CN110034829B - Anti-interference method and device for multi-user wireless communication system - Google Patents

Anti-interference method and device for multi-user wireless communication system Download PDF

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CN110034829B
CN110034829B CN201910189901.2A CN201910189901A CN110034829B CN 110034829 B CN110034829 B CN 110034829B CN 201910189901 A CN201910189901 A CN 201910189901A CN 110034829 B CN110034829 B CN 110034829B
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interference
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communication system
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CN110034829A (en
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陈佳义
张常运
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Shenzhen University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B15/00—Suppression or limitation of noise or interference
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04K—SECRET COMMUNICATION; JAMMING OF COMMUNICATION
    • H04K3/00—Jamming of communication; Counter-measures
    • H04K3/20—Countermeasures against jamming
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/24—Cell structures
    • H04W16/28—Cell structures using beam steering

Abstract

The invention discloses an anti-interference method and an anti-interference device of a multi-user wireless communication system.A UA array is modeled to form a circular array, and antenna units in the circular array are mutually connected through a return network so as to process received and transmitted signals; the UA array forms a beam for each mobile device, the main lobe of the beam points to the position of a user, and an excitation function consisting of weighted harmonics and applied to an antenna element before information transmission is obtained through Fourier transformation; carrying out interference elimination processing on the signals, and introducing a Bessel function to decompose the received interference into components with different spatial frequencies; and forcibly executing relevant constraint control interference items to be invalid through zero forcing transmission, and truncating the components meeting the conditions to suppress the interference. The present invention suppresses interference between multiple users by decomposing the interference into components having different spatial frequencies, the value of each component depending on the ratio of the distance between mobile stations to the wavelength, making the product of the components and the coefficients zero.

Description

Anti-interference method and device for multi-user wireless communication system
Technical Field
The invention relates to the technical field of communication networks, in particular to an anti-interference method and device for a multi-user wireless communication system.
Background
A cloud Radio access network (C-RAN) is a new architecture designed for next generation wireless networks, in which hardware devices are simplified to low complexity Remote Radio Units (RRUs), each of which integrates an antenna and a Radio Frequency (RF) component. The RRUs are connected to the data center by fiber optics for high speed data transmission, and moreover, the low cost and complexity of the RRUs enable their dense deployment to improve network coverage and capacity. In the C-RAN, Base station processing units (BBU) are centralized together, and the centralized signal processing function can realize cloud computing, reduce network operation cost and energy consumption, promote network upgrading and reduce multi-user interference. As it evolves, the cells in a traditional cellular network disappear and the mobile device communicates with a large antenna array (UA) with everywhere. Wherein UA is defined as: the recent trend towards centralized signal processing in radio access networks has shown that future networks may contain ubiquitous antennas that form a large array of antennas in a wide range.
A UA communication network can be considered as an ultimate extension of the MIMO (Multiple-Input-Multiple-Output) network, since it has many antenna elements, providing ubiquitous access to wireless networks. Unlike conventional point-to-point or multipoint-to-point systems, in UA systems, where the mobile devices are surrounded by dense antennas, signals reach the mobile stations from all directions, and when data is transmitted, the mobile stations inevitably interfere with each other.
In mobile communication, if a plurality of users occupy the same time-frequency resource when transmitting or receiving signals, there is a problem of multi-user interference. For an uplink of a multi-user MIMO system, the multi-user interference problem is a multi-user detection problem; for the downlink of a multi-user MIMO system, the multi-user interference problem can be expressed as a base station precoding problem.
The multi-user detection is proposed so far, and various proposed algorithms are infinite, and can be divided into two categories, namely linear multi-user detection and nonlinear multi-user detection according to different algorithm implementation modes.
In linear multi-user detection, the decorrelating detector and the minimum mean square error detector are two classical detection algorithms. The linear transformation matrix for decorrelating multi-user detection is the inverse matrix of the cross-correlation matrix of the spread spectrum sequences of all users, and is characterized in that multi-user interference is completely eliminated, the optimal near-far resistance performance can be obtained under the condition that the power of other users is unknown, but the complete inhibition of the multi-user interference is at the cost of noise amplification. The minimum mean square error multi-user detector considers the influence of multi-user interference and noise on the system performance, and takes the minimum mean square error as a performance evaluation index, so that the compromise between multi-user interference suppression and noise amplification can be obtained. The performance of a minimum mean square error detector is generally better than a decorrelating detector.
