CN113595945B - Channel estimation method suitable for PDSCH of 5G system - Google Patents
Channel estimation method suitable for PDSCH of 5G system Download PDFInfo
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Abstract
The invention relates to a channel estimation method suitable for a PDSCH of a 5G system, and belongs to the technical field of communication. Combining with the basic idea of a DFT channel estimation algorithm, firstly, carrying out inverse discrete Fourier transform according to frequency domain response at a pilot frequency DMRS estimated by an LS algorithm, then adding a Hamming window, then taking the average value of the median and the maximum value of the channel response amplitude modes of all sample points outside a cyclic prefix as a threshold value in the cyclic prefix, carrying out noise reduction operation, and finally, carrying out discrete Fourier transform and windowing function to obtain a channel estimation result. The invention not only can restrain the influence of energy leakage under the non-integer time delay channel, but also can effectively filter the noise in the cyclic prefix and improve the accuracy of channel estimation.
Description
Technical Field
The invention belongs to the technical field of communication, and relates to a channel estimation method suitable for a PDSCH of a 5G system.
Background
The PDSCH in the 5G system is mainly used for transmitting downlink data, carrying paging information, and transmitting part of system information. The channel estimation technology is used as a key of accurately and effectively recovering a transmitted signal by a 5G terminal, and plays an extremely important role in the whole link of a receiving end. During signal transmission, the communication transmission quality is greatly affected due to the randomness and time-varying nature of the channel environment. In order to ensure that the receiving end can receive the signal from the transmitting end without distortion, a channel estimation technique is generally required.
The most commonly used channel estimation algorithm in engineering implementation is based on Least-squares (LS), the complexity is low, the implementation is easy, the related prior information in a channel is not required to be acquired, the influence of noise is not considered, and the mean Square error is larger when the signal to noise ratio is smaller. Although the channel estimation algorithm based on the linear minimum mean square error (linear minimum MeanSquared, LMMSE) well suppresses the influence of noise, is an optimal criterion in the current pilot channel estimation algorithm, it is not enough to acquire prior information of a channel, which is difficult to obtain in a burst communication system, and the algorithm complexity is high due to the large number of matrix inversion processes, so that hardware implementation is very difficult. Compared with the LS algorithm and the LMMSE algorithm, the channel estimation algorithm based on the Discrete Fourier transform (Discrete FourierTransform, DFT) has a certain improvement on noise processing, the hardware implementation is not complex, and the performance is intermediate, but the traditional DFT algorithm only removes the noise outside the Cyclic Prefix (CP) and does not filter the noise in the Cyclic Prefix, and the problem of energy leakage under the non-integer time delay channel is not considered, so that the performance of the algorithm is affected. In order to suppress the influence of noise in a cyclic prefix, most of the existing improved DFT algorithms are to set a threshold and a decision threshold in the cyclic prefix to filter noise sample points, the threshold is generally selected based on energy values and amplitude modes of sample points inside and outside the cyclic prefix, and the threshold is set in an average value, a maximum value or a median mode. In chinese patent CN104468426a, a threshold corresponding to the lowest error probability detected by each tap is set as a filtering threshold in noise filtering, which can reduce the influence of channel energy leakage, but cannot well solve the problem that when the influence of burst large impulse noise is encountered, the threshold is too large to filter effective data, and the threshold is too small to filter noise; in chinese patent CN201910212458.6, a noise filtering threshold is obtained by smoothing a noise sample point outside the cyclic prefix and a sample point inside the cyclic prefix, which solves the problem that the threshold is set too large to filter a useful sample point inside the cyclic prefix due to line impulse noise interference, but does not consider the problem of energy leakage in a non-integer multiple delay channel.
