CN109005551B - Multi-user NOMA downlink power distribution method of non-ideal channel state information - Google Patents

Multi-user NOMA downlink power distribution method of non-ideal channel state information Download PDF

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CN109005551B
CN109005551B CN201810756250.6A CN201810756250A CN109005551B CN 109005551 B CN109005551 B CN 109005551B CN 201810756250 A CN201810756250 A CN 201810756250A CN 109005551 B CN109005551 B CN 109005551B
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base station
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CN109005551A (en
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张军
刘晓光
张金波
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CETC 54 Research Institute
Nanjing University of Posts and Telecommunications
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Nanjing University of Posts and Telecommunications
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0626—Channel coefficients, e.g. channel state information [CSI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/003—Arrangements for allocating sub-channels of the transmission path
    • H04L5/0048—Allocation of pilot signals, i.e. of signals known to the receiver
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/241—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account channel quality metrics, e.g. SIR, SNR, CIR, Eb/lo
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/20—Control channels or signalling for resource management
    • H04W72/23—Control channels or signalling for resource management in the downlink direction of a wireless link, i.e. towards a terminal

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Abstract

The invention discloses a multi-user NOMA downlink power distribution method of non-ideal channel state information, which comprises the following steps: aiming at a single-cell multi-user NOMA downlink wireless communication system, all users send uplink pilot frequency to a base station, and the base station receives the pilot frequency sent by a user side to carry out channel estimation so as to acquire non-ideal channel state information of all users; according to the non-ideal channel state information of all users acquired by the base station, screening the users by using a user selection scheme, and clustering the screened users; and calculating a sending precoding matrix by using the non-ideal channel state information of the screened users, and then sending a signal to carry out signal transmission by the base station according to the principle of maximizing the total capacity of all users in the same cluster and the solved optimal power distribution result. According to the method, under the condition of non-ideal channel state information, RZF precoding is adopted in the system, more power is distributed to weak users, the throughput of cell edge users is improved, and the fairness of system users is maintained.

Description

Multi-user NOMA downlink power distribution method of non-ideal channel state information
Technical Field
The invention relates to a multi-user NOMA downlink power distribution method of non-ideal channel state information, which can be used in the technical field of wireless communication.
Background
With the rapid development of wireless communication technology, the fifth generation mobile communication is located in a wireless network with high spectrum efficiency and high wireless transmission rate, which supports Access of a large number of users, so a Non-orthogonal Multiple Access (NOMA) technology has been developed, and the main reason for using NOMA is that it can provide services for a plurality of users within the same time and frequency resource, thereby supporting connection of a large number of users. Therefore, the NOMA technology is very beneficial to solving increasingly nervous spectrum resources, and is widely applied to the fields of wireless communication, smart cities, unmanned aerial vehicle networks and the like. NOMA differs from the orthogonal multiple access technique in that NOMA can guarantee fairness and quality of service for users through a flexible power allocation mechanism between strong users and weak users, especially in NOMA, as more power is allocated to weak users, NOMA can provide higher throughput for cell edge users, and thus power allocation and user fairness are the main concerns. The power allocation in NOMA is not just to maximize the total capacity, but takes into account both the total capacity and user fairness at the same time, because if the goal is to maximize the system and rate, NOMA will allocate all power to strong users.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides a multi-user NOMA downlink power allocation method of non-ideal channel state information.
The purpose of the invention is realized by the following technical scheme: a multi-user NOMA downlink power distribution method of non-ideal channel state information comprises the following steps:
s101: aiming at a single-cell multi-user NOMA downlink wireless communication system, all users send uplink pilot frequency to a base station, and the base station receives the pilot frequency sent by a user side to carry out channel estimation so as to acquire non-ideal channel state information of all users;
s102: according to the non-ideal channel state information of all users acquired by the base station in the step S101, users are screened by using a user selection scheme, and the screened users are clustered;
s103: and calculating a sending precoding matrix by using the non-ideal channel state information of the screened users, calculating an optimal power distribution factor under the constraint of ensuring user fairness in the system according to the principle of maximizing the total capacity of all users in the same cluster, and then sending signals by the base station according to the obtained optimal power distribution result to carry out signal transmission.
