CN113965291B - Communication control method, base station, terminal and storage medium - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
- H04L1/0023—Systems modifying transmission characteristics according to link quality, e.g. power backoff characterised by the signalling
- H04L1/0026—Transmission of channel quality indication
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
- H04L1/0009—Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the channel coding
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Abstract
The embodiment of the invention provides a communication control method, a base station, a terminal and a storage medium, wherein the method comprises the following steps: the base station can input the uplink time into a plurality of first prediction models when the base station performs uplink authorization for the terminal to obtain a plurality of uplink channel quality predicted values, so that the base station can determine a target codebook for a modulation and coding strategy for the terminal and authorize the terminal by using the target codebook. The method further comprises the steps of: the terminal inputs the downlink time to a plurality of second prediction models when reporting the channel state information report to the base station to obtain a plurality of downlink channel quality predicted values, so that the terminal can determine the downlink channel quality indication and the target codebook and report the downlink channel quality indication and the target codebook to the base station. Therefore, the base station can obtain more accurate channel quality according to the first prediction model, and the terminal can obtain more accurate channel quality according to the second prediction model, so that the base station can determine a better modulation and coding strategy to target the codebook, and the service capacity of the system is improved.
Description
Technical Field
The present invention relates to the field of wireless communications technologies, and in particular, to a communication control method, a base station, a terminal, and a storage medium.
Background
At present, the base station can provide reasonable modulation and coding strategy indication (Modulation and Coding Scheme, MCS) and precoding matrix indication (Precoding Matrix Indicator, PMI) for the terminal according to the channel quality so as to improve the service capacity of the wireless communication system. It can be appreciated that the key to improving traffic capacity is the channel quality acquired by the base station. In the related art, the base station can acquire channel quality according to the historical channel or the channel quality information reported by the terminal, but the channel quality acquired by the base station in the two modes is the channel quality at the past moment, so that the base station provides modulation and coding strategy indication and precoding matrix indication for the terminal according to the channel quality at the past moment, and certain errors exist, so that the service capacity of the system cannot be effectively improved.
Disclosure of Invention
The embodiment of the invention provides a communication control method, a base station, a terminal and a storage medium, aiming at obtaining more accurate channel quality to improve service capacity.
In a first aspect, an embodiment of the present invention provides a communication control method, including:
receiving a plurality of periodic channel sounding reference signals and a plurality of uplink channel measurement information sent by a terminal;
Measuring the plurality of periodic channel sounding reference signals according to a plurality of codebooks, and establishing an ARIMA model corresponding to each codebook;
adjusting each ARIMA model according to the uplink channel measurement information to obtain a first prediction model corresponding to each codebook;
when uplink authorization is carried out on the terminal, the uplink time of the terminal is input into each first prediction model to obtain an uplink channel quality predicted value corresponding to each codebook;
Determining a modulation and coding strategy of the terminal according to each uplink channel quality estimated value, and determining one of the codebooks as a target codebook;
and authorizing the terminal according to the modulation and coding strategy and the target codebook.
In a second aspect, an embodiment of the present invention further provides a communication control method, including:
receiving a plurality of periodic channel state information reference signals transmitted by a base station and a plurality of downlink channel measurement information;
Measuring the multiple periodic channel state information reference signals according to a plurality of codebooks, and establishing an ARIMA model corresponding to each codebook;
Adjusting each ARIMA model according to the plurality of downlink channel measurement information to obtain a second prediction model corresponding to each codebook;
when reporting a channel state information report to the base station, inputting the downlink time of the terminal into each second prediction mode to obtain a downlink channel quality predicted value corresponding to each codebook;
Determining a downlink channel quality indication of the terminal according to each downlink channel quality estimated value, and determining one of the codebooks as a target codebook;
and reporting the downlink signal quality indication and the target codebook to the base station.
In a third aspect, an embodiment of the present invention further provides a base station, including a processor and a memory; the memory is used for storing a computer program; the processor is configured to execute the computer program and implement the communication control method according to the first aspect when the computer program is executed.
In a fourth aspect, an embodiment of the present invention further provides a terminal, including a processor and a memory; the memory is used for storing a computer program; the processor is configured to execute the computer program and implement the communication control method according to the second aspect when the computer program is executed.
In a fifth aspect, embodiments of the present invention further provide a computer-readable storage medium storing a computer program, which when executed by a processor causes the processor to implement the communication control method according to the first aspect or the communication control method according to the second aspect.
