CN109743118A - A kind of double OFDM underwater acoustic communication methods for expanding the spectral efficient under channel condition of time-varying - Google Patents
A kind of double OFDM underwater acoustic communication methods for expanding the spectral efficient under channel condition of time-varying Download PDFInfo
- Publication number
- CN109743118A CN109743118A CN201811584348.4A CN201811584348A CN109743118A CN 109743118 A CN109743118 A CN 109743118A CN 201811584348 A CN201811584348 A CN 201811584348A CN 109743118 A CN109743118 A CN 109743118A
- Authority
- CN
- China
- Prior art keywords
- signal
- doppler
- time
- estimation
- expanding
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Cable Transmission Systems, Equalization Of Radio And Reduction Of Echo (AREA)
- Radio Transmission System (AREA)
Abstract
A kind of double OFDM underwater acoustic communication methods for expanding the spectral efficient under channel condition of time-varying, belong to technical field of underwater acoustic communication.The present invention carries out bandpass filtering to signal r (k) is received, digital signal is converted into through ADC, after the front-end processings such as down coversion and low-pass filtering, average Doppler is estimated using ambiguity function method, after resampling and frequency correction, signal is multiplexed, time domain equalization and frequency domain equalization, diversity uses OMP-DCD algorithm to carry out residual doppler compensation after merging, using iteration signal processing technique, pass through software- redundancy mapping/demapping, interlacing device and de-interlacing device cascades ldpc decoder and balanced device, close information exchange is realized in the two modules, make full use of the Soft Inform ation back and forth transmitted, it is effective against the double interference for expanding channel of time-varying.The problems such as present invention can preferably compromise in complexity and aspect of performance, efficiently solve serious intersymbol interference in transmission process, inter-carrier interference, Pilot-data interference, the enough real-time implementations on dsp processor of complexity low energy.
Description
Technical field
The invention belongs to technical field of underwater acoustic communication, and in particular to a kind of double spectral efficients expanded under channel condition of time-varying
OFDM underwater acoustic communication method.
Background technique
OFDM is a kind of multi-carrier transmission scheme, and main thought is to divide available bandwidth into largely to have carrier frequency
The subband of rate transforms to high-speed serial data by serioparallel exchange and transmits on parallel orthogonal sub-channels, by increasing symbol
Period effectively offsets the influence of intersymbol interference, while it is reduced in the realization that the mode of frequency domain processing signal is receiving end balanced device
Complexity has the advantages that anti-multi-path capability is strong, band efficiency is high, traffic rate is fast with implementation complexity low etc..OFDM water
Sound communication system is ground mainly around the expansion of the key technologies such as synchronization, channel estimation, efficient error correcting code, Doppler shift
Study carefully, to give full play to the performance of OFDM technology.
The ofdm communication system of early stage is designed by S.Coatelan, and W.K.Lam et al. proposes complete OFDM earliest
The feature and basic structure of communication system, from 2005, American-European many Research Centers carried out OFDM underwater sound communication system on a large scale
Research and obtain many research achievements.Since the transmitting signal of ofdm system is by sending signal in multiple orthogonal sub-carriers
The shortcomings that superposition, this brings the following aspects to ofdm system: (1) vulnerable to the influence of Doppler shift；(2) it is added between protection
Every exchanging the abilities of more way extensions of overcoming for reduce efficiency of transmission；(3) it is influenced by time-varying system too big；(4) the equal power in peak
It compares hardware design and causes very big test.
Summary of the invention
Length is extended on more ways the purpose of the present invention is to solve the ofdm signal of unguarded interval and doppler spread is big
Time-varying it is double expand receiver detection performance lower problem when transmitting in underwater acoustic channels, propose that a kind of time-varying is double and expand under channel conditions
Spectral efficient OFDM underwater acoustic communication method.The present invention uses the ofdm signal and superposed pilot signal energy of unguarded interval
It enough realizes reliable communication and there is spectral efficient, the receiver proposed is able to solve intersymbol interference ISI, inter-carrier interference
The problems such as ICI, Pilot-data interference low with computational complexity and detection performance with higher.
The object of the present invention is achieved like this:
A kind of double OFDM underwater acoustic communication methods for expanding the spectral efficient under channel condition of time-varying, comprising the following steps:
(1) it after initial data is carried out LDPC coding, intertexture and BPSK mapping by transmitting terminal, is modulated by OFDM, by data
On modulates information to parallel subcarriers, then a known pilot signal is added on data-signal and is sent；
(2) the transmitting signal of step (1) reaches communication receiver after channel, receives signal r (k) and passes through front-end processing
Baseband signal is obtained after moduleTo baseband signalIt is obtained after carrying out average Doppler estimation, resampling and frequency correction
Oversampled signalsOversampled signalsIt is multiplexed to NτA signal, this NτA signal carries out diversity processing, independence
Signal Z (k) is finally merged into after weighing apparatus i.e. time domain equalization and frequency domain equalization；The double signals for expanding channel of experience are calculated using compressed sensing
Residual doppler extension in method equalizing signal；
(3) iteration signal processing technique is used in receivers, and decoder and balanced device are cascaded, decoder is passed through
With the iterative feedback of balanced device, constantly progress information exchange, resists underwater acoustic channel decline and inhibit interference, that improves receiver can
By property.
The step (1) specific steps are as follows:
(1.1) data source, that is, binary message stream b LDPC is carried out to encode to obtain coding binary bit stream c；
(1.2) coding binary bit stream is interleaved to the coding binary bit stream d after being interweaved；
(1.3) binary bit stream that step (1.2) obtains BPSK is carried out to map to obtain baseband signalling sequence e；
(1.4) baseband signalling sequence is subjected to serioparallel exchange, IFFT transformation, i.e. OFDM modulation obtains modulated OFDM
Symbol sebolic addressing s；
(1.5) known pilot signal is added in the OFDM symbol sequence that step (1.4) obtains, receiving end this
The pilot signal of superposition is for the double estimations for expanding channel of time-varying；
It (1.6) will include the superposed signal x transmission of data information and pilot frequency information.
