JP3423274B2 - Wireless device - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a configuration of a wireless device capable of changing antenna directivity in real time, and more particularly to a configuration of a wireless device used in an adaptive array wireless base station.

[0002]

2. Description of the Related Art In recent years, various transmission channel allocation methods have been proposed in the mobile communication system in order to effectively use frequencies, and some of them have been put into practical use.

FIG. 9 shows frequency division multiple access.
FIG. 4 is a diagram showing the arrangement of channels in various communication systems of vision multiple access (FDMA), time division multiple access (TDMA), and PDMA (path division multiple access).

First, referring to FIG. 9, FDMA and TDM
A and PDMA will be briefly described. FIG. 9 (a)
FIG. 3 is a diagram showing FDMA, showing different frequencies f1 to f4.
, The analog signals of users 1 to 4 are frequency-divided and transmitted, and the signals of users 1 to 4 are separated by a frequency filter.

In the TDMA shown in FIG. 9B, the digitized signal of each user has different frequencies f1 to f1.
The signal of each user is transmitted as a radio wave of f4 by being time-divided at fixed time intervals (time slots), and the signals of each user are separated by the frequency filter and the time synchronization between the base station and each user mobile terminal device.

On the other hand, recently, the PDMA system has been proposed in order to increase the frequency utilization efficiency of radio waves due to the widespread use of portable telephones. As shown in FIG. 9C, this PDMA system spatially divides one time slot in the same frequency and transmits data of a plurality of users. In this PDMA, the signal of each user is separated by using a frequency filter, time synchronization between the base station and each user mobile terminal device, and a mutual interference canceling device such as an adaptive array.

The operating principle of such an adaptive array radio base station is described in the following document, for example.

B. Widrow, et al .: “Adaptive Antenna
Systems, "Proc. IEEE, vol.55, No.12, pp.2143-2159
(Dec. 1967). SP Applebaum: “Adaptive Arrays”, IEEE Trans.
Antennas & Propag., Vol.AP-24, No.5, pp.585-598
(Sept. 1976). OL Frost, III: “Adaptive Least Squares Optimiz
ation Subject to Linear Equality Constraints, "SEL
-70-055, Technical Report, No.6796-2, Information
System Lab., Stanford Univ. (Aug. 1970). B. Widrow and SD Stearns: “Adaptive Signal Pr
ocessing, "Prentice-Hall, Englewood Cliffs (198
Five). RA Monzingo and TW Miller: “Introduction t
o Adaptive Arrays, "John Wiley & Sons, New York (1
980). JE Hudson: “Adaptive Array Principles,” Peter P
eregrinus Ltd., London (1981). RT Compton, Jr .: “Adaptive Antennas − Concept
s and Performance, "Prentice-Hall, Englewood Cliffs
(1988). E. Nicolau and D. Zaharia: “Adaptive Arrays,” Els
evier, Amsterdam (1989). FIG. 10 is a schematic diagram conceptually showing the operating principle of such an adaptive array radio base station. In FIG. 10, one adaptive array radio base station 1 is provided with an array antenna 2 composed of n antennas # 1, # 2, # 3, ..., #n, and its radio wave reaches the first range. It is shown as a shaded area 3. On the other hand, the range in which the radio waves of other adjacent radio base stations 6 reach is represented as a second shaded area 7.

In the area 3, a radio signal is transmitted and received between the mobile phone 4 which is the terminal of the user A and the adaptive array radio base station 1 (arrow 5). On the other hand, in the area 7, a radio signal is transmitted and received between the mobile phone 8 which is the terminal of another user B and the radio base station 6 (arrow 9).

[0010] Here, the mobile phone 4 of the user A happens to occur.
When the frequency of the radio wave signal of B is equal to the frequency of the radio wave signal of the mobile phone 8 of the user B, the radio wave signal from the mobile phone 8 of the user B becomes an unnecessary interference signal in the area 3 depending on the position of the user B. It will be mixed in the radio signal between the mobile phone 4 of the user A and the adaptive array radio base station 1.

As described above, in the adaptive array radio base station 1 which receives the mixed radio wave signals from both the users A and B, if the user A does not perform any processing.
A signal in which signals from both B and B are mixed is output, and the call of the user A who should originally call is hindered.

[Construction and Operation of Conventional Adaptive Array Antenna] In the adaptive array radio base station 1,
In order to remove the signal from the user B from the output signal, the following processing is performed. FIG. 11 is a schematic block diagram showing the configuration of the adaptive array radio base station 1.

First, assuming that the signal from the user A is A (t) and the signal from the user B is B (t), the received signal x1 (at the first antenna # 1 constituting the array antenna 2 of FIG. t) is expressed by the following equation: x1 (t) = a1 * A (t) + b1 * B (t) where a1 and b1 are coefficients that change in real time as described later.

Next, the received signal x at the second antenna # 2
2 (t) is expressed by the following equation: x2 (t) = a2 * A (t) + b2 * B (t) where a2 and b2 are coefficients that similarly change in real time.

Next, the received signal x at the third antenna # 3
3 (t) is expressed by the following equation: x3 (t) = a3 * A (t) + b3 * B (t) where a3 and b3 are similarly coefficients that change in real time.

Similarly, the received signal xn (t) at the nth antenna #n is expressed by the following equation: xn (t) = an × A (t) + bn × B (t) where: Similarly, an and bn are coefficients that change in real time.

The above coefficients a1, a2, a3, ..., An
Is the array antenna 2 for the radio signal from the user A.
The antennas # 1, # 2, # 3, ..., #n configuring the antennas have different relative positions (for example, the antennas are spaced from each other by 5 times the wavelength of the radio signal, that is, about 1 meter. Are arranged), and there is a difference in the reception intensity at each antenna.

Further, the above coefficients b1, b2, b3, ...
Similarly, bn also indicates that a radio signal from the user B has a difference in reception intensity at each of the antennas # 1, # 2, # 3, ..., #n. As each user is moving, these coefficients change in real time.

