CN108834155B - Method for optimizing spectrum efficiency based on multiple parameters of large-scale antenna system - Google Patents
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Abstract
The invention provides a method for optimizing spectrum efficiency based on multiple parameters of a large-scale antenna system, which can improve the spectrum efficiency of the system. The method comprises the following steps: establishing a model for optimizing spectral efficiency by multiple parameters, wherein the multiple parameters comprise: antenna selection matrix, beam forming vector, transmitting power and pilot frequency sequence length; optimizing an antenna selection matrix according to the established multi-parameter optimization spectrum efficiency model; optimizing a beam forming vector and transmitting power according to the established multi-parameter optimization spectrum efficiency model and the antenna selection matrix obtained through optimization; optimizing the length of a pilot frequency sequence according to the established multi-parameter optimized spectrum efficiency model and the antenna selection matrix, the beam forming vector and the transmitting power obtained through optimization; and substituting the antenna selection matrix, the beam forming vector sum, the transmitting power and the optimized pilot frequency sequence length which are obtained by optimization into the established multi-parameter optimized spectrum efficiency model to obtain the optimized spectrum efficiency. The invention is suitable for the frequency spectrum efficiency optimization operation.
Description
Technical Field
The invention relates to the technical field of wireless communication, in particular to a method for optimizing spectrum efficiency based on multiple parameters of a large-scale antenna system.
Background
In recent years, as global wireless communication technology has been increasingly developed, the demand for wireless communication data services has exponentially increased. In addition, the wireless communication system adopts a static (fixed) spectrum allocation strategy, and spectrum resources are increasingly in short supply. The large-scale antenna (Massive Multiple-Input Multiple-Output, Massive MIMO) technology does not need to update the terminal equipment of the user in a large area, and only needs to transform the base station, so that the spectrum utilization rate and the system capacity of the system can be improved, and the problem of spectrum shortage is solved.
In a large-scale antenna system, many solutions to many problems such as pilot pollution, channel effective estimation, power consumption and hardware equipment cost are in urgent need of research. The current common methods are as follows:
the problem of hardware equipment cost is effectively solved based on an antenna selection technology; based on the beam forming technology, larger array gain can be obtained, the channel capacity is obviously improved, and the problem of power consumption is solved; mitigating or eliminating pilot pollution based on both channel estimation and pilot scheduling directions; at present, the methods have obvious effect on solving the problems respectively aimed at, but the methods cannot comprehensively and uniformly solve the problems of pilot pollution, power consumption, high complexity of the system, high cost and the like in a large-scale antenna system.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method for optimizing spectrum efficiency based on multiple parameters of a large-scale antenna system, so as to solve the problems of pilot pollution, high power consumption, high complexity of the system and high cost in the prior art.
In order to solve the above technical problem, an embodiment of the present invention provides a method for optimizing spectrum efficiency based on multiple parameters of a large-scale antenna system, including:
establishing a model for optimizing spectral efficiency by multiple parameters, wherein the multiple parameters comprise: antenna selection matrix, beam forming vector, transmitting power and pilot frequency sequence length;
optimizing an antenna selection matrix according to the established multi-parameter optimization spectrum efficiency model;
optimizing a beam forming vector and transmitting power according to the established multi-parameter optimization spectrum efficiency model and the antenna selection matrix obtained through optimization;
optimizing the length of a pilot frequency sequence according to the established multi-parameter optimized spectrum efficiency model and the antenna selection matrix, the beam forming vector and the transmitting power obtained through optimization;
and substituting the antenna selection matrix, the beam forming vector sum, the transmitting power and the optimized pilot frequency sequence length which are obtained by optimization into the established multi-parameter optimized spectrum efficiency model to obtain the optimized spectrum efficiency.
Further, the established multi-parameter optimization spectrum efficiency model is as follows:
arg max R
variables w,S,ps,τ；
where variables represent the optimization variables of the model, R represents the spectral efficiency, w is the beamforming vector, S is the antenna selection matrix, psIs the transmit power and τ is the pilot sequence length sent by the user.
Further, the spectral efficiency R is expressed as:
where K is the number of users in a large-scale antenna system, IKThe matrix is a K multiplied by K dimensional unit matrix, the non-superscript H is a M multiplied by K dimensional channel matrix between M antennas of the base station BS and K users in the system, the superscript H represents the conjugate of the matrix, and | | represents the determinant of the matrix.