The embodiment of the invention provides a communication control method, a base station, a terminal and a storage medium, wherein the method comprises the following steps: the base station can input the uplink time into a plurality of first prediction models when the base station performs uplink authorization for the terminal to obtain a plurality of uplink channel quality predicted values, so that the base station can determine a target codebook for a modulation and coding strategy for the terminal and authorize the terminal by using the target codebook. The method further comprises the steps of: the terminal inputs the downlink time to a plurality of second prediction models when reporting the channel state information report to the base station to obtain a plurality of downlink channel quality predicted values, so that the terminal can determine the downlink channel quality indication and the target codebook and report the downlink channel quality indication and the target codebook to the base station. Therefore, the base station can obtain more accurate channel quality according to the first prediction model, and the terminal can obtain more accurate channel quality according to the second prediction model, so that the base station can determine a better modulation and coding strategy to target the codebook, and the service capacity of the system is improved.
Drawings
FIG. 1 is a schematic view of an alternative application scenario according to various embodiments of the present invention;
FIG. 2 is a schematic flow chart of a method according to an embodiment of the invention;
FIG. 3 is a flowchart of step S120 in another embodiment of the present invention;
FIG. 4 is a schematic representation of a graph of prediction based on ARIMA model;
FIG. 5 is a flowchart of step S130 according to another embodiment of the present invention;
FIG. 6 is a flowchart of step S150 according to another embodiment of the present invention;
FIG. 7 is a schematic block diagram of a base station according to an embodiment of the present invention
Fig. 8 is a schematic block diagram of a structure of a terminal in an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The flow diagrams depicted in the figures are merely illustrative and not necessarily all of the elements and operations/steps are included or performed in the order described. For example, some operations/steps may be further divided, combined, or partially combined, so that the order of actual execution may be changed according to actual situations.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The method provided by the embodiment of the application can be applied to an application scene shown in fig. 1, and the method provided by the embodiment of the application can be applied to a terminal 10, such as a mobile terminal, wherein the mobile terminal can be an electronic device such as a mobile phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant, a wearable device and the like; in addition, the method provided by the embodiment of the application can also be applied to the base station 20. It should be noted that, the base station 20 may be connected with a plurality of terminals 10, that is, the base station 20 may schedule a plurality of terminals 10.
The communication control method provided by the embodiment of the invention can be used for a base station, as shown in fig. 2, and the method can include, but is not limited to, steps S110 to S160.
Step S110, a plurality of periodic channel sounding reference signals and a plurality of uplink channel measurement information transmitted by the terminal are received.
In some embodiments, the uplink reference signals may be divided into two classes, one class being demodulation reference signals, which may be transmitted simultaneously with the physical uplink shared channel (PHYSICAL SHARED CHANNEL, PUSCH) for demodulation of data; the other is a channel Sounding reference signal (Sounding REFERENCE SIGNAL, SRS), which is mainly used for channel quality estimation, and the channel Sounding reference signal can be divided into two types, one is a periodic channel Sounding reference signal and the other is an aperiodic channel Sounding reference signal. Based on this, the base station can receive the periodic channel sounding reference signal transmitted by the terminal for a set period of time L for establishing an ARIMA model (Autoregressive Integrated Moving Average model, differential integrated moving average autoregressive model). In addition, the base station may also receive a plurality of uplink channel measurement information, such as measurement information generated by the terminal measuring the physical uplink shared channel, for adjusting the established ARIMA model. In some embodiments, the set time length L may be configured according to different application scenarios. In some embodiments, the base station may first receive a plurality of periodic channel sounding reference signals to establish an ARIMA model, and then receive a plurality of uplink channel measurement information to adjust the established ARIMA model.
Step S120, measuring a plurality of periodic channel sounding reference signals according to a plurality of codebooks, and establishing an ARIMA model corresponding to each codebook.
In some embodiments, the base station receives the periodic channel sounding reference signal more advantageously for accumulation of data, i.e. the ARIMA model can be established in a shorter time, which makes the result predicted by the base station according to the first prediction model more accurate in the subsequent process. Based on the above, the base station may measure the sounding reference signal of each periodic channel according to a plurality of codebooks, and further establish a plurality of ARIMA models corresponding to each codebook, where the codebooks may be antenna precoding matrices that may be supported by the terminal during uplink transmission. For example, if the number of antenna precoding matrices that the terminal can support during uplink transmission is N, the base station may measure a plurality of periodic channel sounding reference signals according to N codebooks, thereby establishing N ARIMA models, where one codebook corresponds to one ARIMA model, and N is an integer greater than 1.
In some embodiments, as shown in fig. 3, step S120 may include, but is not limited to, sub-steps S121 and S122.
