Internet of things DFT precoding FBMC carrier synchronization and channel estimation method

Abstract

The invention discloses an Internet of Things DFT precoding FBMC carrier synchronization and channel estimation method, and relates to the technical field of wireless communication, and the method comprises the steps: obtaining to-be-transmitted FBMC symbol data, and constructing three continuous training sequence symbols; the three continuously placed training sequence symbols and other data symbols completing conjugate symmetric mapping are subjected to pre-FFT and IFFT subcarrier modulation and multi-phase filtering of a data mapping DFT precoding FBMC-OQAM system, and then corresponding sending signals of a time domain are obtained; at a receiving end, carrying out multi-phase filtering and IFFT subcarrier demodulation on a received signal to obtain a received data signal, and in a second training sequence symbol, taking data on the 0th, 2th, 4th,..., (M-1) th subcarriers as pilot frequency points to carry out channel estimation; the method can realize carrier synchronization and channel estimation at the same time, and has a relatively low peak-to-average ratio.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to an Internet of Things DFT precoding FBMC carrier synchronization and channel estimation method. Background Art

[0002] In recent years, the Filter Bank Multi-Carrier with Offset Quadrature Amplitude Modulation (FBMC-OQAM) system has the potential application advantages in the space-ground integrated massive asynchronous user scenarios due to its extremely low out-of-band radiation performance and the ability to relax the synchronization between users.

[0003] In IoT transmission, the power consumption of the communication system is an important factor. In order to facilitate low-power transmission, a new type of DFT precoding FBMC-OQAM system based on data mapping has been proposed in recent years on the basis of the traditional FBMC-OQAM system to reduce the peak-to-average ratio of the transmitted signal, improve the efficiency of the power amplifier, and achieve low-power transmission. In the data-mapped DFT precoding FBMC-OQAM system, how to achieve efficient carrier frequency deviation and channel estimation is an important issue in the application of the FBMC system.

[0004] In the FBMC-OQAM system, due to the superposition effect of symbols, it is difficult to construct the synchronization sequence; in addition, as a real orthogonal system, FBMC-OQAM has inherent imaginary interference between its data, which will cause interference at the pilot point when using the pilot for channel estimation, thus affecting the channel estimation. In addition, in wireless communications, carrier frequency deviation will cause serious inter-carrier interference, and the accuracy of channel estimation is directly related to the demodulation performance of the system. Summary of the invention

[0005] To solve the above problems, the present invention proposes an Internet of Things DFT precoding FBMC carrier synchronization and channel estimation method, designs a training sequence with a lower peak-to-average ratio, and uses the training sequence to achieve carrier synchronization and channel estimation.

[0006] A method for DFT precoding FBMC carrier synchronization and channel estimation for the Internet of Things, comprising the following steps:

[0007] The FBMC symbol data to be transmitted is obtained, and three consecutive training sequence symbols are constructed. The data sequence structures of the three consecutive training sequence symbols are respectively expressed as follows:

[0008]

[0009] Among them, j n、j n+1 、j n+2 is the phase factor term required for OQAM modulation, n is the symbol number, z(k) is the first M / 4 sequence values ​​of the CAZAC sequence with a length of M / 2-1, w(k) is a weighted coefficient sequence, when k=1, 2, ..., M / 4-1, the value is the reciprocal value of the weighted superposition of the corresponding filter signal value, and M is the number of subcarriers in the FBMC system;

[0010] The three consecutively placed training sequence symbols together with other data symbols that have completed conjugate symmetric mapping are subjected to pre-FFT, IFFT subcarrier modulation, and multi-phase filtering of the data mapping DFT precoding FBMC-OQAM system to obtain the corresponding transmission signal in the time domain;

[0011] At the receiving end, the received signal is subjected to multi-phase filtering and IFFT subcarrier demodulation to obtain a received data signal. In the second training sequence symbol, the data on the 0th, 2nd, 4th, ..., M-1th subcarriers are used as pilot points for channel estimation.