Signal x1 received by each antenna
(T), x2 (t), x3 (t), ..., xn (t) are
Corresponding switches 10-1, 10-2, 10-3, ...
The weight vector control unit 11 enters the receiving unit 1R configuring the adaptive array radio base station 1 via 10-n.
To the corresponding multipliers 12-1 and 12
, -2, 12-3, ..., 12-n are respectively applied to one input.

Weights w1, w2, w3, ..., Wn for received signals at the respective antennas are applied from the weight vector control unit 11 to the other inputs of these multipliers. These weights are calculated in real time by the weight vector control unit 11 as described later.

Therefore, the received signal x at antenna # 1
1 (t) passes through the multiplier 12-1 and then w1 × (a1A
(T) + b1B (t)), and the received signal x2 (t) at the antenna # 2 passes through the multiplier 12-2 and becomes w2 × (a
2A (t) + b2B (t)), and the received signal x3 (t) at the antenna # 3 passes through the multiplier 12-3 and becomes w3 ×.
(A3A (t) + b3B (t)), and the received signal xn (t) at the antenna #n becomes wn × (anA (t) + bnB (t)) via the multiplier 12-n.

These multipliers 12-1, 12-2, 12
The outputs of −3, ..., 12-n are added by the adder 13,
The output is as follows: w1 (a1A (t) + b1B (t)) + w2 (a2A
(T) + b2B (t)) + w3 (a3A (t) + b3B
(T)) + ... + wn (anA (t) + bnB (t)) This is divided into a term related to the signal A (t) and a term related to the signal B (t) as follows: (w1a1 + w2a2 + w3a3 + ... + wnan) A
(T) + (w1b1 + w2b2 + w3b3 + ... + wnb
n) B (t) Here, as will be described later, the adaptive array radio base station 1 identifies the users A and B, and the weights w1, w2, w3 are set so that only the signals from the desired users can be extracted.
..., calculate wn. For example, in the example of FIG. 11, the weight vector control unit 11 extracts coefficients A1, a in order to extract only the signal A (t) from the user A who should originally make a call.
, A, b1, b2, b3, ..., bn are regarded as constants so that the coefficient of the signal A (t) is 1 as a whole and the coefficient of the signal B (t) is 0 as a whole. Weight w
1, w2, w3, ..., Wn are calculated.

That is, the weight vector control unit 11
Solves the signal A by solving the following system of linear equations
Calculate the weights w1, w2, w3, ..., Wn in which the coefficient of (t) is 1 and the coefficient of the signal B (t) is 0: w1a1 + w2a2 + w3a3 + ... + wnan = 1 w1b1 + w2b2 + w3b3 + ... + wnbn = 0 This simultaneous linear equation Although the explanation of the solution is omitted, it is well known as described in the documents listed above, and is already put into practical use in the adaptive array radio base station.

Thus, the weights w1, w2, w3, ..., W
By setting n, the output signal of the adder 13 becomes as follows: Output signal = 1 × A (t) + 0 × B (t) = A (t) [User identification, training signal] The identification of the users A and B is performed as follows.

FIG. 12 is a schematic diagram showing the frame structure of a radio signal of a mobile phone. The radio signal of the mobile phone is mainly composed of a preamble composed of a signal sequence known to the radio base station and data (voice etc.) composed of a signal sequence unknown to the radio base station.

The signal sequence of the preamble includes a signal sequence of information for distinguishing whether the user is a desired user to talk to the radio base station. Weight vector control unit 11 of adaptive array radio base station 1
11 (FIG. 11) compares the training signal corresponding to the user A extracted from the memory 14 with the received signal sequence, and extracts the signal which seems to include the signal sequence corresponding to the user A. Performs vector control (determination of weight). The signal of the user A extracted in this way is externally output from the adaptive array radio base station 1 as an output signal SRX (t).

On the other hand, in FIG. 11, an input signal STX (t) from the outside enters the transmission unit 1T which constitutes the adaptive array radio base station 1, and is fed into the multipliers 15-1, 15-2,
15-3, ..., 15-n are given to one input. The weights w1, w2, w3, ..., Wn previously calculated by the weight vector control unit 11 based on the received signal are copied and applied to the other inputs of these multipliers.

The input signals weighted by these multipliers are sent to the corresponding switches 10-1, 10-2, 10
−3, ..., 10-n, the corresponding antenna # 1,
#N, # 2, # 3, ..., #n, and within area 3 in FIG.

Here, the signal transmitted using the same array antenna 2 as at the time of reception is the same as that of the received signal by the user A.
Since the target radio wave is weighted, the transmitted radio signal is received by the mobile phone 4 of the user A as if it had directivity to the user A. FIG. 13 is a diagram showing an image of transmission and reception of a radio signal between the user A and the adaptive array radio base station 1 as described above. Compared with the area 3 in FIG. 10 which shows the range in which radio waves actually reach, as shown in the virtual area 3 a in FIG. 13, the directivity is set from the adaptive array radio base station 1 to the mobile phone 4 of the user A as a target. Along with this, the image of the radio signal being radiated is visualized.

[0030]

As mentioned above, the PDMA is used.
The scheme requires a technique to remove co-channel interference. In this respect, the adaptive array that adaptively directs the null to the interference wave is an effective means because it can effectively suppress the interference wave even when the level of the interference wave is higher than the level of the desired wave.

By the way, when an adaptive array is used for the base station, it is possible not only to eliminate interference at the time of reception but also to reduce unnecessary radiation at the time of transmission. At this time, as the array pattern at the time of transmission, an array pattern at the time of reception may be used or a method of newly generating from the result of the DOA estimation or the like. The latter is FDD (Frequency Divi)
Although it can be applied regardless of whether it is a sion duplex or TDD (Time Division Duplex), complicated processing is required. On the other hand, when the former is used for FDD, the array pattern of transmission and reception is different, and therefore, the array arrangement and the weight must be corrected. Therefore, in general, application in TDD is premised, and good characteristics are obtained in an environment where external slots are continuous.

As described above, in the TDD / PDMA system using the adaptive array in the base station, when the array pattern (weight vector pattern) obtained in the uplink is used in the downlink, there is a motion with angular spread. When a typical Rayleigh propagation factor is assumed, the transmission directivity may deteriorate in the downlink due to the time difference between the uplink and the downlink.

