Channel estimation method and apparatus using frequency selective characteristic in wireless communication system

Abstract

A method for estimating a channel of a reception device in a wireless communication system comprises the steps of: estimating a reception channel on the basis of a received signal; determining a signal-to-noise ratio of the received signal; estimating a frequency selective characteristic of the reception channel; determining a moving average filter on the basis of the signal-to-noise ratio and the frequency selective characteristic; and applying the determined moving average filter to the estimated reception channel.

Description

Method and apparatus for channel estimation using frequency-selective characteristics in a wireless communication system

[0001] The present disclosure relates to a method and apparatus for channel estimation using frequency-selective characteristics in a wireless communication system.

[0002] In OFDM (orthogonal frequency division multiplexing) communication systems such as LTE (long term evolution) and NR (new radio), data is transmitted using time and frequency resources. For example, in the case of a PUSCH (physical uplink shared channel), when the base station provides scheduling information to the terminal, the terminal transmits data in the allocated frequency and time domains based on that information. In this case, the PUSCH can be allocated in units of multiple OFDM symbols in the time domain and multiple RBs (resource blocks) in the frequency domain. A single RB consists of 12 subcarriers, and each subcarrier is called a RE (resource element).

[0003] In order for a base station to decode data received from a terminal, it must estimate the channel of the received signal. In general communication systems, pilot signals for channel estimation between a transmitter and a receiver are defined, and a representative example is the demodulation reference signal (DMRS) defined in the 3GPP (3rd Generation Partnership Project) NR standard.

[0004] DMRS symbols can be assigned to multiple symbols within the time domain according to scheduling information, and the subcarriers of multiple RBs assigned in the frequency domain are distinguished into DMRS RE and DATA RE. Six or four DMRS REs are assigned to a single RB depending on the DMRS configuration type, and DMRS can be assigned to the entire RB area when transmitting multiple layers using the MIMO (multiple input multiple output) technique. The receiver performs channel estimation using the DMRS REs within the entire received RB area.

[0005] Representative channel estimation methods using DMRS in OFDM systems include the least-square (LS) method and the minimum mean square error (MMSE) method. Although the MMSE method guarantees excellent performance, it is difficult to apply to actual systems due to its high implementation complexity and large amount of computation. The LS method is used in most systems because it has relatively lower complexity compared to the MMSE method, but various methods are being developed to improve it as performance degradation occurs.

[0006] The information described above may be provided as related art for the purpose of aiding understanding of this document. None of the foregoing is to be claimed as prior art related to this document, nor is it to be used to determine prior art.

[0007] The present disclosure relates to an efficient channel estimation method and apparatus in a wireless communication system, and provides a method and apparatus for adaptively selecting a frequency domain filter by considering frequency-selective characteristics in a wireless communication channel undergoing multipath fading.

[0008] According to one aspect of the present disclosure, a receiving device for estimating a channel in a wireless communication system comprises: a transceiver; and a memory for storing one or more instructions, and at least one processor operably coupled to the memory, configured to execute one or more instructions stored in the memory, wherein when the one or more instructions are executed alone or together by the at least one processor, the receiving device: estimates a receiving channel based on a receiving signal, determines a signal-to-noise ratio of the receiving signal, estimates a frequency-selective characteristic of the receiving channel, determines a moving average filter based on the signal-to-noise ratio and the frequency-selective characteristic, and applies the determined moving average filter to the estimated receiving channel.

[0009] According to one aspect of the present disclosure, a method for estimating a channel of a receiving device in a wireless communication system comprises: estimating a receiving channel based on a receiving signal; determining a signal-to-noise ratio of the receiving signal; estimating a frequency-selective characteristic of the receiving channel; determining a moving average filter based on the signal-to-noise ratio and the frequency-selective characteristic; and applying the determined moving average filter to the estimated receiving channel.

[0010] According to one aspect of the present disclosure, in a non-transient computer-readable medium storing one or more instructions, the one or more instructions are executed by at least part of at least one processor of an electronic device, wherein the electronic device: estimates a receiving channel based on a receiving signal, determines a signal-to-noise ratio of the receiving signal, estimates a frequency-selective characteristic of the receiving channel, determines a moving average filter based on the signal-to-noise ratio and the frequency-selective characteristic, and applies the determined moving average filter to the estimated receiving channel.

[0011] Through one or more embodiments of the present disclosure, the amount of change in the channel in the frequency domain can be estimated without time domain conversion of the received signal, thereby reducing complexity and improving estimation performance regardless of the number of resource blocks.

[0012] In addition, when using a moving average filter in the frequency domain, the filter size can be determined based on frequency selectivity, which can improve channel estimation performance.

[0013] The above and other aspects, features, and advantages will become more apparent from the following description, which is referenced together with the attached drawings.

[0014] Figure 1 is a flowchart of the channel estimator operation of a receiving device in a wireless communication system.

[0015] FIGS. 2A and 2B are diagrams illustrating an example of a method for determining frequency-selective characteristics based on converting a signal assigned in the frequency domain into a time domain signal by performing an inverse discrete Fourier transform (IDFT) (or inverse fast Fourier transform (IFFT)) in a wireless communication system.

[0016] FIG. 3 is a diagram showing an example of the configuration of a block diagram of a channel estimator of a receiving device in a wireless communication system according to one embodiment of the present disclosure.

[0017] FIG. 4 is a flowchart illustrating an example of the operation of a channel estimator of a receiving device in a wireless communication system according to one embodiment of the present disclosure.

[0018] FIG. 5 is a flowchart illustrating an example of an operation to determine the number of subcarriers to group channels to estimate channel change amounts in a preprocessing operation for estimating frequency channel characteristics according to one embodiment of the present disclosure.

[0019] FIG. 6 is a diagram illustrating an example of a method for converting subcarriers into average channel values ​​when the number of subcarriers to be grouped to estimate the channel change amount in FIG. 5 is determined to be '3' according to one embodiment of the present disclosure.

[0020] FIG. 7 is a flowchart illustrating an example of an operation to determine frequency-selective characteristics and select the size of a moving average filter according to one embodiment of the present disclosure.

[0021] FIG. 8 is a diagram comparing performance by simulating the probability of determining a TDL-A channel as a TDL-A channel according to the signal-to-noise ratio interval when using a moving average filter according to one embodiment of the present disclosure.