[0012] Furthermore, the three consecutively placed training sequence symbols are superimposed in the time domain transmission signal to form a special time domain conjugate symmetric CAZAC sequence with a length of M / 2, and the special time domain conjugate symmetric CAZAC sequence is used to perform carrier synchronization detection, which specifically includes the following steps:

[0013] The three training symbol sequences are divided by the phase factor j n 、j n+1 、j n+2 The rest is represented by z'. The first and second halves of z' are the same and have a conjugate symmetry relationship inside. The first or second half of z' is represented by u and u # Two length M / 4 sequence vectors are represented, where u # is a specific conjugate symmetric sequence of u;

[0014] At the receiver, a local sequence u'=[-(u # ) * ,u * ], where the superscript * means taking conjugate, taking two consecutive parts of length M / 4 from the received special time-domain conjugate symmetric CAZAC sequence, and performing correlation operations on the two parts of the sequence except the first value with the corresponding parts of the local sequence to obtain correlation results;

[0015] The correlation result of the first part of the sequence is conjugated and multiplied by the correlation result of the second part of the sequence to obtain a frequency deviation measurement function;

[0016] The fractional frequency offset estimation is obtained according to the frequency offset measurement function, and the carrier frequency offset compensation is performed using the frequency offset estimation value to complete the fractional carrier frequency synchronization.

[0017] Further, the frequency deviation metric function is expressed as:

[0018]

[0019] Wherein, l represents the sampling sequence number, r(l) is the sampling value of the received signal, u'(l) is the sequence value of the local sequence, v is the frequency offset, Δl is the starting position of the sampling sequence number of the special time domain sequence, and F is the subcarrier spacing;

[0020] At this time, the estimated value of the frequency deviation v is By obtaining the phase of the frequency deviation metric function J(v), we can obtain:

[0021]

[0022] Among them, angle() is a phase operation.

[0023] Furthermore, in the second training sequence symbol, the data on the 0th, 2nd, 4th, ..., M-1th subcarriers are used as pilot points for channel estimation, which is expressed as:

[0024]

[0025] in, is the channel coefficient of the mth subcarrier position in the second training symbol of the symbol, b m,n is the pilot data value at the mth subcarrier position, which is the sequence c2 / j n+1 The mth value of the Fourier transform result sequence, y m，n is the filtered frequency domain signal value received corresponding to the pilot signal point, j m is the phase factor.

[0026] Furthermore, w(k) is a weighted coefficient sequence. When k=1, 2, ..., M / 4-1, the value is the inverse value of the weighted superposition of the corresponding filter signal value, which is expressed as:

[0027]

[0028] Among them, p1, p2, ... p 4K is a sequence block of the prototype filter signal divided into length M / 4, and K is the overlap factor.

[0029] Furthermore, the z(k) is a ZC sequence of length M / 4-1, which is expressed as:

[0030]

[0031] Among them, o is the root sequence number and Nc is the sequence length.

[0032] Furthermore, the signal transmission process from the transmitting end to the receiving end of the data mapping DFT precoding FBMC-OQAM system includes the following steps:

[0033] The original signal to be transmitted is grouped, converted into serial and parallel signals, conjugate-symmetric mapped, special training sequences are inserted, and DFT precoding is performed to obtain a data sequence in which real and virtual signals are alternately arranged;

[0034] Perform IFFT conversion and multi-phase filtering on the data sequence and output the baseband transmission signal, which is then sent to the channel after carrier frequency modulation;

[0035] The signal received from the channel is subjected to polyphase filtering, FFT subcarrier demodulation, equalization and OQAM demodulation to obtain real data;

[0036] After adding phase factors, IFFT conversion, demapping and serial-to-parallel conversion operations to the real data, the data is output.

[0037] Furthermore, the conjugate symmetric mapping comprises the following steps:

[0038] For any nth set of original data, use vector x n Indicates that the original data x n The nth group of data sequences mapped is represented by vector b n express;

[0039] The nth group of original data x n The following formula is used to map the nth group of data sequence b that satisfies the specific conjugate symmetry property. n :

[0040]

[0041] Among them, the value range of n is a non-negative integer; x n (k) represents the nth group of original data x n The kth data in b n (k) is represented by the nth group of data sequence b n The kth data in ; those marked with superscript * represent conjugate values; is the real part operation; It is the operation of taking the imaginary part.