Preferably, in step S101, the wireless communication system includes a base station and a plurality of users, the base station sends a superposition signal to the user side, the transmitting end adopts regularized zero-forcing precoding based on non-ideal channel state information, and the receiving end utilizes a successive interference cancellation technique to cancel inter-cluster interference and inter-user interference; assuming that the base station has N antennas and the user set is Q, wherein Q has M users, each user has a single antenna, M > 2K, where > represents that the number is much larger than the total number of users scheduled by the system is 2K and satisfies 2K > N, the base station estimates the channel by using the uplink pilot sequence sent by the user, and the obtained non-ideal channel state information is represented as:
Figure BDA00017254116900000210
wherein M is equal to [1, 2]，
Figure BDA0001725411690000022
Representing the estimated channel between the base station and the mth user, with vector size nx 1, TmIs an N x N deterministic non-negative decision matrix, representing the transmit correlation matrix of the base station antennas,
Figure BDA0001725411690000023
xmand vmAll represent a complex Gaussian random vector of Nx 1, whose elements all obey the independent equal distribution of 0 mean, 1/N variance, τmFor channel estimation parameters, indicating the accuracy of the channel estimation, τmE (0, 1), e represents belonging to,
Figure BDA0001725411690000024
representing the square root operation of the matrix.
Preferably, the user sends the uplink pilot to the base station, and the base station estimates the channel according to the known pilot sent by the user, assuming that the length of the uplink pilot sequence sent by each user is TtThe uplink transmission power of the receiver is puTo aboveComplex white gaussian noise power of both uplink and downlink is σ2Calculating channel estimation parameters
Figure BDA0001725411690000025
Where ρ isuIs an uplink signal-to-noise ratio, and
Figure BDA0001725411690000026
preferably, in step S102, the specific steps of the user selecting the scheme are as follows:
step S2 a: definition u (t) represents the tth user, where t e [1, 2]The non-ideal channel state information of M users is obtained as
Figure BDA0001725411690000027
Superscript (·)HRepresenting a conjugate transpose operation of a matrix;
step S2 b: randomly selecting K users from a user set Q, wherein the user set is defined as U (1),. U (K), and U ═ U (1),. U (K) represents a user set of the randomly selected K users, and the large-scale fading factor of the users in the system is b1And b2And b is1＞b2I is initialized to 1, and the user u (i) selects a paired user from the remaining user set S, and defines the remaining user set S as { u (K +1),.., u (M) }, and there are M-K users, which should satisfy the following conditions:
Figure BDA0001725411690000028
Figure BDA0001725411690000029
wherein j belongs to [ K +1]，m0For the channel correlation coefficients of user u (i) and user u (j),
Figure BDA0001725411690000031
for the estimated channel of user u (j), r is a fixed constant. j takes the value from K +1 into m: (i, j), m (i, j) and channel correlation coefficient m are calculated0Comparing if the calculated result of m (i, j) is less than or equal to m0，
Figure BDA0001725411690000032
Step S2c is executed, if the j value is substituted into m (i, j), the calculated result is larger than m0And is and
Figure BDA0001725411690000033
step S2d is executed;
step S2 c: continuously taking the value of j back to m (i, j), and calculating the result of m (i, j) and the channel correlation coefficient m0Comparing until finding j satisfying the condition;
step S2 d: successfully pairing the user u (i) with the user u (j), combining the user u (i) with the user u (j) into a group to form a cluster, stopping value calculation of the j, and executing the step S2 e;
step S2 e: for the users u (i) and u (j) which are successfully paired, the estimated channel matrixes are respectively
Figure BDA0001725411690000034
And
Figure BDA0001725411690000035
then
Figure BDA0001725411690000036
Denotes u (i) as a strong user in the same cluster,
Figure BDA0001725411690000037
indicating u (j) is a weak user in the same group of clusters, and executing step S2 f;
step S2 f: and (3) removing the user U (j) paired with the user U (i), namely, the user U (j) does not participate in the pairing of the rest users any more, executing i ═ i +1, executing step S2b, and continuing the pairing of the rest users in the user set U until all the users in the set U are paired.
Preferably, in step S103, K clusters formed by the screened users are used, wherein each cluster has two users, and the base is obtainedNon-ideal estimated channel between station and ith user in kth cluster
Figure BDA0001725411690000038
The vector size is 1 XN, where i ∈ [1, 2 ]]，k∈[1，...，K]，
Figure BDA0001725411690000039
And
Figure BDA00017254116900000310
respectively estimating channel vectors for strong users and weak users in the kth cluster, and finally obtaining the non-ideal estimated channel matrix of the strong users in all the clusters
Figure BDA00017254116900000311
The matrix size is K × N.
Preferably, in step S103, the transmitting end calculates the regularization parameter by using regularization zero-forcing pre-coding
Figure BDA00017254116900000312
Where ρ is the signal-to-noise ratio, and
Figure BDA00017254116900000313
p is the downlink transmission power, σ2The complex gaussian white noise power for the downlink user,
Figure BDA00017254116900000314
n is the number of base station antennas, L is the total number of system users, and the channel matrix is estimated according to the nonideal of the strong users
Figure BDA00017254116900000315
Positive regularization parameter β, calculation
Figure BDA00017254116900000316
Wherein (·)-1Representing the inverse operation of the matrix, defining a transmission precoding matrix with G being NxK, the precoding matrix is limited by the transmission power and satisfies tr (GG)H) NP is less than or equal to, P is more than 0, tr (-) represents the tracing of the matrixOperation, calculating according to the constraint condition of the transmission precoding matrix
Figure BDA00017254116900000317
Wherein epsilon represents a normalization parameter satisfying the constraint of the transmission power of the base station, and the sending precoding matrix is calculated according to the result calculated in the previous step:
Figure BDA0001725411690000041
wherein INIs a unit array of N multiplied by N.
Preferably, in step S103, the power allocation factors of users in the same group change with the change of the non-ideal channel state information of the users, so that the optimal power allocation factor is calculated to implement the optimal dynamic power allocation, and the specific steps are as follows:
step S3 a: suppose that the true channel between the base station and the ith user in the kth cluster is
Figure BDA0001725411690000042
The vector size is 1 XN, and
Figure BDA0001725411690000043
wherein
Figure BDA0001725411690000044
Is a complex Gaussian random vector of 1 XN, whose elements satisfy 0 mean, 1/N variance independent and same distribution, Tk，iIs an N × N deterministic non-negative deterministic matrix. Thereby obtaining the real channel vector of the weak user in the kth cluster
Figure BDA0001725411690000045
According to the sending pre-coding matrix G, the effective power of the users in the kth cluster is calculated
Figure BDA0001725411690000046
Wherein Ex{ f (x) } denotes the expectation of f (x) with respect to variable x, | · non-calculation2A squaring operation representing a vector norm;
step S3 b: using the true channel vector of the weak user in the kth cluster
Figure BDA0001725411690000047
And transmitting the precoding matrix G, calculating
Figure BDA0001725411690000048
Wherein U isBEstimating channel matrix for interference of other clusters to kth cluster in system, strong users of all clusters
Figure BDA0001725411690000049
Removing strong user estimated channel vector in kth cluster
Figure BDA00017254116900000410
To obtain
Figure BDA00017254116900000411
The matrix size is (K-1) xN;
step S3 c: according to the effective power U of users in the k clusterAAnd inter-cluster interference UBCalculating the optimal power distribution factor of the strong user in the kth cluster:
Figure BDA00017254116900000412
wherein the content of the first and second substances,
Figure BDA00017254116900000413
ε represents a normalization parameter satisfying the constraint of the transmission power of the base station, ρ is the signal-to-noise ratio, and
Figure BDA00017254116900000414
p is total transmission power, and the optimal power distribution factor of the weak users in the kth cluster is
Figure BDA00017254116900000415
The technical scheme of the invention has the advantages that: the method adopts a more practical scene, namely under the condition of non-ideal channel state information, RZF precoding is adopted in the system, more power can be distributed to weak users, and the throughput of cell edge users is greatly improved, so that the cell edge user experience and the service quality are enhanced, and the fairness of system users is maintained.
