Control device and method thereof

Abstract

To allow wireless parameters selected or determined based on measurement results of radio quality to contribute to improving the possibility of achieving target communication quality.SOLUTION: A control device (1) predicts probability distribution of radio quality when downlink transmission from a base station (2) to a wireless terminal (3) or uplink transmission from the wireless terminal (3) to the base station (2) is performed. The control device (1) uses the obtained probability distribution to calculate an expected value of a block error rate or reliability of downlink or uplink transmission. The control device (1) determines values of each of one or more parameters related to downlink or uplink transmission, taking into account the obtained expected value.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] The present disclosure relates to a wireless communication system, and particularly to the determination of parameters related to wireless communication.

Background Art

[0002] Patent Document 1 describes the selection of an MCS index by a transmission device. The transmission device determines a first candidate value MCS_A and a second candidate value MCS_B of a Modulation and Coding Scheme (MCS). MCS_A is determined based on the channel quality between the transmission device and the reception device, and is an MCS index that satisfies a target block error rate (Block Error Rate (BLER)) in the channel between the transmission device and the reception device. The channel quality is, for example, a signal to interference plus noise ratio (SINR), a signal to noise ratio (SNR), or a signal to interference ratio (SIR). On the other hand, MCS_B is determined such that the number of packet divisions when dividing transmission data into a plurality of transport blocks is not more than the allowable number of packet divisions based on a delay requirement (for example, an allowable time for delay). Then, the transmission device sets a range with MCS_A as the upper limit and MCS_B as the lower limit as the selection range of the MCS index, and selects any one MCS index from the set selection range. Thereby, the occurrence of delay caused by the division of transmission data packets can be suppressed, and low latency can be guaranteed. Note that the transmission device is a base station (e.g., eNB or gNB) in the case of downlink, and a wireless terminal (e.g., User Equipment (UE)) in the case of uplink. The reception device is a wireless terminal in the case of downlink, and a base station in the case of uplink.

[0003] Patent Document 2 describes the selective use of first and second MCS tables by a base station (e.g., gNB) and a wireless terminal (e.g., UE). Each MCS table associates multiple MCS indices with different combinations of modulation order and code rate. The minimum code rate specified in the second MCS table (e.g., 30) is less than the minimum code rate specified in the first MCS table (e.g., 120). The base station uses Radio Resource Control (RRC) signaling or Downlink Control Information (DCI) to instruct the wireless terminal which MCS table to use for either or both downlink reception and uplink transmission. In one example, the second MCS table may be used in cases where low latency and high reliability are required. [Prior art documents] [Patent Documents]

[0004] [Patent Document 1] International Publication No. 2019 / 049212 [Patent Document 2] International Publication No. 2020 / 031357 [Overview of the project] [Problems that the invention aims to solve]

[0005] In downlink transmissions in wireless systems such as Long Term Evolution (LTE) systems and fifth-generation (5G) systems, the base station (e.g., eNB or gNB) determines the MCS for downlink transmission based on the Channel State Information (CSI) report received from the wireless terminal (e.g., UE). However, there is a delay (e.g., tens of ms) between the time the wireless terminal measures the reception quality (e.g., SINR) of the CSI-related reference signal (e.g., CSI-RS) and the time the base station determines the MCS based on the CSI report. Furthermore, errors may occur in the measurement of the CSI-related reference signal by the wireless terminal. Due to these factors, the radio quality (or channel state) when downlink transmission is performed may differ from that when the wireless terminal measures the CSI-related reference signal. This difference may lead to a situation where the radio parameters (e.g., MCS) selected or determined based on the measurement results of the radio quality (or channel state) cannot achieve the target communication quality (e.g., target BLER). Patent documents 1 and 2 do not provide a solution to the above-mentioned problems.

[0006] One of the objectives that the embodiments disclosed herein seek to achieve is to provide apparatus, methods, and programs that contribute to improving the likelihood that radio parameters (e.g., MCS) selected or determined based on radio quality measurement results can achieve target communication quality (e.g., target BLER). It should be noted that this objective is only one of several objectives that the embodiments disclosed herein seek to achieve. Other objectives or problems and novel features will be revealed in the description herein or in the accompanying drawings. [Means for solving the problem]

[0007] In a first embodiment, the control device includes at least one memory and at least one processor coupled to the at least one memory. The at least one processor is configured to predict a probability distribution of radio quality when a downlink transmission from a base station to a radio terminal or an uplink transmission from the radio terminal to the base station is performed. The at least one processor is configured to use the probability distribution to calculate an expected value of the block error rate (BLER) or reliability of the downlink or uplink transmission. Furthermore, the at least one processor is configured to take the expected value into consideration to determine the value of each of one or more parameters related to the downlink or uplink transmission.

[0008] In the second embodiment, the method performed by the control device includes the following steps: (a) Predicting the probability distribution of radio quality when downlink transmission from a base station to a wireless terminal or uplink transmission from the wireless terminal to the base station, (b) Using the probability distribution, calculate the expected value of the block error rate (BLER) or reliability of the downlink or uplink transmission, and (c) Taking the above-mentioned expected values ​​into consideration, determine the value of each of the one or more parameters relating to the downlink or uplink transmission.

[0009] In the third aspect, the program includes a set of instructions (software code) that, when loaded into a computer, cause the computer to perform the method described in the second aspect above. [Effects of the Invention]

[0010] According to the above-described embodiment, it is possible to provide an apparatus, method, and program that contribute to improving the likelihood that radio parameters (e.g., MCS) selected or determined based on the measurement results of radio quality can achieve target communication quality (e.g., target BLER). [Brief explanation of the drawing]

[0011] [Figure 1] It is a diagram showing a configuration example of a wireless communication system according to an embodiment. [Figure 2] It is a flowchart showing an example of the operation of a control device according to an embodiment. [Figure 3] It is a flowchart showing an example of the operation of a control device according to an embodiment. [Figure 4] It is a flowchart showing an example of the operation of a control device according to an embodiment. [Figure 5] It is a diagram for explaining an example of the operation of a control device according to an embodiment. [Figure 6] It is a flowchart showing an example of the operation of a control device according to an embodiment. [Figure 7] It is a diagram for explaining an example of the operation of a control device according to an embodiment. [Figure 8] It is a flowchart showing an example of the operation of a control device according to an embodiment. [Figure 9] It is a diagram for explaining an example of the operation of a control device according to an embodiment. [Figure 10] It is a block diagram showing a configuration example of a control device according to an embodiment.

