CN103812807A - Method for enhancing antijamming capability of multi-carrier communication system of cosine modulated filter bank - Google Patents
Method for enhancing antijamming capability of multi-carrier communication system of cosine modulated filter bank Download PDFInfo
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Abstract
The invention discloses a convex optimization technology-based method for enhancing the antijamming capability of a multi-carrier communication system of a cosine modulated filter bank, and belongs to the technical field of wireless communication. The method includes the following steps of: performing base band modulation and R bit string on an original signal at the transmitting end, and transforming to obtain a parallel signal; inserting a zero value into the parallel signal randomly; performing the modulation of the comprehensive cosine modulated filter bank on the signal into which the zero value is inserted, and transmitting the signal through a Gaussian channel; processing the received signal passing through the Gaussian channel by the receiving end, namely performing fast Fourier transform, performing frequency domain equilibrium on the signal, and performing fast Fourier transform on the signal to obtain a time domain signal; making the time domain signal pass through a convex optimization technology-based interference estimation module to obtain a jamming signal contained in the time domain signal, and performing subtraction operation on the time domain signal and the jamming signal to obtain a new signal; and performing operation of demodulation, base band demodulation and the like of a cosine modulated analysis filter bank on the new signal to obtain the originally-transmitted signal. By the convex optimization technology-based method, the reliability of signal transmission can be improved effectively.
Description
Technical field
The invention belongs to wireless communication technology field, particularly a kind of method of the enhancing cosine-modulation filter bank multi-carrier anti-interference of communication system ability based on protruding optimisation technique.
Background technology
Cosine-modulation filter bank multi-carrier technology is a kind of subcarrier multiplexing technology, belongs to the one in filter bank multi-carrier (FBMC) technology.Multi-carrier modulation technology is widely used in various communication standards because of the multipath effect that it can effectively resist in wireless channel.Its thought is to adopt several subcarriers, and the corresponding specific subchannel of each subcarrier, each sub data flow of parallel transmission.Existing multi-carrier modulation mainly contains multitone realization, orthogonal multiple carrier modulation (OFDM) and the multi-carrier modulation based on wavelet transformation.Traditional FBMC system is modulated based on discrete Fourier transform (DFT) bank of filters.But DFT bank of filters can not thoroughly be eliminated interband aliasing and disturb, be not so good as cosine transform for the Information Compression of signal effective.Thereby cosine-modulation bank of filters arises at the historic moment, it produces from DFT bank of filters, and the fast algorithm of the discrete cosine transform based on type 4, can reach the reconstruction completely of signal.Cosine-modulation bank of filters communication system has a lot of advantages compared to OFDM: higher transmission rate, and good anti-intersymbol interference ability, anti-ISI ability, need not increase Cyclic Prefix, and the availability of frequency spectrum is more high.But it also has shortcoming own, due to its multicarrier characteristic, time domain is disturbed and can greatly be reduced FBMC systematic function.
The information technology of high speed development is being challenged the signal handling capacity of physical system, and traditional signal processing model can not adapt to the data of magnanimity like this, and therefore compressive sensing theory framework is suggested.Compressive sensing theory is the succinct information of perception in the signal of redundancy, thereby effectively reduce the data volume of system processing.The main research of compressed sensing has the sparse expression of signal, design and the signal of observing matrix to recover.Accurate signal recovery algorithms is the key in compressed sensing.Compressed sensing is pointed out as long as signal is compressible or can be by rarefaction representation under certain transform domain, so just can with the incoherent observing matrix of transform-based, high conversion gained dimensional signal be projected on a lower dimensional space with one, and can from these a small amount of measurement data, reconstruct original signal with high probability.Compressive sensing theory mainly comprises following several respects content: the sparse expression of (1) signal.In general signal x itself is not sparse, and it just need to find certain orthogonal basis or tight frame Ψ.Make signal x is sparse at Ψ after conversion.(2) design of observing matrix Ф.Compressive sensing theory, by observing matrix perception information, so how to design and the more incoherent observing matrix of orthogonal basis, is the prerequisite of guarantee information integrality.(3) signal recovers.Signal recovers to have solved from owing to determine restoring signal problem Systems with Linear Observation, and the recovery algorithms how designing is rapidly and efficiently the basis that compressive sensing theory is able to extensive use.Recovery algorithms is rapidly and efficiently the basis that compressive sensing theory is able to extensive use.Its core concept is that data sampling and compression merging are carried out.There are two aspect basic demands: the sparse property of signal, the non-correlation of observing matrix and transformation matrix.Existing relevant proof random matrix and 4 type cosine transform matrixes have good non-correlation.The advantage of compressed sensing technology is can be lower than the sampling rate that is Qwest's sample rate, signal is sampled, thereby has reduced the energy consumption in signals collecting and transmitting procedure.Protruding method of relaxation is that compressed sensing recovery problem is transformed into minimum l
1the protruding optimization problem of norm.Protruding optimization is the special nonlinear optimization technology of a class that solves the maximum (minimum) of protruding target function under convex function constraint.Protruding optimization method has advantages of that local minizing point is global minimizer, and when particularly target function is strictly convex function, global minimum only has one so.L
1it is again a separable function that norm can comprise sparse characteristic, and protruding method of relaxation utilizes this feature as target function, can effectively solve the signal recovery problems in compressed sensing.Common protruding optimization method: interior point method, gradient projection method, iteration weighting method and collapse threshold method etc.Sparse gradient projection method is take gradient descent method as basic sparse signal restoration methods, its introduce hidden variable by the target function of non-differentiability be transformed into can be micro-without the protruding target function of constraint.Sparse gradient project algorithms are not affected by initial value, effectively process the problem of extensive signal, but also dredge signal recovery method the running time that can utilize the continuous scheme of a kind of regular factor to reduce algorithm, its introduce hidden variable by the target function of non-differentiability be transformed into can be micro-without the protruding target function of constraint.
