CN115065579B - Channel estimation method, device, electronic equipment and storage medium - Google Patents
Channel estimation method, device, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN115065579B CN115065579B CN202210887101.XA CN202210887101A CN115065579B CN 115065579 B CN115065579 B CN 115065579B CN 202210887101 A CN202210887101 A CN 202210887101A CN 115065579 B CN115065579 B CN 115065579B
- Authority
- CN
- China
- Prior art keywords
- sub
- block
- channel estimation
- data
- frequency domain
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/0202—Channel estimation
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0413—MIMO systems
- H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Power Engineering (AREA)
- Radio Transmission System (AREA)
Abstract
The application provides a channel estimation method, a channel estimation device, electronic equipment and a storage medium. When a receiving end performs channel estimation, the orthogonality between channels is destroyed due to the difference of sub-band precoding, which results in the degradation of channel estimation performance. In the method, on the basis of the existing time domain channel estimation scheme, the sub-band precoding characteristic of a transmitting terminal is introduced into channel estimation, and the influence of different precoding of the transmitting terminal on the channel estimation is eliminated by performing inverse processing of precoding processing of the transmitting terminal on an initial channel estimation value, so that the performance of the whole channel estimation is improved, and the demodulation performance of a receiving terminal is optimized.
Description
Technical Field
The present application relates to wireless communication technologies, and in particular, to a channel estimation method and apparatus, an electronic device, and a storage medium.
Background
With the increasing demand of wireless services, MIMO (Multiple Input Multiple Output) technology is applied well in NR (New Radio) systems. However, in the MIMO technology, multiple transmit antennas of a transmitter transmit multiple data streams to the same user, which may cause interference between the data streams. For this reason, a precoding technique is adopted in the 5G NR system. The precoding technology adapts to different channel environments by utilizing channel information to carry out preprocessing at a transmitting end, eliminates interference among a plurality of data streams and improves the reliability of a system.
Precoding of data shared channels by 5G NR systems defines two configurations: full-band based precoding and sub-band based precoding. Based on the precoding of the whole band, choose the same suitable precoding matrix to process for the data of the whole bandwidth of transmitting terminal; the sub-band based precoding is to divide the data of the full bandwidth of the transmitting end into sub-bands, the size of the RB (Resource block, frequency domain Resource block) of the sub-band division is selected according to the specification, and then a suitable precoding matrix is selected for each sub-band to process.
Since the noise of the channel and the multipath fading in the wireless communication system affect the correctness of the signal processing of the receiver, it is necessary to perform channel estimation by using a channel estimation algorithm for channel compensation. However, in the subband-based precoding scenario, orthogonality between channels is destroyed due to different subband precoding, so that performance of channel estimation is degraded and demodulation performance is deteriorated.
Disclosure of Invention
In order to solve the problem of performance degradation of channel estimation at a receiving end due to different sub-band pre-coding performed at a transmitting end, embodiments of the present application provide a channel estimation method, apparatus, electronic device, and storage medium.
In a first aspect, an embodiment of the present application provides a channel estimation method, which is applied to a receiving end in a 5G NR system, where a transmitting end of the 5G NR system performs different precoding on each subband by dividing the subband, and different subbands are configured with different precoding matrices, and the method includes: performing channel estimation on the received frequency domain data to obtain an initial frequency domain channel estimation value; dividing the initial frequency domain channel estimation value into N first sub-blocks, wherein N is the number of sub-bands, each first sub-block corresponds to one sub-band, and different first sub-blocks correspond to different sub-bands; processing the first sub-blocks and an inverse matrix of a pre-coding matrix configured for the sub-band corresponding to each first sub-block to obtain intermediate processing data of each first sub-block; denoising the intermediate processing data of each first sub-block to obtain optimized data; dividing the optimized data into N second sub-blocks, wherein each second sub-block corresponds to one sub-band, and different second sub-blocks correspond to different sub-bands; restoring the optimized data of each second sub-block into the optimized frequency domain channel estimation value corresponding to each second sub-block by utilizing the pre-coding matrix configured to the sub-band corresponding to each second sub-block; and determining a target channel estimation value according to the optimized frequency domain channel estimation value corresponding to each second sub-block.
In a possible embodiment, processing an inverse matrix of a precoding matrix configured for each first sub-block and a subband corresponding to each first sub-block includes: and for each first sub-block, multiplying the inverse matrix of the pre-coding matrix configured for the sub-band corresponding to the first sub-block by the first sub-block, and determining the intermediate processing data of the first sub-block according to the calculation result.
In a possible embodiment, denoising the intermediate processing data of each first sub-block to obtain optimized data includes: arranging the intermediate processing data of each first sub-block according to the original position of each first sub-block, and transforming the arranged data from a frequency domain to a time domain to obtain a time domain channel estimation value; and carrying out windowing and denoising on the time domain channel estimation value, and transforming the data subjected to windowing and denoising from the time domain to the frequency domain to obtain the optimized data.
In a possible embodiment, the restoring the optimized data of each second sub-block to the optimized frequency domain channel estimation value corresponding to each second sub-block by using the precoding matrix configured for the sub-band corresponding to each second sub-block includes: and for each second sub-block, multiplying the precoding matrix configured for the sub-band corresponding to the second sub-block by the second sub-block, and determining the optimized frequency domain channel estimation value corresponding to the second sub-block according to the calculation result.
In a possible embodiment, the frequency domain data comprises at least reference data comprising a plurality of symbols located at different frequency domain positions; the target channel estimation value corresponds to a plurality of symbols at different frequency domain positions in the reference data; the method further comprises the following steps: and carrying out interpolation operation on the target channel estimation values of a plurality of symbols corresponding to different frequency domain positions in the reference data, and obtaining the target channel estimation values corresponding to all symbols at all frequency domain positions in the frequency domain data according to the operation result.
