The method of determining the frequency and device for its implementation (options)

 

(57) Abstract:

The invention relates to the field of broadband mobile communications systems, in particular can be used in the direct channel standards UMTS and cdma2000, for adjusting the frequency of the reference oscillator required for coherent reception of messages, and can also be used when building satellite communication systems, where there may be large frequency shift. The technical result is the definition of frequency when a large a priori uncertainty ranges frequency [-FmaxFmax], achieving high detection accuracy frequency even at very low signal/noise reduction value-dimensional characteristics of the device. Determination of the frequency of successively after Q iterations, the gradual narrowing of the a priori uncertainty ranges of frequency to achieve the required accuracy assessment allows you to use at each iteration, a smaller number of parallel frequency channels of the signal relative to the prototype. The required accuracy of the determination of the frequency is achieved by using the reference signal function that allows you to recover information about the possible frequency value of the frequency interval for which the radios are formed on the basis of k corresponding estimates of correlation, that allows to obtain an estimate of the frequency with high accuracy even at very low signal-to-noise. 3 S. and 3 C.p. f-crystals, 5 Il.

The invention relates to the field of broadband mobile communications systems, in particular can be used in the direct channel standards UMTS and cdma2000, for adjusting the frequency of the reference oscillator required for coherent reception of messages, and can also be used when building satellite communication systems, where there may be large frequency shift.

During operation of the system broadband cellular communication possible misalignment between F carrier frequency of the received useful signal and the reference oscillator frequency of the mobile station. This misalignment (frequency shift) may be due to Doppler frequency offset (due to the movement of the mobile station) and the instability of the frequency of the reference generators mobile and base stations. The influence of the detuning frequency of the communication quality can deteriorate. Therefore, the problem of determination of the frequency (getting assessment) to further adjust the frequency mismatch F.

Correction of the frequency mismatch can be conducted with the correctly point frequency paths of the receiver. The choice of the structuring of the correction depends on the specific conditions of its implementation and is not considered part of this specification.

In any communication system after switching on there is a detuning frequency F, and the a priori uncertainty interval frequency relative to true values are known in advance and is [-FmaxFmax]. For communication systems, organized in accordance with the standards UMTS and cdma2000, Fmax is 11 kHz. In the operation of the device frequency required to reduce the a priori uncertainty interval and to determine the frequency with an accuracy of 150 Hz.

The most commonly used methods are the phase frequency. All of them implement the idea of detecting and filtering quasi-permanent phase change and use the estimates of the changes in phase to generate a signal assessment frequency. Discriminatory characteristics of the digital phase detector is periodic and has a sawtooth shape. The periodic nature of the discriminatory characteristics is the cause of the seizure for a false assessment of the frequency, if the counting time interval there will be a shift signal in phase is greater than n where n times always with the same phase; for symbols transmitted information n = 4.

The fundamental differences between all existing phase methods for determining the frequencies are in the implementation of the conversion of the constant phase shift in the measured parameter, uniquely associated with an existing frequency shift. As one evaluation phase under conditions of noise and fading signal is usually insufficient to determine the frequency producing the accumulation and averaging of the estimates. The duration of the averaging determines the accuracy of the generated estimates of the incidence and the inertia of the device frequency in General. The transformation function of the received signal evaluation phase in the evaluation of frequency usually represents the dependence of the measured parameter from the frequency and optimized in accordance with the requirement of a minimum of complexity.

One of the most simple ways to assess a constant phase shift complex photomanipulating signal is the selection of the phase shift between two successively adopted by the complex characters and their subsequent averaging [1. J. Spilker. "Digital satellite communications". Meters, Communication. 1978, pp. 387 - 404] . This operation can be implemented as the multiplication of complex OTS is authorized component. This approach is a special case of n-fold multiplication of the input signal followed by filtration n*ocomponent. Here n is the multiplicity manipulation carrier,othe carrier frequency.

In the time domain, the average frequency of the signal can be determined electron-counting frequency meter by counting the number of positive and negative transitions of the signal through the zero level per unit of time [2. C. S. Peruashev. "Radioavtomatika". M" Owls.radio, 1982]. However, this estimate of the average frequency (through kvazichastitsy) always turns out to be too high in relation to the average value. Improving the accuracy of estimation of the mean frequency is possible by applying the algorithm using fractional differentiation signal in the time domain, but in this case, the procedure increases the computational complexity of the method.

The known method and device for determining the frequency in the digital communication system as described [3. Patent US # 4,938,906 "Frequency Estimation system", Jan.8, 1991]. This method generates a frequency estimation using linear regression, analyzing the timing phase. Thus an optimal least-squares solution. Data the method and the device allow you to determine costituiscono has a limit on the maximum phase shift between the analyzed samples.

