CN113556305B - FBMC iterative channel equalization method and system suitable for high-frequency selective fading - Google Patents
FBMC iterative channel equalization method and system suitable for high-frequency selective fading Download PDFInfo
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Abstract
The invention belongs to the technical field of multi-carrier communication, and discloses an FBMC iterative channel equalization method and system suitable for high-frequency selective fading, wherein the FBMC iterative channel equalization method suitable for high-frequency selective fading comprises the following steps: generating a transmission signal and a reception signal, respectively; calculating the corresponding symbol a p,q The analysis filter bank output signal of (a); initializing an iterative equalization algorithm, wherein q =2; carrying out first equalization; reconstructing the symbol for the first time; carrying out second equalization; reconstructing the symbol for the second time; let q = q +1, repeat the first equalization, the first reconstructed symbol, the second equalization and the second reconstructed symbol if q < N-1; otherwise, all equalization information is obtained, and the channel equalization is finished. The analysis filter output signal model used by the invention is an accurate model, does not use strict slow fading or flat fading approximation in the traditional method, is suitable for any fading FBMC/OQAM communication system, eliminates residual interference under a high-frequency selective channel, and improves the system performance.
Description
Technical Field
The invention belongs to the technical field of multi-carrier communication, and particularly relates to an FBMC iterative channel equalization method and system suitable for high-frequency selective fading.
Background
At present, compared with an Orthogonal Frequency Division Multiplexing (OFDM) technique, a Filter Bank Multi-Carrier (FBMC) technique adopts a prototype Filter with good time-Frequency localization characteristics, so that the Filter Bank FBMC technique can well resist interference without a cyclic prefix, and has the advantages of high spectral efficiency, low out-of-band leakage and the like, and therefore receives wide attention. The Offset Quadrature Amplitude Modulation (OQAM) technique adopted by the FBMC system can only satisfy the orthogonality of the real number domain between the subcarriers, and there is inherent imaginary part interference in the complex number domain, so how to reduce the equalization error caused by the inherent interference becomes a hot point of research in recent years.
At present, the research method for channel equalization of FBMC/OQAM system mainly still uses Zero Forcing (ZF) equalization and Minimum Mean Square Error (MMSE) equalization methods commonly used in OFDM systems, wherein Baltar LG and Waldhauser D S, etc. design a fractional-interval Decision Feedback Equalizer (DFE) in "MMSE sub-channel decision feedback equalization for filter bank based multicarrier systems", which can reduce mean square error (MMSE) and has better equalization performance, but this scheme can only be used in flat fading, and once the frequency selectivity is improved, the equalization performance of this scheme will be greatly reduced. In recent years, FBMC/OQAM channel estimation and equalization techniques combined with Deep learning have become a research hotspot, wherein x.cheng and d.liu et al in "Deep learning-based channel estimation and equalization scheme for FBMC/OQAM systems" and "arescan-DNN based channel estimation and equalization scheme in FBMC/OQAM systems" have performed Deep learning on channel estimation and equalization schemes, wherein channel state information and constellation demapping methods are learned through a Deep neural network model, and then a distorted frequency domain sequence is implicitly equalized to directly obtain binary bits. Although equalization techniques have been extensively studied in recent years, most of them are still studied under severe slow fading or flat fading channels, and in high frequency selective channels, the traditional equalization scheme will cause residual interference to remain and affect the system performance. Therefore, an FBMC iterative channel equalization method suitable for high frequency selective fading is needed.
Through the above analysis, the problems and defects of the prior art are as follows:
(1) The existing equalization method has the problem of poor equalization performance under high-frequency selective fading.
(2) Most of the existing equalization technologies are studied under strict slow fading or flat fading channels, and the traditional equalization scheme can cause residual interference to remain and affect the system performance under high-frequency selective channels.
The difficulty in solving the above problems and defects is:
the existing equalization scheme has insufficient accuracy on interference calculation during equalization under a high-frequency selective fading channel, and the performance of the system is seriously influenced.
The significance of solving the problems and the defects is as follows:
through symbol reconstruction after equalization, pseudo pilot frequency calculation and iterative equalization, inherent interference can be greatly inhibited, and the equalization performance can be effectively improved.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides an FBMC iterative channel equalization method and system suitable for high-frequency selective fading, and aims to solve the problem that the existing equalization method has poor equalization performance under high-frequency selective fading.