Further, the optimizing the antenna selection matrix according to the established multi-parameter optimized spectrum efficiency model includes:
performing convex optimization processing on the established model according to step-by-step optimization equivalent to joint optimization, and converting the model from a non-convex objective function into a convex objective function;
in the obtained convex objective function, after the beam forming vector, the transmitting power and the pilot frequency sequence length are fixed, the derivative g of the convex objective function to the antenna selection matrix is calculatedi；
Derivative g of the antenna selection matrix according to the convex objective functioniCalculating the maximum value S of the lower boundary of the convex objective functioni+1；
According to the maximum value S of the lower boundary of the convex objective functioni+1And obtaining an optimized antenna selection matrix.
Further, the convex objective function obtained after transformation is represented as:
where α are convex function coefficients.
Further, the optimizing the beamforming vector and the transmission power according to the established multi-parameter optimized spectrum efficiency model and the antenna selection matrix obtained by optimization includes:
and according to step optimization equivalent to joint optimization, convex optimization processing is carried out on the established model, and the model is converted from a non-convex objective function into a convex objective function:
arg maxf(w)＝fcave(w)+fvex(w)
wherein f iscave(w) concave functions in the convex objective function f (w), fvex(w) convex functions of the convex objective function f (w);
according to the obtained convex objective function, after the pilot frequency sequence length is fixed, the partial derivative of the concave function in the convex objective function to the beam forming vector is calculated by utilizing the antenna selection matrix obtained by optimization
Wherein,
representing partial derivative of the variable of the concave function;
partial derivative of a beamforming vector according to a concave function in a convex objective function
Maximum value w of lower boundary of convex objective functioni+1；
Maximum value w based on the lower boundary of the convex objective functioni+1And obtaining the optimized beam forming vector and the optimized transmitting power.
Further, the optimizing the pilot sequence length according to the established multi-parameter optimized spectrum efficiency model and the antenna selection matrix, the beamforming vector and the transmission power obtained through optimization includes:
constructing a pilot frequency sequence length optimization function according to an energy efficiency maximization principle;
and according to the established multi-parameter optimization spectrum efficiency model, after the spectrum efficiency is fixed to be a preset constant, searching the pilot frequency sequence length which enables the energy efficiency to be maximized by utilizing the antenna selection matrix, the beam forming vector and the transmitting power which are obtained through optimization, and obtaining the optimized pilot frequency sequence length.
Further, the constructed pilot sequence length optimization function is expressed as:
further, the channel refers to an uplink channel of a large-scale antenna system.
The technical scheme of the invention has the following beneficial effects:
in the scheme, a model for optimizing the spectrum efficiency by multiple parameters is established; optimizing an antenna selection matrix according to the established multi-parameter optimization spectrum efficiency model; optimizing a beam forming vector and transmitting power according to the established multi-parameter optimization spectrum efficiency model and the antenna selection matrix obtained through optimization; optimizing the length of a pilot frequency sequence according to the established multi-parameter optimized spectrum efficiency model and the antenna selection matrix, the beam forming vector and the transmitting power obtained through optimization; and substituting the antenna selection matrix, the beam forming vector sum, the transmitting power and the optimized pilot frequency sequence length which are obtained by optimization into the established multi-parameter optimized spectrum efficiency model to obtain the optimized spectrum efficiency. Therefore, by optimizing the 4 parameters of the antenna selection matrix, the beam forming vector, the transmitting power and the pilot sequence length in the established spectrum efficiency model, the problems of pilot pollution, large power consumption, high complexity and high cost in a large-scale antenna system can be comprehensively solved, and the spectrum efficiency of the system is improved.
Drawings
Fig. 1 is a schematic flowchart of a method for optimizing spectrum efficiency based on multiple parameters of a large-scale antenna system according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a Massive MIMO communication system according to an embodiment of the present invention;
fig. 3 is a schematic diagram illustrating comparison between the GA effect and the method for multi-parameter optimization of spectrum efficiency of a large-scale antenna system according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantages of the present invention more apparent, the following detailed description is given with reference to the accompanying drawings and specific embodiments.
Aiming at the problems of the existing pilot frequency pollution, high power consumption, high system complexity and high cost, the invention provides a method for optimizing the spectrum efficiency based on multiple parameters of a large-scale antenna system.