In these systems due to the spread spectrum signal using the modulation of the transmitted data of the orthogonal code sequences and coding scramblers code. In the modulation and coding complex symbols is converted into a sequence of encoded complex chips information. At the reception, after the transfer of the signal at zero frequency and digitized by the ADC, make decoding of superimposed codes and accumulation (summation) of the decoded chip for receiving the transmitted symbol. By decoding and summing the received chips is the correlation processing of the received signal. Signal-to-noise ratio for the received chips are very low, thus, obtaining reliable estimates of the phase of the signal is possible only after the correlation signal processing.

On the other hand, as noted above, for all digital phase methods of estimating the frequency of the limitation on the maximum phase shift between the readings /n, where n is the multiplicity of manipulation when receiving photomanipulating signal. At high frequency the phase shift for the received symbols of the useful signal will exceed the maximum let is either certain frequency [-FmaxFmax].

The known method and device for determination of frequency based on the frequency discriminator using a pair of adjacent frequency filters. The basic idea implemented in this case, consists of nding the center of gravity of the power spectrum of the signal [4. U. Lindsley "synchronization Systems in communication and control". The owls. radio, 1979; 5. Automatic frequency control using split-band signal strength measurements: U.S. Pat. USA N 5487186, MKI N 04 1/16 IN. Scarpa, Carl G. ; Hitachi America, Ltd. - N 368747, Appl. 4.1.95, publ. 23.1.96, NCI 455.192.2].

This solution allows to determine the frequency without decoding imposed extend sequences (i.e., without correlation signal processing). The received signal is divided between two adjacent frequency filters, which occupies half the bandwidth, and compares the signal levels in each of these bands. A differential signal is used for signal assessment frequency. [5. Automatic frequency control using split-band signal strength measurements: U.S. Pat. USA N 5487186, MKI N 04 1/16 IN. Scarpa, Carl G.; Hitachi America, Ltd. - N 368747: Appl. 4.1.95, publ. 23.1.96, NCI 455.192.2].

The disadvantage of this approach is the need to build two filters of high order and a large accumulation time to achieve dostatochnoe frequency is the method and the device, described in [6. C. I. Tikhonov "Optimal reception of signals. M, Radio and communications, 1983, page 199 Fig. 3.13, page 230 of Fig. 3.21]. This method is based on using multi-channel receiver, consisting of n parallel channels.

This method of frequency is as follows:

nominate m hypotheses about the value of frequency, which is divided a priori interval of frequencies [-FmaxFmax] on m frequency potentialof with a frequency band F each;

for each of the hypotheses Fi, corresponding to the middle frequency potentialof, where i takes values from 1 to m, compute the correlation of the signal at time T, forming the m estimates of the correlation;

identify the modules of the estimated correlation;

choose the hypothesis with the maximum value of the modulus of the correlation estimation and calculate the frequency estimation.

To implement the described method using the device shown in Fig. 1, which contains:

the reference signal generator 1 generator complex samples lo for all n channels;

m parallel frequency channels, each of which consists of series-connected:

multiplier 2 - complex multiplier adopted chips and integrated samples generators is rinyateh chips) and the node module definition 5 (to calculate the magnitude of a complex number);

the evaluation unit frequency 6 for a comparison of the estimates of correlation and generating a signal assessment frequency assessment unit frequency contains:

site selection a maximum of 7 to define a channel number with a maximum result of accumulation

site formation evaluation frequency 8 - for conversion of the unit 7 in the frequency estimation.

The device operates as follows.

After decoding, orthographic and scramblers code sequences chips received signal received at the n multiplier products 2, where each chip is multiplied by a complex reference oscillator reference signal eUNESCOFi - i-I hypothesis (Central frequency putinterval), t - time. Thus, the output of each multiplier products generated signal with a shift in frequency that is equal to (Fi - F).

In block formation evaluation 3 by means of the adder 4 is coherent accumulation of chips information at time T. Thus, m is formed estimates of the correlation corresponding to the hypotheses.

In node 5 determines the assessment module correlation, which is transmitted to the node select max 7. Node 7 is selected the maximum result of the accumulation, the number sootvetstvuyushiye hypothesis.

However, the use of parallel circuits is not possible due to the large cost and size of the device frequency required to achieve the required accuracy assessment.

The task, which directed the claimed group of inventions is:

determining the frequency with large a priori uncertainty ranges frequency [-FmaxFmax],

achieving high detection accuracy frequency even at very low signal-to-noise,

the decrease in value-dimensional characteristics of the device.

To solve this problem is proposed a method of determining frequency and two versions of the device for its realization.