Disclosure of Invention
In view of the above, the present invention is directed to providing a channel estimation method suitable for PDSCH of 5G system, which takes the average value of the median and the maximum value of the channel response amplitude modes of all sample points outside the cyclic prefix as the threshold value in the cyclic prefix to perform noise reduction operation, and adds a window function to achieve the effect of filtering noise in the cyclic prefix and energy leakage under the non-integer time delay channel.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a channel estimation method suitable for a PDSCH of a 5G system comprises the following steps:
s1: dividing the received pilot signal with a locally generated pilot signal to obtain a channel frequency domain response estimated value at the pilot frequency according to an LS algorithm idea;
s2: multiplying the frequency domain response of the pilot frequency estimated by the LS algorithm with a frequency domain window function, and then converting the frequency domain response into a time domain through inverse discrete Fourier transform;
s3: performing time domain noise reduction operation, including setting all sample points outside the cyclic prefix to zero, and taking the average value of the median and the maximum value of the channel response amplitude modes of all sample points outside the cyclic prefix as a threshold value in the cyclic prefix to perform noise reduction operation;
s4: performing discrete Fourier transform on the time domain data points with noise filtered to obtain a frequency domain, and removing a window function to obtain all channel estimation frequency domain response results;
further, the step S1 specifically includes: channel frequency response H of pilot frequency sub-carrier obtained by LS algorithm LS Expressed as:
H LS (k)＝Y(k)/X(k)＝H(k)+W(k)/X(k)
wherein X (k) is a pilot signal sent by a sending end, Y (k) is a pilot signal received by a receiving end, and W (k) is noise added in the channel transmission process.
Further, the step S2 includes the steps of:
s21: multiplying the pilot frequency domain response obtained by LS estimation algorithm with window function to obtain H w (k) Expressed as:
H w (k)＝H LS (k)·C(k)
where C (k) is the frequency domain form of the Hamming window function.
S22: channel for obtaining pilot subcarriers using LS algorithmAfter the frequency response windowing function, the pilot frequency domain channel response is converted into a time domain by inverse discrete Fourier transform to obtain the channel impulse response of the nth sample point to obtain h LS (n) expressed as:
where 0.ltoreq.n.ltoreq.N-1, W (N) =IDFT (W (k)/X (k)).
Further, step S3 includes the steps of:
s31: after the pilot frequency domain channel response is converted to the time domain, all sample points except the cyclic prefix are set to zero, and the representation is as follows:
wherein N is CP H is the length of the cyclic prefix DFT (N) is the sample point within the cyclic prefix after the cyclic prefix outer noise reduction operation, L is the channel impulse response length, and N is the total length of the sample point.
S32: taking the channel response amplitude modulo median T of all sample points outside the cyclic prefix 1 Expressed as:
T 1 ＝mediam||h DFT-1 (N CP )|,|h DFT-1 (N CP +1)|,…,|h DFT-1- (N-1)|]
wherein the dielectric function represents a median, and the channel response amplitude modulo maximum value T of all sample points outside the cyclic prefix is taken 2 Expressed as:
T 2 ＝max[|h DFT-1 (N CP )|,|h DFT-1 (N CP +1)|,…,|h DFT-1 (N-1)|]
where the max function indicates taking the maximum value. Then calculate T 1 And T 2 The average value T of (2) is:
taking T as a threshold noise reduction threshold in the cyclic prefix, reserving sample points which are larger than the threshold and setting the sample points which are smaller than the threshold to zero, so that channel time domain response h after noise reduction can be obtained new-DFT (n)。
Further, the step S4 specifically includes the following steps:
s41: performing discrete Fourier transform on the time domain data points with noise filtered to be converted into a frequency domain, wherein the discrete Fourier transform is expressed as follows:
H new-DFT (k)＝DFT[h new-DFT (n)]
s42: removing window function to obtain all frequency domain response results H of channel estimation after noise filtering DFT (k) This can be expressed as:
H DFT (k)＝H new-DFT (k)/W(k)。
the invention has the beneficial effects that: and taking the average value of the median and the maximum value of the channel response amplitude modes of all sample points outside the cyclic prefix as a threshold value in the cyclic prefix to perform noise reduction operation, effectively filtering noise in the cyclic prefix, and adding a window function can inhibit the influence of energy leakage in the inverse discrete Fourier transform process.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objects and other advantages of the invention may be realized and obtained by means of the instrumentalities and combinations particularly pointed out in the specification.
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For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in the following preferred detail with reference to the accompanying drawings, in which:
fig. 1 is a flowchart of a channel estimation system based on DMRS pilot in a 5G OFDM system according to a preferred embodiment of the present invention;
fig. 2 is a flow chart of a channel estimation method suitable for PDSCH of 5G system according to the present invention.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the illustrations provided in the following embodiments merely illustrate the basic idea of the present invention by way of illustration, and the following embodiments and features in the embodiments may be combined with each other without conflict.
Wherein the drawings are for illustrative purposes only and are shown in schematic, non-physical, and not intended to limit the invention; for the purpose of better illustrating embodiments of the invention, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the size of the actual product; it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there are terms such as "upper", "lower", "left", "right", "front", "rear", etc., that indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but not for indicating or suggesting that the referred device or element must have a specific azimuth, be constructed and operated in a specific azimuth, so that the terms describing the positional relationship in the drawings are merely for exemplary illustration and should not be construed as limiting the present invention, and that the specific meaning of the above terms may be understood by those of ordinary skill in the art according to the specific circumstances.
Please refer to fig. 1-2.
The invention is applicable to the 5G system shown in fig. 1, and the pilot signal is a standard DMRS signal in the 3GPP 5G NR protocol under the assumption of a single antenna model. Binary data stream input at transmitting end of 5G OFDM system is subjected to modulation, serial-parallel conversion, pilot frequency insertion and inverse fast Fourier transform (I)nverse Fast FourierTransform, IFFT) to N sub-carriers frequency domain data X L (k) Conversion to time domain data x l (n) then adding a cyclic prefix, whose length is typically greater than the maximum channel delay, the IFFT transformation formula is as follows:
after parallel-to-serial conversion, the signal is sent to a multipath channel, and the impulse response of the channel can be expressed as follows:
where l is the number of paths of the channel multipath channel, a i Is the amplitude of the ith path, τ i Is the delay of the i-th path. After the signal passes through a multipath fading channel and removes the cyclic prefix, a time domain signal obtained by convolution operation with the channel response can be expressed as:
wherein w (n) is additive Gaussian white noise, and the frequency domain signal obtained by discrete Fourier transform is:
Y R (k)＝X L (k)H(k)+W(k),0≤k≤N-1
wherein X is L (k) Is a transmitted signal, Y R (k) Is the received signal, H (k) is the frequency response of the multipath channel, and W (k) is the noise response in the frequency domain.
Based on the system, taking an example of a transmitting antenna port to a receiving antenna as an example, referring to fig. 1 and fig. 2, the method for estimating a channel applicable to PDSCH of 5G system according to the present invention includes the following steps:
step S1: frequency domain data Y for a received signal in a 5G system R (k) Dividing the extracted pilot signal Y (k) with the locally generated pilot signal X (k) to obtain a channel frequency domain response estimated value H at the pilot LS (k) Is that;
H LS (k)＝Y(k)/X(k)＝H(k)+W(k)/X(k)
wherein N is 0.ltoreq.n-1, W (N) =idft (W (k)/X (k)) is a noise signal. The useful CIR of the channel is mainly concentrated on the first L sample points within the cyclic prefix and includes only noise outside the cyclic prefix, which can be obtained:
step S2: multiplying the pilot frequency domain response obtained by LS estimation algorithm with window function to obtain H w (k) Expressed as:
H w (k)＝H LS (k)·C(k)
c (k) is the frequency domain form of the Hamming window function, the Hamming window is simple and practical and suitable for unknown signals, so that the Hamming window is also suitable for receiving signals of an actual system which are interfered by noise, in addition, the side lobe and fluctuation of the Hamming window are smaller, the selectivity is higher, the influence of energy leakage can be effectively restrained by the Hamming window according to the principle that the side lobe is smaller and the leakage is smaller, and therefore the Hamming window function is selected.
After the LS algorithm obtains the channel frequency response windowing function of the pilot frequency subcarrier, the discrete Fourier inversion is utilized to convert the pilot frequency domain channel response to the time domain to obtain the channel impulse response of the nth sample point to obtain h LS (n) expressed as:
where 0.ltoreq.n.ltoreq.N-1, W (N) =IDFT (W (k)/X (k)), k=0, and 1 … N-1 represents pilot subcarrier sequence numbers.
