CN104506262B - Based on the autocorrelative self adaptation DTMB frequency spectrum detecting method of PN sequences - Google Patents

Abstract

The invention discloses a kind of be based on the autocorrelative self adaptation DTMB frequency spectrum detecting method of PN sequences, comprise the following steps：DTMB frequency spectrums are obtained, and is carried out based on the autocorrelative thick judgement of pseudo noise sequence PN sequence to obtain the first decision statistics T_PNACWith the first decision threshold γ_PNAC；According to the first decision threshold γ_PNACFirst threshold value γ is set₁With the second threshold value γ₂, tentatively to judge state；After preliminary judgement state, further carry out accumulating autocorrelative thin judgement based on unequal interval PN sequences, to obtain decision statistics and decision threshold so as to judge the state of DTMB frequency spectrums.The detection method of the embodiment of the present invention, by arranging double threshold threshold value, realize adopting based on the autocorrelative thick judgement of pseudo noise sequence PN sequence and autocorrelative thin judgement is accumulated based on unequal interval PN sequences, effectively improve frequency spectrum detection performance, and computation complexity is reduced, the use requirement of user is met well.

Description

Based on the autocorrelative self adaptation DTMB frequency spectrum detecting method of PN sequences

Technical field

The present invention relates to digital information transmission technical field, more particularly to a kind of to be based on PN (Pseudo-noise Sequence, pseudo noise sequence) autocorrelative self adaptation DTMB of sequence (Digital Television Terrestrial Multimedia Broadcasting, T-DMB) frequency spectrum detecting method.

Background technology

Radio-frequency spectrum is limited extremely valuable resource, and its scarcity is that same time the same area can only have One communication system uses same section of frequency spectrum, other communication systems use this section of frequency spectrum, will otherwise bring serious doing Disturb.Communication spectrum trend in short supply, also allows people to think deeply now, is reducing frequency spectrum shared by existing communication system by technological progress While bandwidth, how to develop new frequency spectrum, be multiplexed existing frequency spectrum.

Primary spectrum all it is divided totally when, the analog digital conversion of terrestrial television produces the sky of radio and television " white frequency spectrum " Ideler frequency spectrum resource, then seem more precious.Radio and television " white frequency spectrum " mainly include be allocated do radio and television use, it is but real The radio frequency band that border is not used, and it is due to frequency range when analog transmissions platform is broken and idle due to protective rate requirement Frequency range.Wherein, DTMB is the relevant DTV and the standard of digital broadcasting of China's formulation, while and International Telecommunication Union DTTB international standard, which adopts time-domain synchronization OFDM (TDS-OFDM) modulation system.It is most Developed country has completed simulated television to the conversion of DTV, and China is also in simulated television to DTV The critical period of conversion, thus will discharge the substantial amounts of resource of frequency range.In addition, the white frequency spectrum of radio and television is located at VHF (Very High Frequency, very high frequency(VHF)) and UHF (Ultra High Frequency, superfrequency) frequency range, superior signal propagate with And indoor Penetration Signature, using the teaching of the invention it is possible to provide good large area is covered, with high practical value.

Orderly opening frequency spectrum access Land use systems are key of the effective using frequency spectrum resource, and cognitive radio tool There is learning capacity, with surrounding interactive information, perceive current time, the frequency spectrum service condition in space, limiting and reducing punching While prominent generation effectively, intelligently using idle frequency spectrum resource.Frequency spectrum perception is the important of cognitive radio with detection One of technology, perceives the presence of DTMB digital TV ground signal primary users in white frequency spectrum bands, causes to become efficient utilization white The important channel of frequency spectrum resource and technology.

In correlation technique, frequency spectrum sensing method mainly includes energy measuring method, matched filter detection and feature detection method Deng and being directed to the frequency spectrum perception technology of DTMB DTV frequency bands, the characteristics of mainly for digital television signal, using signal Existing information is estimated with parameter.At present, for DTMB signals frequency spectrum perception technology mainly for DTMB signals the characteristics of, Frequency spectrum perception performance is general or computation complexity is larger, it is impossible to meet the use requirement of user well.

The content of the invention

It is contemplated that at least solving one of technical problem in above-mentioned correlation technique to a certain extent.

For this purpose, it is an object of the invention to proposing a kind of based on the autocorrelative self adaptation DTMB frequency spectrum detection side of PN sequences Method, the detection method can improve frequency spectrum detection performance, and reduce computation complexity.

