CN109474412A - A Universal Filtered Multi-Carrier Method Based on Selective Mapping - Google Patents

Abstract

The present invention provides a general filtering multi-carrier method based on selection mapping. The sub-carriers are divided into B sub-bands, and each sub-band is expanded into U different candidate sub-bands. For the candidate sub-bands, each candidate sub-band are multiplied by a set of randomly generated twiddle factors, and an FIR filter is used to filter the sub-carriers of each sub-band, and the sub-band with the smallest peak-to-average power ratio is selected from the candidate sub-bands of the transmitting end for transmission. The transmission signals in the selected B sub-bands are superimposed in the time domain to form a new transmission signal, the received signal is subjected to fast Fourier transform to remove the interference signal, and the transmission signal is directly recovered from the received signal by linear equalization. , and the equalized signal performs the inverse operation of the twiddle factor to reconstruct the original transmitted signal. The PAPR performance of the invention is effectively improved and has certain engineering application value.

Description

A Universal Filtered Multi-Carrier Method Based on Selective Mapping

technical field

The present invention relates to the technical field of wireless communication, in particular to a general filtering multi-carrier method.

Background technique

In the 4G era, the commercialization of LTE-Advanced basically meets people's needs for multiple transmissions such as voice, video, and network, and greatly enriches people's growing spiritual and cultural life. However, with the continuous improvement of image resolution and the increase of user online time, mobile data traffic has exploded exponentially, massive IoT devices are emerging, and new application scenarios are emerging, such as: holographic projection, unmanned driving, robots, Artificial intelligence, augmented reality, and mobile social networking, etc. The existing 4G network can no longer meet the needs of future communication, and 5G came into being in this context. Different from the single application scenario of 4G, IoT and M2M communication will become the main driving force of 5G communication. In other words, 5G will mainly solve the performance challenges faced in multiple scenarios. 5G technology needs to comprehensively consider multiple technical indicators such as peak rate, spectrum efficiency, network energy efficiency and delay, effectively support various types of services, and meet the characteristics of large capacity, multiple access, high mobility, high transmission rate and low delay .

OFDM is widely used in LTE, WiMAX, WIFI, HIPERLAN/2, DVB, ADSL and other wired and wireless occasions due to its advantages of anti-multipath fading, low complexity and seamless integration of multi-antenna technology. However, higher peak power, out-of-band radiation, and strict time synchronization limit the discontinuous spectrum of carrier aggregation, while looser synchronization and localized spectrum characteristics will be one of the most important requirements for the physical layer of future wireless networks. This also makes IMT-2020 need to seek more diverse transmission technologies. Generalized frequency division multiplexing (GFDM) has attracted the attention of scholars, because only one cyclic prefix (CP) is used for a group of symbols instead of CP for each symbol, GFDM has higher bandwidth than OFDM efficiency. The variable filter design and the sparse nature of the signal make GFDM robust to synchronization errors and more suitable for interactive scenarios with spectral fragmentation. However, the use of large size FFT and successive interference cancellation (SIC) algorithm causes high complexity and decoding delay at the receiver. Non-orthogonal waveform design also makes GFDM and FBMC face the same dilemma: complex pilot design and incompatible multi-antenna technology.

After the development of previous generations of communication technologies, the requirements of eMBB have been basically met, but the wireless technologies that meet the communication scenarios of uRLLC and mMTC have not been sufficiently developed. That is to say, it is particularly urgent to study the low-latency wireless transmission technology for small packet transmission that satisfies IoT and M2M communication. UFMC is a new filtering transmission mechanism to meet this demand. By dividing the entire frequency band into several groups of sub-bands, and filtering the carriers of each group of sub-bands, UFMC reduces the length of the filter and the out-of-band power. The modulation method of QAM is adopted, which is seamlessly connected with MIMO technology, which is very suitable for short uplink burst communication or low-latency communication. However, the higher PAPR affects the energy efficiency of UFMC and does not meet the requirements of 5G green communication.

The traditional solution to the PAPR problem in multicarrier systems is to lower the operating point of the nonlinear power amplifier, an approach that usually results in a significant loss of power efficiency. To solve this problem, many researchers have proposed different solutions. For example: clipping method (ACF), constellation expansion method (ACE), selective mapping method (SLM) and partial transmission sequence method (PTS). Among them, SLM has attracted the attention of a large number of scholars, because of its better performance and no interference and distortion characteristics. Although the PAPR of OFDM has been well known, the PAPR research of UFMC has not received enough attention. According to the current literature review, only W RONG has proposed a low-complexity PTS (LC-PTS) UFMC to reduce the PAPR of the system. Unfortunately, the system performance has declined.

