CN103812807B - 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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- CN103812807B CN103812807B CN201410073771.3A CN201410073771A CN103812807B CN 103812807 B CN103812807 B CN 103812807B CN 201410073771 A CN201410073771 A CN 201410073771A CN 103812807 B CN103812807 B CN 103812807B
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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 to a kind of filter of enhancing cosine-modulation based on convex optimisation technique
The method of ripple device group multi-carrier communications systems capacity of resisting disturbance.
Background technology
Cosine modulated filters group multi-transceiver technology is a kind of subcarrier multiplexing technology, belongs to filter bank multi-carrier
(fbmc) one of technology.Multi-carrier modulation technology can effectively resist multipath effect in wireless channel and wide because of it
General is applied in various communication standards.Its thought is using several subcarriers, and each subcarrier corresponds to one specifically
Subchannel, each sub-data flow of parallel transmission.Existing multi-carrier modulation mainly has multitone to realize, orthogonal multiple carrier is adjusted
System (ofdm) and the multi-carrier modulation based on wavelet transformation.Traditional fbmc system is based on discrete Fourier transform (dft) filter
Ripple device group is modulated.But dft wave filter group can not thoroughly eliminate interband aliasing interference, for signal Information Compression not
As cosine transform effect is good.Thus cosine modulated filters group is arisen at the historic moment, it is to produce from dft wave filter group, based on class
The fast algorithm of the discrete cosine transform of type 4, can reach the reconstruction completely of signal.Cosine modulated filters group communication system phase
There are a lot of advantages: higher transfer rate compared with ofdm, preferably anti-intersymbol interference ability, anti-ISI ability, without
Increase Cyclic Prefix, the availability of frequency spectrum is higher etc..But, it also has the shortcomings that itself, and due to its multi-carrier nature, time domain is disturbed
Fbmc systematic function can greatly be reduced.
The information technology of high speed development challenges the signal handling capacity of physical system, and traditional signal processing model is
Do not adapt to the data of such magnanimity, therefore compressive sensing theory framework is suggested.Compressive sensing theory is in the signal of redundancy
Perceive succinct information, thus effectively reducing the data volume that system is processed.The main research of compressed sensing has the dilute of signal
Relieving the exterior syndrome reaches, the design of observing matrix and signal recover.Accurate signal recovery algorithms are the keys in compressed sensing.Compressed sensing
As long as pointing out that signal is compressible or can be by rarefaction representation under certain transform domain, then just can with one with conversion base
Incoherent observing matrix projects to converting the high dimensional signal of gained on a lower dimensional space, and can be from these a small amount of measurements
In data, original signal is reconstructed with high probability.Compressive sensing theory mainly comprises following several respects content: the sparse table of (1) signal
Reach.In general signal x itself is not sparse, and it is accomplished by finding certain orthogonal basis or tight frame ψ.Make signal x through becoming
It is sparse in ψ after changing.(2) design of observing matrix ф.Compressive sensing theory passes through observing matrix perception information, so such as
What designs the more incoherent observing matrix with orthogonal basiss, is to ensure that the premise of information integrity.(3) signal recovers.Signal is extensive
Solve again from owing recovery signal problem constant linear observation, the recovery algorithms how designing rapidly and efficiently are compressive sensing theories
It is able to wide variety of basis.Recovery algorithms rapidly and efficiently are that compressive sensing theory is able to wide variety of basis.Its core
Thought is data sampling and compression merging is carried out.There are two aspect basic demands: openness, observing matrix and the transformation matrix of signal
Non-correlation.Existing related proof random matrix and 4 type cosine transform matrixes have good non-correlation.Compressed sensing technology
Advantage be can be with less than being that the sampling rate of Qwest's sample rate is sampled to signal, thus decreasing signals collecting and biography
Energy expenditure during defeated.Convex method of relaxation is that compressed sensing recovery problem is transformed into minimum l1The convex optimization problem of norm.
Convex optimization is the special nonlinear optimization skill of a class of the maximum (minimum) solving convex object function under convex function constraint
Art.Convex optimization method has the advantages that local minizing point is global minimizer, and particularly object function is strictly convex function
When, then global minimum only.l1It is a separable function that norm can comprise sparse characteristic again, convex method of relaxation profit
With this feature as object function, can effectively solve the problem that the signal recovery problems in compressed sensing.Common convex optimization method:
Interior point method, gradient projection method, iteration weighting method and collapse threshold method etc..Sparse gradient projection method is based on gradient descent method
Sparse signal restoration methods, it introduces hidden variable and the object function of non-differentiability is transformed into the convex object function of no constraint that can be micro-.
Sparse gradient project algorithms are not affected by initial value, the problem of the extensive signal of effective process, but also can using one kind just
Then the continuous scheme of the factor reduces the run time of algorithm and dredges signal recovery method, and it introduces hidden variable by the object function of non-differentiability
It is transformed into the convex object function of no constraint that can be micro-.
Content of the invention
In view of this, it is an object of the invention to provide a kind of enhancing cosine modulated filters group based on convex optimisation technique
The method of multi-carrier communications systems capacity of resisting disturbance, the method can effectively improve the reliability of signal transmission.
For reaching above-mentioned purpose, the present invention following technical scheme of offer:
A kind of method strengthening cosine modulated filters group multi-carrier communications systems capacity of resisting disturbance, comprises the following steps:
Step one: first primary signal x is carried out with baseband modulation in transmitting terminal and r position serial to parallel conversion obtains parallel signal；Step 2: simultaneously
Radom insertion null value in row signal, null value number is fixed；Step 3: cosine-modulation integrated filter is carried out to the signal of insertion null value
Device group is modulated, then is launched by Gaussian channel；Step 4: receiving terminal to receipt signal y after Gaussian channel at
Reason, first carries out fast Fourier transform, then carries out frequency domain equalization to signal, then carry out inverse fast Fourier transform to signal and obtain
To time-domain signal r；Step 5: again by time-domain signal r after based on convex optimisation technique interference estimation block, obtain comprising in r
Interference signal s, then again by signal r with carry out subtracting computing with interference signal s, obtain new signal；Step 6: again to new
Signal carries out the operation such as cosine modulated filters analysis filter group demodulation base band demodulating, obtains originally transmitted signal x.
Further, the baseband modulation in transmitting terminal adopts bpsk, qpsk, 16qam or 64qam modulation system.
Further, interference signal must is fulfilled for sparse characteristic, and that is, the nonzero coefficient k of signal is far smaller than dimension n of signal.
Further, the value of the nonzero coefficient k of signal is less than 5, makes interference signal meet sparse as much as possible requirement.
Further, l null value of radom insertion in the parallel signal of transmitting terminal, but null value number deducts r for n, i.e. l=n-
R, wherein n be insertion null value after parallel signal length, also for the dimension of interference signal, and n is 2 index, be 128,256 or
Person 512.
Further, the nonzero coefficient k of interference signal is necessarily less than number l of transmitting terminal parallel signal radom insertion null value, l
Also it is far smaller than dimension n of signal, that is, have k < l < < n.
Further, it is cosine modulated filters in the synthesis filter group of transmitting terminal and the analysis filter group of receiving terminal
Group, is all based on 4 type discrete cosine transforms.
Further, the described interference estimation block method therefor based on convex optimisation technique is compressed sensing convexity optimal reconfiguration
Sparse gradient projection method in method.The variable that the method recovers required for interference signal is to have observing matrix ф, basic matrix respectively
For ψ, and observation r, wherein observing matrix ф is the random Gaussian matrix of l × n, and random Gaussian matrix is to obey to be desired for
0, variance is the independent identically distributed elementary composition matrix of 1/m, and ψ is the 4 type discrete cosine transformation matrix of n × n, observation
It is signal r.
The beneficial effects of the present invention is: the method for the invention is by connecing in cosine filter group multi-carrier communications systems
Receiving end introduces and completes estimating it is achieved that extensive to primary signal to interference signal based on the interference estimation block of convex optimisation technique
Multiple, it is that the reliable reception of multi-carrier communications systems signal provides a kind of simple and effective solution.
Brief description
In order that the purpose of the present invention, technical scheme and beneficial effect are clearer, the present invention provides drawings described below to carry out
Illustrate:
The schematic flow sheet of the cosine modulated filters group multi-carrier communications systems that Fig. 1 provides for the present invention；
The internal frame diagram of the cosine modulated filters group that Fig. 2 provides for the present invention；
The receiving terminal immunity module schematic flow sheet that Fig. 3 provides for the present invention.
Specific embodiment
Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described in detail.
It is as follows that the method for the anti-interference of communication system ability that the present invention provides implements step:
1) first baseband modulation and serial to parallel conversion are carried out to primary signal x signal.
2) signal after baseband modulation is carried out serial to parallel conversion.
3) l null value of radom insertion in parallel signal, but null value number is fixed.
4) signal of insertion null value is carried out with 4 type cosine synthesis filter groups to modulate and launch by Gaussian channel.
5) time-domain signal receiving y being carried out fast Fourier transform (fft) becomes frequency-region signal it is therefore an objective to believe to this
Number carry out frequency domain equalization, eliminate the impact of white Gaussian noise, then carrying out inverse fast Fourier transform (ifft), obtaining signal
h.
6) signal h is carried out serial to parallel conversion, obtain parallel signal r.
7) Interference Estimation based on convex optimization, the observing matrix ф needed for construction signal reconstruction.Want accurate reconstruction signal,
ф must is fulfilled for limited equidistant characteristics (rip) criterion, and ф can meet this characteristic for random Gaussian matrix in the present invention.Using sight
Survey matrix ф, observation r, 4 type dct transformation matrix ψ, by the sparse gradient projection method of convex optimization, signal is reconstructed, estimates
Count out channel disturbance s, wherein r is the signal after inverse fast Fourier transform, ψ is the 4 type discrete cosine transformation matrix of n × n.
8) more former parallel signal and interference signal are carried out subtracting computing and obtain new signal.
9) the new signal obtaining is carried out 4 type Cosine Analysis wave filter group demodulation, the signal demodulating is carried out base band
Demodulation parallel serial conversion, recovers primary signal.
The schematic flow sheet of the cosine modulated filters group multi-carrier communications systems that Fig. 1 provides for the present invention, as illustrated,
The present invention is broadly divided into four parts:
1st, the cosine modulated filters group Multi-Carriers system configuration that the present invention uses:
Cosine modulated filters group is that transmitting terminal adopts synthesis filter, and receiving terminal adopts analysis filter.Integrated filter
Device and analysis filter, all using cosine modulated filters group (referring to Fig. 2), carry out 4 type cosine transforms.
2nd, the signal processing of transmitting terminal:
Digital signal first passes through baseband modulation, and generally can select has the modulation methods such as bpsk, qpsk, 16qam, 64qam
Formula, the signal after baseband modulation is done the serial to parallel conversion of r position, then l null value of radom insertion, utilizes convex optimization when being easy to receive
Technology estimates interference.Signal is carried out with the modulation of cosine-modulation synthesis filter group again, finally by parallel serial conversion, obtains one
Base band temporal modulation signal after fbmc modulation, this signal is launched by Gaussian channel.Wherein, the subcarrier of setting
Number is n, and n is 2 index, and l < < n.
3rd, the signal processing of receiving terminal:
Sending signal is affected by white Gaussian noise and interference through Gaussian channel, and receiving terminal first carries out express delivery to signal
Fourier transformation (fft), then signal is equalized, eliminate white Gaussian noise impact.Then fast Fourier is carried out to signal
Inverse transformation (ifft), obtains signal r, and r is put in depositor, subsequently enters the interference estimation block based on convex optimisation technique,
Obtain interference signal s using sparse gradient projection method, deduct interference signal s using the r in depositor, the signal obtaining carries out remaining
String Modulation analysis wave filter group, thus recover primary signal.
4th, the sparse gradient project algorithms estimated disturbance signal of convex optimization
Due to the null value in transmitting terminal parallel signal radom insertion, this portion subcarriers is made not carry information.Meet sparse
Property interference add signal after, through fast Fourier transform (dft) conversion, the energy of interference has been assigned each height and has carried
On ripple, process, in receiving terminal, the subcarrier that transmitting terminal does not carry information, can be achieved with the estimation to interference.Due to pre-setting
Time domain interference nonzero value number be k, k is far smaller than n, make interference signal meet signal in compressive sensing theory have openness
Requirement, so utilize observing matrix ф, observation r, 4 type dct transformation matrix ψ, thrown by sparse gradient in convex optimized algorithm
Shadow method is reconstructed to interference signal it is possible to estimate channel disturbance s.Wherein ф is the random matrix of l × n, and r is in quick Fu
Signal after leaf inverse transformation, ψ is the 4 type discrete cosine transformation matrix of n × n.
Finally illustrate, preferred embodiment above only in order to technical scheme to be described and unrestricted, although logical
Cross above preferred embodiment the present invention to be described in detail, it is to be understood by those skilled in the art that can be
In form and various changes are made to it, without departing from claims of the present invention limited range in details.
Claims (5)
1. a kind of strengthen cosine modulated filters group multi-carrier communications systems capacity of resisting disturbance method it is characterised in that: include
Following steps:
Step one: first primary signal x is carried out with baseband modulation in transmitting terminal and r position serial to parallel conversion obtains parallel signal；
Step 2: radom insertion null value in parallel signal, null value number is fixed；
Step 3: the modulation of cosine-modulation synthesis filter group is carried out to the signal of insertion null value, then is launched by Gaussian channel；
Step 4: receiving terminal, to the receipt signal y process after Gaussian channel, first carries out fast Fourier transform, then
Frequency domain equalization is carried out to signal, then inverse fast Fourier transform is carried out to signal and obtain time-domain signal r；
Step 5: again by time-domain signal r after based on convex optimisation technique interference estimation block, obtain the interference letter comprising in r
Signal r then is carried out subtracting computing with interference signal s, obtains new signal by number s again；
Step 6: newer signal is carried out with the operation of cosine modulated filters analysis filter group demodulation base band demodulating, obtains
Originally transmitted signal x；
Interference signal must is fulfilled for sparse characteristic, and that is, the nonzero coefficient k of signal is far smaller than dimension n of signal；In transmitting terminal
L null value of radom insertion in parallel signal, but null value number deducts r for n, i.e. and l=n-r, wherein n believe parallel for after insertion null value
Number length, also for the dimension of interference signal, and n is 2 index, is 128,256 or 512；The nonzero coefficient k of interference signal
It is necessarily less than number l of transmitting terminal parallel signal radom insertion null value, l is also far smaller than dimension n of signal, that is, have k < l < < n.
2. a kind of side strengthening cosine modulated filters group multi-carrier communications systems capacity of resisting disturbance according to claim 1
Method it is characterised in that: transmitting terminal baseband modulation adopt bpsk, qpsk, 16qam or 64qam modulation system.
3. a kind of side strengthening cosine modulated filters group multi-carrier communications systems capacity of resisting disturbance according to claim 2
Method it is characterised in that: the value of the nonzero coefficient k of signal be less than 5, make interference signal meet sparse as much as possible requirement.
4. a kind of side strengthening cosine modulated filters group multi-carrier communications systems capacity of resisting disturbance according to claim 3
Method it is characterised in that: be cosine modulated filters in the synthesis filter group of transmitting terminal and the analysis filter group of receiving terminal
Group, is all based on 4 type discrete cosine transforms.
5. a kind of side strengthening cosine modulated filters group multi-carrier communications systems capacity of resisting disturbance according to claim 3
Method it is characterised in that: the described interference estimation block method therefor based on convex optimisation technique be compressed sensing convexity optimal reconfiguration
Sparse gradient projection method in method.
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| EP3203695A1 (en) * | 2016-02-04 | 2017-08-09 | ABB Schweiz AG | Matrix equalizer for cmfb transmission in dispersive channels |
| 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 |
| CN114640563A (en) * | 2020-12-15 | 2022-06-17 | 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 |
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