The step (2) specific steps are as follows:
(2.1) front end processing block: received analog signal r (k) carries out bandpass filtering, converts after ADC analog-to-digital conversion
At obtaining baseband signal after digital signal, down coversion, low-pass filtering
(2.2) average Doppler is estimated: first passing through the pilot signal meter of the reception signal and a cycle of cross-correlation distortion
Ambiguity function is calculated, peak position is found and estimates optimal time-varying Doppler's scale factor, then throwing is utilized to above-mentioned peak value
Object line interpolation method advanced optimizes Doppler's estimation；
Average Doppler estimation is that the Doppler section for having maximum value is calculated by ambiguity function method, it may be assumed that
Wherein, χ (m :) is the Doppler section of ambiguity function, and m is doppler position, and n is delay positions,WithRespectively
For the estimated value of m and n；
After parabolic interpolation method, Doppler shift estimation is obtainedFor
WhereinK is indicated
In moment kTestObtain estimated value；
The scale factor accordingly estimatedFor
Wherein, fcFor the centre frequency for emitting signal, time change step length TestLess than one OFDM symbol duration Ts, i.e.,
Test< Ts；
(2.3) resampling and frequency correction: the discrete time estimation of the comparative example factor carries out linear interpolation, then using slotting
Scale factor resampling signal after valueCome the Doppler's frequency for compensating time-varying doppler spread, while basis being needed to estimate
Move fd(t) frequency correction is carried out, signal is obtained
Signal after resampling and frequency correctionFor
Wherein,ForThe continuous time signal obtained by linear interpolation,For the continuous of Doppler frequency shift
The estimation of time time-varying, tn=tn-1+Tr(n),Td=1/ (FNτ), F is transmitted signal bandwidth, NτFor
Oversample factor；
(2.4) oversampled signalsIt is multiplexed to NτA signal, this NτA signal carries out diversity processing, independent balanced
It is ultimately to be incorporated into together after time domain equalization and frequency domain equalization；
The output x of time-domain equalizer m branch based on channel estimationm(p) it is
Wherein,For the impulse response of balanced device, TeqFor time delay, LeqFor equalizer length, N is subcarrier number；
The frequency domain equalizer of m branch exports Zm(k) it is
Wherein XmIt (k) is the discrete Fourier transform of m branch time-domain equalizer output,Estimate for time domain channel,
γFDFor regularization parameter；
All diversity frequency domains merge output Z (k)
(2.5) the double signals for expanding channel of experience are using the residual doppler extension in compressed sensing algorithm equalizing signal.
The step (3) specific steps are as follows:
(3.1) turbo iterative process initializes: priori conditions mean μ=0 of setting transmitting symbol and priori conditions variance
V=1, channel estimation initial value are
(3.2) according to channel estimation and the priori conditions mean value computation ISI mean value of the transmitting symbol of calculating；
(3.3) LMMSE, that is, Linear Minimum Mean is utilized according to MSE, that is, Mean-Square Error criterion
Square Error algorithm updates equalizer filter coefficients vector, sends out after calculating equilibrium using equalizer filter coefficients vector
Penetrate the estimated value of symbol；
(3.4) the external information log-likelihood ratio L of each coded-bit of balanced device output is calculated by transmitting sign estimatione
(x)；
Wherein,Posterior probability when for symbol to be estimated being+1,For symbol to be estimated
Posterior probability when being -1,For the prior information of balanced device input；
(3.5) external information log-likelihood ratio obtains prior information log-likelihood ratio L after deinterleavinga(b), defeated as decoder
Enter, gives decoder and decoded based on MAP criterion, export the decoder external information L ' of next iteratione(b) and decoding result；
If the number of iterations is not up to maximum number of iterations thresholding, then carry out in next step；When reaching maximum number of iterations or iteration without gain
When, terminate iterative process, output decoder decodes result；
(3.6) decoder external information L 'e(b) become the prior information L ' of next iteration after interweavinga(x) soft map is carried out
To the priori conditions mean μ and priori conditions variance v of transmitting symbol, under BPSK modulation
μ=tanh (L 'a(x)/2),
V=1- | μ |2；
(3.7) channel estimation is carried out using the priori conditions mean μ and priori conditions variance v of transmitting symbol, obtains channel
Estimated value
(3.8) go to step (3.2).
Residual doppler described in step (2.5) is balanced, since underwater acoustic channel is sparse in time domain and frequency domain, to examine
The sparsity for considering delay-Doppler domain, after compensating for average Doppler, to the double letters for having residual doppler for expanding channel of experience
Number use OMP-DCD, that is, Orthogonal Matching Pursuit-Dichotomous Coordinate Descent algorithm
Carry out delay-Doppler-amplitude Combined estimator.