[0022] FIG. 9 is a diagram comparing channel estimation performance in a TDL-C channel when using a moving average filter according to one embodiment of the present disclosure.

[0023] FIG. 10 is a diagram comparing channel estimation performance in a TDL-A channel when using a moving average filter according to one embodiment of the present disclosure.

[0024] FIG. 11 is a diagram comparing channel estimation performance in a TDL-C channel when using a moving average filter according to one embodiment of the present disclosure.

[0025] FIG. 12 is a flowchart illustrating an example of the operation of a receiving device according to one embodiment of the present disclosure.

[0026] FIG. 13 is a block diagram showing the structure of a receiving device according to one embodiment of the present disclosure.

[0027] The operating principles of the present disclosure will be described in detail below with reference to the attached drawings. In describing the present disclosure below, specific descriptions of related known functions or configurations will be omitted if it is determined that such detailed descriptions would unnecessarily obscure the essence of the present disclosure. Furthermore, the terms described below are defined in consideration of their functions in the present disclosure, and these may vary depending on the intentions or practices of the user or operator. Therefore, their definitions should be based on the content throughout this specification.

[0028] The advantages and features of the present disclosure and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the accompanying drawings. However, the present disclosure is not limited to the embodiments disclosed below but may be implemented in various different forms. These embodiments are provided merely to ensure that the disclosure is complete and to fully inform those skilled in the art of the scope of the invention, and the present disclosure is defined only by the scope of the claims. Throughout the specification, like reference numerals refer to like components.

[0029] At this point, it will be understood that each block of the process flow diagrams and combinations of the flow diagrams can be executed by computer program instructions.

[0030] Additionally, each block may represent a module, segment, or part of code containing one or more executable instructions for executing a specified logical function(s). It should also be noted that in some alternative execution examples, the functions mentioned in the blocks may occur out of order. For instance, two blocks described in succession may actually be executed substantially simultaneously, or the blocks may be executed in reverse order according to their corresponding functions.

[0031] In this embodiment, the term "part" refers to a software or hardware component such as an FPGA (Field Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit), and the "part" performs certain roles. However, the meaning of "part" is not limited to software or hardware. The "part" may be configured to reside in an addressable storage medium or configured to run one or more processors. Thus, as an example, the "part" includes components such as software components, object-oriented software components, class components, and task components, as well as processes, functions, attributes, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuits, data, databases, data structures, tables, arrays, and variables. The functions provided within the components and "parts" may be combined into a smaller number of components and "parts" or further separated into additional components and "parts." In addition, the components and 'parts' may be implemented to utilize one or more CPUs within the device or secure multimedia card. Also, in the embodiments, 'parts' may include one or more processors.

[0032] In the present disclosure, each of the phrases such as “A / B”, “A or B”, “A and / or B”, “at least one of A and B”, “at least one of A or B”, “A, B or C”, “at least one of A, B and C”, and “at least one of A, B, or C” may include any one of the items listed together in the corresponding phrase, or all possible combinations thereof. Terms such as “first”, “second”, or “first” or “second” may be used simply to distinguish a component from another component and do not limit the components in any other aspect (e.g., importance or order).

[0033] Terms used in the following description to identify connection nodes, terms referring to network entities, terms referring to messages, terms referring to interfaces between network entities, terms referring to various identification information, etc., are examples provided for the convenience of explanation. Accordingly, the present disclosure is not limited to the terms described below, and other terms referring to objects having equivalent technical meanings may be used.

[0034] In the present disclosure, a base station (BS) is a network entity capable of performing resource allocation for terminals and communicating with terminals through a wireless network, and may be at least one of an eNode B, Node B, gNB, RAN (Radio Access Network), AN (Access Network), RAN node, IAB (Integrated Access / Backhaul) node, a wireless access unit, a base station controller, a node on a network, or a TRP (transmission reception point). A terminal (user equipment: UE) may be at least one of a terminal, MS (Mobile Station), cellular phone, smartphone, computer, or a multimedia system capable of performing communication functions.

[0035] The present disclosure describes embodiments using terms used in 3GPP, such as LTE and NR, but these are examples for illustrative purposes. Various embodiments of the present disclosure may be modified and applied to other communication systems to suit the characteristics of each system, and the present disclosure is described based on the 3GPP NR uplink specification.

[0036] Figure 1 is a flowchart of the channel estimator operation of a receiving device in a wireless communication system.

[0037] The channel estimator of the receiving device of FIG. 1 may include at least one of a fast Fourier transform (FFT) (100), a resource selector (110), a decorrelator (120), a frequency domain channel estimator (130), and a frequency domain filter (140). The channel estimator of FIG. 1 may be included in a base station.

[0038] Referring to FIG. 1, the pilot signal received in FIG. 1 can be converted into a signal in the frequency domain through a Fast Fourier Transform (FFT) operation in the FFT (100). The pilot signal may be referred to as a reference signal (RS). The pilot signal may be used for monitoring, control, equalization, ensuring continuity, synchronization, or reference purposes.

[0039] The channel estimator of FIG. 1 can select a resource element (RE) (e.g., frequency tone) allocated to a specific electronic device (e.g., UE) for a signal converted into the frequency domain through a resource selector (110).

[0040] A channel estimator can generate an input signal for channel estimation based on a signal and a reference signal corresponding to at least one resource element (RE) assigned to an electronic device. In one embodiment, the channel estimator can generate an input signal for channel estimation through an inverse correlation with a signal corresponding to at least one resource element (RE) assigned to an electronic device via an inverse correlator (120). In one or more embodiments, the inverse correlator (120) can reduce autocorrelation within a signal or reduce cross-correlation between a series of signals.

[0041] In one embodiment, the inverse correlator (120) of the channel estimator may generate an input signal for channel estimation by applying a complex conjugate of a reference signal to a signal corresponding to at least one resource area (RB) assigned to an electronic device. For example, the input signal for channel estimation may be generated by dividing the signal corresponding to at least one resource area (RB) assigned to an electronic device by the reference signal. In one embodiment, the reference signal may include a demodulation reference signal (DMRS). In one embodiment, the signal corresponding to at least one resource area (RB) assigned to an electronic device may include a reference signal sequence (e.g., DMRS sequence) corresponding to a symbol (e.g., DMRS symbol) containing the reference signal among the received signals provided by the communication circuit.