[0042] The present invention provides an Internet of Things DFT precoding FBMC carrier synchronization and channel estimation method, which has the following beneficial effects:

[0043] The present invention constructs a conjugate symmetric special training sequence, inserts the special training sequence into the signal conjugate symmetric mapping of the transmitting end of the FBMC-OQAM system or before the signal conjugate symmetric mapping, and forms a training sequence with three conjugate symmetric transmitting sequences for channel estimation, and uses the time domain signal characteristics of the special training sequence to estimate and correct the carrier frequency offset. The method uses a set of training sequences to simultaneously realize carrier synchronization and channel estimation, has high spectrum efficiency, low peak-to-average ratio, and low computational complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 This is a flow chart of a channel estimation method for an Internet of Things DFT precoding FBMC system in an embodiment of the present invention;

[0045] Figure 2 This is a flow chart of the DFT precoding FBMC carrier synchronization method for the Internet of Things in an embodiment of the present invention;

[0046] Figure 3 This is a diagram of the architecture of a data mapping DFT precoding FBMC-OQAM system in an embodiment of the present invention;

[0047] Figure 4 This is an example diagram of a data sequence satisfying a specific conjugate symmetry characteristic in an embodiment of the present invention;

[0048] Figure 5 A schematic diagram of a prototype filter signal segmentation in an embodiment of the present invention;

[0049] Figure 6 A schematic diagram of a transmission signal in an embodiment of the present invention;

[0050] Figure 7 Schematic diagram of the construction process of the FBMC signal in an embodiment of the present invention;

[0051] Figure 8 Schematic diagram of inherent imaginary interference of FBMC-OQAM modulation in an embodiment of the present invention;

[0052] Fig. 9 Schematic diagram of root mean square error performance evaluation of carrier estimation in an embodiment of the present invention;

[0053] Fig.10 It is a schematic diagram of the bit error rate performance of channel estimation in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0055] The present invention aims at a novel data mapping DFT precoding FBMC-OQAM system and proposes an Internet of Things DFT precoding FBMC carrier synchronization and channel estimation method, which can complete the carrier frequency offset estimation and channel estimation functions while having low complexity.

[0056] The data mapping DFT precoding FBMC-OQAM system architecture is shown in the figure below: Figure 3 As shown, specifically including:

[0057] The data mapping DFT precoding FBMC-OQAM system transmitter includes a preprocessing module and a transmitting module; the preprocessing module is used to preprocess the original data to be transmitted to obtain the real and virtual alternating pretransmission data that meets the real orthogonal requirements of the FBMC-OQAM system; the transmitting module is used to send the preprocessed pretransmission data from the transmitting end. The preprocessing module includes: a front serial-to-parallel conversion module 21, a conjugate symmetry module 22, a front FFT module 23, a front IFFT module 24 and a front polyphase filtering module 25.

[0058] The pre-serial-to-parallel conversion module 21 is used to group the pre-transmitted original data and perform serial-to-parallel conversion on each group of original data. In one embodiment, the length of each group of original data is set to M / 2, where M is the number of subcarriers in the FBMC-OQAM system, M=2 L , L is a natural number greater than 2.

[0059] The conjugate symmetry module 22 is used to map each set of original data after serial-to-parallel conversion into a data sequence that satisfies a specific conjugate symmetry property. n Indicates that the original data x n The nth group of data sequences mapped is represented by vector b n Indicates; the nth group of original data x n The following formula is used to map the nth group of data sequence b that satisfies the specific conjugate symmetry property. n :

[0060]

[0061] Among them, the value range of n is a non-negative integer; x n (k) represents the nth group of original data x n The kth data in b n (k) is represented by the nth group of data sequence b n The kth data in Figure 4 shown.

[0062] The pre-FFT module 23 is used to perform DFT precoding on each group of mapped data sequences to obtain real and imaginary alternating pre-transmission data that meets the real orthogonality requirement of the FBMC-OQAM system.

