CN110881010B - Statistical CSI-assisted multi-user NOMA downlink transmission method - Google Patents
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Abstract
The invention provides a statistical CSI-assisted multi-user NOMA downlink transmission method, which comprises the steps that firstly, a base station estimates non-ideal channel state information by using an uplink pilot signal, and divides users into a plurality of clusters according to the non-ideal channel state information; then, calculating a regularized zero-forcing precoding sending matrix according to the non-ideal channel state information, wherein the calculation of the regularization factor is based on statistical channel state information; and finally, designing an optimal transmission power distribution factor based on the statistical channel state information. The invention maximizes the total transmission rate of all users in the system under the condition of satisfying the rate constraint of weak users in the system, and the regularization factor and the power distribution factor in the system only depend on the statistical channel state information.
Description
Technical Field
The invention relates to a statistical CSI-assisted multi-user NOMA downlink transmission method, and belongs to the technical field of wireless communication.
Background
As mobile communication technology has developed today, the spectrum resources have become increasingly strained. Meanwhile, in order to meet the rapidly increasing demand for mobile services, people have begun to find new mobile communication technologies that can meet the user experience demand and improve spectrum efficiency. Under such a background, a Non-orthogonal Multiple Access (NOMA) technique has been proposed. The basic idea of non-orthogonal multiple access (NOMA) technology is to adopt non-orthogonal transmission at a transmitting end, actively introduce interference information and realize correct demodulation at a receiving end through a Serial Interference Cancellation (SIC) receiver. Although the complexity of the receiver using SIC technology is increased to some extent, the spectral efficiency can be improved well. By adopting the NOMA technology, a plurality of users can be served at the same time and in the same frequency resource, and the problem that the existing frequency spectrum resource is increasingly tense can be solved. Therefore, the NOMA technique is widely used in communication systems. However, how to perform beam design and power allocation becomes an urgent problem to be solved at present.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a statistical CSI (channel state information) -assisted multi-user NOMA (non-orthogonal multiple access) downlink transmission method, which can improve the total transmission rate of the system and reduce the complexity of the system implementation.
The invention provides a statistical CSI (channel state information) assisted multi-user NOMA (non-orthogonal multiple access) downlink transmission method, a system of the method comprises a multi-antenna base station and a plurality of single-antenna users, and the method comprises the following steps:
s1, in the multi-user NOMA downlink transmission system assisted by statistical channel state information, a base station estimates non-ideal channel state information by using an uplink pilot signal, and divides users into a plurality of clusters according to the non-ideal channel state information; go to step S2;
s2, calculating a regularized zero-forcing precoding sending matrix according to the non-ideal channel state information, wherein the calculation of the regularization factor is based on the statistical channel state information; go to step S3;
and S3, designing an optimal transmission power distribution factor based on the statistical channel state information.
The invention designs a multi-user NOMA downlink transmission method assisted by statistical channel state information by taking the maximization of the total throughput of a cell as a target and considering the fairness of cell users. The method is suitable for a single-cell multi-user NOMA downlink wireless transmission system, the system comprises a multi-antenna base station and a plurality of single-antenna users, and the plurality of users are divided into a plurality of clusters. The method is based on the principle of 'maximizing total rate', and designs the optimal regularized zero-forcing precoding factor and the optimal power distribution factor according to the statistical channel state information.
As a further technical solution of the present invention, the specific method of step S1 is as follows:
s101, assuming that the base station has N antennas, the system has M single-antenna users, the total number of users scheduled by the system is 2K, wherein M > 2K, and 2K > N, then after all users send pilot signals to the base station, the base station estimates the non-ideal channel state information of each user, the non-ideal channel state information of the kth user can be expressed as,
wherein k is ∈ [1, M ∈],Is the estimated channel for user k with a vector size of 1 xN, βkRepresenting the large-scale fading coefficient, τ, of the kth userkRepresents an accuracy parameter of the channel estimation, and τk∈[0,1],zk、qkEach represents an Nx 1 complex Gaussian random vector whose elements all follow an independent uniform distribution of 0 means and 1/N variance (.)HRepresents a conjugate transpose of a vector; go to step S102;
s102, according to the non-ideal channel state information, clustering all users by adopting the following scheme, wherein the users in the kth cluster need to meet the following conditions,
Corrk≥θk,|βk,1-βk,2|≥βk,0
wherein, CorrkRepresents the correlation between the user 1 and user 2 channels in the kth cluster, βk,1Represents the large-scale fading coefficient, beta, of user 1 in the kth clusterk,2Represents the large-scale fading coefficient, beta, of user 2 in the kth clusterk,0Threshold, θ, representing large scale fading in the kth clusterkA threshold value representing the correlation coefficient in the kth cluster,andis a vector of size 1 x N,indicating the estimated channel for the strong user in the kth cluster,represents the estimated channel of the weak user in the kth cluster,andthe meaning is the same, one is in the form of a row and one is in the form of a column.
The specific method for the transmitting end to design the regularized zero-forcing precoding transmission matrix based on the non-ideal channel state information in step S2 is as follows:
s201, supposeAndvectors with the size of 1 multiplied by N respectively represent the estimated channels of strong users and weak users in the kth cluster; go to step S202;
s202, let K × N regularized zero-forcing precoding matrix G be expressed as
Wherein the content of the first and second substances,represents all strong user non-ideal channel matrices and to representIs the conjugate transpose of (1), xi represents the normalization parameter, alpha represents the regularization factor, INRepresents an identity matrix of size N, ()-1Representing matrix inversion; go to step S203;
s203, let xi express as a normalization parameter for making the emission power of the base station meet the constraint, and the power limit to be met is
tr{GGH}≤NP,P>0
Wherein G isHDenotes the conjugate transpose of the K × N regularized zero-forcing precoding matrix G, P denotes the total transmit power of the base station,tr (.) represents matrix tracing.
In the above steps, the regularization factor α is designed based on the total rate maximization principle and only depends on statistical channel state information, where the statistical channel state information is θk,βk,1,βk,2,τkAnd the like.
The specific method of step S3 is as follows:
setting the optimal transmission power distribution factor of the strong user in the kth cluster asThe optimal transmission power distribution factor of the weak user isThen the following formula is adopted to calculate
Wherein R isk,0For weak users in the kth clusterMinimum transmission rate, θ, to be satisfiedkRepresents the correlation between the strong user and the weak user in the kth cluster, and rho is the signal-to-noise ratio(P represents total transmission power of the station,. sigma.)2Representing the noise power), τkis a channel estimation parameter andk∈[0,1]alpha denotes the regularization parameter of the regular zero-forcing precoding,large scale fading factor, e, representing all strong userskRepresenting a scalar quantity to be calculated, wherein eta is a K multiplied by 1 vector quantity, and theta is a K multiplied by K matrix; go to step S302;
further, the elements in the k-th row and l-th column of the matrix Θ can be calculated as follows,
the elements in matrix theta at row k and column l can be calculated as follows,
wherein e iskRepresenting a scalar quantity that needs to be calculated.
Further, the calculation formula of the kth element in the vector η is as follows:
wherein e iskRepresenting a scalar quantity that needs to be calculated.
Further, ekThe calculation can be carried out by a fixed point iteration method, and the specific steps are as follows:
step (a) first of allInitializing, let t equal to 1, for all(k∈[1,K]) Assigned a value of 1, i.e.WhereinPerforming step (b) with the t-th iteration value representing e _ k;
Wherein, betak,1Representing a large-scale fading coefficient of a strong user in the kth cluster, wherein alpha represents a regularization parameter of regular zero-forcing precoding;
(c) calculated from the formula of step (b)And further whether it satisfies the following condition or not,
wherein epsilon represents a threshold value for judging the convergence degree of the algorithm, if the condition is not satisfied, let t be t +1, and execute step (b) again; if satisfied, the final result can be obtainedk=1,2,......,K。
Compared with the prior art, the invention adopting the technical scheme has the following technical effects:
(1) the invention considers the non-ideal channel state information, better fits the practical application scene, and utilizes the regularized zero-forcing pre-coding to carry out pre-coding design, which is superior to the traditional zero-forcing pre-coding;
(2) the invention provides an expression of the optimal power distribution factor based on the statistical channel state information, and can adapt to the rapidly changing channel due to the design based on the statistical channel state information, and has higher practical value compared with the traditional method.
In conclusion, the invention maximizes the total transmission rate of all users in the system under the condition of satisfying the rate constraint of strong users in the system, and the regularization factor and the power distribution factor in the system only depend on the statistical channel state information.
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FIG. 1 is a schematic flow chart of the present invention.
Detailed Description
The technical scheme of the invention is further explained in detail by combining the attached drawings: the present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection authority of the present invention is not limited to the following embodiments.
The embodiment provides a statistical channel state information assisted multi-user NOMA downlink transmission method, wherein a system of the method comprises a multi-antenna base station and a plurality of single-antenna users, and the plurality of users are divided into a plurality of clusters; the method comprises the following steps:
s1, in the multi-user NOMA downlink transmission system assisted by the statistical channel state information, the base station estimates the non-ideal channel state information by using the uplink pilot signal, and divides the users into a plurality of clusters according to the non-ideal channel state information. The specific method comprises the following steps:
s101, assuming that the base station has N antennas, the system has M single-antenna users, the total number of users scheduled by the system is 2K, wherein M > 2K, and 2K > N, then after all users send pilot signals to the base station, the base station estimates the non-ideal channel state information of each user, the non-ideal channel state information of the kth user can be expressed as,
wherein k is ∈ [1, M ∈],Is the estimated channel for user k with a vector size of 1 xN, βkRepresenting the large-scale fading coefficient, τ, of the kth userkRepresents an accuracy parameter of the channel estimation, and τk∈[0,1],zk、qkEach represents an Nx 1 complex Gaussian random vector whose elements all follow an independent uniform distribution of 0 means and 1/N variance (.)HRepresents a conjugate transpose of a vector;
s102, according to the non-ideal channel state information, clustering all users by adopting the following scheme, wherein the users in the kth cluster need to meet the following conditions,
Corrk≥θk,|βk,1-βk,2|≥βk,0
wherein, CorrkRepresents the correlation between the user 1 and user 2 channels in the kth cluster, βk,1Represents the large-scale fading coefficient, beta, of user 1 in the kth clusterk,2Represents the large-scale fading coefficient, beta, of user 2 in the kth clusterk,0Threshold, θ, representing large scale fading in the kth clusterkA threshold value representing the correlation coefficient in the kth cluster,andis a vector of size 1 x N,indicating the estimated channel for the strong user in the kth cluster,indicating the estimated channel of the weak user in the kth cluster.
And S2, calculating a regularized zero-forcing precoding sending matrix according to the non-ideal channel state information, wherein the calculation of the regularization factor is based on the statistical channel state information. The sending end designs a regularized zero-forcing precoding sending matrix based on the non-ideal channel state information. The specific method comprises the following steps:
s201, supposeAndvectors with the size of 1 multiplied by N respectively represent the estimated channels of strong users and weak users in the kth cluster; go to step S202;
s202, let K × N regularized zero-forcing precoding matrix G be expressed as
Wherein the content of the first and second substances,represents all strong user non-ideal channel matrices and to representIs the conjugate transpose of (1), xi represents the normalization parameter, alpha represents the regularization factor, INRepresents an identity matrix of size N, ()-1Representing matrix inversion;
s203, let xi express as a normalization parameter for making the emission power of the base station meet the constraint, and the power limit to be met is
tr{GGH}≤NP,P>0
Wherein G isHDenotes the conjugate transpose of the K × N regularized zero-forcing precoding matrix G, P denotes the total transmit power of the base station,tr (.) represents matrix tracing.
The regularization factor alpha is designed based on the principle of total rate maximization and only depends on statistical channel state information, wherein the statistical channel state information refers to thetak,βk,1,βk,2,τkAnd the like.
And S3, designing an optimal transmission power distribution factor based on the statistical channel state information. The specific method comprises the following steps:
setting the optimal transmission power distribution factor of the strong user in the kth cluster asThe optimal transmission power distribution factor of the weak user isThen the following formula is adopted to calculate
Wherein R isk,0Minimum transmission rate, theta, to be satisfied by weak users in the kth clusterkRepresents the correlation between the strong user and the weak user in the kth cluster, and rho is the signal-to-noise ratio(P represents total transmission power of the station,. sigma.)2Representing the noise power), τkis a channel estimation parameter andk∈[0,1]alpha denotes the regularization parameter of the regular zero-forcing precoding,large scale fading factor, e, representing all strong userskRepresenting a scalar quantity to be calculated, η is a K × 1 vector, Θ is a K × K matrix, the elements in the kth row and the l column of the matrix Θ can be calculated as follows,
wherein e iskRepresenting a scalar quantity that needs to be calculated.
The calculation formula of the kth element in the vector η is as follows:
wherein e iskRepresenting a scalar needing to be calculated, and ek can be calculated by a fixed point iteration method, and the specific steps are as follows:
step (a) is initialized first, let t equal to 1, for all(k∈[1,K]) Assigned a value of 1, i.e.Performing step (b);
Wherein, betak,1Representing a large-scale fading coefficient of a strong user in the kth cluster, wherein alpha represents a regularization parameter of regular zero-forcing precoding;
(c) calculated from the formula of step (b)And further whether it satisfies the following condition or not,
wherein epsilon represents a threshold value for judging the convergence degree of the algorithm, if the condition is not satisfied, let t be t +1, and execute step (b) again; if satisfied, the final result can be obtainedk=1,2,……,K。
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can understand that the modifications or substitutions within the technical scope of the present invention are included in the scope of the present invention, and therefore, the scope of the present invention should be subject to the protection scope of the claims.
Claims (4)
1. A statistical CSI-assisted multi-user NOMA downlink transmission method is characterized in that a system of the method comprises a multi-antenna base station and a plurality of single-antenna users; the method comprises the following steps:
s1, the base station estimates the non-ideal channel state information by using the uplink pilot signal, and divides the user into a plurality of clusters according to the non-ideal channel state information; the specific method comprises the following steps:
s101, assuming that the base station has N antennas, the system has M single-antenna users, the total number of users scheduled by the system is 2K, wherein M > 2K, and 2K > N, then after all users send pilot signals to the base station, the base station estimates the non-ideal channel state information of each user, the non-ideal channel state information of the kth user can be expressed as,
wherein k is ∈ [1, M ∈],Is the estimated channel for user k with a vector size of 1 xN, βkRepresenting the large-scale fading coefficient, τ, of the kth userkRepresents an accuracy parameter of the channel estimation, and τk∈[0,1],zk、qkEach represents an Nx 1 complex Gaussian random vector whose elements all follow an independent uniform distribution of 0 means and 1/N variance (.)HRepresents a conjugate transpose of a vector; go to step S102;
s102, according to the non-ideal channel state information, all users are clustered, and then the users in the kth cluster need to satisfy the following conditions,
Corrk≥θk,|βk,1-βk,2|≥βk,0
wherein, CorrkRepresents the correlation between the user 1 and user 2 channels in the kth cluster, βk,1Represents the large-scale fading coefficient, beta, of user 1 in the kth clusterk,2Represents the large-scale fading coefficient, beta, of user 2 in the kth clusterk,0Threshold, θ, representing large scale fading in the kth clusterkA threshold value representing the correlation coefficient in the kth cluster,andis a vector of size 1 x N,indicating the estimated channel for the strong user in the kth cluster,an estimated channel representing a weak user in the kth cluster; go to step S2;
s2, calculating a regularized zero-forcing precoding sending matrix according to the non-ideal channel state information, wherein the calculation of the regularization factor is based on the statistical channel state information; the specific method for designing the regularized zero-forcing precoding transmission matrix by the transmitting end based on the non-ideal channel state information is as follows:
s201, supposeAndvectors with the size of 1 multiplied by N respectively represent the estimated channels of strong users and weak users in the kth cluster; go to step S202;
s202, let K × N regularized zero-forcing precoding matrix G be expressed as
Wherein the content of the first and second substances,represents all strong user non-ideal channel matrices and to representIs the conjugate transpose of (1), xi represents the normalization parameter, alpha represents the regularization factor, INRepresenting an identity matrix of size N; go to step S203;
s203, let xi express as a normalization parameter for making the emission power of the base station meet the constraint, and the power limit to be met is
tr{GGH}≤NP,P>0
Wherein G isHDenotes the conjugate transpose of the K × N regularized zero-forcing precoding matrix G, P denotes the total transmit power of the base station,tr (-) represents matrix tracing; go to step S3;
s3, designing an optimal transmission power distribution factor based on the statistical channel state information; the specific method comprises the following steps:
setting the optimal transmission power distribution factor of the strong user in the kth cluster asThe optimal transmission power allocation factor of the weak user isThen, the following formula is adopted to calculate
Wherein R isk,0Minimum transmission rate, theta, to be satisfied by weak users in the kth clusterkRepresents the correlation between the strong user and the weak user in the kth cluster, and rho is the signal-to-noise ratioP represents the total transmission power of the station, σ2Which is indicative of the power of the noise, τkis a channel estimation parameter andk∈[0,1]alpha denotes the regularization parameter of the regular zero-forcing precoding,large scale fading factor, e, representing all strong userskRepresenting a scalar quantity to be calculated, η is a K × 1 vector and Θ is a K × K matrix.
4. The statistical CSI-assisted multi-user NOMA downlink transmission method of claim 3, wherein e iskThe calculation can be carried out by a fixed point iteration method, and the specific steps are as follows:
step (a) is initialized first, let t equal to 1, for allAssigned a value of 1, i.e.Performing step (b);
Wherein, betak,1Represents the large-scale fading coefficients of the strong users in the kth cluster,α represents a regularization parameter of the regular zero-forcing precoding;
(c) calculated from the formula of step (b)And further whether it satisfies the following condition or not,
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