That is, there is a time interval from the transmission of radio waves from the user terminal to the base station on the uplink (uplink) to the emission of the radio waves from the base station to the user terminal on the downlink (downlink). Therefore, when the moving speed of the user terminal cannot be ignored, the transmission directivity deteriorates due to an error between the emission direction of the radio wave from the base station and the actual direction in which the user terminal exists.

As a method of estimating the downlink weight in consideration of such channel fluctuations, a method of estimating the downlink transmission response vector by extrapolation using the reception response vector obtained in the uplink is proposed. Has been done.

However, if there is an estimation error in the reception response vector estimated in the uplink due to noise of the received signal or sampling error, an error will occur in the result of the extrapolation processing, and the transmission response vector in the downlink will be accurately estimated. I can't
As a result, there is a problem that good transmission directivity control cannot be performed.

The present invention has been made in order to solve the above-mentioned problems. Even if there is an estimation error in the reception response vector estimated in the uplink, the transmission response vector in the downlink is calculated. It is an object of the present invention to provide a wireless device that can be accurately estimated and, in turn, can perform good transmission directivity control.

[0037]

SUMMARY OF THE INVENTION The present invention is a radio apparatus for changing the antenna directivity in real time and transmitting and receiving signals to and from a plurality of terminals in a time division manner. , And a transmission circuit and a reception circuit that share a plurality of antennas when transmitting and receiving signals,
The reception circuit, when receiving the reception signal, based on the signals from the plurality of antennas, the reception signal separation means for separating a signal from a specific terminal among the plurality of terminals, and a plurality of reception signal separation means when receiving the reception signal. Based on the signal from the antenna, including the reception propagation path estimation means for estimating the reception response vector of the propagation path from the specific terminal, the transmission circuit, based on the estimation result of the reception propagation path estimation means, of the transmission signal A transmission channel estimating means for estimating the transmission response vector of the channel during transmission,
Transmission directivity control means for updating the antenna directivity at the time of transmitting the transmission signal based on the estimation result of the transmission channel estimation means. The transmission channel estimation means is an extrapolation process based on a plurality of reception response vectors of the uplink slot from the specific terminal estimated by the reception channel estimation means, and the transmission response vector of the downlink slot to the specific terminal. An extrapolation means for calculating, a storage means holding a plurality of parameters used in the extrapolation processing, which is predetermined according to the propagation environment of the propagation path, and a propagation environment of the propagation path, And selecting means for selecting a parameter corresponding to the estimated propagation environment from among the parameters and applying it to the extrapolation processing by the extrapolating means.

According to the present invention, even if there is an estimation error in the reception response vector estimated in the uplink, by selecting the parameter used for the extrapolation processing according to the propagation environment of the propagation path, The transmission response vector can be accurately estimated, and good transmission directivity control can be realized.

Preferably, the parameter is an extrapolation distance in the extrapolation processing by the extrapolation means, and the storage means holds and selects a plurality of extrapolation distances determined in advance in accordance with the Doppler frequency representing the propagation environment. The means estimates the Doppler frequency of the propagation path, selects the extrapolation distance corresponding to the estimated Doppler frequency from the held extrapolation distances, and applies it to the extrapolation processing by the extrapolation means.

According to the present invention, the extrapolation error increases as the extrapolation distance in extrapolation increases if the uplink reception response vector has an estimation error. Therefore, according to the Doppler frequency representing the propagation environment. By selecting the extrapolated distance, it is possible to accurately estimate the transmission response vector.

More preferably, the selecting means selects a shorter extrapolation distance as the estimated Doppler frequency is lower, and a longer extrapolation distance as the estimated Doppler frequency is higher.

According to the present invention, the lower the Doppler frequency, the smaller the fluctuation of the propagation environment. Therefore, the extrapolation is prevented from being performed more than the actual fluctuation amount by shortening the extrapolation distance, and the higher the Doppler frequency, the more the propagation. Since the environment changes greatly, extrapolation can be performed sufficiently by increasing the extrapolation distance.

More preferably, the parameter is an extrapolation distance in extrapolation processing by the extrapolation means, and the storage means is
Retaining a plurality of extrapolation distances that are predetermined in accordance with the signal error between the separated signal and the expected desired signal, which represents the propagation environment, and the selecting means estimates the signal error in the propagation path,
An extrapolation distance corresponding to the estimated signal error is selected from the held extrapolation distances and applied to the extrapolation processing by the extrapolation means.

According to the present invention, the extrapolation distance corresponding to the signal error representing the propagation environment is selected in view of the fact that the estimation error of the uplink reception response vector increases and the extrapolation error also increases if the signal error is large. By doing so, it is possible to accurately estimate the transmission response vector.

More preferably, the selecting means selects a shorter extrapolation distance as the estimated signal error is larger, and selects a longer extrapolation distance as the estimated signal error is smaller.

According to the present invention, since the extrapolation error increases as the signal error increases, the extrapolation error is suppressed by shortening the extrapolation distance, and the extrapolation error decreases as the signal error decreases. Sufficient extrapolation can be performed by increasing the distance.

More preferably, the parameter is an extrapolation distance in extrapolation processing by the extrapolation means, and the storage means is
The Doppler frequency that represents the propagation environment, and a plurality of extrapolation distances that are predetermined according to the signal error between the separated signal and the expected signal are held, and the selection means includes the Doppler frequency and the signal of the propagation path. The error is estimated, and the extrapolation distance corresponding to the estimated Doppler frequency and the signal error is selected from the held extrapolation distances and applied to the extrapolation processing by the extrapolation means.

According to the present invention, in view of the fact that the Doppler frequency and the signal error increase the extrapolation error, an accurate transmission response vector is selected by selecting the extrapolation distance according to the Doppler frequency and the signal error representing the propagation environment. Can be estimated.

More preferably, the selecting means tentatively selects the extrapolation distance corresponding to the estimated Doppler frequency, and corrects the tentatively selected extrapolation distance corresponding to the estimated signal error.

According to the present invention, the basic extrapolation distance is selected by the Doppler frequency having a great influence on the extrapolation error, and the extrapolation distance is corrected based on the signal error, so that more accurate transmission can be achieved. It is possible to estimate the response vector.

More preferably, the relationship between the propagation environment and the plurality of parameters is individually determined for each radio device.

According to the present invention, since the correspondence between the propagation environment and the parameter is obtained for each individual radio device by pre-measurement, it is possible to estimate the transmission response vector with higher accuracy.

More preferably, the relationship between the propagation environment and the plurality of parameters is commonly determined by the plurality of wireless devices.

According to the present invention, when the individual difference between wireless devices is small, the correspondence between the propagation environment and the parameters is made common among a plurality of wireless devices, thereby simplifying the manufacturing process of the wireless devices. Can be planned.

[0055]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS [First Embodiment] FIG. 1 is a schematic block diagram showing a configuration of a radio apparatus (radio base station) 1000 of a PDMA base station according to an embodiment of the present invention.

In the configuration shown in FIG. 1, the user PS
4 antennas # 1 to # 1 in order to distinguish 1 from PS2.
# 4 is provided. However, the number of antennas may be more generally N (N: natural number).

In transmission / reception system 1000 shown in FIG. 1, signals are received from antennas # 1 to # 4 and received by corresponding user, for example, receiving unit SR1 and user PS1 for separating signals from user PS1. A transmitter ST1 for transmitting a signal is provided. Antenna #
The connections between 1 to # 4 and the receiving section SR1 and the transmitting section ST1 are selectively switched by the switches 10-1 to 10-4.

That is, received signals RX1 (t), RX2 (t), RX3 (t), received by the respective antennas,
RX4 (t) is the corresponding switch 10-1, 10-
2, 10-3, 10-4 via the receiving section SR1,
It is given to the reception weight vector calculator 20 and the reception response vector calculator 22, and the corresponding multiplier 12-
It is given to one input of 1, 12-2, 12-3, 12-4, respectively.

To the other inputs of these multipliers, the weighting factors wrx11, wrx21, wr for the reception signals from the reception weight vector calculator 20 for the respective antennas are input.
x31 and wrx41 are applied. These weighting factors are calculated by the reception weight vector calculator 20 as in the conventional example.
Is calculated in real time.

The transmitter ST1 receives the reception response vector calculated by the reception response vector calculator 22, and estimates the propagation path at the time of transmission, that is, the virtual reception response at the time of transmission, as will be described later. A transmission response vector estimator 32 that obtains a transmission response vector by estimating a vector, a memory 34 that transmits and receives data between the transmission response vector estimator 32, and stores and holds the data, and a transmission response vector estimator 32. Transmission weight vector calculator 3 for calculating a transmission weight vector based on the estimation result
0, the transmission signal is received at one input, and the weight coefficient wtx from the transmission weight vector calculator 30 is received at the other input.
Multipliers 15-1, 15-2, 15-3 and 15-4 to which 11, wtx21, wtx31 and wtx41 are applied are included. Multipliers 15-1, 15-2, 15-3, 15-4
The output from is via the switches 10-1 to 10-4,
Antennas # 1 to # 4 are provided.

Although not shown in FIG. 1, the same configuration as the receiving section SR1 and the transmitting section ST1 is provided for each user.

[Operation Principle of Adaptive Array] The operation of the receiver SR1 will be briefly described as follows.

Received signal RX1 received by the antenna
(T), RX2 (t), RX3 (t), RX4 (t) are
It is expressed by the following formula.

[0064]

[Equation 1]

Here, the signal RXj (t) is the j-th (j
= 1, 2, 3, 4, 4), and the signal Srxi (t) represents the signal transmitted by the i-th (i = 1, 2) user.

Further, the coefficient hji represents the complex coefficient of the signal from the i-th user received by the j-th antenna, and nj (t) represents the noise included in the j-th received signal. .

The above equations (1) to (4) are expressed in vector form as follows.

[0068]

[Equation 2]

In equations (6) to (8), [...] T
Indicates the transposition of [...]. Here, X (t) is the input signal vector, Hi is the reception response vector of the i-th user,
N (t) indicates a noise vector, respectively.

As shown in FIG. 1, the adaptive array antenna multiplies the input signals from the respective antennas by the weighting factors wrx1i to wrx4i and outputs the resultant signal as the received signal SRX (t).

With the above preparations, the operation of the adaptive array when extracting the signal Srx1 (t) transmitted by the first user is as follows.

Output signal y1 of adaptive array 100
(T) can be expressed by the following equation by multiplying the vector of the input signal vector X (t) and the weight vector W1.

[0073]

[Equation 3]

That is, the weight vector W1 is a weighting factor w by which the j-th input signal RXj (t) is multiplied.
It is a vector whose elements are rxj1 (j = 1, 2, 3, 4).

Here, y1 represented by the equation (9)
Substituting the input signal vector X (t) expressed by the equation (5) into (t) gives the following.

[0076]

[Equation 4]

When the adaptive array 100 operates ideally, the weight vector W1 is sequentially controlled by the well-known method by the weight vector control unit 11 so as to satisfy the following simultaneous equations.

[0078]

[Equation 5]

When the weight vector W1 is completely controlled so as to satisfy the expressions (12) and (13), the output signal y1 (t) from the adaptive array 100 is finally expressed by the following expression.

[0080]

[Equation 6]

That is, the output signal y1 (t) contains the signal Sr transmitted by the first user of the two users.
x1 (t) will be obtained.

[Outline of Operation of Radio Equipment 1000] FIG. 2
3 is a flowchart for explaining an outline of a basic operation of the wireless device 1000 which is a premise of the present invention.

In radio apparatus 1000, attention is paid to the fact that the weight vector (weighting coefficient vector) of the adaptive array can be uniquely expressed by the reception response vector of each antenna element, and the time variation of the reception response vector is estimated to indirectly To estimate the weight.

First, the receiver SR1 estimates the propagation path of the received signal based on the received signal (step S).
100). The estimation of the propagation path corresponds to obtaining the impulse response of the signal sent from the user in the equations (1) to (4).

In other words, in equations (1) to (4), for example, if the reception response vector H1 can be estimated,
It is possible to estimate the transmission path when the signal from the user PS1 is received.

