KR100372900B1 - Apparatus for transceiving data in smart antenna system - Google Patents

Abstract

The present invention relates to a transmitting and receiving device of a smart antenna system for efficiently transmitting and receiving signals using an array antenna in a CDMA system, the smart antenna system for receiving M digital signals using an array antenna consisting of Ne antennas Means for calculating a Ne-dimensional complex weight vector for each signal for beamforming each signal from the Ne antenna input signals; And a complex multiplication means for complex-multiplexing the Ne-dimensional complex weight vector with the digital signal received at the antenna and a complex summation means for summing the complex multiplied result. Therefore, the smart antenna system not only reduces the calculation amount for obtaining the weight vector by beamforming the desired user signal direction but also improves performance by simultaneously using the pilot channel and the traffic channel.

Description

Transmitter and receiver of smart antenna system {Apparatus for transceiving data in smart antenna system}

The present invention relates to a smart antenna system, and in particular, to improve the capacity of a CDMA mobile communication system by using an array antenna to maintain the beam pattern of the antenna toward the user direction smart antenna that can maximize transmission and reception efficiency and suppress other interference signals It relates to a transmitting and receiving device of the system.

In general, a CDMA system uses the same frequency band for all users at the same time, and is assigned a unique code of its own to distinguish from each other. Accordingly, the interference of the CDMA system includes intracell interference caused by other user signals in the same cell and intercell interference caused by user signals of other cells. The capacity of a CDMA system is a system limited by this amount of interference.

Therefore, one method of increasing the capacity of a CDMA system is to reduce the amount of interference.

Conventional commercial systems, such as the IS-95, use three sector antennas in this way. A three sector antenna divides a cell into three sectors and a sector antenna is provided in each sector to transmit and receive a transmission and reception signal of each sector. This can ideally reduce the amount of interference by 1/3 compared to a single cell when the user distribution is uniform.

The three sector antenna system was able to secure sufficient system capacity in systems with relatively low data rates, such as digital cellular systems and PCS systems.

However, in a system that needs to support high-speed data services such as in an IMT-2000 system, it is difficult to secure a capacity necessary for smooth system operation with a sector antenna.

Therefore, there is a need for a new method that can greatly increase the system capacity, smart antenna system has attracted a lot of attention as one method for this.

In general, a smart antenna system uses a series of array antennas to maintain the antenna beam pattern in the desired user direction to maximize transmission and reception efficiency and suppress other interference signals.

1 and 2 show a conventional omnidirectional antenna system and a smart antenna system using a linear array antenna, respectively.

As shown in Fig. 1, the omnidirectional antenna 10 simultaneously accepts all user signals (mobile stations # 1 to mobile stations # 4). However, in the smart antenna system using the linear array antenna 2 of FIG. 2, the amount of interference can be greatly reduced by receiving a maximum of a desired user signal and suppressing other user signals by beamforming in a desired direction.

The performance of such a smart antenna system is determined by the accuracy of the weight vector for beamforming. Direct matrix inversion (DMI) using only the data in the current finite time interval block, using the minimum mean square error (MMSE) as a performance index, and calculating the new weight vector to update the weight vector. In the algorithm of the method, the weight vector W may be obtained as in Equation 1 below.

here, Is the covariance matrix of the input signal, Ne × Ne, Is a correlation vector between the input signal and the reference signal, and is Ne × 1. Ne is also the number of antenna elements.

The physical meaning of Equation 1 is to increase the gain of the antenna beam in the desired user direction and minimize the gain in the direction of the unwanted user.

Especially noteworthy is minimizing the gain towards the unwanted user, which is commonly referred to as nulling. R.A. R.A. Monzingo and T. Double You. In Introduction to Adaptive Arrays, authored by TW Miller and published by John Wiley Sons of New York in 1980, this nulling is when the number of unwanted users is below Ne-1. It is well known that nulling does not hold when well applied and the number of unwanted users is greater than Ne.

Therefore, in TDMA in which the same frequency is time-divided into N _TS time slots, Is a relatively small value, The condition can be satisfied to effectively null the unwanted user signal. However, the CDMA system has a very large system capacity, so that the number of antenna elements must be larger than the capacity number in order to satisfy the nulling condition.

However, this is almost impossible because it requires too many antenna elements from the practical implementation point of view.

Also, from the perspective of implementation, Equation 1 (In general, the amount of computation needed to calculate the inverse matrix directly by the woman method is It is very well known that there is a problem that acts as a limitation in actual implementation.

Therefore, in the CDMA system, since a large number of users makes it difficult to obtain a nulling effect, a method of simply forming a main beam in a desired user direction without a nulling action may be used. That is, the weight vector can be obtained as in Equation 2 below.

Unlike Equation 1, Equation 2 has an advantage of easy processing in real time because there is no inverse matrix of the covariance matrix.

In a pilot channel assisted modulation (PCAM) in which a reverse channel structure of a CDMA mobile communication system has a traffic channel and a pilot channel in parallel, power of a pilot channel is relatively lower than that of a traffic channel. The conventional method is to obtain a weight vector based on Equation 1 The correlation value of the pilot channel is used when calculating. This is because the traffic channel information cannot be directly used because it is a signal modulated by random data.

But, When using only the pilot channel, there is a problem in that the pilot channel has a relatively low power compared to the traffic channel, and thus there is a limit in obtaining an accurate weight vector.

SUMMARY OF THE INVENTION The present invention has been made to solve the problems of the prior art, and an object of the present invention is to simultaneously use a pilot channel and a traffic channel to obtain a weight vector for effective beamforming in a smart antenna system of a CDMA mobile communication system. To provide a transceiver of a smart antenna system that can implement a weight vector, a small amount of calculation.

1 is a conventional omni CDMA system.

2 is an exemplary diagram of beamforming of a smart antenna system.

3 is a configuration diagram of a CDMA smart antenna system receiver according to an embodiment of the present invention;

FIG. 4 is a block diagram of a CDMA smart antenna system receiver according to the present invention shown in more detail with the exception of the microprocessor, searcher, decimator, deinterleaver, channel decoder and data decompressor in FIG.

5 is a block vector estimator block diagram of FIG.

<Description of the symbols for the main parts of the drawings>

10: Omni-directional antenna 20: Linear array antenna

30 microprocessor 31 RF / IF / baseband converter and ADC

32: searcher 33: finger

34: weight vector estimator 35: decimator

36: complex multiplier and summer 37, 48: rake summer

38: deinterleaver 39: channel decoder

39-1: Data Restorer 39-2, 49: Hard Limiter

40: RF transceiver 41: weighted vector estimator

42, 49-1, 55: Memory 43, 47, 50, 53, 56: Multiplier

44, 59: summer 45: channel estimator

46: traffic despreader

51: average section for averaging despread pilot information for Ns chips

52: pilot channel information usage constant used for weight vector calculation, 0 ≤ a ≤ 1

54: block that averages despread traffic information for one symbol period

57: A block for averaging despread traffic information during the Nt symbol period

58: traffic channel information usage constant used for weight vector calculation, 0 ≦ 1-a ≦ 1

59-1: low pass filter

In order to achieve the above object of the present invention, a smart antenna system according to one aspect of the present invention provides a smart antenna system for receiving M digital signals, which are spread spectrum CDMA signals, using an array antenna composed of Ne antennas. Means for calculating a Ne-dimensional complex weight vector for each signal, for beamforming each signal from the two antenna input signals; Complex multiplication means for complex multiplying the Ne-dimensional complex weight vector and the digital signal received at the antenna; And a complex summing means for summing the complex multiplied results, wherein the weighted vector is a means for using a pilot channel to beam only in a desired user signal direction without nulling an interference signal, each of Ne antennas. A despreader that despreads the signal of the despreader; A summer for adding the despreaded result to the Ns chip period; A divider for dividing the output of the summer by Ns to obtain an average; And a low pass filter for low pass filtering the output of the divider.

In addition, the smart antenna system according to another feature for achieving the above object of the present invention, any one of the FDD system or TDD system for transmitting M digital signals using an array antenna consisting of Ne antennas An antenna system comprising: means for calculating a Ne-dimensional complex weight vector for each signal for beamforming of each signal for Ne antenna transmission signals; And complex multiplication means for complex multiplying the Ne-dimensional complex weight vector and the digital signal transmitted to the antenna, wherein the complex weight vector is a vector sum of weight vectors for multiple paths of a user signal used for receiving beamforming. After the conversion, the reverse array manifold is converted using the same function as the forward array manifold, and then used as a weight vector for the forward link.

According to the smart antenna system according to the present invention, the beamforming method not only reduces the calculation amount for obtaining the weight vector by beamforming in the direction of the desired user signal, but also uses the pilot channel and the traffic channel simultaneously, thereby performing better than the other cases. Can improve.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement the present invention.

In the present invention, a method of effectively configuring a beam in an array antenna system and a smart antenna receiver structure will be described with reference to an embodiment.

3 is a configuration diagram of a receiver for a smart antenna system according to an embodiment of the present invention.

As shown in FIG. 3, data and control signals between blocks in the smart antenna system receiver according to the embodiment of the present invention are controlled by the microprocessor 30.

The RF / IF / baseband / ADC 31 converts an RF signal received from Ne (an integer of 1 or more) antenna elements into IF and baseband signals and then converts them into digital signals by A / D conversion. Each antenna element signal converted into a digital signal is input to searcher 32 for initial synchronization acquisition and multipath search.

The finger 33 receives initial synchronization information from the searcher 32 to acquire and maintain finer synchronization and to detect data information. In addition, the weight vector estimator 34 provides the synchronization information necessary for despreading each antenna signal and provides the decimation information required by the decimator 35. In this case, the decimator 35 downsamples the 8 times oversampled signal into an early / on / late signal.

The complex multiplier and adder 36 calculates a complex multiplication of the spread spectrum digital complex input signal and the complex weight vector for beamforming, adds the result to form a single bit stream, and converts the result into a finger 33. Enter it.

The path-specific detection data detected by the finger 33 is combined in the rake summer 37, and the result is transmitted to the deinterleaver 38. The output of the deinterleaver 38 is transmitted in the order of the channel decoder 39 and the data decompressor 39-1. The output of the rake summer 37 is determined by a binary code at the hard limiter 39-2, and is then fed back to the weight vector estimator 34 to compensate for the sign of the traffic channel information.

FIG. 4 illustrates the CDMA smart antenna receiver structure in more detail except for the microprocessor, the searcher, the decimator, the deinterleaver, the channel decoder, and the data decompressor.

As shown in FIG. 4, when the number of users is M and the number of multipaths is L, the signal x (n) received at the array antenna may be expressed as follows.

here, Is an array response vector of [Ne × 1], d is the distance between antenna elements, λ is the wavelength of the carrier signal, Ne is the number of antenna elements, Tc is one chip period, Is the size variable of the kth user / ℓth path, Is the channel phase variable of the k th user / ℓ th path, Is the angle of incidence of the signal at the kth user / ℓth path, Is the time delay of the k th user / ℓ th path, Average 0 / variance Is the AWGN [Ne × 1] noise vector.

Equation 3 may also be expressed as Equation 5 below.

In FIG. 4, the output of the RF transceiver 40 of each antenna element is input to the weight vector estimator 41 as an A / D converted digital signal.

A block diagram of the weight vector estimator 41 is shown in FIG.

As shown in FIG. 5, the weight vector estimator 41 despreads the traffic channel data in order to obtain a weight vector using the traffic channel, averages the data in a symbol unit, and stores the data in the memory 42.

The weight vector obtained by the weight vector estimator 41 is multiplied by the input signal and the multiplier 43 in units of chips, and then summed into one bit stream by the adder 44. The bit stream is channel estimator 45. Is used to estimate channel estimates for data demodulation at &lt; RTI ID = 0.0 &gt;

The channel estimation information is multiplied by the output of the traffic despreader after the complex conjugate is taken. This result is passed to a rake summer 48 that combines multipath signal information. The sum of the signal energy for each path obtained by the rake summer 48 is determined by the binary code in the hard limiter 49, stored in the memory 49-1, and at a suitable time, the traffic symbol code of the memory 42 is determined. Is used to compensate.

In general, the weight vector in the DMI method is obtained as in Equation 6 below.

here Is a covariance matrix for the input signal of the k-th user, l-th path, and Ne × Ne, Is a correlation vector between the input signal and the reference signal for the k-th user, the l-th path, and is Ne × 1. Where Ne is the number of antenna elements. The physical meaning of Equation 6 is to increase the gain of the antenna beam in the desired user direction and minimize the gain in the direction of the unwanted user.

Here, minimizing the gain in an undesired user direction is called nulling, and nulling is not established when the number of unwanted users is greater than Ne. The CDMA system is actually Ne << M because the system capacity is very large.

Therefore, in a situation where there are very many users, Arithmetic action does not have great effect in terms of nulling unwanted user signals. Accordingly, in the present invention, the weight vector is calculated using the basic philosophy as shown in Equation 7 below, in which a main beam is formed only in a signal direction of a desired user in forming a beam using an array antenna using the characteristics of the CDMA system. It is shown in the present invention.

Equation 6 is a limitation of the actual implementation depending on the hardware processor used because the amount of inverse of the covariance matrix is very large. However, since the calculation of the weight vector according to Equation 7 in the present invention obtains only the cross-correlation vector of the input signal and the reference signal, it can be seen that the amount of calculation is significantly smaller than that in Equation 6.

In order to explain a specific method of obtaining a weight vector by the method of Equation 7, the present invention considers a coherent system that transmits a pilot channel on the reverse link simultaneously with a traffic channel. Such systems generally have a lower allocation power of the pilot channel than the allocation power of the traffic power.

Since the pilot channel transmits information previously known from the transmitter, the pilot channel can be used as a direct reference signal like a training sequence in a TDMA system. On the other hand, since traffic channel information is a signal modulated by binary data information, it cannot be used directly. That is, when the pilot channel and the traffic channel are used as information sources for calculating the weight vector, the two channels have the following advantages and disadvantages.

First, since the pilot channel transmits data known in advance, it can be used directly if the receiver can know only the synchronization information.

On the other hand, it is transmitted at a lower power than traffic channel information. The traffic channel has a disadvantage in that a higher power than the pilot channel is allocated and transmitted, whereas the traffic channel is modulated by information data and cannot be directly used.

As a way to use the traffic channel, a signal modulated to traffic information that is a pseudo-random binary code is determined in advance by the hard limiter 49 using the symbol energy value obtained by the rake summer 48, and then inverse. It is used after compensating for the sign of the traffic channel by feedback.

Therefore, if the pilot channel and the traffic channel are used at the same time, more improved performance can be obtained.

5 is a means for obtaining a weight vector using the pilot channel and the traffic channel information as described above. The output of the despreader 50 after receiving the digital information spread from each antenna element and despreading it with a pilot despread code is expressed by Equation (8).

After chip-by-chip pilot channel despreading , j = 1, 2, ..., Ne are averaged during the Ns chip period (51), and the signal is expressed as shown in Equation 9 below.

The output of the despreader 53 after receiving the digital information spread from each antenna element and despreading it with the traffic despread code is as follows.

After Chip Despreading , j = 1, 2, ..., Ne are averaged (54) for one symbol period (by SF chip, SF: spreading factor), and the signal is expressed as follows.

The energy value in symbol units represented by Equation 11 is stored in the memory 55 as a signal modulated by original data binary information. The value stored in this memory is multiplied by a pre-demodulated data symbol ^ d _k which is the output of the hard limiter 49 (56) and averaged during the Nt symbol after the sign is compensated (56). Display this output as follows:

Equations 9 and 12 are channel estimation information for channels and channel estimation information for traffic channels, respectively, and the two vectors are summed as in Equation 13 below.

Here, 0≤a≤1 is a constant that determines the ratio using the pilot channel and traffic channel information. For example, when a = 1, the weight vector is calculated using only the pilot channel, and when a = 0, the weight vector is calculated using only the traffic channel. In the case of a = 0.5, the weight vector is obtained by using the pilot channel and the traffic channel at the same ratio.

The output of summer 59, which combines channel information using pilot channels and channel information using traffic, is low pass filtered in low pass filter 59-1 to further improve performance. In this case, a low pass IIR filter or FIR filter may be used as the low pass filter, and the cutoff frequency of the filter may be the maximum Doppler frequency including channel information. Therefore, the low pass filtered weight vector is expressed as follows.

Where h (n) is the impulse response vector of the low pass filter.

The calculation amount of the equation (6) by the conventional method and the equation (14) proposed in the present invention can be compared as follows.

First, the calculation amount of Equation 6 is as follows for each term.

O Calculation

-Number of operations needed: KNe (Ne + 1) / 2 CMs = 2 KNe (Ne + 1) RMs + KNe (Ne + 1) RAs

O Inverse of

The number of operations required by the Trench ’s calculation method:

^{(7N 2/4) Flops =} (7 Ne 2) RMs + (7Ne 2) RAs

O Calculation

-KNe CMs = 4KNe RMs + 2KNe RAs

O matrix Wow Odds

Number of operations required: Ne ² CMs = 4Ne ² RMs + 4Ne ² RAs

Therefore, the total calculation is shown in Table 1.

#. of Multiplicaions #. of Additoins Complex operator KNe (Ne + 1) / 2 + (7Ne 2/4) + KNe + Ne 2 [CMs] 7/4 Ne ² [CAs] Real operations 2KNe (Ne + 1) + 11Ne ² + 4KNe [RMs] KNe (Ne + 1) + 9Ne ² + 2KNe [RAs]

Next, the calculation amount of Equation 14 is as follows.

O Calculation

-KNe CMs = 4KNe RMs + 2KNe RAs

O Calculation

-(KNe + K) CMs = (4KNe + 4K) RMs + (2KNe + 2K) RAs

O Calculation

2CMs = 8RMs + 4Ras

Convolution calculation when using O 1st order IIR filter

( )

-1 CMs + 1CAs = 4 RMs + 4RAs

Therefore, the total calculation is shown in Table 2.

#. of Multiplicaions #. of Additoins Complex operations (2KNe + K + 3) [CMs] 1 [CAs] Real operations 4 (2KNe + K + 3) [RMs] 2 (2KNe + K + 3) + 2 [RAs]

It can be seen from Table 1 and Table 2 that the proposed method has a much smaller amount of calculation.

The weight vector for the backward beamforming may be considered in the case of a time division duplex (TDD) system and a frequency division duplex (FDD) system. First, in the TDD system, since the reverse carrier frequency f _u and the forward carrier frequency f _d are the same, the reverse array manifold ( A _u ) and the forward array manifold ( A _d ) are the same. Therefore, reverse beamforming may be performed using the weight vector for forward beamforming as it is.

On the other hand, in the FDD system, because f _u ≠ f _d , the array manifolds of the forward link and the reverse link are different. Therefore, a function that converts an array manifold of a reverse link into an array manifold of a forward link can be introduced.

Therefore, after the weight vector for the forward link is converted into the weight vector of the reverse link by Equation 15, Equation 16 may be used as a result.

here, Represents a reverse weight vector, Denotes a forward weight vector.

As described above, a pilot channel assisted modulation (PCAM) scheme and a pilot symbol for simultaneously transmitting data information and pilot information as a method for coherent demodulation of a reverse link (link from a mobile station to a base station) in a CDMA mobile communication system. There is a Pilot Symbol Assisted Modulation (PSAM) method that periodically inserts the data into the data information. In this case, in the PCAM scheme, the pilot channel power is generally lower than the data channel power. Since the pilot channel information is an unmodulated signal, not only can channel information be estimated using this, but also can be used as a reference signal for beamforming in a smart antenna system.

On the other hand, even though the data channel information is transmitted at higher power than the traffic channel, the data channel information is modulated with binary data having random characteristics, and thus cannot be directly used as a reference signal for beamforming.

However, in the present invention, after reconstructing the sign of the data channel by a method of feedbacking the estimated symbol by hard decision, a more efficient beamforming can be performed by calculating the weight vector using this information.

In addition, the weight vector used in the reverse direction for the forward beamforming of the FDD system may be frequency corrected and then used as the forward weight vector.

Although the above has been described with reference to a preferred embodiment of the present invention, those skilled in the art will be able to variously modify and change the present invention without departing from the spirit and scope of the invention as set forth in the claims below. It will be appreciated.

As described above, in the CDMA system according to the present invention, the beamforming method of the smart antenna system not only reduces the calculation amount for obtaining the weight vector by beamforming in the desired user signal direction, but also uses the pilot channel and the traffic channel simultaneously. However, there is an effect that can improve the performance compared to the other cases.

Claims (17)

delete delete delete A smart antenna system for receiving M digital signals, which are spread spectrum CDMA signals, using an array antenna composed of Ne antennas, Means for calculating a Ne-dimensional complex weight vector for each signal, for beamforming each signal from the Ne antenna input signals; Complex multiplication means for complex multiplying the Ne-dimensional complex weight vector and the digital signal received at the antenna; And A complex summing means for summing the complex multiplied results, The weight vector is, Means for using a pilot channel to beam only in the desired user signal direction without the effect of nulling the interfering signal, A despreader that despreads each of the Ne antennas; A summer for adding the despreaded result to the Ns chip period; A divider for dividing the output of the summer by Ns to obtain an average; And And a low pass filter for low pass filtering the output of the divider. The method of claim 4, wherein The low pass filter, Transmitting and receiving device of a smart antenna system, characterized in that consisting of IIR filter or FIR filter. The method of claim 5, The limit frequency of the low pass filter is, Transceiver of a smart antenna system, characterized in that determined by the maximum Doppler frequency. The method of claim 4, wherein The weight vector is a means for obtaining a weight vector using a traffic channel (or an information channel) in order to beam only in a desired user signal direction without nulling an interference signal. A hard limiter for determining a binary code by receiving an energy value in symbol units in a rake adder; An adder for despreading the traffic signals of each of Ne antenna signals to obtain an energy value in symbol units; A memory block for storing Nd traffic energy values in symbol units; A multiplier that multiplies the traffic energy value of the memory block by a symbol of a hard limiter; A summer for adding Nt outputs of the multiplier; And And a divider for dividing the output of the adder by Nt in order to average the output of the adder. The method of claim 4, wherein The weight vector is a means for obtaining a weight vector using a traffic channel (or an information channel) in order to beam only in a desired user signal direction without nulling an interference signal. A hard limiter for determining a binary code by receiving an energy value in symbol units in a rake adder; An adder for despreading the traffic signals of each of Ne antenna signals to obtain an energy value in symbol units; A memory block for storing Nd traffic energy values in symbol units; A multiplier that multiplies the traffic energy value of the memory block by a symbol of a hard limiter; A summer for adding Nt outputs of the multiplier; A divider for dividing the output of the summer by Nt to average the output of the summer; And And a low pass filter for low pass filtering the output of the divider. The method of claim 8, The low pass filter, Transmitting and receiving device of a smart antenna system, characterized in that consisting of IIR filter or FIR filter. The method of claim 9, The limit frequency of the low pass filter is, Transceiver of a smart antenna system, characterized in that determined by the maximum Doppler frequency. The method of claim 4, wherein The weight vector is a means for simultaneously using pilot channel data and traffic data in order to beam only in a desired user signal direction without nulling an interference signal. A despreader for despreading the pilot signal of each of the Ne antennas as a means for using the pilot information; A summer for adding the despreaded result to the Ns chip period; A multiplier for multiplying the output of the summer by a (0 <a <1) and outputting r _p ; A hard limiter for determining a binary code by receiving an energy value of a symbol unit in a rake adder as a means for using a traffic channel (or an information channel); An adder for despreading the traffic signals of each of the Ne antenna signals to obtain an energy value in symbol units; A memory block for storing Nd traffic energy values in symbol units; A multiplier that multiplies the traffic energy value of the memory block by a symbol of a hard limiter; A summer for adding Nt outputs of the multiplier; A multiplier for outputting r _t by multiplying (1-a) the output of the summer; A summer for adding the r _p and r _t ; A low pass filter for low pass filtering the output of the summer; And Transceiver of the smart antenna system, characterized in that it comprises a gain control unit for adjusting the gain of the output of the Ne low pass filter. The method of claim 11, The low pass filter, Transmitting and receiving device of a smart antenna system, characterized in that consisting of IIR filter or FIR filter. The method of claim 12, The limit frequency of the low pass filter is, Transceiver of a smart antenna system, characterized in that determined by the maximum Doppler frequency. delete delete delete In the smart antenna system of any one of the FDD system or TDD system for transmitting M digital signals using an array antenna consisting of Ne antennas, Means for calculating a Ne-dimensional complex weight vector for each signal for beamforming each signal for Ne antenna transmission signals; And Complex multiplication means for complex multiplying the Ne-dimensional complex weight vector and the digital signal transmitted to the antenna, The complex weight vector obtains a vector sum of weight vectors of multiple paths of a user signal used for receiving beamforming, converts the reverse array manifold to a function equal to the forward array manifold, and then converts the forward link. Transmitting and receiving device of a smart antenna system, characterized in that used as a weight vector for.