WO2019205110A1

WO2019205110A1 - Channel estimation method, device and receiver

Info

Publication number: WO2019205110A1
Application number: PCT/CN2018/084933
Authority: WO
Inventors: 王继辉; 陈佳超; 郁新华; 赵所峰; 白海
Original assignee: 深圳市汇顶科技股份有限公司
Priority date: 2018-04-27
Filing date: 2018-04-27
Publication date: 2019-10-31
Also published as: CN110651454B; CN110651454A

Abstract

Provided by the present invention are a channel estimation method, device and receiver, the method comprising: caching pilot frequency data in N subframes, the N subframes comprising current subframes to be processed, and N being an integer greater than or equal to two; carrying out inter-subframe merging for the pilot frequency data in the N subframes to obtain merged pilot frequency data; and carrying out channel estimation on the current subframes to be processed according to the merged pilot frequency data. With the technical solution provided by the present invention, the accuracy of channel estimation in an NB-IoT system may be improved, and the receiving performance of a system may be improved.

Description

Channel estimation method, device and receiver

Technical field

The present invention relates to the field of mobile communications technologies, and in particular, to a channel estimation method, apparatus, and receiver.

Background technique

Mobile communication is moving from the connection between people and people to the connection between people and things and things, and the Internet of Everything becomes an inevitable trend. However, the current 4G network is not capable of connecting objects and objects. Therefore, the industry chain has studied the use of Long Term Evolution (LTE) technology to carry the Internet of Things (IoT) connection from a few years ago. After continuous technological evolution, the 3rd Generation Partnership Project (3GPP) officially established the Narrow Band Internet of Things (NB-IoT) standard based on cellular networks in 2016. Compared with the existing network coverage gain of 20dB, NB-IoT has the ability to increase the coverage area by 100 times, and has lower power consumption and cost, so it has broad market prospects.

The NB-IoT standard is a branch of the evolutionary Internet of Things protocol of LTE. The receiver algorithm is very similar to LTE. The processing flow is specifically as follows: after the receiver receives the time domain signal, it first synchronizes the signal; after the signal is synchronized, the time domain is The signal is subjected to Cyclic Prefix (CP) processing and Fast Fourier Transformation (FFT) to transform the time domain signal into a frequency domain signal; then the channel estimation is performed according to the frequency domain signal, and then the channel estimation result is performed according to the channel estimation result. Perform channel equalization and demodulation, and finally perform de-scrambling, de-rate matching, and decoding on the demodulated data to obtain an original signal.

As an emerging technology, NB-IoT technology simplifies LTE to meet the needs of the Internet of Things. There is no mature receiver algorithm at present. From the receiving principle, the receiver of the NB-IoT system can adopt the receiver algorithm of the LTE system. In the receiver algorithm of the LTE system, when performing channel estimation, the least square method (Least Square, LS) is generally used to perform channel estimation on the pilot signals in the frequency domain signal. However, the amount of pilot signal data available for channel estimation in the LTE system is 100 times that of the NB-IoT, and the approximate NB-IoT system requires 100 times to achieve the same noise reduction effect. Therefore, if the receiver of the NB-IoT system completely applies the receiver algorithm of the LTE system, the channel estimation result will be poor, and finally the system receiving performance is very low, and only the minimum requirements of the protocol can be met.

Summary of the invention

In view of this, the present invention provides a channel estimation method, apparatus and receiver for reducing the influence of noise on channel estimation of the NB-IoT system, improving the accuracy of channel estimation, and thereby improving system reception performance.

In order to achieve the above object, in a first aspect, an embodiment of the present invention provides a channel estimation method, including:

Cache pilot data in N subframes, where N subframes include a current subframe to be processed, and N is an integer greater than or equal to 2;

Merging the pilot data in the N subframes to obtain the combined pilot data;

Channel estimation is performed on the current to-be-processed subframe according to the combined pilot data.

By utilizing the slow channel fading feature of the NB-IoT system, the pilot data of the N subframes including the current subframe to be processed is merged between the subframes, and then channel estimation is performed, thereby effectively reducing the noise of the received data. Improve the accuracy of channel estimation and improve system reception performance.