Embodiments for Carrying Out the Invention

[0012] Hereinafter, specific embodiments will be described in detail with reference to the drawings. In each drawing, the same or corresponding elements are denoted by the same reference numerals, and redundant descriptions are omitted as necessary for clarity of explanation.

[0013] The plurality of embodiments described below can be implemented independently or can be implemented in appropriate combinations. These plurality of embodiments have different novel features. Therefore, these plurality of embodiments contribute to solving different purposes or problems and contribute to achieving different effects.

[0014] The following embodiments are mainly described with respect to the Third Generation Partnership Project (3GPP (registered trademark)) Long Term Evolution (LTE) system and the fifth generation mobile communication system (5G system). However, these embodiments may be applied to other wireless communication systems.

[0015] As used herein, depending on the context, "(if)~then" may be interpreted to mean "when", "at or around the time", "after", "upon", "in response to determining", "in accordance with a determination", or "in response to detecting". These expressions may be interpreted to have the same meaning depending on the context.

[0016] First, the configuration of a wireless communication system common to a plurality of embodiments will be described. FIG. 1 shows a configuration example of a wireless communication system according to a plurality of embodiments. In the example of FIG. 1, the wireless communication system includes a control device 1, a base station 2, and a wireless terminal 3. The base station 2 may be referred to as an eNB, gNB, radio station, radio access network node, or wireless access point. The wireless terminal 3 may be referred to as a user equipment (UE), user terminal, or wireless transceiver. Each element (network function) shown in FIG. 1 can be implemented, for example, as a network element on dedicated hardware, as a software instance running on dedicated hardware, or as a virtualized function instantiated on an application platform.

[0017] Base station 2 communicates with wireless terminal 3 via an air interface. Base station 2 transmits downlink signals to wireless terminal 3 and receives uplink signals from wireless terminal 3. Base station 2 may communicate simultaneously with multiple wireless terminals, including wireless terminal 3. Wireless terminal 3 may communicate simultaneously with multiple base stations, including base station 2. Wireless terminal 3, or wireless terminal 3 and base station 2, may be applied to industrial applications such as manufacturing facilities, transportation systems, and logistics systems. For example, wireless terminal 3 may be implemented in manufacturing robots, automated guided vehicles (AGVs), construction machinery, or other equipment used in cities, buildings, transportation networks, and public infrastructure.

[0018] Base station 2 may include a Central Unit (CU) and one or more Distributed Units (DUs). The CU may include a CU Control Plane (CU-CP) Unit and one or more CU User Plane (CU-UP) Units. In some implementations, the CU may host RRC functionality, Service Data Adaptation Protocol (SDAP) layer functionality, and Packet Data Convergence Protocol (PDCP) layer functionality. The DUs, on the other hand, may host Radio Link Control (RLC) layer, Medium Access Control (MAC) layer, and some or all of the Physical (PHY) layer functionality. Base station 2 may further include one or more Radio Units (RUs) responsible for some physical layer or Layer 1 (e.g., Low PHY) signaling and Radio Frequency (RF) signaling.

[0019] The control device 1 provides control and optimization of the base station 2 and its resources through data acquisition and actions on a control interface. This control interface may be, for example, an Open Radio Access Network (O-RAN) E2 interface. The control device 1 may be a Radio Access Network (RAN) Intelligent Controller (RIC) or integrated into one. The control device 1 may also be integrated into the base station 2.

[0020] <First Embodiment> The configuration example of the wireless communication system according to this embodiment may be the same as the example shown in Figure 1. This embodiment provides an example of the operation performed by the control device 1.

[0021] Figure 2 is a flowchart showing an example of the operation of the control device 1. In step 201, the control device 1 predicts the probability distribution of radio quality when downlink transmission from base station 2 to wireless terminal 3 or uplink transmission from wireless terminal 3 to base station 2 occurs.

[0022] The radio quality may be SINR, SNR, SIR, or Reference Signal Received Quality (RSRQ). In the case of downlink, the radio quality may be or be based on the reception quality of the downlink CSI-related reference signal transmitted from base station 2 to radio terminal 3. In the case of uplink, the radio quality may be or be based on the reception quality of the uplink CSI-related reference signal transmitted from radio terminal 3 to base station 2. If base station 2 and radio terminal 3 are the gNB (or gNB-CU or gNB-DU) and UE of the 5G system, the downlink CSI-related reference signal may be the CSI Reference Signal (CSI-RS) or Synchronization Signal (SS), and the uplink CSI-related reference signal may be the Sounding Reference Signal (SRS).

[0023] The probability distribution of radio quality can also be called the probability density function (PDF) of radio quality. The control device 1 may collect a time series of radio quality data from the base station 2 and calculate, determine, or derive the probability distribution of radio quality based on this data. In some implementations, the control device 1 may perform inference based on artificial intelligence (AI) or machine learning (ML) to obtain the probability distribution or probability density function of radio quality. AI / ML inference means prediction or decision based on a trained machine learning model. The control device 1 may use the time series of radio quality data as input data to a trained machine learning model for performing inference. The control device 1 may generate the input data supplied to the trained machine learning model from the time series of radio quality data.

[0024] The control device 1 may train the machine learning model. Alternatively, a device or computer system different from the control device 1 (e.g., Non-Real-Time RIC) may train the machine learning model and supply the trained machine learning model (i.e., trained parameters) to the control device 1.

[0025] The probability distribution of radio quality is influenced by various factors. These factors include the model or type of the radio terminal 3, the speed of the radio terminal 3, the interference status of the radio terminal 3, the presence or absence of obstructions, the transmission time interval of the CSI-related reference signal, the frequency density of the transmission resources for the CSI-related reference signal, the transmission time interval of the CSI report, the use of beamforming, the transmission time interval of the demodulation-related reference signal, the frequency density of the transmission resources for the CSI-related reference signal, the frequency density of the transmission resources for the demodulation-related reference signal, and the use of Multi-Input Multi-Output (MIMO). These factors may be further considered when training a machine learning model. In addition, the control device 1 may use these factors as input data to obtain the probability distribution of radio quality from the trained learning model. The demodulation-related reference signal is used in the receiver to demodulate the transmitted signal. In other words, the demodulation-related reference signal is used for channel estimation. If base station 2 and wireless terminal 3 are the gNB (or gNB-CU or gNB-DU) and UE of the 5G system, the demodulation-related reference signal may be Demodulation RS (DMRS).

