CN103260240B - Based on the scattering signal source locating method of distribution coupling in extensive MIMO - Google Patents
Based on the scattering signal source locating method of distribution coupling in extensive MIMO Download PDFInfo
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Abstract
In extensive mimo systems (MIMO), operation steps based on the scattering signal source locating method of probability distribution coupling is as follows: (1) Signal Pretreatment stage: the average autocorrelation matrix calculating the user's signal received, and be multiplied with it with the response vector of antenna array, obtain the vector expression of the probability density function at the user Bo Da angle (DOA) of superposition. (2) in the iterative estimate stage: the vector that normalization method obtains, obtain the positional information of user by probability density function coupling, in normalized vector, then delete this part signal estimated. This process is after repeatedly loop iteration, so that it may obtain the positional information of all users. The present invention utilizes the nearly orthogonal of the antenna response vector of extensive MIMO that the average autocorrelation matrix of Received signal strength is converted into vector, and obtains customer position information by the method for probability distribution coupling. The inventive method under the prerequisite improving customer position information estimated accuracy, can reduce the complexity estimated.
Description
Technical field
The present invention relates to a kind of for the scattering signal source locating method in extensive MIMO, exactly, it is a kind of estimate the center DOA of scattering information source and the method for angle spread, belongs to wireless communication technology field.
Background technology
Along with the continuous growth of data service, existing antenna amount has been difficult to meet system to the demand of spectrum effectiveness. By increasing the antenna amount of base station, it is possible to greatly improve diversity gain and the spatial multiplexing gain of system, which forms extensive mimo system. In large-scale and multiple users mimo system, base station is configured with hundreds and thousands of antennas, and each user only configures an antenna, adopt time-division duplex, all signal processing, comprise channel estimating, signal detection and signal precoding all in base station process, reduce the computation burden of user terminal. But, owing to antenna array area is limited, the sky distance between centers of tracks of extensive array antenna is less, and in rural area and suburb, owing to the angle spread of signal is less, the Received signal strength of antenna for base station exists dependency. Consequently, it is desirable to adopt beam forming technique to obtain directivity gain of antenna instead of the space diversity gain (shown in Figure 1) of wide-angle expansion. And beam forming technique needs the positional information of user, namely the DOA of user's signal estimates. Different from the localization method in radar system, in radio communication system, signal have passed through multipath reflection and arrives base station, and therefore the DOA of signal is the multiple value in certain scope instead of a value, and information source then shows as scattering information source. Due to the general Gaussian distributed of DOA of multipath signal, so in a wireless communication system, the localization method of scattering information source is exactly average and the variance of estimating DOA distribution, and corresponding is exactly center DOA and the angle spread of scattering information source. But in extensive mimo system, traditional DOA estimation method complexity for scattering information source is extremely high, so reducing complexity is that can scattering source DOA estimation method the key point of through engineering approaches.
In extensive MIMO, computation complexity is a most important problem of implementation. Existing method of estimation is all the calculating based on matrix, and wherein the search coverage of part method is very big. The best method of estimation of performance is maximum likelihood (ML) and approximate maximum likelihood (AML) algorithm, but, search for each time and all contain matrix computations, and the variable of search comprises the angle information of each user's signal power, noise power and each user, therefore complexity is the highest, it is difficult to practical in extensive mimo system. Covariance matching estimates that (COMET) method is by coupling covariance matrix and average cross-correlation matrix, can close to ML algorithm performance, although the calculated amount searched for each time reduces to some extent, but the scope of search does not become, so complexity is still very high. Based on the method for subspace and the method based on wave beam shaping, there is similar estimation expression formula, the orthogonality that wherein make use of pseudo noise space and noiseless covariance matrix based on the method for subspace estimates center DOA and angle spread, and the method being shaped based on wave beam obtains the estimated value of positional information by minimise interference power. The scope of the search of these two kinds of methods has only included center DOA and the angle spread of single user, and complexity greatly reduces than ML and COMET, but search still contains matrix computations every time, so complexity is still higher.
In addition, existing method of estimation is all assume that the angle spread of each user is less, then utilize the approximate expression of Taylor expansion acquisition signal covariance matrix to carry out the estimation of positional information, but this kind is similar to and has relatively big error when angle spread is bigger, the performance of existing method of estimation can be caused to reduce along with the increase of angle spread.
So for the problem of performance and complexity these two aspects in existing method, the present invention proposes the method for estimation of the scattering information source center DOA of a kind of low complex degree and angle spread.
