CN107579760B - Energy distribution method of zero forcing MIMO communication system - Google Patents

Energy distribution method of zero forcing MIMO communication system Download PDF

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CN107579760B
CN107579760B CN201610503084.XA CN201610503084A CN107579760B CN 107579760 B CN107579760 B CN 107579760B CN 201610503084 A CN201610503084 A CN 201610503084A CN 107579760 B CN107579760 B CN 107579760B
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戴继生
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Suzhou shuoshi Electronic Technology Co.,Ltd.
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Abstract

The energy distribution method of the zero forcing MIMO communication system comprises the following steps: s1) obtaining the total user number and each user antenna number and the base station channel state information thereof, and constructing each user information matrix; s2) carrying out singular value decomposition on the information matrix to generate a subchannel gain value; s3) inputting all subchannel gain values into a breakpoint function to generate complex breakpoint values; s4) initializing the user antenna energy distribution value and establishing a temporary storage set; s5) a breakpoint value is taken to be compared with all the subchannel gain values so as to update the temporary storage set; s6) constructing an energy efficiency function; s7) inputting the breakpoint values as variables into an energy efficiency function to generate result values, and if the result values are larger than threshold values, returning to S5 until all the breakpoint values are calculated; if the result value is smaller than the threshold value, performing S8; s8) the energy distribution function is input by taking the root value of the energy efficiency function, the new antenna energy distribution values of all users are calculated, and the energy of the new antenna energy distribution values is output, so that the energy output with better energy efficiency under the constraint condition of total energy of multiple users can be realized.

Description

Energy distribution method of zero forcing MIMO communication system
Technical Field
The invention relates to a MIMO communication system, in particular to an energy distribution method of a zero-forcing MIMO communication system with priority on energy efficiency.
Background
In order to further improve the spectrum utilization rate of the communication system, new changes in the aspects of network system structure, networking technology, wireless transmission technology and the like are needed in the mobile communication technology. Multiple-input multiple-output (MIMO) technology has become one of the core technologies of future communication systems, and will also be one of the core technologies adopted by the wlan standard. However, the energy consumption of the communication system is greatly increased while improving the radio transmission performance.
The method is different from the traditional MIMO communication system in pursuing faster and better data transmission capacity, the MIMO communication system with the prior energy efficiency mainly focuses on the two aspects of energy saving and environment protection, and according to the characteristics and the target of the MIMO communication system, the method efficiently utilizes resources such as time, space, frequency spectrum, energy, facilities and the like, reduces energy consumption as far as possible, reduces comprehensive energy consumption, avoids electromagnetic pollution and ensures information safety on the premise of meeting the reasonable requirements of each service.
Zero-Forcing (ZF) MIMO communication systems are relatively easy to implement in practice, and some new energy allocation methods for Zero-Forcing MIMO communication systems have been proposed in an attempt to give priority to energy efficiency. For example, in the documents "Miao G., Energy-efficient uplink multi-user MIMO," IEEE Transactions on Wireless Communications 12(5) (2013) "2302-. However, in the multi-user MIMO communication system, the rf circuits of each user are independent, and the total energy constraint cannot meet the practical application.
Disclosure of Invention
Aiming at the defects of the existing method, the invention provides an energy distribution method of a zero-forcing MIMO communication system, which can fully utilize the piecewise linear characteristic of multi-user energy distribution under the constraint condition of total energy in the environment of a multi-user MIMO communication system to realize the redistribution of an energy output result with better energy efficiency, and has small overall calculated amount and wider application range.