Next, the transmission response vector estimator 32
Predicts the propagation path at the time of transmission, that is, the reception response vector at the time of transmission from the reception response vector at the time of reception (step S102). This predicted reception response vector corresponds to the transmission response vector at the time of transmission.

Further, the transmission weight vector calculator 30
Calculates the transmission weight vector based on the predicted transmission response vector, and the multipliers 15-1 to 15-4
(Step S104).

[Operation of Reception Response Vector Calculator 22] Next, the basic operation of the reception response vector calculator 22 shown in FIG.

First, assuming that the number of antenna elements is four and the number of users communicating at the same time is two, the signals output from the receiving circuit via each antenna are expressed by the above equations (1) to (4).
It is represented by.

At this time, if the equations in which the received signals of the antennas represented by the equations (1) to (4) are represented by vectors are rewritten, the following equations (5) to (8) are obtained.

[0091]

[Equation 7]

Here, when the adaptive array operates well, the signals from each user are separated and extracted, so that the signals Srxi (t) (i = 1, 2) are all known values. Become.

At this time, by utilizing the fact that the signal Srxi (t) is a known signal, the reception response vector H1 = [h
11, h21, h31, h41] and H2 = [h12, h22, h
32, h42] can be derived as described below.

That is, the received signal and the known user signal, for example, the signal Srx1 (t) from the first user
When the ensemble average (time average) is calculated by multiplying by, the result is as follows.

[0095]

[Equation 8]

In equation (16), E [...] Indicates the time average, and S * (t) is the conjugate complex of S (t).
If the time to take the average is long enough, the average value is as follows.

[0097]

[Equation 9]

Here, the value of equation (18) becomes 0 because
This is because the signal Srx1 (t) and the signal Srx2 (t) have no correlation with each other. The value of the equation (19) becomes 0 because there is no correlation between the signal Srx1 (t) and the noise signal N (t).

Therefore, the ensemble average of the equation (16) results in the reception response vector H as shown below.
Is equal to 1.

[0100]

[Equation 10]

By the above procedure, the reception response vector H1 of the signal transmitted from the first user PS1 can be estimated.

Similarly, the reception response vector H2 of the signal transmitted from the second user PS2 can be estimated by performing the ensemble averaging operation of the input signal vector X (t) and the signal Srx2 (t). Is.

The ensemble averaging as described above is performed, for example, on a predetermined number of data symbol sequences at the beginning and a predetermined number of data symbol sequences at the end in one time slot at the time of reception.

[Estimation of Transmission Response Vector] FIG. 3 is a conceptual diagram for explaining the basic operation of the transmission response vector estimator 32 which is the premise of the present invention. Consider an 8-slot configuration in which 4 users are assigned to each of the upper and lower lines as a PDMA burst. The slot configuration is such that, for example, the first 31 symbols are the first training symbol sequence, the subsequent 68 symbols are the data symbol sequence, and the last 31 symbols are the second training symbol sequence.

As described above, the training symbol sequences are provided at the beginning and the end of the uplink slot, and both reception response vectors are calculated using the algorithm of the reception response vector calculator 22 described above.

Then, the reception response vector for the downlink is estimated by extrapolation processing (linear extrapolation).

That is, if the value of any one element of the reception response vector at time t is f (t), the value f (t0) at the time t0 of the head training symbol sequence of the uplink slot and the uplink slot Based on the value f (t1) of the last training symbol sequence at time t1, the value f (t) at time t of the downlink slot is
It can be predicted as follows.

F (t) = [f (t1) -f (t0)] /
(T1−t0) × (t−t0) + f (t0) In the above description, a training symbol string is provided at the beginning and the end of the uplink slot, and primary extrapolation is performed. A training symbol string is also provided in the center of the slot, and the value f (t) at time t is calculated as 2 from the value of the reception response vector at three points in the uplink slot.
It is also possible to adopt a configuration in which the extrapolation is used for estimation. Alternatively, higher-order extrapolation can be performed by increasing the positions of the training symbol strings in the uplink slots.

The present invention relates to an improvement of the downlink (reception) response vector estimation method by such extrapolation processing, the details of which will be described later, and the transmission weight vector will be described first. The determination of will be described.

[Determination of Transmission Weight Vector] When the estimated value of the reception response vector at the time of transmission is obtained as described above, the transmission weight vector can be obtained by any of the following three methods.

I) Method by orthogonalization Weight vector W (1) (i) = [w of user PS1 at time t = iT (i: natural number, T: unit time interval)
tx11, wtx12, wtx13, wtx14]. In order to direct the null to the user PS2, the following conditions may be satisfied.

The propagation path (reception response vector) predicted for the user PS2 is V (2) (i) = [h1 '(2) (i),
h2 '(2) (i), h3' (2) (i), h4 '(2) (i)]. Here, hp '(q) (i) is p of the qth user.
It is a predicted value for the time i of the reception response vector for the th antenna. Similarly, it is assumed that the propagation path V (1) (i) has been predicted for the user PS1.

At this time, W (1) (i) TV (2) (i) = 0
W (1) (i) is determined so that The following conditions c1) and c2) are imposed as restraint conditions.

[0114] c1) W (1) (i) TV (1) (i) = g (constant value) c2) Minimize ‖W (1) (i) ‖.

The condition c2) corresponds to minimizing the transmission power. ii) Method Using Pseudo-Correlation Matrix Here, as described above, the adaptive array is composed of several antenna elements and a part for controlling each element weight value. Generally, when the input vector of the antenna is represented by X (t) and the weight vector is represented by W, the output Y (t) = WTX.
When the weight vector is controlled so as to minimize the mean square difference between (t) and the reference signal d (t) (MMSE criterion: least square error method criterion), the optimum weight Wopt is expressed by the following equation (Wiener solution). Given.

[0116]

[Equation 11]

However,

[0118]

[Equation 12]

It is necessary to satisfy. Here, YT represents the transpose of Y, Y * represents the complex region of Y, and E [Y] represents the ensemble average. This weight value causes the adaptive array to generate an array pattern so as to suppress unnecessary interference waves.

By the way, in the method using the pseudo correlation matrix, the above equation (21) is calculated by the pseudo correlation matrix described below.