Because the linear multi-user detection method has high complexity and slow convergence, the research direction considered from the realizability point of view is mainly focused on the nonlinear multi-user detection method. Non-linear multi-user detection includes Parallel Interference Cancellation (PIC), Serial Interference Cancellation (SIC). The parallel interference cancellation detector makes an initial decision on the output of the matched filter of each user, uses it to estimate the multiple access interference, and subtracts it from the initial output to obtain an output closer to the true transmitted signal, then makes a decision and an estimation, and so on, and repeats the above steps until obtaining the expected performance index. The serial interference cancellation detector performs data decision for each of a plurality of users in a received signal, and determines one of them to reproduce the signal and subtract a multiple access interference caused by the user signal.
The base station precoding technology is that under the condition that the channel state information is known, a transmitting end carries out preprocessing operation on a transmitting signal by using the channel state information, so that the throughput of a user and a system is further improved. The user terminal sends an uplink pilot signal to the base station, the base station estimates a channel according to the received pilot signal change, and the base station performs pre-interference suppression coding on the sent signal by using the obtained channel related information, so that the signal when the signal after the pre-interference suppression coding reaches the user terminal after being transmitted through the channel is just the signal before the pre-interference suppression coding. In the technology, the sending ends need to be mutually coordinated, and the downlink transmission is easy to realize. The precoding techniques can also be classified into codebook-based precoding methods and non-codebook-based precoding methods.
The precoding method based on the codebook requires that a sending end and a receiving end share the same codebook set, then a matrix which enables the system performance to be optimal is selected from a determined matrix set according to the specific channel condition, and the serial number of the matrix in the codebook set is fed back to the sending end. The precoding scheme enables the data volume required to be transmitted by the feedback channel to be small, and the data volume is only several bits, so that the cost is greatly saved.
The non-codebook precoding utilizes the reciprocity characteristic of a channel, obtains uplink channel information according to an uplink sending signal, obtains downlink channel information based on the channel reciprocity, and utilizes the obtained channel information to carry out matrix decomposition to generate a required precoding matrix. The non-codebook precoding method has outstanding advantages in a TDD (time Division multiplexing) system, and reduces the overhead of uplink feedback.
However, the multi-user interference suppression technology in the prior art still cannot meet the requirement of communication development, that is, there is a problem that multi-user interference cannot be effectively suppressed.
Accordingly, the prior art is yet to be improved and developed.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide an anti-interference method and apparatus for a multi-user wireless communication system, which can suppress interference between multiple users by decomposing received interference into components with different spatial frequencies, wherein the value of each component depends on the ratio of the distance between mobile stations to the wavelength, and the product of the components and the coefficient is zero.
The technical scheme adopted by the invention for solving the technical problem is as follows:
an anti-interference method of a multi-user wireless communication system, wherein the anti-interference method of the multi-user wireless communication system comprises the following steps:
modeling the UA array to form a circular array, wherein antenna units in the circular array are connected with each other through a backhaul network to process received and transmitted signals;
the UA array forms a beam for each mobile device, the main lobe of the beam points to the position of a user, and an excitation function consisting of weighted harmonics and applied to an antenna element before information transmission is obtained through Fourier transformation;
carrying out interference elimination processing on the signals, and introducing a Bessel function to decompose the received interference into components with different spatial frequencies;
and forcibly executing relevant constraint control interference items to be invalid through zero forcing transmission, and truncating the components meeting the conditions to suppress the interference.
The invention focuses on studying the signal processing aspect of the UA communication system, considering that data of multiple users are transmitted in free space, where the power between any two users is proportional to the distance between them; the interference strength between two users decreases as the user separation distance increases; thus, even given a single-user transmission, interference can be suppressed by increasing the distance of the users; furthermore, path loss is inversely proportional to distance regardless of the distance between users in circular and spherical UA communications.