To reach above-mentioned purpose, the embodiment of the present invention proposes a kind of based on the autocorrelative self adaptation DTMB frequency spectrum of PN sequences Detection method, comprises the following steps：T-DMB DTMB frequency spectrums are obtained, and is carried out based on pseudo noise sequence PN sequence Autocorrelative thick judgement is arranged to obtain the first decision statistics T_PNACWith the first decision threshold γ_PNAC；According to first decision gate Limit γ_PNACFirst threshold value γ is set₁With the second threshold value γ₂, with according to the first decision statistics T_PNAC, it is described First threshold value γ₁With the second threshold value γ₂Tentatively judge the state of the DTMB frequency spectrums；And judge described preliminary After the state of DTMB frequency spectrums, the DTMB frequency spectrums are further carried out carefully to sentence based on the accumulation of unequal interval PN sequences is autocorrelative Certainly, the state of the DTMB frequency spectrums is judged to obtain decision statistics and decision threshold.

Propose according to embodiments of the present invention based on the autocorrelative self adaptation DTMB frequency spectrum detecting method of PN sequences, by setting Double threshold threshold value is put based on double threshold perception detection, so as to adopt based on pseudo noise sequence PN sequence certainly outside double threshold Related thick judgement, and autocorrelative thin judgement is accumulated using based on unequal interval PN sequences within double threshold, realize The detection of DTMB frequency spectrums, effectively improves frequency spectrum detection performance, and reduces computation complexity, and the use for meeting user well will Ask.

In addition, it is according to the above embodiment of the present invention based on the autocorrelative self adaptation DTMB frequency spectrum detecting method of PN sequences also There can be following additional technical characteristic：

Further, in one embodiment of the invention, it is described slightly to sentence based on pseudo noise sequence PN sequence is autocorrelative Certainly obtaining the first decision statistics T_PNACWith the first decision threshold γ_PNACSpecifically include：

For reception signal y (n) in fixed detecting period carries out related interval for signal frame length M_i, correlation length be frame Head length L_iAuto-correlation, i is different frame head long patterns, and common C autocorrelation result in the fixed detecting period Cumulative mean, the first statistic is：

Wherein, m is auto-correlation original position, and c is frame number, and n is frame in symbol sequence number；

Next described first decision statistics T_PNACFor：

And for specified false-alarm probability P_FA, the first decision threshold γ_PNACFor：

Wherein,For normalized noise power,For noise power.

Further, in one embodiment of the invention, the first decision threshold γ_PNACMore than first thresholding Threshold gamma₁, and the first decision threshold γ_PNACLess than the second threshold value γ₂, wherein, it is described according to described first Decision statistics T_PNAC, the first threshold value γ₁With the second threshold value γ₂Tentatively judge the DTMB frequency spectrums state tool Body includes：If the first decision statistics T_PNACLess than the first threshold value γ₁, then it is judged to frequency spectrum idle condition； If the first decision statistics T_PNACMore than the second threshold value γ₂, then it is judged to spectrum occupancy state, otherwise sentences It is set to nondeterministic statement, and determines whether.

Further, in one embodiment of the invention, it is described that the DTMB frequency spectrums are further carried out being based on Interval PN sequences accumulate autocorrelative thin judgement, judge the DTMB frequency spectrums to obtain decision statistics and decision threshold State is specifically included：Judge the pattern of DTMB frame heads；

If the DTMB frame heads are stationary phase pattern, for reception signal y (n) in the fixed detecting period Related interval is carried out for d signal frame length dM_i, correlation length be frame head length L_iAuto-correlation, and it is described it is fixed perceive when Interior common C_dIndividual autocorrelation result cumulative mean, formula are as follows：

Wherein, m is auto-correlation original position, and c is frame number, and n is frame in symbol sequence number；

Constructing the second statistic is：

Wherein, altogether using the accumulation auto-correlation of D different interval, the second decision statistics are：

For specified false-alarm probability P_FA, the second decision threshold γ_DIPNACFor：

Wherein,For normalized noise power,For noise power, For normalization coefficient；

If the DTMB frame heads are rotatable phase pattern, for reception signal y (n) in the fixed detecting period Related interval is carried out for d signal frame length dM_i, correlation length be frame head length L_iAuto-correlation, and it is described it is fixed perceive when Interior common C_dIndividual autocorrelation result cumulative mean, formula are as follows：

Wherein, m is auto-correlation original position, and c is frame number, and n is frame in symbol sequence number；

Constructing the 3rd statistic is：

Wherein, the 3rd decision statistics are：

For specified false-alarm probability P_FA, the 3rd decision threshold is：

Wherein,For normalized noise power.