In a second aspect, an embodiment of the present application provides a channel estimation apparatus, which is applied to a receiving end in a 5G NR system, where a transmitting end of the 5G NR system performs different precoding on each subband by dividing the subband, and different subbands are configured with different precoding matrices, and the apparatus includes: an initial channel estimation unit, configured to perform channel estimation on the received frequency domain data to obtain an initial frequency domain channel estimation value; a first processing unit to: dividing the initial frequency domain channel estimation value into N first sub-blocks, wherein N is the number of sub-bands, each first sub-block corresponds to one sub-band, and different first sub-blocks correspond to different sub-bands; processing the first sub-blocks and an inverse matrix of a pre-coding matrix configured for the sub-band corresponding to each first sub-block to obtain intermediate processing data of each first sub-block; the de-noising unit is used for de-noising the intermediate processing data of each first sub-block to obtain optimized data; and a second processing unit for: dividing the optimized data into N second sub-blocks, wherein each second sub-block corresponds to one sub-band, and different second sub-blocks correspond to different sub-bands; restoring the optimized data of each second sub-block into the optimized frequency domain channel estimation value corresponding to each second sub-block by utilizing the pre-coding matrix configured to the sub-band corresponding to each second sub-block; and determining a target channel estimation value according to the optimized frequency domain channel estimation value corresponding to each second sub-block.
In a possible implementation manner, when processing an inverse matrix of a precoding matrix configured for each first sub-block and a subband corresponding to each first sub-block, the first processing unit is specifically configured to: and aiming at each first sub-block, multiplying the inverse matrix of the pre-coding matrix configured for the sub-band corresponding to the first sub-block by the first sub-block, and determining the intermediate processing data of the first sub-block according to the calculation result.
In a possible implementation manner, when denoising the intermediate processing data of each first sub-block to obtain the optimized data, the denoising unit is specifically configured to: arranging the intermediate processing data of each first sub-block according to the original position of each first sub-block, and transforming the arranged data from a frequency domain to a time domain to obtain a time domain channel estimation value; and carrying out windowing denoising on the time domain channel estimation value, and transforming the data subjected to windowing denoising from the time domain to the frequency domain to obtain the optimized data.
In a possible embodiment, when the second processing unit restores the optimized data of each second sub-block to the optimized frequency domain channel estimation value corresponding to each second sub-block by using the precoding matrix configured for the sub-band corresponding to each second sub-block, the second processing unit is specifically configured to: and for each second sub-block, multiplying the precoding matrix configured for the sub-band corresponding to the second sub-block by the second sub-block, and determining the optimized frequency domain channel estimation value corresponding to the second sub-block according to the calculation result.
In a third aspect, embodiments provide an electronic device comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor, the processor being caused by the machine-executable instructions to: the steps of the above method are implemented.
In a fourth aspect, embodiments of the present application provide a machine-readable storage medium having stored therein machine-executable instructions that, when executed by a processor, implement the steps of any of the above-described methods.
According to the technical scheme, the precoding characteristic of the transmitting end is introduced into channel estimation, and the influence on the whole channel estimation due to different precoding of each sub-band is eliminated by carrying out an inverse process reduction on the initial channel estimation value according to the sub-band precoding processing executed by the transmitting end. Compared with the conventional channel estimation scheme, the method can avoid the problems such as peak leakage of a PDP (Power delay profile), and the like, so that the demodulation performance is greatly improved.
Drawings
Fig. 1 is a schematic flow chart of a channel estimation method according to an embodiment of the present application.
Fig. 2 illustrates an example of sub-block division of initial channel estimation values in the channel estimation method according to fig. 1.
Fig. 3 is a schematic flow chart diagram of a channel estimation method according to an embodiment of the present application.
Fig. 4 is a schematic block diagram of a channel estimation apparatus according to an embodiment of the present application.
Fig. 5 is a schematic hardware structure diagram of a channel estimation apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Fig. 1 shows a schematic flow chart of a channel estimation method according to an embodiment of the application. The channel estimation method can be applied to a scene that a transmitting end carries out different pre-coding on a data sharing channel by dividing sub-bands. In this scenario, different subbands may be configured with different precoding matrices. The method can be applied to a receiving end in a 5G NR system, and the receiving end can be any terminal, server, electronic equipment and the like with wireless signal receiving capability.
As shown in fig. 1, the channel estimation method includes the following steps 101 to 106.
Step 101, performing channel estimation on the received frequency domain data to obtain an initial frequency domain channel estimation value.
After receiving data through a wireless communication channel, a receiving end may perform time-frequency domain conversion on the received data, and then perform channel estimation on the obtained frequency domain data to obtain an initial frequency domain channel estimation value.
In the embodiment of the present application, the channel estimation may adopt time domain based channel estimation, frequency domain based channel estimation, transform domain based channel estimation, and the like. Common channel estimation calculation methods include, for example, LS (Least Square) and MMSE (minimum-Mean Square Error) algorithms, which are not limited in this application.
And 102, dividing the initial frequency domain channel estimation value into N first sub-blocks, wherein N is the number of sub-bands, each first sub-block corresponds to one sub-band, and different first sub-blocks correspond to different sub-bands.
The receiving end may divide the initial channel estimation value obtained in step 101 into N first sub-blocks according to a sub-band resource dividing manner of the transmitting end, where N is the number of sub-bands, each first sub-block corresponds to one sub-band, and different first sub-blocks correspond to different sub-bands.
For example, if the size of the sub-band resource block RB for sub-band resource division at the transmitting end is represented by SizeTotalRB and the size of the total RB allocated to the user is represented by SizeTotalRB, the number of first sub-blocks N = SizeTotalRB/sizetorb. The size of the sub-band resource block RB may be determined by the receiving end according to user configuration information.