As an optional implementation manner of the embodiment of the present invention, before performing the inter-subframe combining of the pilot data in the N subframes, the method further includes:

Performing frequency offset estimation on N subframes according to pilot data in N subframes, to obtain frequency offset estimation values of N subframes;

Performing frequency offset compensation on pilot subframes other than the current to-be-processed subframe in the N subframes according to the frequency offset estimation value, based on the current to-be-processed subframe;

The merging of the pilot data in the N subframes includes:

Merging between the pilot subframe after the frequency offset compensation and the pilot data in the current subframe to be processed is performed.

The frequency offset between the subframes can be reduced by performing frequency offset compensation on pilot subframes other than the current subframe to be processed in the subframes before the subframes are merged in the subframes of the N subframes. The impact on the combined effect, thereby improving the accuracy of channel estimation.

As an optional implementation manner of the embodiment of the present invention, the N subframes are N subframes whose reception time is continuous.

By merging the consecutive subframes of the N subframes to reduce the interval between the reference subframe and the current subframe to be processed, the channel estimation error caused by the frequency offset between the subframes is reduced, and the channel is improved. Estimated accuracy.

As an optional implementation manner of the embodiment of the present invention, the N subframes include X subframes that are located before the current to-be-processed subframe and Y subframes that are located after the current to-be-processed subframe, where the sum of X and Y is equal to N-1.

By selecting the reference subframes before and after the current pending subframe, the error of the frequency offset estimation can be reduced, the noise reduction effect of the merge between the subframes is improved, and the accuracy of the channel estimation is improved.

As an optional implementation manner of the embodiment of the present invention, when N is an odd number, the current to-be-processed subframe is the (N+1)/2th subframe; when N is an even number, the current to-be-processed subframe is the Nth. /2 or N/2+1 subframes.

The referenced subframe is selected before and after the current to-be-processed subframe, so that the current to-be-processed subframe is located in the middle of the N subframes, and the combined noise reduction effect can be further improved.

As an optional implementation manner of the embodiment of the present invention, the value of N is 9.

By setting the value of N to 9, the receiver can achieve better noise reduction.

As an optional implementation manner of the embodiment of the present invention, performing merging between the subframes of the pilot data in the N subframes includes:

The pilot data of the same pilot position in the N subframes is arithmetically averaged.

The pilot data of the same pilot position in the N subframes is weighted averaged.

As an optional implementation manner of the embodiment of the present invention, performing channel estimation on the current to-be-processed subframe according to the merged pilot data includes:

The channel estimation value at the pilot position in the current to-be-processed subframe is calculated by least squares using the combined pilot data.

In a second aspect, an embodiment of the present invention provides a channel estimation apparatus, including:

a buffering module, configured to buffer pilot data in N subframes, where the N subframes include a current to-be-processed subframe, where N is an integer greater than or equal to 2;

a merging module, configured to perform merging between the subframes of the pilot data in the N subframes to obtain the combined pilot data;

And a channel estimation module, configured to perform channel estimation on the current to-be-processed subframe according to the combined pilot data.

As an optional implementation manner of the embodiment of the present invention, the device further includes:

a frequency offset estimation module, configured to perform frequency offset estimation on the N subframes according to pilot data in the N subframes, to obtain a frequency offset estimation value between the N subframes;

a frequency offset compensation module, configured to perform frequency offset compensation on pilot subframes other than the current to-be-processed subframe in the N subframes according to the frequency offset estimation value, based on the current to-be-processed subframe;

The merging module is specifically configured to: perform merging between the pilot subframe after performing frequency offset compensation and the pilot data in the current to-be-processed subframe.

As an optional implementation manner of the embodiment of the present invention, the merging module is specifically configured to:

As an optional implementation manner of the embodiment of the present invention, a channel estimation module is specifically configured to:

For the beneficial effects of the apparatus provided by the foregoing second aspect and the possible embodiments of the second aspect, reference may be made to the beneficial effects brought by the first aspect and the possible implementation manners of the first aspect, and details are not described herein again. .

In a third aspect, an embodiment of the present invention provides a receiver, including: a memory and a processor, where the memory is used to store a computer program; and the processor is configured to execute any one of the foregoing first aspect and the first aspect when the computer program is invoked Said method.