Summary of the invention
In view of this, the object of the present invention is to provide a kind of method of the enhancing cosine-modulation filter bank multi-carrier anti-interference of communication system ability based on protruding optimisation technique, the method can effectively improve the reliability of signal transmission.
For achieving the above object, the invention provides following technical scheme:
A method that strengthens cosine-modulation filter bank multi-carrier anti-interference of communication system ability, comprises the following steps: step 1: first primary signal x is carried out to baseband modulation and R position serial to parallel conversion obtains parallel signal at transmitting terminal; Step 2: radom insertion null value in parallel signal, null value number is fixed; Step 3: the signal that inserts null value is carried out to the modulation of cosine-modulation synthesis filter banks, then launched by Gaussian channel; Step 4: receiving terminal is processed the reception signal y after Gaussian channel, first carries out fast Fourier transform, then signal is carried out to frequency domain equalization, then signal is carried out to inverse fast Fourier transform obtains time-domain signal r; Step 5: again by time-domain signal r by based on after protruding optimisation technique interference estimation block, the interference signal s that obtains comprising in r, then again by signal r with subtract computing with interference signal s, obtain new signal; Step 6: newer signal is carried out the operations such as cosine-modulation filter analysis bank of filters solution mediation base band demodulating, obtain original transmitted signal x.
Further, adopt BPSK, QPSK, 16QAM or 64QAM modulation system in the baseband modulation of transmitting terminal.
Further, interference signal must meet sparse characteristic, and the nonzero coefficient K of signal is far smaller than the dimension N of signal.
Further, the value of the nonzero coefficient K of signal is less than 5, makes interference signal meet sparse requirement as much as possible.
Further, a radom insertion L null value in the parallel signal of transmitting terminal, deducts R but null value number is N, i.e. L=N-R, and wherein N is the length of inserting parallel signal after null value, is also the dimension of interference signal, and the N index that is 2, is 128,256 or 512.
Further, the nonzero coefficient K of interference signal must be less than the number L of transmitting terminal parallel signal radom insertion null value, and L is also far smaller than the dimension N of signal, has K<L<<N.
Further, being cosine-modulation bank of filters at the synthesis filter banks of transmitting terminal and the analysis filterbank of receiving terminal, is all based on 4 type discrete cosine transforms.
Further, the described interference estimation block method therefor based on protruding optimisation technique is that compressed sensing convexity is optimized the sparse gradient projection method in Reconstruction Method.It is respectively to have observing matrix Ф that the method is recovered the needed variable of interference signal, basic matrix is Ψ, and measured value r, the random Gaussian matrix that wherein observing matrix Ф is L × N, random Gaussian matrix is to obey to expect to be 0, variance is the matrix of the independent identically distributed element composition of 1/M, and Ψ is the 4 type discrete cosine transform matrixes of N × N, and measured value is signal r.
Beneficial effect of the present invention is: the method for the invention completes the estimation to interference signal by the interference estimation block of introducing based on protruding optimisation technique at cosine filter group multi-carrier communications systems receiving terminal, realize the recovery to primary signal, for the reliable reception of multi-carrier communications systems signal provides a kind of simple and effective solution.
Accompanying drawing explanation
In order to make object of the present invention, technical scheme and beneficial effect clearer, the invention provides following accompanying drawing and describe:
Fig. 1 is the schematic flow sheet of cosine-modulation filter bank multi-carrier communication system provided by the invention;
Fig. 2 is the internal frame diagram of cosine-modulation bank of filters provided by the invention;
Fig. 3 is receiving terminal immunity module schematic flow sheet provided by the invention.
Embodiment
Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described in detail.
The method specific implementation step of anti-interference of communication system ability provided by the invention is as follows:
1) first primary signal x signal is carried out to baseband modulation and serial to parallel conversion.
