Self-adaptive modulation and coding method and device for time-varying channel

Abstract

The invention provides an adaptive modulation coding method and device for a time-varying channel, and relates to the technical field of satellite internet. The method comprises the following steps: sending an analog OFDM signal to a receiving end; receiving the current state information of the time-varying channel fed back by the receiving end, and performing channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information; and querying a pre-constructed database according to the predicted channel state information, determining a first CQI level according to the queried targeted channel state information, and updating an MCS level required for generating the analog OFDM signal according to the first CQI level so as to realize adaptive modulation coding of the time-varying channel according to the updated MCS level. The device executes the method. According to the adaptive modulation and coding method and device for the time-varying channel provided by the embodiment of the invention, the timeliness and accuracy of predicting the channel state information are ensured.

Description

Technical Field

[0001] The present invention relates to the field of satellite Internet technology, and in particular to an adaptive modulation and coding method and device for a time-varying channel. Background Art

[0002] Adaptive modulation and coding (AMC) optimizes transmission efficiency and reliability by dynamically adjusting transmission parameters (such as modulation mode, coding rate, and power) to match channel conditions in real time. This improves transmission efficiency, ensures communication quality, and enhances system robustness.

[0003] The existing technology uses a GRU network to model historical channel states and uses a deep Q network algorithm to train and optimize the GRU network, ultimately outputting the optimal modulation and coding rate. However, the real-time changes of channel states are frequent and complex. The existing technology only outputs the optimal modulation and coding rate based on the model established based on the historical channel states, which cannot adapt to the frequent and complex real-time changes of channel states in time-varying channels, resulting in poor timeliness and accuracy of the adaptive modulation and coding method. Summary of the Invention

[0004] In response to the problems in the prior art, embodiments of the present invention provide a method and apparatus for adaptive modulation and coding of a time-varying channel, which can at least partially solve the problems in the prior art.

[0005] In one aspect, the present invention proposes an adaptive modulation and coding method for a time-varying channel applied to a transmitting end; the method comprises:

[0006] Send analog OFDM signal to the receiving end;

[0007] receiving current state information of the time-varying channel fed back by the receiving end, and performing channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information;

[0008] querying a pre-built database according to the predicted channel state information, determining a first CQI level according to the targeted channel state information obtained from the query, and updating an MCS level required for generating the simulated OFDM signal according to the first CQI level, so as to implement adaptive modulation and coding of the time-varying channel according to the updated MCS level;

[0009] The preset channel prediction model is optimized according to a first comparison result between a second CQI level fed back by the receiving end and the first CQI level.

[0010] The simulated OFDM signal is generated according to the MCS level and simulation parameter configuration information of the time-varying channel.

[0011] Wherein, constructing the database includes:

[0012] Obtain multiple discrete time-varying channel parameters, multiple channel models, and multiple MCS levels;

[0013] Combining the plurality of discrete time-varying channel parameters to obtain a plurality of channel parameter combinations;

[0014] Combining each group of the channel parameter combinations with the multiple channel models, and combining each of the channel models with the multiple MCS levels, to obtain simulation event information;

[0015] The simulation event information is simulated, and the database is constructed according to the simulation results.

[0016] The plurality of discrete time-varying channel parameters include at least a rainfall rate; accordingly, the adaptive modulation and coding method for the time-varying channel further includes:

[0017] The Weibull distribution is used as a distribution function to characterize the rainfall rate distribution, and the time-varying property of the time-varying channel is simulated according to the distribution function.

[0018] The multiple channel models include at least the NTN-TDL channel model; accordingly, the adaptive modulation and coding method for the time-varying channel further includes:

[0019] The NTN-TDL channel model is modeled and simulated based on the Rice sine sum method.

[0020] Optimizing the preset channel prediction model includes:

[0021] If it is determined that the first comparison result is different, retraining the preset channel prediction model;

[0022] If it is determined that the first comparison result is the same, continue to use the preset channel prediction model.

[0023] In one aspect, the present invention proposes an adaptive modulation and coding method for a time-varying channel applied to a receiving end; the method comprises:

[0024] receiving an analog OFDM signal sent by a transmitting end, and acquiring current state information of a time-varying channel according to the analog OFDM signal;

[0025] determining a transmission block error rate under a current signal-to-noise ratio according to the current state information, and adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level;

[0026] The second CQI level is sent to the transmitting end.

[0027] The adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold to obtain a second CQI level includes:

[0028] If it is determined that the transmission block error rate is less than the transmission block error rate threshold, the current CQI level is simulated to be gradually increased until the transmission block error rate corresponding to the increased CQI level is greater than or equal to the transmission block error rate threshold, and the second CQI level is determined according to the increased CQI level.

[0029] The determining the second CQI level according to the increased CQI level includes:

[0030] If it is determined that the difference between the increased CQI level and the current CQI level is greater than a preset number of levels, determining the difference between the increased CQI level and the preset number of levels as the second CQI level;

[0031] If it is determined that the difference between the increased CQI level and the current CQI level is less than or equal to a preset number of levels, the current CQI level is determined as the second CQI level.

[0032] The adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold to obtain a second CQI level includes:

[0033] If it is determined that the transmission block error rate is greater than or equal to the transmission block error rate threshold, the current CQI level is simulated to be gradually reduced until the reduced CQI level is less than the transmission block error rate threshold, and the second CQI level is determined according to the reduced CQI level.

[0034] The determining the second CQI level according to the reduced CQI level includes:

[0035] A CQI level one level lower than the decreased CQI level is determined as the second CQI level.

[0036] In one aspect, the present invention provides an adaptive modulation and coding device for a time-varying channel applied to a transmitting end; the device comprises:

[0037] A generating unit, configured to send an analog OFDM signal to a receiving end;

[0038] a prediction unit, configured to receive the current state information of the time-varying channel fed back by the receiving end, and perform channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information;

[0039] a modulation unit, configured to query a pre-constructed database according to the predicted channel state information, determine a first CQI level according to the targeted channel state information obtained from the query, and update the MCS level required for generating the simulated OFDM signal according to the first CQI level, so as to implement adaptive modulation and coding of the time-varying channel according to the updated MCS level;

[0040] The preset channel prediction model is optimized according to a first comparison result between a second CQI level fed back by the receiving end and the first CQI level.

[0041] In one aspect, the present invention provides an adaptive modulation and coding device for a time-varying channel applied to a receiving end; the device comprises:

[0042] an acquisition module, configured to receive an analog OFDM signal sent by a transmitting end, and acquire current state information of a time-varying channel according to the analog OFDM signal;

[0043] a determination module, configured to determine a transmission block error rate under a current signal-to-noise ratio according to the current state information, and adjust the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level;

[0044] A sending module is configured to send the second CQI level to the sending end.

[0045] In another aspect, an embodiment of the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following method is implemented:

[0046] Send analog OFDM signal to the receiving end;

[0047] receiving current state information of the time-varying channel fed back by the receiving end, and performing channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information;

[0048] querying a pre-built database according to the predicted channel state information, determining a first CQI level according to the targeted channel state information obtained from the query, and updating an MCS level required for generating the simulated OFDM signal according to the first CQI level, so as to implement adaptive modulation and coding of the time-varying channel according to the updated MCS level;

[0049] The preset channel prediction model is optimized based on a first comparison result between a second CQI level fed back by the receiving end and the first CQI level;

[0050] Alternatively, receiving an analog OFDM signal sent by a transmitting end, and acquiring current state information of a time-varying channel according to the analog OFDM signal;

[0051] determining a transmission block error rate under a current signal-to-noise ratio according to the current state information, and adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level;

[0052] The second CQI level is sent to the transmitting end.