The benefits of the receiver provided by the foregoing third aspect and the possible implementation manners of the third aspect can be seen in the beneficial effects of the first aspect and the possible implementation manners of the first aspect, and no longer Narration.

In a fourth aspect, an embodiment of the present invention provides a computer readable storage medium, wherein a computer program is stored thereon, and when the computer program is executed by a processor, the method according to any one of the first aspect and the first aspect is implemented.

The computer readable storage medium provided by the foregoing fourth aspect and the possible implementation manners of the fourth aspect, the beneficial effects of which can be seen in the first aspect and the possible implementation manners of the first aspect, This will not be repeated here.

DRAWINGS

1 is a schematic flowchart of a channel estimation method according to an embodiment of the present invention;

2 is a schematic diagram of a NB-IoT frame structure;

3 is a schematic diagram of a frame format of a NB-IoT pilot subframe;

FIG. 4 is a schematic structural diagram of inter-subframe merging according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of channel fading of NB-IoT according to an embodiment of the present invention;

FIG. 6 is a schematic diagram of a noise reduction effect of inter-subframe combining according to an embodiment of the present invention;

FIG. 7 is a schematic flowchart diagram of another channel estimation method according to an embodiment of the present disclosure;

FIG. 8 is a schematic structural diagram of a channel estimation apparatus according to an embodiment of the present disclosure;

FIG. 9 is a schematic structural diagram of another channel estimation apparatus according to an embodiment of the present disclosure;

FIG. 10 is a schematic structural diagram of a receiver according to an embodiment of the present invention.

detailed description

The receiver algorithm of the NB-IoT system is very similar to that of LTE, but since the number of pilots of the NB-IoT is small, if the receiver algorithm of the LTE system is completely applied, the channel estimation result is poor.

Taking the most common channel estimation and equalization algorithm: LS+ Zero Force (ZF) as an example, the Orthogonal Frequency Division Multiplexing (OFDM) system model used in LTE systems can be expressed by formula (1.1). :

Y=XH+W (1.1)

Where H is the channel response, X is the known pilot transmission signal, Y is the received pilot signal, and W is the Additive White Gaussian Noise (AWGN) vector superimposed on the pilot subchannel. .

Channel estimation value obtained by LS algorithm

As shown in formula (1.2):

It can be known from equation (1.2) that the LS channel estimation algorithm ignores the influence of noise and is therefore sensitive to the influence of noise interference. It can be known from equation (1.3) that when the channel noise is large, the accuracy of the estimation is greatly reduced.

After obtaining the estimated value of the signal response H, the channel can be equalized using the ZF algorithm without considering the influence of the noise W, as shown in equation (1.4).

Similarly, ZF equalization ignores the impact of AWGN and can cause certain problems. Equation (1.5) is the effect caused by the ZF algorithm after considering the noise.

among them,

Is the estimated value of the transmitted signal X.

It can be seen that since the filtering characteristic of the zero-forcing equalizer is opposite to the channel characteristic, a large amplitude gain is introduced to the noise of the frequency point, and the output is greatly affected by the noise, and the performance is significantly reduced.

The existing LTE system mainly utilizes the characteristics of LTE pilot signals, and uses Wiener filtering or transform domain noise reduction to improve the accuracy of channel estimation. However, the data volume of the pilot signals in the NB-IoT system is only The 1/100 of the LTE system, therefore, if the receiver of the NB-IoT system completely applies the receiver algorithm of the LTE system, the channel estimation result is very poor, and finally the system receiving performance is very low, and only the minimum requirements of the protocol can be met.

In order to solve the above technical problem, an embodiment of the present invention provides a channel estimation method, apparatus, and receiver, which mainly utilizes a channel fading slowness of an NB-IoT system, and uses a pilot of a current subframe to be processed and a plurality of subframes before and after it. The data is combined to achieve data denoising, and then channel estimation is performed to improve channel estimation accuracy and thereby improve receiver performance.

The technical solution of the present invention will be described in detail below with reference to the accompanying drawings.

FIG. 1 is a schematic flowchart of a channel estimation method according to an embodiment of the present invention. As shown in FIG. 1 , the method provided in this embodiment may include the following steps:

S101. Cache pilot data in N subframes.

Specifically, the subframe structure of the NB-IoT is similar to that of LTE. 2 is a schematic diagram of a NB-IoT frame structure, and FIG. 3 is a schematic diagram of a frame format of a NB-IoT pilot subframe. As shown in FIG. 2, each radio frame has 10 subframes, and two radio frames are shown in FIG. 2: an even frame on the left and an odd frame on the right. The

subframes

5 and 9 of the even frame are used for transmitting the synchronization signal, the subframe 5 of the odd frame is also used for transmitting the synchronization signal, the subframe for transmitting the synchronization signal does not contain the pilot data, and the other is not used for transmitting the synchronization signal. The subframes each contain pilot data, and these subframes may be simply referred to as pilot subframes.

As shown in FIG. 3, each subframe is divided into 2 slots, the left half of each subframe is an even slot, and the right half is an odd slot; each slot has 7 OFDM symbols (I), each The OFDM symbols are fixed with only 12 subcarriers. According to the protocol, the pilot data is mapped on the last two OFDM symbols of each slot. NB-IoT supports 1 or 2 antenna ports. When the antenna ports are two, the pilot data positions on the two antenna ports are different. For details, see Figure 3. When the antenna port is one, the pilot data is in The resource element (RE) mapped on the other antenna port is vacant and is not used for the transmission of this antenna port. Among them, one symbol on the frequency of one subcarrier in time domain is called an RE.

In this embodiment, after receiving the baseband signal, the receiver completes the de-CP operation according to the protocol, and then converts the pilot data in the N subframes after the data is converted from the time domain to the frequency domain by the FFT.

The N subframes include a current to-be-processed subframe and a reference subframe. FIG. 4 is a schematic structural diagram of inter-subframe merging according to an embodiment of the present invention. As shown in FIG. 4, two radio frames are shown, and subframes 10-19 are 0-9 of the odd frame in FIG. 2. Assuming that the current to-be-processed subframe is the subframe 10, the N-1 subframes before and after the subframe 10 are selected as the reference subframe. For convenience of description, the following is also taken as an example of the subframe to be processed. Technical solution of the invention.

The N subframes may be N subframes with consecutive reception times, for example, N subframes include

subframes

8, 9, 10, and 11; and may also be N subframes whose reception time is discontinuous, for example, N subframes include subframe 6 8, 10 and 12. As the subframe interval is larger, the frequency offset between the subframes is larger, and the error is larger when the subsequent merged subframes are noise-reduced. To improve the accuracy of the channel estimation, as a preferred implementation manner, N subframes are received. The time-continuous N subframes are such that the interval between the reference subframe and the current subframe to be processed becomes smaller.

In addition, the reference subframes in the N subframes may select subframes that are located before the current subframe to be processed, for example,

subframes

7, 8 and 9 before the subframe 10 are selected in the reference subframe; or may be selected in the current to-be-processed subframe. Subframes after the frame, for example,

sub-frames

11, 12, and 13 after the sub-frame 10 are selected with reference to the sub-frame. The AWGN of the receiver obeys a normal distribution with a mean value of 0. In order to further improve the accuracy of the channel estimation, in this embodiment, preferably, the N subframes include X subframes located before the current to-be-processed subframe and are currently located. The Y subframes after the subframe are processed, where the sum of X and Y is equal to N-1, that is, the reference subframe is selected before and after the current to-be-processed subframe, and the positive and negative between the reference subframe and the current to-be-processed subframe are The noise cancels each other to reduce the noise of the current subframe to be processed.

Further, the current to-be-processed subframe may be located in the middle of the N subframes, that is, when N is an odd number, the current to-be-processed subframe is the (N+1)/2th subframe; when N is an even number, the current to-be-processed The subframe is the N/2th or N/2+1th subframe to improve the noise reduction effect of the current subframe to be processed. For example, as shown in FIG. 4, N subframes include subframes 6-14, and subframe 10 is at an intermediate position.

Since the subframes for transmitting the synchronization signal may be included in the N subframes, in order to ensure the merging between the subframes, in this embodiment, N is an integer greater than or equal to 2. The specific value of N can be determined according to the combined noise reduction effect of the system, and should not be too small, so as to avoid the bad noise reduction effect; it should not be too large, so as to avoid introducing excessive frequency offset and affecting the noise reduction effect. In this embodiment, preferably, the value of N is 9, and at this value of N, the system can achieve a better noise reduction effect. The value of N in FIG. 4 is 9. For ease of understanding, the technical solution of the present invention is exemplified by taking the subframe merged diagram shown in FIG. 4 as an example.

It should be noted that the receiver can automatically determine whether the subframe is a pilot subframe according to the protocol, and when buffering, only the pilot data of the pilot subframe can be buffered. For example, in FIG. 4, the synchronization signal is mapped in the subframe 9, and there is no pilot data, so it is not used for merging. When buffering, it is not necessary to buffer the subframe 9.

S102. Perform inter-subframe combining on pilot data in N subframes to obtain combined pilot data.

Specifically, the NB-IoT is mainly applied to a non-high-speed mobile scenario (the moving speed is less than 150 Km/h), and the channel fading is slow. FIG. 5 is a schematic diagram of channel fading of the NB-IoT according to the embodiment of the present invention, as shown in FIG. The abscissa is the sampling time point and the ordinate is the channel response power. The data between any 9 subframes (for example, the three segments of data in FIG. 5) is smooth, and the mean before and after is approximately the intermediate value, so the method of inter-subframe merging can be used for noise reduction.

In the above step S101, the buffered pilot data may be represented by a two-dimensional matrix for each subframe, for example, by a matrix of 2×4 (single antenna) or 4×2 (dual antenna). When inter-subframe merging is performed, the merging between the matrices of N subframes is performed.

In the specific merging, the pilot data of the same pilot position in the N subframes may be arithmetically averaged, or the pilot data of the same pilot position in the N subframes may be weighted and averaged.

Take the weighted average method as an example. The specific formula is as follows:

Nrs_rx_combine(t)=∑w(i)*nrs_rx(i) (1.6)

Where i=-4,-3,-2,0,1,2,3,4, nrs_rx_combine(t) represents the combined pilot data, and nrs_rx(i) represents the interval between the current pending subframe and i. Referring to the pilot data of the subframe, w(i) is a weight, and the sum of each w(i) is 1. Since the subframe corresponding to i=-1 does not transmit the pilot signal, no merging is performed.

When merging is performed, the matrix of N subframes is weighted and averaged, that is, the pilot data of the same column in each matrix is weighted and averaged.

S103. Perform channel estimation on the current to-be-processed subframe according to the combined pilot data.

Specifically, after the received data is denoised by combining the pilot subframes, the channel estimation value at the pilot position of the current to-be-processed subframe may be first estimated according to the combined pilot data, and then according to the channel at the pilot position. The estimated value estimates the channel estimate at the non-pilot position of the current pending subframe, completing the channel estimate for the entire current pending subframe.

Wherein, when estimating the channel estimation value at the pilot position of the current to-be-processed subframe, the LS method may be used to calculate the channel estimation value at the pilot position in the current to-be-processed subframe, and the specific formula may be expressed as follows:

among them,

The channel estimation value at the pilot position of the current pending subframe, nrs_tx(t) represents the pilot data of the current pending subframe known by the transmitting and receiving parties defined by the local protocol, that is, the current to-be-processed subframe transmitted by the transmitter Pilot data.

Of course, other more complex channel estimation methods may be used to calculate the channel estimation value at the pilot position in the current to-be-processed subframe. In this embodiment, the LS channel estimation method can achieve better channel estimation, and thus The LS channel estimation method is preferably employed to reduce system processing overhead.

When the channel estimation value at the non-pilot position of the current to-be-processed subframe is estimated according to the channel estimation value at the pilot position, the existing various methods may be used, which is not specifically limited in this embodiment.

The channel fading of the NB-IoT system is slow, and the signal loss after merging the data is small. Moreover, the AWGN of the NB-IoT receiver obeys a normal distribution with a mean of 0, which is not affected by channel fading. Theoretically, the combined noise reduction effect is the best. Therefore, in this embodiment, by combining the sub-frames, the noise of the received data can be effectively reduced, the accuracy of the channel estimation can be improved, and the receiving performance of the system can be improved. FIG. 6 is a schematic diagram of a noise reduction effect of inter-subframe combining according to an embodiment of the present invention. As shown in Fig. 6, taking the most typical extended pedestrian channel model (Extended Pedestrian A model 1 Hz, EPA1) as an example, for the same received data, when the inter-subframe merging is not performed, the receiver's performance curve, ie, signal-to-noise The Signal-to-Noise Ratio (SNR)-Block Error Rate (BLER) curve is shown in curve A. After the inter-subframe combination, the SNR-BLER curve of the receiver is shown as curve B. Shown. Comparing the curves A and B, the combined receiver performance is improved by more than 4 dB before the merger in the case of the 0.01 block error rate.

The channel estimation method provided in this embodiment uses the NB-IoT system to slow channel fading, and combines the pilot data of N subframes including the current subframe to be processed, and then performs channel estimation. The noise of the received data can be effectively reduced, the accuracy of the channel estimation is improved, and the receiving performance of the system is improved.

FIG. 7 is a schematic flowchart of another channel estimation method according to an embodiment of the present disclosure. This embodiment is a further optimization and supplement to the foregoing embodiment shown in FIG. 1. On the basis of the foregoing embodiment shown in FIG. As shown in FIG. 7, the method provided in this embodiment may include the following steps:

S201. Cache pilot data in N subframes.

For the step, reference may be made to the description of the step S101 corresponding to the embodiment shown in FIG. 1 , and details are not described herein.

S202. Perform frequency offset estimation on the N subframes according to the pilot data in the N subframes to obtain a frequency offset estimation value of the N subframes.

Since the pilot data transmitted between different subframes has a frequency offset of one subframe, the reference subframe may be subjected to frequency offset compensation before combining to improve the accuracy of channel estimation.

Specifically, the correlation of the pilot data in the N subframes may be used to perform frequency offset estimation on the N subframes, and the frequency offset estimation value w of the N subframes is estimated. The specific frequency offset estimation method may be an existing frequency offset estimation method, which is not limited in this embodiment.

S203: Perform frequency offset compensation on the pilot subframes other than the current to-be-processed subframe in the N subframes according to the frequency offset estimation value, based on the current to-be-processed subframe.

In estimating the frequency offset estimation value w of the N subframes, the frequency offset compensation may be performed on the other pilot subframes in the N subframes by using the formula (1.8), and the other pilot subframes in the N subframes are compensated, that is, the other pilots are compensated. The frequency offset of the subframe relative to the current subframe to be processed to eliminate the influence of the transmission data on the frequency offset.

Nrs_rx_comp(i)=nrs_rx(i)*e ^-j*w*i ,i=-4,-3,-2,1,2,3,4 (1.8)

Where nrs_rx(i) represents the pilot data of the reference subframe with the current pending subframe interval i, and nrs_rx_comp(i) represents the nrs_rx(i) after the frequency offset compensation.

In addition, the frequency offset compensation in this step may also directly adjust the crystal oscillator frequency of the receiver to achieve frequency offset correction.

S204. Perform merging between the pilot subframe after performing frequency offset compensation and the pilot data in the current to-be-processed subframe.

Specifically, after the frequency offset compensation is performed on the reference subframe, when the pilot data in the N subframes is merged between the subframes in step S102 in FIG. 1, specifically, the pilots after performing frequency offset compensation are used. The frame and the pilot data in the current pending subframe are merged between the subframes. The corresponding formula (1.6) is updated to formula (1.9):

Nrs_rx_combine(t)=∑w(i)*nrs_rx_comp(i) (1.9)

Where i=-4,-3,-2,0,1,2,3,4. Replace nrs_rx(i) in equation (1.6) with nrs_rx_comp(i).

For the specific principle of the inter-subframe merging, refer to step S102, and details are not described herein again.

S205. Perform channel estimation on the current to-be-processed subframe according to the combined pilot data.

For the step, refer to the description of step S103 corresponding to the embodiment shown in FIG. 1 above, and details are not described herein.

The channel estimation method provided in this embodiment performs frequency offset compensation on pilot subframes other than the current to-be-processed subframe in the N subframes before performing the inter-subframe combining on the pilot data of the N subframes. The effect of the inter-subframe frequency offset on the merging can be reduced, the accuracy of the channel estimation is improved, and the system receiving performance is improved.

Figure 8 is a schematic structural diagram of a channel estimation apparatus according to an embodiment of the present invention. As shown in Figure 8, the apparatus provided in this embodiment includes:

The buffering module 101 is configured to buffer pilot data in N subframes, where the N subframes include a current subframe to be processed, and N is an integer greater than or equal to 2;

The merging module 102 is configured to perform merging between the subframes of the pilot data in the N subframes to obtain the combined pilot data.

The channel estimation module 103 is configured to perform channel estimation on the current to-be-processed subframe according to the combined pilot data.

The device provided in this embodiment may be integrated in the receiver of the NB-IoT system, or may be a separate device.

As an optional implementation manner of this embodiment, the N subframes are N subframes whose reception time is continuous.

As another optional implementation manner of this embodiment, the N subframes include X subframes located before the current to-be-processed subframe and Y subframes located after the current to-be-processed subframe, where the sum of X and Y is equal to N-1.

Further, when N is an odd number, the current to-be-processed subframe may be the (N+1)/2th subframe; when N is an even number, the current to-be-processed subframe may be the N/2th or N/2+1. Subframes.

As a specific implementation manner of this embodiment, the value of N may be 9.

As a specific implementation manner of this embodiment, the merging module 102 is specifically configured to:

As another specific implementation manner of this embodiment, the merging module 102 is specifically configured to:

As a specific implementation manner of this embodiment, the channel estimation module 103 is specifically configured to:

The channel estimation value at the pilot position in the current to-be-processed subframe is calculated by least squares according to the combined pilot data.

The device provided in this embodiment can perform the method embodiment shown in FIG. 1 , and the implementation principle is similar to the technical effect, and details are not described herein again.

FIG. 9 is a schematic structural diagram of another channel estimation apparatus according to an embodiment of the present disclosure. This embodiment is an optimization supplement to the foregoing embodiment shown in FIG. 8. As shown in FIG. 9, in the foregoing embodiment shown in FIG. The device provided in this embodiment may further include:

The frequency offset estimation module 104 is configured to perform frequency offset estimation on the N subframes according to the pilot data in the N subframes, to obtain a frequency offset estimation value of the N subframes.

The frequency offset compensation module 105 is configured to perform frequency offset compensation on the pilot subframes other than the current to-be-processed subframe in the N subframes according to the frequency offset estimation value, based on the current to-be-processed subframe;

The merging module 102 is configured to: perform merging between the pilot subframe after performing frequency offset compensation and the pilot data in the current to-be-processed subframe.

The apparatus provided in this embodiment may be integrated in a receiver of the NB-IoT system or may be a separate device.

The device provided in this embodiment can perform the method embodiment shown in FIG. 7 , and the implementation principle is similar to the technical effect, and details are not described herein again.

FIG. 10 is a schematic structural diagram of a receiver according to an embodiment of the present invention. As shown in FIG. 10, the receiver provided in this embodiment includes: a memory 201 and a processor 202, where the memory 201 is used to store a computer program; and the processor 202 is configured to execute the method described in any one of the foregoing method embodiments when calling the computer program. method.

The receiver provided in this embodiment can perform the foregoing method embodiments, and the implementation principle is similar to the technical effect, and details are not described herein again.

The embodiment of the invention further provides a computer readable storage medium, on which a computer program is stored, and when the computer program is executed by the processor, the method described in any one of the foregoing method embodiments is implemented.

Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, and are not intended to be limiting; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that The technical solutions described in the foregoing embodiments may be modified, or some or all of the technical features may be equivalently replaced; and the modifications or substitutions do not deviate from the technical solutions of the embodiments of the present invention. range.