The user configuration information is control information related to resource allocation, source coding, channel access, data transmission, and the like, and may be different according to different user requirements. If the receiving end is located at the eNode side, the user configuration information is predefined by the eNode; if the receiving end is located at the UE side, the user configuration information is signaled from the eNode to the UE. That is, the user configuration information is known to the receiving end.
Fig. 2 shows an example of sub-block division of the initial channel estimation values in step 102. As shown in fig. 2, the sub-band resource division at the transmitting end is consistent with the sub-block division at the receiving end for the initial channel estimation value
Can be divided into N sub-blocks
And each divided sub-block corresponds to one sub-band, and each sub-band is configured with a precoding matrix.
In step 103, processing the first sub-blocks and the inverse matrix of the precoding matrix configured for the sub-band corresponding to each first sub-block to obtain intermediate processing data of each first sub-block; this processing is performed to eliminate the receiver estimation error due to the difference in the transmitter precoding.
The main principle of precoding is to design a precoding matrix to process a transmission signal by using known channel state information, so as to decompose user data into parallel data streams to realize interference removal.
The 5G NR system defines two precoding modes, namely codebook-based precoding and non-codebook-based precoding. The codebook is a set of a finite number of precoding matrices. Based on codebook precoding, a transmitting terminal and a receiving terminal share a set of codebook, the receiving terminal selects the most appropriate codebook according to channel characteristics, the serial number is fed back to the transmitting terminal, and the transmitting terminal performs precoding on transmitting data by using the corresponding codebook. The precoding based on the non-codebook generally utilizes reciprocity of a channel, and a transmitting terminal directly processes the channel matrix after acquiring the channel matrix to obtain a precoding matrix and precode transmitting data.
It should be understood that in the embodiment of the present application, the precoding matrix used by the transmitting end for precoding is known by the receiving end. The receiving end may extract information related to the precoding matrix from the user configuration information.
In the embodiment of the present application, the precoding characteristic of the transmitting end is introduced into the channel estimation of the receiving end. In step 103, by processing the inverse matrix of the precoding matrix configured for each first sub-block and the sub-band corresponding to the first sub-block, the estimation error of the receiving end due to different precoding of the transmitting end can be eliminated. Specific implementation of this "processing" will be described in detail in the following embodiments.
And 104, denoising the intermediate processing data of each first sub-block to obtain optimized data.
The receiving end denoises the intermediate processing data of each first sub-block obtained in step 103. In the embodiment of the present application, the "denoising" process is a generic term of a series of channel processes for performing channel optimization, and does not exclude other processes than the "denoising" process in a narrow sense. In the following embodiments, specific implementations of this "denoising" process are described.
And 105, dividing the optimized data into N second sub-blocks, wherein each second sub-block corresponds to one sub-band, and different second sub-blocks correspond to different sub-bands.
The receiving end may divide the optimized data obtained in step 104 into N second sub-blocks corresponding to the N first sub-blocks, where each second sub-block corresponds to one sub-band, and different second sub-blocks correspond to different sub-bands. That is, the N second sub-blocks are divided in the same manner as the N first sub-blocks, and both correspond to the sub-band resource division at the transmitting end.
106, restoring the optimized data of each second sub-block into the optimized frequency domain channel estimation value corresponding to each second sub-block by using the pre-coding matrix configured to the sub-band corresponding to each second sub-block; and determining a target channel estimation value according to the optimized frequency domain channel estimation value corresponding to each second sub-block.
The receiving end firstly processes the initial channel estimation value by utilizing the inverse matrix of the precoding matrix configured for the sub-band corresponding to each sub-block, eliminates the influence of the precoding of the transmitting end on the subsequent channel processing, and then performs channel optimization, thereby improving the performance of the whole channel estimation. However, since the receiving end performs channel estimation by using the precoded data, after the channel optimization (e.g., denoising) is completed, it is necessary to perform a precoding reduction on the optimized data by using the precoding matrix to recover the precoding property of the channel matrix.
In step 106, the receiving end may recover the optimized data of each second sub-block to the optimized frequency domain channel estimation value corresponding to each second sub-block by using the precoding matrix configured for the sub-band corresponding to each second sub-block. And then, determining a target channel estimation value according to the optimized frequency domain channel estimation value corresponding to each second sub-block. For example, the optimized frequency domain channel estimation values corresponding to the second sub-blocks may be arranged according to the original positions of the second sub-blocks, so as to obtain the target channel estimation value.
In some examples, processing the inverse matrix of the precoding matrix configured for each first sub-block and the subband corresponding to each first sub-block in step 103 above includes:
and aiming at each first sub-block, multiplying the inverse matrix of the pre-coding matrix configured for the sub-band corresponding to the first sub-block by the first sub-block, and determining the intermediate processing data of the first sub-block according to the calculation result.
The receiving end can obtain the precoding matrix adopted by the transmitting end for each subband according to the user configuration information
Inverting all the precoding matrixes to obtain precoding inverse matrixes
. For each first sub-block, the inverse matrix of the precoding matrix configured for the sub-band corresponding to the first sub-block may be multiplied by the first sub-block in the frequency domain to obtain a calculation result, and then the intermediate processing data of the first sub-block may be determined according to the calculation result
For example, the calculation result may be directly used as the intermediate processing data of the first sub-block, or the calculation result may be further processed, and the processed result may be used as the intermediate processing data of the first sub-block. For example, the calculation result is multiplied by a constant, etc., and the present application does not limit the processing. In this way, the influence of the difference of sub-band precoding on the channel estimation value can be eliminated.
In some examples, denoising the intermediate processed data of each first sub-block in the step 104 to obtain optimized data includes:
arranging the intermediate processing data of each first sub-block according to the original position of each first sub-block, and transforming the arranged data from a frequency domain to a time domain to obtain a time domain channel estimation value;
and carrying out windowing and denoising on the time domain channel estimation value, and transforming the data subjected to windowing and denoising from the time domain to the frequency domain to obtain the optimized data.
The receiving end arranges the intermediate processing data of the N first sub-blocks according to the original positions of the N first sub-blocks to obtain an integral channel estimation value
And N is a natural number from 1 to N. Then, the receiving end can estimate the entire channel
Performing discrete inverse Fourier transform (IDFT) or fast inverse Fourier transform (IFFT) to obtain the channel estimation value
Transforming from frequency domain to time domain to obtain time domain channel estimate
。
Because the precoding matrix adopted by the transmitting end for each subband is different, the orthogonality of the channel is destroyed, and if the data is directly subjected to IDFT or IFFT transformation, the peak leakage of the PDP of the whole bandwidth is easily caused. However, according to the channel estimation method in the embodiment of the present application, before the data is subjected to IDFT or IFFT transformation, the influence of the difference of the precoding matrix on the channel processing is already eliminated, and the performance of the subsequent denoising processing is optimized.
There are various ways to perform windowing and denoising on the time domain channel estimation value, for example, a signal in a window may be retained, and all signals outside the window are set to zero, or an optimized scheme may be adopted, and a signal smaller than a threshold in the window is also set to zero to remove noise in the window.
And after windowing and denoising the time domain channel estimation value, the receiving end converts the windowed and denoised data from the time domain to the frequency domain again to obtain the optimized data.
The above only describes the way of denoising in time domain, but the difference of sub-band precoding will also have the same effect on denoising in frequency domain. If the denoising of the intermediate processing data of each first sub-block in step 104 is performed in the frequency domain, after the influence of sub-band precoding is eliminated by the above channel estimation method, the intermediate processing data does not need to be subjected to frequency domain-time domain and time domain-frequency domain conversion, but is directly subjected to denoising in the frequency domain by, for example, wiener filtering, and then the processing of step 105 is performed on the denoised data.
The "denoising" process mentioned in this document represents only a broad channel optimization process, and is not limited to the above description, and many other embodiments are possible.
In some examples, in step 106, restoring the optimized data of each second sub-block to the optimized frequency-domain channel estimation value corresponding to each second sub-block by using the precoding matrix configured for the sub-band corresponding to each second sub-block includes:
and for each second sub-block, multiplying the precoding matrix configured for the sub-band corresponding to the second sub-block by the second sub-block, and determining the optimized frequency domain channel estimation value corresponding to the second sub-block according to the calculation result.
For example, the optimization data obtained in step 104 may be used
Show that
Sub-block division to obtain N second sub-blocks
. And for each second sub-block, multiplying the precoding matrix configured for the sub-band corresponding to the second sub-block by the second sub-block to obtain a calculation result, and determining the optimized frequency domain channel estimation value corresponding to the second sub-block according to the calculation result. For example, the calculation result may be directly used as the optimized frequency-domain channel estimation value of the second sub-block, or the calculation result may be further processed, and the processed result may be used as the optimized frequency-domain channel estimation value of the second sub-block. For example, the calculation result is multiplied by a constant, etc., and the present application does not limit the processing.
In some examples, the frequency domain data includes at least reference data, the reference data includes a plurality of symbols located at different frequency domain positions, the target channel estimation value corresponds to the plurality of symbols located at different frequency domain positions in the reference data, and the channel estimation method further includes:
and carrying out interpolation operation on the target channel estimation values of a plurality of symbols corresponding to different frequency domain positions in the reference data, and obtaining the target channel estimation values corresponding to all symbols at all frequency domain positions in the frequency domain data according to the operation result.
In a specific implementation, the channel estimation of the receiving end on the received frequency domain data can be realized by the channel estimation of the reference data. The reference data functions as a pilot signal, and can be used for measurement of channel state information, channel measurement, data demodulation, beam training, time-frequency parameter tracking, and the like. The reference data includes a plurality of symbols located at different frequency domain locations. The frequency domain position corresponds to a specific subcarrier position, and bit information contained in one symbol is determined by a specifically adopted modulation-demodulation mechanism. The target channel estimate corresponds to a plurality of symbols at different frequency domain locations in the reference data. By performing interpolation operation on the target channel estimation values of a plurality of symbols corresponding to different frequency domain positions in the reference data, the target channel estimation values corresponding to all symbols at all frequency domain positions allocated to the user can be obtained according to the operation result. The interpolation process includes employing both time domain interpolation and frequency domain interpolation. The operation result obtained by the interpolation operation may be directly used as the final target channel estimation value, or the operation result obtained by the interpolation operation may be further optimized, and the obtained optimization processing result is used as the final target channel estimation value, and the implementation of the optimization processing is related to a specific application, and is not limited in the present application.
In some examples, channel estimating the received frequency domain data in step 101 to obtain the initial channel estimate comprises:
and extracting reference data from the received frequency domain data, and performing conjugate multiplication on the extracted reference data and the reference data locally and pre-stored by the receiving end in a frequency domain to obtain the initial channel estimation value.
Assuming that the locally pre-stored reference data is represented by A, the extracted reference data is represented by B, and the channel between the transmitting end and the receiving end is represented by H, A, B and H satisfy the relation:
A˙H = B … （1）
ideally, the reference data B received by the receiving end should be identical to the pre-stored reference data a. However, in practice, due to the influence of channel fading and the like, the data received by the receiving end is deviated from the original data, and therefore, it is necessary to estimate the channel. According to the existing channel estimation algorithm, such as LS algorithm, MMSE algorithm, etc., the original data and the channel matrix are frequency domain multiplied, as shown in the above equation (1). Therefore, the value H is obtained as the channel estimation. By multiplying both the left and right of equation (1) by the conjugate a of the reference data a, (a) H = a B can be obtained. In a specific implementation, the amplitude of a is normalized so that a modulo 1 is obtained, and the a B results are the results of the channel estimation.
Up to this point, the description of the channel estimation method shown in fig. 1 is completed.
In subband-based precoding, orthogonality between channels is destroyed due to different precoding of each subband, resulting in degraded performance of channel estimation. By adopting the channel estimation method shown in fig. 1, the initial channel estimation value can be restored in an inverse process according to the sub-band precoding processing executed by the transmitting end, thereby eliminating the influence on the whole channel estimation due to different precoding of each sub-band. Compared with the conventional channel estimation scheme, the method can avoid the problems such as peak leakage of a PDP (Power delay profile), and the like, so that the demodulation performance is greatly improved.
Fig. 3 shows a schematic flow chart of a channel estimation method according to an embodiment of the present application in a 5G NR application scenario. The channel estimation method can be applied to a receiver at the UE side for downlink channel estimation, and can also be applied to a receiver at the eNode side for uplink channel estimation.
In step 301, the receiving end extracts reference data at a position corresponding to the DMRS from the received frequency domain data, and obtains an initial frequency domain channel estimation value by applying an LS estimation algorithm.
In the 5G NR system, a receiving end may extract reference data of a position corresponding to a DMRS from frequency-domain data received via a reference channel. The reference channel is divided into an uplink reference channel and a downlink reference channel, which are different from a data channel for transmitting user data. Common reference signals include SRS (uplink sounding reference signal), DMRS (demodulation reference signal), DRS (demodulation reference signal), CRS (cell reference signal), and the like. In the embodiments of the present application, the channel estimation method is explained with an example in which DMRS is used as reference data.
The receiving end may apply an LS estimation algorithm to the data at the position corresponding to the extracted DMRS to obtain an initial frequency domain channel estimation value. Namely, the data of the extracted corresponding position of the DMRS is subjected to conjugate multiplication with the locally stored DMRS data to obtain the frequency domain channel estimation values of all symbols and subcarriers of the DMRS position
。
In step 302, the receiving end obtains the size of each sub-band resource and the pre-coding matrix corresponding to each sub-band according to the user configuration information, and multiplies the sub-band corresponding to the initial frequency domain channel estimation value by the corresponding pre-coding inverse matrix.
The receiving end can obtain the size of each sub-band resource divided by precoding at the transmitting end and a precoding matrix corresponding to each sub-band according to the user configuration information. Therefore, the frequency domain channel estimation value can be divided according to the same division mode
Divided into N blocks of sub-bands
And the number of N is the size of the total sub-band resource distributed by the user divided by the size of each sub-band resource. Precoding matrix applied simultaneously to each sub-band
Inverting to obtain precodingInverse matrix
. Multiplying the N blocks of frequency domain channel estimation values by the N blocks of precoding inverse matrixes respectively to obtain N blocks of optimized frequency domain channel estimation values
。
In the formula (I), the compound is shown in the specification,
。
placing the N optimized frequency domain channel estimation values according to the original positions before blocking to obtain an integral frequency domain channel estimation value
Therefore, the influence of different sub-band precoding on the channel estimation value is eliminated.
In step 303, the frequency domain channel estimation value is IFFT transformed to obtain a time domain channel estimation value.
In step 304, denoising is performed on the time domain channel estimation value to obtain a denoised time domain channel estimation value.
The receiving end performs IFFT on the frequency domain channel estimation value obtained after the step 302 is executed, and obtains a time domain channel estimation value
. Then, estimating the time domain channel
De-noising to obtain de-noised time domain channel estimation value
。
The common time domain denoising scheme is windowing denoising, a simple denoising scheme can adopt signal retention in a window, signals outside the window are all set to be zero, an optimized scheme can also be adopted, and signals smaller than a threshold in the window are also set to be zero to remove noise in the window.
In step 305, FFT transformation is performed on the denoised time domain channel estimation value to obtain the denoised frequency domain channel estimation value.
Time domain channel estimation value after denoising at receiving end
FFT is carried out to obtain a denoised frequency domain channel estimation value
。
In step 306, the sub-band corresponding to the denoised frequency domain channel estimation value is multiplied by the corresponding pre-coding matrix to obtain the restored DMRS frequency domain channel estimation value.
The frequency domain channel estimation value is divided into blocks according to the sub-band in step 302
Divided into N blocks of sub-bands
The N blocks of frequency domain channel estimation values are precoded and restored, namely, the N blocks of frequency domain channel estimation values are multiplied by N precoding matrixes respectively
Obtaining N restored frequency domain channel estimated values
。
In the formula (I), the compound is shown in the specification,
。
placing the frequency domain channel estimation values restored by the N blocks according to the original positions before blocking, thereby obtaining the frequency domain channel estimation values of the positions of the symbols and the subcarriers where the DMRS is positioned
。
In step 307, time domain and frequency domain interpolation is performed on the DMRS frequency domain channel estimation value to obtain channel estimation values corresponding to all symbols at all frequency domain positions allocated to the user.
And the receiving end performs time domain and frequency domain interpolation on the channel estimation values of the positions of the symbols where the DMRS are located and the frequency domain subcarriers, so as to obtain the channel estimation values corresponding to all the symbols on all the frequency domain positions allocated by the user.
The channel estimation method proposed by the present application is described above with reference to specific embodiments. The channel estimation method is optimized on a conventional time domain channel estimation scheme, before an initial channel estimation value is transformed from a frequency domain to a time domain through IFFT to be denoised, the initial channel estimation value is restored in an inverse process according to the sub-band precoding processing of a transmitting end, namely, the sub-band corresponding to the receiving end is multiplied by the inverse of a precoding matrix according to the precoding matrix corresponding to each sub-band of the transmitting end, so that the influence of each sub-band when different precoding matrices are adopted to directly carry out IFFT on the whole channel estimation value is eliminated. Because the technical scheme avoids the problem of PDP leakage caused by directly carrying out IFFT, compared with the conventional time domain channel estimation scheme, the demodulation performance is greatly improved.
The channel estimation method according to the embodiment of the present application is described above, and the channel estimation device according to the embodiment of the present application is described below.
Referring to fig. 4, fig. 4 is a structural diagram of an apparatus provided in the embodiment of the present application. The apparatus corresponds to the method flow shown in fig. 1, and can be applied to a receiving end of a 5G NR system, where a transmitting end of the 5G NR system performs different precoding for each subband by dividing the subband, and different subbands are configured with different precoding matrices.
As shown in fig. 4, the apparatus may include:
an initial channel estimation unit 401, configured to perform channel estimation on the received frequency domain data to obtain an initial frequency domain channel estimation value;
a first processing unit 402, configured to divide the initial frequency domain channel estimation value into N first sub-blocks, where N is the number of sub-bands, each first sub-block corresponds to one sub-band, and different first sub-blocks correspond to different sub-bands; processing the first sub-blocks and an inverse matrix of a pre-coding matrix configured for the sub-band corresponding to each first sub-block to obtain intermediate processing data of each first sub-block; the processing is used for eliminating receiving end estimation errors caused by different precoding of the transmitting end;
a denoising unit 403, configured to denoise the intermediate processing data of each first sub-block to obtain optimized data; and
a second processing unit 404, configured to divide the optimized data into N second sub-blocks, where each second sub-block corresponds to one sub-band, and different second sub-blocks correspond to different sub-bands; restoring the optimized data of each second sub-block into the optimized frequency domain channel estimation value corresponding to each second sub-block by utilizing the pre-coding matrix configured to the sub-band corresponding to each second sub-block; and determining a target channel estimation value according to the optimized frequency domain channel estimation value corresponding to each second sub-block.
In some examples, when processing the inverse matrix of the precoding matrix configured for each first sub-block and the subband corresponding to each first sub-block, the first processing unit 402 is specifically configured to: and aiming at each first sub-block, multiplying the inverse matrix of the pre-coding matrix configured for the sub-band corresponding to the first sub-block by the first sub-block, and determining the intermediate processing data of the first sub-block according to the calculation result.
In some examples, the denoising unit 403, when denoising the intermediate processing data of each first sub-block to obtain optimized data, is specifically configured to: arranging the intermediate processing data of each first sub-block according to the original position of each first sub-block, and transforming the arranged data from a frequency domain to a time domain to obtain a time domain channel estimation value; and carrying out windowing and denoising on the time domain channel estimation value, and transforming the data subjected to windowing and denoising from the time domain to the frequency domain to obtain the optimized data.
In some examples, when the precoding matrix configured for the sub-band corresponding to each second sub-block is used to restore the optimized data of each second sub-block to the optimized frequency domain channel estimation value corresponding to each second sub-block, the second processing unit 404 is specifically configured to: and for each second sub-block, multiplying the precoding matrix configured for the sub-band corresponding to the second sub-block by the second sub-block, and determining the optimized frequency domain channel estimation value corresponding to the second sub-block according to the calculation result.
In some examples, the frequency domain data includes at least reference data including a plurality of symbols at different frequency domain locations, the target channel estimate corresponds to the plurality of symbols at the different frequency domain locations in the reference data, the apparatus further includes: and the interpolation unit is used for carrying out interpolation operation on the target channel estimation values of a plurality of symbols corresponding to different frequency domain positions in the reference data and obtaining the target channel estimation values corresponding to all symbols at all frequency domain positions in the frequency domain data according to the operation result.
The embodiment of the application also provides a hardware structure of the channel estimation device. Referring to fig. 5, fig. 5 is a structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 5, the hardware structure may include: a processor 501 and a machine-readable storage medium 502 storing machine-executable instructions executable by the processor; the processor 501 is configured to execute machine-executable instructions to implement the methods disclosed in the above examples of the present application.
Based on the same application concept as the method, the embodiment of the present application further provides a machine-readable storage medium, where several computer instructions are stored, and when the computer instructions are executed by a processor, the method disclosed in the above example of the present application can be implemented.
The machine-readable storage medium may be, for example, any electronic, magnetic, optical, or other physical storage device that can contain or store information such as executable instructions, data, and the like. For example, the machine-readable storage medium may be: RAM (random Access Memory), volatile Memory, non-volatile Memory, flash Memory, a storage drive (e.g., a hard drive), a solid state drive, any type of storage disk (e.g., an optical disk, a dvd, etc.), or similar storage medium, or a combination thereof.
The apparatuses, modules or units illustrated in the above embodiments may be specifically implemented by a computer chip or an entity, or implemented by a product with certain functions. For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, apparatus, electronic device, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Furthermore, these computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (11)
1. A channel estimation method is applied to a receiving end in a 5G new air interface NR system, wherein a transmitting end of the 5G NR system performs different precoding on each subband by dividing the subband, and different subbands are configured with different precoding matrices, and the method comprises the following steps:
performing channel estimation on the received frequency domain data to obtain an initial frequency domain channel estimation value;
dividing the initial frequency domain channel estimation value into N first sub-blocks, wherein N is the number of sub-bands, each first sub-block corresponds to one sub-band, and different first sub-blocks correspond to different sub-bands; processing the first sub-blocks and an inverse matrix of a pre-coding matrix configured for the sub-band corresponding to each first sub-block to obtain intermediate processing data of each first sub-block;
denoising the intermediate processing data of each first sub-block to obtain optimized data;
dividing the optimized data into N second sub-blocks, wherein each second sub-block corresponds to one sub-band, and different second sub-blocks correspond to different sub-bands; restoring the optimized data of each second sub-block into the optimized frequency domain channel estimation value corresponding to each second sub-block by utilizing the pre-coding matrix configured to the sub-band corresponding to each second sub-block; and determining a target channel estimation value according to the optimized frequency domain channel estimation value corresponding to each second sub-block.
2. The method of claim 1, wherein processing an inverse matrix of a precoding matrix configured for each first sub-block and the sub-band corresponding to each first sub-block comprises:
and for each first sub-block, multiplying the inverse matrix of the pre-coding matrix configured for the sub-band corresponding to the first sub-block by the first sub-block, and determining the intermediate processing data of the first sub-block according to the calculation result.
3. The method of claim 1, wherein de-noising the intermediate processed data of each first sub-block to obtain optimized data comprises:
arranging the intermediate processing data of each first sub-block according to the original position of each first sub-block, and transforming the arranged data from a frequency domain to a time domain to obtain a time domain channel estimation value;
and carrying out windowing and denoising on the time domain channel estimation value, and transforming the data subjected to windowing and denoising from the time domain to the frequency domain to obtain the optimized data.
4. The method of claim 1, wherein the recovering the optimized data of each second sub-block into the optimized frequency-domain channel estimation value corresponding to each second sub-block by using the precoding matrix configured for the sub-band corresponding to each second sub-block comprises:
and for each second sub-block, multiplying the precoding matrix configured for the sub-band corresponding to the second sub-block by the second sub-block, and determining the optimized frequency domain channel estimation value corresponding to the second sub-block according to the calculation result.
5. The method according to any of claims 1 to 4, wherein the frequency domain data comprises at least reference data comprising a plurality of symbols located at different frequency domain positions; the target channel estimation value corresponds to a plurality of symbols at different frequency domain positions in the reference data;
the method further comprises the following steps:
and carrying out interpolation operation on the target channel estimation values of a plurality of symbols corresponding to different frequency domain positions in the reference data, and obtaining the target channel estimation values corresponding to all symbols at all frequency domain positions in the frequency domain data according to the operation result.
6. A channel estimation apparatus, applied to a receiving end in a 5G new air interface NR system, where a transmitting end of the 5G NR system performs different precoding on each subband by dividing the subband, and different subbands are configured with different precoding matrices, the apparatus comprising:
an initial channel estimation unit, configured to perform channel estimation on the received frequency domain data to obtain an initial frequency domain channel estimation value;
a first processing unit to:
dividing the initial frequency domain channel estimation value into N first sub-blocks, wherein N is the number of sub-bands, each first sub-block corresponds to one sub-band, and different first sub-blocks correspond to different sub-bands;
processing the first sub-blocks and an inverse matrix of a pre-coding matrix configured for the sub-band corresponding to each first sub-block to obtain intermediate processing data of each first sub-block;
the de-noising unit is used for de-noising the intermediate processing data of each first sub-block to obtain optimized data; and
a second processing unit to:
dividing the optimized data into N second sub-blocks, wherein each second sub-block corresponds to one sub-band, and different second sub-blocks correspond to different sub-bands;
restoring the optimized data of each second sub-block into the optimized frequency domain channel estimation value corresponding to each second sub-block by utilizing the pre-coding matrix configured to the sub-band corresponding to each second sub-block;
and determining a target channel estimation value according to the optimized frequency domain channel estimation value corresponding to each second sub-block.
7. The apparatus according to claim 6, wherein the first processing unit, when processing the inverse matrix of the precoding matrix configured for each first sub-block and the sub-band corresponding to each first sub-block, is specifically configured to:
and for each first sub-block, multiplying the inverse matrix of the pre-coding matrix configured for the sub-band corresponding to the first sub-block by the first sub-block, and determining the intermediate processing data of the first sub-block according to the calculation result.
8. The apparatus of claim 6, wherein the denoising unit, when denoising the intermediate processing data of each first sub-block to obtain the optimized data, is specifically configured to:
arranging the intermediate processing data of each first sub-block according to the original position of each first sub-block, and transforming the arranged data from a frequency domain to a time domain to obtain a time domain channel estimation value;
and carrying out windowing denoising on the time domain channel estimation value, and transforming the data subjected to windowing denoising from the time domain to the frequency domain to obtain the optimized data.
9. The apparatus according to any one of claims 6 to 8, wherein the second processing unit, when restoring the optimized data of each second sub-block to the optimized frequency-domain channel estimation value corresponding to each second sub-block by using the precoding matrix configured for the sub-band corresponding to each second sub-block, is specifically configured to:
and for each second sub-block, multiplying the precoding matrix configured for the sub-band corresponding to the second sub-block by the second sub-block, and determining the optimized frequency domain channel estimation value corresponding to the second sub-block according to the calculation result.
10. An electronic device comprising a processor and a machine-readable storage medium storing machine-executable instructions executable by the processor, the processor being caused by the machine-executable instructions to: carrying out the method steps of any one of claims 1 to 5.
