CN100336316C - Method and device for shaping wave beam form of intellectual antenna - Google Patents

Abstract

The present invention relates to a method and a device for the wave beam figuration of an intellectual antenna. Firstly, sampling output data of a radio frequency receiver from every antenna array element is estimated in a channel way by the known training sequence of every user, and the channel estimation of all antennae of all users is obtained; then, the average power of every discrete point of a channel is worked out for the channel estimation of all the antennae of all the users, and at least one channel corresponding to a discrete point with maximum average power is found out to be taken as a strong diameter of multiple diameters; finally, the sampling output data of the receiver of every antenna array element is multiplied by a weight value and then summed to obtain a sum signal for every user, a group of weight values are searched for making the power of the sum signal minimized under the constraint condition that the inner product of the weight value and any strong diameter of the strong diameters is a constant, and the weight values which meet the condition are taken as final output weight values so as to realize wave beam figuration. The present invention has the advantages that a wireless communication system is caused to have higher capacity and better performance, and the project realization of the present invention is simple and practical.

Description

A kind of beam form-endowing method of smart antenna and device thereof

Technical field

The present invention relates to wireless communication system, particularly the method for wave beam forming and device thereof in the use of aerial array in the TDD wireless communication system.

Background technology

An important target is exactly the capacity maximum that makes system in the design wireless communication system, just system's number of users maximum of serving simultaneously.And because the cdma wireless communication system is an interference limiting system, so a kind of method that increases power system capacity just is to use the interference reduction between the family, can reduce interference between the user by the transmitting power that reduces each user, thereby increase the capacity of system.Use smart antenna can improve carrier/interface ratio, thereby can reduce each user's transmitting power, thus corresponding reduction inter-user interference, the sensitivity that improves system.

The control of cdma system required power guarantees that all signals that arrive the base station roughly have identical power level.Because smart antenna can be kept apart the upward signal of different user, thereby reduce the requirement of power control or relax the influence that imperfect power is controlled.The wave beam forming of smart antenna can make the base station with beam position targeted customer narrower, that more assemble, thereby reduces multipath fading and other non-targeted customer's interference, therefore can improve link-quality.Because the energy of wave beam is collected at a wave beam, rather than is dispersed in all directions in space, so the increase of its coverage, and improved the ability that penetrates building.Can make the directional diagram of smart antenna cover the temporary transient very high hot zones of user density by the weights of adjusting antenna.

Smart antenna (Smart Antenna, SA) spatial character and the Digital Signal Processing that utilizes signal to transmit, algorithm process by the advanced person, reception and launching beam to the base station carry out wave beam formation and figuration, thereby reach the purpose that reduces interference, increase capacity, expansion covering, improves communication quality, reduction transmitting power and raising wireless data transmission rate.

The wave beam forming technology refers generally to the process according to the calculation of parameter optimal weight vector in the Array Signal Processing field, then make a general reference sometimes according to measurement and estimated parameter and carry out the Digital Signal Processing process of (can comprise time domain and spatial domain).Here the wave beam forming technology is meant according to requirements such as beam position, beamwidth, 0:00 direction, side lobe levels and calculates optimal weight vector and form the process of wave beam.

Smart antenna generally includes multi-beam intelligent antenna and adaptive smart antenna.

The multi-beam intelligent antenna system, also can be described as switched beam system (Switched Beam System), take accurate dynamically switched-beam switching mode, the wave beam that utilizes a plurality of different fixing to point to covers whole user area, along with user's moving in the sub-district, base station selected wherein only wave beam, thereby the intensity of enhancing received signal.Though advantages such as that multi-beam intelligent antenna has is simple in structure, response speed is fast are limited in one's ability to the inhibition of disturbing, and are difficult to realize signal optimum reception and emission, when subscriber signal departs from main lobe direction, the reception variation.