[0026] In step 202, the control device 1 calculates the expected value of the BLER or reliability of the downlink or uplink transmission using the predicted probability distribution of radio quality. The expected value of BLER can be derived by integral calculation using the probability density function of radio quality (e.g., SINR) and the BLER vs. radio quality (e.g., SINR) curve. For example, when SINR has a probability density function p(s) and the BLER vs. SINR curve is e(s), the expected value of BLER is obtained by the following integral:

number

[0027] Reliability refers to the reliability of communication. Reliability may also be defined as 1-BLER. In this case, the expected value of reliability can be obtained, for example, by subtracting the expected value of BLER from 1. Alternatively, for example, the expected value of BLER can be derived by integral calculation using the probability density function of radio quality (e.g., SINR) and the reliability versus radio quality (e.g., SINR) curve. BLER can be said to be the probability that data (or data packets, transport blocks) cannot be successfully transmitted in a predetermined minimum number of attempts. Conversely, reliability can be said to be the probability that data can be successfully transmitted in a predetermined number of retries.

[0028] The BLER-to-wireless quality curve may be stored in memory within the control unit 1 or in external memory accessible by the control unit 1. The BLER-to-wireless quality curve may be obtained by a curve fitting method using the SINR and BLER measurement results. Alternatively, the BLER-to-wireless quality curve may be obtained by machine learning or deep learning that takes into account the SINR and BLER measurement results and other factors.

[0029] In step 203, the control unit 1 determines the value of each of one or more parameters related to downlink or uplink transmission, taking into account the calculated BLER or reliability expectation. The control unit 1 may also determine the value of each of one or more parameters related to downlink or uplink transmission, taking into account the communication quality requirements imposed on the downlink or uplink transmission. More specifically, the control unit 1 may determine the value of each of one or more parameters so that the downlink or uplink transmission is expected to satisfy the communication quality requirements. The control unit 1 may determine a combination of multiple parameters that affect the achievement of the communication quality requirements, in other words, that are correlated with the communication requirements. In this case, the control unit 1 may adjust the values ​​of the multiple parameters in relation to each other so that the communication quality requirements are satisfied.

[0030] Communication quality requirements may include BLER or reliability requirements. BLER or reliability requirements include the target value of BLER (e.g., 10 -2 , 10 -3 Alternatively, a reliability target value (e.g., 99%, 99.9%) may be set.

[0031] Furthermore, or alternatively, the communication quality requirements may include delay requirements. These delay requirements may also be referred to as delay constraints or delay budgets. The delay requirements may define the allowable delay for end-to-end communication at the application layer. Alternatively, the delay requirements may define the allowable delay for downlink or uplink transmission at the wireless layer. The allowable delay at the wireless layer may be derived from the allowable delay for end-to-end communication at the application layer.

[0032] Communication quality requirements may be changed or updated dynamically. Changes or updates to communication quality requirements may be based on the requirements of the application (or application layer). For example, if we consider a use case where wireless terminal 3 is mounted on an AGV, the latency requirements required by the application may vary depending on the movement speed of the AGV on which wireless terminal 3 is mounted. Furthermore, this latency requirement may vary depending on the distance between the AGV on which wireless terminal 3 is mounted and other AGVs.

[0033] When determining the values ​​of one or more parameters, the control device 1 may consider other factors, such as the radio load of the base station (in other words, the utilization rate of radio resources). For example, if the radio resource utilization rate is temporarily high, the control device 1 may temporarily relax the reliability target value. Conversely, if the radio resource utilization rate is temporarily low, the control device 1 may temporarily tighten the reliability target value. This makes it possible to satisfy a predetermined reliability target value as a long-term average reliability.

[0034] Figure 3 shows an example of the process in step 203 of Figure 2. In step 301, the control unit 1 obtains the BLER or reliability and delay requirements. These communication quality requirements may be stored in memory within the control unit 1 or in external memory accessible to the control unit 1. The control unit 1 may communicate with an application or other device or computer system (e.g., Non-Real-Time RIC) to obtain some or all of these communication quality requirements.

[0035] In step 302, the control device 1 determines the value of one or more parameters such that both the BLER or reliability and delay requirements are satisfied.

[0036] In the examples in Figures 2 and 3, one or more parameters may include a Modulation and Coding Scheme (MCS) for adaptive modulation coding. The MCS may be represented by an MCS index. The MCS or MCS index represents a combination of modulation order (or modulation scheme) and code rate. A larger MCS or MCS index corresponds to a larger modulation order and a higher code rate. Therefore, for a given radio quality (e.g., SINR) or channel state, a larger MCS index improves radio resource utilization efficiency but increases BLER.

[0037] Furthermore, or alternatively, one or more parameters may include the maximum number of retransmissions. The maximum number of retransmissions may be the maximum number of hybrid automatic repeat request (HARQ) retransmissions at the MAC sublayer. A higher number of retransmissions results in a smaller BLER but increased latency.

[0038] Furthermore, or alternatively, one or more parameters may include a parameter indicating whether or not packet duplication is used. In the case of LTE and 5G systems, packet duplication may be the duplication of packets (i.e., PDCP Protocol Data Units (PDUs)) at the PDCP layer in carrier aggregation or for split bearers in dual connectivity. The use of packet duplication contributes to a decrease in BLER or an improvement in reliability. On the other hand, the use of packet duplication reduces the efficiency of radio resource utilization.

[0039] Furthermore, or alternatively, one or more parameters may include the number of MIMO layers, a parameter indicating whether Single-User (SU) MIMO or Multi-User (MU) MIMO is used, or both. The number of MIMO layers may also be called the number of MIMO transmit layers, spatial multiplexing, or spatial streams. Generally, the more MIMO layers or spatial multiplexing there are, the more likely interference is to occur. Also, interference is more likely to occur in MU-MIMO than in SU-MIMO.