Compared with zero-forcing precoding, the performance is obviously improved, user selection is carried out at the same time, and the performance is also improved to a certain degree. The method is based on the principle of 'maximizing total capacity', dynamically allocates the transmitting power to the users in the cluster, improves the throughput of weak users, and maintains the fairness among the users.
Drawings
Fig. 1 is a flowchart of a multi-user NOMA downlink power allocation method for non-ideal channel state information according to an embodiment of the present invention.
Fig. 2 is a flowchart illustrating an implementation of step S102 in fig. 1.
Fig. 3 is a flowchart illustrating an implementation of step S103 in fig. 1.
Detailed Description
Objects, advantages and features of the present invention will be illustrated and explained by the following non-limiting description of preferred embodiments. The embodiments are merely exemplary for applying the technical solutions of the present invention, and any technical solution formed by replacing or converting the equivalent thereof falls within the scope of the present invention claimed.
The invention discloses a multi-user NOMA downlink power distribution method of non-ideal channel state information, which takes the fairness of users in a system as constraint based on the principle of 'maximizing total capacity' to realize the optimal power distribution to the users in the same cluster in the system, as shown in figure 1, the method comprises the following steps:
s101: aiming at a single-cell multi-user NOMA downlink wireless communication system, all users send uplink pilot frequency to a base station, and the base station receives the pilot frequency sent by a user side to carry out channel estimation so as to acquire non-ideal channel state information of all users;
s102: according to the non-ideal channel state information of all users acquired by the base station in the step S101, users are screened by using a user selection scheme, and the screened users are clustered;
s103: and calculating a sending precoding matrix by using the non-ideal channel state information of the screened users, calculating an optimal power distribution factor under the constraint of ensuring user fairness in the system according to the principle of maximizing the total capacity of all users in the same cluster, and then sending signals by the base station according to the obtained optimal power distribution result to carry out signal transmission.
Specifically, in step S101, the single-cell multi-user NOMA downlink wireless communication system with non-ideal channel state information includes a base station and multiple users, the base station sends a superimposed signal to the user terminal, and the receiving terminal utilizes a successive interference cancellation technique to cancel inter-cluster interference and inter-user interference. Suppose the base station has N antennas, and the user set is Q, where Q has M users, each user has a single antenna, M > 2K, where > means that the total number of users scheduled by the system is much larger than 2K, and 2K > N is satisfied. The user sends the up pilot frequency to the base station, the length of the up pilot frequency sequence sent by each user is TtThe uplink transmission power of the receiver is puComplex white gaussian noise power for both uplink and downlink is σ2Calculating channel estimation parameters
Figure BDA0001725411690000061
Wherein tau ismIndicating the accuracy of the channel estimate, τmIs e (0, 1), and belongs to puIs an uplink signal-to-noise ratio, and
Figure BDA0001725411690000062
the base station estimates the channel by using the uplink pilot sequence sent by the user, and the acquired non-ideal channel state information is represented as:
Figure BDA0001725411690000063
wherein M is equal to [1, 2]，
Figure BDA0001725411690000064
Representing the estimated channel between the base station and the mth user, with vector size nx 1, TmIs an N x N deterministic non-negative decision matrix, representing the transmit correlation matrix of the base station antennas,
Figure BDA0001725411690000065
xmand vmAll represent an N x 1 complex gaussian random vector whose elements are subject to an independent equal distribution of 0 means, 1/N variance,
Figure BDA0001725411690000066
representing the square root operation of the matrix.
As shown in fig. 2, a flowchart of specific implementation steps of the user selection scheme in step S102 in fig. 1 specifically includes the following steps:
step 201: definition u (t) represents the tth user, where t e [1, 2]The non-ideal channel state information of M users is obtained as
Figure BDA0001725411690000067
Superscript (·)HRepresenting a conjugate transpose operation of the matrix.
Step 202: k users are randomly selected from the user set Q, defined as U (1),. ·, U (K), where U ═ { U (1),. ·, U (K) } denotes a user set of randomly selected K users, and i is initialized to 1.
Step 203: suppose that the large-scale fading factor of a user in the system is b1And b2And b is1＞b2User u (i) selects a paired user from the remaining user set S, defining the remaining user set S ═ { u (K +1),.. u (m) }, where i ∈ [1, 2]The following conditions are satisfied:
Figure BDA0001725411690000068
Figure BDA0001725411690000069
wherein j is in the range of [ K +1]，m0For the channel correlation coefficients of user u (i) and user u (j),
Figure BDA00017254116900000610
for the estimated channel of user u (j), r is a fixed constant.
Step 204: and j is taken from K +1 to m (i, j) in sequence.
Step 205: calculating m (i, j) and channel correlation coefficient m0Comparing if the calculated result of m (i, j) is less than or equal to m0And is and
Figure BDA00017254116900000611
step 206) is executed, the calculated result of substituting j into m (i, j) is larger than m0，
Figure BDA00017254116900000612
Step 207 is performed).
Step 206: continuously taking the value of j back to m (i, j), and calculating the result of m (i, j) and the channel correlation coefficient m0And comparing until finding j meeting the condition.
Step 207: and successfully pairing the user u (i) with the user u (j), combining the user u (i) with the user u (j) into a group to form a cluster, and stopping the value calculation of the j. For the users u (i) and u (j) which are successfully paired, the estimated channel matrixes are respectively
Figure BDA0001725411690000071
And
Figure BDA0001725411690000072
then
Figure BDA0001725411690000073
Denotes u (i) as a strong user in the same cluster,
Figure BDA0001725411690000074
denoted u (j) as weak users in the same cluster.
Step 208: the user u (j) paired with user u (i) is removed, i.e. user u (j) no longer participates in the pairing of the remaining users.
Step 209: and executing i to i +1, and continuing the pairing of the rest users in the user set U.
Step 210: and when i is larger than K, completing the pairing of all the users in the set U, and finishing the user selection.
As shown in fig. 3, a flowchart of a specific implementation step of calculating an optimal power allocation factor in step S103 in fig. 1 is shown, where power allocation factors of users in the same group change with changes in non-ideal channel state information of the users, so that the optimal power allocation factor is calculated to implement optimal dynamic power allocation, and the specific implementation step includes the following steps:
step 301: and K clusters formed by the screened users are utilized, wherein each cluster comprises two users. Obtaining a non-ideal estimated channel between a base station and an ith user in a kth cluster
Figure BDA0001725411690000075
The vector size is 1 XN, where i ∈ [1, 2 ]]，k∈[1，...，K]，
Figure BDA0001725411690000076
And
Figure BDA0001725411690000077
respectively estimating channel vectors for strong users and weak users in the kth cluster, thereby obtaining non-ideal estimated channel matrixes of the strong users in all the clusters
Figure BDA0001725411690000078
The matrix size is K × N. The sending end adopts regularization zero-forcing pre-coding and calculates regularization parameters
Figure BDA0001725411690000079
Where ρ is the signal-to-noise ratio, and
Figure BDA00017254116900000710
p is the downlink transmission power, σ2Complex gaussian white for downlink usersThe power of the noise is set to be,
Figure BDA00017254116900000711
n is the number of base station antennas, and L is the total number of system users. Estimating channel matrix from strong user non-idealities
Figure BDA00017254116900000715
And a regularization parameter beta, calculating
Figure BDA00017254116900000712
Wherein (·)-1Representing the inverse of the matrix. Defining a transmission precoding matrix with G being NxK, wherein the precoding matrix is limited by transmission power and satisfies tr (GG)H) NP is less than or equal to, P is more than 0, tr (-) represents the trace-solving operation of the matrix, and the computation is carried out according to the constraint condition of the sending pre-coding matrix
Figure BDA00017254116900000713
Wherein epsilon represents a normalization parameter satisfying the constraint of the transmission power of the base station, and the sending precoding matrix is calculated according to the result calculated in the previous step:
Figure BDA00017254116900000714
wherein INIs a unit array of N multiplied by N.