Adaptive smart antenna system (Adaptive Antenna System) takes fully adaptive array autotrack mode, adjust the weighted value of each antenna element by different self adaptations, reach and form some adaptive beam, from several users' of motion tracking purpose, can carry out the maximum possible coupling simultaneously to current transmission environment.There is maximum power features to decompose in the wireless system Adaptive Criterion at present, maximum signal to noise ratio feature decomposition and maximum signal interference ratio feature decomposition, wherein maximum power features is decomposed, the maximum signal to noise ratio feature decomposition does not all have the interference of consideration to other non-targeted customers, only considers to make targeted customer's power maximum.That is to say that these algorithms have only been considered the energy of the main lobe of wave beam, and do not have the energy of consideration facing to the secondary lobe of interference user.Though maximum signal interference ratio feature decomposition algorithm has been taken all factors into consideration the energy of wave beam main lobe and secondary lobe, performance can reach optimum in theory, and this algorithm need be to matrix inversion and characteristic value decomposition.Therefore, the complexity of this algorithm is higher, and Project Realization is difficult.

In sum, have higher capacity and more performance, must design a kind of simple, real-time working and be convenient to based on the beam form-endowing method that uses in the intelligent antenna wireless system in order to make wireless communication system.

Summary of the invention

Technical problem to be solved by this invention is to provide a kind of beam form-endowing method of simple and practical adaptive smart antenna, by designing a kind of new adaptive signal processing method, make wireless communication system when using the beam form-endowing method of this smart antenna, can finish the optimization of the energy of the main lobe of wave beam and secondary lobe adaptively, make the user's that aims at the mark main lobe energy maximum, the side-lobe energy of aiming at non-targeted customer is as far as possible little, simultaneously can solve the interference that multipath transmisstion brings, and this algorithm can simple realization on engineering, and can obtain good effect.

Another object of the present invention is to provide a kind of beam size enlargement apparatus of adaptive smart antenna, can simple realization on engineering.

To achieve these goals, the invention provides a kind of beam form-endowing method of smart antenna, its characteristics are that described method comprises the steps:

Step 1 is utilized the known training sequence of each user, and the sampling dateout from the radio frequency receiver of each root bay is carried out channel estimation process, obtains the channel estimating of all users on all antennas;

Step 2 averages the computing of power to the channel estimating on all antennas of each user, obtains the average power on each discrete point of channel;

Step 3 obtains the pairing channel of at least one maximum average power as the strong footpath in the multipath according to the average power on described each discrete point;

Step 4, at each user, the sampling dateout of the radio frequency receiver of each root bay be multiply by weights sues for peace then and obtains one and Signal Processing, described weights satisfy with described strong footpath in the inner product in any strong footpath be under the constraints of constant, obtaining one group of weights makes described and minimum power signal, and with the weights that satisfy condition final weights, thereby realize wave beam forming as output.

The beam form-endowing method of above-mentioned smart antenna, its characteristics are, in step 4, each user are carried out following processing: $\left\{\begin{array}{c}\min W^H{R}_{\mathrm{xx}}W\\ H^{H}W=a\end{array}\right.,$ Wherein, W is a weight matrix, R _XxBe the correlation matrix of antenna reception data, the H matrix is the matrix of expression channel impulse response, and its column vector is a multipath component, comprises at least one strong footpath, and a is a constant vector; To obtain final weights.

The beam form-endowing method of above-mentioned smart antenna, its characteristics are, in step 4, described minimum power process is to finish by an adaptive iteration process, when the difference of the weights of twice iteration less than a predefined thresholding, then stop iteration, export final weights.

The beam form-endowing method of above-mentioned smart antenna, its characteristics are, also comprise an initialization procedure before described adaptive iteration process, and it comprises the steps:

Receive data X according to described antenna and generate correlation matrix R _Xx

Obtain projection operator P;

Obtain constant vector A;

To the weights initialize.

The beam form-endowing method of above-mentioned smart antenna, its characteristics are, realize that described adaptive iteration process is according to W (n+1)=P (I-μ R _Xx) W (n)+A carries out iterative processing, and the output weights otherwise are proceeded iterative processing as final weights when satisfying ‖ W (n+1)-W (n) ‖≤δ, wherein, δ is predefined thresholding, and μ is a step factor, and n be more than or equal to zero integer.

The beam form-endowing method of above-mentioned smart antenna, its characteristics are, the correlation matrix R of described reception data _XxCan be by carrying out the statistical correlation processing or averaging relevant $R_{\mathrm{xx}}=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{X}^H\left(i\right)X\left(i\right)$ Handle or carry out instantaneous relevant R _Xx=X ^H(i) X (i) handles and obtains, and wherein, N is the number of channel; Described projection operator can be by making P=I-H (H ^HH) ^-1H ^HObtain; Described constant vector can be by making A=H (H ^HH) ^-1A obtains; Described weights initial value can obtain by making W (0)=A.

The beam form-endowing method of above-mentioned smart antenna, its characteristics are, step factor $0<\mathrm{\&mu;}<\frac{2}{{\mathrm{\&lambda;}}_{\max }},$ λ wherein _MaxBe R _XxEigenvalue of maximum.

The beam form-endowing method of above-mentioned smart antenna, its characteristics are that the channel estimation process process in step 1 can be passed through h _i=(M ^HM) ^-1M ^He _iObtain the channel estimating of all users on all antennas, wherein M is the training matrix of all users' training sequence composition, e _iBe the numerical value of the training sequence that in a pulse, receives of i root antenna, h _iBe the impulse response of each channel, 1≤i≤N.

The beam form-endowing method of above-mentioned smart antenna, its characteristics are, can pass through in step 2 $\mathrm{power}\_\mathrm{use}{r}_k\left(m\right)=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{\left|h_{i,k}\left(m\right)\right|}^2$ Average power on each discrete point of acquisition channel, wherein m represents the sequence number in footpath, and k represents k user, and N is the number of channel, h _{I, k}Be the impulse response of i channel of k user, and 1≤i≤N.

The present invention also provides a kind of beam size enlargement apparatus of smart antenna, comprises

N identical omnidirectional antenna units;

N radio-frequency (RF) transceiver, each radio-frequency (RF) transceiver is equipped with A-D converter and digital-to-analog converter;

Baseband processor is provided with and an a described N radio-frequency (RF) transceiver corresponding N channel estimator and an adaptive signal processor, is used to realize that adaptive weights calculate; Its characteristics are that described adaptive signal processor comprises

The average power estimator module, be used for the average power on each discrete point on all antennas that N channel impulse response according to the output of described channel estimator calculate each user, and find out the pairing channel of at least one maximum power and export as the strong footpath in the multipath;

Matrix maker module is used for according to the strong footpath sequence number of described average power estimator output the channel impulse response of the described channel estimator output of correspondence by column vector generator matrix H;

Calculator modules is used for calculating projection operator P and constant vector A and output according to matrix H;

Correlation matrix maker module, the data that are used for described antenna is received generate correlation matrix R _XxAnd output;

The self-adaptive processing module is used for the output according to described calculator modules and correlation matrix maker module, carries out self-adaptive processing, the weights of output adaptive, and then the figuration of realization wave beam.

Because at wireless communication system, often need estimate channel with training sequence, therefore the present invention utilizes the known training sequence of each user, sampling dateout from the radio frequency receiver of each root bay is carried out channel estimating, obtain the channel estimating of all users on all antennas.Then the channel estimating on all antennas of each user is obtained average power on each discrete point of channel, find out the average power of a maximum or the average power of several maximums, the channel of the average power correspondence that these are big is exactly the several most powerful paths in the multipath.At each user, make the sampling dateout of the receiver of each root bay multiply by weights and sue for peace then, these group weights satisfy with a plurality of strong footpaths in the inner product in any strong footpath be to seek the minimum power that one group of weights makes this and signal under the constraints of constant.The present invention does not directly retrain all of a user, is in order to make algorithm engineering realize simple but basic the maintenance has identical performance with this optimal algorithm of maximum signal interference ratio feature decomposition.Because multipath signal is uncorrelated, so a plurality of most powerful paths process weights directly addition later on of the assurance of the minimization process under this constraints targeted customer, footpath that other power of targeted customer is more weak and other non-targeted customer's signal then are suppressed.And this affined minimization process can be finished by an adaptive iterative process.When the norm of the difference of the weights of twice iteration less than a predefined thresholding, just stop iteration, export final weights.

By beam form-endowing method of the present invention and device, can be so that wireless communication system has higher capacity and more performance, can finish the optimization of the energy of the main lobe of wave beam and secondary lobe adaptively, make the user's that aims at the mark main lobe energy maximum, the side-lobe energy of aiming at non-targeted customer is as far as possible little, can solve the interference that multipath transmisstion brings simultaneously; And the present invention can simple realization and practical on engineering.

Describe the present invention below in conjunction with the drawings and specific embodiments, but not as a limitation of the invention.

Description of drawings

Fig. 1 is the radio communication base station structured flowchart of smart antenna of the present invention;

Fig. 2 is the emitting structural block diagram of the wireless communication system of the present invention with smart antenna;

Fig. 3 is an adaptive signal processor structure chart of the present invention;

Fig. 4 is the implementing procedure block diagram of adaptive weight computational methods of the present invention.

Embodiment

System involved in the present invention has the mobile communication system that the smart antenna self-adapting wave beam weight calculates, and Fig. 1 represents the architecture of base station of wireless system.Mainly comprise N identical omnidirectional antenna units 201A, 201B ..., 201N, N radio-frequency (RF) transceiver 203A, 203B ..., 203N and baseband processor 204.All radio-frequency (RF) transceiver 203 are used same local oscillation signal source, work mutually to guarantee the radio-frequency (RF) transceiver in the same base station.Be equipped with A-D converter (ADC) and digital-to-analog converter (DAC) in each radio-frequency (RF) transceiver, so the base band input and output of all radio-frequency (RF) transceiver 203 are digital signal, they are connected by the high-speed figure bus with 204 of baseband processor.Baseband processor 204 comprises and N the corresponding N of a radio-frequency (RF) transceiver channel estimator 207A, 207B ..., 207N and an adaptive signal processor 208.100 expression base station equipments among the figure.Realize that adaptive weights calculate and in baseband processor 204, finish.

Suppose that N array element of smart antenna receives K user's signal, this K user's signal is X through the dateout of simulating to the digitalizer sampling of each radio-frequency (RF) transceiver ₁(n), X ₂(n) ..., X _N(n), n is a n chip.N sampling dateout X ₁(n), X ₂(n) ..., X _N(n) deliver to N channel estimator 207A respectively, 207B ..., 207N and adaptive signal processor 208.Each channel estimator 207A, 207B ..., 207N exports N channel impulse response h ₁, h ₂..., h _NTo adaptive signal processor 208, the needed weights of adaptive signal processor 208 output downlink.The downlink structure as shown in Figure 2, data source module 301 produces the needed data of downlink, these data are delivered to channel coding module 302 and are encoded, deliver to spread spectrum module 304 then and carry out spread spectrum, data behind the spread spectrum are delivered to N weighter module 305A, 305B ..., 305N, the weights of these weighter are delivered to N modulation module 306A, 306B from adaptive signal processor 208 then through the data of weighting, ..., deliver to N antenna after 306N modulates and finish emission.

The concrete processing procedure of channel estimating is: known each user's training sequence, the numerical value of the training sequence that i root antenna receives in a pulse (burst) is e _i, then have

e _i＝Mh _i (6)

M is the matrix of being made up of user's training sequence to some extent, therefore can be write as the estimation of channel

h _i＝(M ^HM) ^-1M ^He _i (7)

For the TDD system of CDMA, the Metzler matrix that all users' training sequence is formed can be write as circular matrix, therefore can find the solution (6) formula with the FFT conversion,

h _i＝ifft(fft(e _i)/fft(M(：，1))) (8)

Calculate channel response on all antennas, the N that obtains channel impulse response h respectively by said process ₁, h ₂..., h _NBe input to adaptive signal processor 208, further handle the weights that obtain down beam shaping through it.With k user is example, the channel response h on k all antennas of user _{1, k}, h _{2, k}..., h _{N, k}Deliver to the average power estimator module 401 among Fig. 3, its average power on all antennas is asked in every footpath

$\mathrm{power}\_\mathrm{use}{r}_k\left(m\right)=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{\left|h_{i,k}\left(m\right)\right|}^2---\left(9\right)$

M represents the sequence number in footpath.Find out the maximum pairing most powerful path of several performance numbers, select 2 to 3 strong footpaths generally speaking, and their sequence number is delivered to matrix maker module 402.Matrix maker module 402 is write them as a matrix H by column vector according to the sequence number of most powerful path.The output H of matrix maker module 402 is delivered to calculator modules 403 calculate projection operator and constant vector respectively according to formula (3) and (4).Received signal is delivered to correlation matrix maker module 404 generate correlation matrix R according to formula (2) _XxSelf-adaptive processing module 405 is delivered in the output of calculator modules 403 and correlation matrix maker module 404 carried out interative computation according to formula (5), wherein the selection of the step factor in (5) formula is satisfied

$0<\mathrm{\&mu;}<\frac{2}{{\mathrm{\&lambda;}}_{\max }},$ λ _MaxBe R _XxEigenvalue of maximum, if weights satisfy the criterion in the 3rd step, finishing iteration and export weights W then, otherwise continue iteration.

Referring to Fig. 4, be the handling process of example explanation intelligent antenna beam shaping with 8 antennas among the figure.

Step 501 at first, is carried out channel estimating by channel estimation module;

Step 502, estimated result are delivered to the average power module of calculating the estimation channel and are averaged power calculation;

Step 503 is carried out most powerful path according to the result of calculation of step 502 and is looked for and form matrix H;

Step 504 is calculated projection operator and constant vector according to matrix H;

Step 505 is carried out initialization to weights;

Step 506 is utilized and to be treated that repeatedly algorithm finishes the iterative computation of weights;

Step 507, to judging of the difference of the weights of double iteration,, then finish to calculate and the output weights if the norm of the difference of double weights satisfies predetermined conditions, if do not satisfy condition, then return step 506 and continue to calculate up to satisfying end condition.

The present invention is applicable to the wireless communication system with smart antenna.Any engineer who is engaged in the radio communication exploitation as long as have the ABC of smart antenna and Adaptive Signal Processing, can use method of the present invention to design a high-quality antenna system.

Certainly; the present invention also can have other various embodiments; under the situation that does not deviate from spirit of the present invention and essence thereof; those of ordinary skill in the art work as can make various corresponding changes and distortion according to the present invention, but these corresponding changes and distortion all should belong to the protection range of the appended claim of the present invention.

Claims (10)

1, a kind of beam form-endowing method of smart antenna is characterized in that, described method comprises the steps:

Step 1 is utilized the known training sequence of each user, and the sampling dateout from the radio frequency receiver of each root bay is carried out channel estimation process, obtains the channel estimating of all users on all antennas;

Step 2 averages the computing of power to the channel estimating on all antennas of each user, obtains the average power on each discrete point of channel;

Step 3 obtains the pairing channel of at least one maximum average power as the strong footpath in the multipath according to the average power on described each discrete point;

Step 4, at each user, the sampling dateout of the radio frequency receiver of each root bay be multiply by weights sues for peace then and obtains one and Signal Processing, described weights satisfy with described strong footpath in the inner product in any strong footpath be under the constraints of constant, obtaining one group of weights makes described and minimum power signal, and with the weights that satisfy condition final weights, thereby realize wave beam forming as output.

2, the beam form-endowing method of smart antenna according to claim 1 is characterized in that, in step 4, each user is carried out following processing: $\left\{\begin{array}{c}\min W^H{R}_{\mathrm{xx}}W\\ H^{H}W=a\end{array}\right.,$ Wherein, W is a weight matrix, R _XxBe the correlation matrix of antenna reception data, the H matrix is the matrix of expression channel impulse response, and its column vector is a multipath component, comprises at least one strong footpath, and a is a constant vector; To obtain final weights.

3, the beam form-endowing method of smart antenna according to claim 2, it is characterized in that, in step 4, described minimum power process is to finish by an adaptive iteration process, when the difference of the weights of twice iteration less than a predefined thresholding, then stop iteration, export final weights.

4, the beam form-endowing method of smart antenna according to claim 3 is characterized in that, also comprises an initialization procedure before described adaptive iteration process, and it comprises the steps:

Receive data X according to described antenna and generate correlation matrix R _Xx

Obtain projection operator P;

Obtain constant vector A;

To the weights initialize.

5, the beam form-endowing method of smart antenna according to claim 4 is characterized in that, realizes that described adaptive iteration process is according to W (n+1)=P (I-μ R _Xx) W (n)+A carries out iterative processing, and satisfying || W (n+1)-W (n) || the output weights otherwise are proceeded iterative processing as final weights during≤δ, and wherein, δ is predefined thresholding, and μ is a step factor, and n be more than or equal to zero integer.

6, the beam form-endowing method of smart antenna according to claim 5 is characterized in that, the correlation matrix R of described reception data _XxCan be by carrying out the statistical correlation processing or averaging relevant $R_{\mathrm{xx}}=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{X}^H\left(i\right)X\left(i\right)$ Handle or carry out instantaneous relevant R _Xx=X ^H(i) X (i) handles and obtains, and wherein, N is the number of channel; Described projection operator can be by making P=I-H (H ^HH) ^-1H ^HObtain; Described constant vector can be by making A=H (H ^HH) ^-1A obtains; Described weights initial value can obtain by making W (0)=A.

7, the beam form-endowing method of smart antenna according to claim 5 is characterized in that, step factor $0<\mathrm{\&mu;}<\frac{2}{{\mathrm{\&lambda;}}_{\max }},$ λ wherein _MaxBe R _XxEigenvalue of maximum.

8, the beam form-endowing method of smart antenna according to claim 5 is characterized in that, the channel estimation process process in step 1 can be passed through h _i=(M ^HM) ^-1M ^He _iObtain the channel estimating of all users on all antennas, wherein M is the training matrix of all users' training sequence composition, e _iBe the numerical value of the training sequence that in a pulse, receives of i root antenna, h _iBe the impulse response of each channel, 1≤i≤N.

9, the beam form-endowing method of smart antenna according to claim 5 is characterized in that, can pass through in step 2 $\mathrm{power}\_{\mathrm{user}}_k\left(m\right)=\frac{1}{N}\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{\left|h_{i,k}\left(m\right)\right|}^2$ Average power on each discrete point of acquisition channel, wherein m represents the sequence number in footpath, and k represents k user, and N is the number of channel, h _{I, k}Be the impulse response of i channel of k user, and 1≤i≤N.

10, a kind of beam size enlargement apparatus of smart antenna comprises

N identical omnidirectional antenna units;

N radio-frequency (RF) transceiver, each radio-frequency (RF) transceiver is equipped with A-D converter and digital-to-analog converter;

Baseband processor is provided with and an a described N radio-frequency (RF) transceiver corresponding N channel estimator and an adaptive signal processor, is used to realize that adaptive weights calculate; It is characterized in that described adaptive signal processor comprises:

The average power estimator module, be used for the average power on each discrete point on all antennas that N channel impulse response according to the output of described channel estimator calculate each user, and find out the pairing channel of at least one maximum power and export as the strong footpath in the multipath;

Matrix maker module is used for according to the strong footpath sequence number of described average power estimator output the channel impulse response of the described channel estimator output of correspondence by column vector generator matrix H;

Calculator modules is used for calculating projection operator P and constant vector A and output according to matrix H;

Correlation matrix maker module, the data that are used for described antenna is received generate correlation matrix R _XxAnd output;

The self-adaptive processing module is used for the output according to described calculator modules and correlation matrix maker module, carries out self-adaptive processing, the weights of output adaptive, and then the figuration of realization wave beam.

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