That is, the weight vector W (k) (i) for the user k is calculated using the estimated complex received signal coefficient h '(k) n (i). Assuming that the array response vector of the kth user is V (k) (i), it can be obtained as follows, as described above.

[0122]

[Equation 13]

At this time, the autocorrelation matrix Rxx (i) of the virtual received signal at t = iT is expressed by the following equation using V (k) (i).

[0124]

[Equation 14]

However, N is a virtual noise term added because Rxx (i) is an integer. In the calculation in the present invention, for example, N = 1.0 × 10 −5.

Correlation vector rxd between received signal and reference signal
(I) is expressed by the following equation.

[0127]

[Equation 15]

Therefore, the weights for the downlink at time t = iT can be obtained from the equations (21), (25) and (26).

The inverse matrix calculation of the equation (25) can be optimally calculated for the user k by the inverse matrix lemma.
In particular, in the case of two users, the weight is calculated by the following simple formula.

[0130]

[Equation 16]

When the autocorrelation matrix is given in this way,
For the method of calculating the weight vector, see, for example, T. Ohgane, Y. Ogawa, and
K. Itoh, Proc. VTC'97, vol.
2, pp. 725-729, May 1997, or literature: Tanaka, Ohgane, Ogawa, Ito, IEICE Technical Report, vo
l. RCS98-117, pp. 103-108, Oc
t. 1998.

Iii) Method of directing beam to user PS1 Focusing only on the point of directing the beam to the user PS1, the following formula may be satisfied.

W (1) (i) = V (1) (i) * If any of the methods described above is used to determine the weight vector at the time of transmission and then the weight vector is transmitted, a dynamic Rayleigh signal such as angular spread can be obtained. When a propagation path is assumed, it is possible to suppress the deterioration of transmission directivity in the downlink caused by the time difference between the uplink and the downlink even in the TDD / PDMA system.

Next, FIG. 4 is a conceptual diagram for explaining the transmission response vector estimating principle of the present invention. The "ideal state" shown in the upper part of FIG. 4 is basically a further simplification of the conceptual diagram shown in FIG.

That is, based on the reception response vector 1 and the reception response vector 2 which are the reception response vectors of the two points in the same slot of the uplink calculated by the reception response vector calculator 22 of FIG. 1 in step S100 of FIG. By performing linear extrapolation up to the original transmission timing of the corresponding slot of the downlink, the correct transmission response vector of the downlink can be estimated.

Here, the "ideal state" in FIG. 4 is premised on that the reception response vectors 1 and 2 have no estimation error.

However, as shown in the case "including the response vector estimation error" in the lower part of FIG. 4, for example, the reception response vector 2 has an error such as the reception response vector 2'because of an estimation error due to noise or sampling error. If a linear extrapolation is performed (at the same extrapolation distance) on the basis of these reception response vectors 1 and 2 ′, the transmission response vector at the transmission timing is further deviated. Therefore, the wrong transmission response vector will be estimated.

Therefore, if the transmission weight vector calculator 30 of FIG. 1 performs the transmission weight determination processing (step S104 of FIG. 2) based on such an incorrect transmission response vector, the obtained transmission weight is also incorrect. Therefore, a directivity error in the downlink, that is, a transmission error is caused. In particular, since the radio base station and the terminal are at a long distance, a slight directional error causes a large transmission error.

Therefore, according to the present invention, it is assumed that there is an estimation error in the uplink reception response vector and the appropriate parameter for extrapolation processing, particularly extrapolation distance, is adjusted according to the propagation environment in the propagation path. , It is intended to realize a correct transmission directivity by estimating a correct transmission response vector in the downlink.

FIG. 5 is a conceptual diagram for explaining the principle of determining the extrapolation distance according to the embodiment of the present invention.

The propagation environment of the propagation path is represented, for example, by the fluctuation of the reception coefficient of the propagation path, that is, the degree of fading. The degree of fading is expressed by a so-called Doppler frequency (FD) as a physical quantity.

The Doppler frequency FD in the propagation environment is estimated as follows, for example. That is, the correlation value of two reception response vectors temporally before and after the reception signal of each user separated by the adaptive array processing is calculated. If there is no fading, the two reception response vectors match and the correlation value is 1. On the other hand, if the fading is severe, the difference between the reception response vectors becomes large and the correlation value becomes small. If the relationship between the correlation value of the reception response vector and the Doppler frequency FD is experimentally obtained in advance and is stored in the memory, the Doppler frequency FD at that time is calculated by calculating the correlation value of the reception response vector. Can be estimated.

First, focusing on the Doppler frequency representing the degree of fading, the operation principle of the embodiment of the present invention will be described.

As described above, when the reception response vector 2 is deviated by the estimation error like the reception response vector 2 ', the extrapolation error becomes larger as the extrapolation distance becomes longer, and it depends on the original transmission response vector. It will be wrong.

Generally, the smaller the fading, that is, the lower the Doppler frequency FD, the smaller the fluctuation of the reception coefficient of the propagation path. Therefore, in such a case, the extrapolation distance is shortened to prevent extrapolation beyond the actual fluctuation amount. More specifically, when the Doppler frequency FD is low, a short distance extrapolation from the reception response vector 2'to the point a marked with X is performed as in the case of FIG. The vector is estimated to be regarded as the correct transmission response vector at the point b of the X mark.

On the other hand, the greater the fading, the more
That is, the higher the Doppler frequency FD, the larger the fluctuation of the reception coefficient of the propagation path. Therefore, in such a case, a sufficient extrapolation is performed by increasing the extrapolation distance. More specifically, when the Doppler frequency FD is high, extrapolation is performed for a relatively long distance from the reception response vector 2'to the point c of the mark X as in the case of FIG. The transmission response vector is estimated and regarded as the correct transmission response vector at point d of the X mark.

Such processing is mainly executed by the transmission response vector estimator 32 shown in FIG. FIG. 6 is a flowchart showing an extrapolation process focusing on such a Doppler frequency FD.

Referring to FIG. 6, in step S1,
First, the reception response vector calculator 22 of FIG. 1 estimates the propagation path, and specifically, the reception response vectors 1 and 2'of the uplink are estimated.