As shown in fig. 1, the method for optimizing spectrum efficiency based on multiple parameters of a large-scale antenna system according to the embodiment of the present invention includes:
s101, establishing a multi-parameter optimization spectrum efficiency model, wherein the multi-parameter optimization spectrum efficiency model comprises the following steps: antenna selection matrix, beam forming vector, transmitting power and pilot frequency sequence length;
s102, optimizing an antenna selection matrix according to the established multi-parameter optimization spectrum efficiency model;
s103, optimizing a beam forming vector and transmitting power according to the established multi-parameter optimization spectrum efficiency model and the antenna selection matrix obtained through optimization;
s104, optimizing the length of a pilot frequency sequence according to the established multi-parameter optimization spectrum efficiency model and the antenna selection matrix, the beam forming vector and the transmitting power obtained through optimization;
and S105, bringing the antenna selection matrix, the beam forming vector sum, the transmitting power and the optimized pilot frequency sequence length which are obtained through optimization into the established multi-parameter optimized spectrum efficiency model to obtain the optimized spectrum efficiency.
The method for optimizing the spectrum efficiency based on the multiple parameters of the large-scale antenna system establishes a model for optimizing the spectrum efficiency based on the multiple parameters; optimizing an antenna selection matrix according to the established multi-parameter optimization spectrum efficiency model; optimizing a beam forming vector and transmitting power according to the established multi-parameter optimization spectrum efficiency model and the antenna selection matrix obtained through optimization; optimizing the length of a pilot frequency sequence according to the established multi-parameter optimized spectrum efficiency model and the antenna selection matrix, the beam forming vector and the transmitting power obtained through optimization; and substituting the antenna selection matrix, the beam forming vector sum, the transmitting power and the optimized pilot frequency sequence length which are obtained by optimization into the established multi-parameter optimized spectrum efficiency model to obtain the optimized spectrum efficiency. Therefore, by optimizing the 4 parameters of the antenna selection matrix, the beam forming vector, the transmitting power and the pilot sequence length in the established spectrum efficiency model, the problems of pilot pollution, large power consumption, high complexity and high cost in a large-scale antenna system can be comprehensively solved, and the spectrum efficiency of the system is improved.
In the foregoing specific embodiment of the method for optimizing spectrum efficiency based on multiple parameters of a large-scale antenna system, further, the established multi-parameter optimization spectrum efficiency model is:
arg max R
variables w,S,ps,τ；
where variables represent the optimization variables of the model, R represents the spectral efficiency, w is the beamforming vector, S is the antenna selection matrix, psIs the transmit power and τ is the pilot sequence length sent by the user.
Further, the spectral efficiency R is expressed as:
where K is the number of users in a large-scale antenna system, IKThe matrix is a K multiplied by K dimensional unit matrix, the non-superscript H is a M multiplied by K dimensional channel matrix between M antennas of the base station BS and K users in the system, the superscript H represents the conjugate of the matrix, and | | represents the determinant of the matrix.
In the embodiment of the present invention, as shown in fig. 2, a schematic diagram of a large-scale antenna system structure is shown, and it is assumed that a Base Station (BS) is equipped with M antennas, and K single-antenna users conform to a flat fading uplink channel. All users are mobile within a specified range centered at the base station, or certainly not mobile.
In this embodiment, it is assumed that the large-scale antenna system includes: a Base Station (BS) with M transmit antennas and K single-antenna users, where M is greater than or equal to K, and K users occupy the same time-frequency resource to transmit data, and then a received signal y of the BS is represented as:
y＝HSwx+n
where y is a received signal of a Base Station (BS), a vector of M × 1 dimensions; h is M multiplied by K dimensional channel matrix H [ H ] between M antennas of base station BS and K users in system1,h2,...,hm]The channel between the mth antenna of the BS and the kth user is hkH of, K x 1 dimensionkA channel vector corresponding to the mth transmit antenna; w is M rootThe beamforming weights of the transmission antennas, which represent beamforming vectors, are M × 1-dimensional matrices, and w ═ w1,w2,...,wm]T∈R+，R+Represents positive real number, w is less than or equal to 1mThe m-th transmitting antenna beam forming weighted value, | | | | | represents the norm of the matrix, and epsilon represents belonging to the set; x is the transmitted signal vector, x ═ x1,x2,...,xm]TT denotes the transpose of the matrix, xmIs a symbol transmitted from the mth transmission antenna; n is a zero-mean additive white gaussian noise vector, an M × 1 dimensional vector; s is an antenna selection matrix, which is a diagonal matrix of dimension M × M, trace (S) K, which represents the traces of the matrix, such that:
after the received signal y of the base station BS passes through the linear detector, a received signal r is obtained, which can be represented as:
r＝AHy
where a is a linear detection matrix of dimension M × K, and when a linear zero-forcing detector is used, a is H, and non-superscript H is a channel matrix of dimension M × K between M antennas of a Base Station (BS) and K users; the superscript H denotes the conjugate of the matrix.