2) signal after baseband modulation is carried out to serial to parallel conversion.
3) a radom insertion L null value in parallel signal, but null value number is fixed.
4) carry out 4 type cosine synthesis filter banks modulation and launch by Gaussian channel inserting the signal of null value.
5) the time-domain signal y receiving is carried out to fast Fourier transform (FFT) and become frequency-region signal, object is that this signal is carried out to frequency domain equalization, eliminates the impact of white Gaussian noise, then, carrying out inverse fast Fourier transform (IFFT), obtains signal h.
6) signal h is carried out to serial to parallel conversion, obtain parallel signal r.
7) Interference Estimation based on protruding optimization, the required observing matrix Ф of structure signal reconstruction.Reconstruction signal accurately, Ф must meet limited equidistant characteristics (RIP) criterion, and Ф is that random Gaussian matrix can meet this characteristic in the present invention.Utilize observing matrix Ф, measured value r, 4 type dct transform matrix Ψ, sparse gradient projection method by protruding optimization is reconstructed signal, estimate channel disturbance s, wherein r is the signal after inverse fast Fourier transform, and Ψ is the 4 type discrete cosine transform matrixes of N × N.
8) more former parallel signal and interference signal are subtracted to computing and obtain new signal.
9) the new signal obtaining is carried out to 4 type Cosine Analysis bank of filters demodulation, the signal demodulating is carried out to base band demodulating and parallel serial conversion, recover primary signal.
Fig. 1 is the schematic flow sheet of cosine-modulation filter bank multi-carrier communication system provided by the invention, and as shown in the figure, the present invention is mainly divided into four parts:
1, the cosine-modulation filter bank multi-carrier system structure that the present invention uses:
Cosine-modulation bank of filters is that transmitting terminal adopts synthesis filter, and receiving terminal adopts analysis filter.Synthesis filter and analysis filter all adopt cosine-modulation bank of filters (referring to Fig. 2), carry out 4 type cosine transforms.
2, the signal processing of transmitting terminal:
Digital signal is first passed through baseband modulation, that conventionally can select has modulation systems such as BPSK, QPSK, 16QAM, 64QAM, signal after baseband modulation is done to the serial to parallel conversion of R position, then a radom insertion L null value, utilizes protruding optimisation technique to estimate interference while being convenient to receive.Again signal is carried out to the modulation of cosine-modulation synthesis filter banks, finally by parallel serial conversion, obtain a base band time domain modulation signal after FBMC modulation, this signal is launched by Gaussian channel.Wherein, the subcarrier number of setting is N, the index that N is 2, and L<<N.
3, the signal processing of receiving terminal:
Transmitted signal is subject to the impact of white Gaussian noise and interference through Gaussian channel, receiving terminal first carries out express delivery Fourier transform (FFT) to signal, then signal is carried out to equilibrium, eliminates white Gaussian noise impact.Then signal is carried out to inverse fast Fourier transform (IFFT), obtain signal r, r is put into register, then enter the interference estimation block based on protruding optimisation technique, utilize sparse gradient projection method to obtain interference signal s, utilize the r in register to deduct interference signal s, the signal obtaining carries out cosine-modulation analysis filterbank, thus the primary signal of recovering.
4, the sparse gradient project algorithms estimated disturbance signal of protruding optimization
Due at transmitting terminal parallel signal radom insertion null value, make not carry information of this part subcarrier.The interference that meets sparse property adds after signal, and through fast Fourier transform (DFT) conversion, the energy of interference has just been assigned on each subcarrier, processes the not subcarrier of carry information of transmitting terminal at receiving terminal, just can realize the estimation to disturbing.Because the nonzero value number that has set in advance time domain interference is K, K is far smaller than N, make interference signal meet signal in compressive sensing theory to have the requirement of sparse property, utilize like this observing matrix Ф, measured value r, 4 type dct transform matrix Ψ, are reconstructed interference signal by sparse gradient projection method in convex optimized algorithm, just can estimate channel disturbance s.The random matrix that wherein Ф is L × N, r is the signal after inverse fast Fourier transform, Ψ is the 4 type discrete cosine transform matrixes of N × N.
Finally explanation is, above preferred embodiment is only unrestricted in order to technical scheme of the present invention to be described, although the present invention is described in detail by above preferred embodiment, but those skilled in the art are to be understood that, can make various changes to it in the form and details, and not depart from the claims in the present invention book limited range.
Claims (8)
1. a method that strengthens cosine-modulation filter bank multi-carrier anti-interference of communication system ability, is characterized in that: comprise following
Step:
Step 1: first primary signal x is carried out to baseband modulation and R position serial to parallel conversion obtains parallel signal at transmitting terminal;
Step 2: radom insertion null value in parallel signal, null value number is fixed;
Step 3: the signal that inserts null value is carried out to the modulation of cosine-modulation synthesis filter banks, then launched by Gaussian channel;
Step 4: receiving terminal is processed the reception signal y after Gaussian channel, first carries out fast Fourier transform, then signal is carried out to frequency domain equalization, then signal is carried out to inverse fast Fourier transform obtains time-domain signal r;
Step 5: again by time-domain signal r by based on after protruding optimisation technique interference estimation block, the interference signal s that obtains comprising in r, then again by signal r with subtract computing with interference signal s, obtain new signal;
Step 6: newer signal is carried out the operations such as cosine-modulation filter analysis bank of filters solution mediation base band demodulating, obtain original transmitted signal x.
2. a kind of method that strengthens cosine-modulation filter bank multi-carrier anti-interference of communication system ability according to claim 1, is characterized in that: the baseband modulation at transmitting terminal adopts BPSK, QPSK, 16QAM or 64QAM modulation system.
3. a kind of method that strengthens cosine-modulation filter bank multi-carrier anti-interference of communication system ability according to claim 1, is characterized in that: interference signal must meet sparse characteristic, and the nonzero coefficient K of signal is far smaller than the dimension N of signal.
4. a kind of method that strengthens cosine-modulation filter bank multi-carrier anti-interference of communication system ability according to claim 3, is characterized in that: the value of the nonzero coefficient K of signal is less than 5, makes interference signal meet sparse requirement as much as possible.
5. a kind of method that strengthens cosine-modulation filter bank multi-carrier anti-interference of communication system ability according to claim 3, it is characterized in that: a radom insertion L null value in the parallel signal of transmitting terminal, but null value number is N deducts R, be L=N-R, wherein N is the length of parallel signal after insertion null value, also be the dimension of interference signal, and the N index that is 2, be 128,256 or 512.
6. a kind of method that strengthens cosine-modulation filter bank multi-carrier anti-interference of communication system ability according to claim 3, it is characterized in that: the nonzero coefficient K of interference signal must be less than the number L of transmitting terminal parallel signal radom insertion null value, L is also far smaller than the dimension N of signal, has K<L<<N.
7. a kind of method that strengthens cosine-modulation filter bank multi-carrier anti-interference of communication system ability according to claim 3, it is characterized in that: being cosine-modulation bank of filters at the synthesis filter banks of transmitting terminal and the analysis filterbank of receiving terminal, is all based on 4 type discrete cosine transforms.
8. a kind of method that strengthens cosine-modulation filter bank multi-carrier anti-interference of communication system ability according to claim 3, is characterized in that: the described interference estimation block method therefor based on protruding optimisation technique is that compressed sensing convexity is optimized the sparse gradient projection method in Reconstruction Method.
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| CN108886502A (en) * | 2016-02-04 | 2018-11-23 | Abb瑞士股份有限公司 | Matrix equalizer for the CMFB transmission in the channel of dispersion |
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| WO2016026115A1 (en) * | 2014-08-21 | 2016-02-25 | 华为技术有限公司 | Method and apparatus for generating and processing frequency division multiple waveform signal |
| CN105515711A (en) * | 2015-12-25 | 2016-04-20 | 中国民航大学 | Compression sensing and reception diversity combined range finder interference suppression system |
| CN105515711B (en) * | 2015-12-25 | 2018-01-02 | 中国民航大学 | Joint compressed sensing and the rangefinder Interference Suppression System for receiving diversity |
| CN108886502A (en) * | 2016-02-04 | 2018-11-23 | Abb瑞士股份有限公司 | Matrix equalizer for the CMFB transmission in the channel of dispersion |
| CN108886502B (en) * | 2016-02-04 | 2021-12-24 | 日立能源瑞士股份公司 | Matrix equalizer for CMFB transmission in dispersive channels and method thereof |
| CN105915473A (en) * | 2016-05-26 | 2016-08-31 | 中南大学 | OFDM (Orthogonal Frequency Division Multiplexing) system parametric channel estimation and equalization method based on compressed sensing technology |
| CN105915473B (en) * | 2016-05-26 | 2019-07-12 | 中南大学 | A kind of estimation of ofdm system parametric channel and equalization methods based on compressed sensing technology |
| CN106302279A (en) * | 2016-08-04 | 2017-01-04 | 成都极比特通信技术有限公司 | FBMC system equalization method based on interference variance statistics |
| WO2022127811A1 (en) * | 2020-12-15 | 2022-06-23 | 华为技术有限公司 | Signal transmission method and device |
| CN117591379A (en) * | 2024-01-17 | 2024-02-23 | 苏州元脑智能科技有限公司 | Signal transmission optimization system, method and server board card |
| CN117591379B (en) * | 2024-01-17 | 2024-05-03 | 苏州元脑智能科技有限公司 | Signal transmission optimization system, method and server board card |
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