Further, in one embodiment of the invention, the first threshold value γ₁With the second threshold value γ₂ It is given to expect detection probability P_D0On the basis of carry out self-adaptative adjustment, wherein, γ₁=γ_PNAC/k,γ₂=k γ_PNAC, k is thresholding Regulation coefficient.

Further, in one embodiment of the invention, the self-adaptative adjustment is specifically included：Gating limits coefficient k_step To perceive adjusting step of the judgement to the thresholding regulation coefficient k each time, while arranging threshold coefficient k_stepMaximum k_max With minima k_min=1, when detect be judged to frequency spectrum idle condition when, increase threshold coefficient Δ₁；It is judged to frequency when detecting During spectrum seizure condition, reduce threshold coefficient Δ₂：

Decision threshold regulation coefficient k is made to be adjusted to actually detected probability and expect detection probability P_D0Reach dynamic equilibrium.

Further, in one embodiment of the invention, the fixed detecting period can be 50ms.

Further, in one embodiment of the invention, cumulative maximum auto-correlation interval D=20.

Further, in one embodiment of the invention, the threshold coefficient k_step=0.001, the threshold coefficient k_stepMaximum k_max=3, the threshold coefficient k_stepMinima k_min=1.

Further, in one embodiment of the invention, when expecting to detect primary user, the expectation detection is set Probability P_D0=0.98.

The additional aspect of the present invention and advantage will be set forth in part in the description, and partly will become from the following description Obtain substantially, or recognized by the practice of the present invention.

Description of the drawings

The above-mentioned and/or additional aspect and advantage of the present invention will become from the description with reference to accompanying drawings below to embodiment It is substantially and easy to understand, wherein：

Fig. 1 is based on the autocorrelative self adaptation DTMB frequency spectrum detecting method of PN sequences according to one embodiment of the invention Flow chart；

Fig. 2 is based on the autocorrelative self adaptation DTMB frequency spectrum detection side of PN sequences according to a specific embodiment of the invention The flow chart of method；

Fig. 3 is bent with the detection performance under fixed threshold coefficient according to the adaptive threshold coefficient of one embodiment of the invention Line schematic diagram；And

Fig. 4 is the threshold coefficient self-adaptative adjustment and convergence curve schematic diagram according to one embodiment of the invention.

Specific embodiment

Embodiments of the invention are described below in detail, the example of the embodiment is shown in the drawings, wherein from start to finish Same or similar label represents same or similar element or the element with same or like function.Below with reference to attached The embodiment of figure description is exemplary, it is intended to for explaining the present invention, and be not considered as limiting the invention.

Additionally, term " first ", " second " are only used for describing purpose, and it is not intended that indicating or implying relative importance Or the implicit quantity for indicating indicated technical characteristic.Thus, define " first ", the feature of " second " can express or Implicitly include one or more this feature.In describing the invention, " multiple " are meant that two or more, Unless otherwise expressly limited specifically.

In the present invention, unless otherwise clearly defined and limited, term " installation ", " being connected ", " connection ", " fixation " etc. Term should be interpreted broadly, for example, it may be being fixedly connected, or being detachably connected, or be integrally connected；It can be machine Tool connects, or electrically connects；Can be joined directly together, it is also possible to be indirectly connected to by intermediary, can be two units Connection inside part.For the ordinary skill in the art, above-mentioned term can be understood at this as the case may be Concrete meaning in bright.

In the present invention, unless otherwise clearly defined and limited, fisrt feature second feature it " on " or D score The first and second feature directly contacts can be included, it is also possible to be not directly contact including the first and second features but by it Between other characterisation contact.And, fisrt feature second feature " on ", " top " and " above " it is special including first Levy directly over second feature and oblique upper, or fisrt feature level height is merely representative of higher than second feature.Fisrt feature exists Second feature " under ", " lower section " and " below ", or be merely representative of directly over second feature and oblique upper including fisrt feature Fisrt feature level height is less than second feature.