And step S121, measuring the channel sounding reference signals of each period according to a plurality of codebooks to obtain signal-to-interference-and-noise ratio time sequences corresponding to each codebook.
In some embodiments, for a periodic channel sounding reference signal, the base station may use several codebooks to measure the signal respectively, so that several signal-to-interference-and-noise-ratio values corresponding to the respective codebooks may be obtained, for example, the base station may use N codebooks to measure a periodic channel sounding reference signal respectively, so that N signal-to-interference-and-noise-ratio values may be obtained. It can be understood that, by measuring the sounding reference signal of multiple periodic channels by using several codebooks and placing multiple signal-to-interference-and-noise ratio values corresponding to the same codebook in the same sequence, multiple signal-to-interference-and-noise ratio time sequences can be obtained, i.e. one signal-to-interference-and-noise ratio time sequence corresponds to one codebook.
For example, assuming that the number of antenna precoding matrices that the terminal can support during uplink transmission is three, and the base station receives four periodic channel sounding reference signals sent by the terminal, the base station may measure the four signals according to three codebooks, respectively, so as to obtain four signal-to-interference-and-noise ratio time sequences, which are respectively a first signal-to-interference-and-noise ratio time sequence corresponding to the first codebook, such as {1_sinr1,1_sinr2,1_sinr3,1_sinr4}, a second signal-to-interference-and-noise ratio time sequence corresponding to the second codebook, such as {2_sinr1,2_sinr2,2_sinr3,2_sinr4}, and a third signal-to-interference-noise ratio time sequence corresponding to the third codebook, such as {3_sinr1,3_sinr2,3_sinr3,3_sinr4}.
In the substep S122, an ARIMA model corresponding to each signal-to-interference-and-noise ratio time sequence is established based on each signal-to-interference-and-noise ratio time sequence.
In some embodiments, the base station may establish a corresponding ARIMA model based on a signal-to-interference-and-noise ratio time sequence, and it is understood that an ARIMA model also corresponds to a codebook. Therefore, the base station can establish a plurality of corresponding ARIMA models according to a plurality of signal-to-interference-and-noise ratio time sequences. The modeling process is briefly described below using an ARIMA model built from a signal-to-interference-and-noise ratio time series.
1) And (5) smoothing the signal-to-interference-and-noise ratio time sequence. If the signal-to-interference-and-noise ratio time sequence is to be modeled, the time sequence needs to be stabilized, so that the data in the signal-to-interference-and-noise ratio time sequence can show a certain change trend. In some embodiments, if the signal-to-noise ratio time sequence itself is a smoother time sequence, then no smoothing is necessary; if the signal-to-noise ratio time sequence is not a stable time sequence, the stable processing is needed, and the path loss, the transmitting power, the frequency resource and the like can influence the signal-to-interference noise ratio value obtained by the base station according to the channel sounding reference signal of the codebook measurement period, so that the transmitting power of each frequency resource can be assumed to be known, the influence of the transmitting power and the frequency resource on the signal-to-interference noise ratio value can be stripped, and the stable processing can be carried out on the signal-to-interference noise ratio time sequence according to the path loss. Based on this, the signal-to-interference-and-noise ratio time series can be smoothed by the following formula,
Wherein SINR (t) represents a signal-to-interference-and-noise value at time t, P SRS represents a transmission power averaged to each frequency resource, C is a constant and its size can be determined according to different application scenarios, and d (t) represents a time sequence after performing a smoothing process. In some embodiments, the signal-to-noise ratio time sequence is processed within two times according to the above manner, so that a smoother signal-to-noise ratio time sequence can be obtained.
2) And determining and modeling model parameters. The ARIMA model may be denoted ARIMA (p, d, q), where p represents an autoregressive term, q represents a moving average term, and d represents the number of differences that the time series becomes a stationary time series. In some embodiments, three model parameters of the ARIMA model may be determined first, and the ARIMA model may be built, as briefly discussed below.
A) And (5) determining model parameters. In some embodiments, the magnitude of the parameter d depends on the number of treatments in step 1) described above, e.g. one treatment in step 1), d is equal to 1. In some implementations, the parameters p and q may be determined according to red-pool information criteria (Akaike Information Criterion, AIC) and bayesian information criteria (Bayesian Information Criterion, BIC). For example, a set of p and q values may determine a set of AIC and BIC values, and then traversing multiple sets of p and q values may obtain multiple sets of AIC and BIC values, so that a set of AIC and BIC values with the smallest values may be selected and a set of p and q values corresponding to the set of AIC and BIC values may be determined according to the set of AIC and BIC values, where the set of p and q values are the parameters p and q.