The OMP-DCD algorithm specifically includes the following steps:
(2.5.1) input:Redundant dictionary ADegree of rarefication K；WhereinExpression length is M
Received signal vector, initialization: enable residual epsilon0=y, the number of iterations q=1, U0=φ；
(2.5.2) cognitive phase: by residual epsilon and ajCarry out inner product:It determines corresponding
τ0,q,υ0,q, wherein ajIt is the jth column of A；τ and υ respectively indicates relative time delay and Doppler's scale；
The estimation of (2.5.3) time delay: local dictionary A is constructedτ(Ωτ,Ωυ), whereinΩυ=
{υ0,q}；Determine corresponding τq, wherein aτ,jIt is AτJth column；WhereinWhen indicating opposite
Prolong the estimated value of τ；
(2.5.4) Doppler estimation: local dictionary A is constructedυ(Ωτ,Ωυ), wherein Ωτ={ τq, Determine corresponding υq, wherein aυ,jIt is AυJth column；WhereinIndicate the estimated value of Doppler's scale υ；
(2.5.5) updates dictionary: Uq=Uq-1∪uυ,q；Least square problem: α is solved using DCD algorithmq=argminα||
y-Uqα||2；
(2.5.6) updates residual error: εq=y-Uqαq, the number of iterations increment q=q+1；
(2.5.7) judges whether to meet condition q > K, if satisfied, then iterative process stops；If conditions are not met, returning
(2.5.2) is continued cycling through；
(2.5.8) output: αq, Ω={ { τ1,υ1,α1},...,{τq,υq,αq}}。
The received signal vector y is built such that based on the signal model of redundant dictionary:
To estimate amplitude fading, Doppler's scale υ and relative time delay τ using the sparse restructing algorithm of compressed sensing, need first to exist
Splitting parametric grid in Doppler's scale and the parameter space in relative time delay, i.e.,
Wherein,
υn+1=υn+ Δ υ, n=1 ..., Dυ-1
τn+1=τn+ Δ τ, n=1 ..., Dτ-1
Redundant dictionary A is established further according to parametric grid and transmitting time domain plethysmographic signal s (t), i.e.,
Wherein
To establish the signal model of the redundant dictionary, i.e.,
Y=A α+η
Wherein
Recycle the sparse restructing algorithm of the compressed sensing, that is, OMP-DCD algorithm according to known received signal vector y
Sparse vector α is reconstructed with redundant dictionary A, according to the corresponding Doppler's scale of the location estimation of nonzero element in α and phase
To time delay, amplitude fading is estimated according to the value of nonzero element in α.
The beneficial effects of the present invention are:
The present invention is communicated using the ofdm signal and superposed pilot signal of unguarded interval in double expand in underwater acoustic channel of time-varying,
Receiving end carries out doppler spread to the cross ambiguity function of pilot signal and corresponding interpolation technique by calculating reception signal
Estimation and compensation, design a kind of practicable receiver can efficient detection data-signal, can efficiently solve transmission process
In serious intersymbol interference, inter-carrier interference, Pilot-data interference the problems such as.With work under noiseless situation, possessed
The ideal receiver of U.S. channel state information is compared, this receiver has the snr loss less than 3dB in the double expansion channels of time-varying.
Meanwhile the enough real-time implementations on DSP, that is, Digital Signal Processing processor of this Receiver Complexity low energy.
Detailed description of the invention
Fig. 1 is complete signal product process figure；
Fig. 2 is that receiver of the invention handles block diagram；
Fig. 3 is that receiver front end handles block diagram；
Fig. 4 is average Doppler estimation processing block diagram；
Fig. 5 is time-domain equalizer block diagram；
Fig. 6 is that time domain channel estimates block diagram.
Specific embodiment
The present invention is described in more detail with reference to the accompanying drawing.
Specific embodiment 1:
A kind of double OFDM underwater acoustic communication methods for expanding the spectral efficient under channel condition of time-varying, include the following steps:
After initial data is carried out LDPC coding, intertexture and BPSK mapping by step 1, transmitting terminal, modulates, will count by OFDM
It is believed that breath is modulated on parallel subcarriers, then a known pilot signal is added on data-signal and is sent, is being received
Hold this superposed signal for the double estimations for expanding channel of time-varying；
Step 2, step 1 transmitting signal communication receiver is reached after channel, to receive signal r (k) carry out signal
Processing, the specific steps are as follows:
Step 2.1, front end processing block, received analog signal r (k) carry out bandpass filtering, are converted into digital letter through ADC
Number, obtain baseband signal after down coversion, low-pass filtering
Step 2.2, average Doppler estimation first pass through the pilot signal of the reception signal and a cycle of cross-correlation distortion
Ambiguity function is calculated, peak position is found and estimates optimal time-varying Doppler's scale factor, then appeal peak value is utilized
Parabola interpolation method advanced optimizes Doppler's estimation；
Average Doppler estimation is that the Doppler section for having maximum value is calculated by ambiguity function method, it may be assumed that
Wherein, χ (m :) is the Doppler section of ambiguity function, and m is doppler position, and n is delay positions,WithRespectively
For the estimated value of m and n；
After parabolic interpolation method, Doppler shift estimation is obtainedFor
WhereinK is indicated
In moment kTestObtain estimated value；
The scale factor accordingly estimatedFor
Wherein, fcFor the centre frequency for emitting signal, time change step length TestLess than one OFDM symbol duration Ts, i.e.,
Test< Ts；
The discrete time estimation of step 2.3, resampling and frequency correction, the comparative example factor carries out linear interpolation, then sharp
With the scale factor resampling signal after interpolationIt compensates time-varying doppler spread, while needing how general according to estimating
Strangle frequency displacement fd(t) frequency correction is carried out, signal is obtained
Signal after resampling and frequency correctionFor
Wherein,ForThe continuous time signal obtained by linear interpolation,For the continuous of Doppler frequency shift
The estimation of time time-varying, tn=tn-1+Tr(n),Td=1/ (FNτ), F is transmitted signal bandwidth, NτFor
Oversample factor；
Step 2.4, oversampled signalsIt is multiplexed to NτA signal, this NτA signal carries out diversity processing, independent
Equilibrium is that time domain equalization and frequency domain equalization are ultimately to be incorporated into together；
The output x of time-domain equalizer m branch based on channel estimationm(p) it is
Wherein,For the impulse response of balanced device, TeqFor time delay, LeqFor equalizer length, N is subcarrier number；
The frequency domain equalizer of m branch exports Zm(k) it is
Wherein XmIt (k) is the discrete Fourier transform of m branch time-domain equalizer output,Estimate for time domain channel,
γFDFor regularization parameter；
All diversity frequency domains merge output Z (k)