[0063] The pre-IFFT module 24 is used to perform IFFT conversion on the DFT precoded data sequence, that is, to perform subcarrier modulation of the FBMC-OQAM system.

[0064] The pre-polyphase filtering module 25 is used to perform polyphase filtering on the data sequence signal after subcarrier modulation and output a baseband transmission signal, which is then sent to the channel 26 after carrier frequency modulation by the intermediate frequency and radio frequency processing units.

[0065] The receiving end of the FBMC-OQAM system includes a receiving module and a post-processing module; the receiving module is used to obtain real data by performing multi-phase filtering, FFT subcarrier demodulation, equalization and OQAM demodulation operations on the received baseband signal; the post-processing module is used to add phase factors, IFFT conversion, demapping and serial-to-parallel conversion operations to the real data obtained by the receiving module, and then use it as the output data of the FBMC-OQAM system. Among them, the receiving module includes a post-multi-phase filtering module 31, a post-FFT module 32 and a demodulation output module 33; the post-multi-phase filtering module 31, the post-FFT module 32 and the demodulation output module 33 are used to perform multi-phase filtering, FFT subcarrier demodulation, equalization and OQAM demodulation operations on the signal received from the channel 26, respectively.

[0066] Based on the above system, the present invention proposes an Internet of Things DFT precoding FBMC carrier synchronization and channel estimation method, constructs a conjugate symmetric special training sequence, inserts the special training sequence into the FBMC-OQAM system after the signal conjugate symmetric mapping or before the signal conjugate symmetric mapping at the transmitting end, and forms a synchronization sequence with three conjugate symmetric transmitting sequences for signal estimation, and uses the frequency domain characteristics of the special training sequence to estimate and correct the carrier frequency offset.

[0067] The specific process is as follows Figure 1 As shown, the method comprises the following steps:

[0068] S1. Obtain the FBMC signal to be transmitted.

[0069] Observe the construction process and characteristics of the FBMC signal, such as Figure 7 As shown, in the mapped DFT precoding FBMC system, the final transmission signal is composed of the mapped data copied to the same length as the prototype filter and then point-to-point multiplied with the prototype filter to generate an FBMC symbol signal. The different symbols before and after are offset and superimposed to obtain the final transmission signal.

[0070] S2. Use this transmission signal construction process to design a synchronization sequence; construct three consecutive training sequence symbols. Assume that the training sequence symbol numbers are: n, n+1, n+2. The data sequence structures of the three consecutive training sequence symbols are respectively expressed as:

[0071]

[0072] Wherein, M is the number of subcarriers in the FBMC system, which is generally assumed to be an even number; the value 1 in the sequence can be any other real value, in particular, the first 1 and the third 1 can be any complex number and its conjugate value respectively; the z(k) sequence is the first M / 4 part of the CAZAC sequence with a length of M / 2-1, and the CAZ AC sequence can be a ZC sequence:

[0073]

[0074] Where o is the root sequence number and Nc is the sequence length.

[0075] w(k) is a weighted coefficient sequence. When k = 1, 2, ..., M / 4-1, the value is the inverse value of the weighted superposition of the corresponding filter signal value:

[0076]

[0077] Among them, p1, p2, ... p 4K is the prototype filter signal divided into sequence blocks of length M / 4, and K is the overlap factor.

[0078] If the phase factor j is not considered in the three training sequences n If the influence of the same sequence is not obtained, it has the same sequence form, represented by z'. The first half and the second half of z' are the same, and there is a conjugate symmetry relationship inside. z' can be represented by u and u # Two sequence vectors of length M / 4 are represented.

[0079] The data sequence is DFT precoded (pre-FFT module) to obtain real and virtual alternating pre-transmission data that meets the real orthogonal requirements of the FBMC-OQAM system, and the transmission signal sequence is obtained after IFFT subcarrier modulation and multi-phase filtering; the training sequence is superimposed in the transmission signal by DFT precoding, IFFT subcarrier modulation, and multi-phase filtering to form a uu with a length of M / 2. # The sequence is parsed as follows Figure 5 , 6 shown.

[0080] For the DFT precoded FBMC system, the training data is subjected to DFT precoding, IDFT subcarrier modulation, and multi-phase filtering operations to obtain the transmission signal. Since DFT precoding and IDFT subcarrier modulation are a pair of inverse transforms, when performing multi-phase filtering, it is equivalent to copying the data of each training symbol into K copies (K is the overlap factor), and then multiplying it point-to-point with the prototype filter signal to obtain a single FBMC symbol transmission signal. Finally, multiple FBMCs are offset by one symbol period and superimposed to obtain the final transmission signal s(t). For the convenience of representation, the present invention segments the prototype filter sequence, and the segment length is M / 4, such as Figure 5 According to the above process, since the filter energy is mainly concentrated in the middle six blocks, ignoring the superposition effect of other segments, then Figure 6 The transmitted signal sequence within the red dashed line portion, except for the first value, corresponding to the part of u can be expressed as follows (assuming that the sequence number k in this part of the sequence is 1, 2, ..., M / 4-1):

[0081]

[0082] Similarly, corresponding to u # Partially expressed as:

[0083]

[0084] Among them, the last step in the above formula is derived from the symmetry characteristics of the filter signal, such as Figure 6 shown.

[0085] S3, carrier synchronization detection: three consecutively placed training sequence symbols are superimposed in the time domain transmission signal to form a special time domain conjugate symmetric CAZAC sequence of length M / 2, and the special time domain conjugate symmetric CAZAC sequence is used to perform carrier synchronization detection, specifically including the following steps:

[0086] The three training symbol sequences are divided by the previous phase factor j n 、j n+1 、j n+2 The rest is represented by z'. The first and second halves of z' are the same, and there is a conjugate symmetry relationship inside. The first or second half of z' can be represented by u and u # Two length M / 4 sequence vectors are represented, where u # is a specific conjugate symmetric sequence of u.

[0087] At the receiver, a local sequence u'=[-(u # ) * ,u *], where the superscript * means taking the conjugate, taking two consecutive parts of length M / 4 from the received special time-domain conjugate symmetric CAZAC sequence, and performing correlation operations on the two parts of the sequence except the first value with the corresponding parts of the local sequence to obtain the correlation results.

[0088] The correlation result of the first part of the sequence is conjugated and multiplied with the correlation result of the second part of the sequence to obtain a frequency deviation measurement function; a fractional frequency deviation estimate is obtained according to the frequency deviation measurement function, and the frequency deviation estimate is used to perform carrier frequency deviation compensation to complete fractional carrier frequency synchronization.

[0089] Among them, the frequency deviation measurement function is expressed as:

[0090]

[0091] Wherein, l represents the sampling sequence number, r(l) is the sampling value of the received signal, u'(l) is the sequence value of the local sequence, v is the frequency offset, Δl is the starting position of the sampling sequence number of the special time domain sequence, and F is the subcarrier spacing.

[0092] At this time, the estimated value of the frequency deviation v is By obtaining the phase of the frequency deviation metric function J(v), we can obtain:

[0093]

[0094] Among them, angle() is a phase operation.

[0095] The carrier estimation method of the training sequence in the present invention is simulated by MATLAB. The system frequency deviation is set to 0.5 times the subcarrier spacing. The root mean square error (RMSE) performance of the carrier estimation is as follows: Fig. 9 As shown, good estimation performance is achieved.

[0096] S4. After the transmitted signal reaches the receiver through the channel, the received signal r(t) is subjected to receiving filtering, IFFT subcarrier demodulation and other operations to obtain the received data symbol y m，n :

[0097]

[0098] Among them, x m,n is the real number data corresponding to the transmitter, is the channel coefficient of this point, the second term in the above formula is the imaginary interference from the surrounding data signal, and the third term is the noise.

[0099] According to the system principle of FBMC-OQAM, the imaginary interference has symmetrical characteristics, such as Figure 8The training sequence designed by the present invention, after DFT precoding, forms a data arrangement in the time-frequency domain as shown in Table 1:

[0100] Table 1 Data arrangement

[0101] nth symbol (training symbol 1) The n+1th symbol (training symbol 2) The n+2th symbol (training symbol 3) <![CDATA[j n b 0，n ]]> <![CDATA[j n+1 b 0，n ]]> <![CDATA[j n+2 b 0，n =-j n b 0，n ]]> 0 0 0 <![CDATA[j n b 2，n ]]> <![CDATA[j n+1 b 2，n ]]> <![CDATA[j n+2 b 2，n =-j n b 2，n ]]> 0 0 0 … … … <![CDATA[j n b m，n ]]> <![CDATA[j n+1 b m，n ]]> <![CDATA[j n+2 b m，n =-j n b m，n ]]> … … … 0 0 0 <![CDATA[j n b M-1，n ]]> <![CDATA[j n+1 b M-1，n ]]> <![CDATA[j n+2 b M-1，n =-j n b M-1，n ]]>

[0102] According to the arrangement of the data in Table 1, combined with the symmetric distribution of the imaginary interference, it can be seen that at the non-zero data point position in the second training symbol, the imaginary interference superposition is approximately 0, so these data points can be used as pilots to directly perform channel estimation. 0，n , 0, b 2，n , 0, …, b m，n , 0, …, 0, b M-1，n ] The sequence is the training sequence c2 with j removed n+1 DFT calculation result after factor term.

[0103] At this time, the channel coefficient can be directly estimated using the pilot points in the second training symbol, that is:

[0104]

[0105] in, is the channel coefficient of the mth subcarrier position of the symbol, b m,n is the data value of the mth subcarrier position, which is the sequence c2 / j n+1 The mth value of the Fourier transform result sequence, y m,n is the filtered frequency domain signal value received corresponding to the pilot signal point, j m is the phase factor.

[0106] The channel estimation method for the training sequence in the present invention is simulated with MATLAB, and the bit error rate performance is as follows: Fig.10 As shown, good estimation performance is achieved.

[0107] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for DFT precoding FBMC carrier synchronization and channel estimation for the Internet of Things, characterized in that: The following steps are involved: The FBMC symbol data to be transmitted is obtained, and conjugate symmetric mapping is performed, and three consecutive training sequence symbols are constructed at the same time. The data sequence structures of the three consecutive training sequence symbols are respectively expressed as follows: Among them, j n 、j n+1 、j n+2 is the phase factor term required for OQAM modulation, n is the symbol number, z(k) is the first M / 4 sequence values ​​of the CAZAC sequence with a length of M / 2-1, w(k) is a weighted coefficient sequence, when k=1, 2, ..., M / 4-1, the value is the reciprocal value of the weighted superposition of the corresponding filter signal value, and M is the number of subcarriers in the FBMC system; The three consecutively placed training sequence symbols together with other data symbols that have completed conjugate symmetric mapping are subjected to pre-FFT, IFFT subcarrier modulation, and multi-phase filtering of the data mapping DFT precoding FBMC-OQAM system to obtain the corresponding transmission signal in the time domain; At the receiving end, the received signal is subjected to multi-phase filtering and IFFT subcarrier demodulation to obtain a received data signal. In the second training sequence symbol, the data on the 0th, 2nd, 4th, ..., M-1th subcarriers are used as pilot points for channel estimation.

2. According to claim 1, a method for DFT precoding FBMC carrier synchronization and channel estimation of the Internet of Things is characterized in that: The three consecutively placed training sequence symbols are superimposed in the time domain transmission signal to form a special time domain conjugate symmetric CAZAC sequence with a length of M / 2, and the special time domain conjugate symmetric CAZAC sequence is used to perform carrier synchronization detection, which specifically includes the following steps: The three training symbol sequences are divided by the phase factor j n 、j n+1 、j n+2 The rest is represented by z'. The first and second halves of z' are the same and have a conjugate symmetry relationship inside. The first or second half of z' is represented by u and u # Two length M / 4 sequence vectors are represented, where u # is a specific conjugate symmetric sequence of u; At the receiver, a local sequence u'=[-(u # ) * ,u * ], where the superscript * means taking conjugate, taking two consecutive parts of length M / 4 from the received special time-domain conjugate symmetric CAZAC sequence, and performing correlation operations on the two parts of the sequence except the first value with the corresponding parts of the local sequence to obtain correlation results; The correlation result of the first part of the sequence is conjugated and multiplied by the correlation result of the second part of the sequence to obtain a frequency deviation measurement function; The fractional frequency offset estimation is obtained according to the frequency offset measurement function, and the carrier frequency offset compensation is performed using the frequency offset estimation value to complete the fractional carrier frequency synchronization.

3. The method for DFT precoding FBMC carrier synchronization and channel estimation for the Internet of Things according to claim 2, characterized in that: The frequency deviation metric function is expressed as: Wherein, l represents the sampling sequence number, r(l) is the sampling value of the received signal, u'(l) is the sequence value of the local sequence, v is the frequency offset, Δl is the starting position of the sampling sequence number of the special time-domain conjugate symmetric CAZAC sequence, and F is the subcarrier spacing; At this time, the estimated value of the frequency deviation v is By obtaining the phase of the frequency deviation metric function J(v), we can obtain: Among them, angle() is a phase operation.

4. The method for DFT precoding FBMC carrier synchronization and channel estimation for the Internet of Things according to claim 1, characterized in that: In the second training sequence symbol, the data on the 0th, 2nd, 4th, ..., M-1th subcarriers are used as pilot points for channel estimation, which is expressed as: in, is the channel coefficient of the mth subcarrier position in the second training symbol of the symbol, b m,n is the pilot data value at the mth subcarrier position, which is the sequence c2 / j n+1 The mth value of the Fourier transform result sequence, y m,n is the filtered frequency domain signal value received corresponding to the pilot signal point, j m is the phase factor.

5. The method for DFT precoding FBMC carrier synchronization and channel estimation for the Internet of Things according to claim 1, characterized in that: The w(k) is a weighted coefficient sequence. When k=1, 2, ..., M / 4-1, the value is the inverse value of the weighted superposition of the corresponding filter signal value, which is expressed as: Among them, p1, p2, ... p 4K is a sequence block of the prototype filter signal divided into length M / 4, and K is the overlap factor.

6. The method for DFT precoding FBMC carrier synchronization and channel estimation for the Internet of Things according to claim 1, characterized in that: The z(k) is a ZC sequence of length M / 4-1, which is expressed as: Among them, o is the root sequence number and Nc is the sequence length.

7. The method for DFT precoding FBMC carrier synchronization and channel estimation for the Internet of Things according to claim 1, characterized in that: The signal transmission process from the data mapping DFT precoding FBMC-OQAM system transmitting end to the receiving end includes the following steps: The original signal to be transmitted is grouped, converted into serial and parallel signals, conjugate-symmetric mapped, special training sequences are inserted, and DFT precoding is performed to obtain a data sequence in which real and virtual signals are alternately arranged; Perform IFFT conversion and multi-phase filtering on the data sequence and output the baseband transmission signal, which is then sent to the channel after carrier frequency modulation; The signal received from the channel is subjected to polyphase filtering, FFT subcarrier demodulation, equalization and OQAM demodulation to obtain real data; After adding phase factors, IFFT conversion, demapping and serial-to-parallel conversion operations to the real data, the data is output.

8. The method for DFT precoding FBMC carrier synchronization and channel estimation for the Internet of Things according to claim 7, characterized in that: The conjugate symmetric mapping comprises the following steps: For any nth set of original data, use vector x n Indicates that the original data x n The nth group of data sequences mapped is represented by vector b n express; The nth group of original data x n The following formula is used to map the nth group of data sequence b that satisfies the specific conjugate symmetry property. n : Among them, the value range of n is a non-negative integer; x n (k) represents the nth group of original data x n The kth data in b n (k) is represented by the nth group of data sequence b n The kth data in ; those marked with superscript * represent conjugate values; is the real part operation; It is the operation of taking the imaginary part.

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