The low complexity precoding proposed by the present invention can be specifically designed with the fourier series of the circular UA and the spherical harmonics of the spherical UA, whose coefficients are set to excite different phase patterns of the circular array, mainly to decompose the received interference into components with different spatial frequencies, where the value of each component depends on the ratio of the distance between the mobile stations and the wavelength, making the product of these components and coefficients zero, thereby suppressing the interference between multiple users.
Drawings
FIG. 1 is a flow chart of a preferred embodiment of the interference rejection method of the multiuser wireless communication system of the present invention;
FIG. 2 is a schematic diagram of UA modeled as a circular array in a preferred embodiment of the interference rejection method of the multiuser wireless communication system of the present invention;
FIG. 3 is a diagram illustrating a zero-order Bessel function graph according to a preferred embodiment of the interference suppression method for a multiuser wireless communication system in accordance with the present invention;
FIG. 4 is a schematic diagram of UA modeled as a spherical UA array in a preferred embodiment of the interference rejection method of the multiuser wireless communication system in accordance with the present invention;
FIG. 5 is a schematic diagram of an operating environment of an anti-jamming device of a multi-user wireless communication system according to a preferred embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
An anti-interference method of a multi-user wireless communication system according to a preferred embodiment of the present invention is, as shown in fig. 1, an anti-interference method of a multi-user wireless communication system, wherein the anti-interference method of the multi-user wireless communication system includes the following steps:
step S10, modeling the UA array to form a circular array, where the antenna elements in the circular array are interconnected through a backhaul network to process the received and transmitted signals.
Specifically, as shown in FIG. 2, UA is modeled as a circular array with a center of circle o and a radius of radius r0(ii) a It is assumed that the distribution of dense UAs is continuous, which facilitates theoretical analysis. The system includes a UA centered at an origin and a single antenna user surrounded by the UA. Then the polar coordinates of each user X are
Figure BDA0001994067240000061
Wherein r isX> 0 is the distance from the origin,
Figure BDA0001994067240000062
is an angle relative to the positive x-axis. Suppose that each user X is a large distance from the array, r0＞＞rXSo that user X to any antenna a ═ (r)0And θ) can be approximated as:
Figure BDA0001994067240000063
the antenna elements in the array are interconnected by a backhaul network so that they can cooperatively process received and transmitted signals.
All antennas are omni-directional, and assuming there are U users in the network, X can be used1,Λ,Xu,Λ,XURepresents, user XuThe channel response between antenna A is available hu(theta) is represented by the following formula
Figure BDA0001994067240000071
Where g and q are the antenna gains of the mobile station user and the array elements, set to constants, and λ represents the wavelength.
Precoding a transmission signal using the obtained channel-related information, if the channel information is knownu(theta) design of xuRepresenting data symbols sent by UA to user u. The signal transmitted by the antenna a (θ) can thus be represented as
Figure BDA0001994067240000072
The signal received at the subscriber is as follows:
Figure BDA0001994067240000073
wherein z isuIs a mean of 0 and a variance of σ2White gaussian noise.
Step S20, the UA array forms a beam for each mobile device, and the main lobe of the beam points to the position of the user, and obtains the excitation function consisting of weighted harmonics applied to the antenna elements before transmitting information by fourier transform.
Specifically, the design of the precoder specifically includes: the UA array may form one beam for each mobile device, the main lobe of the beam pointing to the user's location.
Interference between users is inevitable and in order to eliminate the interference between them, Spatial Zero-forcing (SZF) transceivers have been proposed, which are designed based on weighted combinations of different beams in the array. Since the array is circular and the precoder function is a periodic function with a period of 2 pi, a general form consisting of weighted harmonics can be obtained by fourier transformation as given in equation (4), which can be viewed as the excitation function applied to the antenna elements before transmitting the information.
Figure BDA0001994067240000081
Wherein, cu01, and when m ≠ 0, cu,mWith 0, different harmonics correspond to different transmission beam patterns, and the superposition of these transmission beams, i.e. the coefficient c, is weightedu,mBy performing the planning, SZF can be realized.