Describe with reference to the accompanying drawings propose according to embodiments of the present invention based on the autocorrelative self adaptation DTMB frequency of PN sequences Spectrum detection method.With reference to shown in Fig. 1, the detection method is comprised the following steps：

S101, obtains T-DMB DTMB frequency spectrums, and carries out based on pseudo noise sequence PN sequence auto-correlation Thick judgement obtaining the first decision statistics T_PNACWith the first decision threshold γ_PNAC。

Wherein, in one embodiment of the invention, it is with reference to shown in Fig. 2, autocorrelative based on pseudo noise sequence PN sequence It is thick to adjudicate to obtain the first decision statistics T_PNACWith the first decision threshold γ_PNACSpecifically include：

For reception signal y (n) in fixed detecting period carries out related interval for signal frame length M_i, correlation length be frame Head length L_iAuto-correlation, i is different frame head long patterns, and common C autocorrelation result in fixed detecting period is added up Averagely, the first statistic is：

Wherein, m is auto-correlation original position, and c is frame number, and n is frame in symbol sequence number,

Secondly decision statistics are the first decision statistics T_PNACFor：

And for specified false-alarm probability P_FA, decision threshold is the first decision threshold γ_PNACFor：

Wherein,For normalized noise power,For noise power.

Further, in one embodiment of the invention, fixed detecting period can be 50ms.

S102, according to the first decision threshold γ_PNACFirst threshold value γ is set₁With the second threshold value γ₂, with basis First decision statistics T_PNAC, the first threshold value γ₁With the second threshold value γ₂The preliminary state for judging DTMB frequency spectrums.

Wherein, in one embodiment of the invention, the first decision threshold γ_PNACMore than the first threshold value γ₁, and First decision threshold γ_PNACLess than the second threshold value γ₂, wherein, according to the first decision statistics T_PNAC, the first threshold value γ₁With the second threshold value γ₂Tentatively judge that DTMB frequency spectrum states are specifically included：If the first decision statistics T_PNACLess than One threshold value γ₁, then it is judged to frequency spectrum idle condition；If the first decision statistics T_PNACMore than the second threshold value γ₂, Then it is judged to spectrum occupancy state, is otherwise judged to nondeterministic statement, and determines whether.

Specifically, with reference to shown in Fig. 2, dual-threshold judgement：Double threshold γ is set₁≤γ_PNAC≤γ₂；If T_PNAC<γ₁Then Directly judge that frequency spectrum is idle, that is, judge that CTMB primary users are present；If T_PNAC>γ₂Then directly judge that frequency spectrum takes, that is, judge DTMB primary users are not present；If γ₁≤T_PNAC≤γ₂Uncertain region is then considered at, and step S103 will be then carried out based on not PN sequences accumulate autocorrelative further accurate detection at equal intervals.

S103, after the state for tentatively judging DTMB frequency spectrums, is further carried out based on unequal interval PN to DTMB frequency spectrums Sequence accumulates autocorrelative thin judgement, to obtain decision statistics and decision threshold so as to judge the state of DTMB frequency spectrums.

Wherein, in one embodiment of the invention, DTMB frequency spectrums are further carried out tired based on unequal interval PN sequences The autocorrelative thin judgement of product, to obtain decision statistics and decision threshold so as to the state for judging DTMB frequency spectrums is specifically included：

Judge the pattern of DTMB frame heads.

If DTMB frame heads are stationary phase pattern, for reception signal y (n) in fixed detecting period carries out correlation At intervals of d signal frame length dM_i, correlation length be frame head length L_iAuto-correlation, and common C in fixed detecting period_dIt is individual from Correlated results cumulative mean, formula are as follows：

Wherein, m is auto-correlation original position, and c is frame number, and n is frame in symbol sequence number,

Construction statistic is that the second statistic is：

Wherein, altogether using the accumulation auto-correlation of D different interval, decision statistics are that the second decision statistics are：

For specified false-alarm probability P_FA, decision threshold is the second decision threshold γ_DIPNACFor：

Wherein,For normalized noise power,For noise power, For normalization coefficient.

If DTMB frame heads are rotatable phase pattern, for reception signal y (n) in fixed detecting period carries out correlation At intervals of d signal frame length dM_i, correlation length be frame head length L_iAuto-correlation, and common C in fixed detecting period_dIt is individual from Correlated results cumulative mean, formula are as follows：

Wherein, m is auto-correlation original position, and c is frame number, and n is frame in symbol sequence number,

Construction statistic is that the 3rd statistic is：

Wherein, decision statistics are that the 3rd decision statistics are：

For specified false-alarm probability P_FA, decision threshold is that the 3rd decision threshold is：

Wherein,For normalized noise power,For noise power, For normalization coefficient.