[0053] An embodiment of the present invention provides a computer-readable storage medium, including:

[0054] The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following method is implemented:

[0055] Send analog OFDM signal to the receiving end;

[0056] receiving current state information of the time-varying channel fed back by the receiving end, and performing channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information;

[0057] querying a pre-built database according to the predicted channel state information, determining a first CQI level according to the targeted channel state information obtained from the query, and updating an MCS level required for generating the simulated OFDM signal according to the first CQI level, so as to implement adaptive modulation and coding of the time-varying channel according to the updated MCS level;

[0058] The preset channel prediction model is optimized based on a first comparison result between a second CQI level fed back by the receiving end and the first CQI level;

[0059] Alternatively, receiving an analog OFDM signal sent by a transmitting end, and acquiring current state information of a time-varying channel according to the analog OFDM signal;

[0060] determining a transmission block error rate under a current signal-to-noise ratio according to the current state information, and adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level;

[0061] The second CQI level is sent to the transmitting end.

[0062] An embodiment of the present invention further provides a computer program product, comprising a computer program. When the computer program is executed by a processor, the computer program implements the following method:

[0063] Send analog OFDM signal to the receiving end;

[0064] receiving current state information of the time-varying channel fed back by the receiving end, and performing channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information;

[0065] querying a pre-built database according to the predicted channel state information, determining a first CQI level according to the targeted channel state information obtained from the query, and updating an MCS level required for generating the simulated OFDM signal according to the first CQI level, so as to implement adaptive modulation and coding of the time-varying channel according to the updated MCS level;

[0066] The preset channel prediction model is optimized based on a first comparison result between a second CQI level fed back by the receiving end and the first CQI level;

[0067] Alternatively, receiving an analog OFDM signal sent by a transmitting end, and acquiring current state information of a time-varying channel according to the analog OFDM signal;

[0068] determining a transmission block error rate under a current signal-to-noise ratio according to the current state information, and adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level;

[0069] The second CQI level is sent to the transmitting end.

[0070] The adaptive modulation and coding method and device for a time-varying channel provided in an embodiment of the present invention sends an analog OFDM signal to a receiving end; receives current state information of the time-varying channel fed back by the receiving end, and performs channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information; queries a pre-constructed database based on the predicted channel state information, determines a first CQI level based on the targeted channel state information obtained by the query, and updates and generates the MCS level required for the analog OFDM signal based on the first CQI level, so as to realize adaptive modulation and coding of the time-varying channel according to the updated MCS level; wherein the preset channel prediction model is optimized based on a first comparison result between a second CQI level fed back by the receiving end and the first CQI level, and the predicted channel state information is obtained based on the current state information through the preset channel prediction model, thereby ensuring the timeliness and accuracy of the predicted channel state information; in addition, the second CQI level is compared with the first CQI level, and the preset channel prediction model is optimized accordingly, thereby further ensuring the accuracy of the predicted channel state information.

[0071] The adaptive modulation and coding method and apparatus for a time-varying channel provided by an embodiment of the present invention receive an analog OFDM signal sent by a transmitting end, obtain current state information of the time-varying channel based on the analog OFDM signal; determine a transmission block error rate under a current signal-to-noise ratio based on the current state information, and adjust the current CQI level based on a second comparison result between the transmission block error rate under the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level; send the second CQI level to the transmitting end, and determine the second CQI level by considering the margin between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold, thereby further overcoming spurious interference of random channels and ensuring correct and effective communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0073] Figure 1 It is a flowchart of an adaptive modulation and coding method for a time-varying channel provided by one embodiment of the present invention.

[0074] Figure 2 It is a schematic diagram illustrating the structure of the NTN-TDL channel model provided by an embodiment of the present invention.

[0075] Figure 3 This is a schematic diagram of the Rice sine sum simulation principle provided by an embodiment of the present invention.

[0076] Figure 4 Schematic diagram illustrating a simulation result database provided by an embodiment of the present invention.

[0077] Figure 5 Schematic diagram illustrating the Box-Jenkins modeling method provided by an embodiment of the present invention.

[0078] Figure 6 3 is a schematic diagram illustrating an absolute error curve between predicted CSI and actual CSI provided by an embodiment of the present invention.

[0079] Figure 7 It is a flowchart of an adaptive modulation and coding method for a time-varying channel provided by another embodiment of the present invention.

[0080] Figure 8 This is a schematic diagram illustrating determining the second CQI level provided by an embodiment of the present invention.

[0081] Figure 9This is a schematic diagram illustrating determining a second CQI level according to another embodiment of the present invention.

[0082] Figure 10 It is a signaling interaction diagram of the adaptive modulation and coding method for a time-varying channel provided by an embodiment of the present invention.

[0083] Figure 11 It is a structural diagram of an adaptive modulation and coding device for a time-varying channel provided by one embodiment of the present invention.

[0084] Figure 12 It is a structural diagram of an adaptive modulation and coding device for a time-varying channel provided by another embodiment of the present invention.

[0085] Figure 13 A schematic diagram of the physical structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0086] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention. It should be noted that, unless there is a conflict, the embodiments and features in the embodiments of this application can be combined with each other in any manner.

[0087] Figure 1 FIG. 1 is a flow chart of an adaptive modulation and coding method for a time-varying channel provided by an embodiment of the present invention. Figure 1 As shown, the adaptive modulation and coding method for a time-varying channel provided in an embodiment of the present invention is applied to a transmitting end; the method includes:

[0088] Step S1: Send an analog OFDM signal to a receiving end.

[0089] Step S2: receiving the current state information of the time-varying channel fed back by the receiving end, and performing channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information.

[0090] Step S3: querying a pre-built database based on the predicted channel state information, determining a first CQI level based on the targeted channel state information obtained from the query, and updating the MCS level required for generating the simulated OFDM signal based on the first CQI level, so as to implement adaptive modulation and coding for the time-varying channel based on the updated MCS level;

[0091] The preset channel prediction model is optimized according to a first comparison result between the second CQI level and the first CQI level fed back by the receiving end.

[0092] In step S1 above, the device sends an analog OFDM signal to the receiving end. The device can be a computer device that executes the method, for example, a transmitting end. The acquisition, storage, use, and processing of data in the technical solution of this application comply with relevant regulations. The method of the present invention requires the use of a pre-built database, and the construction of the database includes:

[0093] Obtain multiple discrete time-varying channel parameters, multiple channel models, and multiple MCS levels. In order to fully simulate the rapid time-varying characteristics of the time-varying channel, it is necessary to obtain multiple discrete time-varying channel parameters and model large-scale attenuation types with rapid time-varying characteristics, including cloud attenuation and rainfall attenuation, to simulate the time-varying channel with high fidelity.

[0094] The plurality of discrete time-varying channel parameters include at least a rainfall rate; accordingly, the adaptive modulation and coding method for the time-varying channel further includes:

[0095] The Weibull distribution is used as the distribution function to characterize the rainfall rate distribution, and the time-varying property of the time-varying channel is simulated based on the distribution function.

[0096] Rainfall attenuation in large-scale attenuation is highly time-varying. The absorption and scattering of raindrops in a rainy environment will cause millimeter wave signal attenuation. Under conditions of unpredictable weather, high rainfall frequency, heavy rainfall, and frequent changes in air humidity, the channel quality will fluctuate. Based on recent rainfall rate observation data, the Weibull distribution, which can still accurately characterize the rainfall rate distribution under heavy rainfall conditions, is used as the distribution function. , which can be expressed as:

[0097] ;

[0098] Where r is the raindrop radius, b is the raindrop shape parameter and b>0, and λ is the distribution scale parameter and λ>0. Rainfall attenuation and related parameters such as rainfall rate are linearly related, so rainfall attenuation also follows a Weibull distribution. Since path loss is only related to transmission distance and signal frequency, path loss is a constant for this variable, and channel attenuation also follows a Weibull distribution.