SUMMARY OF THE INVENTION

In order to overcome the deficiencies of the prior art, the present invention provides a general filtering multi-carrier method based on selective mapping.

The technical scheme adopted by the present invention to solve its technical problem comprises the following steps:

(1) At the transmitting end, the sub-bands are first divided according to the number of carriers, and the total number of sub-carriers N is divided into B sub-bands;

(2) expanding each subband into U different candidate subbands, the transmitting end generates BU different candidate subbands in total, and the candidate subbands all contain the data information originally transmitted by the transmitting end;

(3) For BU candidate subbands, each candidate subband is multiplied by a set of randomly generated twiddle factors B ^(u) , B ^(u) = [b _u,0 ,b _u,1 ,...,b _{u ,N/B-1} ] ^T , where u=1,2,...,U,b _u,N/B-1 ∈{±1,±j}, the rotated signal is represented as S _i,j =[b _i,0 S _0, b _i,1 S _1,..., b _i,N/B-1 S _N/B-1 ], where i=1,2,...,B,j=1,2 ,…,U;

(4) The signal in the frequency domain is transformed into the time domain by inverse fast Fourier transform, which is expressed as:

where S _i,j (k) is the candidate signal in the frequency domain, and O _i is the subcarrier index set in the ith subband;

(5) Use an FIR filter to filter the sub-carriers of each sub-band. The time-domain impulse response of the filter of the i-th sub-band is fi, i=1,2,...,B, and the filtered signal x is obtained _i,j (l), in order to simplify the analysis, the same filtering process is applied to the U candidate subbands, which is expressed as:

x _i,j (l)=s _i,j (l)*f _i (l)l=0,1,...,N+L-2 (2)

Among them, * represents the linear convolution operation, and _si,j (l) represents the time domain signal;

(6) The transmitting end selects a subband with the smallest peak-to-average power ratio from every U candidate subbands for transmission, and transmits a total of B subband signals x _i . The selected subband index and twiddle factor are in the form of sideband information Sent to the receiver to reproduce the received signal information:

x _i (l)=min{x _i,j (l)}l=0,1,...,N+L-2 (3)

(7) The transmission signals in the B subbands selected from the BU subbands are superimposed in the time domain to form a new transmission signal, which is expressed as:

(8) At the receiving end, fast Fourier transform is performed on the received signal at 2N points, and the signal in the time domain is converted into the signal Y in the frequency domain, which is expressed as:

Y=WPHFVS+WPn∈C ^2N×1 (5)

where W is a 2N-point FFT transform matrix, P is an extended identity matrix, H is a Toeplitz matrix related to the channel impulse response, F is a matrix composed of Toeplitz matrices, and V is an inverse Fourier transform matrix The formed diagonal matrix, S is the signal matrix formed by the frequency domain signal to be sent after selection;

(9) The even-digit signal in the received signal Y is the signal that needs to be demodulated, the odd-digit signal is the interference signal, the odd-digit signal is discarded, and only the even-digit signal is demodulated, and the demodulated signal after the interference signal is removed Y _i is expressed as:

Y _i =P _i ^T WPHFVS+P _i ^T WPn∈C ^N×1 (6)

Let Φ=P _i ^T WPHFV, Φ is a diagonal matrix, and P _i is a 2N×N matrix. Therefore, the signal Y _i (k), i=1,...,B of the kth subcarrier depends only on the transmission the signal S _i,j (k) and the diagonal matrix Φ;

(10) The transmitted signal is directly recovered from the received signal by the method of linear equalization, and the zero-forcing equalization (ZF) and the minimum mean square error equalization (MMSE) are used to restore the signal;

Among them, Φ(k) is the equalization coefficient of the kth subcarrier, σ is the ratio of signal and noise power, and * represents the conjugate transpose operator;

(11) Assuming that the receiving end has a transmitted copy of the twiddle factor, the equalized signal performs the inverse operation of the twiddle factor to reconstruct the original transmitted signal.

The twiddle factor in the step (3) can be a cyclic shift sequence, a Hadamard sequence, a Riemann sequence or a Helmert sequence.