Claims

A channel estimation method, comprising:

Cache pilot data in N subframes, where the N subframes include a current to-be-processed subframe, where N is an integer greater than or equal to 2;

Merging the pilot data in the N subframes to obtain the combined pilot data;

Channel estimation is performed on the current to-be-processed subframe according to the combined pilot data.
The method according to claim 1, wherein before the merging the pilot data in the N subframes, the method further comprises:

Performing frequency offset estimation on the N subframes according to pilot data in the N subframes, to obtain a frequency offset estimation value of the N subframes;

Performing frequency offset compensation on the pilot subframes other than the current to-be-processed subframe in the N subframes according to the frequency offset estimation value, according to the current to-be-processed subframe;

The performing the merging between the subframes of the pilot data in the N subframes includes:

The inter-subframe combining is performed on the pilot subframe after the frequency offset compensation and the pilot data in the current to-be-processed subframe.
The method according to claim 1 or 2, wherein the N subframes are N subframes in which reception time is continuous.
The method according to any one of claims 1-3, wherein the N subframes include X subframes located before the current to-be-processed subframe and Y located after the current to-be-processed subframe Subframes, wherein the sum of X and Y is equal to N-1.
The method according to claim 4, wherein when N is an odd number, the current to-be-processed subframe is the (N+1)/2th subframe; when N is an even number, the current to-be-processed subframe is the Nth /2 or N/2+1 subframes.
Method according to claim 4 or 5, characterized in that the value of N is 9.
The method according to any one of claims 1-6, wherein the performing the merging of the pilot data in the N subframes comprises:

The pilot data of the same pilot position in the N subframes is arithmetically averaged.
The method according to any one of claims 1-6, wherein the performing the merging of the pilot data in the N subframes comprises:

The pilot data of the same pilot position in the N subframes is weighted averaged.
The method according to any one of claims 1-8, wherein the performing channel estimation on the current to-be-processed subframe according to the merged pilot data includes:

And calculating, by using a least square method, a channel estimation value at a pilot position in the current to-be-processed subframe according to the combined pilot data.
A channel estimation apparatus, comprising:

a buffering module, configured to buffer pilot data in the N subframes, where the N subframes include a current to-be-processed subframe, where the N is an integer greater than or equal to 2;

a merging module, configured to perform merging of pilot data in the N subframes to obtain combined pilot data;

And a channel estimation module, configured to perform channel estimation on the current to-be-processed subframe according to the combined pilot data.
The device according to claim 10, wherein the device further comprises:

a frequency offset estimation module, configured to perform frequency offset estimation on the N subframes according to pilot data in the N subframes, to obtain a frequency offset estimation value of the N subframes;

a frequency offset compensation module, configured to perform frequency offset compensation on a pilot subframe other than the current to-be-processed subframe in the N subframes according to the frequency offset estimation value, with reference to the current to-be-processed subframe ;

The merging module is specifically configured to: perform merging between the pilot subframe after performing frequency offset compensation and the pilot data in the current to-be-processed subframe.
The apparatus according to claim 10 or 11, wherein the N subframes are N subframes in which reception time is continuous.
The apparatus according to any one of claims 10 to 12, wherein the N subframes include X subframes located before the current to-be-processed subframe and Y located after the current to-be-processed subframe Subframes, wherein the sum of X and Y is equal to N-1.
The apparatus according to claim 13, wherein when N is an odd number, the current to-be-processed subframe is the (N+1)/2th subframe; when N is an even number, the current to-be-processed subframe is the Nth /2 or N/2+1 subframes.
Device according to claim 13 or 14, characterized in that the value of N is 9.
The device according to any one of claims 10-15, wherein the merging module is specifically configured to:

The pilot data of the same pilot position in the N subframes is arithmetically averaged.
The device according to any one of claims 10-15, wherein the merging module is specifically configured to:

The pilot data of the same pilot position in the N subframes is weighted averaged.
The device according to any one of claims 10-17, wherein the channel estimation module is specifically configured to:

And calculating, by using a least square method, a channel estimation value at a pilot position in the current to-be-processed subframe according to the combined pilot data.
A receiver, comprising: a memory and a processor, the memory for storing a computer program; the processor for performing the computer program according to any one of claims 1-9 when the computer program is invoked method.
A computer readable storage medium having stored thereon a computer program, wherein the computer program is executed by a processor to implement the method of any of claims 1-9.