The invention is realized in such a way that an FBMC iterative channel equalization method suitable for high-frequency selective fading comprises the following steps:
step one, generating a sending signal and a receiving signal respectively;
step two, calculating corresponding symbol a p,q The analysis filter bank output signal of (1);
initializing an iterative equalization algorithm, wherein q =2;
step four, carrying out first equalization;
step five, reconstructing the symbol for the first time;
step six, performing second equalization;
step seven, reconstructing the symbol for the second time;
step eight, enabling q = q +1, and if q is smaller than N-1, repeating the step four to the step seven; otherwise, all equalization information is obtained, and the channel equalization is finished.
Further, in the first step, the generating the transmission signal and the reception signal respectively includes:
(1) Constructing pilot symbols a composed of FBMC/OQAM symbols 0 All zero symbols a of FBMC/OQAM 1 FBMC/OQAM, data symbol a 2 ,a 3 ,…,a N-1 A frame structure of the composition; wherein N is more than or equal to 2 and is a positive integer, and represents the total number of FBMC/OQAM symbols in a frame; a is n ＝[a 0,n ,a 1,n ,…,a M-1,n ] T Wherein M =2 z Z is more than or equal to 2, z is a positive integer, and M represents the number of subcarriers in one FBMC/OQAM symbol;
(2) Calculating a baseband transmission signal s (l) consisting of M subcarriers and N FBMC/OQAM symbols:
wherein l =0,1, \8230, (N-1) M/2+ L g -1，
g m,n (l) Denotes a m,n G (i) adopts a PHYDYAS prototype filter with the length of L g KM +1, k representing the overlap factor, take a typical value of 4;
G 0 ＝1，G 1 ＝0.97196，
G 3 ＝0.235147；
(3) And (2) passing the baseband transmission signal s (l) through a multipath fading channel to obtain a baseband receiving signal y (l):
wherein [ h (0, n), h (1, n), \ 8230;, h (L) h -1,n)]Denotes the firstImpulse response of multipath channel during transmission of n FBMC/OQAM symbols, L h Denotes maximum, w (l) denotes mean zero and variance σ 2 Complex white gaussian noise.
Further, in step (1), the constructing of the pilot and data frame structure includes:
1) The first FBMC/OQAM symbol is a pilot symbol a 0 ＝[a 0,0 ,a 1,0 ,…,a M-1,0 ] T Wherein a is m,0 Represents a pseudo-randomly generated real number with a value of 1 or-1,m =0,1, \8230;, M-1;
2) The second FBMC/OQAM symbol is pilot symbol a 1 ＝[0,0,…,0] T For isolating pilot symbols from data symbols;
3) The remaining N-2 FBMC/OQAM symbols a 2 ,a 3 ,…,a N-1 For transmitting data, wherein a m,n Is a real-valued OQAM symbol, M =0,1, \ 8230;, M-1, N =4,1, \ 8230;, N-1.
Further, in step two, the calculation of the corresponding symbol a p,q Comprises:
output signal y of symbol obtained after baseband receiving signal passes through analysis filter bank p,q Comprises the following steps:
wherein, time frequency points (m, n) and (p, q) respectively represent OQAM symbols positioned on the nth (q) time symbol and the mth (p) subcarrier; Δ m = m-p, Δ n = n-q representing the difference in indices; h (Δm,Δn) (p + Δ m, q + Δ n) belongs to
A channel frequency domain response vector H corresponding to M sub-carriers on the nth FBMC/OQAM symbol n ＝[H(0,n),H(1,n),...,H(M-1,n)] T And interference factor moment E (Δm,Δn) Multiplication of the arrays:
further, in step three, the iterative equalization algorithm is initialized, and q =2, including:
symbol index q =2 for initial equalization, symbol after first equalization
Symbol after second equalization
Further, in step four, the first equalizing includes:
considering the first-order left-adjacent domain of a symbol
Interference analysis filterbank output signal y using channel response matrix and q-th symbol q Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q First time estimate of
(1) The inherent interference of the FBMC/OQAM system mainly comes from first-order interference, and according to the sequence of equalization on time symbols, the first equalization only considers the inherent interference brought by a first-order left neighborhood, and is expressed as:
(2) Let y q ＝[y 0,q ,y 1,q ,...,y M-1,q ] T The output signal y of the analysis filterbank for the qth symbol vector q Expressed as:
(3) Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q First time estimate of
Wherein the expression of the zero-forcing equalization is:
wherein, the first and the second end of the pipe are connected with each other,
the operation of taking the real part of the pair.