The beneficial effect of the present invention is that compared with the traditional UFMC, the PAPR performance is effectively improved. The simulation results show that SLM-UFMC can reduce the PAPR of UFMC by up to 1.8dB at Prob(PAPR>PAPRO)=10 ^-4 . As the number of candidate subbands increases, the PAPR performance of the system is further improved. In the case of unrestricted hardware, the present invention has certain engineering application value. The present invention improves the energy efficiency of UFMC, and is more in line with the requirements of 5G green communication, and it is easy to combine with non-orthogonal multiple access technology. Further increase the capacity of the system. At the same time, this also lays the foundation for the large-scale application of the UFMC system in the future 5G small packet low-latency transmission scenarios and the Internet of Things and machine-to-machine communication.

Description of drawings

FIG. 1 is a typical structural diagram of the universal filtering multi-carrier system of the present invention.

FIG. 2 is a block diagram of a general filtering multi-carrier system based on selection mapping of the present invention.

FIG. 3 is a comparison of PAPR performance under different modulation modes of the OFDM, UFMC, SLM-OFDM and SLM-UFMC systems of the present invention.

FIG. 4 shows the performance of SLM-UFMC PAPR under different numbers of candidate subbands of the present invention.

Detailed ways

The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

Due to the sub-band filtering of UFMC, SLM and UFMC cannot be simply combined, but some modules need to be adjusted. After a reasonable design, a general filtering multi-carrier system based on selective mapping is proposed. Through the combination of UFMC and SLM, the PAPR performance of the system is effectively improved. The simulation also shows that SLM-UFMC can reduce the PAPR of UFMC by as much as 1.8dB at Prob(PAPR>PAPR0)=10 ^-4 , which also makes SLM-UFMC more in line with the requirements of 5G green communication, and the present invention is easy and non-positive The combination of multiple access technology further improves the capacity of the system, which also lays the foundation for the large-scale application of UFMC in future 5G small packet low-latency transmission scenarios, as well as in the Internet of Things and machine-to-machine communication.

(1) At the transmitting end, the sub-bands are first divided according to the number of carriers, and the total number of sub-carriers N is divided into B sub-bands;

(2) expanding each subband into U different candidate subbands, the transmitting end generates BU different candidate subbands in total, and the candidate subbands all contain the data information originally transmitted by the transmitting end;

(3) For BU candidate subbands, each candidate subband is multiplied by a set of randomly generated twiddle factors B ^(u) , B ^(u) = [b _u,0 ,b _u,1 ,...,b _{u ,N/B-1} ] ^T , where u=1,2,…,U, b _u,N/B-1 ∈{±1,±j}, different twiddle factors bring different system performance, also Other types of twiddle factors can be used, such as cyclic shift sequences, Hadamard sequences, Riemann sequences or Helmert sequences, and the rotated signal is represented as S _i,j =[b _i,0 S _0, b _i,1 S _{1,. ..,} b _{i, N/B-1} S _N/B-1 ], where i=1,2,...,B, j=1,2,...,U;

(4) The signal in the frequency domain is transformed into the time domain by inverse fast Fourier transform, which is expressed as:

where S _i,j (k) is the candidate signal in the frequency domain, and O _i is the subcarrier index set in the ith subband;

(5) Use an FIR filter to filter the sub-carriers of each sub-band. The time-domain impulse response of the filter of the i-th sub-band is fi, i=1,2,...,B, and the filtered signal x is obtained _i,j (l), in order to simplify the analysis, the same filtering process is applied to the U candidate subbands, which is expressed as:

x _i,j (l)=s _i,j (l)*f _i (l)l=0,1,...,N+L-2 (2)

Among them, * represents the linear convolution operation, and _si,j (l) represents the time domain signal;

(6) The transmitting end selects a subband with the smallest peak-to-average power ratio from every U candidate subbands for transmission, and transmits a total of B subband signals x _i . The selected subband index and twiddle factor are in the form of sideband information Sent to the receiver to reproduce the received signal information:

x _i (l)=min{x _i,j (l)}l=0,1,...,N+L-2 (3)

(7) The transmission signals in the B subbands selected from the BU subbands are superimposed in the time domain to form a new transmission signal, which is expressed as:

(8) At the receiving end, for the received signal, the traditional method is to perform zero-filling operation on it, that is, a certain number of zeros are added to the back of the received signal, so that the length of the received signal is 2N. The received signal at the 2N point is subjected to fast Fourier transform, and the signal in the time domain is converted into the signal Y in the frequency domain, which is expressed as:

Y=WPHFVS+WPn∈C ^2N×1 (5)

where W is a 2N-point FFT transform matrix, P is an extended identity matrix, H is a Toeplitz matrix related to the channel impulse response, F is a matrix composed of Toeplitz matrices, and V is an inverse Fourier transform matrix The formed diagonal matrix, S is the signal matrix formed by the frequency domain signal to be sent after selection;

(9) The even-digit signal in the received signal Y is the signal that needs to be demodulated, the odd-digit signal is the interference signal, the odd-digit signal is discarded, and only the even-digit signal is demodulated, and the demodulated signal after the interference signal is removed Y _i is expressed as:

Y _i =P _i ^T WPHFVS+P _i ^T WPn∈C ^N×1 (6)

Let Φ=P _i ^T WPHFV, Φ is a diagonal matrix, and P _i is a 2N×N matrix. Therefore, the signal Y _i (k), i=1,...,B of the kth subcarrier depends only on the transmission the signal S _i,j (k) and the diagonal matrix Φ;

(10) The transmitted signal is directly recovered from the received signal by the method of linear equalization, and the zero-forcing equalization (ZF) and the minimum mean square error equalization (MMSE) are used to restore the signal;

Among them, Φ(k) is the equalization coefficient of the kth subcarrier, σ is the ratio of signal and noise power, and * represents the conjugate transpose operator;

(11) Assuming that the receiving end has a transmitted copy of the twiddle factor, the equalized signal performs the inverse operation of the twiddle factor to reconstruct the original transmitted signal.

The embodiments of the present invention are as follows:

In order to deeply describe and understand the embodiments of the present invention, the basic principle of the traditional UFMC is firstly analyzed, and its principle block diagram is shown in FIG. 1 .

A total of N sub-carriers are divided into B sub-bands, that is, each sub-band has n=N/B sub-carriers, and the i-th sub-band has the number of sub-carriers n _i , i=1,2,...,B. At the transmitting end, a certain number of bits of information are mapped onto the symbol S by Gray code M-ary quadrature amplitude modulation (M-QAM). Then these symbols are allocated to each subband by means of carrier division, wherein the frequency domain symbol allocated to the ith subband is S _i (i=1, 2, . . . , B). These symbols Si are then transformed to time-domain signals _Si by means of an N-point Inverse Fast Fourier Transform ( _IFFT ). Then, UFMC performs a filtering process on each subband, superimposing and summing all subbands.

For the received signal, the conventional practice is to add a certain number of zeros after the received signal, so that the length of the received signal reaches 2N. Then perform fast Fourier transform on the received signal at point 2N, convert the signal in the time domain into the signal Y in the frequency domain, and the transmitted signal Y _i can be directly recovered from the received signal by equalization, i=1, 2,  … , B.

A general filtering multi-carrier system based on selection mapping proposed by the present invention is implemented as follows, and the block diagram is shown in FIG. 2 .

In SLM-UFMC, a total of N subcarriers are firstly divided into B subbands, and then each subband is expanded into U different candidate subbands. In this way, the transmitter generates BU different candidate subbands. These candidate subbands all contain the originally transmitted data information. After IFFT and filtering processing, B subbands with the smallest PAPR are selected from the BU candidate subbands for superposition transmission. Figure 2 shows the system block diagram of a general filtering multi-carrier system based on selective mapping. For BU candidate subbands, each candidate subband is multiplied by a set of twiddle factors B ^(u) = [b _u,0 ,b _{u ,1} ,...,b _u,N/B-1 ] ^T , where u=1,2,...,U. Different twiddle factors may bring different system performance, such as cyclic shift sequence, Hadamard sequence, Riemann sequence or Helmert sequence, etc. The rotated signal can be expressed as:

S _i,j = [b _i,0 S _0, b _i,1 S _1,..., b _i,N/B-1 S _N/B-1 ] (9)

Among them, i=1,2,...,B, j=1,2,...,U.