[0099] In a real channel environment, channel parameters such as rainfall rate and air humidity vary continuously. Due to limited simulation computing power, continuously varying parameters such as rainfall rate and air humidity are sampled using appropriate sampling intervals, discretizing them into a finite sequence. This accurately characterizes the overall patterns of these channel parameters. Therefore, in channel simulation, multiple discrete sets of simulation parameters such as rainfall rate and air humidity that follow the overall patterns of real channel variations are added to simulate the time-varying nature of the real channel.

[0100] The multiple channel models include at least an NTN-TDL channel model; accordingly, the adaptive modulation and coding method for a time-varying channel also includes:

[0101] The NTN-TDL channel model is modeled and simulated using the Rice sine sum method. Satellite-to-ground communications based on 5G standards are a key step in building non-terrestrial networks (NTNs). Tapped delay lines (TDLs) simulate the multipath propagation characteristics of signals by combining taps with different delays.

[0102] For satellite communications, there will be a direct LOS path and an indirect NLOS path at the receiving end. The proportion of direct and indirect paths varies in different channel environments. The power and delay characteristics of the NTN-TDL channel are characterized and modeled. Line of sight (LOS) refers to the straight-line path along which wireless signals propagate between the transmitter and receiver.

[0103] When the receiving end is in a complex urban environment, multipath effects are a major cause of channel time-varying properties. Based on the presence of a direct path and the number of multipath paths at the receiving end, channel models are categorized into four types: NTN-TDL-A, NTN-TDL-B, NTN-TDL-C, and NTN-TDL-D. NTN-TDL-A and NTN-TDL-B are channel models for two different NLOS scenarios, with scenario B featuring more multipath paths. NTN-TDL-C and NTN-TDL-D are channel models for two LOS scenarios, with scenario D featuring even more multipath paths.

[0104] like Figure 2 As shown, the NTN-TDL channel model can be equivalent to an FIR filter. Each tap of the FIR filter is time-varying, and the tap coefficients (g0(t)…g n (t)) obeys Rayleigh or Rice distribution, n represents the order of the filter, and the input signal is delayed ( ) and then multiplied by the tap coefficient and then accumulated and output. Since g0(t) corresponds to the LOS direct path, g1(t)…g n (t) corresponds to the NLOS non-direct path, so g0(t) needs to obey the Rice distribution, and g1(t)…g n (t) obeys the Rayleigh distribution.

[0105] For each tap's Rayleigh or Rice distribution, Rice's sine method is used for modeling and simulation. The principle of Rice's sine and simulation is as follows: Figure 3 shown.

[0106] where μ1(nTs) and μ2(nTs) are colored Gaussian random processes simulated by the sine sum method, ci,n is the amplitude of the n-th sine wave, θi,n is the phase of the n-th sine wave, and they obey a uniform distribution between (0, 2π] and are independent of each other. fi,n is the frequency of the n-th sine wave.

[0107] ;

[0108] From the above formula, we can see that using the Rice sine sum method to simulate the Rayleigh distribution requires determining three parameters: fi,n, ci,n and θi,n.

[0109] Determine the parameters using the MEDS method:

[0110] ;

[0111] ;

[0112] Where fmax is the maximum Doppler frequency deviation and Ni is the number of superimposed sine waves.

[0113] Therefore, simulation of the NTN-TDL model requires the following parameters: PDP (power delay profile), Doppler spread, Rice's K factor, and the number of superimposed sine waves at each tap using the Rice sine sum method. PDP, Doppler spread, and Rice's K factor are obtained through channel measurement and parameter fitting, and the number of sine waves is fixed at 48.

[0114] Combining multiple discrete time-varying channel parameters to obtain multiple sets of channel parameter combinations; Figure 4 As shown, the multiple discrete time-varying channel parameters may include polarization tilt, temperature, air humidity, atmospheric pressure, rainfall rate, water vapor density, rainfall height, etc. The multiple discrete time-varying channel parameters may be combined in a full permutation manner.

[0115] Each channel parameter combination is combined with multiple channel models, and each channel model is combined with multiple MCS levels to obtain simulation event information; each channel parameter combination can be combined with multiple channel models in a full permutation manner. Each channel model can be combined with multiple MCS levels in a full permutation manner.

[0116] The simulation event information is simulated, and a database is constructed based on the simulation results. The simulation event information can be input into an existing simulation software tool, and the simulation results can be output through the existing simulation software tool.

[0117] The constructed database can at least include a mapping between the block error rate (BLER) and signal-to-noise ratio (SNR) corresponding to different CQI levels. For example, when the SNR is 15dB, the database can be queried to determine that the highest CQI that meets the BLER ≤ 10% is 12. The channel quality indicator (CQI) represents the current channel quality and corresponds to the channel's signal-to-noise ratio (SNR). Its value range is 0 to 31. A CQI value of 0 indicates the worst channel quality, while a CQI value of 31 indicates the best channel quality. Common values ​​range from 12 to 24.

[0118] Taking the downlink channel PDSCH as an example, it is necessary to pre-simulate the mapping curves of BLER and SNR under different channel parameters such as rainfall rate and air humidity, different channel models, and different modulation and coding rates. The simulation output results will serve as the supporting database for the adaptive modulation and coding scheme.

[0119] To ensure the completeness of the database, the simulation items must also ensure completeness. The time-varying channel parameters include polarization tilt, air density, rainfall rate, rainfall height, temperature, atmospheric pressure, water vapor density, etc. According to a reasonable sampling interval, they are discretized into a finite sequence that can correctly represent the overall law of the data. The discrete values ​​of different channel parameters are combined to represent the environmental information of different real channels.

[0120] The simulation conditions themselves do not have the time-varying characteristics of real channel conditions. All channel state changes under a certain real channel condition are based on a database containing multiple groups of channel parameters. During the simulation process, channel parameters are called one by one from the database to simulate the changing pattern of the real channel.

[0121] A simulated OFDM signal is generated based on the MCS level and the simulation parameter configuration for the time-varying channel. The modulation and coding scheme (MCS) is a parameter used to describe the quality and performance of wireless links in wireless communication systems. It is defined by the combination of modulation method and coding efficiency, reflecting the efficiency and reliability of data transmission.

[0122] The MCS level can be determined based on the CQI level. For example, if CQI=7 corresponds to 16QAM, the MCS level should fall within the 16QAM index range of 10-16. In this case, Quadrature Amplitude Modulation (QAM) can be used to determine the CQI level. Similarly, the MCS level can be determined based on the CQI level.

[0123] Orthogonal Frequency Division Multiplexing (OFDM) is actually a type of multi-carrier modulation (MCM). It uses frequency division multiplexing to achieve parallel transmission of high-speed serial data, offering robustness against multipath fading and supporting multi-user access.

[0124] The generation of a simulated OFDM signal is described as follows:

[0125] 1. The MAC layer at the transmitting end generates a transport block (TB), which contains data, system information, or paging information to be sent to one or more receiving ends. A cyclic redundancy check (CRC) is calculated for the entire transport block, and the calculated CRC bits are appended to the end of the TB. If the length of the bit sequence after the CRC is appended exceeds the maximum input block size supported by the channel encoder, it is necessary to split it into multiple smaller code blocks, and a CRC is calculated and appended to each of the split code blocks.

[0126] 2. Channel coding is performed on the code blocks with CRC attached, adding redundant bits to improve resistance to channel errors. Channel coding outputs a coded bit stream with a fixed code rate. Rate matching determines the actual number of coded bits to be sent based on the physical resources allocated by the current scheduler (number of allocated PRBs, modulation order, number of transmission layers, etc.) and the current HARQ process status (initial transmission or retransmission). If the transport block is divided into multiple code blocks, after rate matching, the output bit streams of all code blocks after rate matching need to be concatenated in sequence to form a long coded bit sequence. Hybrid Automatic Repeat Request (HARQ) is a technology that combines forward error correction (FEC) and automatic repeat request (ARQ).

