CN109286474A - Underwater sound communication Adaptive Modulation algorithm based on Steady State Square Error - Google Patents
Underwater sound communication Adaptive Modulation algorithm based on Steady State Square Error Download PDFInfo
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- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
- H04L1/0002—Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the transmission rate
- H04L1/0003—Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the transmission rate by switching between different modulation schemes
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Abstract
The present invention relates to technical field of underwater acoustic communication, specifically one kind is especially suitable for practical underwater sound communication system, the underwater sound communication Adaptive Modulation algorithm based on Steady State Square Error of communications system transmission reliability can be effectively improved, it is characterized in that transmitting terminal sends signal to establish the link with receiving end first, it handles signal is received, mean square error SMSE is obtained, and is converted to SNR；Then, it feeds back to transmitting terminal and is modulated the adaptively selected of mode, the present invention is compared with prior art, and it is not required to assume known to underwater acoustic channel status information, output SMSE based on blind equalization realizes the adaptive adjustment of modulation system, and the index considers influence of the underwater acoustic channel difference to detection performance, the tap length of blind equalizer can adaptively be adjusted according to specific underwater acoustic channel.
Description
Technical field:
It is specifically a kind of especially suitable for practical underwater sound communication system the present invention relates to technical field of underwater acoustic communication,
Communications system transmission reliability can be effectively improved, be not required to assume the water based on Steady State Square Error known to channel state information
Sound communication Adaptive Modulation algorithm.
Background technique:
The multipath of spatial variations and limited bandwidth produce significant limit to the achievable handling capacity of communication system at any time
System.And non-adaptive link transmission is that guarantee system is in acceptable performance, system is generally only for the worst channel condition
It is designed, this causes channel capacity to be underutilized.Especially for Underwater Acoustic Environment, underwater acoustic channel has narrow bandwidth
Characteristic improves the availability of frequency spectrum to make full use of limited bandwidth, and the Adaptive Modulation algorithm research in underwater sound communication starts
Attention by researchers at home and abroad.
The existing research about Adaptive Modulation focuses primarily upon communicating landline system, the research being directed under Underwater Acoustic Environment
It is limited.Recently, document Radosevic A, Ahmed R, Duman T M, et al.Adaptive OFDM modulation
for underwater acoustic communications:Design considerations and experimental
Results [J] .IEEE Journal of Oceanic Engineering, 2014,39 (2): 357-370 proposes a kind of base
In the adaptive modulation scheme of channel estimating, the program realize on condition that before having been estimated that the moment channel information, then base
In following channel information of the channel information prediction at moment before, to realize the adjustment of modulation system.Document Wan L, Zhou H,
Xu X,et al.Adaptive modulation and coding for underwater acoustic OFDM[J]
.IEEE Journal of Oceanic Engineering,2015,40(2):
327-336 proposes a kind of adaptive modulation scheme based on signal-to-noise ratio, and the program utilizes the channel shape estimated
State information calculates effective signal-to-noise ratio, is used as the adjustment that module is modulated mode.But both Adaptive Modulation sides
Method is required to assume underwater acoustic channel status information (Channel State Information, CSI) it is known that but since the underwater sound is believed
The property complicated and changeable in road, CSI are difficult to obtain.
Adaptive modulation system overall structure is as shown in Figure 1.Firstly, transmitter sends signal and receiver is established when work
Link.Then, receiving end carries out signal-to-noise ratio (SNR) estimation according to signal is received, and feeds back to transmitter, for realizing modulation system
It is adaptively selected.
Reception signal of the modulated signal s (n) after underwater acoustic channel are as follows:
R (n)=s (n) * h (n)+v (n) (1)
Wherein, h (n) is the impulse response of underwater acoustic channel, is obtained by BELLHOP model, and v (n) is additive white Gaussian noise,
Mean value is zero, and variance is* convolution algorithm is indicated；
The existing adaptive modulation scheme based on signal-to-noise ratio is as follows: where such as the system block diagram of the receiving end provided Fig. 2
It is shown, it receives signal and is on the one hand sent into blind equalizer, restore the modulation intelligence sent；On the one hand for estimating signal-to-noise ratio
(Signal-to-Noise Ratio, SNR), it is adaptively selected in a manner of feeding back to transmitting terminal and be modulated.
For signal-to-noise ratio (SNR) estimation, after realizing channel estimation based on minimum variance principle (Least Square, LS), according to
Channel estimation results carry out SNR calculating.Channel estimation is estimated by known training sequence, the basic principle is that estimation channel
Impulse response minimizes the channel impulse response of estimation and the error of actual channel impulse response.Receive signal such as formula (1) institute
Show, frequency domain form may be expressed as: R=HS+V (2)
The cost function of channel estimation indicates are as follows:
Ask local derviation that can obtain above formula:
The impulse response function of channel is obtained as a result, are as follows:
Assuming that send signal energy be it is normalized, then signal-to-noise ratio (SNR) estimation value are as follows:
After estimating SNR, by this instantaneous SNR feedback to transmitting terminal.Assuming that channel is interior constant during this period, transmitting terminal is being connect
After the estimation SNR for receiving feedback, it is modulated the selection of mode accordingly.And the switching threshold in Adaptive Modulation algorithm is extremely heavy
It wants.Threshold of the present invention is based on maximum system throughput criterion and obtains, defining handling capacity is the unit time in system
The interior information content that can correctly transmit, as follows:
Γ (γ)=(1-BER (γ)) log2(M)(7)；It follows that handling capacity Γ is the function about signal-to-noise ratio γ, M
Represent the size of planisphere.It is approximate public according to BER of the bit error rate and signal-to-noise ratio provided in document [3] under different modulating mode
Formula, the Adaptive Modulation algorithm steps based on maximize handling capacity are as follows:
(1) assume that the modulation system for having n kind to be selected in adaptive modulation scheme, set are represented by m={ m1,
m2,...,mn}；
(2) throughput curve of n kind modulation system will generate n-1 intersection point, and be n sections of areas by signal-to-noise ratio interval division
Between, SNR, the as switching threshold of modulation system corresponding to n-1 throughput curve intersection point are calculated, with set sΓ={ sΓ,1,
sΓ,2,...,sΓ,n-1Indicate, in order to find out the switching threshold of the Adaptive Modulation based on maximize handling capacity criterion, enable adjacent
The handling capacity of two kinds of modulation systems is equal, can solve intersection point, obtains threshold value sΓ={ sΓ,1,sΓ,2,...,sΓ,n-1, such as following formula institute
Show:
Γi(γ)=Γi+1(γ) i=1,2 ..., n-1 (8)
Wherein, Γi(γ) represents the handling capacity of i-th kind of modulation system of adaptive modulation scheme selection.Following table gives
The Threshold being calculated based on maximize handling capacity criterion:
The switching threshold statistical form of 1 modulation system of table
(3) threshold value set sΓ={ sΓ,1,sΓ,2,...,sΓ,n-1By entire signal-to-noise ratio interval division be n section, if general
The instantaneous SNR of receiving end feedback is indicated with γ, as γ < sΓ,1、sΓ,j≤ γ < sΓ,j(1≤j≤n-2) or γ >=sΓ,n-1When,
Select the maximum modulation system of handling capacity in respective bins.
As shown in the above, in traditional adaptive modulation scheme based on SNR, the selection of modulation system is with noise
Than for index, and the estimation of signal-to-noise ratio is dependent on the estimation to underwater acoustic channel.In fact, complicated and changeable due to underwater acoustic channel
Property, channel state information are difficult to estimate to obtain, and cause signal-to-noise ratio (SNR) estimation to be difficult to realize, therefore traditional based on the adaptive of signal-to-noise ratio
Modulation scheme is answered to be not particularly suited for actual underwater sound communication system.
Summary of the invention:
The present invention is directed to shortcoming and defect existing in the prior art, proposes one kind more suitable for practical underwater sound communication system
System, the output SMSE based on blind equalizer realize Adaptive Modulation, and SMSE is converted into the selection that signal-to-noise ratio is modulated mode,
It does not need to carry out channel estimation, the underwater sound communication based on Steady State Square Error for obtaining the status information of underwater acoustic channel is adaptive
Modulation algorithm.
The present invention can be achieved by the following measures:
A kind of underwater sound communication Adaptive Modulation algorithm based on Steady State Square Error, it is characterised in that transmitting terminal is sent first
Signal handles signal is received to establish the link with receiving end, obtains mean square error SMSE, and be converted to SNR；And
Afterwards, it feeds back to transmitting terminal and is modulated the adaptively selected of mode, wherein the received signal vector entered in blind equalizer indicates
For following formula:
uf(n)=[r (n) ..., r (n+L-1)] (9)
Output of the signal vector after blind equalization are as follows:
Wherein, tap weights vector and tap coefficient update are respectively as follows:
wf(n)=and [c (0), c (1) ..., c (L-1) ,]T (11)
Wherein error signal are as follows:
E (n)=efR(n)+jefI(n) (13)
Wherein, the real part e of error signalfR(n) with imaginary part efI(n) specific formula for calculation is as follows:
Blind equalization uses multi-modulus algorithm (Multi-Modulus Algorithm, MMA), wherein constant mould R2Real part R2R
With imaginary part R2IIt respectively indicates as follows:
SMSE is calculated by the output error signal e (n) of blind equalization, can be obtained by following formula:
SNR can be calculated by following formula:
Then the SNR estimated is corrected using data fitting algorithms on the basis of formula (19) result, so as to more preferable
Ground is modulated the selection of mode, the specific steps are as follows:
(1) polynomial curve fitting method is used, for two groups of given data: practical SNR and estimation SNR is used respectively
γs=[γs,1,γs,2,...,γs,m] and γg=[γg,1,γg,2,...,γg,m] indicate, it is secondary multinomial to construct a n (n≤m)
Formula is expressed as follows:
In order to make the signal-to-noise ratio estimated closer to practical signal-to-noise ratio, the data error quadratic sum in same position is enabled to reach
To minimum value, it is shown below:
Therefore, problem, which is converted into, seeks I (a0,a1,...,an) minimum problem, indicated using following:
I.e.
It may be expressed as: with matrix form
By mathematical knowledge it is found that formula (24) only has unique solution, and the unique solution is polynomial of degree n pn(γg) coefficient A
=[a0,a1,...,an], and coefficient array A can be acquired by the pivot elimination approach solving equations (24) in mathematics.
(2) multinomial coefficient A=[a is acquired by step (1)0,a1,...,an] after to get arrived practical SNR and estimation
The fitting of a polynomial relationship of SNR, then substituted into the polynomial relation formula solved
After obtaining curve matching, the relational expression of improved SMSE and SNR are as follows:
Wherein, S=[SMSE1,SMSE2,...,SMSEn] (i=1,2 ..., n), and (0 < SMSEi≤1)。
Realize that Adaptive Modulation is calculated after data are fitted to obtain the relationship of SMSE and SNR, then with maximize handling capacity criterion
Method, step is identical as the existing Adaptive Modulation process flow based on SNR, this is not repeated.
Present invention further proposes the change tap length Adaptive Modulations of based on SMS E, receive end structure at this time and use and divide
Section linear filter structure, blind equalizer is by comparing accumulative mean square error (the Accumulated Squared under different length
Error, ASE), the length of tap coefficient vector is updated, feeding back to transmitting terminal, mode is adaptively selected to be estimated for being modulated
SNR is counted, the output SMSE for being also based on change tap length blind equalization is obtained；
L is wherein enabled to be expressed as being segmented the tap length of FIR filter, the tap of blind equalizer used in current algorithm
Weight vector is wv(n)=and [c (0), c (1) ..., c (l-1) ,]T, with u (n)=[r (0) ..., r (l-1)] representation signal vector,
Then the w (n+1) of subsequent time is provided according to stochastic gradient descent method principle, is shown below:
ASE for carrying out tap length adjustment can be obtained by following formula:
Wherein l indicates the number of segment that current tap vector includes, and every section of length is p, and β≤1 is the forgetting factor in algorithm,
evl(n) for when the error of leading portion；
evl(n)=yvl,R(n)(|yvl,R(n)|2-R2R)+jyvl,I(n)(|yvl,I(n)|2-R2I) (29)
The wherein constant mould R in blind equalizer2Calculating see formula (16) and (17)；
By shown in formula (28), it can be deduced that l sectionsL-1 sections can similarly be obtained
IfThen show that the performance of blind equalization can be improved by increasing tap length.Next time
In iteration, algorithm will increase the tap length of blind equalization, since filter tap weight vector w (n) is only non-zero in blind equalization
The centre cap of value initializes, and algorithm can just converge to the minimum of cost function desired value, that is, be initialized as w (0)=
[0,...,0,1,0,...,0]；In order to guarantee that centre tapped weight specific gravity is maximum, in the algorithm for increasing p sections of taps updates,
Weigh tap vector wv(n) it extends, is shown below to both sides:
Correspondingly, signal vector uv(n) are as follows:
uv(n)=[r (n) ..., r (n+l+p-1)] (32)
IfThen show that the performance of blind equalization can be reduced by increasing tap length, next time
In iteration, algorithm will reduce the tap length of blind equalization, tap weights vector wv(n) and signal vector uv(n) respectively indicate as
Under:
uv(n)=[r (n) ..., r (n+l-p-1)] (34)
Become in tap blind equalization algorithm and participates in the parameter alpha that tap updatesupAnd αdownFollowing relationship should be met:
Wherein, αupAnd αdownNumerical value it is closer, tap length variation it is more frequent；It is obtained using tap length blind equalization is become
SMSE out, can obtain the SNR of modified estimation after over-fitting, it is fed back to transmitting terminal, based on maximization system throughput
Measure the adaptive adjustment that criterion realizes modulation system.
The invention proposes with blind equalization output Steady State Square Error (Steady-state Mean Square Error,
It SMSE is) the Adaptive Modulation algorithm of index, which is simultaneously not required to assume underwater acoustic channel status information it is known that based on blind equalization
The adaptive adjustment that SMSE realizes modulation system is exported, and the index considers influence of the underwater acoustic channel difference to detection performance,
The tap length of blind equalizer can adaptively be adjusted according to specific underwater acoustic channel.
Detailed description of the invention:
Attached drawing 1 is Adaptive Modulation the general frame.
Attached drawing 2 is the Adaptive Modulation receiving end structural block diagram based on SNR.
Attached drawing 3 is the fixed taps length Adaptive Modulation receiving end structural block diagram of based on SMS E in the present invention.
Attached drawing 4 is the change tap length Adaptive Modulation receiving end structural block diagram of based on SMS E in the present invention.
Attached drawing 5 is the estimation SNR and practical SNR graph of relation in emulation embodiment of the present invention under BPSK modulation.Attached drawing 6
It is the estimation SNR and practical SNR graph of relation in emulation embodiment of the present invention under 4QAM modulation.
Attached drawing 7 is the estimation SNR and practical SNR graph of relation in emulation embodiment of the present invention under 8QAM modulation.
Attached drawing 8 is the estimation SNR and practical SNR graph of relation in emulation embodiment of the present invention under 16QAM modulation.
Attached drawing 9 is that the handling capacity of the fixed taps length different modulating mode in emulation embodiment of the present invention based on SNR is bent
Line chart.
Attached drawing 10 is the throughput curve of the change tap length different modulating mode in emulation embodiment of the present invention based on SNR
Figure.
Attached drawing 11 is the handling capacity of the fixed taps length different modulating mode of based on SMS E in emulation embodiment of the present invention
Curve graph.
Attached drawing 12 is that the handling capacity of the change tap length different modulating mode of based on SMS E in emulation embodiment of the present invention is bent
Line chart.
Attached drawing 13 is the handling capacity comparative graph of the adaptive modulation system in emulation embodiment of the present invention based on SNR.
Specific embodiment:
The present invention is further illustrated with emulation experiment with reference to the accompanying drawing.
Wherein system emulation parameter setting is as follows: assuming that the information sequence length sent is 1000 bits, carrier frequency is
12kHz, underwater acoustic channel are obtained using BELLHOP model, and transmitting terminal and receiving end are respectively positioned on 10m depth position under sea, and wave is high
0.6m, distance is 100m between transmitting terminal and receiving end.Modulation system is set as tetra- kinds of modes of BPSK, 4QAM, 8QAM, 16QAM.
The SNR that based on SMS E is fitted with data is estimated as follows: the validity of based on SMS E estimation SNR is first verified that, by this
Modified estimated value, uncorrected estimated value and practical SNR are compared.When modulation system is BPSK, simulation result is such as
Shown in Fig. 5, the relationship of SMSE and SNR is correctly, can be realized and be adjusted using SMSE estimation SNR in result verification formula (20)
The selection of perfect square formula, but due to the imperfection of blind equalization, exporting SMSE, there are errors with theoretially optimum value.It can be with from Fig. 5
Find out, the SNR estimated value obtained after polynomial curve fitting method and the relationship of practical SNR are more approached, by bent
Relational expression after line fitting is as follows:
Wherein, S is the SMSE value in adaptive modulation system, γgTo estimate SNR value.
When modulation system is 4QAM, the relation curve of estimation SNR and practical SNR are as shown in fig. 6, estimation SNR and reality
Curve matching relational expression between SNR is as follows:
When modulation system is 8QAM, the relation curve of estimation SNR and practical SNR are as shown in fig. 7, estimation SNR and reality
Curve matching relational expression between SNR is as follows:
When modulation system is 16QAM, the relation curve of estimation SNR and practical SNR are as shown in figure 8, estimation SNR and reality
Curve matching relational expression between SNR is as follows:
By Fig. 5 to Fig. 8 as it can be seen that result is similar, the estimation SNR equilibrium after fitting approaches actual SNR, therefore based on SMS E
Realize that the scheme of modulation system is feasible.
The throughput curve simulation result under different modulating is compared below, wherein Fig. 9-10 gives traditional base
In SNR, throughput curve simulation result under different modulating mode.
Figure 11-Figure 12 gives based on SMS E, throughput curve simulation result under different modulating mode.
Using based on the adaptive of fixed taps it can be seen from the throughput curve of above-mentioned different adaptive modulation schemes
Modulation throughput curve intersection point is less than using based on the Adaptive Modulation throughput curve intersection point for becoming tap length.This is because
When Adaptive Modulation is using tap blind equalization algorithm is become, better SMSE performance can get, to improve output SNR, improve system
The throughput performance of system.
The handling capacity of different adaptive modulation schemes is compared below:
Figure 13 gives under maximize handling capacity criterion, and the throughput curve of two kinds of adaptive modulation schemes compares.By
Figure 13, which can be seen that, realizes Adaptive Modulation whether based on SNR or based on SMS E, when receiving end is blind using tap length is become
When balanced, the handling capacity of system is improved.This is because better error code can be obtained by becoming the detection of tap length blind equalization
Rate performance.This explanation is more applicable for underwater acoustic channel complicated and changeable based on the Adaptive Modulation algorithm for becoming tap length.In addition,
From Figure 13 it can also be seen that based on SMS E's proposed by the present invention is adaptive under the blind equalization precondition using same way
Answer modulation scheme that can obtain and throughput performance similar in the adaptive modulation scheme based on SNR.But the side that the present invention is mentioned
Case simultaneously is not required to estimate underwater acoustic channel, thus more suitable for actual underwater sound communication system.
In conclusion the invention proposes a kind of underwater sound communication Adaptive Modulation algorithm based on Steady State Square Error, it should
Scheme estimates SNR based on the output SMSE of blind equalization, realizes the adaptive of modulation system based on maximum system throughput criterion
Selection does not need the underwater acoustic channel status information estimation in conventional method.Furthermore, it is also proposed that a kind of change tap length is blind
Weigh detection algorithm, for improving the bit error rate performance of system, further improves the figureofmerit of handling up of system.Simulation results show
Based on SMS E realizes Adaptive Modulation and becomes the validity of tap length blind equalization detection algorithm.Simulation result is also demonstrated and is mentioned
Adaptive Modulation algorithm can obtain with throughput of system performance similar in conventional method, but suggest plans more suitable for the practical underwater sound
The realization of communication system.
Claims (2)
1. a kind of underwater sound communication Adaptive Modulation algorithm based on Steady State Square Error, it is characterised in that transmitting terminal sends letter first
Number to be established the link with receiving end, handles signal is received, obtain mean square error SMSE, and be converted to SNR；It is then anti-
Transmitting terminal of feeding is modulated the adaptively selected of mode, wherein the received signal vector entered in blind equalizer is expressed as down
Formula:
uf(n)=[r (n) ..., r (n+L-1)] (10)
Output of the signal vector after blind equalization are as follows:
Wherein, tap weights vector and tap coefficient update are respectively as follows:
wf(n)=and [c (0), c (1) ..., c (L-1) ,]T (12)
Wherein error signal are as follows:
E (n)=efR(n)+jefI(n) (14)
Wherein, the real part e of error signalfR(n) with imaginary part efI(n) specific formula for calculation is as follows:
Blind equalization uses multi-modulus algorithm (Multi-Modulus Algorithm, MMA), wherein constant mould R2Real part R2RWith void
Portion R2IIt respectively indicates as follows:
SMSE is calculated by the output error signal e (n) of blind equalization, can be obtained by following formula:
SNR can be calculated by following formula:
Then correct the SNR that estimates using data fitting algorithms on the basis of formula (20) result, so as to preferably into
The selection of row modulation system, the specific steps are as follows:
Step (1) uses polynomial curve fitting method, for two groups of given data: practical SNR and estimation SNR is used respectively
γs=[γs,1,γs,2,...,γs,m] and γg=[γg,1,γg,2,...,γg,m] indicate, it is secondary multinomial to construct a n (n≤m)
Formula is expressed as follows:
In order to make the signal-to-noise ratio estimated closer to practical signal-to-noise ratio, the data error quadratic sum in same position is enabled to reach most
Small value, is shown below:
Therefore, problem, which is converted into, seeks I (a0,a1,...,an) minimum problem.It is following to indicate:
I.e.
It may be expressed as: with matrix form
By mathematical knowledge it is found that formula (25) only has unique solution, and the unique solution is polynomial of degree n pn(γg) coefficient A=
[a0,a1,...,an], and coefficient array A can be acquired by the pivot elimination approach solving equations (25) in mathematics.Step (2) is by step
Suddenly (1) acquires multinomial coefficient A=[a0,a1,...,an] after to get arrived practical SNR and estimate SNR fitting of a polynomial close
System, then substituted into the polynomial relation formula solvedAfter obtaining curve matching,
The relational expression of improved SMSE and SNR is as follows:
Wherein, S=[SMSE1,SMSE2,...,SMSEn] (i=1,2 ..., n), and (0 < SMSEi≤1)。
Adaptive Modulation algorithm is realized after data are fitted to obtain the relationship of SMSE and SNR, then with maximize handling capacity criterion.
2. a kind of underwater sound communication Adaptive Modulation algorithm based on Steady State Square Error according to claim 1, feature
It is to propose the change tap length Adaptive Modulation of based on SMS E, receives end structure at this time and use piecewise linearity filter knot
Structure, blind equalizer is by comparing the accumulative mean square error (Accumulated Squared Error, ASE) under different length, more
The length of new tap coefficient vector feeds back to transmitting terminal for being modulated the adaptively selected estimation SNR of mode, is also based on
The output SMSE for becoming tap length blind equalization is obtained；
Wherein enable l be expressed as being segmented the tap length of FIR filter used in current algorithm, the tap weights of blind equalizer to
Amount is wv(n)=and [c (0), c (1) ..., c (l-1) ,]T, with u (n)=[r (0) ..., r (l-1)] representation signal vector, then under
The w (n+1) at one moment is provided according to stochastic gradient descent method principle, is shown below:
ASE for carrying out tap length adjustment can be obtained by following formula:
Wherein l indicates the number of segment that current tap vector includes, and every section of length is p, and β≤1 is the forgetting factor in algorithm, evl
(n) for when the error of leading portion；
evl(n)=yvl,R(n)(|yvl,R(n)|2-R2R)+jyvl,I(n)(|yvl,I(n)|2-R2I) (30)
The wherein constant mould R in blind equalizer2Calculating see formula (17) and (18)；
By shown in formula (29), it can be deduced that l sectionsL-1 sections can similarly be obtained
IfThen show that the performance of blind equalization can be improved by increasing tap length.In iteration next time
In, algorithm will increase the tap length of blind equalization, since filter tap weight vector w (n) is only nonzero value in blind equalization
Centre cap initialization, algorithm can just converge to the minimum of cost function desired value, that is, be initialized as w (0)=[0 ..., 0,
1,0,...,0]；In order to guarantee that centre tapped weight specific gravity is maximum, in the algorithm for increasing p section taps updates, weigh tap to
Measure wv(n) it extends, is shown below to both sides:
Correspondingly, signal vector uv(n) are as follows:
uv(n)=[r (n) ..., r (n+l+p-1)] (32)
IfThen show that the performance of blind equalization can be reduced by increasing tap length, in iteration next time
In, algorithm will reduce the tap length of blind equalization, tap weights vector wv(n) and signal vector uv(n) it respectively indicates as follows:
uv(n)=[r (n) ..., r (n+l-p-1)] (34)
Become in tap blind equalization algorithm and participates in the parameter alpha that tap updatesupAnd αdownFollowing relationship should be met:
Wherein, αupAnd αdownNumerical value it is closer, tap length variation it is more frequent；It is obtained using change tap length blind equalization
SMSE, can obtain the SNR of modified estimation after over-fitting, it is fed back to transmitting terminal, quasi- based on maximum system throughput
Then realize the adaptive adjustment of modulation system.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110430151A (en) * | 2019-07-06 | 2019-11-08 | 哈尔滨工业大学（威海） | The blind decision-feedback frequency domain equalization algorithm of change tap length towards underwater sound communication |
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| CN115514425A (en) * | 2022-11-15 | 2022-12-23 | 北京理工大学 | OFDM-based adaptive multi-system underwater acoustic communication method and device |
| CN115514425B (en) * | 2022-11-15 | 2023-03-14 | 北京理工大学 | OFDM-based adaptive multi-system underwater acoustic communication method and device |
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