Step 302: suppose that the true channel between the base station and the ith user in the kth cluster is
Figure BDA0001725411690000081
The vector size is 1 XN, and
Figure BDA0001725411690000082
wherein
Figure BDA0001725411690000083
Is a complex Gaussian random vector of 1 XN, whose elements satisfy 0 mean, 1/N variance independent and same distribution, TkiIs an NxN deterministic non-negative definite matrix, thereby obtaining the truth of the weak users in the kth clusterReal channel vector
Figure BDA0001725411690000084
According to the sending pre-coding matrix G, the effective power of the users in the kth cluster is calculated
Figure BDA0001725411690000085
Wherein Ex{ f (x) } denotes the expectation of f (x) with respect to variable x, |, 2 denotes the squaring operation of the vector modulo.
Step 303: using the true channel vector of the weak user in the kth cluster
Figure BDA0001725411690000086
And transmitting the precoding matrix G, calculating
Figure BDA0001725411690000087
Wherein U isEEstimating channel matrix for interference of other clusters to kth cluster in system, strong users of all clusters
Figure BDA0001725411690000088
Removing strong user estimated channel vector in kth cluster
Figure BDA0001725411690000089
To obtain
Figure BDA00017254116900000810
The matrix size is (K-1). times.N.
Step 304: according to the effective power U of users in the k clusterAAnd inter-cluster interference UBCalculating the optimal power distribution factor of the strong user in the kth cluster:
Figure BDA00017254116900000811
wherein
Figure BDA00017254116900000812
ρ is the signal-to-noise ratio, and
Figure BDA00017254116900000813
p is total transmission power, and the optimal power distribution factor of the weak users in the kth cluster is
Figure BDA00017254116900000814
According to the method, under the condition of non-ideal channel state information, RZF precoding is adopted in the system, meanwhile, more power can be distributed to weak users, and the throughput of cell edge users is greatly improved, so that the cell edge user experience and the service quality are enhanced, and the fairness of system users is maintained.
The invention has various embodiments, and all technical solutions formed by adopting equivalent transformation or equivalent transformation are within the protection scope of the invention.