[0042] The frequency domain channel estimator (130) can estimate a channel using an input signal for channel estimation. For example, the frequency domain channel estimator (130) can perform channel estimation using an LS method. The frequency domain filter (140) can reduce noise signals with respect to the estimated channel value. For example, a moving average filter may be used as the frequency domain filter (140). In one or more embodiments, the moving average filter may be a digital filter that calculates the average of a data set over a specific time interval or data point interval. The moving average filter may be used for smoothing data, reducing noise, and / or highlighting trends in time series data.

[0043] In an OFDM system, the base station estimates the channel of the received signal using the DMRS within the PUSCH transmitted by the terminal, and an example of expressing the frequency domain received signal by a formula is Equation 1 below.

[0044]

[0045] is the receiving channel of the k-th subcarrier, is the DMRS transmitted from the k-th subcarrier. represents the noise signal of the k-th subcarrier. Here is the transmitted received signal It can be obtained by estimating the channel using the LS method, and an example of this expressed in a formula is Equation 2 below.

[0046]

[0047] receiving channel Noise signal added to This can degrade the quality of the channel and impair channel estimation performance. Noise signals can be reduced in the frequency domain using appropriate filters; for example, a moving average filter can be used. An example of a signal passing through the moving average filter is given by Equation 3 below.

[0048]

[0049] ε is the size of the moving average filter, and since it must be selected as an appropriate value considering the amount of noise signal, its size can be determined based on the signal-to-noise ratio of the received signal. Equation 3 is adjacent to the k-th subcarrier. An example of a method for taking the average of the channels of subcarriers is illustrated, which can reduce the noise signal of each subcarrier.

[0050] However, in communication systems, wireless channels possess frequency-selective characteristics where the channel value in the frequency domain changes due to multipath fading. Multipath fading refers to a transmitted signal reaching a receiver via multiple paths, during which the transmitted signal may have different channel values ​​and time delays. This characteristic implies that the longer the time delay, the greater the change in the frequency domain channel, while the shorter the time delay, the smaller the change in the frequency domain channel. A large change in the channel is equivalent to the channel being inconsistent, and if a moving average filter of the wrong size is used without considering the changing channel, channel estimation performance can further deteriorate. Therefore, the optimal size of the moving average filter In order to select, the signal-to-noise ratio of the received signal and the amount of change of the channel can be considered together in the embodiments of the present disclosure.

[0051] For one or more examples, the time delay can be estimated by converting the signal in the frequency domain to the time domain. An example of a formula representing the conversion of a received signal in the frequency domain into a signal in the time domain by performing an inverse fast Fourier transform (IFFT) or an inverse discrete Fourier transform (IDFT) is shown in Equation 4 below.

[0052]

[0053] In the above formula, the symbol * represents a convolution operation, and changes in the wireless channel are caused by multipath fading, and an example of expressing this formula is Equation 5 below.

[0054]

[0055] is the received signal for the t-th sample in the time domain, and represents the DMRS transmitted in the t-th sample, and is the noise signal of the t-th sample. is the channel value for the i-th path, and represents the time delay value for the i-th path. Assuming that the DMRS received at each subcarrier k in the frequency domain is all 1, the DMRS converted to the time domain can be expressed as an impulse response as shown in Equation 6 below.

[0056]

[0057] The received signal converted to the time domain can be represented as an impulse response with a noise signal added, and in this case, the channel value may exist in a sample with a time delay. The resolution capable of distinguishing the time delay value of the received signal is proportional to the number of samples in the time domain, and the resolution of the time delay value can be reduced as the number of RBs allocated in the frequency domain increases.

[0058] FIGS. 2A and 2B are diagrams illustrating an example of a method for determining frequency-selective characteristics based on a signal assigned in the frequency domain in a wireless communication system, converted into a time domain signal by performing an inverse discrete Fourier transform (IDFT) (or inverse fast Fourier transform (IFFT)).

[0059] Figure 2a is an example of converting 1RB (IDFT size = 6) and 2RB (IDFT size = 12) allocated in the frequency domain into time domain signals by performing IDFT. It can be seen that the resolution of the time delay in 2RB is smaller than in 1RB, allowing for a more accurate estimation of the time delay value.

[0060] Referring to Fig. 2b, a specific threshold value can be set, samples below the threshold value are considered as noise signals, and among the samples above the threshold value, the sample with the smallest time delay (e.g., the first time delay) and the sample with the largest time delay can be selected. A representative time delay value can be estimated by calculating the distance difference between the two selected samples, and this value can be used as a metric to determine frequency-selective characteristics.

[0061] When using a moving average filter in the frequency domain to reduce noise signals in a wireless communication channel experiencing multipath fading, channel estimation performance may deteriorate if the frequency-selective characteristics of the channel are not considered.

[0062] As previously discussed, there is a method to estimate the time delay of a multipath fading channel by converting a frequency domain signal into a time domain signal. However, proper interpretation may be difficult due to CIR (channel impulse response) leakage occurring during this conversion, and it may be difficult to accurately estimate the time delay value if the RB allocated to the frequency domain is small, as the resolution of the time domain samples increases. Additionally, because the complexity increases during the process of converting the frequency domain signal to the time domain, some communication systems may experience performance degradation by using a moving average filter that does not consider the frequency characteristics of the channel.

[0063] Embodiments of the present disclosure propose a method that can solve problems of the prior art occurring in the time domain and improve channel estimation performance by estimating frequency-selective characteristics of a received signal in the frequency domain in a wireless communication channel undergoing multipath fading.

[0064] Specifically, we propose a method for minimizing complexity in the channel of a received signal in the frequency domain and estimating the amount of change in the channel, a method for determining the characteristics of the channel, and a method for selecting the size of a moving average filter suitable for the channel characteristics.

[0065] FIG. 3 is a diagram showing an example of the configuration of a block diagram of a channel estimator of a receiving device in a wireless communication system according to one embodiment of the present disclosure.

[0066] Referring to FIG. 3, the channel estimator may include at least one of a decorrelator (300), an SNR (signal to noise ratio) estimator (310), a pre-processing unit (320), a frequency selectivity estimator (330), a filter selector (340), and a frequency domain filter (350).

[0067] The channel estimator can generate an input signal for channel estimation through an inverse correlation of a signal corresponding to at least one resource element (RE) via an inverse correlation unit (300). The input signal for channel estimation may include a reference signal sequence (e.g., DMRS sequence) corresponding to a symbol (e.g., DMRS symbol) containing a reference signal among the received signals.