[0040] Furthermore, or alternatively, one or more parameters may include either or both the time interval and frequency density of the downlink reference signal (e.g., CSI-RS or DMRS or both) transmitted by base station 2. Furthermore, or alternatively, one or more parameters may include the time interval of the channel status report (e.g., CSI report) transmitted by radio terminal 3. Furthermore, or alternatively, one or more parameters may include either or both the time interval and frequency density of the uplink reference signal (e.g., SRS or DMRS or both) transmitted by radio terminal 3. The transmission time interval may be called or replaced with the transmission frequency, transmission pattern, or transmission period. The frequency density of the downlink or uplink reference signal is the frequency density of the reference signal resources and depends on the frequency arrangement of the reference signal resources. The frequency density of reference signal resources may be defined, for example, as the number of reference signal resources (e.g., Resource Elements (Res)) per given set of frequency resources (e.g., Physical Resource Block (PRB)). The time interval and frequency density of downlink or uplink reference signal transmissions may collectively be referred to as the downlink or uplink reference signal time-frequency density or transmission frequency. Increasing the reference signal transmission frequency (or time-frequency density) or CSI report transmission frequency contributes to reducing the statistical variability (i.e., standard deviation and variance) of the SINR probability distribution. On the other hand, increasing the reference signal transmission frequency or CSI report transmission frequency increases the consumption of radio and computing resources.

[0041] Furthermore, or alternatively, one or more parameters may include the subcarrier spacing. A larger subcarrier spacing tends to enhance frequency diversity and suppress effective SINR fluctuations. Also, a larger subcarrier spacing reduces delay. Conversely, a smaller subcarrier spacing improves frequency utilization efficiency. The subcarrier spacing may be selected by selecting the Bandwidth Part (BWP).

[0042] As described above, the control device 1 may adjust the values ​​of multiple parameters to satisfy one or more communication quality requirements (e.g., BLER or reliability and delay requirements). Several examples are shown below.

[0043] The control unit 1 may adjust the MCS applied to each link depending on whether packet replication is used and the number of redundant links to which replicated packets are transmitted. For example, if the delay requirement requested by the application can be met if the BLER is 0.01 or less, the control unit 1 may adjust the MCS applied to each link so that the BLER of each of the two redundant links is 0.1 or less. The control unit 1 may increase the MCS index of the links of cells or base stations with high loads and decrease the MCS index of the links of cells or base stations with low loads. This can help equalize the load on the two cells or base stations while maintaining the combined delay requirement achievement rate of the two links.

[0044] The control device 1 may adjust the MCS according to the frequency of transmission of the reference signal or the frequency of transmission of the CSI report. For example, increasing the frequency of transmission of CSI-RS on the downlink and increasing the frequency of transmission of CSI reports from the wireless terminal 3 to the base station can improve the certainty of the predicted SINR. In this case, the control device 1 can increase the MCS index to meet the BLER and delay requirements. The control device 1 may consider the increase in downlink resource utilization efficiency due to increasing the MCS index and the decrease in downlink resource utilization efficiency due to increasing the frequency of transmission of the reference signal.

[0045] In the operation described with reference to Figures 2 and 3, the control device 1 predicts the probability distribution or probability density function of the radio quality (e.g., SINR) when downlink or uplink transmission occurs, and uses the predicted probability distribution or probability density function to determine the value of one or more parameters (e.g., MCS index) related to downlink or uplink transmission. In other words, when determining the value of one or more parameters related to downlink or uplink transmission, the control device 1 takes into account the expected statistical variability of radio quality. This can contribute to improving the accuracy of estimating the expected value of BLER or reliability, and can contribute to improving the likelihood that the parameters selected or determined based on the measurement results of radio quality can achieve the target communication quality (e.g., target BLER).

[0046] <Second Embodiment> The configuration example of the wireless communication system according to this embodiment may be the same as the example shown in Figure 1. This embodiment provides a detailed example of the operation of the control device 1 described in the first embodiment.

[0047] In this embodiment, the control device 1 determines a plurality of BLER or reliability expectation values ​​corresponding to different candidate values ​​of a first parameter related to downlink or uplink transmission. The control device 1 then selects a value for the first parameter to be applied to downlink or uplink transmission from among the one or more candidate values ​​corresponding to one or more BLER or reliability expectation values ​​that satisfy the BLER or reliability requirements. The first parameter may include MCS (or MCS index). The first parameter may further include one or both of the parameters indicating the maximum number of retransmissions and whether or not packet duplication is used. The first parameter may include other parameters.

[0048] The operation of the control device 1 will be described in more detail below. Figure 4 is a flowchart of an example of the operation of the control device 1. In the example in Figure 4, the first parameter includes at least the MCS.

[0049] In step 401, the control device 1 predicts the SINR probability density function when a downlink transmission from the base station 2 to the wireless terminal 3 or an uplink transmission from the wireless terminal 3 to the base station 2 occurs. The method for determining the SINR probability density function may be the same as any of the methods described in relation to step 201 in Figure 2 in the first embodiment.

[0050] In step 402, the control device 1 calculates multiple BLER or reliability expectations for multiple MCS candidate values ​​using the SINR probability density function and multiple BLER vs. SINR curves corresponding to multiple MCS candidate values. The BLER or reliability expectation for each MCS candidate value can be derived by integral calculation using the SINR probability density function and the BLER vs. SINR curve corresponding to that MCS candidate value.

[0051] As described in relation to the first embodiment, multiple BLER vs. SINR curves may be stored in memory within the control unit 1 or in external memory accessible by the control unit 1. Each BLER vs. SINR curve may be obtained by a curve fitting method using the SINR and BLER measurement results for each MCS. Alternatively, each BLER vs. SINR curve may be obtained by machine learning or deep learning that takes into account the SINR and BLER measurement results for each MCS and other factors.

[0052] In step 403, the control unit 1 selects an MCS value to be applied to the downlink or uplink transmission from among one or more MCS candidate values ​​corresponding to one or more BLER or reliability expectations that satisfy the BLER or reliability requirements. The control unit 1 may further consider other traffic quality requirements, such as delay requirements. The control unit 1 may select an MCS value to be applied to the downlink or uplink transmission that satisfies both the BLER or reliability requirements and the delay requirements.

[0053] Referring to Figure 5, a specific example of the operation in Figure 4 will be explained. The control device 1 predicts the SINR probability density function 501 when a downlink or uplink transmission is performed. This corresponds to step 401 in Figure 4. Next, the control device 1 uses the SINR probability density function 501 and several BLER vs. SINR curves 521, 522, and 523 to obtain results 541, 542, and 543, which include several confidence expectations. As already explained, the confidence expectation is calculated by subtracting the BLER expectation from 1.