[0127] 3. The concatenated coded bit sequence is subjected to a bit-by-bit modulo-2 addition operation with a cell-specific and receiver-specific pseudo-random sequence. Scrambling makes the signals from adjacent cells or receivers look like random noise, reducing co-channel interference. The scrambled bit sequence is mapped to complex symbols according to the specified modulation scheme. Layer mapping maps the modulated symbol sequence to one or more transmission layers. Precoding maps the symbols on each transmission layer to antenna ports. The symbol sequence on each antenna port after precoding is mapped to a virtual resource block. The virtual resource block is then mapped to the actual physical resource block. Finally, the complex symbols on each antenna port, allocated to a specific physical resource block, are accurately mapped to the resource elements within that physical resource block.

[0128] 4. Each antenna port generates a two-dimensional time-frequency resource grid. Each point on the grid is either empty or carries the modulation symbol, reference signal, or other channel / signal symbol of the antenna port. Each column of the resource grid for each antenna port undergoes an inverse fast Fourier transform to convert the frequency domain complex symbol sequence into a time domain complex value sequence. A portion of the sampling points at the end of the inverse fast Fourier transform output sequence is copied and added to the beginning of the sequence. The length of the cyclic prefix needs to be greater than the maximum delay spread of the channel. The digital time domain complex value sequence is converted into an analog signal. After up-conversion, power amplification and other RF processing, an analog OFDM signal is generated and sent to the receiver through the antenna RF port.

[0129] In step S2, the apparatus receives the current state information of the time-varying channel fed back by the receiving end and performs channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information. The preset channel prediction model can be obtained by training an autoregressive integrated moving average model (ARIMA).

[0130] The channel state information at the current moment is predicted based on historical channel state information. ARIMA predicts the value at the current moment k using the values ​​of several items in the time series preceding the current moment k and the random error. ARIMA models have three orders: p, d, and q, often written as ARIMA(p,d,q). Here, p represents the order of the autoregressive model, d represents the order of differencing, and q represents the order of the moving average model.

[0131] ARIMA modeling is implemented using the Box-Jenkins method, which has three stages: identification, evaluation and testing, and application. Figure 5 The specific instructions are as follows:

[0132] (1) Identification:

[0133] The first stage includes data preparation and model selection. Data preparation transforms the CSI time series data into a stationary series. Model selection implies that some order selection method is needed to identify potential models.

[0134] If the channel state information time series, that is, the CSI time series, is non-stationary, it is necessary to perform differential calculation to make the CSI time series stationary before performing time series model fitting. The mathematical expression of the d-order difference is as follows:

[0135] ;

[0136] in, To calculate the sequence after stabilization, B is the lag factor, r k is the time series of outdated channel state information.

[0137] There are many methods to determine the p and q orders in the model. Generally, the tailing and truncation properties of the autocorrelation function and partial autocorrelation function of the CSI time series after stationary processing are calculated, or the parameters p and q of the ARIMA model are determined by minimizing the amount of information.

[0138] (2) Evaluation and testing:

[0139] The second stage estimates the potential model parameters and selects the best model using appropriate criteria. The order p and q of the ACF / PACF method are determined based on the rules in Table 1:

[0140] Table 1

[0141]

[0142] While using tailing and truncation to determine the order of a model is relatively simple, this method is often highly subjective. The AIC algorithm can address the problem of overfitting in prediction algorithms. This criterion balances model complexity with the model's ability to fit the dataset. The mathematical expression for AIC is:

[0143] ;

[0144] Where a represents the number of model parameters, and L represents the likelihood function corresponding to the predicted CSI.

[0145] For the above formula, the order corresponding to the minimum AIC result is selected. The maximum likelihood value can improve the model's ability to fit the CSI dataset. Configuring the number of model parameters introduces a complexity penalty term. These settings can effectively reduce the probability of overfitting.

[0146] After selecting the best model, a mixed test of the ACF / PACF residuals of the CSI time series is required. If white noise exists in the residual data, the third stage can be performed.

[0147] (3) Application:

[0148] The optimal model parameters p and q are determined in the second step, and the obtained model is used to predict CSI. , we can directly use ARIMA(p,d,q) to fit the model, which is equivalent to the difference order d=0. In this case, the model is expressed as ARIMA(p,0,q). The mathematical formula of the ARIMA(p,0,q) model is as follows:

[0149] ;

[0150] in, is the CSI time series after stabilization, and the parameters (λ1…λ p ) is the autoregressive coefficient, (θ1…θ q ) is the sliding average coefficient, represents a white noise sequence.

[0151] The CSI for each transmission time interval (TTI) is calculated in the software simulation platform and used as the input time series for the channel state prediction algorithm. The TTI is set to 10ms based on the delay of the low-orbit satellite. The simulation parameters of the ARIMA-based channel state prediction algorithm are shown in Table 2:

[0152] Table 2

[0153]

[0154] The algorithm's training set is a fixed-length (1000 TTIs) channel state information (CSI) time series that contains complete information about all simulation events. The transmitter generates random binary data and sequentially processes the signal using all modulation and coding methods involved in the present invention. The channel simulation conditions involve all channel parameter combinations in the simulation events to ensure the completeness of the training set. The receiver uses channel estimation to obtain CSI and collects CSI time series of fixed time length as the training set for the prediction algorithm. The present invention predicts the CSI after the next 100 transmission delay intervals, and each CSI prediction is based on the CSI of the previous 1000 transmission delay intervals.

[0155] The root mean square error (RMSE), mean absolute error (MAE) and correlation coefficient (Pearson) are used to measure the prediction effect of the algorithm. The mathematical expressions are as follows:

[0156] ;

[0157] ;

[0158] ;

[0159] in, represents the real CSI, represents the predicted CSI, m represents the size of the prediction set, express The mean of express The mean of express The standard deviation of express The standard deviation of .

[0160] The performance indicators of the simulated ARIMA prediction method are: RMSE is 0.224, MAE is 0.182, and Pearson is 0.327. The absolute error between the predicted CSI value and the actual CSI value is as follows: Figure 6 As shown:

[0161] From the simulation results, it can be seen that as time goes by, when the data fluctuation is small, the signal prediction error under the ARIMA algorithm becomes smaller and smaller, and the curve approaches 0. This shows the effectiveness of the ARIMA channel prediction algorithm.

[0162] During the simulation, adaptive modulation and coding is performed based on the ARIMA channel prediction results at the current transmit signal-to-noise ratio (SNR). Taking the downlink PDSCH channel as an example, the overall simulation process is mainly divided into the transmitter, channel, and receiver. The transmitter completes the data generation, modulation, and encoding processes. The receiver receives the signal after channel processing and completes demodulation and decoding to restore the original data. During the simulation, the channel parameter combinations of all simulation items are called one by one to simulate the changing patterns of the real channel environment.

[0163] In the above step S3, the apparatus queries a pre-built database based on the predicted channel state information, determines a first CQI level based on the targeted channel state information obtained from the query, and updates the MCS level required for generating the simulated OFDM signal based on the first CQI level, so as to implement adaptive modulation and coding of the time-varying channel based on the updated MCS level;

[0164] The preset channel prediction model is optimized according to a first comparison result between the second CQI level and the first CQI level fed back by the receiving end.

[0165] The database is queried based on the predicted channel state information to obtain the targeted channel state information. The similarity between the predicted channel state information and the preset channel state information stored in the database can be calculated, and the preset channel state information with the largest similarity result is determined as the targeted channel state information.

[0166] An SNR corresponding to the targeted channel state information may be determined, and then a first CQI level corresponding to the SNR may be determined according to a mapping relationship stored in a database. The mapping relationship includes a mapping relationship between a preset SNR and a preset CQI level.

[0167] Different MCS levels correspond to different modulation and coding schemes. For example, MCS level 1 corresponds to a coding rate of 157 / 1024 and a modulation scheme of BPSK; MCS level 2 corresponds to a coding rate of 193 / 1024 and a modulation scheme of BPSK. Channel coding adds redundant bits according to the given coding rate, and modulation generates complex symbols according to the given modulation scheme.

[0168] Optimize the preset channel prediction model, including:

[0169] If it is determined that the first comparison result is different, the preset channel prediction model is retrained; when the two CQI levels are different, it means that when training the ARIMA channel prediction model, the channel state information of the continuously changing channel is incomplete in the database, and it is necessary to add the channel state information obtained by channel estimation under the current simulation conditions to the database, and use the data in the database to retrain the model offline.

[0170] If the first comparison result is determined to be the same, the preset channel prediction model is continued to be used. When the two CQI levels are the same, it means that when training the ARIMA channel prediction model, the channel state information of the continuously changing channel is complete in the database, and the model can continue to be used for channel prediction.

[0171] Since the second COI level is the CQI level recommended by the receiving end based on the current simulation conditions, it is compared with the first CQI level obtained by data matching at the transmitting end, and the preset channel prediction model is optimized accordingly, further ensuring the accuracy of the predicted channel state information.

[0172] An adaptive modulation and coding method for a time-varying channel provided in an embodiment of the present invention sends an analog OFDM signal to a receiving end; receives current state information of the time-varying channel fed back by the receiving end, and performs channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information; queries a pre-constructed database based on the predicted channel state information, determines a first CQI level based on the targeted channel state information obtained by the query, and updates the generated MCS level required for the analog OFDM signal based on the first CQI level, so as to realize adaptive modulation and coding of the time-varying channel according to the updated MCS level; wherein the preset channel prediction model is optimized based on a first comparison result between a second CQI level and the first CQI level fed back by the receiving end, and the predicted channel state information is obtained based on the current state information through the preset channel prediction model, thereby ensuring the timeliness and accuracy of the predicted channel state information; in addition, the second CQI level is compared with the first CQI level, and the preset channel prediction model is optimized accordingly, thereby further ensuring the accuracy of the predicted channel state information.

[0173] In the above optional embodiment, the simulated OFDM signal is generated according to the MCS level and the simulation parameter configuration information of the time-varying channel.

[0174] The adaptive modulation and coding method for a time-varying channel provided by the embodiment of the present invention can truly simulate the actual time-varying characteristics of the channel according to the simulation parameter configuration information, thereby facilitating the generation of a high-fidelity simulated OFDM signal.

[0175] In the above optional embodiment, building a database includes:

[0176] Acquire multiple discrete time-varying channel parameters, multiple channel models, and multiple MCS levels; refer to the above embodiment for description and no further details will be given.

[0177] A plurality of discrete time-varying channel parameters are combined to obtain a plurality of channel parameter combinations; the description can be made with reference to the above embodiment and will not be repeated here.

[0178] Each channel parameter combination is combined with a plurality of channel models, and each channel model is combined with a plurality of MCS levels to obtain simulation event information. The above description can be referred to and will not be repeated here.

[0179] The simulation event information is simulated, and a database is constructed based on the simulation results.

[0180] The adaptive modulation and coding method for a time-varying channel provided by the embodiment of the present invention ensures that the database covers the complete simulation event information as fully as possible, thereby ensuring the adequacy of the data source provided for the model.

[0181] In the above optional embodiment, the multiple discrete time-varying channel parameters include at least a rainfall rate; accordingly, the adaptive modulation and coding method for a time-varying channel further includes:

[0182] The Weibull distribution is used as the distribution function to characterize the rainfall rate distribution, and the time-varying property of the time-varying channel is simulated according to the distribution function.

[0183] The adaptive modulation and coding method for a time-varying channel provided by the embodiment of the present invention can truly simulate the time-varying nature of the time-varying channel.

[0184] In the above optional embodiment, the multiple channel models include at least the NTN-TDL channel model; accordingly, the adaptive modulation and coding method for the time-varying channel further includes:

[0185] The NTN-TDL channel model is modeled and simulated based on the Rice sine sum method. The above description can be referred to in detail.

[0186] The adaptive modulation and coding method for a time-varying channel provided by the embodiment of the present invention can optimize simulation efficiency and computational complexity.

[0187] In the above optional embodiment, optimizing the preset channel prediction model includes:

[0188] If it is determined that the first comparison result is different, the preset channel prediction model is retrained; the above description can be referred to and will not be repeated here.

[0189] If the first comparison result is determined to be the same, the preset channel prediction model is continued to be used.

[0190] The adaptive modulation and coding method for a time-varying channel provided by the embodiment of the present invention can further optimize a preset channel prediction model.

[0191] Figure 7 FIG. 1 is a flow chart of an adaptive modulation and coding method for a time-varying channel provided by an embodiment of the present invention. Figure 7 As shown, the adaptive modulation and coding method for a time-varying channel provided by an embodiment of the present invention is applied to a receiving end; the method includes:

[0192] Step R1: Receive an analog OFDM signal sent by a transmitting end, and obtain current state information of a time-varying channel according to the analog OFDM signal.

[0193] Step R2: Determine the transmission block error rate under the current signal-to-noise ratio according to the current state information, and adjust the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold to obtain a second CQI level.

[0194] Step R3: Send the second CQI level to the transmitting end.

[0195] In step R1 above, the device receives an analog OFDM signal sent by a transmitter and obtains current state information of a time-varying channel based on the analog OFDM signal. The device may be a computer device that executes the method, such as a receiving end. The acquisition, storage, use, and processing of data in the technical solution of this application comply with relevant regulations. Obtaining current state information of a time-varying channel based on the analog OFDM signal includes:

[0196] Performing waveform demodulation on the analog OFDM signal to obtain a waveform-demodulated signal;

[0197] Perform channel estimation on the waveform-demodulated signal to obtain current state information.

[0198] In step R2 above, the apparatus determines a transmission block error rate (BER) at a current signal-to-noise ratio (SNR) based on the current state information, and adjusts the current CQI level based on a second comparison result between the BER rate at the current SNR and a BER threshold, thereby obtaining a second CQI level. The BER threshold can be set independently based on actual conditions and may be set to 0.1.

[0199] Determining a transmission block error rate at a current signal-to-noise ratio based on current state information includes:

[0200] Demodulate and decode the current status information to obtain the number of time slots with transmission errors;

[0201] The transmission block error rate under the current signal-to-noise ratio is calculated based on the number of time slots with transmission errors.

[0202] Adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold to obtain a second CQI level includes:

[0203] If it is determined that the transmission block error rate is less than the transmission block error rate threshold, the current CQI level is simulated to be gradually increased until the transmission block error rate corresponding to the increased CQI level is greater than or equal to the transmission block error rate threshold, and the second CQI level is determined based on the increased CQI level.

[0204] Determining a second CQI level according to the increased CQI level includes:

[0205] If it is determined that the difference between the increased CQI level and the current CQI level is greater than the preset number of levels, the difference between the increased CQI level and the preset number of levels is determined as the second CQI level; the preset number of levels can be set independently according to actual conditions and can be selected as 2. Figure 8 As shown, the current CQI level is level 5. The current CQI level is increased to level 6. At this time, the transmission block error rate is still less than the transmission block error rate threshold. Then the level 6 CQI is increased to level 7. At this time, the transmission block error rate is still less than the transmission block error rate threshold. Then the level 7 CQI is increased to level 8 ( Figure 8 (Not shown) If the transmission block error rate is greater than the transmission block error rate threshold, level 8 is determined as the increased CQI level. Level 3 is obtained by subtracting level 8 from level 5. Since level 3 is greater than the preset number of levels 2, the second CQI level = level 8 - 2 = level 6.