Further, in one embodiment of the invention, cumulative maximum auto-correlation interval D=20.

In an embodiment of the present invention, based on the embodiment of the present invention perceives detection by double threshold, adopt outside double threshold With based on the autocorrelative algorithm of PN sequences, judge whether frequency spectrum is empty by the PN sequences autocorrelation peak of adjacent DTMB signals frame head In the spare time, autocorrelative algorithm is accumulated using unequal interval PN sequences within double threshold, by the DTMB signal frames of different interval certainly Related cumulative mean obtains more accurate statistics.

Further, in one embodiment of the invention, with reference to shown in Fig. 2, the first threshold value γ¹With the second thresholding Threshold gamma₂Detection probability P is expected given_D0On the basis of carry out self-adaptative adjustment, wherein, γ₁=γ_PNAC/k,γ₂=k γ_PNAC, k is thresholding regulation coefficient.Say, the embodiment of the present invention is adaptively adjusted judgement according to channel circumstance and court verdict Thresholding [γ₁,γ₂]。

Specifically, in one embodiment of the invention, adapt to adjustment to specifically include：

Gating limits coefficient k_stepTo perceive adjusting step of the judgement to thresholding regulation coefficient k each time, while arranging thresholding Coefficient k_stepMaximum k_maxWith minima k_min=1, when detect be judged to frequency spectrum idle condition when, increase threshold coefficient Δ₁；When detect be judged to spectrum occupancy state when, reduce threshold coefficient Δ₂：

Decision threshold regulation coefficient k is made to be adjusted to actually detected probability and expect detection probability P_D0Reach dynamic equilibrium.

Wherein, in one embodiment of the invention, threshold coefficient k_step=0.001, threshold coefficient k_stepMaximum k_max=3, threshold coefficient k_stepMinima k_min=1.

Further, in one embodiment of the invention, when expecting to detect primary user, the expectation detection is set Probability P_D0=0.98.In short, if it is desire to detect primary user, arranging P_D0≈ 1, then Δ₁It is very big, when adjudicating frequency spectrum and being idle K value will be increased with larger step-length rapidly, and when frequency spectrum occupancy is adjudicated, k value will be reduced with less step-length.If it is desire to detection Less than primary user, P is set_D0Otherwise ≈ 0 is then.As described above, being restrained by decision threshold coefficient k rapidly, realize actually detected general Rate reaches dynamic equilibrium with expectation detection probability.The embodiment of the present invention can be under default expectation verification and measurement ratio, and self adaptation is perceived With regulation decision threshold, the perceptual performance of single node is effectively improved.

The embodiment of the present invention is according to channel situation and judgement situation real-time adjustment decision threshold；When channel condition is poor, letter Make an uproar than it is relatively low when, the algorithm for adopting computation complexity higher to ensure to detect degree of accuracy, when channel condition preferably, signal to noise ratio it is higher When, the less algorithm of complexity is adopted in the case where detection degree of accuracy is ensured；Carrier frequency is deviateed, multi-path jamming has stronger Resistivity.Specifically, the effect of the embodiment of the present invention can be further illustrated by following emulation.

Simulated conditions are as follows：DTMB signals are produced by random signal source, and the frame head mode of DTMB is PN595, detecting period For 52ms (90 DTMB signal frames of correspondence), false-alarm probability is set to P_FA=0.01, simulation times are 5000 times.D=20 is used Individual accumulation autocorrelation result is obtaining detection statistic.

Emulation 1

Under the carrier wave frequency deviation and GD8 multipath channels of 20ppm, when false alarm rate is set as 0.01, it is less than false dismissal probability Signal to noise ratio required for 0.01 is -21.7dB.

Emulation 2

When being respectively 1.0,1.2,1.5,2.0,2.5 to fixed threshold coefficient k, and proposed using the embodiment of the present invention Adaptive threshold coefficient k carries out missing inspection performance simulation.Now, it is k to arrange threshold coefficient k adjusting steps_step=0.001, it is maximum Value is k with minima_max=3, k_min=1, expect that detection probability is P_D0=0.98.Shown in simulation result reference Fig. 3, different Under signal to noise ratio, self adaptation is adjusted by threshold coefficient k, it is ensured that while reaching and expecting detection probability adopt multiple as much as possible It is miscellaneous to spend less algorithm.

Emulation 3

Initial k=1.2 is set, the convergence situation of threshold coefficient k in SNR=-20dB, is emulated.With reference to shown in Fig. 4, After 50-100 detection judgement, threshold coefficient will be compared with rapid convergence.

Propose according to embodiments of the present invention based on the autocorrelative self adaptation DTMB frequency spectrum detecting method of PN sequences, by with Based on double threshold perceives detection, using based on the autocorrelative algorithm of PN sequences outside double threshold, by adjacent DTMB signals The PN sequences autocorrelation peak of frame head judges whether frequency spectrum is idle, is accumulated from phase using unequal interval PN sequences within double threshold The algorithm of pass, obtains more accurate statistics by the DTMB signal frame auto-correlations cumulative mean of different interval, and can basis Channel status is adaptively adjusted the value of double threshold, the demand of balanced algorithm complexity, perceptual performance and channel circumstance, and DTMB frequency spectrum perceptions can be applied to, under difficult channel conditions can self adaptation and rapidly adjusting parameter, effectively improve frequency Spectrum detection performance, reduction algorithm complex, so as to realize the detection of DTMB frequency spectrums, effectively improve frequency spectrum detection performance, and drop Low computation complexity, meets the use requirement of user well.

In flow chart or here any process described otherwise above or method description are construed as, expression includes It is one or more for realizing specific logical function or process the step of the module of code of executable instruction, fragment or portion Point, and the scope of the preferred embodiment of the present invention includes other realization, wherein the suitable of shown or discussion can not be pressed Sequence, including according to involved function by it is basic simultaneously in the way of or in the opposite order, carry out perform function, this should be of the invention Embodiment person of ordinary skill in the field understood.

Expression or here logic described otherwise above and/or step, for example, are considered use in flow charts In the order list of the executable instruction for realizing logic function, may be embodied in any computer-readable medium, for Instruction execution system, device or equipment (as computer based system, the system including processor or other can hold from instruction The system of row system, device or equipment instruction fetch execute instruction) use, or with reference to these instruction execution systems, device or set It is standby and use.For the purpose of this specification, " computer-readable medium " can any can be included, store, communicate, propagate or pass The dress that defeated program is used for instruction execution system, device or equipment or with reference to these instruction execution systems, device or equipment Put.The more specifically example (non-exhaustive list) of computer-readable medium is including following：With the electricity that one or more connect up Connecting portion (electronic installation), portable computer diskette box (magnetic device), random access memory (RAM), read only memory (ROM), erasable edit read-only storage (EPROM or flash memory), fiber device, and portable optic disk is read-only deposits Reservoir (CDROM).In addition, computer-readable medium can even is that the paper that can print described program thereon or other are suitable Medium, because for example by carrying out optical scanning to paper or other media edlin, interpretation can then be entered or if necessary with which His suitable method is processed to electronically obtain described program, is then stored in computer storage.

It should be appreciated that each several part of the present invention can be realized with hardware, software, firmware or combinations thereof.Above-mentioned In embodiment, the software that multiple steps or method can be performed in memory and by suitable instruction execution system with storage Or firmware is realizing.For example, if realized with hardware, and in another embodiment, can be with well known in the art Any one of row technology or their combination are realizing：With for the logic gates of logic function is realized to data signal Discrete logic, the special IC with suitable combinational logic gate circuit, programmable gate array (PGA), scene Programmable gate array (FPGA) etc..

Those skilled in the art are appreciated that to realize all or part of step that above-described embodiment method is carried Suddenly the hardware that can be by program to instruct correlation is completed, and described program can be stored in a kind of computer-readable storage medium In matter, the program upon execution, including one or a combination set of the step of embodiment of the method.

Additionally, each functional unit in each embodiment of the invention can be integrated in a processing module, it is also possible to It is that unit is individually physically present, it is also possible to which two or more units are integrated in a module.Above-mentioned integrated mould Block both can be realized in the form of hardware, it would however also be possible to employ the form of software function module is realized.The integrated module is such as Fruit using in the form of software function module realize and as independent production marketing or use when, it is also possible to be stored in a computer In read/write memory medium.

Storage medium mentioned above can be read only memory, disk or CD etc..

In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show Example ", or the description of " some examples " etc. mean specific features with reference to the embodiment or example description, structure, material or spy Point is contained at least one embodiment or example of the present invention.In this manual, to the schematic representation of above-mentioned term not Identical embodiment or example are referred to necessarily.And, the specific features of description, structure, material or feature can be any One or more embodiments or example in combine in an appropriate manner.

Although embodiments of the invention have been shown and described above, it is to be understood that above-described embodiment is example Property, it is impossible to limitation of the present invention is interpreted as, one of ordinary skill in the art is in the principle and objective without departing from the present invention In the case of above-described embodiment can be changed within the scope of the invention, change, replace and modification.

Claims (8)

1. it is a kind of to be based on the autocorrelative self adaptation DTMB frequency spectrum detecting method of PN sequences, it is characterised in that to comprise the following steps：

Obtain T-DMB DTMB frequency spectrums, and carry out based on pseudo noise sequence PN sequence it is autocorrelative it is thick judgement with Obtain the first decision statistics T_PNACWith the first decision threshold γ_PNAC, wherein, it is described based on pseudo noise sequence PN sequence auto-correlation Thick judgement obtaining the first decision statistics T_PNACWith the first decision threshold γ_PNACSpecifically include：

For reception signal y (n) in fixed detecting period carries out related interval for signal frame length M_i, correlation length be frame head it is long Degree L_iAuto-correlation, i is different frame head long patterns, and common C autocorrelation result in the fixed detecting period is added up Averagely, the first statistic is：

$t_{PNAC}\left(m\right)=\frac{1}{{\mathrm{CL}}_i}\underset{c=0}{\overset{C-1}{\&Sigma;}}\underset{n=0}{\overset{L_{i-1}}{\&Sigma;}}y(m+n+{\mathrm{cM}}_i)\&CenterDot;y^{*}(m+n+(c+1\left)M_i\right),$

Wherein, m is auto-correlation original position, and c is frame number, and n is frame in symbol sequence number；

Next described first decision statistics T_PNACFor：

$T_{PNAC}=\underset{0\&le;m\&le;M_i}{max}\left|t_{PNAC}\left(m\right)\right|,$

And for specified false-alarm probability P_FA, the first decision threshold γ_PNACFor：

${\mathrm{\&gamma;}}_{PNAC}={\left({\mathrm{\&sigma;}}_0^{2}ln\frac{1}{1-{(1-P_{FA})}^{1/M_i}}\right)}^{1/2},$

Wherein,For normalized noise power,For noise power；

According to the first decision threshold γ_PNACFirst threshold value γ is set₁With the second threshold value γ₂, with according to described One decision statistics T_PNAC, the first threshold value γ₁With the second threshold value γ₂Tentatively judge the shape of the DTMB frequency spectrums State；And

After the state for tentatively judging the DTMB frequency spectrums, the DTMB frequency spectrums are further carried out based on unequal interval PN sequences The autocorrelative thin judgement of row accumulation, judges the state of the DTMB frequency spectrums to obtain decision statistics and decision threshold, its In, it is described that the DTMB frequency spectrums are further carried out to accumulate autocorrelative thin judgement based on unequal interval PN sequences, sentenced with obtaining Certainly statistic and decision threshold are specifically included so as to the state for judging the DTMB frequency spectrums：

Judge the pattern of DTMB frame heads；

If the DTMB frame heads are stationary phase pattern, for reception signal y (n) in the fixed detecting period is carried out Related interval is d signal frame length dM_i, correlation length be frame head length L_iAuto-correlation, and in the fixed detecting period Common C_dIndividual autocorrelation result cumulative mean, formula are as follows：

$A\left(m,d\right)=\frac{1}{C_d{L}_i}\underset{c=0}{\overset{C_d-1}{\mathrm{\&Sigma;}}}\underset{n=0}{\overset{L_{i-1}}{\mathrm{\&Sigma;}}}y\left(m+n+{\mathrm{cM}}_i\right)\&CenterDot;y^{*}\left(m+n+\left(c+d\right)M_i\right),$

Wherein, m is auto-correlation original position, and c is frame number, and n is frame in symbol sequence number；

Constructing the second statistic is：

$t_{DIPNAC}\left(m\right)=\underset{d=1}{\overset{D}{\mathrm{\&Sigma;}}}{C}_d{C}_{d+1}A\left(m,d\right)A^{*}\left(m,d+1\right),$

Wherein, altogether using the accumulation auto-correlation of D different interval, the second decision statistics are：