The double signals for expanding channel of step 2.5, experience are using the residual doppler extension in compressed sensing algorithm equalizing signal；
Step 3 communicates, this hair in order to which the ofdm signal of unguarded interval effectively reliably expands in underwater acoustic channels in time-varying pair
It is bright to use iteration signal processing technique in receivers, decoder and balanced device are cascaded, decoder and balanced device are passed through
Iterative feedback, constantly progress information exchange, be effective against underwater acoustic channel decline and inhibit interference, further increase receiver
Reliability, the specific steps are as follows:
Step 3.1, the initialization of turbo iterative process, priori conditions mean μ=0 of setting transmitting symbol and priori conditions
Variance v=1, channel estimation initial value are
Step 3.2, the priori conditions mean value computation ISI mean value according to the transmitting symbol of channel estimation and calculating；
Step 3.3 updates equalizer filter coefficients vector using LMMSE algorithm according to MSE criterion, is filtered using balanced device
Wave device coefficient vector calculates the estimated value of transmitting symbol after equilibrium；
Step 3.4, the external information log-likelihood ratio that each coded-bit that balanced device exports is calculated by transmitting sign estimation
Le(x)；
Wherein,Posterior probability when for symbol to be estimated being+1,For symbol to be estimated
Posterior probability when being -1,For the prior information of balanced device input；
Step 3.5, external information log-likelihood ratio obtain prior information log-likelihood ratio L after deinterleavinga(b), as decoding
Device input is given decoder and decoded based on MAP criterion, exports the decoder external information L ' of next iteratione(b) it is tied with decoding
Fruit.If the number of iterations is not up to maximum number of iterations thresholding, then carry out in next step.When reaching maximum number of iterations or iteration without increasing
When beneficial, terminate iterative process, output decoder decodes result；
Step 3.6, decoder external information L 'e(b) become the prior information L ' of next iteration after interweavinga(x) soft mapping is carried out
The priori conditions mean μ and priori conditions variance v of transmitting symbol are obtained, under BPSK modulation
μ=tanh (L 'a' (x)/2),
V=1- | μ |2；
Step 3.7 carries out channel estimation using the priori conditions mean μ and priori conditions variance v of transmitting symbol, obtains letter
Road estimated value
Step 3.8 gos to step 3.2.
Specific embodiment 2: illustrating present embodiment according to Fig. 1, the concrete operation step of present embodiment step 1 is such as
Under:
Step 1.1 encodes data source, that is, binary message stream b progress LDPC to obtain coding binary bit stream c；
Coding binary bit stream is interleaved the coding binary bit stream d after being interweaved by step 1.2；
Step 1.3 maps the binary bit stream progress BPSK that step 1.2 obtains to obtain baseband signalling sequence e；
Baseband signalling sequence is carried out serioparallel exchange, IFFT (Inverse Fast Fourier by step 1.4
Transformation it) converts, i.e. OFDM modulation obtains modulated OFDM symbol sequence s；
Known pilot signal is added in the OFDM symbol sequence that step 1.4 obtains by step 1.5, receiving end this
The pilot signal of a superposition is for the double estimations for expanding channel of time-varying；
Step 1.6 will be sent including the superposed signal x of data information and pilot frequency information.
Other steps are same as the specific embodiment one.
Specific embodiment 3: considering that underwater acoustic channel may be considered that in time domain described in step 2.5 described in present embodiment
It is sparse with frequency domain, thus consider the sparsity in delay-Doppler domain, it is double to experience to expand after compensating for average Doppler
The signal for having residual doppler of channel uses OMP-DCD i.e. Orthogonal Matching Pursuit-Dichotomous
Coordinate Descent algorithm carries out delay-Doppler-amplitude Combined estimator.
Orthogonal matching pursuit OMP algorithm is a kind of greedy algorithm, and basic thought is: regarding observation signal as redundancy original
The linear combination of certain atoms in character library seeks optimal solution or locally optimal solution by the iterative process of certain number, so that
Estimate that the residual error of signal and original signal is smaller and smaller, final realize approaches original signal.The core concept of OMP algorithm:
The reconstruct to sparse signal α is realized using the method for iteration.Each iteration selection has the original of maximum correlation with current residual error
Then son subtracts relevant portion from observation vector, repeat the above process, until the number of iterations reaches degree of rarefication K.Due to every
Need to solve least square problem in secondary iteration, OMP algorithm operation quantity is larger, the present invention by OMP algorithm with to dividing coordinate to decline
DCD algorithm combines, and using OMP-DCD algorithm, the DCD algorithm based on binary search thought makes answering for sparse reconstruction solution
Miscellaneous degree substantially reduces.
The specific implementation step of algorithm is as shown in table 1.Double expansion underwater acoustic channels to be estimated in table 1Be it is sparse to
Amount, D is channel length, degree of rarefication K.Indicate that length is the received signal vector of M.τ and υ are respectively indicated in table 1
Relative time delay and Doppler's scale,WithRespectively indicate the estimated value of τ and υ.To be estimated using the sparse restructing algorithm of compressed sensing
Amplitude fading, Doppler's scale and relative time delay need the first splitting in Doppler's scale and the parameter space in relative time delay
Parametric grid, i.e.,
Wherein,
υn+1=υn+ Δ υ, n=1 ..., Dυ-1
τn+1=τn+ Δ τ, n=1 ..., Dτ-1
Redundant dictionary A is established further according to parametric grid and transmitting time domain plethysmographic signal s (t), i.e.,
Wherein
To establish the signal model of the redundant dictionary, i.e.,
Y=A α+η
Wherein
Recycle the sparse restructing algorithm of compressed sensing according to known received signal vector y and redundant dictionary A to it is sparse to
Amount α is reconstructed, and corresponding Doppler's scale and relative time delay can be estimated according to the position of nonzero element in α, according to non-in α
The value of neutral element can estimate amplitude fading.Dictionary is divided into Global Dictionary and local dictionary, the Global Dictionary A=in table 1
{aj, the column vector a in 1≤j≤DjIt is all unit vector.U represents all column vector structures that index in A belongs to supported collection in table 1
At matrix, collection composed by the index of nonzero element is collectively referred to as supported collection in α, u represent in A with residual epsilon inner product maximum one
Column vector.