[0068] The inverse correlation unit (300) can extract a channel in the frequency domain by removing DMRS from the received signal and improve the channel estimation quality using various techniques. In one or more embodiments, DMRS may be a reference signal used in a cellular communication system to support channel estimation and demodulation of a data signal. The SNR estimation unit (310) can estimate the signal-to-noise ratio of the received signal. The estimated signal-to-noise ratio and the received channel may be transmitted to the preprocessing unit (320), the frequency-selective characteristic estimation unit (330), and the filter selection unit (340).

[0069] The preprocessing unit (320) can perform a preprocessing operation to estimate frequency-selective characteristics.

[0070] The frequency selective characteristic estimation unit (330) can estimate the frequency selective characteristics of the preprocessed channel (or estimated channel) received from the preprocessing unit (320). The frequency selective characteristics are estimated by calculating the amount of change of the received channel and can be expressed as a metric that determines the characteristics of the channel.

[0071] The filter selection unit (340) can select a moving average filter and the size of the filter using the frequency selective characteristic determination result, which is the output value of the frequency selective characteristic estimation unit (330), and the signal-to-noise ratio of the received signal, which is the output value of the SNR estimation unit (310).

[0072] The frequency domain filter section (350) passes the frequency domain receiving channel using a filter selected from the filter selection section (340), and in this process, the noise signal of the receiving channel can be reduced.

[0073] FIG. 4 is a flowchart illustrating an example of the operation of a channel estimator of a receiving device in a wireless communication system according to one embodiment of the present disclosure.

[0074] FIG. 4 illustrates the operation of a channel estimator of a receiving device as illustrated in FIG. 3. In one embodiment, FIG. 4 may illustrate the operation of a channel estimator included in a base station in an OFDM system.

[0075] In step 400, the channel estimator can convert the received signal into a frequency domain signal through FFT and remove DMRS.

[0076] In an OFDM system, the base station can obtain the initial channel value by removing the DMRS within the PUSCH transmitted by the terminal. is the received signal of the r-th antenna, p-th layer, and l-th DMRS symbol, and is the received channel value, and an example of expressing it as a formula is Equation 7.

[0077]

[0078] is DMRS generated from the frequency domain channel estimation block and received signal It can be obtained using [this]. An example of this expressed in a formula is mathematical formula 8 below.

[0079]

[0080] In step 405, the channel estimator can perform frequency domain channel estimation. In one embodiment, the channel estimator can perform channel estimation using the LS method. The channel estimator can use various methods to improve the quality of the initial channel value from which DMRS has been removed.

[0081] In step 410, the channel estimator then determines the power of the receiving channel ( ) and power of the noise signal( The signal-to-noise ratio can be calculated by calculating ), and an example of this expressed in a formula is Equation 9 below.

[0082]

[0083] In the frequency domain, the subcarrier of the receiving channel When it's a dog Is It is the total power of the noise signal estimated from the subcarriers. is the total power of the channel, and an example of calculating the signal-to-noise ratio is given in Equation 10 below.

[0084]

[0085] In step 415, the channel estimator can perform a preprocessing operation for frequency-selective characteristic estimation. Performing the preprocessing operation is described below in FIG. 5.

[0086] In step 420, the channel estimator can estimate frequency-selective characteristics. That is, the channel estimator can estimate the selective characteristics of the frequency domain channel estimated in step 405. In one embodiment, the frequency-selective characteristics can be determined by calculating the change amount of the channel, converting it into a metric, and then determining it.

[0087] In step 425, the channel estimator can select a frequency domain filter and a size. In one embodiment, the channel estimator can determine the frequency domain filter and a size by considering the signal-to-noise ratio of the received signal in step 410 and the frequency-selective characteristics estimated in step 420. The size of the frequency domain filter is of Equation 3. It may include. Detailed operation is described later in FIG. 7.

[0088] In step 430, the receiving channel can pass through a determined frequency domain filter to remove noise signals.

[0089] The change in channel for estimating frequency-selective characteristics can be calculated using the change in subcarriers in the frequency domain of the received channel. When the quality of the received channel is good, channel characteristics can be determined more accurately using the change in each subcarrier; however, in channels with a low signal-to-noise ratio (in cases of poor received channel quality), distortion caused by noise signals may appear greater than the change in channel.

[0090] In one or more examples, the quality of a channel is determined by utilizing the signal-to-noise ratio received from a frequency domain channel estimator, and a preprocessing operation may be performed on a received channel having a signal-to-noise ratio below a certain threshold to reduce the noise signal. In one embodiment, if the quality of the received signal is determined to be good, the preprocessing process may be omitted.

[0091] FIG. 5 is a flowchart illustrating an example of an operation to determine the number of subcarriers to group channels to estimate channel change amounts in a preprocessing operation for estimating frequency channel characteristics according to one embodiment of the present disclosure.

[0092] Figure 5 shows the number of subcarriers to be grouped by the channel estimator in the preprocessing operation for frequency channel characteristic estimation. Illuminates the action of selecting.

[0093] In one embodiment, frequency domain subcarriers as a preprocessing operation to reduce noise signals You can calculate the average channel value by grouping them by number. It can be flexibly selected based on a predetermined number of subcarriers, RB units, or the signal-to-noise ratio, and the number of average channel values ​​for estimating frequency-selective characteristics is of the total number of subcarriers allocated in the frequency domain. The number of subcarriers can be reduced. In one embodiment or a plurality of embodiments, each group may include the same number of subcarriers. For example, if the total number of subcarriers is 10 and M is equal to 2, the 10 subcarriers are divided into two identical groups of 5 subcarriers each. In one embodiment or a plurality of embodiments, at least one of the groups of subcarriers may include different numbers of subcarriers.

[0094] Referring to Fig. 5, it can be determined whether a predefined x value exists in step 500. If a predefined x value exists, in step 510, the channel estimator determines the number of subcarriers to group. It can be determined as the x value.

[0095] On the other hand, if a predefined x value does not exist, the channel estimator can assign a value of "0" to variable i in step 520. In step 530, the channel estimator can determine whether the SNR is less than the threshold (SNR_TH[i]). If the SNR is not less than the threshold (SNR_TH[i]), the channel estimator can assign i+1 to variable i in step 540.

