Control apparatus, control method, and program

Abstract

To suppress performance deterioration of beam foaming even in an environment where a channel fluctuation is large.SOLUTION: A control apparatus generates one or a plurality of channel depending beam forming weights corresponded to one or a plurality of weight generation methods on the basis of the one or the plurality of weight generation methods for generating a beam foaming weight by using an estimated channel matrix, generates one or a plurality of channel non-depending beam foaming weights corresponding to the one or the plurality of other weight generation methods on the basis of the one or the plurality of other weight generation methods that are not based on the channel matrix, calculates an index value in regard to an error between the existed channel matrix and an actual channel matrix, and selects one or all of the one or the plurality of channel depending beam forming weights and the one or the plurality of channel non-depending beam forming weights as a use object weight candidate on the basis of the index value.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present disclosure relates to a control device, a control method, and a program.

Background Art

[0002] As a method for realizing high-capacity communication, large-scale MIMO (Multi-Input Multi-Output), in which a base station having a large number of antennas performs wireless communication with a user (wireless terminal), is known. Large-scale MIMO is also called massive MIMO. Large-scale MIMO can be used, for example, in the uplink (uplink) and downlink (downlink) of a multiple access cellular system such as a fifth-generation mobile communication (5G) system. The base station of large-scale MIMO performs beamforming (BF: Beamforming) according to the user who is the communication partner. At this time, the beamforming weight can direct the directivity of the beam in a predetermined specific direction. Other beamforming weights can be generated based on the channel response between the user and the base station, which is estimated based on the reference signal transmitted from the base station to the user or from the user to the base station. Beamforming using this other beamforming weight generally provides higher performance than beamforming having beam directivity in the above specific direction. However, when the channel varies in the time-frequency direction, the performance of beamforming deteriorates due to the difference between the channel response at the time-frequency when the reference signal is transmitted and the channel response at the time-frequency when actually transmitting and receiving using beamforming.

[0003] As a technique for suppressing the degradation of beamforming performance due to channel fluctuations, a channel prediction technique is known (Non-Patent Document 1). This channel prediction technique predicts the channel response at a time in the future from the latest estimation time using the past channel estimation value and the latest channel estimation value for fluctuations in the time domain. For the channel estimation value at each time, the delay time and complex amplitude for each elementary wave are extracted, and the future complex amplitude of the elementary wave is predicted by extrapolating the change in the complex amplitude of the elementary wave having the same delay time between a plurality of times, and the predicted elementary waves are synthesized to predict the future channel response. The elementary wave corresponds to a multipath component. By determining the beamforming weight based on the predicted channel response, beamforming that follows the time-varying channel becomes possible. As a result, it becomes possible to suppress the degradation of beamforming performance.

Prior Art Documents

Non-Patent Documents

[0004]

Non-Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, in a communication environment with large channel fluctuations, the prediction accuracy by the channel prediction technique of Non-Patent Document 1 may decrease. For this reason, the error between the predicted channel state and the actual channel state becomes large, and the performance of beamforming may deteriorate.

[0006] An object of the present disclosure is to provide a control device, a control method, and a program that can suppress the deterioration of beamforming performance even in an environment with large channel fluctuations.

Means for Solving the Problems

[0007] In one aspect, the control device receives a channel matrix estimated based on a reference signal, and based on one or more weight generation methods for generating beamforming weights using the estimated channel matrix, generates one or more channel-dependent beamforming weights corresponding to the one or more weight generation methods respectively, and based on one or more other weight generation methods including at least one of DFT (Discrete Fourier Transform) beamforming and discrete angle beamforming and not based on the channel matrix, generates one or more channel-independent beamforming weights corresponding to the one or more other weight generation methods respectively, a weight generation unit; a calculation unit that calculates an index value regarding the error between the estimated channel matrix and the actual channel matrix; a weight determination unit that selects, based on the index value, some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as weight candidates that are candidates for use; comprises.

[0008] In another aspect, a control method executed by the control device is Receive a channel matrix estimated based on a reference signal, and generate one or more channel-dependent beamforming weights corresponding to each of the one or more weight generation methods based on one or more weight generation methods for generating beamforming weights using the estimated channel matrix. Generate one or more channel-independent beamforming weights corresponding to each of the one or more other weight generation methods based on one or more other weight generation methods that include at least one of DFT (Discrete Fourier Transform) beamforming and discrete angle beamforming and are not based on the channel matrix. Calculate an index value regarding the error between the estimated channel matrix and the actual channel matrix. Based on the index value, select some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as weight candidates to be used. Including.

[0009] In another aspect, the program Receive a channel matrix estimated based on a reference signal, and generate one or more channel-dependent beamforming weights corresponding to each of the one or more weight generation methods based on one or more weight generation methods for generating beamforming weights using the estimated channel matrix. Generate one or more channel-independent beamforming weights corresponding to each of the one or more other weight generation methods based on one or more other weight generation methods that include at least one of DFT (Discrete Fourier Transform) beamforming and discrete angle beamforming and are not based on the channel matrix. Calculate an index value regarding the error between the estimated channel matrix and the actual channel matrix. Based on the index value, select some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as weight candidates that are candidates for use. Cause the control device to execute a process including this.

Advantages of the Invention

[0010] According to the present disclosure, it is possible to provide a control device, a control method, and a program that can suppress performance degradation of beamforming even in an environment where channel fluctuations are large.

Brief Description of the Drawings

[0011]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Embodiments for Carrying Out the Invention

[0012] Hereinafter, embodiments will be described with reference to the drawings. In the present disclosure, the drawings may be associated with one or more embodiments. Also, each element of the drawings may apply to one or more embodiments. The following description and drawings may be omitted and simplified for clarity of explanation. Also, in the embodiments, the same or equivalent elements are denoted by the same reference numerals, and overlapping explanations are omitted as necessary. Also, each embodiment can be combined with other embodiments as appropriate. Also, in the present disclosure, unless otherwise specified, "at least one of A or B (A / B)" may mean either any one of A or B, or both A and B. Similarly, when "at least one of" is used for three or more elements, it may mean any one of these elements, or any plurality of elements (including all elements).

[0013] <First Embodiment> <Overview of Wireless Communication System> FIG. 1 is a diagram showing an example of the wireless communication system of the present disclosure. In FIG. 1, the wireless communication system includes a wireless communication device 1 and a wireless communication device 2. The wireless communication device 1 has a plurality of antennas. Also, the wireless communication device 2 also has a plurality of antennas. Note that the wireless communication device 1 may be, for example, a base station, and the wireless communication device 2 may be a wireless terminal.

[0014] The wireless communication device 1 transmits a reference signal (hereinafter sometimes referred to as the "first reference signal") to the wireless communication device 2. The wireless communication device 1 may receive the signal transmitted from the wireless communication device 2 using a beamforming weight. That is, the wireless communication device 1 may perform reception beamforming. Also, the wireless communication device 1 may transmit a signal to the wireless communication device 2 using a beamforming weight. That is, the wireless communication device 1 may perform transmission beamforming. The wireless communication device 1 may perform either reception beamforming or transmission beamforming, or both.

[0015] Further, the wireless communication device 2 may transmit a reference signal (hereinafter sometimes referred to as the "second reference signal") to the wireless communication device 1.

[0016] <Configuration example of the control device> FIG. 2 is a block diagram showing an example of the control device of the present disclosure. In FIG. 2, the control device 30 includes a weight generation unit (WEIGHT GENERATOR) 31, a calculation unit (CALCULATOR) 32, and a weight determination unit (WEIGHT DETERMINER) 33. Here, the control device 30 may be disposed inside the wireless communication device 1, or may be disposed outside the wireless communication device 1 and connected to the wireless communication device 1. Hereinafter, the description will be made on the premise that the control device 30 is disposed inside the wireless communication device 1, that is, the control device 30 is mounted on the wireless communication device 1.

[0017] The weight generation unit 31 receives a channel matrix (hereinafter sometimes referred to as the "estimated channel matrix") estimated based on the first reference signal or the second reference signal. This estimated channel matrix is a matrix defined for the channels between the plurality of antennas of the wireless communication device 1 and the plurality of antennas of the wireless communication device 2. Hereinafter, the description will be made on the premise that the estimated channel matrix is estimated based on the second reference signal.

[0018] In addition, the weight generation unit 31 generates "channel-dependent beamforming weights" and "channel-independent beamforming weights". For example, the weight generation unit 31 generates one or more channel-dependent beamforming weights corresponding to each of the one or more weight generation methods based on "one or more weight generation methods for generating beamforming weights using an estimated channel matrix". Further, the weight generation unit 31 generates one or more channel-independent beamforming weights corresponding to each of the one or more other weight generation methods based on "one or more other weight generation methods that form directivity in a specific direction and do not rely on the channel matrix". The "one or more other weight generation methods that form directivity in a specific direction and do not rely on the channel matrix" include at least one of DFT (Discrete Fourier Transform) beamforming and discrete angle beamforming.

[0019] The calculation unit 32 calculates an "index value" regarding the error between the estimated channel matrix and the actual channel matrix. For example, the calculation unit 32 calculates the "index value" based on at least one "evaluation value" regarding the error between the estimated channel matrix and the actual channel matrix. The at least one "evaluation value" includes at least one of a "value corresponding to the elapsed time" from the time when the second reference signal was received to the weight generation reference timing, the communication throughput between the wireless communication device 1 and the wireless communication device 2, and the reception quality of the data transmitted between the wireless communication device 1 and the wireless communication device 2. Here, the "weight generation reference timing" may be the timing (e.g., the current time) when the weight generation unit 31 generated the "channel-dependent beamforming weights" this time.

[0020] The weight determination unit 33 selects some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights generated by the weight generation unit 31 as "weight candidates" that are candidates for use based on the index value calculated by the calculation unit 32.

[0021] <Operation Example of Control Device> FIG. 3 is a flowchart showing an example of the processing operation of the control device of the present disclosure.

[0022] The weight generation unit 31 generates one or more channel-dependent beamforming weights and one or more channel-independent beamforming weights (step S1).

[0023] The calculation unit 32 calculates an "index value" regarding the error between the estimated channel matrix and the actual channel matrix (step S2).

[0024] The weight determination unit 33 selects some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as "weight candidates" that are candidates for use based on the index value (step S3).

[0025] According to the first embodiment as described above, in the control device 10, the weight generation unit 31 generates "channel-dependent beamforming weights" and "channel-independent beamforming weights". The calculation unit 32 calculates an "index value" regarding the error between the estimated channel matrix and the actual channel matrix. The weight determination unit 33 selects some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as "weight candidates" that are candidates for use based on the index value.

[0026] With the configuration of this control device 10, since a "weight candidate" can be selected based on an "index value" regarding the error between the estimated channel matrix and the actual channel matrix, it is possible to suppress the performance degradation of beamforming even in an environment with large channel fluctuations. For example, channel-dependent beamforming based on the channel matrix has high performance when the above error is small, while its performance degrades significantly when the above error is large. On the other hand, channel-independent beamforming that does not rely on the channel matrix has inferior performance compared to ideal channel-dependent beamforming, but the degradation due to the above error is small. Therefore, by selecting some or all of one or more channel-dependent beamforming weights and one or more channel-independent beamforming weights as "weight candidates" based on the index value, a beamforming weight with good performance can be selected as the weight candidate according to the error. As a result, the performance degradation of beamforming can be suppressed.

[0027] <Second Embodiment> <Overview of Wireless Communication System> FIG. 4 is a diagram showing another example of the wireless communication system of the present disclosure. In FIG. 4, the wireless communication system includes a base station 1 and one or more mobile wireless terminals 2. The base station 1 provides wireless access to one or more wireless terminals 2 (users). The base station 1 may be referred to by other names such as an access point, a transmission / reception point (TRP). The base station 1 may be, for example, a gNB of a 5G system, or a system consisting of an RU and a DU. In some implementations, the wireless communication system may utilize multi-user MIMO (Multi-Input Multi-Output) technology for the uplink from a plurality of wireless terminals 2 to the base station 1 or for the downlink from the base station to a plurality of wireless terminals. The base station 1 estimates a channel between one or more wireless terminals 2 and the base station 1 based on a reference signal (i.e., a second reference signal) transmitted from one or more wireless terminals 2, and may perform reception beamforming or transmission beamforming. Also, the base station 1 may receive a channel estimation result based on a reference signal (i.e., a first reference signal) transmitted to one or more wireless terminals 2 and perform reception beamforming or transmission beamforming.

[0028] In the following description, the uplink will be described as an example. However, the present embodiment is also applicable to the downlink. In the case of the downlink, the reception beamforming in the following description may be read as transmission beamforming, and the received signal may be read as the transmission signal. Further, in the following description, for the sake of simplicity, it is assumed that the transmission signal from each wireless terminal 2 is single-carrier transmission, and the channel between each wireless terminal 2 and the base station 1 is flat fading. On the other hand, even in a multipath fading environment where the transmission signal from each mobile wireless terminal 2 uses OFDM (Orthogonal Frequency Division Multiplexing) or SC-FDMA (Single Carrier-Frequency Division Multiple Access), by inserting a cyclic prefix of an appropriate length into the transmission signal, the fading of the channel for each subcarrier unit can be regarded as flat fading. Therefore, the present embodiment may be applied to OFDM and SC-FDMA.

[0029] Here, it is assumed that a transmission signal is transmitted from a total of M (M is an integer of 2 or more) transmission antennas of one or more wireless terminals 2 and received by the base station 1 having N (N is an integer of 2 or more) reception antennas. At this time, the complex signal model in the equivalent low-pass representation is expressed by the following equation (1).

Equation

[0030] <Configuration Example of Base Station> FIG. 5 is a block diagram showing an example of a base station of the present disclosure. In FIG. 5, the base station 1 includes an array antenna 51, a radio unit 52, and a control unit (control device) 60. Note that the base station 1 corresponds to the wireless communication device 1 of the first embodiment.

[0031] The array antenna 51 has antennas 51-1 to 51-N.

[0032] The radio unit 52 performs reception radio processing (e.g., down-conversion, analog-to-digital conversion, etc.) on the radio signal received via the array antenna 51, and outputs the obtained baseband signal to the control unit 60. Further, the radio unit 52 performs transmission radio processing (digital-to-analog conversion, up-conversion, etc.) on the baseband signal received from the control unit 60, and transmits the obtained radio signal via the array antenna 51. That is, the control unit 60 has a signal processing function.

[0033] The signal processing by the control unit 60 includes digital baseband communication processing (data plane processing) and control plane processing for wireless communication. The digital baseband signal processing may include signal processing of a Service Data Adaptation Protocol (SDAP) layer, a Packet Data Convergence Protocol (PDCP) layer, a Radio Link Control (RLC) layer, a Medium Access Control (MAC) layer, and a Physical (PHY) layer. Further, the control plane processing by the control unit 60 may include processing of Non-Access Stratum (NAS) messages, Radio Resource Control (RRC) messages, Medium Access Control (MAC) Control Elements (CEs), and Downlink Control Information (DCI).

[0034] As shown in FIG. 6, the control unit (control device) 60 includes a channel estimator 61, a weight generator 62, a calculator 63, a weight determiner 64, and a beam former 65. FIG. 6 is a block diagram showing another example of the control device of the present disclosure.

[0035] Based on the reference signal received from the radio unit 52, the channel estimator 61 estimates the channel matrix H. The channel estimator 61 outputs the estimated N×M channel matrix H to the weight generator 62 and the calculator 63. Here, the reference signal is, for example, a sounding reference signal (SRS).

[0036] Similar to the weight generator 31 of the first embodiment, the weight generator 62 generates one or more channel-dependent beamforming weights based on the estimated channel matrix H. Also, similar to the weight generator 31 of the first embodiment, the weight generator 62 generates one or more channel-independent beamforming weights that do not depend on the channel matrix H.

[0037] The weight generator 62 outputs the generated one or more channel-dependent beamforming weights and one or more channel-dependent beamforming weights to the weight determiner 64.

[0038] Here, the channel-dependent beamforming weights based on the channel matrix H are, for example, the beamforming weight W by the matched filter (MF) shown in Equation (2) MF the beamforming weight W by Zero Forcing (ZF) shown in Equation (3) ZF the beamforming weight W by Minimum Mean Square Error (MMSE) shown in Equation (4) MMSE and so on.

Number

Number

Number

[0039] Also, the channel-independent beamforming weights are, for example, the DFT beamforming W shown in Equation (5) DFT and the discrete angle beamforming W shown in Equation (6) angle and so on.

Number

Number

[0040] Similar to the calculation unit 32 in the first embodiment, the calculation unit 63 calculates an "index value" regarding the error between the actual channel matrix and the estimated channel matrix. For example, the calculation unit 63 calculates the "index value" based on at least one "evaluation value" regarding the error between the estimated channel matrix and the actual channel matrix. The at least one "evaluation value" includes at least one of a "value corresponding to the elapsed time" from the time when the second reference signal is received to the weight generation reference timing, the communication throughput between the wireless communication device 1 and the wireless communication device 2, and the reception quality of the data transmitted between the wireless communication device 1 and the wireless communication device 2. Here, the "weight generation reference timing" may be the timing (for example, the current time) when the weight generation unit 62 generated the "channel-dependent beamforming weight" this time. Then, the calculation unit 63 outputs the calculated index value to the weight determination unit 64.

[0041] Here, specific examples of the "evaluation value" and the "index value" will be described.

[0042] (Specific Example 1 of Index Value) The calculation unit 63 calculates the elapsed time from the time when the reference signal is received to the weight generation reference timing. For example, the calculation unit 63 may calculate the elapsed time by Equation (7) using the current time as the weight generation reference timing. [Number] Here, T is the current time, and T ref is the time when the previous reference signal was received.

[0043] Then, the calculation unit 63 uses the calculated elapsed time as the "index value". Here, as time elapses from the reception of the reference signal, the influence of the time variation of the channel matrix becomes larger, so the performance of the reception beamforming deteriorates. Therefore, the elapsed time calculated as the evaluation value itself can be used as the "index value".

[0044] (Specific example of index value 2) The calculation unit 63 calculates the elapsed time from the time when the reference signal is received to the weight generation reference timing, and calculates the product of the elapsed time and the time correlation of the estimated channel matrix as an "index value."

[0045] The time correlation ρ of the propagation path between the mth transmitting antenna and the nth receiving antenna n,m can be calculated, for example, using the following formula (8).

number

number

[0046] When the time correlation of the channel matrix is ​​large, the time variation is small, and the effect on the receiving beamforming is small. Therefore, even if the elapsed time from the time when the reference signal was received is the same, the channel error is evaluated to be smaller when the time correlation is large.

[0047] (Specific example of index value 3) The calculation unit 63 calculates the elapsed time from the time when the reference signal is received to the weight generation reference timing. Then, the calculation unit 63 calculates the product of the elapsed time and the number of rays included in the estimated channel matrix as an "index value."

[0048] The angular distribution P of the reception intensity at base station 1 of the signal transmitted from the m-th transmission antenna m (θ) can be obtained by Equation (10).

Equation

[0049] From the number of peaks of the angular distribution obtained by Equation (10), the number of sine waves can be obtained, and from the magnitude of the peaks, the intensity of multipaths can be obtained. That is, the sine waves correspond to the multipath components. As shown in Equation (11), the index value ε may be obtained by calculating the product of the number of sine waves exceeding a certain intensity and the elapsed time.

Equation

[0050] (Specific example 4 of the index value) The calculation unit 63 acquires, as an evaluation value, the correction amount of OLLA (Outer Loop Link Adaptation). OLLA is a method that corrects the SINR (Signal-to-Interference and Noise power Ratio) used for MCS selection and selection of spatial multiplexing terminals, and adjusts the correction amount based on the reception success or failure of data. The calculation unit 63 may calculate, as the index value ε, a value obtained by inverting the sign of the correction value of OLLA as shown in Equation (12).

Equation

[0051] (Specific example 5 of the index value) The calculation unit 63 calculates the elapsed time from the time when the reference signal is received to the weight generation reference timing. Then, the calculation unit 63 uses Equation (13) to calculate the product of the elapsed time and the moving speed of the wireless terminal 2 as the "index value". [Number] Here, v is the moving speed of the wireless terminal 2 estimated or measured. The faster the moving speed, the greater the time variation of the channel response, and the greater the channel error occurs. Therefore, the channel error is evaluated to be large.

[0052] The moving speed of the wireless terminal 2 can be estimated from the Doppler shift by converting the channel estimation value in the time-frequency domain to the channel estimation value in the delay-Doppler domain by symplectic finite Fourier transform. Also, the moving speed of the wireless terminal 2 measured by GPS (Global Positioning System) or GNSS (Global Navigation Satellite System) may be notified by the wireless terminal 2 to the base station 1.

[0053] (Specific example 6 of the index value) The calculation unit 63 calculates the communication throughput (actual measured value of the throughput) between the base station 1 and the wireless terminal 2 as the "evaluation value".

[0054] The throughput can be obtained by adding up the number of bits included in the data for which reception was successful for a plurality of data transmissions from time t1 to time t2, as shown in Expression (14). [Number] Here, S t is the success or failure of data reception at time t, which is 1 in the case of success and 0 in the case of failure. N bit t is the number of bits transmitted at time t.

[0055] The calculation unit 63 may calculate, as the index value ε, a value obtained by subtracting the actually measured value of the throughput from the reference value Th0, as shown in Expression (15). [Number]

[0056] When the beamforming performance deteriorates due to the time-variation of the channel response, the throughput deteriorates and the channel error is highly evaluated.

[0057] (Specific Example 7 of Index Value) The calculation unit 63 acquires the reception quality of the data transmitted between the base station 1 and the wireless terminal 2 as an "evaluation value". The reception quality can be obtained from the result at the time of data reception. For example, by using a demodulation reference signal (DMRS) received simultaneously with the data to estimate a channel matrix including beamforming, the SINR can be obtained. The calculation unit 63 may acquire this SINR as the "evaluation value".

[0058] The calculation unit 63 may calculate, as the index value ε, the reciprocal of the true value Γ of the SINR, as shown in Expression (16). [Number]

[0059] When the reception beamforming performance deteriorates due to the time variation of the channel response, the reception quality deteriorates and the channel error is highly evaluated.

[0060] (Specific Example 8 of Index Value) The calculation unit 63 may use any combination of the above specific examples 1 to 7 of the index value as the final index value. For example, the calculation unit 63 may calculate the arithmetic mean, sum, or product of any combination of the above specific examples 1 to 7 of the index value as the (final) index value.

[0061] Similar to the weight determination unit 33 in the first embodiment, the weight determination unit 64 selects, as a "weight candidate" which is a candidate for use, some or all of one or more channel-dependent beamforming weights and one or more channel-independent beamforming weights based on the index value received from the calculation unit 63. Then, the weight determination unit 64 determines the beamforming weight to be used based on the "weight candidate". Then, the weight determination unit 64 outputs the determined beamforming weight to be used to the beam forming unit 65.

[0062] Here, a specific example of weight determination will be described.

[0063] (Specific Example 1 of Weight Determination) Based on the index value, the weight determination unit 64 selects one beamforming weight from one or more channel-dependent beamforming weights and one or more channel-independent beamforming weights as a weight candidate, and determines this weight candidate as the beamforming weight to be used. For example, based on the correspondence between two or more numerical ranges divided by at least one threshold value and the beamforming weight types corresponding to each numerical range, and the index value, the weight determination unit 64 selects, as a weight candidate, the beamforming weight of the beamforming weight type corresponding to the numerical range including the index value in the correspondence.

[0064] For example, when there are three types of beamforming weights generated by the weight generation unit 62, the weight determination unit 64 can select a weight candidate using two thresholds (that is, the correspondence between three numerical ranges and the types of beamforming weights corresponding to each numerical range) as shown in Equation (17). [Number] Here, W select H is the selected weight candidate. ε is the index value. ε1 and ε2 are threshold values.

[0065] (Specific Example 2 of Weight Determination) The weight determination unit 64 selects, based on the index value, one beamforming weight from one or more channel-dependent beamforming weights and one or more channel-independent beamforming weights as a weight candidate, and determines this weight candidate as the beamforming weight to be used. For example, the weight determination unit 64 includes a "machine learning model". This machine learning model receives the index value and outputs a weight candidate.

[0066] In the case of supervised learning, the machine learning model may be, for example, a deep neural network (DNN) or a recurrent neural network (RNN). Also, in the case of reinforcement learning, the machine learning model may be a DQN (Deep Q-Network). In the case of supervised learning, the training data can be generated as a set of the input index value and the weight candidate to be selected by comparing the throughput of each beamforming weight through offline simulation. Also, in the case of reinforcement learning, the actual throughput, the success or failure of data reception, etc. can be used as the reward for learning. When a plurality of index values are supplied from the calculation unit 63, the input to the machine learning model becomes plural.

[0067] (Specific Example 3 of Weight Determination) The weight determination unit 64 selects, as weight candidates, a plurality of beamforming weights from among one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights based on the index value, and calculates the weighted sum of the plurality of beamforming weights selected as weight candidates as the beamforming weight to be used. For example, as shown in Expression (18), the weight determination unit 64 may calculate the weighted average of the plurality of beamforming weights selected as weight candidates as the beamforming weight to be used. [Number] Here, Expression (18) is the case where three beamforming weights are selected as weight candidates, and α1, α2, and α3 are weighting coefficients. The selection of the plurality of beamforming weights as weight candidates may be performed using a threshold value, as in Specific Example 1 of weight determination, or may be performed using a machine learning model, as in Specific Example 2 of weight determination.

[0068] The beamforming unit 65 performs reception beamforming on the reception signal vector y composed of the reception signals of the respective reception antennas 51 received from the radio unit 52. The reception beamforming is performed by taking the product of the beamforming weight W H received from the weight determination unit 64 and the reception signal vector y. [Number]

[0069] Note that for the reception signal vector y' after reception beamforming, the base station 1 performs multi-user detection, equivalent processing, decoding processing, and upper layer processing.

[0070] <Example of Hardware Configuration of Base Station> FIG. 7 is a diagram showing an example of the hardware configuration of a base station. The base station 1 may have the hardware configuration shown in FIG. 7.

[0071] In FIG. 7, the base station 100 includes an antenna array 11, a Radio Frequency (RF) transceiver 12, a processor 13, a memory 14, and a network interface 15.

[0072] The RF transceiver 12 performs analog RF signal processing to communicate with one or more wireless terminals 2. The RF transceiver 12 may include a plurality of transceivers. The RF transceiver 12 is coupled to the antenna array 11 and the processor 13. The RF transceiver 12 receives modulation symbols from the processor 13, generates a transmission RF signal, and supplies the transmission RF signal to the antenna array 11. Also, the RF transceiver 12 generates a baseband reception signal based on the received RF signal received by the antenna array 11 and supplies the reception signal to the processor 13. The radio unit 52 may be implemented by the RF transceiver 12.

[0073] The network interface 15 is used to communicate with network nodes (e.g., other base stations, Centralized Unit (CU), and core network nodes). The network interface 15 may include, for example, a network interface card (NIC) compliant with the IEEE 802.3 series.

[0074] Processor 13 may include a plurality of processors. For example, Processor 13 may include a modem processor (e.g., Central Processing Unit (CPU), Graphics Processing Unit (GPU), or Digital Signal Processor (DSP)) that performs digital baseband signal processing and a protocol stack processor (e.g., Central Processing Unit (CPU) or Micro Processing Unit (MPU)) that performs control plane processing.

[0075] Memory 14 is composed of a combination of volatile memory and non-volatile memory. The volatile memory is, for example, Static Random Access Memory (SRAM), Dynamic RAM (DRAM), or a combination thereof. The non-volatile memory is Mask Read Only Memory (MROM), Electrically Erasable Programmable ROM (EEPROM), flash memory, or a hard disk drive, or any combination thereof. Memory 14 may include storage located away from Processor 13. In this case, Processor 13 may access Memory 14 via Network Interface 15 or other I / O interfaces.

[0076] Memory 14 may include a computer-readable medium storing one or more software modules (computer programs) containing instruction groups and data for performing at least a part of the processing by base station 100. That is, the control unit 60 of base station 50 may be realized by Processor 13 reading and executing the program stored in Memory 14.

[0077] <Operation Example of Base Station> Next, an operation example of the base station will be described. Here, an example of the processing operation of the control unit (control device) 60 will be particularly described. FIG. 8 is a flowchart showing another example of the processing operation of the control device of the present disclosure.

[0078] The channel estimation unit 61 estimates a channel matrix based on the reference signal received from the radio unit 52 (step S11).

[0079] The weight generation unit 62 generates one or more channel-dependent beamforming weights based on the estimated channel matrix and one or more channel-independent beamforming weights not based on the channel matrix H (step S12).

[0080] The calculation unit 63 calculates an "index value" regarding the error between the actual channel matrix and the estimated channel matrix (step S13).

[0081] The weight determination unit 64 selects some or all of one or more channel-dependent beamforming weights and one or more channel-independent beamforming weights as "weight candidates" that are candidates for use based on the index value (step S14). Then, the weight determination unit 64 determines the beamforming weight to be used based on the "weight candidates" (step S14).

[0082] The beam forming unit 65 performs reception beamforming using the beamforming weight to be used (step S15).

[0083] According to the second embodiment as described above, in the control device 60, the weight generation unit 61 generates a "channel-dependent beamforming weight" and a "channel-independent beamforming weight". The calculation unit 63 calculates an "index value" regarding the error between the estimated channel matrix and the actual channel matrix. The weight determination unit 64 selects some or all of one or more channel-dependent beamforming weights and one or more channel-independent beamforming weights as "weight candidates" that are candidates for use, based on the index value.

[0084] With this configuration of the control device 60, since the "weight candidates" can be selected based on the "index value" regarding the error between the estimated channel matrix and the actual channel matrix, it is possible to suppress deterioration in the performance of beamforming even in an environment where the channel variation is large.

[0085] FIG. 9 is a diagram for explaining the effects. FIG. 9 shows the time change of the instantaneous throughput when the target beamforming weight is determined based on the elapsed time from the reception of the reference signal, from the beamforming weight by the matching filter and the beamforming weight by the discrete angle beamforming. Further, FIG. 9 shows the time change of the instantaneous throughput when only the conventional matching filter is used, and the time change of the instantaneous throughput when only the conventional discrete angle beamforming is used. Further, FIG. 9 shows the simulation results when a wireless terminal having 2 antennas performs uplink communication with a base station having 64 antennas. Time 0 is the time when the reference signal is received. Graph G1 is the time change of the instantaneous throughput when the target beamforming weight is determined based on the elapsed time from the reception of the reference signal, from the beamforming weight by the matching filter according to the present embodiment and the beamforming weight by the discrete angle beamforming. Graph G2 is the time change of the instantaneous throughput when only the matching filter is used. Graph G3 is the time change of the instantaneous throughput when only the discrete angle beamforming is used. It can be seen that when using the matching filter which is channel-dependent beamforming, the instantaneous throughput decreases over time. On the other hand, the discrete angle beamforming which is channel-independent beamforming hardly changes the instantaneous throughput over time. When using the determination of the beamforming according to the present embodiment, it can be seen that when the elapsed time from the reception of the reference signal is small, the instantaneous throughput is close to that of the matching filter, and when the elapsed time is large, the instantaneous throughput is close to that of the discrete angle beamforming. Thus, it can be seen that while obtaining a high instantaneous throughput by the matching filter, the degradation due to the channel time variation can be suppressed.

[0086] <Other embodiments> FIG. 10 is a diagram showing an example of the hardware configuration of the control device. In FIG. 10, the control device 200 has a processor 201 and a memory 202. The processor 201 may be, for example, a microprocessor, an MPU (Micro Processing Unit), or a CPU (Central Processing Unit). The processor 201 may include a plurality of processors. The memory 202 is composed of a combination of a volatile memory and a non-volatile memory. The memory 202 may include storage disposed away from the processor 201. In this case, the processor 201 may access the memory 202 via an I (input) / O (output) interface (not shown).

[0087] The control devices 30 and 60 of the first embodiment and the second embodiment can each have the hardware configuration shown in FIG. 10. The weight generation units 31 and 62, the calculation units 32 and 63, the weight determination units 33 and 64, the channel estimation unit 61, and the beam forming unit 65 of the control devices 30 and 60 of the first embodiment and the second embodiment may be realized by the processor 201 reading and executing a program stored in the memory 202. The program can be stored using various types of non-transitory computer readable media and supplied to the control devices 30 and 60. Examples of non-transitory computer readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks). Further, examples of non-transitory computer readable media include CD-ROM (Read Only Memory), CD-R, CD-R / W. Further, examples of non-transitory computer readable media include semiconductor memories. Semiconductor memories include, for example, mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, RAM (Random Access Memory). Also, the program may be supplied to the control devices 30 and 60 by various types of transitory computer readable media. Examples of transitory computer readable media include electrical signals, optical signals, and electromagnetic waves. The transitory computer readable media can supply the program to the control devices 30 and 60 via wired communication paths such as electric wires and optical fibers, or wireless communication paths.

[0088] As described above, the present disclosure has been described with reference to the embodiments, but the present disclosure is not limited to the above-described embodiments. Various changes that can be understood by those skilled in the art within the scope of the present disclosure can be made to the configuration and details of the present disclosure. And each embodiment can be combined with other embodiments as appropriate.

[0089] Some or all of the above embodiments may be described as follows in the appended claims, but are not limited thereto. (Appendix 1) Receiving a channel matrix estimated based on a reference signal, generating one or more channel-dependent beamforming weights corresponding to each of the one or more weight generation methods based on one or more weight generation methods for generating beamforming weights using the estimated channel matrix, and generating one or more channel-independent beamforming weights corresponding to each of the one or more other weight generation methods based on one or more other weight generation methods including at least one of DFT (Discrete Fourier Transform) beamforming and discrete angle beamforming and not based on the channel matrix, a weight generation unit; A calculation unit that calculates an index value regarding an error between the estimated channel matrix and an actual channel matrix; A weight determination unit that selects some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as weight candidates that are candidates for use based on the index value; A control device comprising: (Appendix 2) The calculation unit calculates the index value based on at least one evaluation value regarding the error; The at least one evaluation value includes at least one of a value corresponding to an elapsed time from the time when the reference signal is received to a weight generation reference timing, a communication throughput between a first wireless device that transmits the reference signal and a second wireless device that receives the reference signal, and a reception quality of data transmitted between the first wireless device and the second wireless device. The control device according to Appendix 1. (Appendix 3) The calculation unit uses the elapsed time as the index value. The control device according to Appendix 2. (Appendix 4) The calculation unit calculates the product of the elapsed time and the time correlation of the estimated channel matrix as the index value. The control device according to Supplementary Note 2. (Supplementary Note 5) The calculation unit calculates the product of the elapsed time and the number of sine waves included in the estimated channel matrix as the index value. The control device according to Supplementary Note 2. (Supplementary Note 6) The calculation unit uses the value obtained by inverting the sign of the correction value of Outer Loop Link Adaptation (OLLA) as the index value. The control device according to Supplementary Note 2. (Supplementary Note 7) The first wireless device is a base station. The second wireless device is a terminal. The weight candidate is a candidate for the beamforming weight used in the base station. The calculation unit calculates the product of the elapsed time and the moving speed of the terminal as the index value. The control device according to Supplementary Note 2. (Supplementary Note 8) Based on the index value, the weight determination unit selects one beamforming weight from the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as the weight candidate, and determines the weight candidate as the beamforming weight to be used. The control device according to any one of Supplementary Notes 2 to 7. (Supplementary Note 9) Based on the index value, the weight determination unit selects a plurality of beamforming weights from the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as the weight candidates, and calculates the weighted sum of the plurality of beamforming weights selected as the weight candidates as the beamforming weight to be used. The control device according to any one of Supplementary Notes 2 to 7. (Supplementary Note 10) The weight determination unit selects, as the weight candidate, a beamforming weight of a beamforming weight type corresponding to a numerical range including the index value in the correspondence relationship, based on the correspondence relationship between two or more numerical ranges divided by at least one threshold value and beamforming weight types corresponding to the respective numerical ranges, and the index value. The control device according to Supplementary Note 8. (Supplementary Note 11) The weight determination unit when the index value is smaller than the threshold value, selects one of the one or more channel-dependent beamforming weights as the weight candidate, when the index value is larger than the threshold value, selects one of the one or more channel-independent beamforming weights as the weight candidate. The control device according to Supplementary Note 10. (Supplementary Note 12) The weight determination unit selects, as the weight candidate, a beamforming weight of a beamforming weight type corresponding to a numerical range including the index value in the correspondence relationship, based on the correspondence relationship between two or more numerical ranges divided by at least one threshold value and beamforming weight types corresponding to the respective numerical ranges, and the index value. The control device according to Supplementary Note 9. (Supplementary Note 13) The weight determination unit includes a machine learning model, the machine learning model receives the index value and outputs the weight candidate. The control device according to Supplementary Note 8. (Supplementary Note 14) The weight determination unit includes a machine learning model, the machine learning model receives the index value and outputs the weight candidate. The control device according to Supplementary Note 9. (Supplementary Note 15) A control method executed by a control device, Receive a channel matrix estimated based on a reference signal, and generate one or more channel-dependent beamforming weights corresponding to each of the one or more weight generation methods based on one or more weight generation methods for generating beamforming weights using the estimated channel matrix, and generate one or more channel-independent beamforming weights corresponding to each of the one or more other weight generation methods based on one or more other weight generation methods that include at least one of DFT (Discrete Fourier Transform) beamforming and discrete angle beamforming and are not based on the channel matrix, Calculate an index value regarding the error between the estimated channel matrix and the actual channel matrix, Based on the index value, select some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as weight candidates to be used, A control method including. (Appendix 16) Calculating the index value includes calculating the index value based on at least one evaluation value regarding the error, The at least one evaluation value includes at least one of a value corresponding to the elapsed time from the time when the reference signal is received to the weight generation reference timing, the communication throughput between a first wireless device that transmits the reference signal and a second wireless device that receives the reference signal, and the reception quality of data transmitted between the first wireless device and the second wireless device. The control method described in Appendix 15. (Appendix 17) The elapsed time is used as the index value. The control method described in Appendix 16. (Appendix 18) Calculating the index value includes calculating the product of the elapsed time and the time correlation of the estimated channel matrix as the index value. The control method described in Appendix 16. (Appendix 19) Calculating the index value includes calculating a product of the elapsed time and the number of sine waves included in the estimated channel matrix as the index value. The control method according to Appendix 16. (Appendix 20) A value obtained by inverting the sign of the correction value of Outer Loop Link Adaptation (OLLA) is used as the index value. The control method according to Appendix 16. (Appendix 21) The first radio device is a base station. The second radio device is a terminal. The weight candidate is a candidate for a beamforming weight used in the base station. Calculating the index value includes calculating a product of the elapsed time and the moving speed of the terminal as the index value. The control method according to Appendix 16. (Appendix 22) Selecting the weight candidate includes selecting, based on the index value, one beamforming weight from among the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as the weight candidate. The control method further includes determining the weight candidate as a beamforming weight to be used. The control method according to any one of Appendices 16 to 21. (Appendix 23) Selecting the weight candidate includes selecting, based on the index value, a plurality of beamforming weights from among the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as the weight candidate. The control method further includes calculating a weighted sum of the plurality of beamforming weights selected as the weight candidate as a beamforming weight to be used. The control method according to any one of Appendices 16 to 21. (Appendix 24) Selecting the weight candidate includes selecting, as the weight candidate, a beamforming weight of a beamforming weight type corresponding to a numerical range including the index value in the correspondence relationship, based on the correspondence relationship between two or more numerical ranges divided by at least one threshold value and beamforming weight types corresponding to each numerical range, and the index value. The control method according to Appendix 22. (Appendix 25) Selecting the weight candidate when the index value is smaller than the threshold value, includes selecting one of the one or more channel-dependent beamforming weights as the weight candidate; when the index value is larger than the threshold value, includes selecting one of the one or more channel-independent beamforming weights as the weight candidate; and includes The control method according to Appendix 24. (Appendix 26) Selecting the weight candidate includes selecting, as the weight candidate, a beamforming weight of a beamforming weight type corresponding to a numerical range including the index value in the correspondence relationship, based on the correspondence relationship between two or more numerical ranges divided by at least one threshold value and beamforming weight types corresponding to each numerical range, and the index value. The control method according to Appendix 23. (Appendix 27) In selecting the weight candidate, a machine learning model that receives the index value and outputs the weight candidate is used. The control method according to Appendix 24. (Appendix 28) In selecting the weight candidate, a machine learning model that receives the index value and outputs the weight candidate is used. The control method according to Appendix 25. (Appendix 29) Receive a channel matrix estimated based on a reference signal, and generate one or more channel-dependent beamforming weights corresponding to each of the one or more weight generation methods based on one or more weight generation methods that generate beamforming weights using the estimated channel matrix. Generate one or more channel-independent beamforming weights corresponding to each of the one or more other weight generation methods based on one or more other weight generation methods that include at least one of DFT (Discrete Fourier Transform) beamforming and discrete angle beamforming and do not depend on the channel matrix, and Calculate an index value regarding the error between the estimated channel matrix and the actual channel matrix, and Based on the index value, select some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as weight candidates to be used, and A program for causing a control device to execute a process including the above. (Appendix 30) Calculating the index value includes calculating the index value based on at least one evaluation value regarding the error, and The at least one evaluation value includes at least one of a value corresponding to the elapsed time from the time when the reference signal is received to the weight generation reference timing, the communication throughput between the first wireless device that transmits the reference signal and the second wireless device that receives the reference signal, and the reception quality of the data transmitted between the first wireless device and the second wireless device. The program according to Appendix 29. (Appendix 31) The elapsed time is used as the index value. The program according to Appendix 30. (Appendix 32) Calculating the index value includes calculating the product of the elapsed time and the time correlation of the estimated channel matrix as the index value. The program described in Supplementary Note 30. (Supplementary Note 33) Calculating the index value includes calculating the product of the elapsed time and the number of sine waves included in the estimated channel matrix as the index value. The program described in Supplementary Note 30. (Supplementary Note 34) A value obtained by inverting the sign of the correction value of Outer Loop Link Adaptation (OLLA) is used as the index value. The program described in Supplementary Note 30. (Supplementary Note 35) The first wireless device is a base station. The second wireless device is a terminal. The weight candidate is a candidate for the beamforming weight used in the base station. Calculating the index value includes calculating the product of the elapsed time and the moving speed of the terminal as the index value. The program described in Supplementary Note 30. (Supplementary Note 36) Selecting the weight candidate includes selecting, based on the index value, one beamforming weight from among the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as the weight candidate. The process further includes determining the weight candidate as the beamforming weight to be used. The program according to any one of Supplementary Notes 30 to 35. (Supplementary Note 37) Selecting the weight candidate includes selecting, based on the index value, a plurality of beamforming weights from among the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as the weight candidates. The process further includes calculating, as the beamforming weight to be used, a weighted sum of the plurality of beamforming weights selected as the weight candidates. The program according to any one of Supplementary Notes 30 to 35. (Supplementary Note 38) Selecting the weight candidate includes selecting, as the weight candidate, a beamforming weight of a beamforming weight type corresponding to a numerical range including the index value based on a correspondence relationship between two or more numerical ranges divided by at least one threshold value and beamforming weight types corresponding to the respective numerical ranges and the index value. The program according to Supplementary Note 36. (Supplementary Note 39) Selecting the weight candidate includes, when the index value is smaller than the threshold value, selecting one of the one or more channel-dependent beamforming weights as the weight candidate; and, when the index value is larger than the threshold value, selecting one of the one or more channel-independent beamforming weights as the weight candidate. The program according to Supplementary Note 38. (Supplementary Note 40) Selecting the weight candidate includes selecting, as the weight candidate, a beamforming weight of a beamforming weight type corresponding to a numerical range including the index value based on a correspondence relationship between two or more numerical ranges divided by at least one threshold value and beamforming weight types corresponding to the respective numerical ranges and the index value. The program according to Supplementary Note 37. (Supplementary Note 41) In selecting the weight candidate, a machine learning model that receives the index value and outputs the weight candidate is used. The program according to Supplementary Note 38. (Supplementary Note 42) In selecting the weight candidate, a machine learning model that receives the index value and outputs the weight candidate is used. The program according to Supplementary Note 39.

Explanation of Signs

[0090] 1 Wireless communication device (base station) 2 Wireless communication device (mobile wireless terminal) 10 Control device 11 Antenna array 12 Transceiver 13 Processor 14 Memory 15 Network interface 30 Control device 31 Weight generation unit 32 Calculation unit 33 Weight determination unit 50 Base station 51 Array antenna 52 Radio section 60 Control unit (control device) 61 Channel estimation unit 62 Weight generation unit 63 Calculation unit 64 Weight determination unit 65 Beamforming unit

Claims

1. Receiving a channel matrix estimated based on a reference signal, and generating one or more channel-dependent beamforming weights respectively corresponding to the one or more weight generation methods based on one or more weight generation methods for generating beamforming weights using the estimated channel matrix, and generating one or more channel-independent beamforming weights respectively corresponding to the one or more other weight generation methods based on one or more other weight generation methods including at least one of DFT (Discrete Fourier Transform) beamforming and discrete angle beamforming and not based on the channel matrix, a weight generation unit; A calculation unit that calculates an index value regarding an error between the estimated channel matrix and an actual channel matrix; A weight determination unit that selects, based on the index value, some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as weight candidates that are candidates for use; A control device comprising:

2. The calculation unit calculates the index value based on at least one evaluation value regarding the error, The at least one evaluation value includes at least one of a value corresponding to an elapsed time from the time when the reference signal is received to a weight generation reference timing, a communication throughput between a first wireless device that transmits the reference signal and a second wireless device that receives the reference signal, and a reception quality of data transmitted between the first wireless device and the second wireless device. The control device according to claim 1.

3. The calculation unit calculates the product of the elapsed time and a time correlation of the estimated channel matrix as the index value. The control device according to claim 2.

4. The calculation unit calculates the product of the elapsed time and the number of sine waves included in the estimated channel matrix as the index value. The control device according to claim 2.

5. Based on the index value, the weight determination unit selects one of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as the weight candidate, and determines the weight candidate as the beamforming weight to be used. The control device according to any one of claims 2 to 4.

6. Based on the correspondence relationship between two or more numerical ranges divided by at least one threshold value and the beamforming weight types corresponding to each numerical range, and the index value, the weight determination unit selects, as the weight candidate, the beamforming weight of the beamforming weight type corresponding to the numerical range including the index value in the correspondence relationship. The control device according to claim 5.

7. The weight determination unit When the index value is smaller than the threshold value, selects one of the one or more channel-dependent beamforming weights as the weight candidate. When the index value is larger than the threshold value, selects one of the one or more channel-independent beamforming weights as the weight candidate. The control device according to claim 6.

8. The weight determination unit includes a machine learning model. The machine learning model receives the index value and outputs the weight candidate. The control device according to claim 5.

9. A control method executed by a control device, Receive a channel matrix estimated based on a reference signal, and based on one or more weight generation methods for generating beamforming weights using the estimated channel matrix, generate one or more channel-dependent beamforming weights respectively corresponding to the one or more weight generation methods, and based on one or more other weight generation methods that include at least one of DFT (Discrete Fourier Transform) beamforming and discrete angle beamforming and are not based on the channel matrix, generate one or more channel-independent beamforming weights respectively corresponding to the one or more other weight generation methods, Calculate an index value regarding the error between the estimated channel matrix and the actual channel matrix, Based on the index value, select some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as weight candidates to be used, A control method including.

10. Receive a channel matrix estimated based on a reference signal, and based on one or more weight generation methods for generating beamforming weights using the estimated channel matrix, generate one or more channel-dependent beamforming weights respectively corresponding to the one or more weight generation methods, and based on one or more other weight generation methods that include at least one of DFT (Discrete Fourier Transform) beamforming and discrete angle beamforming and are not based on the channel matrix, generate one or more channel-independent beamforming weights respectively corresponding to the one or more other weight generation methods, Calculate an index value regarding the error between the estimated channel matrix and the actual channel matrix, Based on the index value, selecting some or all of the one or more channel-dependent beamforming weights and the one or more channel-independent beamforming weights as weight candidates that are candidates for use. A program that causes a control device to execute a process including this.

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