According to the obtained received signal r, establishing a multi-parameter optimization spectrum efficiency model of the uplink system as follows:
arg max R
variables w,S,ps,τ；
where variables represent the optimization variables of the model, R represents the spectral efficiency, w is the beamforming vector, S is the antenna selection matrix, psIs the transmit power and τ is the pilot sequence length sent by the user.
The spectral efficiency R is expressed as:
where K is the number of users in a large-scale antenna system, IKThe matrix is a K multiplied by K dimensional unit matrix, the non-superscript H is a M multiplied by K dimensional channel matrix between M antennas of the base station BS and K users in the system, the superscript H represents the conjugate of the matrix, and | | represents the determinant of the matrix.
In the embodiment of the invention, in S102, S103 and S104, a multi-parameter optimization spectral efficiency model established in S101 can be utilized, step-by-step optimization equivalent to multi-optimization is carried out, and an antenna selection matrix S, a beam forming vector w and transmitting power p are optimized step by stepSAnd a pilot sequence length tau.
In this embodiment, the optimizing the antenna selection matrix according to the established multi-parameter optimized spectrum efficiency model may specifically include:
according to step-by-step optimization equivalent to joint optimization, convex optimization processing is carried out on the established model, an antenna selection matrix is optimized step by step, the model is converted into a convex objective function from a non-convex objective function, and the convex objective function is expressed as:
where a is the convex function coefficient, α is a constant, a > 0;
in the obtained convex objective function, the beam forming vector, the transmitting power and the pilot frequency sequence length are fixed, and then the derivative g of the convex objective function to the antenna selection matrix is calculatedi；
According to the derivative g of the convex objective function obtained by calculation to the antenna selection matrixiCalculating the maximum value S of the lower boundary of the convex objective functioni+1：
Wherein,
a representation definition;
according to the maximum value S of the lower boundary of the convex objective functioni+1And obtaining an optimized antenna selection matrix.
In this embodiment, the optimizing the beamforming vector and the transmission power according to the established multi-parameter optimized spectrum efficiency model and the antenna selection matrix obtained through optimization may specifically include:
according to step optimization equivalent to joint optimization, convex optimization processing is carried out on the established model, and the beamforming vector w and the transmitting power p are optimized step by stepSTransforming the model from a non-convex objective function to a convex objective function:
arg max f(w)＝fcave(w)+fvex(w)
wherein f iscave(w) concave functions in the convex objective function f (w), fvex(w) convex functions of the convex objective function f (w);
in the obtained convex objective function, the pilot frequency sequence length is fixed, and the partial derivative of the concave function in the objective function to the beam forming vector is calculated by utilizing the antenna selection matrix obtained by optimization
Wherein,
representing partial derivative of the variable of the concave function;
partial derivative of beamforming vector according to concave function in objective function
Solving the maximum value w of the lower boundary of the convex objective functioni+1：
Maximum value w based on the lower boundary of the convex objective functioni+1And obtaining the optimized beam forming vector and the optimized transmitting power.
In this embodiment, the optimizing the pilot sequence length according to the established multi-parameter optimized spectrum efficiency model and the antenna selection matrix, the beamforming vector, and the transmission power obtained through optimization may specifically include:
constructing a pilot frequency sequence length optimization function according to an energy efficiency maximization principle;
and according to the established multi-parameter optimization spectrum efficiency model, after the spectrum efficiency is fixed to be a preset constant, searching the pilot frequency sequence length which enables the energy efficiency to be maximized by utilizing the antenna selection matrix, the beam forming vector and the transmitting power which are obtained through optimization, and obtaining the optimized pilot frequency sequence length.