Further, in step five, the reconstructing the symbol for the first time includes:
demodulated data symbol estimates
Recovering the bit data stream of the transmitting end; carrying out OQAM modulation on the recovered bit data stream to obtain a corresponding symbol vector a q First OQAM reconstructed symbol vector
Further, in the sixth step, the second equalizing includes:
considering a first order neighborhood of symbols
Interference analysis filterbank output signal y using channel response matrix and q-1 symbol q- 1, obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q-1 Second order estimate of
(1) According to the data symbol after the first equalization reconstruction, the inherent interference brought by the first-order neighborhood is considered:
(2) Analysis filterbank output signal y for the q-1 th symbol q-1 Expressed as:
(3) Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q-1 Second order estimate of
Wherein the expression of the zero-forcing equalization is:
further, in step seven, the reconstructing the symbol for the second time includes:
demodulated data symbol estimates
Recovering the bit data stream of the sending end; carrying out OQAM modulation on the recovered bit data stream to obtain a corresponding symbol vector a q-1 Second OQAM reconstruction of the symbol vector
Another object of the present invention is to provide an FBMC iterative channel equalization system suitable for high frequency selective fading, which applies the FBMC iterative channel equalization method suitable for high frequency selective fading, and the FBMC iterative channel equalization system suitable for high frequency selective fading comprises:
a signal generating module for generating a transmitting signal s (l) and a receiving signal y (l) respectively;
an output signal calculation module for calculating the corresponding symbol a p,q Analysis filter bank output signal y p,q ；
The initialization module is used for initializing an iterative equalization algorithm, and q =2;
a first-order equalization module for considering a first-order left-adjacent domain of symbols
Interference analysis filterbank output signal y using channel response matrix and qth symbol q Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q First time estimate of
A first symbol reconstruction module for demodulating the data symbol estimation value
Recovering the bit data stream of the transmitting end; carrying out OQAM modulation on the recovered bit data stream to obtain a corresponding symbol vector a q First OQAM reconstruction of symbol vectors
A second equalization module for considering a first order neighborhood of symbols
Interference analysis filterbank output signal y using channel response matrix and q-1 symbol q-1 Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q-1 Second order estimate of
A second symbol reconstruction module for demodulating the data symbol estimate
Recovering the bit data stream of the transmitting end; carrying out OQAM modulation on the recovered bit data stream to obtain a corresponding symbol vector a q-1 Second OQAM reconstructing the symbol vector
The judging module is used for enabling q = q +1, and if q is smaller than N-1, the first equalizing module, the first symbol reconstructing module, the second equalizing module and the second symbol reconstructing module are repeatedly carried out; otherwise, all equalization information is obtained, and the channel equalization is finished.
Another object of the present invention is to provide an information data processing terminal for implementing the FBMC iterative channel equalization method suitable for high-frequency selective fading.
By combining all the technical schemes, the invention has the advantages and positive effects that: the FBMC iterative channel equalization method suitable for high-frequency selective fading provided by the invention utilizes the symbols reconstructed twice as known data information to calculate first-order neighborhood interference, can eliminate residual interference under a high-frequency selective channel, obviously improves the equalization performance of a system, and can be used for a channel equalizer in an FBMC communication system.
The analysis filter output signal model used by the invention is an accurate model, does not use strict slow fading or flat fading approximation in the traditional method, and can be suitable for any fading FBMC/OQAM communication system.
The method takes the neighborhood interference into account during equalization, eliminates the inherent interference among data which cannot be considered by channel estimation, and further improves the equalization performance of the system through iteration.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of an FBMC iterative channel equalization method suitable for high frequency selective fading according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of an FBMC iterative channel equalization method suitable for high frequency selective fading according to an embodiment of the present invention.