[0054] BLER vs. SINR curves 521, 522, and 523 are associated with different combinations of MCS index and maximum number of retransmissions. In other words, in the example in Figure 5, the first parameter includes the MCS and the maximum number of retransmissions. Specifically, BLER vs. SINR curve 521 is the BLER vs. SINR curve when MCS index #20 (MCS-20) is used and no retransmissions occur (i.e., the maximum number of retransmissions is 0). BLER vs. SINR curve 522 is the BLER vs. SINR curve when MCS index #10 (MCS-10) is used and no retransmissions occur. BLER vs. SINR curve 523 is the BLER vs. SINR curve when MCS index #10 (MCS-10) is used and one retransmission occurs.

[0055] Result 541 includes the reliability expectation obtained using the BLER vs. SINR curve 521. Result 542 includes the reliability expectation obtained using the BLER vs. SINR curve 522. Result 543 includes the reliability expectation obtained using the BLER vs. SINR curve 523. As an example, if the reliability requirement imposed on downlink or uplink transmission is 99.9% or higher, the control device 1 may select MCS index #10 (MCS-10) for downlink or uplink transmission.

[0056] In the example in Figure 5, results 541, 542, and 543 each further represent the maximum delay and radio load. If further delay requirements are imposed on downlink or uplink transmissions, the control unit 1 may, in determining the MCS index, select an MCS or combination of MCS and the maximum number of retransmissions where the maximum delay satisfies the delay requirement. If there are multiple candidate MCS values ​​that satisfy the communication quality requirements (e.g., reliability requirements and delay requirements), the control unit 1 may determine the MCS to be applied to downlink or uplink transmissions in such a way that the radio load on base station 2 is small.

[0057] Similar to the first embodiment, in this embodiment, the control device 1 predicts the probability density function of radio quality (e.g., SINR) when downlink or uplink transmission is performed, and uses the predicted probability density function to determine the value of one or more parameters (e.g., MCS index) related to downlink or uplink transmission. In other words, when determining the value of one or more parameters related to downlink or uplink transmission, the control device 1 takes into account the expected statistical variability of radio quality. This can contribute to improving the accuracy of estimating the expected value of BLER or reliability, and can contribute to improving the likelihood that the parameters selected or determined based on the measurement results of radio quality can achieve the target communication quality (e.g., target BLER).

[0058] <Third Embodiment> The configuration example of the wireless communication system according to this embodiment may be the same as the example shown in Figure 1. This embodiment provides a detailed example of the operation of the control device 1 described in the first embodiment.

[0059] In this embodiment, the control device 1 determines a plurality of radio quality probability distributions (or probability density functions) corresponding to different candidate values ​​of a second parameter related to downlink or uplink transmission. Furthermore, the control device 1 calculates a plurality of BLER or reliability expectation values ​​corresponding to these plurality of probability distributions (or probability density functions). Then, the control device 1 selects a value for the second parameter applied to downlink or uplink transmission from among the one or more candidate values ​​corresponding to one or more BLER or reliability expectation values ​​that satisfy the BLER or reliability requirements. The second parameter may include one or any combination of the following: the number of MIMO layers; a parameter indicating whether SU-MIMO or MU-MIMO is used; the time interval for the transmission of downlink reference signals by the base station 2; the time interval for the transmission of channel status reports by the radio terminal 3; the time interval for the transmission of uplink reference signals by the radio terminal 3; and the subcarrier interval.

[0060] The operation of the control device 1 will be described in more detail below. Figure 6 is a flowchart showing an example of the operation of the control device 1. In the example in Figure 6, the second parameter includes at least the number of MIMO layers.

[0061] In step 601, the control device 1 predicts multiple SINR probability density functions corresponding to candidate values ​​with different MIMO layer numbers. The method for determining each SINR probability density function may be similar to any of the methods described in relation to step 201 in Figure 2 in the first embodiment.

[0062] In step 602, the control device 1 calculates multiple BLER or reliability expectations for multiple candidate MIMO layer counts using multiple SINR probability density functions and BLER vs. SINR curves. The BLER or reliability expectation for each MIMO layer count candidate can be derived by integral calculation using the BLER vs. SINR curve and the SINR probability density function corresponding to that MIMO layer count candidate.

[0063] In step 603, the control unit 1 selects a MIMO layer count value to be applied to the downlink or uplink transmission from among candidate MIMO layer count values ​​corresponding to one or more BLER or reliability expectations that satisfy the BLER or reliability requirements. The control unit 1 may further consider other traffic quality requirements, such as delay requirements. The control unit 1 may also select a MIMO layer count value to be applied to the downlink or uplink transmission that satisfies both the BLER or reliability requirements and the delay requirements.

[0064] Referring to Figure 7, a specific example of the operation in Figure 6 will be explained. The control device 1 predicts the SINR probability density functions 701, 702, and 703 when a downlink or uplink transmission is performed. This corresponds to step 601 in Figure 6. The SINR probability density functions 701, 702, and 703 correspond to different combinations of the number of MIMO layers and the selection between SU-MIMO and MU-MIMO. In other words, in the example in Figure 7, the second parameter includes the number of MIMO layers and a parameter indicating whether SU-MIMO or MU-MIMO is used.

[0065] Specifically, SINR probability density function 701 is the SINR probability density function when SU-MIMO is used and the number of transmitting layers is 1. SINR probability density function 702 is the SINR probability density function when SU-MIMO is used and the number of transmitting layers is 2. SINR probability density function 703 is the SINR probability density function when MU-MIMO is used and the number of transmitting layers (or spatial multiplexing) is 2. Generally, interference is more likely to occur with a larger number of MIMO layers or spatial multiplexing. Furthermore, interference is more likely to occur with MU-MIMO than with SU-MIMO. Therefore, SINR probability density function 701 tends to have smaller statistical variability (i.e., variance and standard deviation) than the other two probability density functions 702 and 703. On the other hand, SINR probability density function 703 tends to have larger statistical variability (i.e., variance and standard deviation) than the other two probability density functions 701 and 702.

[0066] Next, the control device 1 uses a plurality of SINR probability density functions 701, 702, and 703 and a BLER vs. SINR curve 722 to obtain results 741, 742, and 743, which include a plurality of reliability expectations. As already explained, the reliability expectation is calculated by subtracting the BLER expectation from 1. Result 741 includes the reliability expectation obtained using the SINR probability density function 701. Result 742 includes the reliability expectation obtained using the SINR probability density function 702. Result 743 includes the reliability expectation obtained using the SINR probability density function 703. As an example, if the reliability requirement imposed on downlink or uplink transmission is 99.9% or higher, the control device 1 may select SU-MIMO and single-layer transmission, or SU-MIMO and dual-layer transmission, for downlink or uplink transmission.

[0067] In the example in Figure 7, results 741, 742, and 743 each further represent the maximum delay. If further delay requirements are imposed on downlink or uplink transmission, the control device 1 may select a combination in which the maximum delay satisfies the delay requirements. Generally, it is known that for uplink transmission by the wireless terminal 3, a smaller number of transmission layers results in better delay performance, and that SU-MIMO offers better delay performance than MU-MIMO. For example, if the reliability requirement is 99.9% or higher and the delay requirement is 5 ms or less, the control device 1 may select SU-MIMO and single-layer transmission for downlink or uplink transmission.

[0068] Similar to the first embodiment, in this embodiment, the control device 1 predicts the probability density function of radio quality (e.g., SINR) when downlink or uplink transmission is performed, and uses the predicted probability density function to determine the value of one or more parameters (e.g., MCS index) related to downlink or uplink transmission. In other words, when determining the value of one or more parameters related to downlink or uplink transmission, the control device 1 takes into account the expected statistical variability of radio quality. This can contribute to improving the accuracy of estimating the expected value of BLER or reliability, and can contribute to improving the likelihood that the parameters selected or determined based on the measurement results of radio quality can achieve the target communication quality (e.g., target BLER).

[0069] <Fourth Embodiment> The configuration example of the wireless communication system according to this embodiment may be the same as the example shown in Figure 1. This embodiment provides a detailed example of the operation of the control device 1 described in the first embodiment.

[0070] From the above description, those skilled in the art will understand that the method described in the second embodiment can be combined with the method described in the third embodiment. This embodiment provides a specific example of such a combination.

[0071] Figure 8 is a flowchart illustrating an example of the operation of the control device 1. In the example in Figure 8, the first parameter relating to downlink or uplink transmission includes at least the MCS (or MCS index). Furthermore, in the example in Figure 8, the second parameter relating to downlink or uplink transmission includes at least the number of MIMO layers.

[0072] In step 801, the control device 1 predicts multiple SINR probability density functions corresponding to candidate values ​​with different MIMO layer numbers. The method for determining each SINR probability density function may be similar to any of the methods described with respect to step 201 in Figure 2 in the first embodiment.

[0073] In step 802, the control device 1 calculates multiple BLER or reliability expectations for different combinations of candidate MIMO layer counts and MCS candidate values. In these calculations, the control device 1 uses multiple SINR probability density functions and multiple BLER vs. SINR curves corresponding to multiple MCS candidate values. The BLER or reliability expectation for each combination of MIMO layer count candidate values ​​and MCS candidate values ​​can be derived by integral calculation using the BLER vs. SINR curve corresponding to the MCS candidate value and the SINR probability density function corresponding to the MIMO layer count candidate value.

[0074] In step 803, the control unit 1 selects a MIMO layer count value and an MCS value to be applied to downlink or uplink transmission from a combination of one or more MIMO layer count candidate values ​​and MCS candidate values ​​corresponding to one or more BLER or reliability expectations that satisfy the BLER or reliability requirement. The control unit 1 may further consider other traffic quality requirements, such as delay requirements. The control unit 1 may select a MIMO layer count value and an MCS value that satisfies both the BLER or reliability requirement and the delay requirement.

[0075] Referring to Figure 9, a specific example of the operation in Figure 8 will be explained. The control device 1 predicts the SINR probability density functions 901, 902, and 903 when a downlink or uplink transmission is performed. This corresponds to step 801 in Figure 8. The SINR probability density functions 901, 902, and 903 correspond to different combinations of the number of MIMO layers and the selection between SU-MIMO and MU-MIMO. In other words, in the example in Figure 9, the second parameter includes the number of MIMO layers and a parameter indicating whether SU-MIMO or MU-MIMO is used.

[0076] Specifically, SINR probability density function 901 is the SINR probability density function when SU-MIMO is used and the number of transmitting layers is 1. SINR probability density function 902 is the SINR probability density function when SU-MIMO is used and the number of transmitting layers is 2. SINR probability density function 903 is the SINR probability density function when MU-MIMO is used and the number of transmitting layers (or spatial multiplexing) is 2.

[0077] Next, the control device 1 calculates multiple BLER or reliability expectation values ​​for different combinations of the first and second parameters using multiple SINR probability density functions 901, 902, and 903 and multiple BLER vs. SINR curves 921, 922, and 923. In the example in Figure 9, the control device 1 may calculate nine BLER or reliability expectation values ​​for nine different parameter combinations. The control device 1 selects MIMO layer count values ​​and MCS values ​​that can satisfy communication quality requirements (e.g., BLER or reliability requirements and delay requirements).

[0078] Similar to the first embodiment, in this embodiment, the control device 1 predicts the probability density function of radio quality (e.g., SINR) when downlink or uplink transmission is performed, and uses the predicted probability density function to determine the value of one or more parameters (e.g., MCS index) related to downlink or uplink transmission. In other words, when determining the value of one or more parameters related to downlink or uplink transmission, the control device 1 takes into account the expected statistical variability of radio quality. This can contribute to improving the accuracy of estimating the expected value of BLER or reliability, and can contribute to improving the likelihood that the parameters selected or determined based on the measurement results of radio quality can achieve the target communication quality (e.g., target BLER).

[0079] Next, the configuration examples of the control device 1 according to the above-described multiple embodiments will be explained below. Referring to Figure 10, the control device 1 includes a network interface 1001, a processor 1002, and a memory 1003.

[0080] Network interface 2701 is used, for example, to communicate with other network elements, functions, or nodes. Network interface 1001 may include, for example, a network interface card (NIC) compliant with the IEEE 802.3 series.

[0081] The processor 1002 may be, for example, a microprocessor, a Micro Processing Unit (MPU), or a Central Processing Unit (CPU). The processor 1002 may include multiple processors.