Table 1: double expansion underwater acoustic channel algorithm for estimating based on OMP-DCD algorithm
Other steps are identical with embodiment two.
Claims (7)
1. a kind of double OFDM underwater acoustic communication methods for expanding the spectral efficient under channel conditions of time-varying, which is characterized in that including with
Lower step:
(1) it after initial data is carried out LDPC coding, intertexture and BPSK mapping by transmitting terminal, is modulated by OFDM, by data information
It is modulated on parallel subcarriers, then a known pilot signal is added on data-signal and sends；
(2) the transmitting signal of step (1) reaches communication receiver after channel, receives signal r (k) and passes through front end processing block
After obtain baseband signalTo baseband signalIt is obtained after carrying out average Doppler estimation, resampling and frequency correction
Sampled signalOversampled signalsIt is multiplexed to NτA signal, this NτA signal carries out diversity processing, independent equilibrium
Signal Z (k) is finally merged into after time domain equalization and frequency domain equalization；Compressed sensing algorithm is used to the double signals for expanding channel of experience
Residual doppler extension in equalizing signal；
(3) iteration signal processing technique is used in receivers, decoder and balanced device are cascaded, by decoder and
The iterative feedback of weighing apparatus, constantly progress information exchange resist underwater acoustic channel decline and inhibit interference, improve the reliable of receiver
Property.
2. a kind of double underwater sound communication sides OFDM for expanding the spectral efficient under channel condition of time-varying according to claim 1
Method, which is characterized in that the step (1) specific steps are as follows:
(1.1) data source, that is, binary message stream b LDPC is carried out to encode to obtain coding binary bit stream c；
(1.2) coding binary bit stream is interleaved to the coding binary bit stream d after being interweaved；
(1.3) binary bit stream that step (1.2) obtains BPSK is carried out to map to obtain baseband signalling sequence e；
(1.4) baseband signalling sequence is subjected to serioparallel exchange, IFFT transformation, i.e. OFDM modulation obtains modulated OFDM symbol
Sequence s；
(1.5) known pilot signal is added in the OFDM symbol sequence that step (1.4) obtains, in this superposition of receiving end
Pilot signal for the double estimations for expanding channels of time-varying；
It (1.6) will include the superposed signal x transmission of data information and pilot frequency information.
3. a kind of double underwater sound communication sides OFDM for expanding the spectral efficient under channel condition of time-varying according to claim 1
Method, which is characterized in that the step (2) specific steps are as follows:
(2.1) front end processing block: received analog signal r (k) carries out bandpass filtering, is converted into counting after ADC analog-to-digital conversion
Baseband signal is obtained after word signal, down coversion, low-pass filtering
(2.2) average Doppler is estimated: first passing through the pilot signal calculating mould for receiving signal and a cycle of cross-correlation distortion
Function is pasted, peak position is found and estimates optimal time-varying Doppler's scale factor, then parabola is utilized to above-mentioned peak value
Interpolation method advanced optimizes Doppler's estimation；
Average Doppler estimation is that the Doppler section for having maximum value is calculated by ambiguity function method, it may be assumed that
Wherein, χ (m :) is the Doppler section of ambiguity function, and m is doppler position, and n is delay positions,WithRespectively m
With the estimated value of n；
After parabolic interpolation method, Doppler shift estimation is obtainedFor
WhereinK indicate when
Carve kTestObtain estimated value；
The scale factor accordingly estimatedFor
Wherein, fcFor the centre frequency for emitting signal, time change step length TestLess than one OFDM symbol duration Ts, i.e. Test
< Ts；
(2.3) resampling and frequency correction: the discrete time estimation of the comparative example factor carries out linear interpolation, then using after interpolation
Scale factor resampling signalCome the Doppler frequency shift f for compensating time-varying doppler spread, while basis being needed to estimated
(t) frequency correction is carried out, signal is obtained
Signal after resampling and frequency correctionFor
Wherein,ForThe continuous time signal obtained by linear interpolation,For the continuous time of Doppler frequency shift
Time-varying estimation, tn=tn-1+Tr(n),Td=1/ (FNτ), F is transmitted signal bandwidth, NτIt is adopted to cross
Like factor；
(2.4) oversampled signalsIt is multiplexed to NτA signal, this NτA signal carries out diversity processing, independent balanced instant
It is ultimately to be incorporated into together after domain equilibrium and frequency domain equalization；
The output x of time-domain equalizer m branch based on channel estimationm(p) it is
Wherein,For the impulse response of balanced device, TeqFor time delay, LeqFor equalizer length, N is subcarrier number；
The frequency domain equalizer of m branch exports Zm(k) it is
Wherein XmIt (k) is the discrete Fourier transform of m branch time-domain equalizer output,For time domain channel estimation, γFD
For regularization parameter；
All diversity frequency domains merge output Z (k)
(2.5) the double signals for expanding channel of experience are using the residual doppler extension in compressed sensing algorithm equalizing signal.