Fig. 3 is a block diagram of an FBMC iterative channel equalization system suitable for high frequency selective fading according to an embodiment of the present invention;
in the figure: 1. a signal generation module; 2. an output signal calculation module; 3. initializing a module; 4. a first equalization module; 5. a first symbol reconstruction module; 6. a second equalization module; 7. a second symbol reconstruction module; 8. and a judging module.
Fig. 4 is a frame structure diagram according to an embodiment of the present invention.
Fig. 5 is a comparison graph of system error performance of the method of the present invention and the conventional method according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
In view of the problems in the prior art, the present invention provides an FBMC iterative channel equalization method and system suitable for high frequency selective fading, and the following describes the present invention in detail with reference to the accompanying drawings.
As shown in fig. 1, an FBMC iterative channel equalization method suitable for high frequency selective fading provided by the embodiment of the present invention includes the following steps:
s101, respectively generating a sending signal and a receiving signal;
s102, calculating corresponding symbol a p,q The analysis filter bank output signal of (1);
s103, initializing an iterative equalization algorithm, wherein q =2;
s104, carrying out first equalization;
s105, reconstructing the symbol for the first time;
s106, performing second equalization;
s107, reconstructing the symbol for the second time;
s108, making q = q +1, if q is less than N-1, repeating S104-S107; otherwise, all equalization information is obtained, and the channel equalization is finished.
A schematic diagram of an FBMC iterative channel equalization method suitable for high frequency selective fading according to an embodiment of the present invention is shown in fig. 2.
As shown in fig. 3, an FBMC iterative channel equalization system suitable for high frequency selective fading according to an embodiment of the present invention includes:
a signal generating module 1, configured to generate a transmission signal s (l) and a reception signal y (l), respectively;
an output signal calculation module 2 for calculating the corresponding symbol a p,q Analysis filter bank output signal y p,q ；
The initialization module 3 is used for initializing an iterative equalization algorithm, and q =2;
a first equalization block 4 for considering a first order left neighborhood of the symbols
Interference analysis filterbank output signal y using channel response matrix and q-th symbol q Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q First time estimate of
A first symbol reconstruction module 5 for demodulating the data symbol estimation value
Recovering the bit data stream of the sending end; carrying out OQAM modulation on the recovered bit data stream to obtain a corresponding symbol vector a q First OQAM reconstructed symbol vector
A second equalization module 6 for considering the first order neighbourhood of the symbol
Interference analysis filterbank output signal y using channel response matrix and q-1 symbol q-1 Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q-1 Second order estimate of
A second symbol reconstruction module 7 for demodulating the data symbol estimation value
Recovering the bit data stream of the transmitting end; carrying out OQAM modulation on the recovered bit data stream to obtain a corresponding symbol vector a q-1 Second OQAM reconstructing the symbol vector
A judging module 8, configured to make q = q +1, and if q is less than N-1, repeat the first equalizing module, the first symbol reconstructing module, the second equalizing module, and the second symbol reconstructing module; otherwise, all equalization information is obtained, and the channel equalization is finished.
The technical solution of the present invention will be further described with reference to the following examples.
The invention discloses an FBMC iterative channel equalization method suitable for high-frequency selective fading, which mainly solves the problem that the existing equalization method is poor in equalization performance under high-frequency selective fading. The technical scheme comprises the following steps: generating a transmission signal; generating a received signal; calculating an analysis filter bank output signal of the corresponding symbol; balancing for the first time; reconstructing the symbol for the first time; reconstructing the symbol for the second time; second equalization; and judging whether the equalization of the last symbol is reached, if not, starting the equalization of the next symbol, otherwise, obtaining the equalization signals of all the symbols, and ending the iterative equalization. The invention uses the symbols reconstructed twice as the known data information to calculate the first-order neighborhood interference, obviously improves the equalization performance and can be used for a channel equalizer in an FBMC communication system.
The implementation of the invention is further described with reference to fig. 2.
1a) Constructing pilot symbols a composed of FBMC/OQAM symbols 0 All zero symbols a of FBMC/OQAM 1 FBMC/OQAM data symbols a 2 ,a 3 ,…,a N-1 The frame structure is formed, wherein N is more than or equal to 2 and is a positive integer, and the N represents the total number of FBMC/OQAM symbols in a frame. a is a n ＝[a 0,n ,a 1,n ,…,a M-1,n ] T Wherein M =2 z Z is more than or equal to 2, z is a positive integer, and M represents the number of subcarriers in one FBMC/OQAM symbol.