Next, in step S2, the degree of fading, that is, the Doppler frequency F
D is estimated.

Next, in step S3, the transmission response vector estimator 32 of FIG. 1 determines the optimum extrapolation parameter, that is, the extrapolation distance according to the Doppler frequency FD, by the method described with reference to FIG. Done. For this purpose, it is assumed that the optimum extrapolation distance determined by the preliminary measurement according to the level of the Doppler frequency FD is stored in the memory 34 of FIG. 1 in advance.

Next, in step S4, extrapolation processing is performed using the extrapolation parameter (extrapolation distance) determined in step S3 described above to estimate the downlink propagation path, that is, the transmission response vector. Done.

Finally, in step S5, the transmission weight vector calculator 30 of FIG. 1 estimates the transmission weight based on the downlink transmission response vector determined in step S4.

As described above, in this embodiment, since the optimum extrapolation distance is selected depending on the level of the Doppler frequency FD, even if there is an estimation error in the uplink reception response vector, the correct transmission response vector is obtained. Can be estimated.

On the other hand, the propagation environment of the propagation path is also represented by the weight estimation error of the signal obtained from the adaptive array output. Such an error is represented by a mean square error (hereinafter referred to as MSE) between a signal value obtained from the adaptive array output and an expected desired signal value. The smaller this MSE is, the more ideal the uplink becomes. Since the weight vector can be estimated accurately, the accuracy of the adaptive array output signal is good. On the contrary, the larger MSE means that the weight vector estimated in the uplink is not optimal, and the accuracy of the adaptive array output signal is poor. In addition,
Since the method of calculating the MSE is well known, its explanation is omitted.

Therefore, an estimation error occurs in the uplink reception response vector according to the magnitude of this MSE, and an extrapolation error also occurs.

Focusing on the above-mentioned MSE, the operating principle of another embodiment of the present invention will be described below.

Returning to FIG. 5A, when the MSE is large and the estimation error of the reception response vector is large, the extrapolation error increases as the extrapolation distance increases, so the extrapolation distance is shortened. . More specifically, when MSE is large, a short distance extrapolation is performed from the reception response vector 2 ′ to the point a marked with X as in the case of FIG. 5A, and the transmission response vector at this point a is obtained. It is estimated and regarded as a correct transmission response vector at point b of the X mark.

On the other hand, as shown in FIG.
Is small and the estimation error of the reception response vector is small, the extrapolation error is small even if the extrapolation distance is long, so the extrapolation error is relatively long. More specifically, MSE
Is small, extrapolation is performed for a relatively long distance from the reception response vector 2 ′ to the point c of the X mark as in the case of FIG. 5B, and the transmission response vector of the c point is estimated to estimate the X mark. It is assumed that it is a correct transmission response vector at point d.

Such processing is mainly executed by the transmission response vector estimator 32 of FIG. 1, and FIG. 7 is a flowchart showing the extrapolation processing focusing on such MSE.

The flowchart shown in FIG. 7 is the same as the flowchart shown in FIG. 6 except for the following points. That is, in step S12, M
SE is calculated, and then, in step S13, the transmission response vector estimator 32 of FIG. 1 determines the optimum extrapolation parameter, that is, the extrapolation distance according to the MSE by the method described with reference to FIG. It For this purpose,
It is assumed that the optimum extrapolation distance determined by the pre-measurement according to the magnitude of MSE is previously held in the memory 34 of FIG.

Since the other processes are as described with reference to FIG. 6, the description thereof will not be repeated here.

As described above, in this embodiment, the MS
Since the optimum extrapolation distance is selected depending on the size of E, it is possible to correctly estimate the transmission response vector even if the uplink reception response vector has an estimation error.

Next, FIG. 8 is a flow chart showing extrapolation processing according to still another embodiment of the present invention. Although the optimal extrapolation distance is determined by the Doppler frequency FD in the embodiment of FIG. 6 and the optimal extrapolation distance is determined by MSE in the embodiment of FIG. 7, FIG.
In the embodiment of the present invention, the Doppler frequency FD and MSE
The optimum extrapolation distance is determined in consideration of both of the above.

That is, in this embodiment, basically, the extrapolation parameter (extrapolation distance) is temporarily determined based on the Doppler frequency FD, and then the extrapolation parameter is corrected based on the MSE and finally determined. Is what you are trying to do.

Referring to FIG. 8, steps S1 and S2 are the same as those in the flowchart of FIG. 6, and therefore description thereof will not be repeated. When the Doppler frequency FD is estimated in step S2, the optimum extrapolation distance is selected and tentatively determined from the correspondence relationship between the Doppler frequency FD and the extrapolation distance stored in the memory 34 in advance.

After that, if the MSE is estimated in step S12, the extrapolation distance is corrected in accordance with the magnitude of this MSE in step S22. For example, MSE
If is large, it is necessary to correct the extrapolation distance to be short,
It is corrected by a coefficient of X <1. On the other hand, when the MSE is small, it is necessary to correct the extrapolation distance longer, and the correction is performed with a coefficient of X> 1. It is assumed that these coefficients are experimentally obtained in advance and stored in the memory 34.

In this way, when the extrapolation distance is finally determined in step S22, the transmission weights are estimated in steps S4 and 5 already described with reference to FIG.

As described above, in this embodiment, the temporary extrapolation distance is selected by the Doppler frequency FD which greatly affects the extrapolation error, and the extrapolation distance is corrected by MSE. It is possible to accurately estimate the transmission response vector.

Since the correspondence relationship between the Doppler frequency or MSE representing the propagation environment and the extrapolation distance varies depending on the individual difference of each radio device casing, it is generally measured in advance for each radio device. It is determined. However, if it is considered that individual differences are small, a common correspondence relationship may be used for a plurality of wireless devices in the entire system.

Further, the extrapolation parameter is not limited to the above-mentioned extrapolation distance, and may be another parameter such as the inclination of extrapolation.

The embodiments disclosed this time are to be considered as illustrative in all points and not restrictive. The scope of the present invention is shown not by the above description but by the scope of the claims, and is intended to include meanings equivalent to the scope of the claims and all modifications within the scope.