4. a kind of double underwater sound communication sides OFDM for expanding the spectral efficient under channel condition of time-varying according to claim 1
Method, which is characterized in that the step (3) specific steps are as follows:
(3.1) turbo iterative process initializes: priori conditions mean μ=0 of setting transmitting symbol and priori conditions variance v=
1, channel estimation initial value is
(3.2) according to channel estimation and the priori conditions mean value computation ISI mean value of the transmitting symbol of calculating；
(3.3) LMMSE, that is, Linear Minimum Mean Square is utilized according to MSE, that is, Mean-Square Error criterion
Error algorithm updates equalizer filter coefficients vector, emits symbol after calculating equilibrium using equalizer filter coefficients vector
Estimated value；
(3.4) the external information log-likelihood ratio L of each coded-bit of balanced device output is calculated by transmitting sign estimatione(x)；
Wherein,Posterior probability when for symbol to be estimated being+1,When for symbol to be estimated being -1
Posterior probability,For the prior information of balanced device input；
(3.5) external information log-likelihood ratio obtains prior information log-likelihood ratio L after deinterleavinga(b), it inputs, send as decoder
Decode based on MAP criterion to decoder, exports the decoder external information L ' of next iteratione(b) and decoding result；Such as iteration
Number is not up to maximum number of iterations thresholding, then carries out in next step；When reaching maximum number of iterations or iteration without gain, terminate
Iterative process, output decoder decode result；
(3.6) decoder external information L 'e(b) become the prior information L ' of next iteration after interweavinga(x) soft mapping is carried out to be sent out
The priori conditions mean μ and priori conditions variance v for penetrating symbol, under BPSK modulation
μ=tanh (L 'a(x)/2),
V=1- | μ |2；
(3.7) channel estimation is carried out using the priori conditions mean μ and priori conditions variance v of transmitting symbol, obtains channel estimation
Value
(3.8) go to step (3.2).
5. a kind of double underwater sound communication sides OFDM for expanding the spectral efficient under channel condition of time-varying according to claim 3
Method, it is characterised in that: residual doppler described in step (2.5) is balanced, due to underwater acoustic channel in time domain and frequency domain be it is sparse,
It is remaining how general to having for the double expansion channels of experience after compensating for average Doppler to consider the sparsity in delay-Doppler domain
The signal of Le uses OMP-DCD, that is, Orthogonal Matching Pursuit-Dichotomous Coordinate
Descent algorithm carries out delay-Doppler-amplitude Combined estimator.
6. a kind of double underwater sound communication sides OFDM for expanding the spectral efficient under channel condition of time-varying according to claim 5
Method, which is characterized in that the OMP-DCD algorithm specifically includes the following steps:
(2.5.1) input:Redundant dictionary ADegree of rarefication K；WhereinIndicate that length is connecing for M
Signal vector is received, initialization: enables residual epsilon0=y, the number of iterations q=1, U0=φ；
(2.5.2) cognitive phase: by residual epsilon and ajCarry out inner product:Determine corresponding τ0,q,
υ0,q, wherein ajIt is the jth column of A；τ and υ respectively indicates relative time delay and Doppler's scale；
The estimation of (2.5.3) time delay: local dictionary A is constructedτ(Ωτ,Ωυ), whereinΩυ={ υ0,q}；Determine corresponding τq, wherein aτ,jIt is AτJth column；WhereinIndicate relative time delay τ's
Estimated value；
(2.5.4) Doppler estimation: local dictionary A is constructedυ(Ωτ,Ωυ), wherein Ωτ={ τq, Determine corresponding υq, wherein aυ,jIt is AυJth column；WhereinIndicate Doppler's scale υ
Estimated value；
(2.5.5) updates dictionary: Uq=Uq-1∪uυ,q；Least square problem: α is solved using DCD algorithmq=argminα||y-Uqα
||2；
(2.5.6) updates residual error: εq=y-Uqαq, the number of iterations increment q=q+1；
(2.5.7) judges whether to meet condition q > K, if satisfied, then iterative process stops；If conditions are not met, returning to (2.5.2)
It continues cycling through；
(2.5.8) output: αq, Ω={ { τ1,υ1,α1},...,{τq,υq,αq}}。
7. a kind of double underwater sound communication sides OFDM for expanding the spectral efficient under channel condition of time-varying according to claim 6
Method, which is characterized in that the received signal vector y is built such that based on the signal model of redundant dictionary:
To estimate amplitude fading, Doppler's scale υ and relative time delay τ using the sparse restructing algorithm of compressed sensing, need first how general
Splitting parametric grid in scale and the parameter space in relative time delay is strangled, i.e.,
Wherein,
υn+1=υn+ Δ υ, n=1 ..., Dυ-1
τn+1=τn+ Δ τ, n=1 ..., Dτ-1
Redundant dictionary A is established further according to parametric grid and transmitting time domain plethysmographic signal s (t), i.e.,
Wherein
To establish the signal model of the redundant dictionary, i.e.,
Y=A α+η
Wherein
Recycle the sparse restructing algorithm of the compressed sensing, that is, OMP-DCD algorithm according to known received signal vector y and superfluous
Sparse vector α is reconstructed in remaining dictionary A, according to the corresponding Doppler's scale of the location estimation of nonzero element in α and it is opposite when
Prolong, amplitude fading is estimated according to the value of nonzero element in α.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811584348.4A CN109743118B (en) | 2018-12-24 | 2018-12-24 | OFDM underwater acoustic communication method with high spectrum efficiency under time-varying double-spread channel condition |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811584348.4A CN109743118B (en) | 2018-12-24 | 2018-12-24 | OFDM underwater acoustic communication method with high spectrum efficiency under time-varying double-spread channel condition |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109743118A true CN109743118A (en) | 2019-05-10 |
| CN109743118B CN109743118B (en) | 2021-05-11 |