[0206] Further explanation is as follows:

[0207] In the current simulation, the BLER at SNR_start1 and the current CQI level is less than 10%. The BLER is greater than 10% only when the current CQI level 5 is increased to level 8. The BLER is also less than 10% when the CQI level is increased to level 7. However, in order to overcome the spurious interference of random channels, the CQI level is only increased to level 6.

[0208] If it is determined that the difference between the increased CQI level and the current CQI level is less than or equal to the preset level number, the current CQI level is determined as the second CQI level. Figure 8 As shown, the current CQI level is 6. The current CQI level is increased to 7. At this time, the transmission block error rate is still less than the transmission block error rate threshold. The CQI level 7 is then increased to 8. However, the transmission block error rate is greater than the transmission block error rate threshold. Therefore, level 8 is determined to be the increased CQI level. Subtracting level 8 from level 6 yields level 2, which is equal to the preset number of levels, 2. Therefore, the second CQI level is the current CQI level 6.

[0209] Further explanation is as follows:

[0210] In the current simulation, the BLER at the SNR_start2 and current CQI levels is less than 10%. The BLER is also less than 10% when the current CQI level 6 is increased to level 7. The BLER is greater than 10% when the level 7 is increased to level 8. At this time, the CQI level is not increased to overcome the spurious interference of random channels.

[0211] Adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold to obtain a second CQI level includes:

[0212] If it is determined that the transmission block error rate is greater than or equal to the transmission block error rate threshold, the current CQI level is simulated to be gradually reduced until the reduced CQI level is less than the transmission block error rate threshold, and the second CQI level is determined according to the reduced CQI level.

[0213] Determining a second CQI level according to the reduced CQI level includes:

[0214] The CQI level that is one level lower than the adjusted CQI level is determined as the second CQI level. Figure 9 As shown in the figure, if the BLER of the CQI level in the current simulation is greater than 10% at the current SNR_start and current CQI level, the CQI level needs to be lowered. After the current CQI level is lowered to level 6, the BLER is already less than 10%. However, in order to overcome the spurious interference of random channels, the CQI level needs to be lowered to level 5.

[0215] In the above step R3, the apparatus sends the second CQI level to the transmitter, so that the transmitter can execute the above method steps applied to the transmitter.

[0216] like Figure 10 As shown, the adaptive modulation and coding method for a time-varying channel provided by an embodiment of the present invention is further described as follows:

[0217] The transmitting end generates a simulated OFDM signal according to the MCS level and simulation parameter configuration information, and sends the simulated OFDM signal to the receiving end. The simulation parameter configuration information may include at least a signal-to-noise ratio.

[0218] The receiving end performs waveform demodulation on the analog OFDM signal to obtain a waveform-demodulated signal; performs channel estimation on the waveform-demodulated signal to obtain current state information, and sends the current state information to the transmitting end.

[0219] The receiving end also demodulates and decodes the current state information to obtain the number of time slots with transmission errors; calculates the transmission block error rate under the current signal-to-noise ratio based on the number of time slots with transmission errors; determines the CQI level recommended by the current simulation conditions based on the comparison result of the transmission block error rate under the current signal-to-noise ratio with the transmission block error rate threshold, that is, determines the above-mentioned second CQI level, and sends the CQI level recommended by the current simulation conditions to the transmitting end. At this point, the method steps applied to the receiving end have been completed.

[0220] The transmitting end receives the current state information, and uses a preset channel prediction model to perform channel prediction on the current channel state information to obtain predicted channel state information.

[0221] The transmitting end obtains the targeted channel state information and determines the CQI level of the next simulation based on this information and the mapping relationship. Specifically, the transmitting end queries the database based on the predicted channel state information to obtain the targeted channel state information and determines the first CQI level, i.e., the CQI level of the next simulation, based on the mapping relationship stored in the database.

[0222] It should be noted that the transmitting end can be a satellite and the receiving end can be a ground station. Within a certain time window, the ground station can receive the signal sent by the satellite, that is, at the starting moment of the time window, the first generation of the simulated OFDM signal according to the MCS level and simulation parameter configuration information is executed (from then on, the CQI level of the next simulation is determined for the first time), and at the end moment of the time window, the last generation of the simulated OFDM signal according to the MCS level and simulation parameter configuration information is executed and sent to the receiving end. The receiving end sends the current status information and the last recommendation of the current simulation conditions to the transmitting end based on the simulated OFDM signal sent last time. CQI level. If the COI level recommended by the current simulation conditions sent last is different from the CQI level of the next simulation corresponding to the current state information sent last, the channel model is retrained one last time. After that, the receiving end can no longer receive the simulated OFDM signal sent by the transmitting end, and the transmitting end naturally can no longer receive the current state information sent by the receiving end. At this time, the channel prediction model has no input data and cannot obtain the predicted channel state information. At this time, the method is terminated, that is, "obtaining the targeted channel state information, and determining the CQI level of the next simulation based on this information and the mapping relationship" and subsequent steps will no longer be executed.

[0223] The transmitter compares the CQI level of the next simulation with the CQI level recommended by the current simulation conditions. If the level comparison results are the same, the preset channel prediction model is used to predict the current channel state information, obtain the predicted channel state information, and execute the subsequent steps. If the level comparison results are different, the preset channel prediction model is retrained and the retrained preset channel prediction model is used to predict the current channel state information, obtain the predicted channel state information, and execute the subsequent steps.

[0224] An adaptive modulation and coding method for a time-varying channel provided by an embodiment of the present invention receives an analog OFDM signal sent by a transmitting end, obtains current state information of the time-varying channel based on the analog OFDM signal; determines a transmission block error rate under a current signal-to-noise ratio based on the current state information, and adjusts the current CQI level based on a second comparison result between the transmission block error rate under the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level; sends the second CQI level to the transmitting end, and determines the second CQI level by considering a margin between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold, thereby further overcoming spurious interference of random channels and ensuring correct and effective communication.

[0225] In the above optional embodiment, adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold to obtain a second CQI level includes:

[0226] If it is determined that the transmission block error rate is less than the transmission block error rate threshold, the current CQI level is simulated and gradually increased until the transmission block error rate corresponding to the increased CQI level is greater than or equal to the transmission block error rate threshold, and a second CQI level is determined based on the increased CQI level. This description can be referred to the above embodiment and will not be repeated here.

[0227] The adaptive modulation and coding method for a time-varying channel provided by the embodiment of the present invention can reasonably determine the second CQI level when the transmission block error rate is less than the transmission block error rate threshold.

[0228] In the above optional embodiment, determining the second CQI level according to the increased CQI level includes:

[0229] If it is determined that the difference between the increased CQI level and the current CQI level is greater than the preset number of levels, the difference between the increased CQI level and the preset number of levels is determined as the second CQI level; please refer to the above embodiment for description and no further details will be given.

[0230] If it is determined that the difference between the increased CQI level and the current CQI level is less than or equal to the preset level number, the current CQI level is determined as the second CQI level.

[0231] The adaptive modulation and coding method for a time-varying channel provided in the embodiment of the present invention further reasonably determines the second CQI level through the increased CQI level.

[0232] In the above optional embodiment, adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold to obtain a second CQI level includes:

[0233] If it is determined that the transmission block error rate is greater than or equal to the transmission block error rate threshold, the current CQI level is simulated to be gradually reduced until the reduced CQI level is less than the transmission block error rate threshold, and a second CQI level is determined based on the reduced CQI level. This can be described with reference to the above embodiment and will not be repeated here.

[0234] The adaptive modulation and coding method for a time-varying channel provided by the embodiment of the present invention can reasonably determine the second CQI level when the transmission block error rate is greater than or equal to the transmission block error rate threshold.

[0235] In the above optional embodiment, determining the second CQI level according to the reduced CQI level includes:

[0236] A CQI level one level lower than the adjusted CQI level is determined as the second CQI level.