[0096] If SNR is less than the threshold (SNR_TH[i]), in step 550, the channel estimator counts the number of subcarriers to group It can be determined by the x[i] value.

[0097] FIG. 6 is a diagram illustrating an example of a method for converting the channel values ​​of subcarriers into average channel values ​​when the number of subcarriers to group the channels to be estimated in FIG. 5 is determined to be '3' according to one embodiment of the present disclosure.

[0098] Figure 6 shows the number of subcarriers to be grouped. In the case of this '3', the assigned in the frequency domain The average channel value of the subcarriers The method of conversion and the average channel value to be used to calculate the frequency-selective characteristics after conversion Illustrates an example regarding the number of.

[0099] Average channel value in the receiving channel of the r-th antenna, p-th layer, and l-th DMRS symbol An example of how to calculate it is shown in mathematical formula 11 below.

[0100]

[0101] Referring to Fig. 6, the number of subcarriers to be grouped If this is determined to be '3', the subcarriers are grouped into sets of 3, and the average channel value ( ... , It is converted to ), and the number of converted average channel values ​​is You can become a dog.

[0102] In one embodiment, when converting the channel values ​​of subcarriers into average channel values, a moving average method used in frequency domain filters can be used. For example, the number of subcarriers to be grouped If this is determined to be '3', silver It is the average channel value of, and Is It can be the average channel value. In this case, the number of average channel values ​​for estimating frequency-selective characteristics is equal to the total number of subcarriers, so the amount of computation can be relatively large.

[0103] In one embodiment, after deriving an average channel value, the channel estimator can determine a distance d between two channels to calculate a channel change amount for determining frequency-selective characteristics. As illustrated in FIG. 6, when the distance d is 1, the channel change amount between immediately adjacent channel values ​​(or average channel values) can be calculated, and when the distance d is 2, the channel change amount of a channel value (or average channel value) at a location 2 units away can be calculated. For example, when the distance d is 2 for calculating the channel change amount from the average channel value illustrated in FIG. 6, and A method for determining frequency selective characteristics by calculating the channel change amount of channel values ​​separated by 2, as shown in FIG. 7, is described later.

[0104] The frequency-selective characteristic estimation unit included in the channel estimator can determine frequency-selective characteristics by calculating the change in average channel values ​​of subcarriers and converting it into a metric. The change in the channel can be estimated in a form similar to the average time delay value by utilizing coefficients for the time delay obtained by differentiating each subcarrier of the received channel; this can be replaced by calculating the difference between subcarrier channel values ​​in the frequency domain.

[0105] To calculate the time delay, the received signal can be differentiated multiple times, which can be expressed as calculating the difference between the difference values ​​between subcarrier channel values ​​in the frequency domain. As this process is performed more frequently, the performance in determining channel characteristics may be improved because the time delay value is reflected in the coefficients; however, since high-band components included in the noise also increase, an appropriate number of repetitions must be selected. In this disclosure, a method for estimating frequency-selective characteristics is described, which estimates the average change amount by calculating the difference between subcarrier channel values ​​in the form of the first derivative of the received channel.

[0106] The change in channel can be calculated as the difference between two average channels adjacent on the complex plane or between two average channel values ​​separated by a predetermined distance (d). Specifically, the average change It can be obtained by converting the ratio of the power difference between real and imag values ​​between adjacent channels separated by d to the power difference between the real and imag values ​​of the current channel into NMSE (normalized mean square error).

[0107] In one embodiment, at the r-th antenna, p-th layer, and l-th DMRS symbol 1 subcarrier The k-th average channel value grouped by units The average change of two average channels separated by a distance d when An example of expressing it as a formula is as shown in mathematical formula 12 below.

[0108]

[0109] In mathematical formula 12, “.r” and “.i” correspond to notations representing the real and imaginary parts of a complex number, respectively.

[0110] is the power of the k-th average channel value. is the power of the difference between the k-th average channel value and the k+d-th average channel value. The average change is calculated by accumulating these values. It can be converted to.

[0111] In one embodiment, the channel estimator is an average change amount By comparing the average change of the channel with a threshold value for determining frequency-selective characteristics, if the average change of the channel is greater than the threshold value, it is determined to be a channel with high frequency-selective characteristics; otherwise, it is determined to be a channel with low frequency-selective characteristics. In one embodiment, the estimated average change of the channel Alternatively, at least one of the selective characteristic results of the determined channel may be reported to the upper layer. The selective characteristic result of the channel may include at least one of the result information determining that the channel has a large frequency selective characteristic or a small frequency selective characteristic, or information indicating whether the average change amount of the channel is greater than the threshold value. Here, the NMSE of the average change amount of the channel is used for explanation, but other statistical characteristics such as the MSE or variance of the average change amount of the channel may also be used.

[0112] In one embodiment, the channel estimator can pre-optimize the threshold value for determining frequency-selective characteristics by using channels defined in communication standards such as 3GPP LTE or NR. For example, it can use various channels with different delay profiles, such as TDL-A channels with small frequency-selective fading (i.e., small frequency-selective characteristics) and TDL-C channels with large frequency-selective fading (i.e., large frequency-selective characteristics) defined in 3GPP NR standards, and can optimize the threshold value based on the probability of properly determining frequency-selective characteristics in each channel.

[0113] In one embodiment, since the channel estimator cannot know the frequency-selective characteristics of the actual received channel, it must set a threshold value by considering all probabilities of correctly determining each channel. For example, if the threshold value is set by considering only the probability of determining a channel as a TDL-A channel in a channel with small frequency-selective characteristics, such as a TDL-A channel, the frequency-selective characteristic determination performance may deteriorate in a channel with large frequency-selective characteristics, such as a TDL-C channel.

[0114] In addition, noise signals present in the receiving channel can affect the magnitude of the average channel change. In one embodiment, since the channel change is calculated to be larger as the noise signal increases, the signal-to-noise ratio of the receiving signal can be considered, the signal-to-noise ratio can be divided into multiple steps, and stepwise optimized threshold values ​​can be used.

[0115] A channel estimator can determine a moving average filter and filter size using the signal-to-noise ratio and frequency-selective characteristics. The moving average filter can be optimized using the same method as the threshold value used to determine the frequency-selective characteristics. In one embodiment, the size of a moving average filter capable of achieving optimal performance according to multiple signal-to-noise ratio intervals in channel models with different frequency-selective characteristics, such as TDL-A channels and TDL-C channels defined in the 3GPP NR standard, can be determined and managed in a table format for use.