Claims (4)

1. A multi-user NOMA downlink power distribution method of non-ideal channel state information is characterized in that: the method comprises the following steps:
s101: aiming at a single-cell multi-user NOMA downlink wireless communication system, all users send uplink pilot frequency to a base station, and the base station receives the pilot frequency sent by a user side to carry out channel estimation so as to acquire non-ideal channel state information of all users;
s102: according to the non-ideal channel state information of all users acquired by the base station in the step S101, users are screened by using a user selection scheme, and the screened users are clustered;
in step S102, the specific steps of the user selection scheme are as follows:
step S2 a: definition u (t) represents the tth user, where t e [1, 2]The non-ideal channel state information of M users is obtained as
Figure FDA0002973937570000011
Superscript (·)HRepresenting a conjugate transpose operation of a matrix;
step S2 b: k users are randomly selected from the user set Q, defined as U (1),. U (K), U ═ U (1),..., u (K) } denotes a set of users randomly selecting K users, whose large-scale fading factor in the system is b1And b2And b is1＞b2I is initialized to 1, and the user u (i) selects a paired user from the remaining user set S, and defines the remaining user set S as { u (K +1),.., u (M) }, and there are M-K users, which should satisfy the following conditions:
Figure FDA0002973937570000012
Figure FDA0002973937570000013
wherein j belongs to [ K +1]，m0For the channel correlation coefficients of user u (i) and user u (j),
Figure FDA0002973937570000014
r is a fixed constant for the estimated channel of user u (j); j is sequentially valued from K +1 and is taken into m (i, j), and m (i, j) and a channel correlation coefficient m are calculated0Comparing if the calculated result of m (i, j) is less than or equal to m0，
Figure FDA0002973937570000015
Step S2c is executed, if the j value is substituted into m (i, j), the calculated result is larger than m0And is and
Figure FDA0002973937570000016
step S2d is executed;
step S2 c: continuously taking the value of j back to m (i, j), and calculating the result of m (i, j) and the channel correlation coefficient m0Comparing until finding j satisfying the condition;
step S2 d: successfully pairing the user u (i) with the user u (j), combining the user u (i) with the user u (j) into a group to form a cluster, stopping value calculation of the j, and executing the step S2 e;
step S2 e: for theSuccessfully paired users u (i) and u (j), the estimated channel matrixes are respectively
Figure FDA0002973937570000021
And
Figure FDA0002973937570000022
then
Figure FDA0002973937570000023
Denotes u (i) as a strong user in the same cluster,
Figure FDA0002973937570000024
indicating u (j) is a weak user in the same group of clusters, and executing step S2 f;
step S2 f: removing the user U (j) paired with the user U (i), that is, the user U (j) does not participate in the pairing of the remaining users any more, executing i ═ i +1, executing step S2b, and continuing the pairing of the remaining users in the user set U until all the users in the set U are paired;
s103: calculating a sending precoding matrix by using the non-ideal channel state information of the screened users, calculating an optimal power distribution factor under the constraint of ensuring user fairness in the system according to the principle of maximizing the total capacity of all users in the same cluster, and then sending signals by a base station according to the obtained optimal power distribution result to carry out signal transmission;
in step S103, the transmitting end calculates regularization parameters by using regularization zero-forcing pre-coding
Figure FDA0002973937570000025
Where ρ is the signal-to-noise ratio, and
Figure FDA0002973937570000026
p is the downlink transmission power, σ2The complex gaussian white noise power for the downlink user,
Figure FDA0002973937570000027
n is the number of base station antennas,l is the total number of system users, and the channel matrix is estimated according to the nonideal of the strong users
Figure FDA0002973937570000028
And a regularization parameter beta, calculating
Figure FDA0002973937570000029
Wherein (·)-1Representing the inverse operation of the matrix, defining a transmission precoding matrix with G being NxK, the precoding matrix is limited by the transmission power and satisfies tr (GG)H) NP is less than or equal to, P is more than 0, tr (-) represents the trace-solving operation of the matrix, and the computation is carried out according to the constraint condition of the sending pre-coding matrix
Figure FDA00029739375700000210
Wherein epsilon represents a normalization parameter satisfying the constraint of the transmission power of the base station, and the sending precoding matrix is calculated according to the result calculated in the previous step:
Figure FDA00029739375700000211
wherein INIs a unit array of NXN;
in step S103, the power allocation factors of the users in the same group change with the change of the non-ideal channel state information of the users, so that the optimal power allocation factor is calculated to realize the optimal dynamic power allocation, and the specific steps are as follows:
step S3 a: suppose that the true channel between the base station and the ith user in the kth cluster is
Figure FDA00029739375700000212
The vector size is 1 XN, and
Figure FDA00029739375700000213
wherein
Figure FDA00029739375700000214
Is a complex of 1 XNGaussian random vector whose elements satisfy 0 mean, 1/N variance independent and same distribution, Tk，iIs an nxn deterministic non-negative deterministic matrix; thereby obtaining the real channel vector of the weak user in the kth cluster
Figure FDA0002973937570000031
According to the sending pre-coding matrix G, the effective power of the users in the kth cluster is calculated
Figure FDA0002973937570000032
Wherein Ex{ f (x) } denotes the expectation of f (x) with respect to variable x, | · non-calculation2A squaring operation representing a vector norm;
step S3 b: using the true channel vector of the weak user in the kth cluster
Figure FDA0002973937570000033
And transmitting the precoding matrix G, calculating
Figure FDA0002973937570000034
Wherein U isBEstimating channel matrix for interference of other clusters to kth cluster in system, strong users of all clusters
Figure FDA0002973937570000035
Removing strong user estimated channel vector in kth cluster
Figure FDA0002973937570000036
To obtain
Figure FDA0002973937570000037
The matrix size is (K-1) xN;
step S3 c: according to the effective power U of users in the k clusterAAnd inter-cluster interference UBCalculating the optimal power distribution factor of the strong user in the kth cluster:
Figure FDA0002973937570000038
wherein the content of the first and second substances,
Figure FDA0002973937570000039
ε represents a normalization parameter satisfying the constraint of the transmission power of the base station, ρ is the signal-to-noise ratio, and
Figure FDA00029739375700000310
p is total transmission power, and the optimal power distribution factor of the weak users in the kth cluster is
Figure FDA00029739375700000311
2. The method of claim 1, wherein the method for allocating the multiuser NOMA downlink power of non-ideal channel state information comprises:
in the step S101, the wireless communication system includes a base station and a plurality of users, the base station sends a superposition signal to a user side, a transmitting side adopts regularized zero-forcing precoding based on non-ideal channel state information, and a receiving side eliminates inter-cluster interference and inter-user interference by using a continuous interference elimination technique; assuming that the base station has N antennas and the user set is Q, wherein Q has M users, each user has a single antenna, M > 2K, where > represents that the number is much larger than the total number of users scheduled by the system is 2K and satisfies 2K > N, the base station estimates the channel by using the uplink pilot sequence sent by the user, and the obtained non-ideal channel state information is represented as:
Figure FDA0002973937570000041
wherein M is equal to [1, 2]，
Figure FDA0002973937570000042
Representing the estimated channel between the base station and the mth user, with vector size nx 1, TmIs an NxN deterministic non-negative definite matrixIndicating the transmit correlation matrix of the base station antenna,
Figure FDA0002973937570000043
xmand vmAll represent a complex Gaussian random vector of Nx 1, whose elements all obey the independent equal distribution of 0 mean, 1/N variance, τmFor channel estimation parameters, indicating the accuracy of the channel estimation, τmE (0, 1), e represents belonging to,
Figure FDA0002973937570000044
representing the square root operation of the matrix.
3. The method of claim 2, wherein the method for allocating the multiuser NOMA downlink power of non-ideal channel state information comprises: the user sends the up pilot frequency to the base station, the base station estimates the channel according to the known pilot frequency sent by the user, the length of the up pilot frequency sequence sent by each user is assumed to be TtThe uplink transmission power of the receiver is puComplex white gaussian noise power for both uplink and downlink is σ2Calculating channel estimation parameters
Figure FDA0002973937570000045
Where ρ isuIs an uplink signal-to-noise ratio, and
Figure FDA0002973937570000046
4. the method of claim 1, wherein the method for allocating the multiuser NOMA downlink power of non-ideal channel state information comprises:
in step S103, using K clusters formed by the screened users, wherein each cluster has two users, acquiring a non-ideal estimated channel between the base station and the ith user in the kth cluster
Figure FDA0002973937570000047
The vector size is 1 x N,where i ∈ [1, 2 ]]，k∈[1，...，K]，
Figure FDA0002973937570000048
And
Figure FDA0002973937570000049
respectively estimating channel vectors for strong users and weak users in the kth cluster, and finally obtaining the non-ideal estimated channel matrix of the strong users in all the clusters
Figure FDA00029739375700000410
The matrix size is K × N.
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