[0237] The adaptive modulation and coding method for a time-varying channel provided in the embodiment of the present invention further reasonably determines the second CQI level by using the reduced CQI level.

[0238] Figure 11 FIG. 1 is a schematic diagram of the structure of an adaptive modulation and coding device for a time-varying channel provided by an embodiment of the present invention. Figure 11 As shown, the adaptive modulation and coding apparatus for a time-varying channel provided by an embodiment of the present invention includes a generating unit 1101, a predicting unit 1102, and a modulating unit 1103, wherein:

[0239] The generation unit 1101 is used to send an analog OFDM signal to a receiving end; the prediction unit 1102 is used to receive the current state information of the time-varying channel fed back by the receiving end, and perform channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information; the modulation unit 1103 is used to query a pre-constructed database according to the predicted channel state information, determine a first CQI level according to the targeted channel state information obtained by the query, and update the MCS level required to generate the analog OFDM signal according to the first CQI level, so as to realize adaptive modulation and coding of the time-varying channel according to the updated MCS level; wherein the preset channel prediction model is optimized based on a first comparison result between the second CQI level and the first CQI level fed back by the receiving end.

[0240] Specifically, the generation unit 1101 in the device is used to send an analog OFDM signal to the receiving end; the prediction unit 1102 is used to receive the current state information of the time-varying channel fed back by the receiving end, and perform channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information; the modulation unit 1103 is used to query a pre-constructed database based on the predicted channel state information, determine the first CQI level based on the targeted channel state information obtained by the query, and update the MCS level required to generate the analog OFDM signal based on the first CQI level, so as to realize adaptive modulation and coding of the time-varying channel according to the updated MCS level; wherein, the preset channel prediction model is optimized based on the first comparison result between the second CQI level and the first CQI level fed back by the receiving end.

[0241] An adaptive modulation and coding device for a time-varying channel provided in an embodiment of the present invention sends an analog OFDM signal to a receiving end; receives current state information of the time-varying channel fed back by the receiving end, and performs channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information; queries a pre-constructed database based on the predicted channel state information, determines a first CQI level based on the targeted channel state information obtained by the query, and updates the generated MCS level required for the analog OFDM signal based on the first CQI level, so as to realize adaptive modulation and coding of the time-varying channel according to the updated MCS level; wherein the preset channel prediction model is optimized based on a first comparison result between a second CQI level and the first CQI level fed back by the receiving end, and the predicted channel state information is obtained based on the current state information through the preset channel prediction model, thereby ensuring the timeliness and accuracy of the predicted channel state information; in addition, the second CQI level is compared with the first CQI level, and the preset channel prediction model is optimized accordingly, thereby further ensuring the accuracy of the predicted channel state information.

[0242] Figure 12 FIG. 1 is a schematic diagram of the structure of an adaptive modulation and coding device for a time-varying channel provided by an embodiment of the present invention. Figure 12 As shown, the adaptive modulation and coding device for a time-varying channel provided by an embodiment of the present invention includes an acquisition module 1201, a determination module 1202, and a sending module 1203, wherein:

[0243] The acquisition module 1201 is used to receive an analog OFDM signal sent by a transmitter, and obtain current state information of a time-varying channel based on the analog OFDM signal; the determination module 1202 is used to determine a transmission block error rate under a current signal-to-noise ratio based on the current state information, and adjust the current CQI level based on a second comparison result between the transmission block error rate under the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level; and the sending module 1203 is used to send the second CQI level to the transmitter.

[0244] Specifically, the acquisition module 1201 in the device is used to receive an analog OFDM signal sent by a transmitting end, and obtain current state information of the time-varying channel based on the analog OFDM signal; the determination module 1202 is used to determine the transmission block error rate under the current signal-to-noise ratio based on the current state information, and adjust the current CQI level based on a second comparison result between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold to obtain a second CQI level; the sending module 1203 is used to send the second CQI level to the transmitting end.

[0245] An adaptive modulation and coding apparatus for a time-varying channel provided by an embodiment of the present invention receives an analog OFDM signal sent by a transmitting end, obtains current state information of the time-varying channel based on the analog OFDM signal, determines a transmission block error rate under a current signal-to-noise ratio based on the current state information, and adjusts a current CQI level based on a second comparison result between the transmission block error rate under the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level; sends the second CQI level to the transmitting end, and determines the second CQI level by considering a margin between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold, thereby further overcoming spurious interference of random channels and ensuring correct and effective communication.

[0246] The embodiment of the present invention provides an embodiment of an adaptive modulation and coding device for a time-varying channel, which can be specifically used to execute the processing flow of the above-mentioned method embodiments. Its functions are not repeated here, and reference can be made to the detailed description of the above-mentioned method embodiments.

[0247] Figure 13 A schematic diagram of the physical structure of a computer device provided in an embodiment of the present invention is shown in FIG. Figure 13 As shown, the computer device includes: a memory 1301, a processor 1302, and a computer program stored in the memory 1301 and executable on the processor 1302. When the processor 1302 executes the computer program, the following method is implemented:

[0248] Send analog OFDM signal to the receiving end;

[0249] receiving current state information of the time-varying channel fed back by the receiving end, and performing channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information;

[0250] querying a pre-built database based on the predicted channel state information, determining a first CQI level based on the targeted channel state information obtained from the query, and updating an MCS level required for generating a simulated OFDM signal based on the first CQI level to implement adaptive modulation and coding for a time-varying channel based on the updated MCS level;

[0251] The preset channel prediction model is optimized based on a first comparison result between the second CQI level and the first CQI level fed back by the receiving end;

[0252] Alternatively, receiving an analog OFDM signal sent by a transmitting end, and obtaining current state information of a time-varying channel according to the analog OFDM signal;

[0253] determining a transmission block error rate under a current signal-to-noise ratio according to the current state information, and adjusting the current CQI level according to a second comparison result of the transmission block error rate under the current signal-to-noise ratio with a transmission block error rate threshold to obtain a second CQI level;

[0254] The second CQI level is sent to the transmitting end.

[0255] This embodiment discloses a computer program product, which includes a computer program. When the computer program is executed by a processor, the following method is implemented:

[0256] Send analog OFDM signal to the receiving end;

[0257] receiving current state information of the time-varying channel fed back by the receiving end, and performing channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information;

[0258] querying a pre-built database based on the predicted channel state information, determining a first CQI level based on the targeted channel state information obtained from the query, and updating an MCS level required for generating a simulated OFDM signal based on the first CQI level to implement adaptive modulation and coding for a time-varying channel based on the updated MCS level;

[0259] The preset channel prediction model is optimized based on a first comparison result between the second CQI level and the first CQI level fed back by the receiving end;

[0260] Alternatively, receiving an analog OFDM signal sent by a transmitting end, and obtaining current state information of a time-varying channel according to the analog OFDM signal;

[0261] determining a transmission block error rate under a current signal-to-noise ratio according to the current state information, and adjusting the current CQI level according to a second comparison result of the transmission block error rate under the current signal-to-noise ratio with a transmission block error rate threshold to obtain a second CQI level;

[0262] The second CQI level is sent to the transmitting end.

[0263] This embodiment provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the following method is implemented:

[0264] Send analog OFDM signal to the receiving end;

[0265] receiving current state information of the time-varying channel fed back by the receiving end, and performing channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information;

[0266] querying a pre-built database based on the predicted channel state information, determining a first CQI level based on the targeted channel state information obtained from the query, and updating an MCS level required for generating a simulated OFDM signal based on the first CQI level to implement adaptive modulation and coding for a time-varying channel based on the updated MCS level;

[0267] The preset channel prediction model is optimized based on a first comparison result between the second CQI level and the first CQI level fed back by the receiving end;

[0268] Alternatively, receiving an analog OFDM signal sent by a transmitting end, and obtaining current state information of a time-varying channel according to the analog OFDM signal;

[0269] determining a transmission block error rate under a current signal-to-noise ratio according to the current state information, and adjusting the current CQI level according to a second comparison result of the transmission block error rate under the current signal-to-noise ratio with a transmission block error rate threshold to obtain a second CQI level;

[0270] The second CQI level is sent to the transmitting end.

[0271] Compared with the technical solutions in the prior art, the embodiments of the present invention provide an adaptive modulation and coding method for a time-varying channel, which sends an analog OFDM signal to a receiving end; receives current state information of the time-varying channel fed back by the receiving end, and performs channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information; queries a pre-constructed database based on the predicted channel state information, determines a first CQI level based on the targeted channel state information obtained by the query, and updates the MCS level required for generating the analog OFDM signal based on the first CQI level, so as to implement adaptive modulation and coding of the time-varying channel according to the updated MCS level; wherein the preset channel prediction model is optimized based on a first comparison result between a second CQI level and the first CQI level fed back by the receiving end, and the predicted channel state information is obtained based on the current state information through the preset channel prediction model, thereby ensuring the timeliness and accuracy of the predicted channel state information; in addition, the second CQI level is compared with the first CQI level, and the preset channel prediction model is optimized accordingly, thereby further ensuring the accuracy of the predicted channel state information;

[0272] Alternatively, an analog OFDM signal sent by a transmitting end is received, and current state information of a time-varying channel is obtained based on the analog OFDM signal; a transmission block error rate at a current signal-to-noise ratio is determined based on the current state information, and the current CQI level is adjusted based on a second comparison result between the transmission block error rate at the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level; the second CQI level is sent to the transmitting end, and the second CQI level is determined by considering a margin between the transmission block error rate at the current signal-to-noise ratio and the transmission block error rate threshold, thereby further overcoming spurious interference from random channels and ensuring correct and effective communication.

[0273] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0274] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0275] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0276] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0277] Throughout this specification, reference to terms such as "one embodiment," "a specific embodiment," "some embodiments," "for example," "example," "specific example," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0278] The above specific embodiments further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An adaptive modulation and coding method for a time-varying channel, characterized in that: The adaptive modulation and coding method for a time-varying channel is applied to a transmitting end; comprising: Send analog OFDM signal to the receiving end; receiving current state information of the time-varying channel fed back by the receiving end, and performing channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information; querying a pre-built database according to the predicted channel state information, determining a first CQI level according to the targeted channel state information obtained from the query, and updating an MCS level required for generating the simulated OFDM signal according to the first CQI level, so as to implement adaptive modulation and coding of the time-varying channel according to the updated MCS level; The preset channel prediction model is optimized according to a first comparison result between a second CQI level fed back by the receiving end and the first CQI level.

2. The adaptive modulation and coding method for time-varying channels according to claim 1, wherein: The simulated OFDM signal is generated according to the MCS level and simulation parameter configuration information of the time-varying channel.

3. The adaptive modulation and coding method for time-varying channels according to claim 1, wherein: Constructing the database includes: Obtain multiple discrete time-varying channel parameters, multiple channel models, and multiple MCS levels; Combining the plurality of discrete time-varying channel parameters to obtain a plurality of channel parameter combinations; Combining each group of the channel parameter combinations with the multiple channel models, and combining each of the channel models with the multiple MCS levels, to obtain simulation event information; The simulation event information is simulated, and the database is constructed according to the simulation results.

4. The adaptive modulation and coding method for time-varying channels according to claim 3, characterized in that: The plurality of discrete time-varying channel parameters include at least a rainfall rate; accordingly, the adaptive modulation and coding method for the time-varying channel further includes: The Weibull distribution is used as a distribution function to characterize the rainfall rate distribution, and the time-varying property of the time-varying channel is simulated according to the distribution function.

5. The adaptive modulation and coding method for time-varying channels according to claim 3, wherein: The multiple channel models include at least the NTN-TDL channel model; accordingly, the adaptive modulation and coding method for the time-varying channel further includes: The NTN-TDL channel model is modeled and simulated based on the Rice sine sum method.

6. The adaptive modulation and coding method for a time-varying channel according to any one of claims 1 to 5, characterized in that: Optimizing the preset channel prediction model includes: If it is determined that the first comparison result is different, retraining the preset channel prediction model; If it is determined that the first comparison result is the same, continue to use the preset channel prediction model.

7. An adaptive modulation and coding method for a time-varying channel, characterized in that: The adaptive modulation and coding method for a time-varying channel is applied to a receiving end, comprising: receiving an analog OFDM signal sent by a transmitting end, and acquiring current state information of a time-varying channel according to the analog OFDM signal; determining a transmission block error rate under a current signal-to-noise ratio according to the current state information, and adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level; The second CQI level is sent to the transmitting end.

8. The adaptive modulation and coding method for time-varying channels according to claim 7, characterized in that: The adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold to obtain a second CQI level includes: If it is determined that the transmission block error rate is less than the transmission block error rate threshold, the current CQI level is simulated to be gradually increased until the transmission block error rate corresponding to the increased CQI level is greater than or equal to the transmission block error rate threshold, and the second CQI level is determined according to the increased CQI level.

9. The adaptive modulation and coding method for time-varying channels according to claim 8, characterized in that: The determining the second CQI level according to the increased CQI level includes: If it is determined that the difference between the increased CQI level and the current CQI level is greater than a preset number of levels, determining the difference between the increased CQI level and the preset number of levels as the second CQI level; If it is determined that the difference between the increased CQI level and the current CQI level is less than or equal to a preset number of levels, the current CQI level is determined as the second CQI level.

10. The adaptive modulation and coding method for time-varying channels according to claim 7, characterized in that: The adjusting the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and the transmission block error rate threshold to obtain a second CQI level includes: If it is determined that the transmission block error rate is greater than or equal to the transmission block error rate threshold, the current CQI level is simulated to be gradually reduced until the reduced CQI level is less than the transmission block error rate threshold, and the second CQI level is determined according to the reduced CQI level.

11. The adaptive modulation and coding method for a time-varying channel according to claim 10, characterized in that: The determining the second CQI level according to the reduced CQI level includes: A CQI level one level lower than the decreased CQI level is determined as the second CQI level.

12. An adaptive modulation and coding device for a time-varying channel, characterized in that: The adaptive modulation and coding device for a time-varying channel is applied to a transmitting end and comprises: A generating unit, configured to send an analog OFDM signal to a receiving end; a prediction unit, configured to receive the current state information of the time-varying channel fed back by the receiving end, and perform channel prediction on the current channel state information based on a preset channel prediction model to obtain predicted channel state information; a modulation unit, configured to query a pre-constructed database according to the predicted channel state information, determine a first CQI level according to the targeted channel state information obtained from the query, and update the MCS level required for generating the simulated OFDM signal according to the first CQI level, so as to implement adaptive modulation and coding of the time-varying channel according to the updated MCS level; The preset channel prediction model is optimized according to a first comparison result between a second CQI level fed back by the receiving end and the first CQI level.

13. An adaptive modulation and coding device for a time-varying channel, characterized in that: The adaptive modulation and coding device for a time-varying channel is applied to a receiving end and includes: an acquisition module, configured to receive an analog OFDM signal sent by a transmitting end, and acquire current state information of a time-varying channel according to the analog OFDM signal; a determination module, configured to determine a transmission block error rate under a current signal-to-noise ratio according to the current state information, and adjust the current CQI level according to a second comparison result between the transmission block error rate under the current signal-to-noise ratio and a transmission block error rate threshold to obtain a second CQI level; A sending module is configured to send the second CQI level to the sending end.

14. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 6 or claims 7 to 11 is implemented.

15. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 or claims 7 to 11 is implemented.

16. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 or claims 7 to 11 is implemented.

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