter according to the order (or sequence) in which the Jacobian rotation is to be applied to the covariance components. Accordingly, the device, method, and storage medium according to the present disclosure can reduce the amount of computation (or computational complexity) and improve (or increase) performance (or diagonalization performance).

[0188] 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 can be clearly understood by a person having ordinary skill in the art to which the present disclosure belongs from the description below.

[0189] As described above, the electronic device may include at least one processor including a processing circuit. The electronic device may include a memory including one or more storage media storing instructions. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to generate covariance information of a channel for receiving antennas based on a channel estimation using a reference signal acquired from another electronic device. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to generate first modified covariance information by setting each of the covariance components of the covariance information corresponding to a first component group determined based on the magnitude of the covariance component among the component groups representing a correlation between the receiving antennas to a reference value. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to generate second modified covariance information by setting each of the covariance components of the first modified covariance information corresponding to a second component group different from the first component group among the component groups to the reference value. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to transmit a signal to the other electronic device according to precoding information determined using the second modified covariance information.

[0190] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to calculate a first sum of magnitudes of covariance components of the covariance information corresponding to each of the component groups. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to determine a first component group among the component groups in which the first sum has a maximum value.

[0191] In one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to compute a second sum of magnitudes of covariance components of the first modified covariance information corresponding to each of the component groups. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to determine a second component group among the component groups in which the second sum has a maximum value.

[0192] According to one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to calculate a first magnitude of each of the covariance components of the covariance information. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to determine a first component group corresponding to a covariance component having a maximum first magnitude among the covariance components of the covariance information.

[0193] According to one embodiment, the instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to calculate a second magnitude of each of the covariance components of the first modified covariance information. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to determine a second component group corresponding to a covariance component having a maximum second magnitude among the covariance components of the first modified covariance information.

[0194] According to one embodiment, the covariance components of the covariance information corresponding to the first component group may be associated with pairs of receive antennas. The receive antenna pairs may be included in the receive antennas.

[0195] According to one embodiment, the receiving antennas may include a first receiving antenna, a second receiving antenna, a third receiving antenna, and a fourth receiving antenna. The covariance components of the covariance information corresponding to the first component group may include a first covariance component and a second covariance component. The first covariance component may be associated with a pair of the first receiving antenna and the second receiving antenna. The second covariance component may be associated with a pair of the third receiving antenna and the fourth receiving antenna.

[0196] According to one embodiment, each of the covariance components of the covariance information corresponding to the first component group may be set to the reference value based on Jacobi rotation. The reference value may include 0.

[0197] According to one embodiment, the precoding information can be applied to the receiving antennas.

[0198] In one embodiment, the first modified covariance information may include a matrix including the covariance components corresponding to the second component group. The second modified covariance information may include a diagonal matrix.

[0199] According to one embodiment, the second modified covariance information may include covariance components corresponding to a third component group different from the first component group and the second component group among the component groups. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to determine sequences indicating an order among the covariance components of the second modified covariance information. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to calculate a parameter related to effective channel information and noise power of the channel by setting each of the covariance components of the second modified covariance information according to each of the sequences to the reference value. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to determine, among the sequences, a sequence in which the parameter has a maximum value. The instructions, when individually or collectively executed by the at least one processor, may cause the electronic device to generate third modified covariance information by setting each of the covariance components of the second modified covariance information to the reference value according to the sequence.

[0200] According to one embodiment, the effective channel information may be calculated based on other precoding information of the other electronic device and a channel estimation matrix of the channel, which is determined by setting each of the covariance components of the second modified covariance information to the reference value.

[0201] In one embodiment, the parameter may include a sum-rate or a signal to noise ratio (SNR).

[0202] The method performed by the electronic device as described above may include an operation of generating covariance information of a channel for receiving antennas based on a channel estimation using a reference signal acquired from another electronic device. The method may include an operation of generating first modified covariance information by setting each of the covariance components of the covariance information, which corresponds to a first component group determined based on a magnitude of the covariance component among component groups indicating a correlation between the receiving antennas, to a reference value. The method may include an operation of generating second modified covariance information by setting each of the covariance components of the first modified covariance information, which corresponds to a second component group different from the first component group, to the reference value. The method may include an operation of transmitting a signal to the other electronic device according to precoding information determined using the second modified covariance information.

[0203] In one embodiment, the method may include calculating a first sum of the magnitudes of covariance components of the covariance information corresponding to each of the component groups. The method may include determining a first component group among the component groups in which the first sum has a maximum value.