In this embodiment, S102-S104 are repeatedly executed until a preset iteration termination condition is satisfied, that is, the frequency spectrum efficiency iteration added value of the system is less than or equal to 0.01, and the antenna selection matrix, the beam forming vector sum, the transmission power and the optimized pilot frequency sequence length which are finally obtained by optimization are brought into the established multi-parameter optimized frequency spectrum efficiency model to obtain the optimized frequency spectrum efficiency.
The channel referred to in this embodiment refers to an uplink channel of a large-scale antenna system.
In order to better understand the method for optimizing the spectrum efficiency based on the multiple parameters of the large-scale antenna system according to the embodiment of the present invention, a specific embodiment is described in detail as follows:
in this embodiment, it is assumed that a Base Station (BS) is equipped with 100 antennas and 55 single-antenna users, and conforms to an uplink channel with flat fading. All users are mobile within a specified range centered at the base station, or certainly not mobile.
In the embodiment of the invention, a large-scale antenna array is configured at a base station end in a system and provides service for a plurality of user terminals at the same time, and the number of antennas configured at the base station is far larger than the number of users at a receiving end; for a flat fading channel, only fast fading is considered because space fading and shadow fading are non-order in number and can be assumed as constants; assuming a coherence time of 196ms, modeling the multi-parameter optimized spectral efficiency may include:
a11, the received signal y of the base station BS is represented as follows:
y＝HSwx+n
wherein n is a zero-mean additive white gaussian noise vector, a 100 x 1 dimensional vector;
a12, using A11 to obtain the received signal of the base station, and passing through a linear zero forcing detector, the received signal of the base station BS is represented as follows:
r＝AHy
wherein a is a linear detection matrix of 100 × 55 dimensions; y is a received signal of a Base Station (BS), a vector of 100 × 1 dimensions;
a13, obtaining a receiving signal r of a base station BS, and establishing a multi-parameter optimization spectrum efficiency model of an uplink system as follows:
variables w,S,ps,τ；
wherein K represents the number of users in the system as 55; i isKIs an identity matrix of 55 x 55 dimensions; tau is the pilot frequency sequence length of pilot frequency sent by the user, and tau is more than or equal to 55 and less than or equal to 196; p is a radical ofsIs the transmit power; the non-superscript H is a 100 × 55 dimensional channel matrix between 100 antennas of a Base Station (BS) and 55 users, H ═ H1,h2,...,hm]The channel between the mth antenna of the BS and the kth user is hkH of 55X 1 dimensionkA channel vector corresponding to the mth transmit antenna; s is an antenna selection matrix, a 100 × 100 dimensional diagonal matrix, trace (S) 55, such that:
where x is the transmitted signal vector, x ═ x1,x2,…,xm]T(T denotes the transpose of the matrix), xmIs a symbol transmitted from the mth transmission antenna; w is a 100 × 1 dimensional matrix of beamforming weights for M transmit antennas, w ═ w1,w2,…,wm]T∈R+(R+Representing positive real number) and | | | w | | | is less than or equal to 1, wmIs a beam forming weight value of the mth transmitting antenna; t is the coherence time; superscript H represents the conjugate of the matrix; trace represents the trace of the matrix; | | represents the norm of the matrix; and | represents a determinant of the matrix.
In this embodiment, it is assumed that a 100 × 1-dimensional signal vector x is randomly generated, the optimized beamforming vector w is a 100 × 1-dimensional vector with | | | w | | ≦ 1, and the transmission power p is randomly generatedS＝wHwE{|x|2The pilot sequence length tau is 55; optimizing an antenna selection matrix S, specifically comprising the following steps:
a21, according to the step-by-step optimization equivalent to the joint optimization, optimizing an antenna selection matrix step by step, and converting a parameter model from a non-convex objective function into a convex objective function;
a22, in the convex objective function, fixing the elements of 100 × 1 dimension of beam forming vector to be 0.1, and transmitting power wHwE{|x|2Generating signals randomly, wherein the length of a pilot sequence is 55;
a23, calculating the derivative of the convex objective function to the antenna selection matrix;
a24, calculating the maximum value S of the lower boundary of the convex objective function according to the derivative of the convex objective function to the antenna selection matrixi+1；
A25, maximum value S of lower boundary of convex objective functioni+1And obtaining an optimized antenna selection matrix.