In the method of determining frequency, implying that the uncertainty interval of the frequency hypotheses about the frequency value for each of the hypotheses calculate the estimation of the correlation signal at time T, the estimated correlation is calculated to estimate the incidence, additionally enter the following sequence of new operations:

the frequency determination carried out successively after Q iterations,

determine the interval of uncertainty of the frequency for each iteration,

each ITER is for the next iteration, and on the last iteration, reduce the interval of uncertainty of the frequency to the desired value, for which at each iteration:

determine the time T of the coherent accumulation of the correlation estimates, as the lesser of two quantities, one of which is equal to the value inversely proportional to the interval of uncertainty of the frequency at a given iteration, and the other is equal to an interval of stationarity of the channel,

push n hypotheses, where n > 1, the frequency value in the frequency interval

for each hypothesis, compute the k estimates of the correlation performed on disjoint time intervals of duration T, where k is determined by the size of the uncertainty interval of the frequency on the next iteration, k, the corresponding estimates of the correlation is used to obtain a General appraisal of the correlation for each of the hypotheses,

form the reference signal function,

determine the center coordinate of the reference signal function at its maximum approximation to the generalized correlation estimates of all n hypotheses,

determine the frequency equal to the center coordinate of the reference signal function,

to obtain a General appraisal of the correlation of each of the hypotheses accumulate the squared modules of the respective estimates of the correlation,

or polynomial regression function, the maximum approximation of the reference signal functions to generalized estimates of correlation hypotheses determined by minimizing the sum of squared deviations of the reference signal function from generalized estimates of correlation hypotheses.

In the device frequency in the first embodiment, containing identical parallel channels receiving the signal, each channel consists of series-connected multiplier and unit formation evaluation, which contains the first adder, the first inputs of the multiplier products parallel receiving channels are combined and an information input device, the second inputs connected to the outputs of the oscillator reference signal, the outputs of blocks formation evaluation connected with the corresponding inputs of the evaluation unit of frequency, containing connected in series site selection maximum and node formation evaluation frequency, the output of which is the output of the evaluation unit frequency and forms the output of the device, in addition enter the following distinguishing characteristics:< / BR>
entered the control unit,

additionally introduced into the shaping unit assessment each parallel channel signal receiving compute node unit square, whose input is connected to the output of first the relevant channel of the reception signal,

additionally introduced into the evaluation unit frequency node determine the scan area, the node generating the timing reference signal function, connected in series compute node of a square frame, and the first adder and connected in series multiplier, a second adder, a compute node of a square number and a divider, a second input connected to the output of the first adder, and the output of the divider is connected to the input node of the choice of the maximum, the inputs of the node defining the scan area and the first inputs of the multiplier are United and connected with the outputs of the second adders blocks formation evaluation, the output node define scan area connected to the first input node generation timing of the reference signal function, the first output of which is connected with the second input of the multiplier and the input node compute the square of the reference frame, and its second output is connected with the second input node of formation evaluation frequency,

the output of the evaluation unit of frequency is connected to the input of the control unit,

the first control output of the control unit, set the values of the frequencies corresponding to the hypotheses, is connected to the generator input reference signal and a second input node for generating timing reference signal is I, connected with the second input of the first adder in each block formation evaluation and the third input node of the generation timing of the reference signal function,

the third control output of the control unit determining the number k of the estimated correlation is connected with the second input of the second adder in each block formation evaluation,

the fourth control output of the control unit that sets the desired precision of the estimate of the frequency, is connected to the fourth input node generating the timing reference signal function.

In the device frequency according to the second variant, containing identical parallel channels receiving the signal, each channel consists of series-connected multiplier and unit formation evaluation, which contains the first adder, the first inputs of the multiplier products parallel receiving channels are combined and an information input device, the second inputs connected to the outputs of the oscillator reference signal, the outputs of blocks formation evaluation connected with the corresponding inputs of the evaluation unit of frequency that contains the site of formation evaluation frequency, the output of which is the output of the evaluation unit frequency and forms the output of the device, dopolnitelniye evaluation of each parallel channel signal receiving compute node of the unit square, an input connected to the output of the first adder and the output to the input of the second adder that generates a generalized assessment of the correlation hypothesis corresponding channel signal,

additionally introduced into the evaluation unit frequency connected in series node define the parameters of the regression function and the computing node of the centre of the regression function, the output of which is connected to the input node of the formation evaluation frequency, and the first input node define the parameters of the regression function are connected to the outputs of the second adders blocks formation evaluation,

the output of the evaluation unit of frequency is connected to the input of the control unit,

the first control output of the control unit, set the values of the frequencies corresponding to the hypotheses, is connected to the generator input reference signal, a second input node define the parameters of the regression function, the second input node of the computing centre of the regression function and the second input node of formation evaluation frequency,

the second control output control unit that establishes a coherent accumulation time T, is connected with the second input of the first adder in each block formation evaluation and the third input node determine parametrically, connected with the second input of the second adder in each block formation evaluation,

the fourth control output of the control unit that sets the desired precision of the estimate of the frequency, is connected to the third input node of the formation of estimating the frequency and the third input node of the computing centre of the regression function.

And in the first and second embodiments of the device are arranged in n identical parallel receiving channels, where m > n > 1.

A comparison of the proposed method for determining the frequency with the prototype shows that the claimed invention is characterized by the presence of new evidence of the way.

In the proposed method, the frequency determination carried out successively after Q iterations, gradually narrowing the a priori uncertainty range frequency to achieve the required accuracy assessment. This approach allows us to use at each iteration, a smaller number of parallel frequency channels of the signal relative to the prototype. The required accuracy of the determination of the frequency is achieved by using the reference signal function that allows you to recover information about the possible frequency value in the frequency domain between the suggested hypotheses.

sootvetstvujushij estimates of correlation, that allows to obtain an estimate of the frequency with high accuracy even at very low signal-to-noise. Therefore, the inventive method has novelty.

A comparison of the proposed method for determining the frequency with other known solutions in this field of technology is not allowed to reveal the characteristics stated in the characterizing part of the claims, therefore, the present invention also meets the criteria of the invention: "new", "technical solution", "significant differences" and has obviousness.

A comparison of the proposed device frequency by the first and second variants of the prototype shows that the proposed device has new blocks and circuit elements, as well as the presence of fundamentally new relations in the block diagram, which allow you to implement new features of the proposed method. Honors versions of devices is a different implementation of the evaluation unit. However, both the first and second options allow you to fully realize all the signs of the claimed method and get an equivalent effect. Therefore, the claimed device frequency (options) has novelty.

Compared the Nicki revealed no signs, stated in the characterizing part of the claims, therefore, the present invention also meets the criteria of the invention: "new", "technical solution", "significant differences" and has obviousness.

Graphics illustrating the invention:

Fig. 1 is a block diagram of a device prototype.

Fig. 2 is a block diagram of the proposed device frequency, which is equal to the claimed device according to the first and second variants of implementation, the distinction execution options is the structure of the evaluation unit of frequency 8.

Fig. 3 is a block circuit evaluation frequency for the inventive device frequency by the first option.

Fig. 4 is a block circuit evaluation frequency for the inventive device frequency for the second option.

Fig. 5 illustrates the principle of the proposed method of frequency determination.

The inventive device frequency (Fig. 2) contains:

the reference signal generator 1 generator complex samples lo for all n hypotheses;

n parallel frequency channels, each tuned to a frequency corresponding to one of the hypotheses, each of n the chips and integrated samples of the reference signal generator;

block formation evaluation 3 (for formation of the generalized correlation estimation M(Fi) for this hypothesis); block 3 contains:

the first adder 4 (complex adder adopted chips),

the compute node unit square 9 (to calculate the squared magnitude of a complex number);

the second adder 10 (adder incoherent accumulation of k estimates of correlation);

the evaluation unit frequency 6 - unit regression analysis, generalized estimates of correlation M(Fi) and signal assessment frequency;

the control unit 11.

The evaluation unit frequency 6 for the claimed device frequency in the first embodiment (Fig. 3) contains:

Node define scan area 12,

The node generating the timing reference signal function 13,

The multiplier 14,

The compute node square countdown 15,

The first adder 17,

The second adder 16,

The computing node of the square of the number 18,

The divider 19,

Site selection max 7,

Site formation evaluation frequency 8.

The evaluation unit frequency 6 for the claimed device frequency for the second variant (Fig. 4) contains:

Node define the parameters of the regression function 20,

The compute node center algorithm is a modified multi-channel scheme, based on the optimal computing functions.

The inventive method is implemented by a sequential step-by-step procedures with regression frequency estimation according to the results of a parallel multi-channel reception. Regression analysis the results of parallel multi-channel reception is used in the first and second versions of the device. The difference is that in the first embodiment of the device uses a reference signal known species with uncertain location on the frequency axis, and the second variant of the device as the frequency location and type of signal functions in the General case are unknown and are determined during analysis.

The inventive method of determining frequency implemented as follows.

The frequency determination carried out successively after Q iterations.

Determine the interval of uncertainty of the frequency for each iteration, each iteration reduces the uncertainty interval frequency for a given iteration to the uncertainty interval frequency for the next iteration and the last iteration to reduce the interval of uncertainty of the frequency to the desired value. Note that the number ITER is selected in the design process of a particular device and optimized based on the requirements of the device for evaluation of the frequency and the required performance.

At each iteration, determine the time T of the coherent accumulation of the correlation estimates as the lesser of two quantities, one of which is equal to, for example, the reciprocal of one-half of the uncertainty interval frequency at a given iteration, and the other is equal to an interval of stationarity of the channel.

Next, at each iteration nominate n hypotheses, where n > 1, the value of the frequency interval frequency, for example, is different from the interval of uncertainty of the frequency in time, where < 2. Then calculate the k estimates of correlation for each hypothesis, performed on disjoint time intervals of duration T. the Value of k determines the formation of generalized estimates of correlation and depends on the size of the uncertainty interval frequency for the next iteration. Change the time of the formation of generalized estimates of correlation allows to achieve the required probability of reduction of the interval of uncertainty of the frequency for a given iteration to the desired value.

To obtain a General appraisal of the correlation of each of the hypotheses using k corresponding estimates of correlation, for example, by the accumulation of their squares modules.

Form the reference signal function and determine the frequency, uravnoveshennym estimated correlation of all n hypotheses.

As the reference signal function can be any function of the form (Sin(x)/(x))2where x = fT, the coordinate of the center of which is found by minimizing the sum of squared deviations of the reference signal function from generalized estimates of correlation hypotheses. Another option reference signal may be any other curved or polynomial regression function, which gives a good approximation to the true shape of the Central lobe of the signal function of the received signal.

When implementing the method of determining frequency device according to the first embodiment uses the block structure 6 shown in Fig. 3, and Fig. 5 illustrates the principle of sequential regression estimates of the frequency according to the results of a parallel multi-channel reception.

At the first step of analyzing the entire a priori uncertainty interval frequency [-FmaxFmax]. To do this, choose the time of the coherent accumulation estimates T as the lesser of two quantities, one of which is equal to, for example, the reciprocal of one-half of the uncertainty interval frequency at a given iteration, and the other is equal to an interval of stationarity of the channel, and push the n hypotheses about the frequency value. Hypotheses are put forward n>/P>For each of the hypotheses compute the generalized correlation scores, which simultaneously form the n values corresponding to the hypotheses, using the following function:

< / BR>
where i is the number of hypotheses, which takes values from 1 to n,

Fi is the frequency corresponding to the i-th hypothesis,

M(Fi) - a summary evaluation of the correlation for each of the first hypothesis (the result of the accumulation of square modules k estimates of correlations)

k is the number of stored estimates of the correlation,

Xi,bReXi,bImthe real and imaginary parts of the coherent accumulation of the received chips in accordance with the i-th hypothesis for the b-th correlation estimation.

Next, define the scan area bounded by frequencies F1and F2. This operation can be performed, for example, by selecting the two hypotheses with the highest value (1) and determine their frequencies. The selection of the two greatest results accumulation allows to reduce the computational complexity of the method, since the desired value of frequency will be in the range of frequencies bounded by the frequencies of these hypotheses.

To determine the frequency to find the maximum of the following crucial functions based on the method of least squares (maximum ASS="ptx2">

The value at which the condition of maximum of (2), and will be required frequency estimation. The estimation of frequency can be made by successive increments and finding the maximum value (), and using a parallel circuit, each of the outputs which corresponds to its value . The choice of a discrete increment of a variable depends on the magnitude of the uncertainty interval frequency at the end of this iteration, and can be defined as a value approximately equal to a quarter of this interval.

In the next step again produce the timing of the coherent accumulation estimates T in accordance with the above rule in the neighborhood of the obtained estimates of the frequency given for this iteration of the interval of uncertainty form the n hypotheses and perform another iteration frequency, specifying obtained at the previous iteration assessment.

After a Q such iterations, the a priori uncertainty interval frequency [-FmaxFmax] narrows down to sizes that match the specified allowable error of estimation.

As noted above, there are two General principle of using the obtained estimate the hours the step of evaluating the obtained value of the frequency transmitted to the correction, for example, in reference generator analog demodulator for slojnenia with the current value of the frequency generator. In this case, is not required for the formation of hypotheses to be considered received on the previous iteration to estimate the incidence, because it will be considered automatically.

The principle of the method of frequency determination based on what type of signal function of the received signal are known a priori and depends on the duration of the coherent signal accumulation. Choose the duration of the coherent signal accumulation must be performed with respect to the interval of orthogonality of the received signal.

Feature of the UMTS standard is a temporary separation of the pilot symbols and symbol information. If the interval of stationarity of the channel, the longer the interval of orthogonality, symbols, pilot signal transmitted always with the same phase, you can perform coherent accumulation of multiple characters.

Meanwhile, the phase of the received symbol information is not defined a priori, because transmission of information to use 4-phase shift keying signal. Thus, when receiving character information, the duration of the coherent accumulation may not exceed the duration the existing restrictions on the use of the symbol information of the proposed algorithm to determine the frequency allows you to shape the frequency estimation using only the symbols of the pilot signal, while the required accuracy of the determination of the frequency for a time not substantially exceeding the time analysis device prototype.

In cdma2000 there is continuously transmitted pilot signal that enables to assess the correlation between adjacent time intervals. While the temporal characteristics of the proposed device significantly outpace that of the device of the prototype.

Does the proposed device in the first embodiment as follows (Fig. 2, figs. 3).

At the beginning of each of the Q iterations, the control unit 11 by using 4 transmits control signals to all units of the device frequency required data corresponding to the number of the iteration.

Using the control signal 1 from the reference signal generator 1 and the node generating the timing reference signal function 13 transmit frequency Fi. The control signal 2 is designed to pass the value of the parameter T (time coherent accumulation signal) to the adder 4 and the node 13. The control signal 3 determines the time non-coherent accumulation of the correlation estimates (number of assessments k) in the adder 10. Control signal 4 allows you to set the resolution change displaced the sequences go on n complex multiplier products 2, where each chip is multiplied by a complex reference oscillator reference signal eUNESCO, Fi is the frequency of the i-th hypothesis, t is the time. Thus, the output of each multiplier products generated signal, shifted in frequency by the value (Fi - F).

In block 3 is the formation of estimation M(Fi) for this hypothesis in accordance with the function (1). For this purpose, by means of the adder 4 is coherent accumulation of chips information at time T. After that, the unit 9 calculates the square of the module of the accumulated coherent sum of (squared correlation estimation).

The adder 10 is designed for non-coherent accumulation of k squares estimates of correlation and formation, thus, the values of the generalized correlation estimation M(Fi) for this hypothesis.

The evaluation unit frequency 6 (Fig. 3) on the obtained function values M(Fi) produces a frequency determination using a crucial function in (2).

Node define scan area 12, which is implemented in this case as the site selection of two maxima, selects a frequency channel with a maximum value of M(Fi) and determines their rooms, which are transmitted to the node 13, where determined by their frequency: F1and F2. Then in the node 13 is the generation timing to F2increments, preset control signal 4 from the control unit 11.

Samples of the regression function from node 13 is coming to the multiplier 14 where it is multiplication with the corresponding counts M(Fi). The result of the multiplication is passed to the adder 16 for summing them for each value on all n channels. Amounts received are transmitted to the computing node of the square of the number 18. Collaboration of nodes 14, 16 and 18 allows to form the numerator of the expression (2).

Node compute the square of the reference 15 is designed to obtain samples (Sin(x)/(x))4. Joint work site 15 and the adder 17 allows to form the denominator of the expression (2).

The output of the divider 19 is formed a decisive function (), the samples are transferred to the node 7 to find the maximum value. For formation evaluation frequency in the node 8 of the node 13 is passed information about the range and discrete changes . Comparison of this information with that found in the node 7 a max () function allows you to decide on the frequency value and to give her an estimate on the output node 8, which forms the output of block 6.

The assessment frequency is transmitted to the control unit 11 for use in the formation of the work continuously, through the same cycles (iterations) assessment frequency. For the organization of the tracking mode by using the proposed structure is necessary to repeat the last (the most accurate) step of estimating the frequency. Note that on the last iteration of the width of the Central lobe of the signal function can be chosen large enough that allows you to use this method to create systems-locked loop with wide band for the hold.

When using method 2 of estimating the frequency of the claimed method implemented using the block 6, the block diagram of which is shown in Fig. 4.

Using the regression function of the form (Sin(x)/(x))2(a special case of curvilinear regression) allows to obtain the best estimate of the frequency shift, since in this case we use the true signal function of received messages. However, the proposed method allows to assess the frequency with several other curvilinear or polynomial regression functions, giving a good approximation to the true shape of the Central lobe of the signal function.

When implementing the method of determining frequency device according to the second variant uses the block structure 6, not only the frequency. The device operates as follows.

At the first step of analyzing the entire a priori uncertainty interval frequency [-FmaxFmax] . To do this, choose the time of the coherent accumulation estimates T in accordance with the above rule and have n hypotheses about the frequency value to the frequency interval, in General not equal to the interval of uncertainty of the frequency for a given iteration.

For each of the hypotheses using blocks 1, 2, 3 and 11 calculates a generalized assessment of the correlation, which simultaneously form the n values corresponding to the hypotheses, using the expression (1). Operation of units 1, 2, 3 and 11 when implementing the method of determining frequency device according to the second option on each of the Q iterations similar to those described above implement the method on the device in the first embodiment. As a result of their work will also be formed generalized estimating the correlation for each of the n hypotheses.

After accumulation in the adder 10 (Fig. 2) k squares estimates of correlation and formation, thus, the values of the function M(Fi) for each of the n hypotheses correlation estimation M(Fi) of the blocks 3 are received in the node definitions of the parameters of the regression function 20.

Node 20 determines the parameters of regressi is the ensure the maximum approximation to these estimates.

Depending on the form of the regression function and how to determine the proximity of the regression function to the existing generalized correlation estimates, there are various algorithms for determining its parameters. We consider two main approaches to defining the parameters of the regression function.

The analytical approach is to obtain exact analytical expressions of the calculation of each parameter. For example, suppose the regression function is a polynomial:

< / BR>
where x is the argument of the polynomial,

abthe coefficients (parameters) of the polynomial,

M - order polynomial.

Consider the definition of the parameters of the regression function by the method of least squares when the parameters of the regression function is chosen so that the sum of squares of the difference of generalized estimates of correlation and regression values of the function at the appropriate point in time was minimal. Let M(Fi) - i-I a summary evaluation of the correlation, a Fi - its coordinate in the frequency axis. Then you need to determine the parameters of the regression polynomial, where the condition of the minimum of the expression:

< / BR>
To find the parameters of the regression function that minimizes the expression (4), need wagenia (4) leads to a system of linear equations, solutions which can be easily determined analytically.

The expression (4) for the General form of the regression function has the form:

< / BR>
wherei- the i-th parameter of the regression function.

Note that the analytical determination of the parameters is possible not for all types of regression functions. In contrast to expression (4) differentiation of expression (5) can lead to a system of nonlinear equations, obtaining exact solutions which is often impossible or requires significant hardware costs. A typical example could be the use of the function (Sin(x)/(x))2.

To determine the parameters of the regression function in this case can be applied numerical methods [7. A. A. Amosov, Y. A. Dubinsky and N. In. Kopchenov. Computational methods for engineers. M., "Higher school", 1994, pages 262-263; 8. Mathematical encyclopedia Ed. by I. M. Vinogradov M., "Soviet encyclopedia", 1982].

After defining the parameter values of the regression function at the node 21, the computation of its center. For this you can use a procedure similar to that of finding the maximum value of the expression (2). This procedure is based on calculating the value of the function at different values per the t to determine the scope of the search of the centre of the regression function. In this case, as previously, the choice of a discrete change of the variable depends on the magnitude of the uncertainty interval frequency at the end of this iteration.

Another way to calculate the center of a regression function may be the location of the extrema of the regression function S(f) on the frequency axis, is uniquely associated with the target value of the center of the regression function.

Node 8 form the frequency estimation, which uses information from the block 11 is advanced to the current iteration of the hypotheses and the accuracy of estimates of frequency at a given iteration (discrete change of the variable of the regression function block 21), received by the control signals. Comparison of this information with that obtained in the node 21 assessment of the location of the centre of the regression function to determine the frequency and to give her an estimate on the output of the block.

Control signals in block 6 of the control unit 11, performs the same functions as before:

signal 1 determines the frequency of the hypotheses that are configured parallel receiving channels (blocks 2 and 3),

signal 2 determines the type of signal functions generated in blocks of 3 evaluations

signal 4 specifies the required accuracy of otekline estimates of T, in the vicinity of the obtained estimates of the frequency given for this iteration of the interval of uncertainty form the n hypotheses and perform another iteration of the estimation of frequency, specifying certain on the previous iteration frequency.

The inventive method of determining the frequency and device for its implementation (options) compared to the prototype allows to obtain fundamentally new technical effect:

to determine the frequency with large a priori uncertainty ranges of frequency in cases where the use phase of the method is in principle impossible,

significantly reduce the cost of implementing the method, which is achieved by determining the frequency successively after Q iterations,

to obtain an estimate of the frequency with high accuracy even at very low signal-to-noise,

to determine the frequency when implementing a method for determining the frequency of the UMTS standard, with time division pilot symbols and characters of information, using only the symbols of the pilot signal, while slightly exceeding the time of evaluation in the prototype,