[0082] Memory 1003 is composed of volatile memory and non-volatile memory. Memory 1003 may include multiple physically independent memory devices. Volatile memory is, for example, Static Random Access Memory (SRAM) or Dynamic RAM (DRAM), or a combination thereof. Non-volatile memory is Mask Read Only Memory (MROM), Electrically Erasable Programmable ROM (EEPROM), flash memory, or hard disk drive, or any combination thereof. Memory 1003 may include storage located away from the processor 1002. In this case, the processor 1002 may access memory 1003 via a network interface 1001 or an I / O interface.

[0083] The memory 1003 may store one or more software modules (computer programs) 1004 containing instruction sets and data for processing by the control device 1 as described in the above-described embodiments. In some implementations, the processor 1002 may be configured to read the software modules 1004 from the memory 1003 and execute them to perform the processing of the control device 1 as described in the above-described embodiments.

[0084] As illustrated with Figure 10, the processor of the control device 1 according to the above embodiment can execute one or more programs, which include a set of instructions for causing a computer to perform the algorithm described with reference to the drawings. The program includes a set of instructions (or software code) for causing the computer to perform one or more functions described in the embodiment when loaded into a computer. The program may be stored on a non-temporary computer-readable medium or a physical storage medium. Examples, but not limited, of the computer-readable medium or physical storage medium include random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technologies, CD-ROM, digital versatile disk (DVD), Blu-ray® disc or other optical disc storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage devices. The program may be transmitted over a temporary computer-readable medium or a communication medium. Examples, but not limited, of the temporary computer-readable medium or communication medium include electrical, optical, acoustic or other forms of propagating signals.

[0085] The embodiments described above are merely examples of how the technical concept obtained by the present inventor can be applied. In other words, the technical concept is not limited to the embodiments described above, and various modifications are certainly possible.

[0086] For example, some or all of the above embodiments may also be described as follows, but are not limited to the following.

[0087] (Note 1) At least one memory, At least one processor coupled to the at least one memory, Equipped with, The aforementioned at least one processor is Predict the probability distribution of radio quality when downlink transmission from a base station to a wireless terminal or uplink transmission from the wireless terminal to the base station. Using the aforementioned probability distribution, calculate the expected value of the block error rate (BLER) or reliability of the downlink or uplink transmission. Taking the aforementioned expected values ​​into consideration, determine the value of each of the one or more parameters related to the downlink or uplink transmission. It is structured in such a way. Control device. (Note 2) The at least one processor is configured to take into account the BLER or reliability requirements imposed on the downlink or uplink transmission in determining the one or more parameters. The control device described in Appendix 1. (Note 3) The aforementioned expected value includes a plurality of expected values ​​corresponding to different candidate values ​​of the first parameter included in the one or more parameters, The at least one processor is configured to select a value for the first parameter from one or more candidate values ​​corresponding to the BLER or one or more expected values ​​that satisfy the reliability requirements. The control device described in Appendix 2. (Note 4) The first parameter includes a Modulation and Coding Scheme (MCS), The control device described in Appendix 3. (Note 5) The first parameter further includes one or both of the parameters indicating the maximum number of retransmissions and whether or not packet duplication is used. The control device described in Appendix 4. (Note 6) The probability distribution includes a plurality of probability distributions corresponding to different candidate values ​​of a second parameter included in the one or more parameters, The aforementioned expected value includes a plurality of expected values ​​corresponding to the plurality of probability distributions, The at least one processor is configured to select a value for the second parameter from among one or more candidate values ​​corresponding to one or more probability distributions corresponding to one or more expected values ​​that satisfy the BLER or reliability requirements. A control device as described in any one of the items 2 to 5 of the appendix. (Note 7) The second parameter includes one or any combination of the following: the number of Multi-Input Multi-Output (MIMO) layers; a parameter indicating whether Single-User (SU) MIMO or Multi-User (MU) MIMO is used; the time interval between transmissions of downlink reference signals by the base station; the frequency density of the downlink reference signals; the time interval between transmissions of channel status reports by the wireless terminal; the time interval between transmissions of uplink reference signals by the wireless terminal; the frequency density of the uplink reference signals; and the subcarrier interval. The control device described in Appendix 6. (Note 8) The at least one processor is configured to further consider, in determining the value of each of the one or more parameters, the delay requirements imposed on the downlink or uplink transmission. A control device as described in any one of the appendices 2 to 7. (Note 9) The at least one processor is configured to determine the value of each of the one or more parameters such that both the BLER or reliability requirement and the delay requirement are satisfied. The control device described in Appendix 8. (Note 10) The at least one processor is configured to predict the probability distribution using channel status reports from the wireless terminal. A control device as described in any one of the appendices 1 to 9. (Note 11) The aforementioned wireless quality includes signal to interference plus noise ratio (SINR), A control device as described in any one of the appendices 1 to 10. (Note 12) The one or more parameters mentioned above include a Modulation and Coding Scheme (MCS). The control device described in Appendix 1 or 2. (Note 13) The one or more parameters mentioned above include the number of Multi-Input Multi-Output (MIMO) layers, or a parameter indicating whether Single-User (SU) MIMO or Multi-User (MU) MIMO is used, or both. The control device described in Appendix 1 or 2. (Note 14) The one or more parameters mentioned above include one or any combination of the following: Modulation and Coding Scheme (MCS); maximum number of retransmissions; a parameter indicating whether packet duplication is used; number of Multi-Input Multi-Output (MIMO) layers; a parameter indicating whether Single-User (SU) MIMO or Multi-User (MU) MIMO is used; time interval for the base station to transmit downlink reference signals; frequency density of the downlink reference signals; time interval for the wireless terminal to transmit channel status reports; time interval for the wireless terminal to transmit uplink reference signals; frequency density of the uplink reference signals; and subcarrier interval. The control device described in Appendix 1 or 2. (Note 15) The control device is located at the base station or the RAN Intelligent Controller (RIC). A control device as described in any one of the appendices 1 to 14. (Note 16) To predict the probability distribution of radio quality when downlink transmission from a base station to a wireless terminal or uplink transmission from the wireless terminal to the base station occurs. Using the aforementioned probability distribution, calculate the expected value of the block error rate (BLER) or reliability of the downlink or uplink transmission, and Taking the aforementioned expected values ​​into consideration, determine the value of each of the one or more parameters related to the downlink or uplink transmission. A method performed by a control device equipped with the above. (Note 17) To predict the probability distribution of radio quality when downlink transmission from a base station to a wireless terminal or uplink transmission from the wireless terminal to the base station occurs. Using the aforementioned probability distribution, calculate the expected value of the block error rate (BLER) or reliability of the downlink or uplink transmission, and Taking the aforementioned expected values ​​into consideration, determine the value of each of the one or more parameters related to the downlink or uplink transmission. A program that instructs a computer to perform a method that includes [a certain feature / function]. [Explanation of Symbols]