As can be seen from equation (4), the mth harmonic has
Figure BDA0001994067240000082
Spatial frequency (period/radian). Coefficient cu,mMay be considered as spatial filtering of these spatial harmonic components to produce the transmission beam pattern of the desired user. The designed filter can therefore invalidate the beam pattern at other mobile stations, this method is called SZF. Assuming that the filter has unity power, i.e.
Figure BDA0001994067240000083
Substituting equation (4) into equation (3) results in the signal received at the mobile station:
Figure BDA0001994067240000084
the first term is the desired signal, the second term is the interference of other users to the desired user, and the third term is noise, so as to make the interference term invalid.
Step S30, performing interference cancellation processing on the signal, and introducing a bezier function to decompose the received interference into components with different spatial frequencies.
Specifically, before eliminating interference, a first type of bessel function needs to be introduced, and an nth order bessel can be defined by formula (7), wherein n is an integer.
Figure BDA0001994067240000091
As shown in fig. 3, fig. 3 is a zero order bezier function graph.
From the bezier function it follows:
Figure BDA0001994067240000092
wherein m is an integer, d (X)1；X2) Is X1And X2A distance therebetween, and
Figure BDA0001994067240000093
the interference can be decomposed into components Ψ having different spatial frequenciesk,u,mFrom equation (6), we can obtain:
Figure BDA0001994067240000094
factor in equation (10)
Figure BDA0001994067240000101
This can be derived from equation (2):
Figure BDA0001994067240000102
wherein is higher than
Figure BDA0001994067240000103
The higher order terms of (2) are ignored.
Substituting equation (8) and equation (11) into equation (10) may further evolve Ψk,u,m：
Figure BDA0001994067240000104
And step S40, forcibly executing relevant constraint control interference item invalidation through zero forcing transmission, and cutting off and suppressing the interference of the components meeting the conditions.
In particular, with zero-forcing transmission, the interference term can be invalidated by enforcing the following constraints:
Figure BDA0001994067240000105
it is necessary to first prove the infinite series number c in the above formulak,mTo Ψk,u,mWhether the product has convergence.
Figure BDA0001994067240000111
From the formulas (5) and (14), c can be knownk,mTo Ψk,u,mThe product of (c) has convergence.
In the transmission beam pattern of mobile station U, where there are U-1 nulls, there are U-1 coefficients c corresponding to the other U-1 mobile station usersk,mWhere m ═ infinity, Λ,0, Λ, ∞, and has U-1 constraint equations as in equation (13). Because there are more variables than equations, the constraint equation solution can be solved, and the interference of other users can be eliminated as long as the solution is obtained.
Each component Ψk,u,mThe value of (A) depends on the ratio of the distance between the mobile stations to the wavelength, which needs to be provided for those with
Figure BDA0001994067240000112
(wherein
Figure BDA0001994067240000113
Is the largest integer not greater than x) of the components Ψk,u,mTruncation is performed because it is difficult to achieve over the entire set, and there is no significant error introduced in equation (13) after truncation. The corresponding coefficient set is denoted as cu,mL 1 ≦ U ≦ U ≦ M, and { Ψ ≦ M }, andu,k,mif 1 is equal to or less than U, k is equal to or less than U, and M is equal to or less than M, then equation (13) can be written in matrix form:
Ψucu＝0 (15)；
wherein the matrix ΨuAnd vector cuCan be represented as follows:
Figure BDA0001994067240000121
let the number of truncation terms M be:
Figure BDA0001994067240000122
the second parameter of the above formula ensures ΨuThe existence of null space only needs to solve the coefficient of SZF, namely the solution c of the equationuThe interference of other users can be eliminated.
SZF coefficient c of u-th user according to the number of truncation itemsuCan be expressed as:
Figure BDA0001994067240000123
wherein span (A) is the expansion space of A (A)-Moore-Penrose inverse matrix of A, K
Figure BDA0001994067240000124
The received Signal-to-Noise Ratio (SNR) can be written as:
Figure BDA0001994067240000125
wherein, PuFor the transmit power, the power of the signal received by user u can be obtained, and its maximum value can be expressed as:
Figure BDA0001994067240000131
wherein e is0＝[0,Λ,0,1,0,Λ,0]TIs a unit vector, vector e0The front and the back of the middle element 1 are provided with M0 elements, | | cu0||2PuThe coefficient c for the power of the received signal for the u-th useru0||2Can be expressed as:
Figure BDA0001994067240000132
due to cuIn a subspace
Figure RE-GDA0002050130120000133
When c is aboveuAnd e0In that
Figure RE-GDA0002050130120000134
When the projections are aligned, the maximum correlation between them is realized, and therefore, the coefficient | | cu0||2Is equal to e0Norm of projection on subspace, i.e.
Figure BDA0001994067240000135
Further, according to the above-mentioned interference suppression method in the circular UA array, the communication system can also be modeled as a spherical UA array, as shown in fig. 4, where the center of the circle is o and the radius is r0. The system comprises a UA with origin as center and U single-antenna users surrounded by UA, the position of user is X1,X2,ΛXuAnd (4) showing. Then XuHas the coordinates of
Figure BDA0001994067240000136
The coordinates of the antenna A are
Figure BDA0001994067240000137
Wherein
Figure BDA0001994067240000138
Is the azimuth angle (theta)uAnd θ) is the polarization angle.
In a spherical UA communication system, the precoder function is changed to:
Figure BDA0001994067240000139
in the above formula { cu,m,ιThe coefficients of the precoder are designed,
Figure BDA00019940672400001310
is a spherical harmonic function, where iota ≦ 0,1, Λ, and-iota ≦ m ≦ iota.
Figure BDA00019940672400001311
Can be expressed as:
Figure BDA0001994067240000141
Figure BDA0001994067240000142
can be expressed by legendre polynomials:
Figure BDA0001994067240000143
then at XuReceived signal
Figure BDA0001994067240000144
Can be expressed as:
Figure BDA0001994067240000145
wherein, PtTo transmit power, Ψu,k,m,ιComprises the following steps:
Figure BDA0001994067240000146
in the introduction of Bessel function Jm(x) Rear, Ψu,k,m,ιThe evolution becomes:
Figure BDA0001994067240000147
psi can be seen from the above formulau,k,m,ιAnd
Figure BDA0001994067240000148
and (4) in proportion. Then there will be a set of coefficients { Ψu,k,m,ιL 0 is less than or equal to l is less than or equal to M and { ck,m,ιL 0 ≦ l ≦ M }, the precoder is designed by enforcing the following constraints:
Figure BDA0001994067240000151
the constraints can be written in matrix form, such that
Figure BDA0001994067240000152
Is composed of
Figure BDA0001994067240000153
Line vector au,l＝[cu,-ι,ι,cu,-ι+1,ι,Λ,cu,ι,ι]Wherein iota is 0,1, Λ.
Can use
Figure BDA0001994067240000154
And au,lAs element definition
Figure BDA0001994067240000155
And
Figure BDA0001994067240000156
Figure BDA0001994067240000157
the matrix form of the constraint is then:
Figure BDA0001994067240000158
solving the coefficient of the precoder according to the matrix equation
Figure BDA0001994067240000159
Multi-user interference in a spherical UA communication system can be eliminated:
Figure BDA00019940672400001510
wherein the content of the first and second substances,
Figure BDA00019940672400001511
is composed of
Figure BDA00019940672400001512
To free space of (2), solve
Figure BDA00019940672400001513
Making the interference between multiple users 0, the SNR of the signal-to-noise ratio received by user u is:
Figure BDA00019940672400001514
existing interference suppression techniques are suitable for cellular networks, however, for the access network architecture C-RAN, cells in a cellular network are obscured and mobile devices communicate with a large antenna array with ubiquitous elements. The centralized signal processing function in the C-RAN can realize cloud computing, reduce network operation cost and energy consumption, promote network upgrading and reduce multi-user interference. Further research on the multi-user interference suppression technology is needed, so that the multi-user interference suppression technology is more suitable for future communication technologies. Unlike conventional point-to-point or multi-point-to-single-point systems, where the mobile devices in the UA system are surrounded by dense antennas, the signals reach the mobile devices from all directions. The interference strength between users can be attenuated along with the increase of the user separation distance, and the interference can not be suppressed only by increasing the distance between users, so that a multi-user precoder needs to be designed. Therefore, the low complexity precoding technique proposed in the UA communication system is designed by the fourier order number of the circular UA and the spherical harmonic of the spherical UA.
Further, as shown in fig. 5, based on the above anti-interference method for the multi-user wireless communication system, the present invention also provides an anti-interference apparatus for the multi-user wireless communication system, where the anti-interference apparatus for the multi-user wireless communication system includes a processor 10, a memory 20, and a display 30. Fig. 5 shows only some of the components of the jamming immunity device of the multi-user wireless communication system, but it should be understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead.
The storage 20 may in some embodiments be an internal storage unit of a tamper resistant device of the multi-user wireless communication system, such as a hard disk or a memory of a tamper resistant device of the multi-user wireless communication system. The memory 20 may also be an external storage device of the anti-jamming device of the multi-user wireless communication system in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, provided on the anti-jamming device of the multi-user wireless communication system. Further, the memory 20 may also include both an internal storage unit and an external storage device of the interference rejection apparatus of the multi-user wireless communication system. The memory 20 is used for storing application software installed in the anti-jamming device of the multi-user wireless communication system and various types of data, such as program codes of the anti-jamming device of the multi-user wireless communication system. The memory 20 may also be used to temporarily store data that has been output or is to be output. In an embodiment, the storage 20 stores an interference rejection program 40 of the multiuser wireless communication system, and the interference rejection program 40 of the multiuser wireless communication system can be executed by the processor 10, so as to implement the interference rejection method of the multiuser wireless communication system in the present application.
The processor 10 may be, in some embodiments, a Central Processing Unit (CPU), microprocessor or other data Processing chip, which is used to run program codes stored in the memory 20 or process data, such as performing interference rejection methods of the multi-user wireless communication system.
The display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch panel, or the like in some embodiments. The display 30 is used for displaying information at the jamming prevention means of the multi-user wireless communication system and for displaying a visual user interface. The components 10-30 of the interference rejection unit of the multi-user wireless communication system communicate with each other via a system bus.
In one embodiment, the following steps are implemented when processor 10 executes immunity program 40 of the multiuser wireless communication system in memory 20:
modeling the UA array to form a circular array, wherein antenna units in the circular array are connected with each other through a backhaul network to process received and transmitted signals;
the UA array forms a beam for each mobile device, the main lobe of the beam points to the position of a user, and an excitation function consisting of weighted harmonics and applied to an antenna element before information transmission is obtained through Fourier transformation;
carrying out interference elimination processing on the signals, and introducing a Bessel function to decompose the received interference into components with different spatial frequencies;
and forcibly executing relevant constraint control interference items to be invalid through zero forcing transmission, and truncating the components meeting the conditions to suppress the interference.
The invention also provides a storage medium, wherein the storage medium stores an anti-interference program of the multi-user wireless communication system, and the anti-interference program of the multi-user wireless communication system is executed by a processor to realize the anti-interference method of the multi-user wireless communication system; as described above.
In summary, the low complexity precoding proposed by the present invention can be specifically designed by using fourier series of circular UA and spherical harmonics of spherical UA, whose coefficients are set to excite different phase patterns of circular array, mainly to decompose the received interference into components with different spatial frequencies, where the value of each component depends on the ratio of the distance between mobile stations and the wavelength, and the product of these components and the coefficients is made zero, so as to suppress the interference between multiple users.
Of course, it will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by instructing relevant hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer readable storage medium, and the program can include the processes of the embodiments of the methods described above when executed. The storage medium may be a memory, a magnetic disk, an optical disk, etc.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.

Claims (10)

1. An anti-interference method for a multi-user wireless communication system, the anti-interference method for the multi-user wireless communication system comprising:
modeling a UA array to form a circular array, wherein antenna units in the circular array are connected with each other through a backhaul network to process received and transmitted signals, and the UA array represents a huge antenna array;
the UA array forms a beam for each mobile device, the main lobe of the beam points to the position of a user, and an excitation function consisting of weighted harmonics and applied to an antenna element before information transmission is obtained through Fourier transformation;
carrying out interference elimination processing on the signals, and introducing a Bessel function to decompose the received interference into components with different spatial frequencies;
and forcibly executing relevant constraint control interference items to be invalid through zero forcing transmission, and truncating the components meeting the conditions to suppress the interference.
2. The method of claim 1, wherein the value of each component of the different spatial frequencies is dependent on a distance to wavelength ratio between the mobile stations.
3. The interference rejection method for a multiuser wireless communication system according to claim 1, wherein the modeling of the UA array to form a circular array, wherein the interconnection of the antenna elements in the circular array through a backhaul network to process the received and transmitted signals specifically comprises:
the UA array is modeled as a circular array with a center of circle o and radius r0；
The circular array includes UA centered at the origin and single antenna users surrounded by UA, then each user X has polar coordinates of
Figure FDA0002554511350000011
Wherein r isX>0 is the distance from the origin point,
Figure FDA0002554511350000021
is an angle relative to the positive x-axis;
when r is0>>rXThen, user X to any antenna a ═ (r)0And θ) is expressed as:
Figure FDA0002554511350000022
theta denotes a polarization angle, and the antenna elements in the array are connected with each other through a backhaul network to cooperatively process received and transmitted signals; all antennas are omni-directional, and assuming there are U users in the network, X can be used1,Λ,Xu,Λ,XURepresents, user XuThe channel response between antenna A is available hu(θ) is represented as follows:
Figure FDA0002554511350000023
where g and q are the antenna gains of the mobile station user and the array elements, set to be constant, and λ represents the wavelength;
precoding a transmission signal using the obtained channel-related information, if the channel information is knownu(theta) design of xuRepresents the data symbols sent by the UA to user u, and therefore the signal sent by antenna a (θ) can be represented as
Figure FDA0002554511350000024
The signal received at the subscriber is as follows:
Figure FDA0002554511350000025
wherein z isuIs a mean value and is 0, and the variance is σ2White gaussian noise.
4. The interference rejection method for a multi-user wireless communication system according to claim 3, wherein said UA array forms a beam for each mobile device, and a main lobe of said beam is directed to a user location, and obtaining an excitation function consisting of weighted harmonics applied to antenna elements prior to transmission of information by Fourier transform specifically comprises:
the UA array forms a beam for each mobile device, and the main lobe of the beam points to the position of a user;
the precoder function is a periodic function with a period of 2 pi, the excitation function applied to the antenna elements before the transmission of information, consisting of weighted harmonics, being obtained by fourier transformation as follows:
Figure FDA0002554511350000031
wherein, cu01, m denotes the frequency of the signal after fourier transform, and when m ≠ 0, cu,m0, different harmonics correspond to different transmission beam patterns, and the coefficient c is adjusted by weighting the superposition of the transmission beamsu,mAnd (6) planning.
5. The method of claim 4, wherein the mth harmonic is derived from equation 4 to have a value of
Figure FDA0002554511350000032
The spatial frequency of (d); coefficient cumIs considered as a spatial harmonic componentTo produce a transmission beam pattern for the desired user; assuming that the filter has unity power, i.e.
Figure FDA0002554511350000033
Substituting equation 4 into equation 3 results in a signal received at the mobile station:
Figure FDA0002554511350000034
the first term is the desired signal, the second term is the interference of other users to the desired user, and the third term is noise.
6. The method of claim 5, wherein the performing interference cancellation on the signal and introducing the Bezier function to decompose the received interference into components with different spatial frequencies specifically comprises:
before eliminating interference, a Bessel function needs to be introduced, wherein an n-th order Bessel can be defined by a formula 7, wherein n is an integer;
Figure FDA0002554511350000041
from the bezier function it follows:
Figure FDA0002554511350000042
wherein m is an integer, d (X)1；X2) Is X1And X2A distance therebetween, and
Figure FDA0002554511350000043
the interference is decomposed into components Ψ having different spatial frequenciesk,u,mFrom equation 6, we obtain:
Figure FDA0002554511350000044
factor in equation 10
Figure FDA0002554511350000051
Can be derived from equation 2
Figure FDA0002554511350000052
Wherein is higher than
Figure FDA0002554511350000053
All higher order terms of (2) are ignored;
substituting equation 8 and equation 11 into equation 10 to further evolve Ψk,u,m：
Figure FDA0002554511350000054
7. The method according to claim 6, wherein the enforcing by zero-forcing transmission that the relevant constraint control interference item is invalid, and truncating the component that satisfies the condition to suppress interference specifically comprises:
the interference term is invalidated by forcing a zero-forcing transmission to enforce the following constraints:
Figure FDA0002554511350000055
it is necessary to first prove the infinite series number c in the above formulak,mTo Ψk,u,mWhether the product has convergence;
Figure FDA0002554511350000061
according to formula 5 and formula 14It can be seen that ck,mTo Ψk,u,mThe product of (a) has convergence;
in the transmission beam pattern of mobile station U, where there are U-1 nulls, there are U-1 coefficients c corresponding to the other U-1 mobile station usersk,mWhere m ═ infinity, Λ,0, Λ, ∞, and has U-1 constraint equations as in equation 13; solving a constraint equation solution to obtain the solution so as to eliminate the interference of other users;
each component Ψk,u,mThe value of (A) depends on the ratio of the distance between the mobile stations to the wavelength, has
Figure FDA0002554511350000062
Component Ψ ofk,u,mIs subjected to truncation, wherein
Figure FDA0002554511350000063
Is the largest integer no greater than x; the corresponding coefficient set is denoted as cu,mL 1 ≦ U ≦ U ≦ M, and { Ψ ≦ M }, andu,k,mif 1 is equal to or less than U, k is equal to or less than U, and M is equal to or less than M, then equation 13 can be written in matrix form:
Ψucu0 formula 15;
wherein the matrix ΨuAnd vector cuCan be represented as follows:
Figure FDA0002554511350000071
let the number of truncation terms M be:
Figure FDA0002554511350000072
the second parameter of the above formula ensures ΨuThe existence of null space, only the solution c of the equation needs to be solveduThe interference of other users can be eliminated.
8. The multiuser wireless communication system antijamming method according to claim 7, characterized in that the null of the u-th user is determined according to the number of truncation itemsZero forcing transceiver coefficient cuCan be expressed as
Figure FDA0002554511350000073
Wherein span (A) is the expansion space of A (A)-Moore-Penrose inverse matrix of A, K
Figure FDA0002554511350000074
The received signal-to-noise ratio SNR can be written as:
Figure FDA0002554511350000075
wherein, PuFor the transmit power, the power of the signal received by user u can be obtained, and its maximum value can be expressed as
Figure FDA0002554511350000081
Wherein e is0＝[0,Λ,0,1,0,Λ,0]TIs a unit vector, vector e0The front and the back of the middle element 1 are provided with M0 elements, | | cu0||2PuThe coefficient c for the power of the received signal for the u-th useru0||2Can be expressed as:
Figure FDA0002554511350000082
due to cuIn a subspace
Figure FDA0002554511350000083
When c is aboveuAnd e0In that
Figure FDA0002554511350000084
When the projections are aligned, the maximum correlation between them is realized, and therefore, the coefficient | | cu0||2Is equal toe0Norm of projection on subspace, i.e.
Figure FDA0002554511350000085
9. An apparatus for suppressing interference in a multiuser wireless communication system, the apparatus comprising: memory, processor and a tamper resistant program of a multi-user wireless communication system stored on the memory and executable on the processor, the tamper resistant program of the multi-user wireless communication system when executed by the processor implementing the steps of the tamper resistant method of the multi-user wireless communication system according to any of claims 1 to 8.
10. A storage medium storing an anti-jamming program for a multiuser wireless communication system, the anti-jamming program for the multiuser wireless communication system implementing the steps of the anti-jamming method for the multiuser wireless communication system according to any one of claims 1 to 8 when executed by a processor.
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