Family
ID=66359639
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811584348.4A Active CN109743118B (en) | 2018-12-24 | 2018-12-24 | OFDM underwater acoustic communication method with high spectrum efficiency under time-varying double-spread channel condition |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109743118B (en) |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110336761A (en) * | 2019-07-12 | 2019-10-15 | 电子科技大学 | The beam space channel estimation methods of the extensive mimo system of millimeter wave |
| CN110784282A (en) * | 2019-09-12 | 2020-02-11 | 浙江大学 | Underwater acoustic communication data reuse method based on soft information transfer |
| CN110808928A (en) * | 2019-10-31 | 2020-02-18 | 苏州桑泰海洋仪器研发有限责任公司 | Orthogonal multi-carrier Doppler estimation calculation method based on channel sparsity detection |
| CN110943945A (en) * | 2019-11-08 | 2020-03-31 | 哈尔滨工程大学 | Underwater sound OFDM superposition coding receiving method |
| CN111106877A (en) * | 2019-12-11 | 2020-05-05 | 中国科学院声学研究所 | Underwater acoustic communication transmission method based on Farrow filtering and code word matching |
| CN111711492A (en) * | 2020-05-09 | 2020-09-25 | 中国科学院声学研究所 | Underwater acoustic communication symbol timing estimation and compensation method and device for deep submersible vehicle |
| CN112054973A (en) * | 2020-08-28 | 2020-12-08 | 西北工业大学 | Minimum mean square error sparse underwater acoustic channel estimation method |
| CN112671473A (en) * | 2020-12-25 | 2021-04-16 | 大连理工大学 | OTFS underwater acoustic communication method based on passive time reversal technology |
| CN112737996A (en) * | 2020-12-25 | 2021-04-30 | 中国科学院声学研究所 | Time-varying timing offset iterative estimation and compensation method and device for underwater acoustic communication |
| CN115118566A (en) * | 2021-03-22 | 2022-09-27 | 诺基亚技术有限公司 | Improved transmission of information in wireless communications |
| CN115134201A (en) * | 2022-07-12 | 2022-09-30 | 上海应用技术大学 | Method for optimizing V2X channel estimation by time delay expansion iterative computation |
| CN115208480A (en) * | 2022-06-30 | 2022-10-18 | 哈尔滨工程大学 | Under-ice underwater acoustic communication method based on joint message transfer |
| CN115378781A (en) * | 2022-07-05 | 2022-11-22 | 厦门大学 | Received signal processing method and device of underwater sound OFDM communication system |
| CN116484180A (en) * | 2023-06-21 | 2023-07-25 | 中国人民解放军国防科技大学 | System and method for extracting communication signal gene |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20090083003A (en) * | 2008-01-29 | 2009-08-03 | 삼성전자주식회사 | Apparatus and method for estimating doppler spread in wireless communication system |
| CN101631099A (en) * | 2009-08-05 | 2010-01-20 | 华南理工大学 | Multi-input and multi-output selectivity OFDM underwater sound communication system and method |
| CN102065046A (en) * | 2009-11-11 | 2011-05-18 | 北京泰美世纪科技有限公司 | Information transmission method and signal generation device of OFDM (Orthogonal Frequency Division Multiplexing) system |
| CN102868659A (en) * | 2012-08-31 | 2013-01-09 | 中国船舶重工集团公司第七一五研究所 | Symbol synchronization and Doppler compensation method for mobile orthogonal frequency division multiplexing (OFDM) underwater sound communication signal |
| CN103491046A (en) * | 2013-09-12 | 2014-01-01 | 江苏科技大学 | Method for processing Doppler expansion of underwater sound high-speed OFDM communication |
| CN107426120A (en) * | 2017-07-24 | 2017-12-01 | 哈尔滨工程大学 | A kind of underwater sound OFDM MFSK channel equalization methods based on least mean-square error |
| CN107911133A (en) * | 2017-11-17 | 2018-04-13 | 厦门大学 | The Doppler factor estimation and compensation method of a kind of mobile underwater sound communication |
| CN108092723A (en) * | 2017-12-28 | 2018-05-29 | 浙江大学 | Independent pathway Doppler effect correction and equalization methods under the double extended channel environment of the underwater sound based on compressed sensing algorithm |
-
2018
- 2018-12-24 CN CN201811584348.4A patent/CN109743118B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20090083003A (en) * | 2008-01-29 | 2009-08-03 | 삼성전자주식회사 | Apparatus and method for estimating doppler spread in wireless communication system |
| CN101631099A (en) * | 2009-08-05 | 2010-01-20 | 华南理工大学 | Multi-input and multi-output selectivity OFDM underwater sound communication system and method |
| CN102065046A (en) * | 2009-11-11 | 2011-05-18 | 北京泰美世纪科技有限公司 | Information transmission method and signal generation device of OFDM (Orthogonal Frequency Division Multiplexing) system |
| CN102868659A (en) * | 2012-08-31 | 2013-01-09 | 中国船舶重工集团公司第七一五研究所 | Symbol synchronization and Doppler compensation method for mobile orthogonal frequency division multiplexing (OFDM) underwater sound communication signal |
| CN103491046A (en) * | 2013-09-12 | 2014-01-01 | 江苏科技大学 | Method for processing Doppler expansion of underwater sound high-speed OFDM communication |
| CN107426120A (en) * | 2017-07-24 | 2017-12-01 | 哈尔滨工程大学 | A kind of underwater sound OFDM MFSK channel equalization methods based on least mean-square error |
| CN107911133A (en) * | 2017-11-17 | 2018-04-13 | 厦门大学 | The Doppler factor estimation and compensation method of a kind of mobile underwater sound communication |
| CN108092723A (en) * | 2017-12-28 | 2018-05-29 | 浙江大学 | Independent pathway Doppler effect correction and equalization methods under the double extended channel environment of the underwater sound based on compressed sensing algorithm |
Non-Patent Citations (1)
| Title |
|---|
| 周焕玲: "基于压缩感知的MIMO_OFDM冰下水声通信技术研究", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
Cited By (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110336761B (en) * | 2019-07-12 | 2021-04-02 | 电子科技大学 | Wave beam space channel estimation method of millimeter wave large-scale MIMO system |
| CN110336761A (en) * | 2019-07-12 | 2019-10-15 | 电子科技大学 | The beam space channel estimation methods of the extensive mimo system of millimeter wave |
| CN110784282A (en) * | 2019-09-12 | 2020-02-11 | 浙江大学 | Underwater acoustic communication data reuse method based on soft information transfer |
| CN110808928A (en) * | 2019-10-31 | 2020-02-18 | 苏州桑泰海洋仪器研发有限责任公司 | Orthogonal multi-carrier Doppler estimation calculation method based on channel sparsity detection |