11. A machine-readable storage medium having stored thereon machine-executable instructions which, when executed by a processor, perform the method steps of any one of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210887101.XA CN115065579B (en) | 2022-07-26 | 2022-07-26 | Channel estimation method, device, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210887101.XA CN115065579B (en) | 2022-07-26 | 2022-07-26 | Channel estimation method, device, electronic equipment and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115065579A CN115065579A (en) | 2022-09-16 |
| CN115065579B true CN115065579B (en) | 2022-11-01 |
Family
ID=83205821
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210887101.XA Active CN115065579B (en) | 2022-07-26 | 2022-07-26 | Channel estimation method, device, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115065579B (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101453258A (en) * | 2007-11-28 | 2009-06-10 | 三星电子株式会社 | SVD pre-coding method, pre-decoding method and system applying the methods |
| CN101582752A (en) * | 2009-06-23 | 2009-11-18 | 重庆邮电大学 | Signal channel counteraction receiving method of precoding MIMO in LTE-A |
| WO2011035594A1 (en) * | 2009-09-28 | 2011-03-31 | 中兴通讯股份有限公司 | Demodulation method and demodulator for orthogonal frequency division multiplexing - multiple input multiple output system |
| WO2016023410A1 (en) * | 2014-08-14 | 2016-02-18 | 电信科学技术研究院 | Downlink channel precoding method and apparatus |
| CN105703813A (en) * | 2016-02-04 | 2016-06-22 | 东南大学 | MIMO system precoding method |
| CN108712198A (en) * | 2018-05-08 | 2018-10-26 | 电子科技大学 | A kind of mixing method for precoding based on subband equivalent channel matrix conditional number |
| WO2018228478A1 (en) * | 2017-06-16 | 2018-12-20 | Qualcomm Incorporated | Frequency selective uplink precoding for new radio |
| CN111464217A (en) * | 2020-03-08 | 2020-07-28 | 复旦大学 | Improved SVD precoding algorithm for MIMO-OFDM |
| WO2022035541A1 (en) * | 2020-08-13 | 2022-02-17 | Qualcomm Incorporated | Techniques for sub-band precoding in sidelink communications |
| CN114285705A (en) * | 2022-03-03 | 2022-04-05 | 新华三技术有限公司 | Channel estimation method and device and electronic equipment |
-
2022
- 2022-07-26 CN CN202210887101.XA patent/CN115065579B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101453258A (en) * | 2007-11-28 | 2009-06-10 | 三星电子株式会社 | SVD pre-coding method, pre-decoding method and system applying the methods |
| CN101582752A (en) * | 2009-06-23 | 2009-11-18 | 重庆邮电大学 | Signal channel counteraction receiving method of precoding MIMO in LTE-A |
| WO2011035594A1 (en) * | 2009-09-28 | 2011-03-31 | 中兴通讯股份有限公司 | Demodulation method and demodulator for orthogonal frequency division multiplexing - multiple input multiple output system |
| WO2016023410A1 (en) * | 2014-08-14 | 2016-02-18 | 电信科学技术研究院 | Downlink channel precoding method and apparatus |
| CN105703813A (en) * | 2016-02-04 | 2016-06-22 | 东南大学 | MIMO system precoding method |
| WO2018228478A1 (en) * | 2017-06-16 | 2018-12-20 | Qualcomm Incorporated | Frequency selective uplink precoding for new radio |
| CN108712198A (en) * | 2018-05-08 | 2018-10-26 | 电子科技大学 | A kind of mixing method for precoding based on subband equivalent channel matrix conditional number |
| CN111464217A (en) * | 2020-03-08 | 2020-07-28 | 复旦大学 | Improved SVD precoding algorithm for MIMO-OFDM |
| WO2022035541A1 (en) * | 2020-08-13 | 2022-02-17 | Qualcomm Incorporated | Techniques for sub-band precoding in sidelink communications |
| CN114285705A (en) * | 2022-03-03 | 2022-04-05 | 新华三技术有限公司 | Channel estimation method and device and electronic equipment |
Non-Patent Citations (3)
| Title |
|---|
| "An Imaginary Interference-Free Method for MIMO Precoding in FBMC/OQAM Systems";You Xu, Zhongxiu Feng;《IEEE Transactions on Vehicular Technology》;20171005;全文 * |
| "基于非正交多址的多用户MIMO方案研究";赵亚军;《中国优秀硕士学位论文全文数据库信息科技辑》;20180615;全文 * |
| 基于预编码的MIMO系统的半盲估计;郝东来等;《吉林大学学报(工学版)》;20070515(第03期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115065579A (en) | 2022-09-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9426011B2 (en) | Reducing out-of-band emission | |
| JP4911780B2 (en) | Wireless communication system, receiving apparatus and receiving method | |
| US9178739B2 (en) | Method of wireless communication with a multi-antenna receiver | |
| CN113259298B (en) | OTFS signal processing method, device, equipment and storage medium | |
| WO2018091528A1 (en) | Processing wireless communication signals | |
| WO2014166164A1 (en) | Method of channel estimation by phase rotation iν orthogonal frequency division multiplexing (ofdm) system | |
| CN101155164B (en) | SINR estimation method for generalized multi-carrier system with DFT spread-spectrum | |
| WO2023156639A1 (en) | Method and apparatus for channel estimation in a mimo-ocdm system | |
| JP7129996B2 (en) | Method and device for inserting K pairs of reference signals | |
| US8385489B2 (en) | Methods and apparatus for wireless channel estimation using interpolation elimination in the Eigen domain | |
| WO2022258193A1 (en) | Generation and reception of precoded signals based on codebook linearization | |
| US11737077B2 (en) | Transmission device and transmission method | |
| CN115065579B (en) | Channel estimation method, device, electronic equipment and storage medium | |
| Hasan | PAPR reduction in OFDM systems based on autoregressive filtering | |
| Haghighi et al. | Effects of side information on complexity reduction in superimposed pilot channel estimation in OFDM systems | |
| CN113411108B (en) | Method, apparatus and storage medium for signal modulation and demodulation | |
| CN112152950B (en) | Channel estimation method and device based on sparse scattered pilot frequency in OFDM system | |
| CN104753834A (en) | Channel estimation method and channel estimation device | |
| EP2328310B1 (en) | Method for estimating a received signal and corresponding device | |
| JPWO2013171823A1 (en) | Receiving apparatus and receiving method | |
| CN108347394B (en) | Multi-carrier communication system and channel estimation method thereof | |
| CN109302360B (en) | Channel estimation method and device, computer readable storage medium and terminal | |
| CN104253773B (en) | Channel equalization method and device | |
| EP2768176B1 (en) | Orthogonal frequency division multiplexing (ofdm) channel estimation to improve the smoothing process | |
| KR102195907B1 (en) | SVD-based F-OFDM System and Transmitting/Receiving Method Thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |