CN109600330A - A kind of diagonal cross-correlation carrier frequency bias estimation of simplification - Google Patents
A kind of diagonal cross-correlation carrier frequency bias estimation of simplification Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L27/00—Modulated-carrier systems
- H04L27/0014—Carrier regulation
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/18—Phase-modulated carrier systems, i.e. using phase-shift keying
- H04L27/20—Modulator circuits; Transmitter circuits
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/0014—Carrier regulation
- H04L2027/0024—Carrier regulation at the receiver end
- H04L2027/0026—Correction of carrier offset
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Abstract
The invention discloses a kind of diagonal cross-correlation Algorithm of Carrier Frequency Offset Estimation of simplification, comprising: S1: setting class PSAM frame structure；S2: baseband receiving signals Z is obtained；S3: it is based on baseband receiving signals Z, by going modulation operations to obtain modulated signal Z 'm；S4: using removing modulated signal Z 'm, cross-correlation operator R is obtained by time domain cross correlation algorithmCC；S5: cross-correlation operator R is utilizedCC, diagonal cross-correlation operator R is obtained by auto-correlation algorithmDCC；S6: diagonal cross-correlation operator R is utilizedDCC, by taking argument to operate to obtain diagonal cross-correlation offset estimationS7: diagonal cross-correlation offset estimation is utilizedDiagonal cross-correlation offset estimation is simplified by using complex signal indexation approximationS8: sub using diagonal cross-correlation offset estimation is simplifiedPass through diagonal cross-correlation offset estimation of the simplification for obtaining bilevel Linear programming in conjunction with Used for Unwrapping Phase Ambiguity algorithmNot only overall complexity is low for this method, and can take into account biggish estimation range and higher estimated accuracy.
Description
Technical field
The present invention relates to wireless communication technology field, the diagonal cross-correlation carrier frequency of more particularly to a kind of simplification
Folk prescription method.
Background technique
Short burst communication system is widely used in the fields such as high-speed mobile communications, satellite communication, military communication, communicating pair
The Doppler effect that relative movement generates makes reception signal produce certain frequency deviation.Biggish frequency deviation will lead to synchrodyne
Error performance sharply deteriorate, to cause the degradation of communication quality.
Traditional frequency offset estimation technique is according to whether can be divided into data auxiliary type DA, unbound nucleus type using pilot tone
NDA and decision-directed DD type etc..Relative to DA estimator, the signal-noise ratio threshold of NDA and DD estimator is all higher.Therefore, compared with
In the short burst communication of low signal-to-noise ratio, the DA estimator estimated by pilot frequency sequence frequency deviation and skew is generallyd use.It leads
Frequency sequence can divide the different location for being inserted into data frame and form different data frame structures.In second generation digital video broadcasting mark
Standard (DVB-S2) (ESTI EN 302.307, V1.2.1Digital Video Broadcasting；Second generation
Framing structure, channel coding and modulation systems for Broadcasting,
Interactive Service, News Gathering and otherbroadband satellite applications,
April 2009) in propose a kind of new data frame structure, main thought is that the pilot tone of certain length is divided into several pieces
Divide again and is inserted into data frame.H.Lo, D.Lee and J.A.Gansman are in " A study ofnon-uniform pilot
Spacing for PSAM " (Proceeding IEEE International Conference Communication,
PP322-325,2000) it is proposed in a kind of based on Pilot symbol assisted modulation (PSAM:Pilot Symbol Assisted
Modulation data frame structure).Pilot frequency sequence is divided into two parts by it, and a part contains several continuous pilot tone symbols
Number, it is placed on frame head, another part is subdivided into discrete frequency pilot sign, is inserted in frame and postamble.
For the specific algorithm of use, DA algorithm for estimating can also be further divided into frequency domain algorithm for estimating and time domain estimation
Algorithm.Under limited pilot-frequency expense, the former estimation range is larger, and the estimated accuracy of the latter is higher.Therefore, joint time-frequency
The advantage that DA algorithm for estimating can combine the two respective, but can bring complexity higher simultaneously and configure more difficult ask with optimized parameter
Topic.Therefore, the researchers of related fields propose some offset estimations with high-precision, wide scope and low complex degree and calculate
Method, these algorithms all directly or indirectly use the time domain related algorithm of low complex degree.M.Luise, R.Reggiannini exist
“Carrier frequency recovery in all-digital modems for burst-mode
It proposes and utilizes in transmissions " (IEEE Transaction Communication, PP1169-1178,1995)
Effect/single pilot blocks auto-correlation algorithm, signal-noise ratio threshold and complexity are lower, but estimated accuracy is not high.Sun Jinhua, king
Avenge Mei Deng " joint pilot and iterative decoding carrier synchronization of short burst transmission system " (Xian Electronics Science and Technology University's journal, 29-
36,41 (1), 2014) cross correlation algorithm using two or more non-intersecting pilot blocks is proposed in, in identical pilot length
It is significantly larger than the algorithm and moderate complexity that M.Luise and R.Reggiannini are proposed with its estimated accuracy under signal-to-noise ratio.So
And all there is identical defect in the time domain related algorithm based on multiple non-intersecting pilot blocks, i.e., frequency offset estimation range it is very narrow and with
Pilot symbol interval is inversely proportional.Tracing sth. to its source, there are phase ambiguities for the time domain related algorithm that is under this frame structure.Due to this
Phase increment in class algorithm estimation is mainly influenced by normalization frequency deviation, pilot interval and noise, therefore, biggish frequency deviation
Or pilot interval can all make it generate phase ambiguity.A.Barbieri, G.Colavolpe are in " On pilot-symbol-
assisted carrier synchronization for DVB-S2systems”(IEEE Transactions on
Broadcasting, PP685-692,53 (3), 2007) a kind of simplification M&M estimation based on DVB-S2 frame structure is proposed in calculate
Method solves phase fuzzy problem using the check bit that LDPC is decoded.J.Palmer, M.Rice are in " Low-Complexity
Frequency Estimation Using Multiple DisjointPilot Blocks in Burst-Mode
It is proposed in Communications " (IEEE Transaction Communication, PP3135-3145,59 (11), 2011)
Using kalman filter to estimation frequency deviation be iterated update non-coding method and solve phase ambiguity, in conjunction with from
Correlation estimation algorithm AC (Auto-Correlation) obtains biggish estimation range, but complexity is very high and does not provide phase
The specific steps of ambiguity solution algorithm.
In conclusion how to provide a kind of carrier wave frequency deviation that can effectively take into account estimation performance and complexity under big frequency deviation
Estimation method, to solve the problems, such as that using phase fuzzy problem existing under PSAM frame be those skilled in the art's urgent need to resolve.
Summary of the invention
In view of this, this method is not only whole the present invention provides a kind of diagonal cross-correlation carrier wave frequency deviation method of simplification
Complexity is low, and can take into account biggish estimation range and higher estimated accuracy.
To achieve the goals above, the present invention adopts the following technical scheme:
A kind of diagonal cross-correlation carrier frequency bias estimation of simplification, comprising:
Step S1: setting class PSAM frame structure；
Step S2: baseband receiving signals Z is obtained；
Step S3: modulated signal Z ' is obtained by going modulation operations based on baseband receiving signals Zm；
Step S4: using removing modulated signal Z 'm, by time domain cross correlation algorithm, obtain cross-correlation operator RCC；
Step S5: cross-correlation operator R is utilizedCC, by auto-correlation algorithm, obtain diagonal cross-correlation operator RDCC；
Step S6: diagonal cross-correlation operator R is utilizedDCC, by taking argument to operate, obtain diagonal cross-correlation offset estimation
Step S7: diagonal cross-correlation offset estimation is utilizedIt is approximate by using complex signal indexation, it is simplified
Diagonal cross-correlation offset estimation
Step S8: sub using diagonal cross-correlation offset estimation is simplifiedBy combining Used for Unwrapping Phase Ambiguity algorithm, solved
Diagonal cross-correlation offset estimation of the simplification of phase ambiguity
Preferably, step S1 is specifically included:
S11: generation data length is LPPilot blocks P, and be divided into m fritter Pm, it is L per small block length, then generate
Data length is D '=(m-1) × t binary data bits sequence D, wherein LP, L and m be positive integer, t is individual data
Block DmLength；
S12: m pilot blocks P is utilizedmWith m-1 data block Dm, by way of multiplexing, obtain class PSAM frame structure.
Preferably, step S2 is specifically included:
S21: it is based on class PSAM frame structure, modulates to obtain modulated signal S by quadrature phase shift keying；
S22: utilizing modulated signal S, by Gaussian white noise channel and affix frequency deviation f, obtains baseband receiving signals Z.
It can be seen via above technical scheme that compared with prior art, the present disclosure provides a kind of the diagonal of simplification
Cross-correlation carrier wave frequency deviation method, the method use autocorrelation estimation, the approximate principle of complex signal indexation and phase solution moulds
The thought of algorithm is pasted, not only overall complexity is low, but also can take into account biggish estimation range and higher estimated accuracy.This hair
The method of bright offer is not limited by specific modulation system, has general applicability.
Method provided by the invention be suitable for big frequency deviation short burst communication system, can also apply in coded system with
Adapt to the short burst communication environment under low signal-to-noise ratio.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The embodiment of invention for those of ordinary skill in the art without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
Fig. 1 is the flow chart of the diagonal cross-correlation carrier wave frequency deviation method of simplification provided by the invention；
Fig. 2 is class PSAM frame structure schematic diagram provided by the invention；
Fig. 3 is the present invention under different signal-to-noise ratio, with diagonal cross-correlation, simplifies diagonal cross-correlation and whole cross-correlation emulation
Offset estimation root-mean-square error curve graph；
Fig. 4 is that the present invention is on the lower side in different frequencies, with the diagonal cross-correlation of simplification of the diagonal cross-correlation of simplification and bilevel Linear programming
The offset estimation root-mean-square error curve graph of emulation；
Fig. 5 is on the lower side, the offset estimation root-mean-square error curve graph emulated with M&M, AC and the present invention in different frequencies.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Referring to attached drawing 1, the embodiment of the invention discloses a kind of diagonal cross-correlation carrier wave frequency deviation methods of simplification, comprising:
Step S1: setting class PSAM frame structure；
Step S2: baseband receiving signals Z is obtained；
Step S3: modulated signal Z ' is obtained by going modulation operations based on baseband receiving signals Zm；
Step S4: using removing modulated signal Z 'm, by time domain cross correlation algorithm, obtain cross-correlation operator RCC；
Step S5: cross-correlation operator R is utilizedCC, by auto-correlation algorithm, obtain diagonal cross-correlation operator RDCC；
Step S6: diagonal cross-correlation operator R is utilizedDCC, by taking argument to operate, obtain diagonal cross-correlation offset estimation
Step S7: diagonal cross-correlation offset estimation is utilizedIt is approximate by using complex signal indexation, it is simplified
Diagonal cross-correlation offset estimation
Step S8: sub using diagonal cross-correlation offset estimation is simplifiedBy combining Used for Unwrapping Phase Ambiguity algorithm, solved
Diagonal cross-correlation offset estimation of the simplification of phase ambiguity
Below with reference to specific steps, embodiment and simulation result, technical scheme is described further.
Step 1, data frame structure (class PSAM frame) is set, refers to attached drawing 2.
(1a) generates the pilot blocks P of certain data length, and is divided into m fritter Pm, it is L per small block length, then produce
Raw data length is D '=(m-1) × t binary data bits sequence D, and wherein L and m is positive integer, and t is individual data
Block DmLength；
(1b) utilizes m pilot blocks PmWith m-1 data block Dm, by way of multiplexing, obtain class PSAM frame structure.
Step 2, baseband receiving signals are obtained.
(2a) is modulated by quadrature phase shift keying (QPSK) using obtained class PSAM frame structure, obtains modulated signal S；
(2b) utilizes modulated signal S, by Gaussian white noise channel and affix frequency deviation f, obtains baseband receiving signals Z.
Step 3, the specific algorithm of diagonal cross-correlation operator is determined:
The baseband signal Z that (3a) will be received is sent to carrier estimation device, takes out the preceding L data of baseband signal Z, as
The first segment pilot tone P1 of baseband signal Z, take out the L+t+1 symbol of Z to the 2L+t+1 symbol data as Z second
Section pilot tone P2；
(3b) utilizes first segment pilot tone P1 and second segment pilot tone P2, respectively obtains first segment pilot tone and removes modulated signal P1d=
P1×(P1′)*Modulated signal P2 is removed with second segment pilot toned=P2 × (P2 ')*, wherein P1 ' and P2 ' is that receiving-transmitting sides are arranged in advance
Transmission signal first segment pilot tone and second segment pilot tone, (P1 ')*For the conjugation of P1 ', (P2 ')*For the conjugation of P2 '；
(3c) removes modulated signal P1 using first segment pilot tonedModulated signal P2 is removed with second segment pilot toned, mutual by time domain
Algorithm is closed, cross-correlation operator R is obtainedCC:
Wherein D is the interval of first segment pilot tone and second segment pilot tone, i.e. D=L
+t；
(3d1) utilizes cross-correlation operator RCC, by taking argument to operate, obtain cross-correlation operator offset estimation
Wherein TsFor symbol period and Ts=
1/(1×104) second, arg { } is to take argument operation；
Herein it should be noted that step (3d1) it is not necessary to, due to needing to use during contrast simulation
It is listed to this parameter, therefore herein.
(3d2) utilizes cross-correlation operator RCC, by auto-correlation algorithm, obtain diagonal cross-correlation operator RDCC:
(3e) utilizes diagonal cross-correlation operator RDCC, by taking argument to operate, obtain diagonal cross-correlation offset estimation
Step 4, the specific algorithm for simplifying diagonal crosscorrelation estimation is determined:
(4a) is firstly, provide complex signal indexation approximation principle: as signal-to-noise ratio Es/N0When > > 1, modulation complex signal P1 is removedd
Amplitude be approximately 1, using plural number exponential form, obtain P1d=| P1d|exp(jarg(P1d))≈exp(jarg(P1d)),
Wherein | | it is modulo operation, exp () is to be derived from right index operation, and j is unit imaginary number；
Diagonal cross-correlation offset estimation that (4b) is obtained using step (3)Pass through the complex signal index of step (4a)
Change approximation operation, is simplified diagonal cross-correlation offset estimation
Wherein
Cross-correlation offset estimation that (4c) is obtained using step (3) and step (4b)Diagonal cross-correlation offset estimation
SonWith diagonal cross-correlation offset estimation of simplificationBy Monte Carlo simulation, the w times offset estimation value is respectively obtainedWith
(4d) repetition step (3)~(4b) is W times total, obtains W offset estimation value WithUsing these offset estimation values and added frequency deviation f,
Calculate normalization inherent spurious frequency deviation ECC、EDCCAnd ESDCC:
What needs to be explained here is that the purpose of Multi simulation running is to obtain the data point in analogous diagram, what is obtained in this way is
Assembly average, the bring error once in a while to avoid single estimation.
Pilot tone block number m=2 in the present embodiment, Pilot Symbol Length L=25, individual data symbol lengths t=250, lead
Symbol interval D=275.Additional frequency deviation f is 10Hz, symbol period Ts=1/ (1 × 104) second.By step (3)~(4d) into
Row emulation, each data point utilize Monte Carlo simulation W=5000 time, obtain Fig. 3, i.e., under different signal-to-noise ratio, with diagonal mutual
Close, simplify the offset estimation root-mean-square error curve of diagonal cross-correlation and cross correlation algorithm emulation.From figure 3, it can be seen that simplifying
The estimation performance of diagonal cross correlation algorithm is suitable with the estimation performance of diagonal cross correlation algorithm, and estimating close to cross correlation algorithm
Count performance.Therefore, bilevel Linear programming algorithm is applied to hereinafter and is simplified in diagonal cross correlation algorithm.
Step 5, the diagonal cross correlation algorithm of the simplification of Used for Unwrapping Phase Ambiguity is determined.
Firstly, providing Used for Unwrapping Phase Ambiguity algorithm principle:
(5a) utilizes the diagonal cross-correlation operator R of step (4b) resulting simplificationSDCC, by taking argument to operate, obtain phase
Increment Delta Φ: ΔΦ=arg { RSDCC}≈2πfTsD；
(5b) utilizes phase increment ΔΦ, by the single mapping relationship for taking argument to operate, obtains the value limitation of ΔΦ:
|ΔΦ|≈|2πfTsD | < π, wherein | | it is the operation that takes absolute value, | f | 1/ (2DT of <s)；
(5c) limits inequality using the value of ΔΦ, by introducing a parameter q, obtain ΔΦ under big frequency deviation ': |
ΔΦ′|≈|2πf′Ts± 2 π q of D | < π, wherein | f ' | 1/ (2T of <s)；
(5d) using the ΔΦ under big frequency deviation ', by going absolute value operation, obtain the offset estimation value of Used for Unwrapping Phase Ambiguity
(5e) utilizes the offset estimation value of Used for Unwrapping Phase AmbiguityBy dichotomizing search, accurate parameter is obtainedSpecifically
Step includes:
Assuming that given pilot interval D, parameter q initial ranging step-lengthWith estimated accuracy ε.
(5e1) is utilizedThe offset estimation value obtained by step (5d)It obtains WhereinFor the initial value of q,For the first guess of frequency deviation f '；
(5e2) is utilizedBy comparingWith ε/TsSize, worked as
When,It takesOtherwise (5e3) is entered step；
(5e3) is utilizedThe offset estimation value obtained by step (5d)It obtains
(5e4) is utilizedBy comparingWith ε/TsSize, worked asWhen,It takesOtherwise, (5e5) is otherwise entered step；
(5e5) utilizes the l times searchThe offset estimation value obtained by step (5d)
It obtains Wherein l is positive integer；
(5e6) is utilizedBy comparingWith ε/TsSize, worked asWhen,It takesAt this timeOtherwise, l=l+1, return step (5e5) are enabled；
(5f) obtains the exact value of parameter q using step (5e1)-(5e6)Pass through the simplification pair with step (4b)
Angle cross-correlation offset estimationIt combines, obtains diagonal cross-correlation offset estimation of simplification of bilevel Linear programming Wherein
Up to the present, detailed explanation has been done to the detailed process of algorithm.Next, doing in conjunction with simulation result into one
Walk explanation.
(5g) utilizes diagonal cross-correlation offset estimation of simplification that step (4b), (5f) are obtainedWith bilevel Linear programming
Simplify diagonal cross-correlation offset estimationBy Monte Carlo simulation, the secondary offset estimation value of w ' is respectively obtained
With
(5h) repetition step (3)~(4b) and step (5e)~(5f) total W ' is secondary, obtains a offset estimation value of W 'WithUtilize these offset estimation values and added
Normalize the frequency deviation f that value is -0.5~0.5i, calculate normalization inherent spurious frequency deviation ESDCC,iAnd EPUW-SDCC,i:
Wherein, added frequency deviation fi∈[-0.5,0.5]/Ts。
Pilot tone block number m=2 in the present embodiment, Pilot Symbol Length L=25, individual data symbol lengths t=250, lead
Symbol interval D=275.Additional frequency deviation fi∈[-0.5,0.5]/Ts, symbol period Ts=1/ (1 × 104) second.By step
(3)~(4b) and step (5e)~(5f) are emulated, and each data point utilizes Monte Carlo simulation W '=5000 time, obtain figure
4, i.e., on the lower side in different frequencies, the offset estimation with the diagonal cross-correlation emulation of the simplification of the diagonal cross-correlation of simplification and bilevel Linear programming is equal
Square error curve.
From fig. 4, it can be seen that compared with the diagonal cross correlation algorithm of simplification, the diagonal cross correlation algorithm of the simplification of bilevel Linear programming
Normalization estimation frequency deviation close to 0.5, and under larger frequency deviation, it is estimated that performance still obtains and simplifies diagonal cross correlation algorithm and exist
Estimation effect in 1/ (2D)=1/550, is shown in partial enlarged view.
Step 6, the estimation effect of the diagonal cross correlation algorithm of the simplification of Used for Unwrapping Phase Ambiguity is compared.
Compared with existing classical carrier estimation algorithm carries out performance.Assume in this example that Eb/N0=8dB and fiTs∈[-
0.5,0.5], U.Mengali is selected, M.Moerlli. is in " Data-aided frequency estimation forburst
It is mentioned in digital transmission " (IEEE Transaction Communication, PP23-25,45 (1), 1997)
A kind of carrier estimation algorithm suitable for big frequency deviation out, i.e. M&M algorithm and J.Palmer, M.Rice is in " Low-
Complexity Frequency Estimation Using Multiple Disjoint Pilot Blocks in
Burst-Mode Communications " (IEEE Transaction Communication, PP3135-3145,59 (11),
2011) a kind of carrier estimation algorithm of the Used for Unwrapping Phase Ambiguity proposed in, i.e. AC algorithm.Each data point utilizes Monte Carlo simulation
5000 times, obtain Fig. 5, i.e., it is on the lower side in different frequencies, it is missed with the offset estimation root mean square that M&M algorithm, AC algorithm and the present invention emulate
Poor curve.From fig. 5, it can be seen that the present invention is identical as the estimation range of other two kinds of algorithms, but estimated accuracy highest.Illustrate this
The estimated value of invention is more acurrate, and then shows effectiveness of the invention.
Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.For device disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is said referring to method part
It is bright.
The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention.
Various modifications to these embodiments will be readily apparent to those skilled in the art, as defined herein
General Principle can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore, of the invention
It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one
The widest scope of cause.
Claims (3)
1. a kind of diagonal cross-correlation carrier frequency bias estimation of simplification characterized by comprising
Step S1: setting class PSAM frame structure；
Step S2: baseband receiving signals Z is obtained；
Step S3: modulated signal Z ' is obtained by going modulation operations based on baseband receiving signals Zm；
Step S4: using removing modulated signal Z 'm, by time domain cross correlation algorithm, obtain cross-correlation operator RCC；
Step S5: cross-correlation operator R is utilizedCC, by auto-correlation algorithm, obtain diagonal cross-correlation operator RDCC；
Step S6: diagonal cross-correlation operator R is utilizedDCC, by taking argument to operate, obtain diagonal cross-correlation offset estimation
Step S7: diagonal cross-correlation offset estimation is utilizedIt is approximate by using complex signal indexation, it is simplified diagonal
Cross-correlation offset estimation
Step S8: sub using diagonal cross-correlation offset estimation is simplifiedBy combining Used for Unwrapping Phase Ambiguity algorithm, solution phase is obtained
Diagonal cross-correlation offset estimation of fuzzy simplification
2. a kind of diagonal cross-correlation carrier frequency bias estimation of simplification according to claim 1, which is characterized in that step
S1 is specifically included:
S11: generation data length is LPPilot blocks P, and be divided into m fritter Pm, it is L per small block length, then generate data
Length is D '=(m-1) × t binary data bits sequence D, wherein LP, L and m be positive integer, t is individual data block Dm
Length；
S12: m pilot blocks P is utilizedmWith m-1 data block Dm, by way of multiplexing, obtain class PSAM frame structure.
3. a kind of diagonal cross-correlation carrier frequency bias estimation of simplification according to claim 2, which is characterized in that step
S2 is specifically included:
S21: it is based on class PSAM frame structure, modulates to obtain modulated signal S by quadrature phase shift keying；
S22: utilizing modulated signal S, by Gaussian white noise channel and affix frequency deviation f, obtains baseband receiving signals Z.
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| CN1472900A (en) * | 2002-08-01 | 2004-02-04 | 上海交通大学 | Method for estimating carrier, frequency shifts of orthogonal FDM communication system |
| CN101018225A (en) * | 2006-12-19 | 2007-08-15 | 北京创毅视讯科技有限公司 | OFDM symbol and frequency synchronization and channel style estimating method |
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