Summary of the invention
In view of this, it is an object of the invention to provide a kind of method utilizing probability distribution coupling to carry out low complex degree location in extensive mimo system, namely a kind of in extensive mimo system, utilize probability distribution coupling to estimate the low-complexity method of center DOA and angle spread. The inventive method make use of the nearly orthogonal of antenna response vector in extensive mimo system, the average cross-correlation matrix based on response vector is converted into one and observes vector. Each search only carries out the calculating of vector, and only needs to search for center DOA and the angle spread of single user, fundamentally reduces the complexity of calculating. And the inventive method carrys out approximate covariance matrix by extensive antenna amount, instead of as existing method by assuming little angle spread carry out approximate covariance matrix, thus reduce the evaluated error under wide-angle expansion condition, it is to increase estimated performance.
In order to achieve the above object, the present invention provides in a kind of extensive mimo system the scattering signal source locating method mated based on probability distribution, for following scene: the communication system comprising a base station and multiple user, within for some time, all users are to base station transmit signals; Base station large-scale antenna array is even linear array; All users and antenna for base station battle array are in same plane; Under the effect of base station power control, the signal to noise ratio of all users is similar to identical. It is characterized in that: described method comprises following two operation stepss:
(1) the Signal Pretreatment stage: the estimation of average autocorrelation matrix as signal covariance matrix calculating the user's signal vector received, and with antenna array to the response of different angles vector and average autocorrelation matrix multiple, obtain the vector expression of the probability density function of the user DOA of superposition. The concrete steps being put forward Signal Pre-Processing Method are as follows:
(11) the signal vector received is multiplied with the conjugate transpose of self and obtains a matrix, multiple for different time-gap such matrix is added and on average just obtains average autocorrelation matrix, and this average autocorrelation matrix is by the estimation as signal covariance matrix.
(12) being divided into M section-90 �� to 90 ��, M is antenna for base station quantity, and the antenna response vector corresponding to end points angle of all sections has nearly orthogonal. Take advantage of average autocorrelation matrix in premultiplication and the right side with its conjugate transpose of these vector sums simultaneously, thus obtain one and observe vector.
(13) this minimum value observing vector is by as the estimation receiving noise, each value that this is observed vector subtracts this minimum value, obtains the vector expression of the DOA distribution of all users of superposition.
Obviously, if antenna for base station quantity M is more big, so the orthogonality of antenna response vector is more strong, so these response vectors can be tieed up one group of orthogonal basis of complex space as M, and the element of the observation vector obtained is exactly M eigenwert of Received signal strength covariance matrix. When each element observing vector is not identical, this observes vector with covariance matrix is one to one. Therefore, estimate that angle parameter can not bring the loss in precision by observation vector. By each element observed in vector being subtracted the minimum value of this vector, eliminate noise power in the part observed in vector, thus obtain the vector expression of the DOA distribution of all users of superposition. The method of estimation carried due to the present invention carrys out very greatly approximate covariance matrix by extensive antenna amount, instead of assumes that Small angle expansion carrys out approximate covariance matrix, thus fundamentally reduce the source of error of estimation, it is to increase estimated accuracy. Further, the vector of acquisition can represent for the superposition that all user DOA distribute, so become the multiplication of vector when carrying out search calculating every time from the multiplication of matrix. Owing to noise power is eliminated, search does not comprise signal power and noise power. Therefore, fundamentally reduce the complexity of calculating.
(2) the iterative estimate stage: by the vector of normalization method first stage acquisition, and mate, with probability density function, the positional information that this vector obtains user, then delete the signal of the user estimated from normalized vector. This process is after repeatedly loop iteration, so that it may to obtain the positional information of all users. The concrete steps being put forward iterative estimate method are as follows:
(21) with this vector of the maximum value normalization method of the vector obtained, then subtract normalized vector with the vector of normalization method probability density function, and calculate the mould of this difference vector. Then, by changing average and the variance of normalization method probability density function, search for the minimum value of this modulus value. The normalization method probability density function that so minimum value is corresponding is exactly the DOA normalization method probability density function of one of them user, thus obtains the center DOA of this user and the estimation of angle spread.
(22) from normalized vector, subtract the vector of the normalization method probability density function of first estimating user, and repeat above-mentioned steps and obtain the center DOA of the 2nd user and the estimation of angle spread. Move in circles, until estimating the positional information of all users.
When the DOA distribution function nearly orthogonal of each user, namely the absolute value of the difference of the center DOA of two users much larger than angle spread and time, in step (21), mould square can approximate representation be the sum of squares that the vector of all user's normalization method probability density functions and normalized vector subtract each other rear delivery. Due to square being inversely proportional to the variance of probability distribution function of mould, so increasing along with antenna for base station quantity and the probability distribution function of each user is tending towards mutually orthogonal, final estimate that asymptotic convergence is to real center DOA and angle spread. Further, the vector owing to obtaining in step (21) is the superposition of probability distribution, by search local minimum, it is possible to obtain the approximate evaluation of the center DOA of all users, the scope therefore searched for greatly reduces, and complexity reduces further.
The present invention is a kind of for the method for estimation of the customer center DOA in extensive mimo system and angle spread based on the localization method that probability distribution is mated. Its advantage is: under the prerequisite improving estimated performance, greatly reduce computation complexity. The innovation of the inventive method it is crucial that: utilize large-scale antenna array to the nearly orthogonal of the response vector of different angles, the average autocorrelation matrix of signal is converted into and observes vector, this element observing vector is approximately the eigenwert of average autocorrelation matrix, almost not loss of accuracy when observe, by this, the positional information that vector obtains all users. The present invention is the method for estimation of a kind of low complex degree, can be shaped for the wave beam of extensive mimo system and realize providing accurate angle information.
Accompanying drawing explanation
Fig. 1 is the present invention's application scene: scattering information source DOA schematic diagram.
Fig. 2 is the schema of localization method in the extensive MIMO of the present invention.
Fig. 3 is in the embodiment of the present invention, and center DOA estimates the analogous diagram of root-mean-square error (RMSE) with antenna amount relation.
Fig. 4 is in the embodiment of the present invention, and angle spread estimates the analogous diagram of RMSE and antenna amount relation.
Embodiment
For making the object, technical solutions and advantages of the present invention clearly, below in conjunction with accompanying drawing, the present invention is described in further detail.
See Fig. 1, first introducing the application scene of the inventive method: the communication system comprising a base station and multiple user, within for some time, all users are to base station transmit signals; Base station large-scale antenna array is even linear array; All users and antenna for base station battle array are in same plane; Under the effect of base station power control, the signal to noise ratio of all users is similar to identical;For the average cross-correlation matrix of base station received signal; zj, j=1,2 ..., M, be withRelevant value;For the value after normalized vector before kth time iteration; For By the value after maximum value normalization method.
See Fig. 2, introduce following two operation stepss of the inventive method:
(1) the Signal Pretreatment stage: the estimation of average autocorrelation matrix as signal covariance matrix calculating the user's signal vector received, and with antenna array to the response of different angles vector and average autocorrelation matrix multiple, obtain the vector expression of the probability density function of the user DOA of superposition. The content of operation of this step is:
(11) the average cross-correlation matrix of Received signal strength is calculated
(12) scope of-90 �� to 90 �� being evenly divided into M decile, M is antenna for base station quantity, and with the response of every section of end points angle calculation array antenna vector, and premultiplication and the right side are taken advantage of respectively with its conjugate transpose of this vector sumObtain zj,j=1,2,��,M��
(13) each zj, j=1,2 ..., M, each element subtract its minimum value, obtain K=0 is set.
(2) the iterative estimate stage: by the vector of normalization method first stage acquisition, and mate, with probability density function, the positional information that this vector obtains user, then delete the signal of the user estimated from normalized vector. This process is after repeatedly loop iteration, so that it may to obtain the positional information of all users. Concrete steps are as follows:
(21) k=k+1, judges whether k equals K+1. If lower than target value, then carry out following step, otherwise terminate algorithm.
(22) use Maximum element normalization method Obtain
(23) by search, searching makesSquare minimum center DOA and the angle spread of rear delivery is subtracted each other, as the estimated value of this user perspective parameter with the vector expression of normalization method probability density function.
(24) calculate normalization method probability density function with the angle parameter that estimates, then from In subtract this normalization method probability density vector expression, obtain
(25) step (21) is returned.
In order to show the low complex degree of the inventive method, at the computation complexity of this simple analysis special case. When antenna for base station quantity is 100, number of users is 2, and maximum angle expands to 4 ��, and search step-length is 0.1 ��, and the order of magnitude of the complex multiplication that traditional method needs is at least 7.2 �� 108, and the order of magnitude of the complex multiplication that the inventive method needs is 1.28 �� 106, it is seen that adopt the inventive method can significantly reduce computation complexity.
In order to show the Practical Performance of the inventive method, applicant carried out Multi simulation running and implement test. In pilot system network configuration models be the application scene shown in Fig. 1. As shown in Figure 3 and Figure 4, estimation two aspects from the estimation of center DOA and angle spread have emulated the result of l-G simulation test respectively. In order to embody the superiority of the inventive method intuitively, the localization method of the emulation result of present method and existing scattering information source is contrasted.
As seen from Figure 3, the inventive method significantly reduces the RMSE that center DOA estimates, the method that is proposed can improve the estimated accuracy of center DOA. Fig. 4 shows, the angle spread that the inventive method obtains estimates that, close to the method based on subspace, performance is better than other method simultaneously. First precision owing to estimating is based upon on the precision basis that center DOA estimates, and then compares the estimated accuracy of angle spread, the inventive method for the estimated accuracy of center DOA and angle spread higher than other method.
The foregoing is only the preferred embodiments of the present invention, not in order to limit the present invention, within the spirit and principles in the present invention all, any amendment of making, equivalent replacement, improvement etc., all should be included within the scope of protection of the invention.
Claims (3)
1., based on the scattering signal source locating method of probability distribution coupling in extensive MIMO, for following scene: the communication system comprising a base station and multiple user, within for some time, all users are to base station transmit signals; Base station large-scale antenna array is even linear array; All users and antenna for base station battle array are in same plane; Under the effect of base station power control, the signal to noise ratio of all users is similar to identical; It is characterized in that: described method comprises following two operation stepss:
(1) the Signal Pretreatment stage: the estimation of average autocorrelation matrix as signal covariance matrix calculating the user's signal vector received, and with antenna array to the response of different angles vector and average autocorrelation matrix multiple, obtain the vector expression of the probability density function of the user DOA of superposition;
(2) the iterative estimate stage: the vector in first stage is normalized by the maximum value in the vector of the probability density function of the user DOA of obtained superposition, search represents, with the vector of normalization method probability density function, square minimum center DOA and the angle spread of subtracting each other rear delivery, as the estimated value of this user perspective parameter, from normalized vector, subtract the vector expression of the normalization method probability density function of first estimating user, obtain the estimated value of the angle parameter of the 2nd user; Move in circles, until estimating the positional information of all users.
2. method according to claim 1, it is characterised in that: in described step (1), Signal Pretreatment comprises following content of operation further:
(11) the signal vector received is multiplied with the conjugate transpose of self and obtains a matrix, multiple for different time-gap such matrix being added and average just acquisition average autocorrelation matrix, this average autocorrelation matrix is by the estimation as signal covariance matrix;
(12) being divided into M section-90 �� to 90 ��, M is antenna for base station quantity, and the antenna response vector corresponding to end points angle of all sections has nearly orthogonal; Take advantage of average autocorrelation matrix in premultiplication and the right side with its conjugate transpose of these vector sums simultaneously, thus obtain one and observe vector;
(13) this minimum value observing vector is as the estimation receiving noise, and each value that this is observed vector subtracts this minimum value, obtains the vector expression of the DOA distribution of all users of superposition.
3. method according to claim 1, it is characterised in that: described step (2) comprises following content of operation further:
(21) with this vector of the maximum value normalization method of the vector obtained, then normalized vector is subtracted with the vector of normalized probability density function, and the vector calculating normalized probability density function subtracts the mould of this difference vector of normalized vector; Then, by changing average and the variance of normalization method probability density function, the minimum value of search difference vector modulus value; The normalization method probability density function that so minimum value is corresponding is exactly the DOA normalization method probability density function of one of them user, thus obtains the center DOA of this user and the estimation of angle spread;
(22) from normalized vector, subtract the vector of the normalization method probability density function of first estimating user, and repeat above-mentioned steps and obtain the center DOA of the 2nd user and the estimation of angle spread; Move in circles, until estimating the positional information of all users.
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| CN105450274B (en) * | 2015-11-09 | 2018-11-23 | 东南大学 | Based on the extensive multiple antennas relay system number of users optimization method that efficiency is optimal |
| US9989633B1 (en) * | 2017-03-15 | 2018-06-05 | Cypress Semiconductor Corporation | Estimating angle measurements for source tracking using a phased array system |
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