| CN110808928B (en) * | 2019-10-31 | 2021-12-10 | 苏州桑泰海洋仪器研发有限责任公司 | Orthogonal multi-carrier Doppler estimation calculation method based on channel sparsity detection |
| CN110943945A (en) * | 2019-11-08 | 2020-03-31 | 哈尔滨工程大学 | Underwater sound OFDM superposition coding receiving method |
| CN111106877A (en) * | 2019-12-11 | 2020-05-05 | 中国科学院声学研究所 | Underwater acoustic communication transmission method based on Farrow filtering and code word matching |
| CN111711492B (en) * | 2020-05-09 | 2021-07-20 | 中国科学院声学研究所 | Underwater acoustic communication symbol timing estimation and compensation method and device for deep submersible vehicle |
| CN111711492A (en) * | 2020-05-09 | 2020-09-25 | 中国科学院声学研究所 | Underwater acoustic communication symbol timing estimation and compensation method and device for deep submersible vehicle |
| CN112054973A (en) * | 2020-08-28 | 2020-12-08 | 西北工业大学 | Minimum mean square error sparse underwater acoustic channel estimation method |
| CN112737996A (en) * | 2020-12-25 | 2021-04-30 | 中国科学院声学研究所 | Time-varying timing offset iterative estimation and compensation method and device for underwater acoustic communication |
| CN112671473B (en) * | 2020-12-25 | 2022-09-20 | 大连理工大学 | OTFS underwater acoustic communication method based on passive time reversal technology |
| CN112671473A (en) * | 2020-12-25 | 2021-04-16 | 大连理工大学 | OTFS underwater acoustic communication method based on passive time reversal technology |
| CN115118566A (en) * | 2021-03-22 | 2022-09-27 | 诺基亚技术有限公司 | Improved transmission of information in wireless communications |
| CN115118566B (en) * | 2021-03-22 | 2024-06-04 | 诺基亚技术有限公司 | Improved transmission of information in wireless communications |
| CN115208480A (en) * | 2022-06-30 | 2022-10-18 | 哈尔滨工程大学 | Under-ice underwater acoustic communication method based on joint message transfer |
| CN115378781B (en) * | 2022-07-05 | 2024-05-10 | 深圳市深海箭鱼科技有限公司 | Received signal processing method and device of underwater acoustic OFDM communication system |
| CN115378781A (en) * | 2022-07-05 | 2022-11-22 | 厦门大学 | Received signal processing method and device of underwater sound OFDM communication system |
| CN115134201A (en) * | 2022-07-12 | 2022-09-30 | 上海应用技术大学 | Method for optimizing V2X channel estimation by time delay expansion iterative computation |
| CN116484180B (en) * | 2023-06-21 | 2023-09-22 | 中国人民解放军国防科技大学 | System and method for extracting communication signal gene |
| CN116484180A (en) * | 2023-06-21 | 2023-07-25 | 中国人民解放军国防科技大学 | System and method for extracting communication signal gene |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109743118B (en) | 2021-05-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109743118A (en) | A kind of double OFDM underwater acoustic communication methods for expanding the spectral efficient under channel condition of time-varying | |
| JP5337165B2 (en) | Channel estimation method and system for wireless communication network with limited inter-carrier interference | |
| RU2332801C2 (en) | Evaluation of wireless communications service channel with variety of parallel data streams | |
| US7440507B1 (en) | Turbo channel estimation for OFDM systems | |
| KR100808949B1 (en) | Method of channel estimation using linear correlation based Interference Cancellation combined with Dicision-Feedback Equalization and apparatus thereof | |
| CN101494528B (en) | Training sequence design and channel estimation method of transmission diversity block transmission system | |
| JP4272665B2 (en) | Apparatus, method, and computer program for estimating channel of OFDM transmission system | |
| CN100385824C (en) | Adaptive channel estimation method of MIMO-OFDM system | |
| CN106549888B (en) | A kind of estimation of joint doubly selective channel and FTNS detection method based on GAMP | |
| JP2009532957A (en) | Channel estimation for rapidly dispersive fading channels | |
| CN106941465B (en) | Transmission method, transmitter, receiver and system of block with super-Nyquist rate | |
| CN108156101B (en) | MIMO-SCFDE system joint iteration channel estimation and iteration equalization method | |
| CN113381951A (en) | MFTN joint channel estimation and equalization method under time-frequency conversion selective fading channel | |
| CN115296970B (en) | Iterative orthogonal time-frequency space waveform detection method based on element-by-element external information | |
| CN107332606B (en) | LEO system differential space-time orthogonal frequency division multiplexing coding method based on double sampling | |
| CN101997799A (en) | Orthogonal frequency division multiplexing (OFDM) channel estimation method based on filter bank | |
| CN107124194A (en) | Marine digital intermediate frequency launches equipment | |
| WO2018000914A1 (en) | Single-carrier channel estimation method | |
| WO2013071759A1 (en) | Method, apparatus, receiver and communication device for estimating phase noise | |
| CN111064544A (en) | Cross-subcarrier underwater acoustic communication filtering multi-tone modulation method based on digital fountain coding | |
| Yin et al. | OFDM demodulation using virtual time reversal processing in underwater acoustic communications | |
| Wu et al. | On the symbol timing recovery in space-time coding systems | |
| CN111092834B (en) | Time reversal space-time block coding and self-adaptive equalization combined underwater acoustic communication method | |
| Yamada et al. | Performance of time and frequency compression of faster-than-nyquist signaling in frequency-selective fading channels | |
| Hao et al. | MIMO TDS-OFDM for underwater acoustic communication with turbo equalization |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210412 Address after: 572024 area A129, 4th floor, building 4, Baitai Industrial Park, yazhouwan science and Technology City, Yazhou District, Sanya City, Hainan Province Applicant after: Nanhai innovation and development base of Sanya Harbin Engineering University Address before: 150001 Intellectual Property Office, Harbin Engineering University science and technology office, 145 Nantong Avenue, Nangang District, Harbin, Heilongjiang Applicant before: HARBIN ENGINEERING University |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |