JP2002271430A - Frequency offset estimating method and frequency offset estimator - Google Patents

Abstract

(57) [Summary] [PROBLEMS] To estimate a frequency offset with high speed and high accuracy under the condition of interference from other users or multipath interference. SOLUTION: This is a frequency offset estimator in a broadcast or communication receiving equipment for estimating a carrier frequency of a received signal, converting a carrier band to a baseband based on the estimation result, and demodulating the signal. A multiplication means 112 for multiplying the known signal, a delay means 113 for outputting the output of the multiplication means at predetermined time intervals, a correlation matrix calculation means 115 for calculating a correlation matrix of a vector having the output of the delay means as an element, Eigenvalue decomposing means for obtaining an eigenvalue of a correlation matrix which is an output of the correlation matrix calculating means, and outputting an eigenvector corresponding to the maximum eigenvalue as a carrier wave waveform
116.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a frequency offset estimating method and a frequency offset estimator.

[0002]

2. Description of the Related Art In many communication systems and broadcasting systems, a signal is transmitted by temporarily converting a transmission signal to a frequency in a carrier band and transmitting the signal, and a receiver side accurately removes a carrier frequency component from the received signal. I do. At this time, many systems estimate a carrier frequency from a received signal. In general, the carrier frequency estimation accuracy greatly affects signal transmission characteristics. In particular, in a digital signal transmission system to which phase modulation is applied, information is added to the phase of a carrier wave to be transmitted.
To extract this information at the receiver, accurate carrier frequency estimation is essential.

Conventionally, in a wired communication system using a metallic cable, a fixed wireless system or a satellite communication system having stable transmission characteristics, a carrier wave regenerator in which a carrier estimator and a demodulator are integrated is used to provide a carrier wave. A method of estimating not only the frequency but also the phase simultaneously and with high accuracy has been used in many cases. FIG. 18 shows a configuration example of a Costas-type carrier recovery circuit. In the figure, 1 is a reception signal input terminal, 2 is a quadrature detector, 3 is a voltage controlled oscillator,
6 to 8 are multipliers, 7 is a subtractor, 8 is an adder, 9 is a loop filter, and 10 and 11 are in-phase / quadrature signal output terminals. FIG. 19 shows a detailed configuration of the quadrature detector 2 used in FIG. In the figure, 12 is an input terminal, 13 and 17 are branch circuits, 14 and 15 are multipliers, 16 is a π / 2 phase shifter, and 19 and 20 are output terminals for in-phase and quadrature signals.

[0004] In addition to the Costas type, an inverse modulation type carrier recovery circuit is known. This is a method in which a received signal is inversely modulated in advance, a carrier wave component is extracted, a frequency of an oscillator is synchronized with the carrier wave, and the carrier wave is reproduced. This inverse modulation type carrier wave reproduction circuit uses TDMA (Time Division Multiplex).
iple Access) has been used in satellite communications. FIG. 20 shows the configuration of an inverse modulation type carrier recovery circuit. In the figure, 21 is a reception signal input terminal, 22 is a preamble signal input terminal, 23 and 24 are branch circuits, and 25 to 27.
Is a multiplier, 28 is a band-pass filter called a tank filter, and 29 is a loop filter.
filter), 30 is a voltage controlled oscillator, and 31 is an output terminal.

[0005] On the other hand, in a mobile communication system in which the transmission line fluctuates drastically, a delay detection system capable of high-speed phase synchronization is used. In the receiver using the delay detection, the frequency is temporarily converted to near the baseband by a local oscillator close to the carrier frequency, and the received signal is subjected to the delay detection. At this time, a stationary phase error due to the oscillation frequency of the local oscillator and the carrier frequency of the received signal appears in the signal after the delay detection. By correcting this stationary phase error, carrier frequency estimation is equivalently performed.

FIG. 21 shows a configuration of a delay detector provided with a frequency difference (referred to as "frequency offset") compensation function between a local oscillator and a carrier wave frequency. In the figure, 32 is a reception signal input terminal, 33 to 36 are multipliers, 37 is an adder, 38 is a subtractor, 39 and 40 are one symbol delay elements,
41 is a discriminator, 42 is a coefficient input terminal of the multiplier 36, 43
Is a delay detector, 44 is a frequency offset estimator, 45 is a local oscillator, and 46 is a demodulated signal output terminal.

In principle, the above-mentioned differential detection method has a characteristic deterioration of less than 3 dB as compared with the synchronous detection method such as the Costas type. For this reason, studies have been made to apply a synchronous detection method that is characteristically advantageous to a mobile communication system. Among them, the phase control method to which the RLS (Recursive Least Squares) algorithm is applied is a PDC (Personal Digital
Cellular) and PHS (Personal Handy-phone System)
TDMA mobile communication systems such as
At the beginning of each slot, not only phase synchronization but also frequency synchronization can be established at high speed. Moreover, since this system can be realized with a relatively small circuit scale, it can be said that this system is excellent for application to a mobile communication system that requires miniaturization and low power consumption. FIG. 22 shows a configuration example of the RLS phase control circuit.
In the figure, 47 is a reception signal input terminal, 48 and 49 are multipliers, 50 and 51 are discriminators, 52 is a one-symbol delay element, 53 is a terminal for inputting a fixed value “1”, and 54 and 55 are RLS controls. Reference numeral 56 denotes a demodulated signal output terminal.

[0008] In a mobile communication system, the same channel is arranged at a distance from each other in order to improve the frequency utilization efficiency over the whole area. That is, several types of carrier frequencies f _{1 to} f _n are prepared, and different carrier frequencies from the adjacent base stations are arranged. Therefore, by using the same frequency for every n base stations, it is possible to cover all service areas with n carrier frequencies, assuming that base stations are arranged linearly. In this configuration, in order to improve the frequency use efficiency, it is desirable to shorten this distance, that is, to reduce the frequency repetition frequency n. However, in that case, co-channel interference occurs.

It is known that this co-channel interference can be removed by applying interference cancellation such as an adaptive array. However, when an adaptive array or the like is applied, since an algorithm for controlling them is generally based on linear estimation theory, it is necessary to simultaneously mount a high-accuracy frequency offset estimating unit. In other words, accurate frequency offset estimation is required in the presence of co-channel interference waves.However, in systems that involve demodulation, such as the Costas-type carrier recovery system and the inverse modulation-type carrier recovery system, accurate demodulation cannot be performed. There is a problem that it is not possible to estimate an accurate frequency offset.

Therefore, as a method for estimating the frequency offset even under such interference conditions, a DFT (Digital Fo
urier Transform) has been proposed. In this method, a known pattern signal is inserted into a part of a transmission signal, and a receiver removes a known pattern signal component from a reception signal and extracts a carrier component. DFT processing is performed on the extracted carrier, and the maximum value is used as the carrier frequency. This method enables accurate frequency offset estimation even in the presence of an interference wave due to the excellent frequency analysis capability of DFT.

FIG. 23 shows a configuration example of a frequency offset estimator using a DFT. In the figure, 61 is a reception signal input terminal, 62 is a local oscillator, 63 and 64 are multipliers,
65 is a known pattern signal (pilot signal: pilot sy)
mbols) storage element, 66 is a DFT, 67 is a maximum value detector, and 68 is an estimated frequency output terminal.

The frequency offset estimating method using the DFT has a considerably high frequency offset estimating capability as compared with the method involving demodulation.
Compared to the frequency offset estimation accuracy achieved in N (Additive White Gaussian Noise), the quality is greatly deteriorated. Although an unrealistic model, accurate frequency offset estimation is difficult even if all are known pattern signals.

By the way, in order to provide a comfortable multimedia service in a mobile communication environment, high-speed signal transmission is required even on a mobile radio transmission path. As is well known, when high-speed communication is performed on a mobile communication transmission line in which an object such as a house that causes reflection and diffraction is present, characteristics are significantly deteriorated due to severe intersymbol interference caused by multipath.
To compensate for this, an adaptive equalizer is effective, but since the control algorithm is based on the linear estimation theory as in the case of the adaptive array, it is necessary to provide a highly accurate frequency offset estimating circuit. A method of realizing a high-accuracy frequency offset estimator by combining an adaptive equalizer and a frequency offset estimating circuit is known. However, in addition to intersymbol interference caused by multipath, co-channel interference is further reduced. In an existing environment, it is difficult to perform accurate frequency offset estimation as described above.

[0014]

As described above, conventionally, there has been a problem that it is difficult to accurately estimate a frequency offset essential for signal demodulation under severe co-channel interference environment.

In the case of providing a multimedia mobile communication system, in addition to co-channel interference, inter-symbol interference due to multipath occurs. On the road,
A conventional frequency estimator provided in a demodulator for a Gaussian channel, Rayleigh fading, or intersymbol interference transmission path has a problem that it is difficult to estimate a frequency with high accuracy.

SUMMARY OF THE INVENTION The present invention has been made to solve such a conventional technical problem. In a receiving facility used for broadcasting or a communication system for transmitting a signal by converting a signal into a carrier wave band, the frequency of a carrier wave is changed. It is intended to provide a technique for accurately estimating.

[0017]

Transmission signal x _k [Means for solving the _problems], and _l is transmitted to a transmission line at a carrier angular frequency omega _l. Here, the suffix l represents the number of the user, and k represents the time. In this case, if the user of the signal 1~K in the transmission path may interfere, additionally there is a delayed wave in each reception signal s _k may be described as follows.

[0018]

(Equation 1) Here, L _c +1 is the maximum delay amount of the transmission path, a _{i, l} ; i =
0, ..., L _c is the impulse response of the first interference wave, omega _l and theta _{0, l} is the frequency and initial phase, T is the symbol period of the l-th signal, the n _k is a noise component.

Actually, the interference includes interference from various systems. Here, for simplicity, it is assumed that the interference is from the same system. Further, in equation (1), the interference is close to the TDMA which is synchronized with each other. The system is assumed.
At this time, it is assumed that the i = 1st signal is a desired signal. That is, consider estimating the frequency component of the i = 1st signal among the signals included in the received signal. Here first,
When the received signal is multiplied by the i = 1st known signal pattern, the following signal is obtained.

[0020]

(Equation 2)Where y_kL-dimensional vector whose elements are time series
Y_k= [Y_k y_k-1 ... y_{k-L + 1}]^TIs defined. Do
And the vector Y_kCan be rewritten as follows: That
The correlation matrix is expressed as follows.

[0021]

(Equation 3) The suffixes T and H in the above equations (3.1) to (3.6) are the transpose and Hermitian transpose of a vector or matrix, respectively. At this time, the correlation matrix R _k of Y _k is expressed as follows.

[0022]

(Equation 4) Here, E [...] means taking a collective average, and Ω _{0, l} and C _l are expressed as follows.

[0023]

(Equation 5) However, in deriving the equations (4.1) and (4.3), the decorrelation between noise and a signal and the decorrelation between signals of different users are used. Further, in the equation (4.1), I is a unit matrix, and σ ² is a variance of noise.

Here, E [C] = ｛E in equation (4.1)
[C _{i, j} ]} is actually as follows.

[0025]

(Equation 6) By substituting the above equations (5.1) and (5.2) into equation (4.1), the following equation is obtained.

[0026]

(Equation 7) Here, the expression (6.1) is modified as follows.

[0027]

(Equation 8) When the above-described correlation matrix R _k is eigenvalue-decomposed, its eigenvalue λ
_i is as follows.

[0028]

(Equation 9) Equations (8.1) and (8.2) mean that equation (7.1) can be modified as follows.

[0029]

(Equation 10) Since λ ₁ > λ ₂ from the equations (8.1) and (8.2), the eigenvector corresponding to the maximum value of the eigenvalues of the correlation matrix is a carrier vector or a frequency offset vector. Therefore, the frequency can be estimated by measuring the frequency of the eigenvector corresponding to the maximum eigenvalue of the correlation matrix. Also, as can be seen from Equations (8.1) and (8.2), by using eigenvalue decomposition, the eigenvalue λ ₁ including the coherent component of the desired signal and the eigenvalue λ ₂ not including the coherent component are obtained. It can be seen that the frequency can be estimated with high accuracy.

Based on the above theoretical considerations, the present invention has the following features.

A first aspect of the present invention is a frequency offset estimating method in a broadcast or communication receiving method for estimating a carrier frequency of a received signal, converting a carrier band to a baseband band based on the estimation result, and demodulating the signal. A multiplication process of multiplying the reception signal by a known signal; a delay process of outputting a result output of the multiplication process at predetermined time intervals; and a correlation matrix of a vector having an output of the delay process as an element. It has a correlation matrix calculation process, and an eigenvalue decomposition process for obtaining an eigenvalue of a correlation matrix which is a result output of the correlation matrix calculation process, and outputting an eigenvector corresponding to the maximum eigenvalue as a carrier wave waveform.

According to a second aspect of the present invention, there is provided a frequency offset estimating method in a broadcast or communication receiving method for estimating a carrier frequency of a received signal, converting a carrier band to a baseband band based on the estimation result, and demodulating the signal. A multiplication process of multiplying the reception signal by a known signal; a delay process of outputting a result output of the multiplication process at predetermined time intervals; and a correlation matrix of a vector having an output of the delay process as an element. Correlation matrix operation processing, eigenvalues of the correlation matrix that is a result output of the correlation matrix operation processing, estimating the maximum value of the frequency component included in the eigenvector corresponding to the maximum eigenvalue, and estimating the frequency of the eigenvector frequency output processing, Have

A third aspect of the present invention is a frequency offset estimator in a broadcasting or communication receiving facility for estimating a carrier frequency of a received signal, converting a carrier band to a baseband band based on the estimation result, and demodulating the signal. Multiplying means for multiplying the received signal by a known signal; delay means for outputting an output of the multiplying means at predetermined time intervals;
A correlation matrix calculating means for calculating a correlation matrix of a vector having the output of the delay means as an element, obtaining an eigenvalue of a correlation matrix which is an output of the correlation matrix calculating means, and outputting an eigenvector corresponding to a maximum eigenvalue as a carrier wave waveform. And eigenvalue decomposition means.

According to a fourth aspect of the present invention, there is provided a frequency offset estimator in a broadcast or communication receiving facility for estimating a carrier frequency of a received signal, converting a carrier band to a baseband band based on the estimation result, and demodulating the signal. Multiplying means for multiplying the received signal by a known signal; delay means for outputting an output of the multiplying means at predetermined time intervals;
A correlation matrix calculating means for calculating a correlation matrix of a vector having the output of the delay means as an element; obtaining an eigenvalue of a correlation matrix which is an output of the correlation matrix calculating means; and calculating a frequency component included in an eigenvector corresponding to a maximum eigenvalue. Eigenvector frequency estimating means for estimating and outputting the maximum value.

[0035]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of the present invention will be described below in detail with reference to the drawings.

<First Embodiment> FIG. 1 shows a configuration of a frequency offset estimator according to a first embodiment of the present invention. In the figure, 100 is an input terminal, 101 is a multiplier, 102 is a pilot signal storage element (pilot symbol).
s) and 103 are delay circuits; 104 is an eigenvalue decomposition unit;
Reference numeral 5 denotes a correlation matrix operation unit, and reference numeral 106 denotes an output terminal of an estimated frequency. In the figure, the input signal at the input terminal 100 is multiplied by a known signal output from the pilot signal storage element 102 to obtain y _k in equation (2). This y _k is used as a delay circuit 1
When the signal is input to the input circuit 03, the delay circuit 103 outputs signal groups y _k , y _k−1 ,..., Y _{k−L + 1} having different delay times. This group of signals is equal to the elements of the vector _Yk .

The correlation matrix calculation unit 105 performs the following calculation using the vector Y _k to obtain the correlation matrix R _k
Get.

[0038]

[Equation 11] In the equation (4.1), the correlation matrix is obtained by the set average of Y _k Y _k ^H , but is actually obtained by the time average based on the ergodic theorem. This correlation matrix is a Hermitian matrix, as can be seen from the equation (11). Therefore, the eigenvalue decomposition can be obtained by various methods such as the Jacobi method and the QR method. The eigenvalue decomposition unit 104 performs this eigenvalue decomposition processing. (Kurose; "Subroutine library for Fortran90-numerical calculation, statistical calculation, three-dimensional CG
Library- ", Morikita Publishing, 1998).

The eigenvalue decomposition section 104 extracts only the eigenvector corresponding to the maximum eigenvalue from the eigenvalues and eigenvectors thus obtained, and outputs this from the output terminal 106 as an estimated frequency offset value.

FIG. 2 shows a detailed configuration of the delay circuit 103 in the above-described frequency offset estimator. In the figure, 201 is an input terminal, 202 to 204 are delay elements,
Reference numerals 05 to 208 denote output terminals of the signal group. When y _k is inputted from the input terminal 201, the signal is delayed, and the signals of y _k , y _k−1 ,..., Y _{k−L + 1} are output to the output terminal 205.
To 208.

<Second Embodiment> Next, a second embodiment of the present invention will be described.
FIG. 3 shows a frequency offset estimator according to the embodiment. In the figure, 111 is an input terminal, 112 is a multiplier, 113 is a delay circuit, 114 is a pilot signal storage element, 115 is a correlation matrix operation unit, 116 is an eigenvalue decomposition unit,
117 is an eigenvector frequency estimating unit, and 118 is an output terminal of the estimated frequency.

In the second embodiment, the first embodiment shown in FIG.
The eigenvalue is obtained from the correlation matrix of the received signal vector, and a vector corresponding to the maximum eigenvalue is generated in the same manner as in the embodiment. Since the generated vector is not necessarily a sine wave, the highest frequency component of the eigenvector is obtained by the eigenvector frequency estimating unit 117 and output from the output terminal 118 as an estimated value of the frequency offset.

FIG. 4 shows a detailed configuration of the eigenvector frequency estimating section 117 described above. In FIG.
1 to 221-4 are input terminals of each element of the eigenvector from the eigenvalue decomposition unit 116, and 222-1 to 222-4 are buffer circuits for storing the eigenvectors, 223 to 229.
Is a multiplier, 230 is a terminal for inputting a fixed value “1”, 23
1 is an adder, 234 is an adaptive control unit, and 235 is an output terminal. Further, adaptive control section 234 generates eigenvector v ₁ =
The following operation is repeatedly performed on [v _1,0 , v _1,1 ,..., V _{1, L-1} ].

[0044]

(Equation 12) Here, μ in Expression (12.3) represents a small coefficient called a step size parameter, and Im [...] represents a function for extracting only an imaginary part.

After repeating the above operation a predetermined number of times m,

(Equation 13) Is output from the terminal 235 as the estimated frequency.

<Third Embodiment> FIG. 5 shows a frequency offset estimator according to a third embodiment of the present invention. Generally, in a wireless system, an approximate frequency is known because signals are arranged in a known radio frequency band. However, in some cases, the initial frequency may be significantly different from the assumed initial frequency due to imperfections of the device. The frequency offset estimating circuit according to the third embodiment is an effective circuit when the estimated frequency deviates greatly from the initial value of the estimation.

In the figure, reference numeral 121 denotes an input terminal;
Is a multiplier, 123 is a pilot signal storage element, 124 is a delay circuit, 125 is a correlation matrix operation unit, 126 is an eigenvalue decomposition unit, 127 is an eigenvector frequency estimation unit, 128 is a DFT circuit, and 129 is an estimation value of a frequency offset. The output terminal 130 is a maximum value detection unit.

The circuit of the third embodiment performs the same processing as the circuit of the second embodiment shown in FIG. 3, except that the eigenvector corresponding to the maximum eigenvalue is input to the DFT circuit 128. To perform DFT processing,
30, the frequency component corresponding to the maximum value is set to an initial value in the frequency estimation of the eigenvector,

[Equation 14] The point is that the eigenvector frequency estimating section 127 performs frequency estimation using this.

In principle, the frequency estimation of the eigenvector by the frequency estimator 117 shown in FIG. 4 employed in the second embodiment is highly accurate, but if the initial value is too large and differs from the actual frequency, May output completely different values. Therefore, in the third embodiment, D
This point can be overcome by using a frequency roughly estimated by the FT circuit 128 as an initial value.

<Application Example 1> FIG. 6 shows a receiver using the frequency offset estimator of the present invention. In FIG.
1 is a carrier band signal input terminal, 132 is a local oscillator, 13
3 to 135 are multipliers, 136 is a delay element, and 137 is FIG.
The frequency offset estimator according to the second embodiment shown in FIG. 5 or the frequency offset estimator according to the third embodiment shown in FIG. 5 is a signal output terminal, and 139 is a band-pass filter.

In this receiver, the frequency of the received signal is temporarily converted to near the baseband, and the frequency offset, which is the error between the local oscillator, which is the IF frequency at that time, and the carrier frequency of the received signal is estimated. That is,
The received signal input from the input terminal 131 is transmitted to the local oscillator 1
The signal from F.32 is multiplied by the multiplier 133 to obtain a signal in the IF frequency band. This signal is passed through a bandpass filter 13
9 and branch off, one of which is a frequency offset estimator 1
37 and estimate the frequency offset. And
The multiplier 135 and the delay element 136 perform a phase integration process on the estimated frequency offset, output a phase error due to the frequency offset from the multiplier 135, and output the output signal of the band-pass filter 139 and the multiplier. 134
To obtain a complete baseband signal and output it from the signal output terminal 138.

<Application Example 2> FIG. 7 shows a CDMA (Code Division Multipl) employing the frequency offset estimator of the present invention.
e) shows the receiving equipment of the base station. In the figure,
140 is a bandpass filter, 141 is a received signal input terminal, 142 is a local oscillator, 143 to 145 are multipliers,
46 is a delay element, 147 is a frequency offset estimator, 1
48 is an external pilot signal storage circuit, 149 to 151 are frequency offset compensators (AFC), 152 to 154 are CDMA receivers, and 155 to 157 are demodulated signal output terminals. In CDMA, several users simultaneously communicate using the same wireless band. Therefore, the signals of several users are mixed in the received signal. Further, strictly speaking, the radio carrier frequency is slightly different for each user. The receiving equipment of FIG. 7 is configured to demodulate the signals of all these users.

In the case of the second application example, similarly to the first application example shown in FIG. 6, the received signal converted to the IF frequency band by the local oscillator 142 is branched into # 1 to #N. Input to frequency offset compensators 149-151.

Different pilot signals are downloaded from the external pilot signal storage circuit 148 to the pilot signal storage elements in each of the frequency offset compensators 149 to 151. Therefore, in each of the frequency offset compensators 149 to 151, the IF frequency of the received signal is removed by the frequency offset estimator 147, the multipliers 144 and 145, and the delay element 146 as described with reference to FIG. It should be noted here that in the frequency offset compensators 149 to 151, only the signal containing the pattern downloaded by the pilot signal storage circuit 148 in the signal, that is, only the desired signal is converted to baseband, and the other signals are converted to baseband. There is no guarantee that it will be converted to. Each output of the frequency offset compensators 149 to 151 is input to each of the receivers 152 to 154 to obtain a demodulated signal.

FIG. 8 shows the configuration of the CDMA receivers 152 to 154 used in the CDMA receiving equipment of FIG. In the figure, 161 is an input terminal, 162 is a delay circuit, 163 to
165 is a matched filter for despreading, 166 to 168
Is a multiplier, 169 is an adder, 170 is an adaptive control unit, 17
1 is a demodulated signal output terminal. The configuration of this receiver is a so-called Rake receiver, and the SNR (Signal-to-Noise Ratio) is obtained by performing in-phase addition of the delayed wave in addition to the preceding wave.
Can be maximized.

As a configuration of the adaptive control unit 170, since the frequency offset has already been removed, the LMS (Least Mean Square) which is an algorithm based on the linear estimation theory is used.
e) The RLS (Recursive Least Squares) method or the like can be applied. The following shows an algorithm when the LMS method is applied as an example. First, the matched filter 163
To 165 is expressed as Z _k = [z _{k, 1} z _{k, 2} …
z _{k, M} ] ^T, and the coefficient vector from the adaptive control unit 170 is W _k = [w _{k, 1} w _{k, 2} ... w _{k, M} ] ^T. Here, M is the number of matched filters. At that time,

(Equation 15) A demodulated signal can be obtained by the following algorithm. Here, D _k is a known symbol pattern called a discrimination value of W _k ^H Z _k or a training signal.

FIG. 9 shows the matched filters 163 to 163 of FIG.
165 shows a specific circuit configuration. The figure shows an example of the configuration when the spreading factor is 4. In the figure, 240 is an input terminal, 241 to 243 are delay elements, 244 to 247 are spreading code input terminals, 248 to 251 are multipliers, 252 is an adder, and 253 is an output terminal.

<Application Example 3> FIG. 10 shows a configuration of a multi-user receiving facility to which the frequency offset estimator of the present invention is applied. In the figure, 181 is a reception signal input terminal, 182 is a local oscillator, 183 is a multiplier, 184 is a bandpass filter, 185 is a frequency offset estimator, 186 is an external pilot signal storage circuit, and 187 to 190 are pilot signal download functions. With frequency offset estimator, 19
1 is a multi-user receiver, and 192 to 194 are demodulated signal output terminals.

In the multi-user receiving equipment having this configuration, the frequency offset of the signal included in the received signal is determined by using the frequency offset estimators 187 to 187 having the pulse signal download function.
Estimate at 190. The estimated value of the frequency offset of each user is input to the multi-user receiver 191. The multi-user receiver 191 collectively demodulates each user's signal using an estimated value of the frequency offset of each user and a known signal embedded between information sequences called a training sequence. The demodulated signal is output from output terminals 192 to 194.

FIG. 11 shows a first configuration example of the multi-user receiver 191 shown in FIG. FIG. 1 shows a configuration example of a four-user receiver. In the figure, 261 is an input terminal,
262 to 265 are input terminals of the estimated offset frequency, 266 is a subtractor, 267 is a squaring circuit, 268 is a maximum likelihood estimator (MLE), 2
69 to 272 are replica generators, 273 is an adaptive control unit for estimating the transmission path impulse response of each user, and 274 to 277 are demodulated signal output terminals. In the figure, a replica is generated by adding a frequency offset information to a normal multi-user receiver to obtain a demodulated signal having the highest likelihood.

FIG. 12 shows a specific configuration of the replica generator employed in the multi-user receiver of FIG. In the figure, 281 is an input terminal, 282 is a delay circuit, 283
288 are multipliers, 289 is the adaptive control unit 273 of FIG.
290 is an adder, 29
1 is a delay element, 292 is an offset frequency input terminal, 2
93 is a replica output terminal.

In this replica generator, the input terminal 281
From the delay circuit 282 and the multipliers 283 to 28
6 and FIR (Finite Impulse Response)
Convolve with the filter to get the baseband replica. On the other hand, by integrating the offset frequency signal from the offset frequency input terminal 292 by the multiplier 288 and the delay element 291, a phase fluctuation component due to the offset frequency is calculated. A multiplier of the received signal is generated by a multiplier 287 by multiplying this phase fluctuation component by a baseband replica.
Output to E circuit 268.

FIG. 13 shows the multi-user receiver 1 shown in FIG.
9 shows a configuration example of an MLE circuit 268 applied to the MLE 91. The figure shows a maximum likelihood estimating circuit for four users using a BPSK modulation signal. In the figure, reference numeral 301 denotes a signal input terminal from the squaring circuit 267 in FIG. Counter, 312 is a clock input terminal, 313, 3
14, 319 and 320 are demodulated signal output terminals and 315 to 3
Reference numeral 18 denotes a provisional judgment value output terminal.

In the MLE circuit 268, the binary counter 311 is driven by a clock to generate all of the four BPSK-modulated user signals. A replica of four users is generated based on the generated provisional determination value, and the square Euclidean distance between the replica and the received signal is determined by the switch circuit 30.
4 is input. A minimum value detector including a subtractor 308, a delay element 310, and a switch circuit 303 obtains a temporary determination value having the minimum squared Euclidean distance, and selects the same by the switch circuit 303 to output a demodulated signal.

The multi-user receiver 191 shown in FIG.
7, the frequency offset of each user is known, as in the case of the CDMA receivers 152 to 154 in FIG. 7, so that an algorithm based on a linear estimation theory such as LMS or RLS can be applied.

FIG. 14 shows a second configuration example of the multi-user receiver 191 shown in FIG. This is provided with a multi-beam antenna that receives a plurality of antenna elements, splits the signal into K beams, and adaptively forms a beam at each of K branch destinations. 10, reference numeral 330 denotes an input terminal of an offset frequency estimated by the frequency offset estimator in FIG. 10, 331 denotes an input terminal of a received signal received by N antenna elements, and 332 to 334 denote beamformers (BFN: Beam Forming Network), 335 to 337 are demodulated signal output terminals.

In the multi-user receiver having this configuration, the i-th beamformer cancels the first to i-1st user signals, and then outputs the SINR (Si
gnalto Interference and Noise Ratio) are controlled to maximize the antenna directivity. At this time, in order to accurately cancel the signal, by giving a phase rotation to each demodulated signal based on the estimated frequency offset, an algorithm based on the linear estimation theory can be used for the control algorithm, and a high interference suppression characteristic can be obtained. Can be achieved. Since the frequency offset differs for each user in an actual communication channel, a high communication quality can be achieved even in an actual communication channel by performing interference cancellation using the configuration shown in FIG.

FIG. 15 shows the multi-user receiver 1 shown in FIG.
19 shows a configuration example of a j-th beamformer BNF (j) in 91. In the figure, reference numerals 341 to 344 denote signal input terminals from the respective antenna elements, and reference numerals 345 to 351, 360, and 3 denote input terminals.
62, 367 to 369 are multipliers, 352 is an adder, 35
3 is a subtractor, 354 is a determiner, 355 is a switch circuit,
Reference numeral 356 denotes a known signal input terminal called a training signal, 357 denotes a demodulation signal output terminal, 358 denotes an adaptive control unit (Adaptive Weight Control), and 371 to 373 denote j-.
An input terminal for a signal demodulated by the first BFN (j-1),
364 is an input terminal of the estimated frequency offset;
1 denotes a delay element, 363 denotes an integrator, and 365 denotes a complex conjugate (·) ^* .

The adaptive control section 358 receives the output signal from the demodulated signal output terminal 357 as a desired signal, the output signal from the subtractor 353 as an error signal, the outputs from the multipliers 367 to 369, and the signals from the input terminals 341 to 344. The coefficients of the multipliers 345 to 351 are adaptively estimated using a linear estimation algorithm as a signal, for example, an LMS or RLS algorithm.

FIG. 16 shows a frequency offset estimation error characteristic by the RLS adaptive phase control method according to the prior art. The vertical axis represents the root mean square of the estimation error, and the horizontal axis represents the number of received symbols. This figure shows the characteristics of the AWGN channel and the two-path model (ISI), the one-wave co-channel interference (CCI), the one-wave co-channel interference, and the case where each channel is a two-path model (CCI + ISI). In FIG.
The characteristics were obtained under the conditions of NR = 0 dB and frequency offset ΔfT = 10 ⁻³ . Here, T represents a symbol period. As can be seen from this characteristic, in the RLS adaptive phase control method, highly accurate estimation is possible in the AWGN channel, but as soon as interference enters, degradation starts, and CCI +
Only an estimation accuracy of about 10 ⁻² is obtained on the ISI transmission line.

FIG. 17 shows a characteristic example of the present invention. The conditions were the same as in the case of acquiring the characteristics of the conventional example shown in FIG. 1
The characteristics were evaluated using only the training signal of 40 symbols. 140 when the frequency offset ΔfT = 10 ⁻³
Although a slight estimation error is seen in the training signal section of the symbol because the phase does not rotate by 2π, the estimation error is 3
It can be seen that the characteristics are excellent to drive down to × 10 ^-4 .

[0072]

According to the present invention, frequency offset estimation can be performed with high accuracy under severe co-channel interference / inter-symbol interference environment. The use of this high-precision frequency offset information not only improves the communication quality of the base station receiver in mobile communication systems, but also enables the use of adaptive arrays and multi-user receivers with powerful interference compensation functions in real communications. Make it applicable.

That is, in order to use a multi-user receiver that requires channel estimation based on the linear estimation theory for actual communication, it is necessary to accurately estimate a frequency offset different for each user even under poor environmental conditions. Although the offset estimator was essential, the present invention solves this problem, and enables a multi-user receiver that can greatly increase the frequency use efficiency to be introduced into a commercial system, thereby improving the frequency use efficiency. Can be improved.

[Brief description of the drawings]

FIG. 1 is a block diagram of a frequency offset estimator according to a first embodiment of the present invention.

FIG. 2 is a block diagram of a delay circuit in the embodiment.

FIG. 3 is a block diagram of a frequency offset estimator according to a second embodiment of the present invention.

FIG. 4 is a block diagram of an eigenvector frequency estimating unit in the embodiment.

FIG. 5 is a block diagram of a frequency offset estimator according to a third embodiment of the present invention.

FIG. 6 is a block diagram of a receiving facility according to a fourth embodiment of the present invention.

FIG. 7 is a block diagram of a receiving facility according to a fifth embodiment of the present invention.

FIG. 8 is a block diagram of a receiver according to the fourth and fifth embodiments.

FIG. 9 is a block diagram of a matched filter in the receiver.

FIG. 10 is a block diagram of a receiving facility according to a sixth embodiment of the present invention.

FIG. 11 is a block diagram of a multi-user receiver according to the sixth embodiment.

FIG. 12 is a block diagram of a replica generator in the multi-user receiver.

FIG. 13 is a block diagram of a maximum likelihood estimation circuit (MLE) in the multi-user receiver.

FIG. 14 is a block diagram showing another configuration example of the multi-user receiver according to the sixth embodiment.

FIG. 15 is a block diagram of a j-th beamformer BFN (j) in the multiuser receiver.

FIG. 16 is a graph showing characteristics of a conventional example.

FIG. 17 is a graph showing characteristics of the present invention.

FIG. 18 is a block diagram of a conventional Costas-type carrier regenerator.

FIG. 19 is a block diagram of a conventional quadrature detector.

FIG. 20 is a block diagram of a conventional inverse transform type carrier regenerator.

FIG. 21 is a block diagram of a conventional delay detector with a frequency offset compensation function.

FIG. 22 is a block diagram of a conventional RLS phase control circuit.

FIG. 23 is a block diagram of a frequency offset estimator to which a conventional DFT is applied.

[Explanation of symbols]

 Reference Signs List 102 pilot signal storage element 103 delay circuit 104 eigenvalue decomposition section 105 correlation matrix calculation section 114 pilot signal storage element 113 delay circuit 115 correlation matrix calculation section 116 eigenvalue decomposition section 117 eigenvector frequency estimation section 123 pilot signal storage element 124 delay circuit 125 correlation Matrix operation unit 126 eigenvalue decomposition unit 127 eigenvector frequency estimation unit 128 DFT 130 maximum value detection unit

Claims (4)

[Claims] 1. A frequency offset estimating method in a broadcast or communication receiving method for estimating a carrier frequency of a received signal, converting a carrier band to a baseband band based on the estimation result, and demodulating the signal. A multiplication process of multiplying a signal by a known signal; a delay process of outputting a result output of the multiplication process at predetermined time intervals; and a correlation matrix calculation process of calculating a correlation matrix of a vector having an output of the delay process as an element. An eigenvalue decomposition process for obtaining an eigenvalue of a correlation matrix that is a result output of the correlation matrix calculation process, and outputting an eigenvector corresponding to a maximum eigenvalue as a carrier waveform. 2. A frequency offset estimating method in a broadcast or communication receiving method for estimating a carrier frequency of a received signal, converting a carrier band to a baseband band based on the estimation result, and demodulating the signal. A multiplication process of multiplying a signal by a known signal; a delay process of outputting a result output of the multiplication process at predetermined time intervals; and a correlation matrix calculation process of calculating a correlation matrix of a vector having an output of the delay process as an element. And estimating the maximum value of the frequency component included in the eigenvector corresponding to the maximum eigenvalue, and estimating and outputting the eigenvalue of the correlation matrix that is the result output of the correlation matrix operation process. . 3. A frequency offset estimator in a broadcasting or communication receiving facility for estimating a carrier frequency of a received signal, converting a carrier band to a baseband band based on the estimation result, and demodulating the signal. Multiplication means for multiplying a signal by a known signal; delay means for outputting an output of the multiplication means at predetermined time intervals; correlation matrix calculation means for calculating a correlation matrix of a vector having an output of the delay means as an element; A frequency offset estimator comprising: an eigenvalue of a correlation matrix which is an output of the correlation matrix calculating means; and an eigenvalue decomposition means for outputting an eigenvector corresponding to a maximum eigenvalue as a carrier waveform. 4. A frequency offset estimator in a broadcast or communication receiving facility for estimating a carrier frequency of a received signal, converting a carrier band to a baseband band based on the estimation result, and demodulating the signal. Multiplication means for multiplying a signal by a known signal; delay means for outputting an output of the multiplication means at predetermined time intervals; correlation matrix calculation means for calculating a correlation matrix of a vector having an output of the delay means as an element; A frequency offset estimator comprising: an eigenvalue of a correlation matrix which is an output of the correlation matrix calculating means, and estimating means for estimating and outputting a maximum value of a frequency component included in an eigenvector corresponding to the maximum eigenvalue. .