The signal in the frequency domain is transformed into the time domain by the inverse fast Fourier transform, and this process is expressed as:

Among them, S _i,j is the candidate signal in the frequency domain, O _i is the subcarrier index set in the ith subband. By performing filtering processing f _i on each group of subcarriers, i=1, 2, . . . , B, the filtered signal x _i,j (l) can be obtained. To simplify the analysis, the same filtering process is applied to the U candidate subbands here. It can be expressed as:

x _i,j (l)=s _i,j (l)*f _i (l)l=0,1,...,N+L-2 (11)

where * denotes a linear convolution operation and s _i,j (l) denotes a time domain signal, where i=1,2,...,B, j=1,2,...,U. The transmitting end selects B subbands x _i with the smallest PAPR from the BU candidate subbands for transmission, i=1, 2,...,B. The selected subband index and twiddle factor information are transmitted to the receiving end in the form of sideband information for reproducing the received signal information.

x _i (l)=min{x _i,j (l)}l=0,1,...,N+L-2 (12)

where i and j are the same as above, and min{·} indicates that the PAPR is the smallest. The selected signals are superimposed in the time domain to form a new transmitted signal, which can be expressed as:

If the above formula is rewritten in matrix form, it can be rewritten as:

Among them, F=[F ₁ , F ₂ ,...,F _B ], V=Λ[V ₁ , V ₂ ,..., V _B ], where Λ represents the diag matrix, Indicates the frequency domain signal to be sent after the minimum PAPR selection, S _B,j is the sent signal corresponding to min{x _B,1 ,x _B,2 ,...,x _B,U }. V _i (i=1,2,...,B) is an N x n _i -dimensional matrix that extracts n _i column vectors from the inverse Fourier transform matrix according to the corresponding subband positions across the available frequency range , the transformation matrices of all subbands just form a complete inverse Fourier transformation matrix. V is a diagonal matrix, and the submatrices on the main diagonal are V ₁ , V ₂ , . . . , V _B . F _i is a (N+L-1)×N-dimensional Toeplitz matrix (L is the length of the linear filter, the filter length of different subbands can be different, and the carrier spacing can also be different), each column of which is composed of The filter impulse response coefficients at the corresponding subband positions are obtained after cyclic shift, and F _i can be adjusted according to the propagation conditions and time-frequency offset of the system.

Assuming that the system has perfect synchronization measures, the received signal y after passing through the channel is regarded as the convolution form of the signal x and the channel h, which is expressed as:

where h is the time-domain impulse response of the channel of length r, * represents a linear convolution with the signal x, H is a Toeplitz matrix related to the channel impulse response, and its first column element is [h ^T ,0 _{1 ×(N+L-2)} ] ^T , its first row element is [h(0),0 _1×(N+L-2) ] ^T , n is a (N+L+r-2) dimension complex white Gaussian noise. If the above formula is rewritten in matrix form, it can be rewritten as:

y=HFVS+n (16)

where H is a Toeplitz matrix related to the channel impulse response, F is a matrix composed of Toeplitz matrices, V is a diagonal matrix composed of an inverse Fourier transform matrix, and S is the frequency domain signal to be sent after selection The formed signal matrix, n is a (N+L+r-2) dimensional complex Gaussian white noise.

For the received signal y, the traditional practice is to perform zero-filling operation on it, that is, a certain number of zeros are added to the back of the received signal, so that the length of the received signal is 2N. Then we perform fast Fourier transform on the received signal at these 2N points, and convert the signal in the time domain into the signal Y in the frequency domain. This process can be expressed as:

Y=WPHFVS+WPn∈C ^2N×1 (17)

where W is the 2N-point FFT transform matrix and P is an extended identity matrix that can be written as In the received signal Y, the even-digit signal is the signal we want to demodulate, and the odd-digit signal is the interference signal. Generally, the odd-digit signal needs to be discarded, and only the even-digit signal is demodulated. This operation can be implemented with a 2N×N matrix _Pi , The demodulated signal Yi after _removing the interference signal can be expressed as:

Y _i =P _i ^T WPHFVS+P _i ^T WPn∈C ^N×1 (18)

Let Φ=P _i ^T WPHFV, where Φ is a diagonal matrix. Therefore, the signal Y _i (k), i=1, . . . , B, depends only on the transmitted signal S _i,j (k) and the diagonal matrix Φ. The transmitted signal is directly reproduced from the received signal by means of linear equalization. Without loss of generality, ZF and MMSE equalization can be used to restore the signal.

in, Indicates the equalized signal. Assuming that the receiving end has a transmitted copy of the twiddle factor, the equalized signal can be reconstructed by performing the inverse operation of the twiddle factor to reconstruct the original transmitted signal.