[0204] In one embodiment, the method may include calculating a second sum of magnitudes of covariance components of the first modified covariance information corresponding to each of the component groups. The method may include determining a second component group among the component groups in which the second sum has a maximum value.

[0205] In one embodiment, the method may include calculating a first magnitude of each of the covariance components of the covariance information. The method may include determining a first component group corresponding to a covariance component having a maximum first magnitude among the covariance components of the covariance information.

[0206] In one embodiment, the method may include calculating a second magnitude of each of the covariance components of the first modified covariance information. The method may include determining a second component group corresponding to a covariance component having a maximum second magnitude among the covariance components of the first modified covariance information.

[0207] According to one embodiment, the covariance components of the covariance information corresponding to the first component group may be associated with pairs of receive antennas. The receive antenna pairs may be included in the receive antennas.

[0208] The non-transitory computer-readable storage medium as described above may store one or more programs that, when individually or collectively executed by at least one processor of an electronic device, store instructions that cause the electronic device to generate covariance information of a channel for receiving antennas based on a channel estimation using a reference signal acquired from another electronic device. The non-transitory computer-readable storage medium may store one or more programs that, when individually or collectively executed by the at least one processor, cause the electronic device to generate first modified covariance information by setting each of the covariance components of the covariance information corresponding to a first component group determined based on a magnitude of the covariance component among the component groups representing a correlation between the receiving antennas to a reference value. The non-transitory computer-readable storage medium may store one or more programs that, when individually or collectively executed by the at least one processor, cause second modified covariance information to be generated by setting each of the covariance components of the first modified covariance information corresponding to a second component group different from the first component group among the component groups to the reference value. The non-transitory computer-readable storage medium may store one or more programs that, when individually or collectively executed by the at least one processor, cause a signal to be transmitted to the other electronic device according to precoding information determined using the second modified covariance information.

[0209] The methods according to the embodiments described in the claims or specification of the present disclosure may be implemented in the form of hardware, software, or a combination of hardware and software.

[0210] When implemented in software, a computer-readable storage medium storing one or more programs (software modules) may be provided. The one or more programs stored in the computer-readable storage medium are configured to be executed by one or more processors in an electronic device. The one or more programs include instructions that cause the electronic device to execute methods according to embodiments described in the claims or specification of the present disclosure. The one or more programs may be provided as a computer program product. The computer program product may be traded between a seller and a buyer as a commodity. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) via an application store (e.g., Play Store™) or directly between two user devices (e.g., smart phones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created in a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0211] These programs (software modules, software) may be stored in random access memory, non-volatile memory including flash memory, read only memory (ROM), electrically erasable programmable read only memory (EEPROM), magnetic disc storage devices, compact disc-ROM (CD-ROM), digital versatile discs (DVDs) or other forms of optical storage devices, magnetic cassettes, or may be stored in memories formed by a combination of some or all of these. In addition, each configuration memory may include multiple copies.

[0212] Additionally, the program may be stored on an attachable storage device that is accessible via a communication network, such as the Internet, an intranet, a local area network (LAN), a wide area network (WAN), a storage area network (SAN), or a combination thereof. Such a storage device may be connected to a device implementing an embodiment of the present disclosure via an external port. Additionally, a separate storage device on the communication network may be connected to a device implementing an embodiment of the present disclosure.

[0213] In the specific embodiments of the present disclosure described above, components included in the disclosure are expressed singularly or plurally, depending on the specific embodiment presented. However, the singular or plural expressions are selected to suit the presented situation for convenience of explanation, and the present disclosure is not limited to singular or plural components. Components expressed in plural may be composed of singular elements, or components expressed in singular may be composed of plural elements.

[0214] According to embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., modules or programs) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

[0215] Meanwhile, although the detailed description of the present disclosure has described specific embodiments, it is obvious that various modifications are possible within the scope of the present disclosure.

Claims

1. In electronic devices, At least one processor comprising a processing circuit; and A memory comprising one or more storage media for storing instructions, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: Generate channel covariance information for receiving antennas based on channel estimation using a reference signal obtained from another electronic device, By setting each of the covariance components of the covariance information corresponding to the first component group determined based on the size of the covariance component among the component groups representing the correlation between the above receiving antennas as a reference value, first modified covariance information is generated, By setting each of the covariance components of the first modified covariance information corresponding to a second component group different from the first component group among the above component groups to the reference value, second modified covariance information is generated, and Causing a signal to be transmitted to the other electronic device according to precoding information determined using the second modified covariance information. Electronic devices.

2. In claim 1, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: Compute a first sum of the magnitudes of the covariance components of the covariance information corresponding to each of the above component groups, and causing the first component group among the above component groups to be determined, wherein the first sum has a maximum value; Electronic devices.

3. In claim 2, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: Compute a second sum of the magnitudes of the covariance components of the first modified covariance information corresponding to each of the above component groups, and causing the second component group among the above component groups to be determined, wherein the second sum has a maximum value; Electronic devices.

4. In claim 1, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: Calculate the first size of each of the covariance components of the above covariance information, and Causing to determine the first component group corresponding to the covariance component having the maximum first size among the covariance components of the covariance information. Electronic devices.

5. In claim 4, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: Compute the second size of each of the covariance components of the above first modified covariance information, and Causing to determine the second component group corresponding to the covariance component having the maximum second magnitude among the covariance components of the first modified covariance information. Electronic devices.

6. In claim 1, The covariance components of the covariance information corresponding to the first component group are related to pairs of receiving antennas, The above receiving antenna pairs are included in the above receiving antennas, Electronic devices.

7. In claim 6, The above receiving antennas include a first receiving antenna, a second receiving antenna, a third receiving antenna, and a fourth receiving antenna, The covariance components of the covariance information corresponding to the first component group include a first covariance component and a second covariance component, The first covariance component is related to the receiving antenna pair of the first receiving antenna and the second receiving antenna, and The second covariance component is related to the receiving antenna pair of the third receiving antenna and the fourth receiving antenna. Electronic devices.

8. In claim 1, Each of the covariance components of the covariance information corresponding to the first component group is set to the reference value based on Jacobi rotation, and The above reference value includes 0, Electronic devices.

9. In claim 1, The above precoding information is applied to the receiving antennas, Electronic devices.

10. In claim 1, The above first modified covariance information includes a matrix including the covariance components corresponding to the second component group, and The above second modified covariance information includes a diagonal matrix, Electronic devices.

11. In claim 1, The second modified covariance information includes covariance components corresponding to a third component group that is different from the first component group and the second component group among the component groups, The above instructions, when individually or collectively executed by the at least one processor, cause the electronic device to: Determine sequences representing the order between the covariance components of the second modified covariance information, By setting each of the covariance components of the second modified covariance information according to each of the above sequences to the reference value, parameters related to the effective channel information and noise power of the channel are calculated, Among the above sequences, determine the sequence in which the parameter has the maximum value, and According to the above sequence, by setting each of the covariance components of the second modified covariance information to the reference value, thereby generating the third modified covariance information, Electronic devices.

12. In claim 11, The above valid channel information is calculated based on the other precoding information of the other electronic device and the channel estimation matrix of the channel, which is determined by setting each of the covariance components of the second modified covariance information to the reference value. Electronic devices.

13. In claim 11, The above parameters include sum-rate or signal to noise ratio (SNR). Electronic devices.

14. In a method performed by an electronic device, An operation of generating channel covariance information for receiving antennas based on channel estimation using a reference signal acquired from another electronic device; An operation of generating first modified covariance information by setting each of the covariance components of the covariance information corresponding to a first component group determined based on the size of the covariance component among the component groups representing the correlation between the receiving antennas to a reference value; An operation of generating second modified covariance information by setting each of the covariance components of the first modified covariance information corresponding to a second component group different from the first component group among the above component groups to the reference value; and Including an operation of transmitting a signal to the other electronic device according to precoding information determined using the second modified covariance information. method.

15. A non-transitory computer-readable storage medium, when individually or collectively executed by at least one processor of an electronic device, causes the electronic device to: Generate channel covariance information for receiving antennas based on channel estimation using a reference signal obtained from another electronic device, By setting each of the covariance components of the covariance information corresponding to the first component group determined based on the size of the covariance component among the component groups representing the correlation between the above receiving antennas as a reference value, first modified covariance information is generated, By setting each of the covariance components of the first modified covariance information corresponding to a second component group different from the first component group among the above component groups to the reference value, second modified covariance information is generated, and Storing one or more programs storing instructions that cause the other electronic device to transmit a signal according to precoding information determined using the second modified covariance information. A non-transitory computer-readable storage medium.

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