In order to achieve the above object, the energy allocation method for a zero-forcing MIMO communication system proposed by the present invention reallocates an energy output result with better energy efficiency under a total energy constraint condition in a multi-user MIMO communication system environment, which comprises the following steps:
s1) obtaining the total user number, the antenna number of each user and the base station channel state information thereof, and constructing an information matrix of each user;
s2) performing singular value decomposition on all information matrices, respectively, to generate a subchannel gain value corresponding to each user;
s3) inputting all subchannel gain values into a breakpoint function to generate complex breakpoint values;
s4) initializing the antenna energy distribution values of all users and establishing a complex temporary storage set;
s5) a breakpoint value is taken out to be compared with all the subchannel gain values in sequence, and the comparison result is updated to the corresponding temporary storage set;
s6) constructing an energy efficiency function according to the values generated in the previous step;
s7) inputting the breakpoint value as a variable into an energy efficiency function to generate a result value, judging whether the result value is larger than a threshold value, if so, returning to the step S5 until all the breakpoint values are calculated; if the result value is smaller than the threshold value, go to step S8;
s8) extracting the root value of the energy efficiency function, calculating new antenna energy distribution values of all users by inputting the root value into the energy distribution function, and outputting the energy.
Further, the information matrix is N × MkA matrix of dimensions, where N denotes the number of antennas of the base station and MkRepresenting the number of antennas for the k-th user. In step S2, the information matrix HkPerforming singular value decomposition to obtain
Figure BDA0001037037350000021
Wherein (·)HWhich represents the transpose of the conjugate,
Figure BDA0001037037350000022
represents Mk×MkMatrix of singular values of the dimension, λkmRepresents HkOf the m-th singular value, UkAnd VkRespectively represent N × MkLeft singular vector matrix sum M of dimensionsk×MkThe right singular vector matrix of the dimension.
Further, step S3 interrupts the point function as
Figure BDA0001037037350000023
Where K is the total number of users, MkIndicates the number of antennas, gamma, of the k-th userkmIs a subchannel gain value representing the mth antenna of the kth user. And the number of breakpoint values is Q,
Figure BDA0001037037350000024
μkdetermined by water injection, i.e. solving equations
Figure BDA0001037037350000025
Wherein (x)+＝max{x，0}，
Figure BDA0001037037350000026
Representing the upper limit of the energy of the transmitter of the kth user.
The breakpoint value generated by the above is recorded as mu(1)，μ(2)，...μ(Q)And arranged in descending order.
Further, in step S4, the plural temporary signals are transmittedThe storage sets at least include a first storage set, a second storage set and a third storage set, respectively A, B and EkAnd (4) showing. In step S5, one of the breakpoint values is taken out and compared with all the subchannel gain values, and the following judgment is performed according to the breakpoint value: if it is
Figure BDA0001037037350000031
Where K 'is a {1, 2.,. K }, and M' is a {1, 2.,. M }, in thatkE, the third temporary storage set is updated to Ek＝EkU { m' }; if it isμ(q)＝μk′And if K ' is larger than {1, 2., K }, updating the first temporary set to a ═ u { K ' } and updating the second temporary set to B ═ B/{ K ' }.
Further, the energy efficiency function in step S6 is
Figure BDA0001037037350000032
Wherein the coefficients a, b, c are defined as:
Figure BDA0001037037350000033
wherein P isrRepresenting the fixed loss of the communication system in addition to the transmitted energy,
Figure BDA0001037037350000034
indicating the efficiency of energy conversion.
Further, the threshold value is set to 0 in step S7.
Further, the energy distribution function in step S8 is
Figure BDA0001037037350000035
Wherein mu*Is the root value of the energy efficiency function.
After the total user number, the antenna number of each user and the base station channel state information of the users in the multi-user MIMO communication system are obtained, the step can be performed, the piecewise linearity characteristic of multi-user energy distribution is fully utilized under the condition of total energy constraint, and the energy output result with better energy efficiency is redistributed.
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The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
FIG. 1 is a schematic representation of the steps of the present invention.
FIG. 2 is a schematic flow diagram of the present invention.
FIG. 3 is a block diagram of the steps of an exemplary embodiment of the present invention.
Fig. 4 is a schematic diagram of energy efficiency values obtained by the present invention and the conventional method when the distance between the transceivers varies from 0.1 to 1.5 km under the condition of 1000 monte carlo experiments.
Detailed Description
FIG. 1 is a schematic representation of the steps of the present invention. The steps are realized through a computer program, the whole calculation amount is small, the processing speed is far better than that of the traditional method, and the burden and the cost of hardware equipment can be reduced. In the figure, steps S1 to S8 are arranged schematically, and steps S5 to S7 are loop processing for obtaining a new antenna energy allocation value after all the breakpoint values are calculated, wherein step S7 is decision making, and determines whether a result value generated after the breakpoint values are input into the energy efficiency function is greater than a threshold value, and returns to step S5 according to the result until all the breakpoint values are calculated or step S8 is performed. After all the calculations are completed, a new antenna energy allocation value is output to each antenna, so that the allocation with the best energy efficiency is achieved, and further, the overall calculation amount is small, so that the burden of hardware equipment is reduced.
FIG. 2 is a schematic flow diagram of the present invention. The steps after subdivision are of course also realized by means of a computer program.
In step S201, the total number of users, the number of antennas per user and the bs channel state information are obtained, wherein the total number of users is defined as K, MkDenotes the number of antennas for the kth user, where K is 1, 2.
In step S202, each of the building blocks is constructedInformation matrix of individual users, wherein the information matrix is defined as HkThe information matrix HkIs NxMkMatrix of dimensions, MkAs well defined above, N represents the number of antennas of the base station.
In step S203, all information matrices are subjected to singular value decomposition, respectively, each information matrix HkThrough singular value decomposition to obtain
Figure BDA0001037037350000041
Wherein (·)HWhich represents the transpose of the conjugate,
Figure BDA0001037037350000042
represents Mk×MkSingular value matrix of dimension, and λkmRepresents HkOf the m-th singular value, UkRepresents NxMkLeft singular vector matrix of dimension, and VkRepresents Mk×MkThe right singular vector matrix of the dimension.
In step S204, a subchannel gain value corresponding to each user is generated, wherein the mth subchannel gain value of the kth user is defined as γkm. Subchannel gain value gammakmThe calculation method of (c) is specifically as follows, first defining the zero-forcing filter matrix G ═ (U)HU)-1UHWherein U ═ U1，U2，...，UK]Reconstructing a subchannel gain value of
Figure BDA0001037037350000043
Wherein sigma2Variance, u, representing white Gaussian noisekmRepresentation matrix (U)HU)-1To (1) a
Figure BDA0001037037350000044
A diagonal element, LkIndicating the propagation loss of the electromagnetic wave corresponding to the k-th user.
In step S205, all the sub-channel gain values are input into a breakpoint function to generate a complex breakpoint value, wherein the breakpoint function is
Figure BDA0001037037350000051
Where K is the total number of users, MkThe number of antennas for the k-th user as described above. And the number of breakpoint values is Q,
Figure BDA0001037037350000052
in addition, μ in the breakpoint functionkDetermined by water injection, i.e. solving equations
Figure BDA0001037037350000053
Wherein (x)+＝max{x，0}，
Figure BDA0001037037350000054
Representing the upper limit of the energy of the transmitter of the kth user.
In step S206, the antenna energy allocation values of all users are initialized, and in order to ensure that the subsequent operations are not affected by the previous values to generate errors, the initialized values are zero, and further, the initialization is pkm＝0，k＝1，2，...，K，m＝1，2，...，MkWherein p iskmRepresenting the amount of energy allocated on the mth antenna of the kth user.
In step S207, a plurality of temporary storage sets, which are a first temporary storage set a, a second temporary storage set B and a third temporary storage set E, are establishedkAnd the temporary storage sets are respectively
Figure BDA0001037037350000055
Where K is 1, 2.
In step S208, a count variable q is set to 1, so as to sequentially take out the breakpoint values and sequentially compare the breakpoint values with the subchannel gain values, and the comparison method makes the following determination according to the sources of the breakpoint values:
if it is
Figure BDA0001037037350000056
Where K 'is a {1, 2.,. K }, and M' is a {1, 2.,. M }, in thatkAnd updating the third temporary storage set to Ek＝Ek∪{m′}；
Mu.s of(q)＝μk′And if K ' is larger than {1, 2., K }, updating the first temporary set to a ═ u { K ' } and updating the second temporary set to B ═ B/{ K ' }.
In step S209, the comparison result is updated to the corresponding temporary storage set.
In step S210, an energy efficiency function is constructed according to the values generated in the previous steps, wherein the energy efficiency function is
Figure BDA0001037037350000057
Wherein the coefficients a, b, c are defined as:
Figure BDA0001037037350000061
wherein P isrRepresents the fixed loss of the communication system in addition to the transmitted energy, and
Figure BDA0001037037350000062
indicating the efficiency of energy conversion.
In step S211, the breakpoint value is input as a variable into the energy efficiency function to generate a result value, i.e., the breakpoint value μ(q+1)The resulting value f (mu) is generated as a variable x in the energy efficiency function f (x)(q+1)) That is, the result value is determined by the energy efficiency function f (x) when x is equal to μ(q+1)The magnitude of the time.
In step S212, it is determined whether the result value is greater than a threshold value, wherein the threshold value is set to 0. When the result value is greater than the threshold value, i.e. f (mu)(q+1)) If not, returning to the step S208 until all the breakpoint values are calculated; when the result value is smaller than the threshold value, i.e., f (mu)(q+1)) If < 0, go to step S213.
In step S213, the root value of the energy efficiency function, that is, the root value of equation f (x) 0, that is, the root of equation f (x) 0, is extracted, and the root value is represented as μ*。
In step S214, the energy distribution function is inputted to the root, new antenna energy distribution values of all users are calculated, and the energy values are outputted, wherein the energy distribution functionIs composed of
Figure BDA0001037037350000063
The root value is the best solution on the premise of energy efficiency priority, and after the calculation of the energy distribution value is completed, the energy distribution value is output to the antenna.
In the above description, the steps S201 to S207 are detailed as the steps S1 to S4 in fig. 1, and the steps S208 to S214 are detailed as the steps S5 to S8 in fig. 1, and the definitions mentioned in each step are described in detail, so that the relationship therebetween can be more easily understood.
FIG. 3 is a block diagram of steps of an exemplary embodiment of the present invention, which particularly and concisely represents technical focus of the present invention to make the overall understanding more rapid and clear.
In step S301, an information matrix H of each user is constructedkThat is, the pre-operation mentioned in step S1 in fig. 1 is completed together, and the information matrix H required to be used subsequently is generatedk。
In step S302, each information matrix HkPerforming singular value decomposition to generate a subchannel gain value gamma corresponding to each userkmThat is, the subchannel gain value γ is obtained in step S2 in fig. 1kmFor use in subsequent calculations of the breakpoint values.
In step S303, Q breakpoints are calculated and arranged in descending order and are respectively recorded as mu(1)，μ(2)，...μ(Q)The method aims to adopt descending order arrangement to be beneficial to subsequent calculation processing.
In step S304, the antenna energy allocation values of all users are initialized to 0, and a temporary storage set A, B, E is createdk. As described above, the power allocation for the antennas is initialized to 0 to avoid interference from previous values and to establish a temporary set A, B, E for use in subsequent loop calculationskAnd the count variable q for the loop is set to 1.
In step S305, according to the breakpoint value mu(q)The source of the value of (c), the corresponding update register set A, B, Ek。
Step (ii) ofIn step S306, the temporary storage set A, B, E updated according to step S305kAnd constructing an energy efficiency function f (x).
In step S307, it is judged whether f (μ)(q+1)) And ≧ 0, that is, whether the determination result value is greater than the threshold value, if so, the count variable is updated to q +1, and the process returns to step S305, and if so, the process proceeds to step S308.
In step S308, the root of equation f (x) 0 is extracted, that is, the root of equation f (x) 0 is solved, and the root is expressed as μ*. Then, the root value is input into an energy distribution function, new antenna energy distribution values of all users are calculated, and energy values of the new antenna energy distribution values are output, wherein the energy distribution function is
Figure BDA0001037037350000071
The root value is the best solution on the premise of energy efficiency priority, and after the calculation of the energy distribution value is completed, the energy distribution value is output to the antenna. In other words, the energy allocation value of the antenna with the best energy efficiency is obtained, and the energy is allocated to each antenna as a result.
For convenience of explanation, in fig. 3, it is not repeatedly confirmed whether all the breakpoint values are completed, but only whether the value of f (x) is smaller than the threshold value 0 is explained, and it can be understood that all the antenna energy allocation value calculations are completed by one processing.
Fig. 4 is a schematic diagram of energy efficiency values obtained by the present invention and the conventional method when the distance between the transceivers varies from 0.1 to 1.5 km under the condition of 1000 monte carlo experiments. To illustrate the performance of the method, assume that there is a multi-user MIMO communication system, where the number of users K is 3, the number of base station antennas N is 6, and the number of antennas of each user is Mk2, K is 1, 2. Each element of the channel state information matrix obeys independent Gaussian distribution of zero mean unit variance, the bandwidth of the system is 10MHz, the noise power is-130 dBm/Hz, and the energy conversion efficiency
Figure BDA0001037037350000081
Fixed loss Pr140dBm for eachThe energy constraints for the user are an upper transmitter power limit of 0.15W and an electromagnetic propagation loss of 128.1+37.61g (d), where d represents the distance between the transceivers in kilometers.
According to the above assumed multi-user MIMO communication system, the energy allocation method of the present invention shown in fig. 3 is performed as follows:
1) in step S301, the transceiving distance d is 0.1 km, and the estimated channel state information matrix of each user is assumed to be:
Figure BDA0001037037350000082
Figure BDA0001037037350000083
Figure BDA0001037037350000084
2) in step S302, the matrix H is divided into1，H2，H3Performing singular value decomposition to generate a subchannel gain value of each user, and obtaining:
γ11＝0.6531，γ12＝0.5958
γ21＝1.9467，γ22＝1.8082
γ31＝1.6445，γ32＝1.0933
3) in step S303, 8 breakpoint values may be calculated:
Figure BDA0001037037350000091
Figure BDA0001037037350000092
Figure BDA0001037037350000093
arranging in descending order to obtain 8 breakpoint values:
μ(1)＝0.5137，μ(2)＝0.5530，
μ(3)＝0.6081，μ(4)＝0.6084，
μ(5)＝0.7581，μ(6)＝1.5311，
μ(7)＝1.6783，μ(8)＝1.6797
4) in step S304, all energy allocation values are initialized to zero, i.e. p11＝p12＝p21＝p22＝p31＝p32＝0；
Initializing a scratch set
Figure BDA0001037037350000094
The counting variable q is set to 1.
5) In step S305, when q is 1,
Figure BDA0001037037350000095
thus, the temporary set E is updated2＝{1}。
6) In step S306, an energy efficiency function is constructed
Figure BDA0001037037350000096
Wherein the values of a, b and c are respectively as follows:
a＝0.9611
b＝-0.1137
c＝1
7) in step S307, f (μ)(2)) Since f (0.5530) is 1.0396 > 0, q is set to 2, and the process returns to step S305.
8) In step S305, when q is 2,
Figure BDA0001037037350000097
thus, the temporary set E is updated2＝{1，2}。
9) In step S306, an energy efficiency function is constructed
Figure BDA0001037037350000098
Wherein the values of a, b and c are respectively as follows:
a＝1.8156
b＝-0.6667
c＝2
10) in step S307, f (μ)(3)) Since f (0.6081) is 1.8465 > 0, q is 3, and the process returns to step S305.
11) In step S305, when q is 3,
Figure BDA0001037037350000101
thus, the temporary set E is updated3＝{1}。
12) In step S306, an energy efficiency function is constructed
Figure BDA0001037037350000102
Wherein the values of a, b and c are respectively as follows:
a＝2.5332
b＝-1.2748
c＝3
13) in step S307, f (μ)(4)) Since f (0.6084) is 2.7681 > 0, q is 4, and the process returns to step S305.
14) In step S305, when q is 4, μ(q)＝0.6084＝μ2Therefore, the update temporary set a ═ {2} and B ═ 1, 3 }.
15) In step S306, an energy efficiency function is constructed
Figure BDA0001037037350000103
Wherein the values of a, b and c are respectively as follows:
a＝1.0992
b＝-0.0581
c＝1
16) in step S307, f (μ)(5)) Since f (0.7581) is 0.6324 > 0, q is 5, and the process returns to step S305.
17) In step S305, when q is 5, μ(q)＝0.7581＝μ3Therefore, the update temporary set a ═ {2, 3} and B ═ 1 }.
18) In step S306, an energy efficiency function is constructed
Figure BDA0001037037350000104
Wherein the values of a, b and c are respectively as follows:
a＝0.6997
b＝0.7000
c＝0
19) in step S307, f (μ)(6)) Since f (1.5311) is 0 ≧ 0, q is 6, and the process returns to step S305.
20) In step S305, when q is 6,
Figure BDA0001037037350000111
thus, the temporary set E is updated1＝{1}。
21) In step S306, an energy efficiency function is constructed
Figure BDA0001037037350000112
Wherein the values of a, b and c are respectively as follows:
a＝0.0851
b＝-0.8311
c＝1
22) in step S307, f (μ)(7)) When f (1.6783) — 0.1038 < 0, step S308 is performed.
23) In step S308, the root of equation f (x) is solved to obtain a root value μ*The final result of the output energy allocation is 1.5311:
p11＝0，p12＝0，
p21＝0.0947，p22＝0.0553，
p31＝0.1500，p32＝0
in the above, it can be seen that steps 5 to 22 are circularly calculated in steps S305 to S307. Through the energy distribution method of the invention, the difference between the advantages and disadvantages of the traditional method can be obviously seen from the curve change in fig. 4, and the distribution scheme for optimizing the energy efficiency of the antenna is realized.
The above description is only exemplary of the present invention and should not be taken as limiting the invention, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (3)

1. An energy allocation method of a zero forcing MIMO communication system is provided, in a multi-user MIMO communication system environment, an energy output result with better energy efficiency is reallocated under the constraint condition of total energy, and the energy allocation method is characterized by comprising the following steps:
s1) obtaining the total user number, the antenna number of each user and the base station channel state information thereof, and constructing an information matrix of each user;
s2) performing singular value decomposition on all information matrices, respectively, to generate a subchannel gain value corresponding to each user;
s3) inputting all subchannel gain values into a breakpoint function to generate complex breakpoint values;
s4) initializing the antenna energy distribution values of all users and establishing a complex temporary storage set;
s5) a breakpoint value is taken out to be compared with all the subchannel gain values in sequence, and the comparison result is updated to the corresponding temporary storage set;
s6) constructing an energy efficiency function according to the values generated in the steps S2-S5;
s7) inputting the breakpoint value as a variable into the energy efficiency function to generate a result value, judging whether the result value is larger than a threshold value, if so, returning to the step S5 until all the breakpoint values are calculated; if the result value is smaller than the threshold value, performing step S8;
s8) extracting the root value of the energy efficiency function, inputting the root value into the energy distribution function to calculate the new antenna energy distribution values of all users and outputting the energy.
2. The method of claim 1, wherein the plurality of temporary sets in step S4 includes a first temporary set, a second temporary set and a third temporary set, respectively A, B and EkAnd (4) showing.
3. The energy distribution method according to claim 1, wherein the threshold value is set to 0 in step S7.
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CN102647259A (en) * 2012-04-07 2012-08-22 西安电子科技大学 Singular value decomposition-based method for uplink transmission of multi-user MIMO (Multiple-Input Multiple-Output) system
CN103997775A (en) * 2014-06-03 2014-08-20 东南大学 Frequency division multiplexing multi-user MIMO energy efficiency optimization method

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