[0088] 1. Control device 2 base station 3 Wireless terminals 1002 Processor 1003 memory 1004 modules

Claims

1. At least one memory, At least one processor coupled to the at least one memory, Equipped with, The aforementioned at least one processor is Predict the probability distribution of radio quality when downlink transmission from a base station to a wireless terminal or uplink transmission from the wireless terminal to the base station. Using the aforementioned probability distribution, calculate the expected value of the block error rate (BLER) or reliability of the downlink or uplink transmission. Taking into consideration the aforementioned expected values ​​and the BLER or reliability requirements imposed on the downlink or uplink transmission, the values ​​of each of the one or more parameters related to the downlink or uplink transmission are determined. It is structured in such a way, The aforementioned expected value includes a plurality of expected values ​​corresponding to different candidate values ​​of the first parameter included in the one or more parameters, The at least one processor is configured to select a value for the first parameter from one or more candidate values ​​corresponding to the BLER or one or more expected values ​​that satisfy the reliability requirements. The first parameter includes a Modulation and Coding Scheme (MCS), The first parameter further includes one or both of the parameters indicating the maximum number of retransmissions and whether or not packet duplication is used. Control device.

2. At least one memory, At least one processor coupled to the at least one memory, Equipped with, The aforementioned at least one processor is Predict the probability distribution of radio quality when downlink transmission from a base station to a wireless terminal or uplink transmission from the wireless terminal to the base station. Using the aforementioned probability distribution, calculate the expected value of the block error rate (BLER) or reliability of the downlink or uplink transmission. Taking into consideration the aforementioned expected values ​​and the BLER or reliability requirements imposed on the downlink or uplink transmission, the values ​​of each of the one or more parameters related to the downlink or uplink transmission are determined. It is structured in such a way, The probability distribution includes a plurality of probability distributions corresponding to different candidate values ​​of a second parameter included in the one or more parameters, The aforementioned expected value includes a plurality of expected values ​​corresponding to the plurality of probability distributions, The at least one processor is configured to select a value for the second parameter from among one or more candidate values ​​corresponding to one or more probability distributions corresponding to one or more expected values ​​that satisfy the BLER or reliability requirements. Control device.

3. The second parameter includes one or any combination of the following: the number of Multi-Input Multi-Output (MIMO) layers; a parameter indicating whether Single-User (SU) MIMO or Multi-User (MU) MIMO is used; the time interval for the base station to transmit the downlink reference signal; the frequency density of the downlink reference signal; the time interval for the wireless terminal to transmit the channel status report; the time interval for the wireless terminal to transmit the uplink reference signal; the frequency density of the uplink reference signal; and the subcarrier interval. The control device according to claim 2.

4. At least one memory, At least one processor coupled to the at least one memory, Equipped with, The aforementioned at least one processor is Predict the probability distribution of radio quality when downlink transmission from a base station to a wireless terminal or uplink transmission from the wireless terminal to the base station. Using the aforementioned probability distribution, calculate the expected value of the block error rate (BLER) or reliability of the downlink or uplink transmission. Taking into consideration the aforementioned expected value, the BLER or reliability requirements imposed on the downlink or uplink transmission, and the delay requirements imposed on the downlink or uplink transmission, the value of each of one or more parameters related to the downlink or uplink transmission is determined. A control device configured in such a way.

5. The at least one processor is configured to determine the value of each of the one or more parameters such that both the BLER or reliability requirement and the delay requirement are satisfied. The control device according to claim 4.

6. To predict the probability distribution of radio quality when downlink transmission from a base station to a wireless terminal or uplink transmission from the wireless terminal to the base station occurs. Using the aforementioned probability distribution, calculate the expected value of the block error rate (BLER) or reliability of the downlink or uplink transmission, and Taking into consideration the aforementioned expected values ​​and the BLER or reliability requirements imposed on the downlink or uplink transmission, determine the value of each of the one or more parameters related to the downlink or uplink transmission. Equipped with, The aforementioned expected value includes a plurality of expected values ​​corresponding to different candidate values ​​of the first parameter included in the one or more parameters, The determination described above includes selecting a value for the first parameter from among one or more candidate values ​​corresponding to one or more expected values ​​that satisfy the BLER or reliability requirements. The first parameter includes a Modulation and Coding Scheme (MCS), The first parameter further includes one or both of the parameters indicating the maximum number of retransmissions and whether or not packet duplication is used. A method performed by a control device.

7. To predict the probability distribution of radio quality when a downlink transmission from a base station to a wireless terminal or an uplink transmission from the wireless terminal to the base station is performed. Using the aforementioned probability distribution, calculate the expected value of the block error rate (BLER) or reliability of the downlink or uplink transmission, and Taking into consideration the aforementioned expected values ​​and the BLER or reliability requirements imposed on the downlink or uplink transmission, determine the value of each of the one or more parameters related to the downlink or uplink transmission. Equipped with, The probability distribution includes a plurality of probability distributions corresponding to different candidate values ​​of a second parameter included in the one or more parameters, The aforementioned expected value includes a plurality of expected values ​​corresponding to the plurality of probability distributions, The determination described above includes selecting a value for the second parameter from among one or more candidate values ​​corresponding to one or more probability distributions corresponding to one or more expected values ​​that satisfy the BLER or reliability requirements. A method performed by a control device.

8. Predicting the probability distribution of radio quality when downlink transmission from a base station to a wireless terminal or uplink transmission from the wireless terminal to the base station, Using the aforementioned probability distribution, calculate the expected value of the block error rate (BLER) or reliability of the downlink or uplink transmission, and Determining the value of each of one or more parameters related to the downlink or uplink transmission, taking into consideration the aforementioned expected value, the BLER or reliability requirements imposed on the downlink or uplink transmission, and the delay requirements imposed on the downlink or uplink transmission. Equipped with, A method performed by a control device.

9. The determination includes determining the value of each of the one or more parameters such that both the BLER or reliability requirement and the delay requirement are satisfied. The method according to claim 8.

10. A program for causing a computer to perform the method described in any one of claims 6 to 9.

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