B) Modeling. The ARIMA model can be regarded as a differential ARMA model (Autoregressive moving average model ), the ARMA model can be denoted as ARMA (p, q), in other words, ARIMA (p, d, q) can be regarded as differential ARMA (p, q), and ARMA (p, q) can be regarded as the following formula
Wherein y t represents the value of the signal-to-interference-and-noise ratio time sequence at time t, mu is a constant, epsilon t represents the value of the white noise sequence with the mean value of 0 and the variance of sigma at time t, gamma i represents an autocorrelation coefficient, theta i represents a moving average parameter, and p and q are model parameters. While the ARMA model can be regarded as a degenerated AR model (Autoregressive model ) or MA model (moving average model, moving average model), where the AR model can be denoted as AR (p), and the AR (p) can be regarded as the following formula
Wherein y t represents the value of the signal-to-interference-and-noise ratio time sequence at the time t, mu 1 is a constant, gamma i represents an autocorrelation coefficient, and p is a model parameter; while the MA model may be denoted as MA (q), MA (q) may be regarded as the following formula
Wherein y t represents the value of the signal-to-interference-and-noise ratio time sequence at the time t, mu 2 is a constant, epsilon t represents the value of the white noise sequence with the mean value of 0 and the variance of sigma at the time t, theta i represents a moving average parameter, and q is a model parameter.
In some embodiments, modeling with an ARMA model, an AR model, or an MA model may be determined from the signal-to-interference-and-noise ratio time series. For example, it can be determined from an autocorrelation function (Autocorrelation Function, ACF) and a partial autocorrelation function (Partial Autocorrelation Function, PACF) of the signal-to-interference-and-noise ratio time series. If ACF tailing of the signal-to-interference-plus-noise ratio time sequence and PACF is p-order tail cutting, modeling by adopting an AR model, namely, fitting the signal-to-interference-plus-noise ratio time sequence by adopting AR (p); if the ACF of the signal-to-interference-and-noise ratio time sequence is q-order truncated and PACF is trailing, modeling by adopting an MA model, namely fitting the signal-to-interference-and-noise ratio time sequence by adopting MA (q); if the ACF of the snr time series is trailing and PACF is also trailing, modeling is performed by using an ARMA model, that is, fitting the snr time series by using ARMA (p, q). Based on this, an ARIMA model can be established based on the p-parameter, q-parameter and a number of signal-to-interference-plus-noise values in the signal-to-interference-plus-noise time sequence determined in step a) on the basis of determining which model to model.
Step S130, each ARIMA model is adjusted according to the uplink channel measurement information to obtain a first prediction model corresponding to each codebook.
Because the ARIMA model established in the step S120 is established according to the periodic channel sounding reference signal, the base station can only input the uplink moment of the terminal in the next period into the ARIMA model to obtain the corresponding uplink channel quality estimated value. For example, as shown in fig. 4, when the base station predicts the channel quality at the future time using the previously established ARIMA model, the base station can only obtain the channel quality at the future time t+t SRS, and in fact any time between the current time T and the future time t+t SRS may be the terminal uplink time. Therefore, in order to enable the base station to obtain the channel quality at any time in the future, so as to improve the accuracy of the channel quality obtained by the base station, a plurality of ARIMA models can be adjusted according to a plurality of uplink channel measurement information to obtain a plurality of first prediction models, and it can be understood that one first prediction model corresponds to one codebook.
In some embodiments, as shown in fig. 5, step S130 may include, but is not limited to, substeps S131 and S132.
Step S131, a plurality of adjustment parameters are determined according to the uplink channel measurement information, wherein the adjustment parameters comprise signal-to-interference-and-noise ratio values and codebooks corresponding to the signal-to-interference-and-noise ratio values.
Step S132, adjusting each ARIMA model according to a plurality of adjustment parameters to obtain each first prediction model.
In some embodiments, the base station may determine an adjustment parameter according to an uplink channel measurement information, where the adjustment parameter includes a signal-to-interference-and-noise ratio value and a codebook corresponding to the signal-to-interference-and-noise ratio value, so that an ARIMA model corresponding to the codebook may be determined according to the codebook, and the signal-to-interference-and-noise ratio value may be used to adjust the ARIMA model, and the adjustment may result in a first prediction model. It can be appreciated that a plurality of adjustment parameters can be determined according to a plurality of uplink channel measurement information, so as to adjust a plurality of ARIMA models, thereby obtaining a plurality of first prediction models.
In some embodiments, a lagrangian (Lagrange) interpolation method may be used to adjust several ARIMA models according to a plurality of adjustment parameters, and a brief description will be given below of an example of adjusting one ARIMA model by one adjustment parameter.