$T_{DIPNAC}=\underset{0\&le;m\&le;M_i}{max}\left|t_{DIPNAC}\left(m\right)\right|,$

For specified false-alarm probability P_FA, the second decision threshold γ_DIPNACFor：

${\mathrm{\&gamma;}}_{DIPNAC}={\left({\mathrm{\&sigma;}}_0^{2}ln\frac{1}{1-{(1-P_{FA})}^{1/M_i}}\right)}^{1/2},$

Wherein,For normalized noise power,For noise power,To return One changes coefficient；

If the DTMB frame heads are rotatable phase pattern, for reception signal y (n) in the fixed detecting period is carried out Related interval is d signal frame length dM_i, correlation length be frame head length L_iAuto-correlation, and in the fixed detecting period Common C_dIndividual autocorrelation result cumulative mean, formula are as follows：

$A_r\left(m,d\right)=\frac{1}{C_d{L}_i}\underset{c=0}{\overset{C_d-1}{\mathrm{\&Sigma;}}}\underset{n=0}{\overset{L_{i-1}}{\mathrm{\&Sigma;}}}\underset{a=0}{\overset{1}{\mathrm{\&Sigma;}}}y\left(m+n+{\mathrm{cM}}_i\right)\&CenterDot;y^{*}\left(m+n+{\left(-1\right)}^a\left(c+d\right)M_i\right),$

Wherein, m is auto-correlation original position, and c is frame number, and n is frame in symbol sequence number；

Constructing the 3rd statistic is：

$t_{r,DIPNAC}\left(m\right)=\underset{d=1}{\overset{D}{\mathrm{\&Sigma;}}}{C}_d{C}_{d+1}{A}_r\left(m,d\right)A_r^{*}\left(m,d+1\right),$

Wherein, the 3rd decision statistics are：

$T_{DIPNAC}=\underset{0\&le;m\&le;M_i}{max}\left|t_{r,DIPNAC}\left(m\right)\right|,$

For specified false-alarm probability P_FA, the 3rd decision threshold is：

${\mathrm{\&gamma;}}_{r,DIPNAC}={\left({\mathrm{\&sigma;}}_{0,r}^2\ln \frac{1}{1-{\left(1-P_{FA}\right)}^{1/M_i}}\right)}^{1/2},$

Wherein,For normalized noise power.

2. the method for claim 1, it is characterised in that the first decision threshold γ_PNACMore than the first thresholding threshold Value γ₁, and the first decision threshold γ_PNACLess than the second threshold value γ₂, wherein, it is described to sentence according to described first Certainly statistic T_PNAC, the first threshold value γ₁With the second threshold value γ₂Tentatively judge that the DTMB frequency spectrums state is concrete Including：

If the first decision statistics T_PNACLess than the first threshold value γ₁, then it is judged to frequency spectrum idle condition；

If the first decision statistics T_PNACMore than the second threshold value γ₂, then it is judged to spectrum occupancy state, it is no Then it is judged to nondeterministic statement, and determines whether.

3. method as claimed in claim 2, it is characterised in that the first threshold value γ₁With the second threshold value γ₂ It is given to expect detection probability P_D0On the basis of carry out self-adaptative adjustment, wherein, γ₁=γ_PNAC/k,γ₂=k γ_PNAC, k is thresholding Regulation coefficient.

4. method as claimed in claim 3, it is characterised in that the self-adaptative adjustment is specifically included：

Gating limits coefficient k_stepTo perceive adjusting step of the judgement to the thresholding regulation coefficient k each time, while arranging thresholding system Number k_stepMaximum k_maxWith minima k_min=1, when detect be judged to frequency spectrum idle condition when, increase threshold coefficient Δ₁； When detect be judged to spectrum occupancy state when, reduce threshold coefficient Δ₂：

Δ₂=k_step,

Decision threshold regulation coefficient k is made to be adjusted to actually detected probability and expect detection probability P_D0Reach dynamic equilibrium.

5. the method for claim 1, it is characterised in that the fixed detecting period is 50ms.

6. the method for claim 1, it is characterised in that cumulative maximum auto-correlation interval D=20.

7. method as claimed in claim 4, it is characterised in that the threshold coefficient k_step=0.001, the threshold coefficient k_stepMaximum k_max=3, the threshold coefficient k_stepMinima k_min=1.

8. method as claimed in claim 4, it is characterised in that when expecting to detect primary user, arranges and described expects detection Probability P_D0=0.98.