Step S3: the method specifically comprises the following steps:
step1: according to the principle of the traditional DFT algorithm, when n is more than or equal to L, h LS (n) =0. The last N-L samples can be considered as noise, L is the channel impulse response length, so after the pilot frequency domain channel response is converted to the time domain, the sample points outside the cyclic prefix can be all zeroed out,expressed as:
step2: taking the channel response amplitude modulo median T of all sample points outside the cyclic prefix 1 Expressed as:
T 1 ＝mediam[|h DFT-1 (N CP )|,|h DFT-1 (N CP +1)|,…,|h DFT-1 (N-1)|]
taking the channel response amplitude modulus maximum value T of all sample points outside the cyclic prefix 2 Expressed as:
T 2 ＝max[|h DFT-1 (N CP )|,|h DFT-1 (N CP +1)|,…,|h DFT-1 (N-1)|]
calculate T 1 And T 2 The average value T of (2) is:
taking T as a threshold noise reduction threshold in the cyclic prefix, reserving sample points which are larger than the threshold and setting the sample points which are smaller than the threshold to zero, so that channel time domain response h after noise reduction can be obtained new-DFT (n) noise reduction operation is:
step S4: will h new-DFT (n) converting to the frequency domain and removing the window function. After the LS estimation is utilized to obtain the pilot frequency domain response in the algorithm process, the influence of signal energy leakage under the non-integer time delay channel on the selected threshold value threshold is restrained by adding a Hamming window, and the energy leakage of useful signals under the non-integer time delay channel can be restrained at the same time by the aid of the frequency domain windowing effect, so that the estimation performance of the DFT improved algorithm is further improved. After the time domain noise reduction, the frequency domain response of all channels is obtained by discrete Fourier transform and dividing by a window function as follows:
H DFT (k)＝DFT[h new-DFT ]/C(k)
based on a basic module and a flow of a 5G OFDM system, the embodiment of the invention takes DMRS as a pilot signal, carries out noise reduction operation outside a cyclic prefix and inside the cyclic prefix respectively on the basis of a traditional DFT channel estimation algorithm, carries out zero setting and noise reduction on the outside of the cyclic prefix, takes the average value of the median and the maximum value of the channel response amplitude modulus of all sample points outside the cyclic prefix as a threshold in the cyclic prefix to carry out noise reduction operation, and effectively filters noise components in the cyclic prefix; meanwhile, a Hamming window is added before the inverse discrete Fourier transform to restrain the influence of energy leakage on channel estimation accuracy in the inverse discrete Fourier transform process.
Finally, it is noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made thereto without departing from the spirit and scope of the present invention, which is intended to be covered by the claims of the present invention.
Claims (2)
1. A channel estimation method suitable for a PDSCH of a 5G system is characterized in that: the method comprises the following steps:
s1: dividing the received pilot signal with a locally generated pilot signal to obtain a channel frequency domain response estimated value at the pilot frequency according to an LS algorithm idea;
s2: multiplying the frequency domain response of the pilot frequency estimated by the LS algorithm with a frequency domain window function, and then converting the frequency domain response into a time domain through inverse discrete Fourier transform;
s3: performing time domain noise reduction operation, including setting all sample points outside a cyclic prefix to zero, and filtering noise sample points in the cyclic prefix based on a threshold value threshold;
s4: converting the data points after noise reduction into all channel frequency domain response results;
in the step S1, a pilot signal selects a standard DMRS reference signal in a 3GPP protocol R15 version 5G system;
in the step S2, the window function selects a hamming window to be expressed as:
n represents the total length of the sample point;
the step S2 specifically comprises the following steps:
s21: firstly, using LS algorithm to obtain channel frequency response of pilot frequency sub-carrier, then using discrete Fourier inversion to convert pilot frequency domain channel response into time domain to obtain channel impulse response of nth sample point;
s22: multiplying the pilot frequency domain response obtained by the LS estimation algorithm with a window function;
the step S3 specifically comprises the following steps:
s31: all the sample points outside the time domain cyclic prefix are set to zero to eliminate noise components outside the cyclic prefix;
s32: and taking the average value of the median and the maximum value of the channel response amplitude modes of all sample points outside the cyclic prefix as a threshold value in the cyclic prefix to perform noise reduction operation, and filtering noise components in the cyclic prefix.
2. The method for channel estimation for PDSCH of 5G system according to claim 1, wherein: the step S4 specifically comprises the following steps:
s41: performing discrete Fourier transform on the time domain data points with noise filtered to a frequency domain;
s42: and (4) windowing, namely dividing the frequency domain data obtained in the step (S41) by a window function of a frequency domain to obtain all channel frequency domain responses.
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