In this embodiment, an antenna selection matrix is obtained, pilot sequence length is fixed, and beamforming vector w and transmission power p are optimizedSThe method comprises the following specific steps:
a31, optimizing the beam forming vector w and the transmitting power p step by step according to the step optimization equivalent to the joint optimizationSConverting the parametric model from a non-convex objective function to a convex objective function:
arg max f(w)＝fcave(w)+fvex(w)
wherein f iscave(w) concave functions in the convex objective function f (w), fvex(w) represents a convex objective functionConvex function in (f), (w);
a32, in the convex objective function obtained, pilot sequence length 55 is fixed, and the partial derivative of the concave function in the objective function to the beam forming vector is calculated by using the antenna selection matrix obtained by optimization
Wherein,
representing partial derivative of the variable of the concave function;
a33 partial derivative of beamforming vector according to concave function of objective function
Constructing a beamforming vector optimization function wi+1：
And A34, solving the formula in A33 to obtain the beam forming vector and the transmitting power.
In this embodiment, the pilot sequence length τ is optimized step by step according to the antenna selection matrix, the beamforming vector, and the transmission power obtained by the above solution, and the specific steps are as follows:
a41, constructing a pilot sequence length optimization function according to an energy efficiency maximization principle;
a42, according to the established multi-parameter optimization spectrum efficiency model, after fixing the spectrum efficiency as a preset constant, searching the pilot sequence length which maximizes the energy efficiency by using the antenna selection matrix, the beam forming vector and the transmitting power which are obtained by optimization, and obtaining the optimized pilot sequence length.
And finally, bringing the antenna selection matrix, the beam forming vector sum, the transmitting power and the optimized pilot frequency sequence length obtained by optimization into the established multi-parameter optimized spectrum efficiency model to obtain the optimized spectrum efficiency.
In this embodiment, fig. 3 is a schematic diagram illustrating a comparison between the spectrum efficiency effect of the multi-parameter optimized spectrum efficiency method of the large-scale antenna system provided in the embodiment and the spectrum efficiency effect of the conventional Genetic (GA) algorithm. The abscissa in fig. 3 is the signal-to-noise ratio (dB) and the ordinate is the spectral efficiency, which results from repeated experiments under the same conditions with an equally increased signal-to-noise ratio at 100 transmit antennas, 55 number of users served, 196ms coherence time. As can be seen from fig. 3, compared with the conventional Genetic (GA) algorithm, the method for improving spectrum efficiency provided by the embodiment of the present invention not only reduces the problems of pilot pollution, power consumption, system complexity and cost, etc. in the system, but also obtains better performance. This demonstrates that the proposed method is comprehensive and efficient. Meanwhile, the comparison result also shows that the method for optimizing the spectrum efficiency based on the multiple parameters of the large-scale antenna system provided by the embodiment of the invention is superior to the performance of the spectrum efficiency of the traditional Genetic (GA) algorithm.
To sum up, the method for optimizing spectrum efficiency based on multiple parameters of a large-scale antenna system provided by the embodiment of the invention mainly has the following advantages:
1) the method for optimizing the spectrum efficiency by multiple parameters of the large-scale antenna system can estimate the channel based on the pilot frequency, acquire complete Channel State Information (CSI) of the channel, schedule the pilot frequency and optimize the length of a pilot frequency sequence, thereby effectively reducing the pilot frequency pollution of the system;
2) the method for optimizing the frequency spectrum efficiency by multiple parameters of the large-scale antenna system can select part of antennas with optimal performance from multiple antennas of the base station to transmit signals, and improves the frequency spectrum efficiency of the system on the premise of not influencing the service quality of users;
3) the method for optimizing the spectrum efficiency by multiple parameters of the large-scale antenna system provided by the embodiment of the invention optimizes the beam forming vector by utilizing the beam forming technology to obtain larger array gain, correspondingly reduces the transmitting power and achieves the same service quality;
4) the spectral efficiency is improved, and under the same condition, the spectral efficiency of the method is superior to that of the traditional classical Genetic Algorithm (GA).
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (3)
1. A method for optimizing spectral efficiency based on multiple parameters of a large-scale antenna system is characterized by comprising the following steps:
establishing a model for optimizing spectral efficiency by multiple parameters, wherein the multiple parameters comprise: antenna selection matrix, beam forming vector, transmitting power and pilot frequency sequence length;
optimizing an antenna selection matrix according to the established multi-parameter optimization spectrum efficiency model;
optimizing a beam forming vector and transmitting power according to the established multi-parameter optimization spectrum efficiency model and the antenna selection matrix obtained through optimization;
optimizing the length of a pilot frequency sequence according to the established multi-parameter optimized spectrum efficiency model and the antenna selection matrix, the beam forming vector and the transmitting power obtained through optimization;
the antenna selection matrix, the beam forming vector sum, the transmitting power and the optimized pilot frequency sequence length which are obtained through optimization are brought into the established multi-parameter optimized spectrum efficiency model, and the optimized spectrum efficiency is obtained;
the established multi-parameter optimization spectrum efficiency model comprises the following steps:
argmaxR
variables w,S,ps,τ；
wherein variables represent the merit of the modelA quantization variable, R denotes spectral efficiency, w is a beamforming vector, S is an antenna selection matrix, psIs the transmission power, tau is the pilot sequence length sent by the user;
wherein the spectral efficiency R is expressed as:
where K is the number of users in a large-scale antenna system, IKThe method comprises the following steps that a K multiplied by K-dimensional unit matrix is adopted, a non-superscript H is an M multiplied by K-dimensional channel matrix between M antennas of a base station BS and K users in a system, the superscript H represents the conjugate of the matrix, and | | represents the determinant of the matrix;
wherein, optimizing the antenna selection matrix according to the established multi-parameter optimized spectrum efficiency model comprises:
performing convex optimization processing on the established model according to step-by-step optimization equivalent to joint optimization, and converting the model from a non-convex objective function into a convex objective function;
in the obtained convex objective function, after the beam forming vector, the transmitting power and the pilot frequency sequence length are fixed, the derivative g of the convex objective function to the antenna selection matrix is calculatedi；
Derivative g of the antenna selection matrix according to the convex objective functioniCalculating the maximum value S of the lower boundary of the convex objective functioni+1；
According to the maximum value S of the lower boundary of the convex objective functioni+1Obtaining an optimized antenna selection matrix;
wherein, optimizing the spectrum efficiency model and the antenna selection matrix according to the established multi-parameter optimization spectrum efficiency model and the antenna selection matrix obtained by optimization comprises the following steps:
and according to step optimization equivalent to joint optimization, convex optimization processing is carried out on the established model, and the model is converted from a non-convex objective function into a convex objective function:
arg maxf(w)＝fcave(w)+fvex(w)
wherein f iscave(w) concave function in the convex objective function f (w)Number fvex(w) convex functions of the convex objective function f (w);
according to the obtained convex objective function, after the pilot frequency sequence length is fixed, the partial derivative of the concave function in the convex objective function to the beam forming vector is calculated by utilizing the antenna selection matrix obtained by optimization
Wherein,
representing partial derivative of the variable of the concave function;
partial derivative of a beamforming vector according to a concave function in a convex objective function
Maximum value w of lower boundary of convex objective functioni+1；
Maximum value w based on the lower boundary of the convex objective functioni+1Obtaining optimized beam forming vector and transmitting power;
the optimizing the frequency spectrum efficiency model according to the established multi-parameter and the antenna selection matrix, the beam forming vector and the transmitting power obtained by optimizing comprises the following steps:
constructing a pilot frequency sequence length optimization function according to an energy efficiency maximization principle;
and according to the established multi-parameter optimization spectrum efficiency model, after the spectrum efficiency is fixed to be a preset constant, searching the pilot frequency sequence length which enables the energy efficiency to be maximized by utilizing the antenna selection matrix, the beam forming vector and the transmitting power which are obtained through optimization, and obtaining the optimized pilot frequency sequence length.
2. The method for optimizing spectral efficiency based on multiple parameters of a massive antenna system according to claim 1, wherein the convex objective function obtained after transformation is represented as:
where a is the convex function coefficient.
3. The method for optimizing spectral efficiency based on multiple parameters of a massive antenna system according to claim 1, wherein the constructed pilot sequence length optimization function is expressed as:
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