[0116] Accordingly, the size of the frequency domain filter is determined based on the signal-to-noise ratio in the moving average filter table that matches the frequency-selective characteristics, and the receiving channel passes through the determined filter so that the noise signal can be removed. An example illustrating the operation of determining the frequency-selective characteristics of the channel estimator and selecting the size of the moving average filter is shown in Figure 7 below.

[0117] FIG. 7 is a diagram illustrating an example of an operation to determine frequency-selective characteristics and select the size of a moving average filter according to one embodiment of the present disclosure.

[0118] Referring to Fig. 7, in step 700, the channel estimator can assign a value of '0' to variable i.

[0119] In step 710, the channel estimator can determine whether the SNR is smaller than the SNR threshold (FSE_SNR_TH[i]) for frequency-selective characteristic estimation. If the SNR is smaller than the SNR threshold (FSE_SNR_TH[i]) for frequency-selective characteristic estimation, in step 715, the channel estimator can substitute 'i+1' for variable i.

[0120] If the SNR is not smaller than the SNR threshold (FSE_SNR_TH[i]) for frequency selectivity estimation, the channel estimator in step 720 can determine the frequency selectivity estimate (FSE).

[0121] In step 730, the channel estimator can assign a value of '0' to variable j.

[0122] In step 740, the channel estimator can determine whether the SNR is smaller than the SNR threshold (MA_SNR_TH[FSE][i]) for determining the moving average filter size for the determined FSE.

[0123] If SNR is less than MA_SNR_TH[FSE][i], the channel estimator in step 745 can substitute 'j+1' for variable j.

[0124] If SNR is not less than MA_SNR_TH[FSE][i], the channel estimator can set the moving average filter size in step 750.

[0125] FIGS. 8 to 11 below illustrate the results of a simulation of a performance evaluation considering 3GPP NR PUSCH transmission conditions to verify the effect of adaptively applying a frequency domain filter according to the frequency selective characteristics of the present disclosure.

[0126] The moving average filter table and the threshold value for determining frequency selectivity were optimized using the TDL-A channel with small frequency selectivity and the TDL-C channel with large frequency selectivity, as defined in the 3GPP NR standard, and can also be optimized for other channels with different delay profiles.

[0127] FIG. 8 is a diagram comparing performance based on the probability of determining a TDL-A channel as a TDL-A channel according to the signal-to-noise ratio interval when using a moving average filter according to one embodiment of the present disclosure.

[0128] FIG. 8 illustrates the simulation results comparing the performance of a method (800) that determines frequency-selective characteristics by calculating time delay values ​​in the time domain and a method (810) that adaptively applies a frequency domain filter proposed in the present disclosure.

[0129] Referring to FIG. 8, when simulating the detection probability of determining from a TDL-A channel to a TDL-A channel according to the signal-to-noise ratio interval, it can be seen that the probability in the method (810) of adaptively applying the adaptive frequency domain filter proposed in this disclosure is higher than the probability in the method (800) of determining frequency-selective characteristics by calculating time delay values ​​in the time domain. In particular, it can be confirmed that the detection performance is higher by more than 50% in the weak electric field region where the signal-to-noise ratio is low.

[0130] FIGS. 9 and 10 are diagrams comparing channel estimation performance in TDL-C channels and TDL-A channels when using a moving average filter according to one embodiment of the present disclosure.

[0131] FIGS. 9 and 10 are results of comparing the channel estimation performance of a method (900) using a fixed moving average filter in TDL-C and TDL-A channels and a method (910) using a moving average filter that determines frequency-selective characteristics and matches the channel characteristics. The moving average filter in the method (900) using a fixed moving average filter uses a filter size optimized for the TDL-C channel.

[0132] Referring to Fig. 9, it can be seen that the method (910) of determining frequency-selective characteristics in the TDL-C channel and using a moving average filter suitable for the TDL-C channel yields the same performance as the method (900) of using an optimized fixed moving average filter in the TDL-C channel.

[0133] Figure 10 is the result of comparing a method (1010) that determines frequency-selective characteristics in a TDL-A channel and uses a moving average filter suitable for a TDL-C channel, and a method (1000) that uses an optimized fixed moving average filter in a TDL-C channel.

[0134] Referring to Fig. 10, the method (1010) that determines frequency-selective characteristics and uses a moving average filter suitable for the TDL-C channel determines frequency-selective characteristics and uses a moving average filter optimized for the TDL-A channel, so it can be seen that the MSE of the channel estimation result is superior to that of the method (1000) that uses a fixed moving average filter optimized for the TDL-C channel without considering channel characteristics, up to 3dB.

[0135] FIG. 11 is a diagram comparing channel estimation performance in a TDL-C channel when using a moving average filter according to one embodiment of the present disclosure.

[0136] Figure 11 is the result of comparing a method (1100) that uses a fixed moving average filter optimized in the TDL-A channel without considering frequency selective characteristics and a method (1110) that determines frequency selective characteristics and uses a moving average filter suitable for the TDL-C channel.

[0137] Referring to Fig. 11, in the method (1110) that determines frequency-selective characteristics and uses a moving average filter suitable for the TDL-C channel, since the frequency-selective characteristics are determined and an optimized moving average filter is used in the TDL-C channel, it can be seen that the MSE of the channel estimation result is superior by more than 12dB compared to the method (1100) that uses a fixed moving average filter optimized in the TDL-A channel without considering frequency-selective characteristics.

[0138] FIG. 12 is a flowchart illustrating an example of a channel estimation operation of a receiving device according to one embodiment of the present disclosure.

[0139] In step 1200, the receiving device can estimate the receiving channel based on the received signal.

[0140] In step 1210, the receiving device can calculate the signal-to-noise ratio of the received signal.

[0141] In step 1220, the receiving device can estimate the frequency-selective characteristics of the receiving channel.

[0142] In step 1230, the receiving device can determine a moving average filter using the signal-to-noise ratio and the frequency-selective characteristics.

[0143] In step 1240, the receiving device may apply the determined moving average filter to the estimated receiving channel.

[0144] According to one aspect of the present disclosure, a method by a receiving device for estimating a channel in a wireless communication system comprises: estimating a receiving channel based on a receiving signal; determining a signal-to-noise ratio of the receiving signal; estimating a frequency-selective characteristic of the receiving channel and determining a moving average filter based on the signal-to-noise ratio and the frequency-selective characteristic; and receiving an operation of applying the determined moving average filter to the estimated receiving channel.