to determine the frequency over time, significantly less time evaluation in the prototype, the implementation of the method determine the mode frequency, namely, that in the interval of uncertainty of the frequency hypotheses about the frequency value for each of the hypotheses calculate the estimation of the correlation signal at time T, estimated correlation calculates the evaluation frequency, wherein the frequency determination carried out successively after Q iterations, determine the interval of uncertainty of the frequency for each iteration, each iteration reduces the uncertainty interval frequency for a given iteration to the uncertainty interval frequency for the next iteration and the last iteration to reduce the interval of uncertainty of the frequency to the desired value, and at each iteration to determine the time T of the coherent accumulation of the correlation estimates, as the smaller of the two quantities, one of which is equal to the value inversely proportional to the interval of uncertainty of the frequency at a given iteration, and the other is equal to an interval of stationarity of the channel, push n hypotheses, where n > 1, the frequency value in the frequency interval for each hypothesis calculate the k estimates of the correlation performed on disjoint time intervals of duration T, where k is determined by the size of the uncertainty interval of the frequency on the next iteration, Otis, form the reference signal function, define the coordinate of the center of the reference signal function, the maximum approximation of the reference signal functions to generalized estimates of the correlation of all n hypotheses, determine the frequency equal to the center coordinate of the reference signal function.

2. The method according to p. 1, characterized in that to obtain a General appraisal of the correlation of each of the hypotheses accumulate the squared modules of the respective estimates of correlation.

3. The method according to p. 1, characterized in that the reference signal function S(f) use the function (Sin(x)/(x))2where x=fň.

4. The method according to p. 1, characterized in that the maximum approximation of the reference signal functions to generalized estimates of correlation hypotheses determined by minimizing the sum of squared deviations of the reference signal function from generalized estimates of correlation hypotheses.

5. Device for determination of frequencies containing the same parallel channels receiving the signal, each channel consists of series-connected multiplier and unit formation evaluation, which contains the first adder, the first inputs of the multiplier products parallel receiving channels are combined and WMO information the evaluation is connected with the corresponding inputs of the evaluation unit of frequency, contains one United site selection maximum and node formation evaluation frequency, the output of which is the output of the evaluation unit frequency and forms the output of the device, characterized in that the control unit and additionally introduced into the shaping unit assessment each parallel channel signal receiving compute node of the unit square, the input connected to the output of the first adder and the output to the input of the second adder that generates a generalized assessment of the correlation hypothesis corresponding channel signal, and the evaluation unit frequency entered the site determine the scan area, the node generating the timing reference signal function, connected in series compute node of a square frame, and the first adder and connected in series multiplier, a second adder, a compute node of a square number and a divider, a second input connected to the output of the first adder, and the output of the divider is connected to the input node of the choice of the maximum, the inputs of the node defining the scan area and the first input of the multiplier unit estimates the frequency of the joint and is connected to the outputs of the second adders blocks formation evaluation, the output node determine the scan area in the block assessment is which is connected with the second input of the multiplier and the input node compute the square of the reference and its second output is connected with the second input node of formation evaluation frequency, the output of the evaluation unit of frequency is connected to the input of the control unit, a first control output of which set the values of the frequencies corresponding to the hypotheses, is connected to the generator input reference signal and a second input node for generating timing reference signal function, the second control output control unit that establishes a coherent accumulation time T, is connected with the second input of the first adder in each block formation evaluation and the third input node of the generation timing of the reference signal function, the third control output of the control unit determining the number k of the estimated correlation connected with the second input of the second adder in each block formation evaluation, the fourth control output of the control unit that sets the desired precision of the estimate of the frequency, is connected to the fourth input node generating the timing reference signal function.

6. Device for determination of frequencies containing the same parallel channels receiving the signal, each channel consists of series-connected multiplier and unit formation evaluation, which contains the first summate the STS, the second inputs connected to the outputs of the oscillator reference signal, the outputs of blocks formation evaluation connected with the corresponding inputs of the evaluation unit of frequency that contains the site of formation evaluation frequency, the output of which is the output of the evaluation unit frequency and forms the output of the device, characterized in that the control unit and additionally introduced into the shaping unit assessment each parallel channel signal receiving compute node of the unit square, the input connected to the output of the first adder and the output to the input of the second adder that generates a generalized assessment of the correlation hypothesis corresponding channel signal, and assessment unit of the frequency is entered serially connected node define the parameters of the regression function and the computing node of the centre of the regression function, the output of which is connected to the input node of the formation evaluation frequency, and the first input node define the parameters of the regression function are connected to the outputs of the second adders blocks formation evaluation, the output of the evaluation unit of frequency is connected to the input of the control unit, the first control output of the control unit, set the values of the frequencies corresponding to the hypotheses connected with Whedon host computing centre of the regression function and the second input node of formation evaluation frequency, the second control output control unit that establishes a coherent accumulation time T, is connected with the second input of the first adder in each block formation evaluation and the third input node define the parameters of the regression function, the third control output of the control unit determining the number k of the estimated correlation is connected with the second input of the second adder in each block formation evaluation, the fourth control output of the control unit that sets the desired precision of the estimate of the frequency, is connected to the third input node of the formation of estimating the frequency and the third input node of the computing centre of the regression function.

 

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