According to the codebook included in the adjustment parameter, an ARIMA model corresponding to the parameter can be determined, and the signal-to-interference-and-noise ratio time sequence used for establishing is assumed to be subjected to two-time smooth processing in the process of establishing the ARIMA model. Based on this, a periodic stationary time sequence may be generated according to the ARIMA model, which stationary time sequence may comprise values of at least one future instant. Then, the signal-to-interference-plus-noise value included in the adjustment parameter and the stationary time sequence are processed into the same dimension, for example, on one hand, the stationary time sequence is processed in a reverse way corresponding to the second stationary processing to obtain a time sequence d (t), and the d (t) includes a plurality of values, such as d (1) and d (2) … … d (n); on the other hand, the signal-to-interference-plus-noise value included in the adjustment parameter is smoothed for the first time, so that both are in the same dimension. At this time, since the time sequence d (t) may be regarded as a plurality of discrete points, and the signal-to-interference-and-noise value included in the adjustment parameter may be regarded as a known discrete point, a lagrangian interpolation method may be used to determine an interpolation function, where the interpolation function is a corresponding first prediction model.
Step S140, when the terminal is up-authorized, the up-time of the terminal is input into each first prediction model to obtain up-channel quality predicted values corresponding to each codebook.
In some embodiments, if the base station inputs the uplink time into a first prediction model, an uplink channel quality estimate may be obtained, and since a first prediction model corresponds to a codebook, an uplink channel quality estimate also corresponds to a codebook. Based on the above, since the first prediction model can estimate the channel quality value at the future time according to the future time, the base station can input the future uplink time of the terminal into each first prediction model to obtain a plurality of uplink channel quality predicted values corresponding to each codebook, and the channel quality values obtained by the base station are also more accurate.
Step S150, according to each uplink channel quality estimated value, determining the modulation and coding strategy of the terminal and determining one of a plurality of codebooks as a target codebook.
In some embodiments, since each uplink channel quality estimated value is relatively accurate, that is, the base station can obtain relatively accurate channel quality, the base station can determine a relatively optimal modulation and coding strategy and codebook for the terminal according to the uplink channel quality estimated values.
In some embodiments, as shown in fig. 6, step S150 may include, but is not limited to, sub-steps S151 and S152.
And step S151, determining the signal-to-interference-and-noise ratio value corresponding to each codebook according to each uplink channel quality estimated value.
Sub-step S152, determining the modulation and coding strategy of the terminal and determining one of several codebooks as the target codebook according to the magnitude relation of the signal-to-interference-plus-noise values.
In some embodiments, an up channel quality estimate is processed in a relatively smooth manner to obtain a signal-to-interference-and-noise value, and since an up channel quality estimate corresponds to a codebook, the signal-to-interference-and-noise value also corresponds to the codebook. Therefore, the same processing as described above is performed on each uplink channel quality estimate, and a plurality of sir values can be obtained.
In some embodiments, since the uplink channel quality estimated value is more accurate, the corresponding signal-to-interference-plus-noise ratio value is also more accurate, the base station may determine a better signal-to-interference-plus-noise ratio value according to the magnitude relation of the signal-to-interference-plus-noise ratio values, and further determine a codebook corresponding to the better signal-to-interference-plus-noise ratio value from the plurality of codebooks according to the signal-to-interference-plus-noise ratio value, and determine a modulation and coding strategy.
And step 160, authorizing the terminal according to the modulation and coding strategy and the target codebook.
In some embodiments, because the base station obtains relatively accurate channel quality and determines the modulation and coding strategy and the target codebook for the terminal, the base station can authorize the terminal according to the modulation and coding strategy and the target codebook, thereby effectively improving the service capacity of the system.
The embodiment of the invention also provides a communication control method which can be used for the terminal, and the method can comprise, but is not limited to, steps S210 to S260.
Step S210, a plurality of periodic channel state information reference signals and a plurality of downlink channel measurement information transmitted by the base station are received.
In some embodiments, the terminal may receive a periodic channel state Information reference signal (CHANNEL STATE Information REFERENCE SIGNAL, CSI-RS) transmitted by the base station for a set length of time L for establishing the ARIMA model. In addition, the terminal may also receive a plurality of downlink channel measurement information, such as measurement information generated by the base station measuring the physical downlink shared channel (Physical Downlink SHARED CHANNEL, PDSCH), for adjusting the established ARIMA model. In some embodiments, the set time length L may be configured according to different application scenarios. In some embodiments, the terminal may first receive a plurality of periodic channel state information reference signals to establish an ARIMA model, and then receive a plurality of downlink channel measurement information to adjust the established ARIMA model.
Step S220, according to a plurality of code books, measuring a plurality of periodic channel state information reference signals, and establishing an ARIMA model corresponding to each code book.
In some embodiments, the periodic channel state information reference signal is received by the terminal to be more beneficial to accumulation of data, i.e. the ARIMA model can be established in a shorter time, which makes the result predicted by the terminal according to the second prediction model more accurate in the subsequent process. Based on the above, the terminal may measure the channel state information reference signals of each period according to a plurality of codebooks, and further establish a plurality of ARIMA models corresponding to each codebook, where the codebooks may be antenna precoding matrices that the terminal may support during uplink transmission. For example, if the number of antenna precoding matrices that the terminal can support during uplink transmission is N, the terminal may measure a plurality of periodic channel state information reference signals according to N codebooks, thereby establishing N ARIMA models, where one codebook corresponds to one ARIMA model, and N is an integer greater than 1.
In some embodiments, step S220 may include, but is not limited to, sub-steps S221 and S222.
Step S221, measuring the channel state information reference signal of each period according to a plurality of codebooks, and obtaining the signal-to-interference-and-noise ratio time sequence corresponding to each codebook.
In some embodiments, for a periodic channel state information reference signal, the terminal may use several codebooks to measure the signal respectively, so as to obtain several signal-to-interference-and-noise-ratio values corresponding to the respective codebooks, for example, the terminal may use N codebooks to measure a periodic channel state information reference signal respectively, so as to obtain N signal-to-interference-and-noise-ratio values. It can be understood that, by measuring the reference signal of the channel state information in multiple periods by using several codebooks, and placing multiple signal-to-interference-and-noise ratio values corresponding to the same codebook in the same sequence, multiple signal-to-interference-and-noise ratio time sequences can be obtained, i.e. one signal-to-interference-and-noise ratio time sequence corresponds to one codebook.
In the substep S222, an ARIMA model corresponding to each signal-to-interference-and-noise ratio time sequence is established based on each signal-to-interference-and-noise ratio time sequence.
In some embodiments, the terminal may establish a corresponding ARIMA model according to a signal-to-interference-and-noise ratio time sequence, and it is understood that an ARIMA model also corresponds to a codebook. Therefore, the terminal can establish a plurality of corresponding ARIMA models according to a plurality of signal-to-interference-and-noise ratio time sequences, and the modeling process is similar to the above embodiment, and will not be repeated here.
Step S230, each ARIMA model is adjusted according to the plurality of downlink channel measurement information to obtain a second prediction model corresponding to each codebook.
Because the ARIMA model established in step S220 is established according to the periodic channel state information reference signal, the terminal can only input the terminal uplink time of the next period into the ARIMA model to obtain the corresponding downlink channel quality estimated value. Therefore, in order to enable the terminal to obtain the channel quality at any time in the future, so as to improve the accuracy of the channel quality obtained by the terminal, a plurality of ARIMA models can be adjusted according to a plurality of downlink channel measurement information to obtain a plurality of second prediction models, and it can be understood that one second prediction model corresponds to one codebook.
In some embodiments, step S230 may include, but is not limited to, sub-steps S231 and S232.
In step S231, a plurality of adjustment parameters are determined according to the plurality of downlink channel measurement information, where the adjustment parameters include a signal-to-interference-and-noise ratio value and a codebook corresponding to the signal-to-interference-and-noise ratio value.
Step S232, adjusting each ARIMA model according to the plurality of adjustment parameters to obtain each second prediction model.
In some embodiments, the terminal may determine an adjustment parameter according to a downlink channel measurement information, where the adjustment parameter includes a signal-to-interference-and-noise ratio value and a codebook corresponding to the signal-to-interference-and-noise ratio value, so that an ARIMA model corresponding to the codebook may be determined according to the codebook, and the signal-to-interference-and-noise ratio value may be used to adjust the ARIMA model, and a second prediction model may be obtained after the adjustment. Therefore, it can be understood that a plurality of adjustment parameters may be determined according to a plurality of downlink channel measurement information, so as to adjust a plurality of ARIMA models to obtain a plurality of second prediction models, and the adjustment process is similar to the above embodiment and will not be repeated here.
Step S240, when reporting the channel state information report to the base station, the downlink time of the terminal is input into each second prediction mode to obtain the downlink channel quality estimated value corresponding to each codebook.
In some embodiments, if the terminal inputs the downlink time into a second prediction model, a downlink channel quality estimated value may be obtained, and since a second prediction model corresponds to a codebook, a downlink channel quality estimated value also corresponds to a codebook. Based on the above, since the second prediction model can estimate the channel quality value at the moment according to the future moment, the terminal can input the future downlink moment of the terminal into each second prediction model to obtain a plurality of downlink channel quality predicted values corresponding to each codebook, and the channel quality values obtained by the terminal are also more accurate.
Step S250, determining the downlink channel quality indication of the terminal according to each downlink channel quality estimated value and determining one of a plurality of codebooks as a target codebook.
In some embodiments, since each downlink channel quality estimate is more accurate, i.e., the terminal can obtain more accurate channel quality, the terminal can determine a better downlink channel quality indicator (Channel Quality Indicator, CQI) and codebook according to the downlink channel quality estimates.
In some embodiments, step S250 may include, but is not limited to, sub-steps S251 and S252.
In sub-step S251, the signal-to-interference-and-noise ratio value corresponding to each codebook is determined according to each downlink channel quality estimate.
Sub-step S252, determining a downlink channel quality indication of the terminal and determining one of the several codebooks as a target codebook according to the magnitude relation of the signal-to-interference-plus-noise values.
In some embodiments, a signal-to-interference-and-noise value is obtained by performing a relatively smooth inverse of a downlink channel quality estimate, and since a downlink channel quality estimate corresponds to a codebook, the signal-to-interference-and-noise value also corresponds to the codebook. Therefore, the same processing is performed on each downlink channel quality predicted value as described above, and a plurality of signal-to-interference-and-noise-ratio values can be obtained.
In some embodiments, since the downlink channel quality estimated value is more accurate, the corresponding signal-to-interference-plus-noise ratio value is also more accurate, the terminal may determine a better signal-to-interference-plus-noise ratio value according to the magnitude relation of the signal-to-interference-plus-noise ratio values, and further determine a codebook corresponding to the signal-to-interference-plus-noise ratio value from the plurality of codebooks, and determine a downlink channel quality indication.
Step S260, reporting the downlink signal quality indication and the target codebook to the base station.
In some embodiments, since the terminal obtains relatively accurate channel quality and determines the downlink channel quality indication and the target codebook according to the relatively accurate channel quality, the terminal can report the two to the base station, so that the base station can determine a relatively optimal modulation and coding strategy and codebook for the terminal according to the two and authorize the terminal, thereby effectively improving the service capacity of the system.
The embodiment of the invention also provides a base station, as shown in fig. 7, comprising a processor and a memory, wherein the memory is used for storing a computer program; the processor is configured to execute a computer program and implement any one of the communication control methods for a base station provided by the embodiments of the present invention when the computer program is executed.
The embodiment of the invention also provides a terminal, as shown in fig. 8, comprising a processor and a memory, wherein the memory is used for storing a computer program; the processor is configured to execute a computer program and implement any one of the communication control methods for a terminal provided by the embodiments of the present invention when the computer program is executed.
It should be appreciated that the Processor may be a central processing unit (Central Processing Unit, CPU), it may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Embodiments of the present invention also provide a computer-readable storage medium storing a computer program that, when executed by a processor, causes the processor to implement any one of the communication control methods provided by the embodiments of the present invention.
Those of ordinary skill in the art will appreciate that all or some of the steps, systems, functional modules/units in the apparatus, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between the functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed cooperatively by several physical components. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer-readable storage media, which may include computer-readable storage media (or non-transitory media) and communication media (or transitory media).
The term computer-readable storage medium includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer-readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer-readable storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
The computer readable storage medium may be, for example, an internal storage unit of the base station or the terminal according to the foregoing embodiment, such as a hard disk or a memory of the base station or the terminal. The computer readable storage medium may also be an external storage device of the base station or the terminal, such as a plug-in hard disk provided on the base station or the terminal, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD), or the like.
While the invention has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (11)
1. A communication control method, characterized by comprising:
receiving a plurality of periodic channel sounding reference signals and a plurality of uplink channel measurement information sent by a terminal;
Measuring the plurality of periodic channel sounding reference signals according to a plurality of codebooks, and establishing an ARIMA model corresponding to each codebook;
adjusting each ARIMA model according to the uplink channel measurement information to obtain a first prediction model corresponding to each codebook;
when uplink authorization is carried out on the terminal, the uplink time of the terminal is input into each first prediction model to obtain an uplink channel quality predicted value corresponding to each codebook;
Determining a modulation and coding strategy of the terminal according to each uplink channel quality estimated value, and determining one of the codebooks as a target codebook;
and authorizing the terminal according to the modulation and coding strategy and the target codebook.