Referring to fig. 4, the specific structure of the pilot and data frame structure is:
first, the first FBMC/OQAM symbol is a pilot symbol a 0 ＝[a 0,0 ,a 1,0 ,…,a M-1,0 ] T Wherein a is m,0 Representing a pseudo-randomly generated real number with a value of 1 or-1,m = -0, 1, \8230, M-1;
secondly, the second FBMC/OQAM symbol is pilot symbol a 1 ＝[0,0,…,0] T The method is used for isolating the pilot frequency symbol and the data symbol, so that the inherent interference of the data to the pilot frequency symbol can be reduced, and the estimation performance is improved;
finally, N-2 FBMC/OQAM symbols a remain 2 ,a 3 ,…,a N-1 For transmitting data, wherein a m,n Is a real-valued OQAM symbol, M =0,1, \ 8230;, M-1, N =4,1, \ 8230;, N-1.
Calculating a baseband transmission signal s (l) consisting of M subcarriers and N FBMC/OQAM symbols:
wherein l =0,1, \8230; (N-1) M/2+ L g -1，
g m,n (l) Denotes a m,n G (i) filtering with a PHYDYAS prototypeDevice with length L g K = KM +1, representing an overlap factor, inappropriately general, K being a typical value of 4;
G0＝1，G1＝0.97196，
G3＝0.235147。
And (2) passing the baseband transmission signal s (l) generated in the step (1) through a multipath fading channel to obtain a baseband receiving signal:
wherein [ h (0, n), h (1, n), \ 8230;, h (L) h -1,n)]Represents the impulse response of the multipath channel during the transmission of the nth FBMC/OQAM symbol, L h Denotes maximum, w (l) denotes mean zero and variance σ 2 Complex white gaussian noise.
Output signal y of symbol obtained after baseband receiving signal passes through analysis filter bank p,q Comprises the following steps:
wherein, time-frequency points (m, n) and (p, q) respectively represent OQAM symbols positioned on the nth (q) time symbol and the mth (p) subcarrier, Δ m = m-p, Δ n = n-q represent difference of indexes, H (Δm,Δn) (p + Δ m, q + Δ n) belongs to
The channel frequency domain response vector corresponding to M sub-carriers on the nth FBMC/OQAM symbolH n ＝[H(0,n),H(1,n),...,H(M-1,n)] T And interference factor moment E (Δm,Δn) Multiplication of the arrays:
step 4, initializing iterative equalization algorithm
Symbol index q =2 for initial equalization, symbol after first equalization
Symbol after second equalization
(5a) The inherent interference of the FBMC/OQAM system mainly comes from first-order interference, and according to the sequence of equalization on the time symbol, the first equalization can only consider the inherent interference brought by the first-order left neighborhood, which can be expressed as:
(5b) Let y q ＝[y 0,q ,y 1,q ,...,y M-1,q ] T Then the output signal of the analysis filter for the qth symbol vector is:
(5c) Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q First time estimate of
Wherein the content of the first and second substances,
the operation of taking the real part is carried out.
Demodulated data symbol estimates
Recovering the bit data stream of the sending end; then, OQAM modulation is carried out on the recovered bit data stream to obtain a corresponding symbol vector a q First OQAM reconstruction of symbol vectors
(7a) According to the data symbol after the first equalization reconstruction, the inherent interference caused by the first-order neighborhood is considered, which can be expressed as:
(7b) The analysis filter output signal for the q-1 th symbol vector is then:
(7c) Obtaining symbols by adopting a zero forcing equalization algorithmVector a q-1 Second order estimate of (2)
Demodulated data symbol estimates
Recovering the bit data stream of the sending end; then, OQAM modulation is carried out on the recovered bit data stream to obtain a corresponding symbol vector a q- Second OQAM reconstructed symbol vector of 1
Step 9. Let q = q +1, if q < N-1, repeat steps (5) - (8); otherwise, equalization information is obtained, and channel equalization is finished.
The technical effects of the present invention will be described in detail with reference to simulation experiments.