[0145] The operation of estimating the frequency-selective characteristic of the receiving channel further includes: an operation of determining the amount of change between the channel values ​​of the subcarriers of the receiving channel; and an operation of estimating the frequency-selective characteristic of the receiving channel based on the amount of change between the channel values.

[0146] The operation of determining the amount of change between the channel values ​​of the subcarriers of the receiving channel further includes: the operation of determining a channel average value calculated by grouping the channel values ​​of the subcarriers of the receiving channel; and the operation of determining the amount of change between the channel average values.

[0147] The number of subcarriers to group the above channel values ​​is predefined or determined based on the above signal-to-noise ratio.

[0148] Based on the fact that the above SNR is above a threshold value, the frequency-selective characteristic is estimated based on the channel average value.

[0149] The amount of change between the channel values ​​of the subcarriers of the above-mentioned receiving channel is determined based on the distance between the channel values.

[0150] Information regarding the frequency selective characteristics of the receiving channel includes at least one of: information on the amount of change between the channel values ​​of the subcarriers of the receiving channel; information indicating whether the receiving channel is a channel with a large frequency selective characteristic or a channel with a small frequency selective characteristic; or information indicating whether the average amount of change of the channel is greater than a threshold value.

[0151] The amount of change between the channel values ​​of the subcarriers of the above-mentioned receiving channel is calculated based on at least one of NMSE (normalized mean square error), MSE (mean square error), or variance.

[0152] Determining the above moving average filter includes determining the size of the above moving average filter.

[0153] Estimating the above-mentioned receiving channel includes estimating the receiving channel using the LS (least-square) method.

[0154] According to one aspect of the present disclosure, a receiving device for estimating a channel in a wireless communication system comprises: a transceiver; and a memory for storing one or more instructions, and at least one processor operably coupled to the memory, configured to execute one or more instructions stored in the memory, wherein when the one or more instructions are executed alone or together by the at least one processor, the receiving device: estimates a receiving channel based on a receiving signal, determines a signal-to-noise ratio of the receiving signal, estimates a frequency-selective characteristic of the receiving channel, determines a moving average filter based on the signal-to-noise ratio and the frequency-selective characteristic, and applies the determined moving average filter to the estimated receiving channel.

[0155] When the above one or more instructions are executed individually or collectively by the at least one processor, the receiving device: determines the amount of change between the channel values ​​of the subcarriers of the receiving channel, and estimates the frequency-selective characteristic of the receiving channel based on the amount of change between the channel values.

[0156] When the above one or more instructions are executed individually or collectively by the above at least one processor, the receiving device: causes the channel values ​​of the subcarriers of the receiving channel to be grouped and the channel average value calculated, and the channel values ​​include the channel average values.

[0157] The number of subcarriers to group the above channel values ​​is predefined or determined based on the above signal-to-noise ratio.

[0158] Based on the fact that the above SNR is above a threshold value, the frequency-selective characteristic is estimated based on the channel average value.

[0159] The amount of change between the channel values ​​of the subcarriers of the above-mentioned receiving channel is determined based on the distance between the channel values.

[0160] Information regarding the frequency selective characteristics of the receiving channel includes at least one of: information on the amount of change between the channel values ​​of the subcarriers of the receiving channel; information indicating whether the receiving channel is a channel with a large frequency selective characteristic or a channel with a small frequency selective characteristic; or information indicating whether the average amount of change of the channel is greater than a threshold value.

[0161] The amount of change between the channel values ​​of the subcarriers of the above-mentioned receiving channel is calculated based on at least one of NMSE (normalized mean square error), MSE (mean square error), or variance.

[0162] When the above one or more instructions are executed individually or collectively by the above at least one processor, the receiving device: determines the size of the moving average filter.

[0163] When the above one or more instructions are executed individually or collectively by the above at least one processor, the receiving device estimates the receiving channel using the LS (least-square) method.

[0164] According to one aspect of the present disclosure, in a non-transient computer-readable medium storing one or more instructions, the one or more instructions are executed by at least part of at least one processor of an electronic device, wherein the electronic device: estimates a receiving channel based on a receiving signal, determines a signal-to-noise ratio of the receiving signal, estimates a frequency-selective characteristic of the receiving channel, determines a moving average filter based on the signal-to-noise ratio and the frequency-selective characteristic, and applies the determined moving average filter to the estimated receiving channel.

[0165] FIG. 13 is a block diagram showing the structure of a receiving device according to one embodiment of the present disclosure.

[0166] The receiving device illustrated in FIG. 13 may include a base station that receives an uplink signal.

[0167] As illustrated in FIG. 13, the receiving device of the present disclosure may include a processor (1301), a transceiver (1302), and a memory (1303). However, the components of the receiving device are not limited to the examples described above. For example, the receiving device may include more components or fewer components than the components described above. In addition, the processor (1301), the transceiver (1302), and the memory (1303) may be implemented in the form of a single chip.

[0168] The processor (1301) can control a series of processes to enable the receiving device to operate according to the embodiments of the present disclosure described above. For example, it can control components of the receiving device (e.g., channel estimators) to perform channel estimation according to the embodiments of the present disclosure. The processor (1301) may include at least one processor, and the processor (1301) can perform the method of the present disclosure described above by executing a program stored in memory (1303).

[0169] The transceiver (1302) can transmit and receive signals with a terminal. The signals transmitted and received with the terminal may include control information and data. The transceiver (1302) may be composed of an RF transmitter that up-converts and amplifies the frequency of a transmitted signal, and an RF receiver that low-noise amplifies a received signal and down-converts the frequency. However, this is merely one embodiment of the transceiver (1302), and the components of the transceiver (1302) are not limited to an RF transmitter and an RF receiver. Additionally, the transceiver (1302) can receive a signal through a wireless channel and output it to a processor (1301), and transmit the signal output from the processor (1301) through a wireless channel.

[0170] According to one embodiment, the memory (1303) may store programs and data necessary for the operation of the receiving device. Additionally, the memory (1303) may store control information or data included in the signals transmitted and received by the receiving device. The memory (1303) may be composed of a storage medium or a combination of storage media such as ROM, RAM, a hard disk, CD-ROM, and DVD. Additionally, the memory (1303) may be a plurality of. According to one embodiment, the memory (1303) may store a program for performing the methods of the embodiments of the present disclosure described above.