The peak-to-average power ratio of the SLM-UFMC system is defined as:

Among them, E[|x(l)| ² ] represents the average power of the signal, and max[|x(l)| ² ] represents the maximum power of the signal. Because the PAPR of a single signal cannot reflect the statistical characteristics of the signal, the complementary cumulative distribution function (CCDF) is usually used to describe the PAPR characteristics of the system, that is, the probability that the PAPR is greater than the given threshold PAPR ₀ :

CCDF _PAPR = Prob(PAPR>PAPR ₀ ) (22)

The PAPR performance of OFDM, UFMC and SLM-OFDM systems under different modulation schemes is compared with that of SLM-UFMC. Computer simulation is used to verify the superiority of the PAPR performance of the SLM-UFMC system. Figure 3 shows the comparison of the PAPR performance of the OFDM, UFMC, SLM-OFDM and SLM-UFMC systems under different modulation methods. To comprehensively evaluate the system performance, we adopt two sets of experimental controls, and CCDF is used to evaluate the PAPR performance of the system. The first group adopts 512 subcarriers and 16QAM modulation, and the second group adopts 128 subcarriers and QPSK modulation.

As can be seen from Figure 3, the traditional UFMC faces more severe PAPR than OFDM, which may be because the subband filter impulse response is not equal to 1, which increases the symbol length and affects the statistical characteristics of the system PAPR. This also poses an urgent problem for the application of UFMC in IoT and M2M communication, that is, how to solve the high PAPR problem of UFMC? At the same time, it can be seen from the figure that the PAPR performance of UFMC has decreased by 0.3dB and 0.5dB respectively compared with OFDM, in two groups of experiments Prob(PAPR>PAPR ₀ )=10 ^-3 . By adopting the SLM method, the PAPR of OFDM can be reduced. Compared with OFDM, the performance of SLM-OFDM is improved by about 3dB and 4dB respectively when Prob(PAPR>PAPR ₀ )=10 ^-4 . Moreover, compared with UFMC, the performance of SLM-UFMC is also improved by 0.5dB and 1.8dB respectively at Prob(PAPR>PAPR ₀ )=10 ^-4 . At the same time, it is also noted that the performance of SLM-OFMD is better than that of SLM-UFMC under the same conditions. At 10 ^-4 , the performances differ by 2.8dB and 2.3dB, respectively. This is consistent with the problem discussed earlier, that is to say, under the same conditions, UFMC faces more serious PAPR problems than OFDM. From the perspective of different modulation methods, QPSK modulation has better performance than 16QAM modulation, which may be because the number of carriers is less, so that the number of sub-carriers that are in step is less and the system peak power superposition is smaller.

The relationship between the PAPR performance of SLM-UFMC and the number U of different candidate subbands is shown in Figure 4, and the values of the number U of candidate subbands are 4, 8, 16, and 64, respectively. As can be seen from the figure, with the increase of the number of candidate subbands, the number of candidate signal replicas that can be selected increases, the range of the selected signal for transmission increases, and the performance of the system gets better and better as the U value increases. At Prob(PAPR>PAPR ₀ )=10 ^-4 , the PAPR of SLM-UFMC can be improved by nearly 1 dB at U=64 compared to U=4. Of course, the performance improvement is at the cost of sacrificing some of the complexity. The larger the number U of candidate subbands, the more IFFTs are required, and the higher the system complexity is. But with the development of hardware technology, complexity may not be the bottleneck restricting the application of a new technology. Therefore, in some cases where the hardware is not limited, the system proposed in this paper can be regarded as an effective method to solve the high PAPR problem of UFMC. At the same time, it also lays the foundation for the large-scale application of UFMC in IoT and M2M communication.

Aiming at the high PAPR problem of UFMC, a general filtering multi-carrier system SLM-UFMC based on selective mapping is proposed. Through the clever combination of SLM and UFMC, the PAPR performance of UFMC is effectively improved. The simulation results show that SLM-UFMC can reduce the PAPR of UFMC by as much as 1.8dB when Prob(PAPR>PAPR0)=10 ^-4 , increase the number of candidate subbands U, and the PAPR performance of SLM-UFMC can be further improved. This also makes the SLM-UFMC more in line with the requirements of 5G green communication, and the present invention can be easily combined with the non-orthogonal multiple access technology to further improve the system capacity. At the same time, it also lays the foundation for the large-scale application of UFMC in the future 5G and the Internet of Things and machine-to-machine communication.