[0172]

As described above, according to the present invention, even if there is an estimation error in the reception response vector estimated on the uplink, the parameter used for the extrapolation processing is selected according to the propagation environment. , The downlink transmission response vector can be accurately estimated, and good transmission directivity can be realized.

[Brief description of drawings]

FIG. 1 is a schematic block diagram showing a configuration of a radio device (radio base station) 1000 of a PDMA base station according to an embodiment of the present invention.

FIG. 2 is a flowchart for explaining an outline of an operation of a wireless device (wireless base station) 1000.

FIG. 3 is a conceptual diagram for explaining a basic operation of a transmission response vector estimator 32.

FIG. 4 is a conceptual diagram for explaining a transmission response vector estimation principle of the present invention.

FIG. 5 is a conceptual diagram for explaining the principle of extrapolation distance determination according to the embodiment of the present invention.

FIG. 6 is a flowchart for explaining an outline of extrapolation processing according to the embodiment of the present invention.

FIG. 7 is a flowchart for explaining an outline of extrapolation processing according to another embodiment of the present invention.

FIG. 8 is a flowchart for explaining an outline of extrapolation processing according to still another embodiment of the present invention.

FIG. 9 is an arrangement diagram of channels in various communication systems of frequency division multiple access, time division multiple access, and PDMA.

FIG. 10 is a schematic diagram conceptually showing the basic operation of an adaptive array radio base station.

FIG. 11 is a schematic block diagram showing a configuration of an adaptive array radio base station.

FIG. 12 is a schematic diagram showing a frame configuration of a radio signal of a mobile phone.

FIG. 13 is a schematic diagram showing an image of transmission and reception of a radio signal between an adaptive array radio base station and a user.

[Explanation of symbols]

SR1 receiver, ST1 transmitter, # 1 to # 4 antennas, 10-1 to 10-4 switch circuits, 12-1 to 1
2-4 Multiplier, 13 Adder, 15-1 to 15-4
Multiplier, 20 reception weight vector calculator, 22 reception response vector calculator, 30 transmission weight vector calculator, 32 transmission response vector estimator, 34 memory,
1000 wireless devices (wireless base stations).

─────────────────────────────────────────────────── ─── Continuation of the front page (58) Fields investigated (Int.Cl. ⁷ , DB name) H04B ⁷ /02-7/12 H01Q 3/00-3/46 H01Q 21/00-25/04

Claims (9)

(57) [Claims] 1. A wireless device which changes the antenna directivity in real time and transmits and receives signals to and from a plurality of terminals in a time division manner, wherein a plurality of discretely arranged antennas are used when transmitting and receiving signals. A receiving circuit, the transmitting circuit and the receiving circuit sharing the plurality of antennas, the receiving circuit, when receiving a reception signal, based on a signal from the plurality of antennas, a signal from a specific terminal among the plurality of terminals A received signal separation means for separating the received signal, based on signals from the plurality of antennas at the time of receiving the received signal, a reception propagation path estimation means for estimating a reception response vector of a propagation path from the specific terminal, Wherein, the transmission circuit, based on the estimation result of the reception propagation path estimation means, a transmission propagation path estimation means for estimating a transmission response vector of a propagation path at the time of transmission of a transmission signal, and Based on the estimation result of the transmission channel estimation means, including a transmission directivity control means for updating the antenna directivity at the time of transmission of the transmission signal, the transmission channel estimation means, by the reception channel estimation means Extrapolation means for calculating the transmission response vector of the downlink slot to the specific terminal by extrapolation processing based on the plurality of reception response vectors of the estimated uplink slot from the specific terminal, and the propagation A storage unit holding a plurality of parameters used for the extrapolation processing, which is predetermined according to a propagation environment of the path, and estimates the propagation environment of the propagation path, and estimates the plurality of the held parameters. And a selection unit that selects a parameter corresponding to the propagated propagation environment and applies it to the extrapolation processing by the extrapolation unit. 2. The parameter is an extrapolation distance in extrapolation processing by the extrapolation means, and the storage means holds a plurality of extrapolation distances determined in advance according to a Doppler frequency representing the propagation environment. However, the selecting means estimates the Doppler frequency of the propagation path, selects the extrapolation distance corresponding to the estimated Doppler frequency from the held extrapolation distances, and selects the extrapolation distance by the extrapolation means. The wireless device according to claim 1, which is applied to extrapolation processing. 3. The radio apparatus according to claim 2, wherein the selecting means selects a shorter extrapolation distance as the estimated Doppler frequency is lower and a longer extrapolation distance as the estimated Doppler frequency is higher. 4. The parameter is an extrapolation distance in extrapolation processing by the extrapolation means, and the storage means is a signal error between the separated signal and the expected desired signal, which represents the propagation environment. Holds a plurality of extrapolation distances determined in advance, the selecting means estimates the signal error of the propagation path, and selects the estimated signal error among the held extrapolation distances. The wireless device according to claim 1, wherein a corresponding extrapolation distance is selected and applied to extrapolation processing by the extrapolation unit. 5. The radio apparatus according to claim 4, wherein the selecting means selects a shorter extrapolation distance as the estimated signal error is larger, and selects a longer extrapolation distance as the estimated signal error is smaller. 6. The extrapolation distance in the extrapolation processing by the extrapolation means, the storage means stores the Doppler frequency representing the propagation environment, and the desired signal expected as the separated signal. Holds a plurality of extrapolation distances determined in advance according to the signal error with, the selecting means estimates the Doppler frequency and signal error of the propagation path, among the plurality of held extrapolation distances. The radio apparatus according to claim 1, wherein an extrapolation distance corresponding to the estimated Doppler frequency and a signal error is selected and applied to extrapolation processing by the extrapolation unit. 7. The selecting means tentatively selects an extrapolation distance corresponding to the estimated Doppler frequency, and corrects the tentatively selected extrapolation distance corresponding to the estimated signal error. 6. The wireless device according to item 6. 8. The wireless device according to claim 1, wherein the relationship between the propagation environment and the plurality of parameters is individually determined for each wireless device. 9. The wireless device according to claim 1, wherein a relationship between the propagation environment and the plurality of parameters is determined commonly to the plurality of wireless devices.