1. Simulation conditions
The effect of the present invention is illustrated by simulation in two frequency selective fading scenarios, and two frequency selective fading scenario simulation parameters are shown in table 1.
TABLE 1 simulation parameters
2. Simulation content and results
The performance of the channel estimation normalized mean square error NMSE of the method and the traditional AFB output signal model, which changes along with the signal-to-noise ratio SNR, is simulated and compared, and the simulation result is shown in figure 5.
As can be seen from fig. 5: 1) Under two frequency selective fading scenes, the NMSE of the channel estimation provided by the invention has better performance than that of the traditional method; 2) The method provided by the invention has the advantages that the performance is obviously improved in a high-frequency selectivity scene, and particularly, the gain of 6-9 dB can be obtained under a high signal-to-noise ratio.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the embodiments of the present invention, and the scope of the present invention should not be limited thereto, and any modifications, equivalents and improvements made by those skilled in the art within the technical scope of the present invention as disclosed in the present invention should be covered by the scope of the present invention.
Claims (4)
1. An FBMC iterative channel equalization method suitable for high-frequency selective fading, which is characterized by comprising the following steps:
step one, generating a sending signal and a receiving signal respectively;
step two, calculating corresponding symbol a p,q The analysis filter bank output signal of (a);
initializing an iterative equalization algorithm, wherein q =2;
step four, carrying out first equalization;
step five, reconstructing the symbol for the first time;
step six, carrying out second equalization;
step seven, reconstructing the symbol for the second time;
step eight, enabling q = q +1, and if q is smaller than N-1, repeating the step four to the step seven; otherwise, all equalization information is obtained, and the channel equalization is finished;
in the first step, the generating the transmission signal and the reception signal respectively includes:
(1) Constructing pilot symbols a composed of FBMC/OQAM symbols 0 All zero symbols a of FBMC/OQAM 1 FBMC/OQAM, data symbol a 2 ,a 3 ,θ,a N-1 A frame structure of components; wherein N is more than or equal to 2 and is a positive integer, and represents the total number of FBMC/OQAM symbols in a frame; a is a n ＝[a 0,n ,a 1,n ,...,a M-1,n ] T Wherein M =2 z Z is more than or equal to 2, z is a positive integer, and M represents the number of subcarriers in one FBMC/OQAM symbol;
(2) Calculating a baseband transmission signal s (l) consisting of M subcarriers and N FBMC/OQAM symbols:
wherein l =0,1, \8230, (N-1) M/2+ L g -1，
g m,n (l) Denotes a m,n G (i) adopts a PHYDYAS prototype filter with the length of L g K = KM +1, representing an overlap factor, with a typical value of 4;
G 0 ＝1，G 1 ＝0.97196，
G 3 ＝0.235147；
(3) Passing the baseband transmission signal s (l) through a multipath fading channel to obtain a baseband receiving signal y (l):
wherein, h (0, n), h (1, n), \8230;, h (L) h -1,n)]Represents the impulse response of the multipath channel during the transmission of the nth FBMC/OQAM symbol, L h Denotes maximum, w (l) denotes mean zero and variance σ 2 Complex white gaussian noise of (a);
in step (1), the constructing of the pilot frequency and data frame structure includes:
1) The first FBMC/OQAM symbol is a pilot symbol a 0 ＝[a 0,0 ,a 1,0 ,…,a M-1,0 ] T Wherein a is m,0 Representing a pseudo-randomly generated real number with a value of 1 or-1,m = -0, 1, \8230, M-1;
2) The second FBMC/OQAM symbol is pilot symbol a 1 ＝[0,0,...,0] T For isolating pilot symbols and data symbols;
3) The remaining N-2 FBMC/OQAM symbols a 2 ,a 3 ,…,a N-1 For transmitting data, wherein a m,n Is a real-valued OQAM symbol, M =0,1, \8230, M-1, N =4,1, \8230, N-1;
in step two, the corresponding symbol a is calculated p,q Comprises:
output signal y of symbol obtained after baseband receiving signal passes through analysis filter bank p,q Comprises the following steps:
wherein, time frequency points (m, n) and (p, q) respectively represent OQAM symbols positioned on the nth (q) time symbol and the mth (p) subcarrier; Δ m = m-p, Δ n = n-q representing the difference in indices; h (Δm,Δn) (p + Δ m, q + Δ n) belongs to
A channel frequency domain response vector H corresponding to M sub-carriers on the nth FBMC/OQAM symbol n ＝[H(0,n),H(1,n),...,H(M-1,n)] T And interference factor moment E (Δm,Δn) Product of the arrays:
in step four, the first equalizing includes:
considering the first order left neighbourhood of the symbol