2. The method of claim 1, wherein said measuring the plurality of periodic channel sounding reference signals from a plurality of codebooks, creating an ARIMA model corresponding to each of the codebooks, comprises:
Measuring each periodic channel sounding reference signal according to the codebooks to obtain a signal-to-interference-and-noise ratio time sequence corresponding to each codebook;
And establishing an ARIMA model corresponding to each signal-to-interference-and-noise ratio time sequence based on each signal-to-interference-and-noise ratio time sequence.
3. The method of claim 1, wherein said adjusting each ARIMA model based on the plurality of uplink channel measurement information to obtain a first prediction model corresponding to each codebook comprises:
determining a plurality of adjustment parameters according to the plurality of uplink channel measurement information, wherein the adjustment parameters comprise signal-to-interference-and-noise ratio values and codebooks corresponding to the signal-to-interference-and-noise ratio values;
And adjusting each ARIMA model according to the plurality of adjustment parameters to obtain each first prediction model.
4. The method of claim 1 wherein said determining a modulation and coding strategy for said terminal based on each of said uplink channel quality estimates and determining one of said plurality of codebooks as a target codebook comprises:
Determining a signal-to-interference-and-noise value corresponding to each codebook according to each uplink channel quality estimated value;
and determining a modulation and coding strategy of the terminal according to the magnitude relation of each signal-to-interference-plus-noise value, and determining one of the codebooks as a target codebook.
5. A communication control method, characterized by comprising:
receiving a plurality of periodic channel state information reference signals transmitted by a base station and a plurality of downlink channel measurement information;
Measuring the multiple periodic channel state information reference signals according to a plurality of codebooks, and establishing an ARIMA model corresponding to each codebook;
Adjusting each ARIMA model according to the plurality of downlink channel measurement information to obtain a second prediction model corresponding to each codebook;
when reporting a channel state information report to the base station, inputting the downlink time of the terminal into each second prediction model to obtain a downlink channel quality estimated value corresponding to each codebook;
Determining a downlink channel quality indication of the terminal according to each downlink channel quality estimated value, and determining one of the codebooks as a target codebook;
and reporting the downlink channel quality indication and the target codebook to the base station.
6. The method of claim 5, wherein said measuring said plurality of periodic channel state information reference signals from a plurality of codebooks, creating an ARIMA model corresponding to each of said codebooks, comprises:
Measuring each periodic channel state information reference signal according to the codebooks to obtain a signal-to-interference-and-noise ratio time sequence corresponding to each codebook;
And establishing an ARIMA model corresponding to each signal-to-interference-and-noise ratio time sequence based on each signal-to-interference-and-noise ratio time sequence.
7. The method of claim 5, wherein adjusting each ARIMA model based on the plurality of downlink channel measurement information to obtain a second prediction model corresponding to each codebook comprises:
determining a plurality of adjustment parameters according to the downlink channel measurement information, wherein the adjustment parameters comprise signal-to-interference-and-noise ratio values and codebooks corresponding to the signal-to-interference-and-noise ratio values;
And adjusting each ARIMA model according to the plurality of adjustment parameters to obtain each second prediction model.
8. The method of claim 5 wherein said determining a downlink channel quality indication for said terminal based on each of said downlink channel quality estimates and determining one of said plurality of codebooks as a target codebook comprises:
Determining a signal-to-interference-and-noise value corresponding to each codebook according to each downlink channel quality predicted value;
and determining the downlink channel quality indication of the terminal and determining one of the codebooks as a target codebook according to the magnitude relation of the signal-to-interference-plus-noise values.
9. A base station comprising a processor and a memory;
The memory is used for storing a computer program;
The processor configured to execute the computer program and implement the communication control method according to any one of claims 1 to 4 when the computer program is executed.
10. A terminal comprising a processor and a memory;
The memory is used for storing a computer program;
The processor configured to execute the computer program and implement the communication control method according to any one of claims 5 to 8 when the computer program is executed.
11. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, causes the processor to implement the communication control method according to any one of claims 1 to 4 or the communication control method according to any one of claims 5 to 8.
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| CN114422007B (en) * | 2022-03-24 | 2022-07-01 | 新华三技术有限公司 | Uplink data modulation method and device |
| WO2023205928A1 (en) * | 2022-04-24 | 2023-11-02 | Qualcomm Incorporated | Predictive beam management mode switching |
| CN114866189B (en) * | 2022-05-06 | 2023-12-19 | 北京佰才邦技术股份有限公司 | Modulation and coding strategy MCS determination method and device |
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