[0171] Methods according to the embodiments described in the claims or specification of the present disclosure may be implemented in the form of hardware, software, or a combination of hardware and software.

[0172] When implemented in software, a computer-readable storage medium may be provided for storing one or more programs (software modules). One or more programs stored in the computer-readable storage medium are configured for execution by one or more processors within an electronic device. One or more programs include instructions that cause the electronic device to execute methods according to the embodiments described in the claims or specification of this disclosure.

[0173] Such programs (software modules, software) may be stored in random access memory, non-volatile memory including flash memory, ROM (Read Only Memory), Electrically Erasable Programmable Read Only Memory (EEPROM), magnetic disc storage devices, Compact Disc-ROM (CD-ROM), Digital Versatile Discs (DVDs), or other forms of optical storage devices, magnetic cassettes. Alternatively, they may be stored in memory composed of some or all of these. Additionally, each constituent memory may include multiple units.

[0174] Additionally, the above program may be stored on an attachable storage device that can be accessed via a communication network such as the Internet, Intranet, Local Area Network (LAN), Wide LAN (WLAN), or Storage Area Network (SAN), or a combination thereof. Such a storage device may be connected to a device performing an embodiment of the present disclosure through an external port. Additionally, a separate storage device on a communication network may be connected to a device performing an embodiment of the present disclosure.

[0175] In the specific embodiments of the present disclosure described above, the components included in the invention are expressed in a singular or plural form according to the specific embodiments presented. However, the singular or plural expression is selected to suit the situation presented for convenience of explanation, and the present disclosure is not limited to singular or plural components; even if a component is expressed in the plural form, it may be composed of a singular form, or even if a component is expressed in the singular form, it may be composed of a plural form.

[0176] Meanwhile, although specific embodiments have been described in the detailed description of the present disclosure, it is understood that various modifications are possible within the scope of the present disclosure. Therefore, the scope of the present disclosure should not be limited to the described embodiments, but should be defined by the claims set forth below as well as equivalents thereof.

Claims

1. In a receiving device for estimating a channel in a wireless communication system, Transmitter / receiver unit (1302); and It includes a memory (1303) that stores one or more instructions, and It includes at least one processor (1301) operably coupled to memory, configured to execute one or more instructions stored in the memory, and When the above one or more instructions are executed alone or together by the above at least one processor, the receiving device: Estimate the receiving channel based on the received signal, and Determine the signal-to-noise ratio of the above received signal, Estimating the frequency selective characteristics of the above receiving channel, A moving average filter is determined based on the above signal-to-noise ratio and the above frequency-selective characteristics, and A receiving device that applies the determined moving average filter to the estimated receiving channel.

2. In paragraph 1, when the one or more instructions are executed individually or collectively by the at least one processor, the receiving device: determines the amount of change between the channel values ​​of the subcarriers of the receiving channel, and A receiving device that estimates the frequency selective characteristics of the receiving channel based on the amount of change between the channel values.

3. In paragraph 2, when the one or more instructions are executed individually or collectively by the at least one processor, the receiving device: calculates a channel average value calculated by grouping the channel values ​​of the subcarriers of the receiving channel, and The above channel values ​​are a receiving device including the above channel average values.

4. A receiving device according to either of paragraphs 2 and 3, wherein the number of subcarriers to group the channel values ​​is predetermined or determined based on the signal-to-noise ratio.

5. In Paragraph 3, A receiving device in which the frequency selective characteristic is estimated based on the channel average value, based on the fact that the above SNR is above a threshold value.

6. In either Paragraph 2 or Paragraph 3, A receiving device in which the amount of change between the channel values ​​of the subcarriers of the above receiving channel is determined based on the distance between the channel values.

7. In paragraph 1, information regarding the frequency selective characteristics of the receiving channel is, Information on the amount of change between the channel values ​​of the subcarriers of the above-mentioned receiving channel, Information indicating whether the above receiving channel is a channel with high frequency selectivity or a channel with low frequency selectivity, or A receiving device comprising at least one of information indicating whether the average change amount of the above channel is greater than a threshold value.

8. A receiving device according to paragraph 2, wherein the amount of change between channel values ​​of subcarriers of the receiving channel is calculated based on at least one of NMSE (normalized mean square error), MSE (mean square error), or variance.

9. In paragraph 1, the receiving device: when the one or more instructions are executed individually or collectively by the at least one processor, the receiving device determines the size of the moving average filter.

10. In claim 1, the receiving device, wherein the one or more instructions, when executed individually or collectively by the at least one processor, cause the receiving device to estimate the receiving channel using the least-square (LS) method.

11. A method for estimating the channel of a receiving device in a wireless communication system, A process of estimating the reception channel based on the received signal; A process for determining the signal-to-noise ratio of the above-mentioned received signal; A process of estimating the frequency-selective characteristics of the above-mentioned receiving channel; A process for determining a moving average filter based on the above signal-to-noise ratio and the above frequency-selective characteristics; and A method comprising the process of applying the determined moving average filter to the estimated receiving channel.

12. In paragraph 11, the process of estimating the frequency-selective characteristics of the receiving channel is, A process for determining the amount of change between the channel values ​​of the subcarriers of the above-mentioned receiving channel; and A method further comprising the process of estimating the frequency-selective characteristics of the receiving channel based on the amount of change between the channel values.

13. In paragraph 12, the process of determining the amount of change between the channel values ​​of the subcarriers of the receiving channel is, A process of determining a channel average value calculated by grouping the channel values ​​of the subcarriers of the above-mentioned receiving channel; and A method further comprising a process for determining the amount of change between the average values ​​of the above channels.

14. A method in which, in either one of claims 12 and 13, the number of subcarriers to group the channel values ​​is predetermined or determined based on the signal-to-noise ratio.

15. In a non-transient computer-readable medium storing one or more instructions, wherein the one or more instructions are executed by at least part of at least one processor (1301) of an electronic device, the electronic device: Estimate the receiving channel based on the received signal, and Determine the signal-to-noise ratio of the above received signal, Estimating the frequency selective characteristics of the above receiving channel, A moving average filter is determined based on the above signal-to-noise ratio and the above frequency-selective characteristics, and A non-transient computer-readable medium that applies the determined moving average filter to the estimated receiving channel.

Images