Interference analysis filterbank output signal y using channel response matrix and q-th symbol q Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q First time estimate of
(1) The inherent interference of the FBMC/OQAM system mainly comes from first-order interference, and according to the sequence of equalization on time symbols, the first equalization only considers the inherent interference brought by a first-order left neighborhood, and is expressed as:
(2) Let y q ＝[y 0,q ,y 1,q ,...,y M-1,q ] T The output signal y of the analysis filterbank for the qth symbol vector q Expressed as:
(3) Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q First time estimate of
Wherein the expression of the zero-forcing equalization is as follows:
wherein the content of the first and second substances,
the operation of taking the real part is carried out;
in the fifth step, the first symbol reconstruction includes:
demodulated data symbol estimates
Recovering the bit data stream of the sending end; carrying out OQAM modulation on the recovered bit data stream to obtain a corresponding symbol vector a q First OQAM reconstructed symbol vector
In step six, the second equalization includes:
considering a first order neighborhood of symbols
Interference analysis filterbank output signal y using channel response matrix and q-1 symbol q-1 Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q-1 Second order estimate of
(1) According to the data symbol after the first equalization reconstruction, the inherent interference brought by the first-order neighborhood is considered:
(2) Analysis filterbank output signal y for the q-1 th symbol q-1 Expressed as:
(3) Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q-1 Second order estimate of (2)
Wherein the expression of the zero-forcing equalization is:
in step seven, the second reconstructing the symbol includes:
demodulated data symbol estimates
Recovering the bit data stream of the sending end; oqam modulation of recovered bit streamTo obtain the corresponding symbol vector a q-1 Second OQAM reconstruction of the symbol vector
2. The FBMC iterative channel equalization method for high frequency selective fading as claimed in claim 1, wherein in step three, said iterative equalization algorithm is initialized, and q =2, comprising:
symbol index q =2 for initial equalization, symbol after first equalization
Symbols after second equalization
3. An FBMC iterative channel equalization system for high frequency selective fading, which implements the FBMC iterative channel equalization method for high frequency selective fading according to any one of claims 1 to 2, wherein the FBMC iterative channel equalization system for high frequency selective fading comprises:
a signal generating module for generating a transmitting signal s (l) and a receiving signal y (l) respectively;
an output signal calculation module for calculating a corresponding symbol a p,q Analysis filter bank output signal y p,q ；
The initialization module is used for initializing an iterative equalization algorithm, and q =2;
a first-order equalization module for considering a first-order left-adjacent domain of symbols
Interference analysis filterbank output signal y using channel response matrix and q-th symbol q Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q First time estimate of
A first time symbol reconstruction module for demodulating the data symbol estimation value
Recovering the bit data stream of the transmitting end; carrying out OQAM modulation on the recovered bit data stream to obtain a corresponding symbol vector a q First OQAM reconstructed symbol vector
A second equalization module for considering a first order neighborhood of symbols
Interference analysis filterbank output signal y using channel response matrix and q-1 symbol q-1 Obtaining a symbol vector a by adopting a zero-forcing equalization algorithm q-1 Second order estimate of
A second symbol reconstruction module for demodulating the data symbol estimate
Recovering the bit data stream of the sending end; carrying out OQAM modulation on the recovered bit data stream to obtain a corresponding symbol vector a q-1 Second OQAM reconstructing the symbol vector
The judging module is used for enabling q = q +1, and if q is smaller than N-1, the first equalizing module, the first symbol reconstructing module, the second equalizing module and the second symbol reconstructing module are repeatedly carried out; otherwise, all equalization information is obtained, and the channel equalization is finished.
4. An information data processing terminal, characterized in that the information data processing terminal is configured to implement the FBMC iterative channel equalization method suitable for high-frequency selective fading according to any one of claims 1 to 2.
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