Claims (2)

1. a general filtering multi-carrier method based on selection mapping, is characterized in that comprising the following steps: (1) At the transmitting end, the sub-bands are first divided according to the number of carriers, and the total number of sub-carriers N is divided into B sub-bands; (2) expanding each subband into U different candidate subbands, the transmitting end generates BU different candidate subbands in total, and the candidate subbands all contain the data information originally transmitted by the transmitting end; (3) For BU candidate subbands, each candidate subband is multiplied by a set of randomly generated twiddle factors B ^(u) , B ^(u) = [b _u,0 ,b _u,1 ,...,b _{u ,N/B-1} ] ^T , where u=1,2,...,U,b _u,N/B-1 ∈{±1,±j}, the rotated signal is represented as S _i,j =[b _i,0 S _0, b _i,1 S ₁ ,...,b _i,N/B-1 S _N/B-1 ], where i=1,2,...,B,j=1,2 ,…,U; (4) The signal in the frequency domain is transformed into the time domain by inverse fast Fourier transform, which is expressed as: where S _i,j (k) is the candidate signal in the frequency domain, and O _i is the subcarrier index set in the ith subband; (5) Use an FIR filter to filter the sub-carriers of each sub-band. The time-domain impulse response of the filter of the i-th sub-band is fi, i=1,2,...,B, and the filtered signal x is obtained _i,j (l), in order to simplify the analysis, the same filtering process is applied to the U candidate subbands, which is expressed as: x _i,j (l)=s _i,j (l)*f _i (l)l=0,1,...,N+L-2 (2) Among them, * represents the linear convolution operation, and _si,j (l) represents the time domain signal; (6) The transmitting end selects a subband with the smallest peak-to-average power ratio from every U candidate subbands for transmission, and transmits a total of B subband signals x _i . The selected subband index and twiddle factor are in the form of sideband information Sent to the receiver to reproduce the received signal information: x _i (l)=min{x _i,j (l)}l=0,1,...,N+L-2 (3) (7) The transmission signals in the B subbands selected from the BU subbands are superimposed in the time domain to form a new transmission signal, which is expressed as: (8) At the receiving end, fast Fourier transform is performed on the received signal at 2N points, and the signal in the time domain is converted into the signal Y in the frequency domain, which is expressed as: Y=WPHFVS+WPn∈C ^2N×1 (5) where W is a 2N-point FFT transform matrix, P is an extended identity matrix, H is a Toeplitz matrix related to the channel impulse response, F is a matrix composed of Toeplitz matrices, and V is an inverse Fourier transform matrix The formed diagonal matrix, S is the signal matrix formed by the frequency domain signal to be sent after selection; (9) The even-digit signal in the received signal Y is the signal that needs to be demodulated, the odd-digit signal is the interference signal, the odd-digit signal is discarded, and only the even-digit signal is demodulated, and the demodulated signal after the interference signal is removed Y _i is expressed as: Y _i =P _i ^T WPHFVS+P _i ^T WPn∈C ^N×1 (6) Let Φ=P _i ^T WPHFV, Φ is a diagonal matrix, and P _i is a 2N×N matrix. Therefore, the signal Y _i (k), i=1,...,B of the kth subcarrier depends only on the transmission the signal S _i,j (k) and the diagonal matrix Φ; (10) The transmitted signal is directly recovered from the received signal by the method of linear equalization, and the zero-forcing equalization (ZF) and the minimum mean square error equalization (MMSE) are used to restore the signal; Among them, Φ(k) is the equalization coefficient of the kth subcarrier, σ is the ratio of signal and noise power, and * represents the conjugate transpose operator; (11) Assuming that the receiving end has a transmitted copy of the twiddle factor, the equalized signal performs the inverse operation of the twiddle factor to reconstruct the original transmitted signal. 2. a kind of general filtering multi-carrier method based on selection mapping according to claim 1, is characterized in that: The twiddle factor in the step (3) can be a cyclic shift sequence, a Hadamard sequence, a Riemann sequence or a Helmert sequence.