CN107979826A - Power distribution method and device in the DAS to communicate under multiplexer mode containing D2D - Google Patents
Power distribution method and device in the DAS to communicate under multiplexer mode containing D2D Download PDFInfo
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Abstract
The present invention is suitable for base station communication technical field, there is provided power distribution method in the DAS of the communication containing D2D under a kind of multiplexer mode, wherein, it is suitable for optimal power allocation method when maximizing SE：First initialize, the corresponding P of ith iteration is then calculated according to the formula of CCCP algorithms1 (i)；I=i+1 is made, calculates the corresponding P of i+1 time iteration1 (i+1)；If P1 (i+1)With P1 (i)Between 2 norms of difference be less than ξ, then P1 (i+1)As optimal power, and terminate iterative operation；It is suitable for the method for optimal power allocation when maximizing EE：First initialize and the corresponding P of the t times iteration is calculated according to the formula of CCCP algorithms2 (t)；T=t+1 is made, calculates the corresponding P of the t+1 times iteration2 (t+1)；The P that will be calculated2 (t+1)Bring the energy efficiency EE of system after addition D2D communicates intod2dMiddle calculating ω1 (t+1)；If the majorized function h after conversion when meeting to maximize EE1(P2 (t+1),ω1 (t+1)) absolute value be less than ξ, then P2 (i+1)As optimal power, and terminate iterative operation；Method provided by the invention improves the communication quality of communication cell and reduces energy expenditure.
Description
Technical Field
The invention belongs to the technical field of base station communication, and particularly relates to a method and a device for distributing power in a DAS (data-based acquisition) with D2D communication in a multiplexing mode.
Background
With the rapid development of the data age, the rapid increase of communication rate and energy consumption becomes a great challenge for modern wireless communication networks. Due to the natural shortcomings of the Co-located Antenna Systems (CAS), researchers have proposed Distributed Antenna Systems (DAS) in order to meet the growing business demands. The method becomes an effective means for improving the bandwidth of a communication system, meeting the communication quality of a user and reducing the energy consumption in communication. The DAS is different from the conventional CAS in that all base station antennas are dispersed throughout the cell, and thus, it is possible to effectively reduce the distance between the base station and the user, thereby reducing large-scale fading of signals during communication, significantly improving the throughput of the communication cell, and reducing the power consumption required for communication under the same conditions.
Another way of communicating between devices (D2D) is also an effective means to improve the quality of user communication and reduce power consumption. The D2D communication is direct communication between two devices without the help of a base station, which can effectively reduce the load of the base station and greatly improve the communication quality between short-distance users and the energy efficiency of the system.
Most of researches on D2D communication are concentrated in CAS, and a lot of researches show that D2D communication in CAS can effectively improve the capacity of a communication cell and the energy efficiency of the communication cell; however, of the studies, few consider the case of combining DAS and D2D communications.
Disclosure of Invention
The invention provides a method and a device for distributing power in a DAS (data-aided system) containing D2D communication in a multiplexing mode, aiming at adding D2D communication into the DAS, multiplexing channels of cellular users by D2D users for communication, and combining the advantages of the two to improve the communication quality of a communication cell and reduce the energy consumption of the cell.
The invention provides a power distribution method in a DAS (data-aided serving access system) containing D2D communication in a multiplexing mode, which is suitable for optimal power distribution when the spectrum efficiency SE is maximized, wherein the DAS comprises n Remote Access Units (RAUs), and n RAUs are distributed in a communication cell, wherein an RAU1 is positioned in the center of the communication cell, the remaining n-1 RAUs are connected with the RAU1 and are uniformly distributed in the communication cell, the communication cell comprises 1 cellular user UE1, 1 pair of D2D user UE2 and UE3, and 1 pair of D2D user multiplexes the channel of the cellular user for communication, and the power distribution method comprises the following steps:
step S101, initializing the iteration number i in the CCCP algorithm to be 0, and initializing the transmission power of the cellular user and the D2D user
Wherein, a convex set of constraints representing the optimal transmit power for the cellular user and the D2D user at maximum SE;
step S102, calculating the corresponding ith iteration according to the formula of the CCCP algorithm
Step S103, let i equal to i +1, and calculate the i +1 th iteration according to the formula of the CCCP algorithm
Step S104, ifAndthe 2 norm of the difference between is less than ξ, thenThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to the step S102;
where ξ represents a small positive error parameter.
The invention also provides a power allocation device in DAS including D2D communication in a multiplexing mode, where the power allocation method is adapted to optimize power allocation when spectrum efficiency SE is maximized, the DAS includes n remote access units RAUs, n of the RAUs are distributed in a communication cell, where an RAU1 is located in the center of the communication cell, and the remaining n-1 RAUs are connected to the RAU1 and uniformly distributed in the communication cell, and the communication cell includes 1 cellular user UE1 and 1 pair of D2D user UE2 and UE3, and 1 pair of D2D users multiplex channels of the cellular users for communication, and the power allocation device includes:
an initialization module for initializing the iteration number i in CCCP algorithm to 0 and initializing the transmission power of cellular users and D2D users
Wherein, a convex set of constraints representing the optimal transmit power for the cellular user and the D2D user at maximum SE;
a calculating module for calculating the corresponding ith iteration according to the formula of the CCCP algorithm
An iteration module, configured to make i ═ i +1, and calculate, according to the formula of the CCCP algorithm, a value corresponding to the i +1 th iteration
An optimum power acquisition module for use inAndwhen the 2 norm of the difference between the two is less than ξ, the judgment is madeThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to the computing module;
where ξ represents a small positive error parameter.
The invention also provides a power allocation method in a DAS including D2D communication in a multiplexing mode, the power allocation method is suitable for optimal power allocation when energy efficiency EE is maximized, the DAS includes n remote access units RAUs, n RAUs are distributed in a communication cell, wherein an RAU1 is located in the center of the communication cell, the remaining n-1 RAUs are connected to the RAU1 and uniformly distributed in the communication cell, the communication cell includes 1 cellular user UE1 and 1 pair of D2D user UE2 and UE3, the power allocation method includes:
step S201, initializing parametersAnd the number of iterations t in the CCCP algorithm is 0, and the transmit powers of the cellular user and the D2D user are initialized
Wherein, a convex set of constraints representing the optimal transmit power for cellular and D2D users at maximum EE;
step S202, calculating the corresponding t iteration according to the formula of the CCCP algorithm
Step S203, let t be t +1, and calculate the corresponding iteration of the t +1 th iteration according to the formula of the CCCP algorithm
Step S204, calculating the calculatedEnergy efficiency EE for systems after bringing in add-on D2D communicationd2dMiddle calculation
Step S205, the transformed optimization function if the maximum EE is satisfiedIs less than ξ, thenThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to step S202;
where ξ represents a small positive error parameter.
The invention also provides a power distribution device in the DAS including D2D communication in the multiplexing mode, wherein the power distribution method is suitable for optimal power distribution when energy efficiency EE is maximized, the DAS includes n remote access units RAUs, n RAUs are distributed in a communication cell, wherein, RAU1 is located at the center of the communication cell, the remaining n-1 RAUs are connected with RAU1 and are uniformly distributed in the communication cell, the communication cell includes 1 cellular user UE1 and 1 pair of D2D user UE2 and UE3, the power distribution method includes:
an initialization module for initializing parametersAnd the number of iterations t in the CCCP algorithm is 0, and the transmit powers of the cellular user and the D2D user are initialized
Wherein, a convex set of constraints representing the optimal transmit power for cellular and D2D users at maximum EE;
a first calculating module, configured to calculate a value corresponding to the t-th iteration according to a formula of the CCCP algorithm
An iteration module, configured to make t equal to t +1, and calculate a value corresponding to the t +1 th iteration according to the formula of the CCCP algorithm
A second calculation module for calculating the calculatedEnergy efficiency EE for systems after bringing in add-on D2D communicationd2dMiddle calculation
An optimum power acquisition module for post-conversion optimization when maximizing EE is satisfiedIs less than ξ, it is determined thatThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to the first computing module;
where ξ represents a small positive error parameter.
Compared with the prior art, the invention has the beneficial effects that: the invention provides a power distribution method and a device in DAS (data-aided distributed system) containing D2D communication in a multiplexing mode, in particular to an optimal power distribution method suitable for maximizing spectrum efficiency and maximizing energy efficiency.
Drawings
Fig. 1 is a schematic diagram of a model of a distributed antenna system DAS provided in the prior art;
fig. 2 is a schematic flowchart of a power allocation method in a DAS with D2D communication in a multiplexing mode according to an embodiment of the present invention;
fig. 3 is a schematic block diagram of a power distribution apparatus in a DAS including D2D communication in a multiplexing mode according to an embodiment of the present invention;
fig. 4 is a schematic flowchart of a power allocation method in a DAS with D2D communication in a multiplexing mode according to an embodiment of the present invention;
fig. 5 is a schematic block diagram of a power distribution apparatus in a DAS including D2D communication in a multiplexing mode according to an embodiment of the present invention;
FIG. 6 is a graph illustrating the variation of the average SE with the variation of the maximum transmission power in different power allocation algorithms according to an embodiment of the present invention;
fig. 7 is a graph illustrating the variation of the average EE with the variation of the maximum transmission power in different power allocation algorithms according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a power distribution method in a DAS (Distributed Antenna system) including D2D communication in a multiplexing mode, wherein a model of the DAS is shown in fig. 1, specifically, a single cell is considered in the invention, the DAS includes n Remote Access Units (RAUs) that are Distributed in the communication cell, wherein an RAU1 is located at the center of the communication cell and can be regarded as a central processing unit, the remaining n-1 RAUs are connected with the RAU1 through optical fibers and are uniformly Distributed in the communication cell, and all RAUs are single Antenna Base Stations (BS) with low power consumption. The communication cell includes 1 cellular User UE1(User Equipment, UE1) and 1 pair of D2D users UE2 and UE 3.
We assume that the D2D user multiplexes the channels of the cellular users for communication and that the channel information is known to both ends of the communication. The bandwidth of the system is set to 1, and the transmission rate of the cellular user is:
wherein p isn,1Denotes the transmit power, h, of the nth RAU to the UE1n,1Which represents the transmission channel between the two,representing the complex white Gaussian noise power, p, of a cellular userdRepresents the transmit power, h, of the sender UE2 in the D2D pair2,1Representing the transport channel between the sender UE2 and the cellular user UE1 in pair D2D.
Similarly, the transmission rate of the D2D pair can be expressed as:
wherein h is2,3Representing the transmission channel between two users in the D2D pair,complex white gaussian noise power, h, representing D2D usern,3Represents a transmission channel between the receiver UE3 of the nth RAU to D2D pair. The fading channel contains a small scale and a large scale fading and can be expressed as:
hn,1＝gn,1wn,1(3)
wherein, gn,1Representing small scale fading between different RAUs to the UE1, can be attributed to independent identically distributed complex gaussian random variables. w is an,1Is independent of gn,1Large scale fading, which can be expressed as:
where c is the average path gain at a reference distance of 1 km. dn,1Representing the distance between the RAU and the UE1 α is a path fading factor, typically ranging from [3,5 ]]。sn,1Is a lognormal distributed fading variable, i.e. 10log10sn,1Has a mean value of 0 and a standard deviation of σsh。
The following is specifically introduced in terms of power optimization for maximizing system SE (Spectral Efficiency) and maximizing system EE (Energy Efficiency):
regarding the optimal power allocation at maximum SE for DAS adding D2D communication in multiplexing mode:
considering the optimal power allocation under the maximum SE in the DAS adding D2D communication, the maximum SE should meet the minimum SE of the system and the requirement of D2D on the minimum SE, the maximum transmit power limits of cellular users and D2D users. The problem can be described as:
wherein, Pc＝{pn,1,n＝1,2,…,N}， Representing the maximum transmit power of the sender UE2 in the UE1 and D2D pairs, respectively. Representing the minimum transmission rates of the cellular user and the D2D user.
In reuse mode, the D2D pair communicates by reusing the frequencies of the cellular users, so the problem of maximizing system SE can be summarized as equation (5). We can see that the problem cannot be solved directly. Therefore, the problem is converted into a special optimization problem of D.C. (difference of the functions) structure by adjusting the form of the problem; we can then solve using an efficient optimization algorithm based on d.c. planning.
Definition P1＝[Pc,pd]，f(P1) As an optimization variable and objective function, equation (5) can be converted into:
wherein:
as can be seen from the expressions (7) and (8), are strictly convex and concave functions, wherein,representing the transformed convex function of the optimal transmit power problem at maximum SE for cellular and D2D users,represents the concave function transformed from the optimal transmit power problem at maximum SE for cellular users and D2D users. In addition, defineFor the set of constraints in equation (5), since the first and third constraints are not linear, we can convert them into the following linear conditions:
thus, setIs a convex set.
From the above discussion, the problem (5) can be transformed into the following optimization problem:
the problem (11) can be solved using the simplified algorithm cccp (convoveconjvexprocedure) algorithm of DCA (d.c. algorithm), which iterates on a convex part of the object function mainly using the mm (orientation minimization) method d.c.
We know that the concave function part of equation (11) has partial derivatives, so we can expand by first-order TaylorThe following iterative expression is obtained:
wherein,represents P1I is the number of iterations,to representAt the point ofThe gradient of (a). From the above analysis we can conclude that the optimal power algorithm for maximizing SE in DAS with D2D communication added is as follows:
regarding a power allocation method in DAS including D2D communication in multiplexing mode, the power allocation method is suitable for optimal power allocation when spectrum efficiency SE is maximized, as shown in fig. 2, and includes:
step S101, initializing the iteration number i in the CCCP algorithm to be 0, and initializing the transmission power of the cellular user and the D2D user
Wherein, a convex set of constraints representing the optimal transmit power for the cellular user and the D2D user at maximum SE;
step S102, calculating the corresponding ith iteration according to the formula of the CCCP algorithm
Specifically, the formula (12) is a formula of the CCCP algorithm, wherein,representing the transmit power of the cellular user and the D2D user,a convex set of constraints representing the optimal transmit power for the cellular user and the D2D user at maximum SE.
Specifically, the step S102 includes:
s1021, obtaining a searching direction of optimal power distribution corresponding to the formula of the CCCP algorithm by using a quasi-Newton method, and obtaining an optimal step length of each step of searching through a linear feedback searching Armijo rule;
s1022, solving the formula of the CCCP algorithm by combining the search direction and the optimal step length and combining an interior point method to obtain the formula corresponding to the ith iteration
Step S103, let i equal to i +1, and calculate the i +1 th iteration according to the formula of the CCCP algorithm
Step S104, ifAndthe 2 norm of the difference between is less than ξ, thenThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to the step S102;
where ξ represents a small positive error parameter.
In particular, ifThe iterative calculation is continued to return to the step S102 until the condition is metAndwhen the 2 norm of the difference between the two is less than ξ, the iterative operation is ended.
The invention provides a power distribution device in a DAS (data acquisition system) with D2D communication in a multiplexing mode, which is suitable for optimal power distribution when the spectrum efficiency SE is maximized, as shown in fig. 3, and comprises:
an initialization module 301, configured to initialize the number of iterations i-0 in the CCCP algorithm, and initialize the transmission power of the cellular user and the D2D user
Wherein, a convex set of constraints representing the optimal transmit power for the cellular user and the D2D user at maximum SE;
a calculating module 302, configured to calculate a value corresponding to the ith iteration according to a formula of the CCCP algorithm
An iteration module 303, configured to make i ═ i +1, and calculate, according to the formula of the CCCP algorithm, a value corresponding to the i +1 th iteration
An optimum power obtaining module 304 for obtaining the optimum powerAndwhen the 2 norm of the difference between the two is less than ξ, the judgment is madeThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to the computing module;
where ξ represents a small positive error parameter.
With regard to the EE model:
according to the known research, the total power consumption P of the systemtotalConsists of three parts, which can be expressed as:
where τ denotes the efficiency of the radio frequency power amplifier, Φ denotes the number of transmitting data users in the system, and when UE2 and UE3 communicate as a D2D pair, Φ is N + 1; when they use conventional cellular communications, phi is N, PdyAnd PstRespectively representing dynamic and static power losses, P0Represents the power consumed by the fiber transmission; after joining the D2D communication, the total transmission power P of the system is expressed as:
the total transmission power P of the system when the D2D user UE2 and UE3 communicate conventionally is expressed as:
the expression of the EE model from the above analysis can be found as follows:
when the UE2 and UE3 communication employ D2D communication, RtotalExpressed as equation (5), and the transmission power is expressed as Pd2d(ii) a When they use conventional cellular communications, the transmission power is denoted as Pcellular。
Regarding the optimal power allocation at maximum EE for DAS adding D2D communication in multiplexing mode:
considering the problem of optimal power allocation when EE is maximized in a downlink DAS with D2D added for communication, the minimum transmission rate and the maximum transmission power requirements of UE1 and UE2 (the transmitting end in the D2D pair) should be met, and the optimization problem can be described as follows:
wherein, P2＝[Pc,pd]Representing the optimization variables, EEd2dRepresenting the energy efficiency of the system after adding D2D communication.
Since (17) is a non-concave nonlinear optimization problem, we cannot directly find the optimal solution by using the traditional optimization method, so the optimization problem is converted into a subtractive optimization problem by using the related theory of fractional programming:
wherein,
according to the related research, the problem (17) always has an optimization problem (18) in the form of an equivalent subtraction, and the equivalence relation between the expressions (17) and (18) is expressed by the following theorem.
Definition of (theorem)If and only ifAndoptimum power of timeEE in the formula (17) can be maximized.
Therefore, according to the above theorem, we can focus on solving their equivalence problem to get the optimal power distribution, but equation (18) is still a non-convex optimization problem, and we can convert it into an optimization problem of d.c. structure; the object function can be converted into the following form:
wherein the convex and concave parts of the object function can be expressed as:
wherein,represents the concave function transformed from the optimum transmit power problem for cellular users and D2D users at maximum EE,defining a transformed convex function representing the optimum transmit power problem for cellular and D2D users at maximum EEFor the set of constraints in equation (19), it can be easily seenIs a convex set. Upper convex partAlso, there is a partial derivative, so we can use the CCCP algorithm to obtain the iterative formula as follows:
wherein,is P2Is used, t is the number of iterations,to representAt the point ofThe gradient of (a).
From the above analysis, we can conclude that the optimal power algorithm for maximizing EE in DAS with D2D communication added is as follows:
as shown in fig. 4, a method for allocating power in a DAS having D2D communication in a multiplexing mode includes:
step S201, initializing parametersAnd the number of iterations t in the CCCP algorithm is 0, and the transmit powers of the cellular user and the D2D user are initialized
Wherein, a convex set of constraints representing the optimal transmit power for cellular and D2D users at maximum EE;
step S202, calculating the corresponding t iteration according to the formula of the CCCP algorithm
Specifically, the above equation (22) is the CCCP algorithm, wherein,representing the transmit power of the cellular user and the D2D user,a convex set of constraints representing the optimum transmit power for maximizing EE for both cellular and D2D users.
Specifically, the step S202 includes:
s2021, obtaining a search direction of optimal power distribution corresponding to a formula of the CCCP algorithm by using a quasi-Newton method, and obtaining an optimal step length of each step of search by linear feedback search Armijo rules;
s2022, solving the formula of the CCCP algorithm by combining the search direction and the optimal step length and combining an inner point method to obtain a formula corresponding to the t-th iteration
Step S203, let t be t +1, and calculate the corresponding iteration of the t +1 th iteration according to the formula of the CCCP algorithm
Step S204, calculating the calculatedEnergy efficiency EE for systems after bringing in add-on D2D communicationd2dMiddle calculation
In particular, using the equationCalculate outAnd EEd2dThe expression of (c) is given in the foregoing analysis and can be calculated based on the expression given in the foregoing analysis.
Step S205, the transformed optimization function if the maximum EE is satisfiedIs less than ξ, thenThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to step S202;
where ξ represents a small positive error parameter.
In particular, ifThe iterative calculation is continued to return to the step S202 until the condition is satisfiedWhen the iteration operation is finished, the iteration operation is ended; in addition, the optimization function h after transformation1The expression of (c) is given in the foregoing analysis and can be calculated based on the expression given in the foregoing analysis.
The invention provides a power distribution device in DAS (data area system) with D2D communication in a multiplexing mode, which is suitable for optimal power distribution when energy efficiency EE is maximized, as shown in fig. 5, and comprises:
an initialization module 401 for initializing parametersAnd the number of iterations t in the CCCP algorithm is 0, and the transmit powers of the cellular user and the D2D user are initialized
Wherein, a convex set of constraints representing the optimal transmit power for cellular and D2D users at maximum EE;
the first calculation module (402) is a module,for calculating the corresponding t-th iteration according to the formula of the CCCP algorithm
An iteration module 403, configured to make t equal to t +1, and calculate a value corresponding to the t +1 th iteration according to the formula of the CCCP algorithm
A second calculation module 404 for calculating the calculatedEnergy efficiency EE for systems after bringing in add-on D2D communicationd2dMiddle calculation
An optimum power acquisition module 405 for a transformed optimization function when maximizing EE is satisfiedIs less than ξ, it is determined thatThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to the first computing module;
where ξ represents a small positive error parameter.
The embodiment of the invention verifies the effectiveness of the algorithm through a simulation experiment, and simultaneously shows that the SE and EE of the communication cell can be greatly improved by combining D2D communication and DAS, and the specific simulation parameters are as follows:
the change in average SE with the change in maximum transmit power is shown in fig. 6, and it can be readily seen that the average SE in a DAS with added D2D communication is much better than a single DAS.
For example, maximizing SE in a DAS with added D2D communication resulted in an approximately 25% improvement over the average SE obtained for a single DAS under the same algorithm when the maximum transmit power was 30 dBm; moreover, the average SE of a single DAS gradually increases slowly as the maximum transmit power becomes higher, while the average SE of a DAS containing D2D communication still increases very quickly, which is a good indication that adding D2D to a large DAS can effectively increase the communication cell SE.
The variation in average EE with variation in maximum transmit power is shown in fig. 7, which shows that the average EE in DAS with added D2D communication is much higher than for DAS alone.
For example, using maximized EE in a DAS with added D2D communication resulted in approximately 18% improvement over the average EE obtained for a single DAS under the same algorithm when the maximum transmit power was 15 dBm. In DAS with added D2D communication, the average EE starts to decrease as the maximum transmit power increases, but it is still higher than a single DAS.
As can be seen from fig. 6 and 7, after D2D communication is added to the DAS, the average SE and EE of the system are better than those of a single DAS, which indicates that adding D2D communication to the DAS is an effective means for improving SE and EE of the communication cell.
According to the method and the device for power distribution in the DAS with D2D communication in the multiplexing mode, D2D communication is considered in the DAS, the frequency of cellular users is multiplexed when D2D users communicate, the utilization rate of system frequency is improved, SE and EE of the system are analyzed in the multiplexing mode, average SE and EE under the system are respectively obtained and maximized, and meanwhile, the effectiveness of theoretical analysis is verified through experiments; meanwhile, the D2D communication is combined with the DAS, so that the advantages of the D2D communication and the DAS can be fully exerted, the communication quality of a communication cell can be greatly improved, the energy consumption of the cell can be reduced, the energy saving and the user communication quality improvement are greatly facilitated, and the distribution method provided by the invention can be applied to 5G communication.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A power allocation method in a DAS including D2D communication in a reuse mode, wherein the power allocation method is adapted to optimize power allocation when spectrum efficiency SE is maximized, the DAS includes n remote access units RAUs, and n RAUs are distributed in a communication cell, where a RAU1 is located at the center of the communication cell, and the remaining n-1 RAUs are connected to the RAU1 and uniformly distributed in the communication cell, and the communication cell includes 1 cellular user UE1 and 1 pair of D2D user UE2 and UE3, and 1 pair of D2D users reuse channels of the cellular users for communication, and the power allocation method includes:
step S101, initializing the iteration number i in the CCCP algorithm to be 0, and initializing the transmission power of the cellular user and the D2D user
Wherein, a convex set of constraints representing the optimal transmit power for the cellular user and the D2D user at maximum SE;
step S102, calculating the corresponding ith iteration according to the formula of the CCCP algorithm
Step S103, let i equal to i +1, and calculate the i +1 th iteration according to the formula of the CCCP algorithm
Step S104, ifAndthe 2 norm of the difference between is less than ξ, thenThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to the step S102;
where ξ represents a small positive error parameter.
2. The method for allocating power in a DAS of claim 1, wherein the CCCP algorithm has a formula:
<mrow> <msubsup> <mi>P</mi> <mn>1</mn> <mrow> <mo>(</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> </msubsup> <mo>=</mo> <munder> <mi>argmax</mi> <mrow> <msub> <mi>P</mi> <mn>1</mn> </msub> <mo>&Element;</mo> <msubsup> <mi>C</mi> <mi>R</mi> <mn>1</mn> </msubsup> </mrow> </munder> <mrow> <mo>(</mo> <msubsup> <mi>f</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>n</mi> <mi>c</mi> <mi>a</mi> <mi>v</mi> <mi>e</mi> </mrow> <mrow> <mi>d</mi> <mn>2</mn> <mi>d</mi> </mrow> </msubsup> <mo>(</mo> <msub> <mi>P</mi> <mn>1</mn> </msub> <mo>)</mo> <mo>+</mo> <mo>&dtri;</mo> <msubsup> <mi>f</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>n</mi> <mi>v</mi> <mi>e</mi> <mi>x</mi> </mrow> <mrow> <mi>d</mi> <mn>2</mn> <mi>d</mi> </mrow> </msubsup> <mo>(</mo> <msubsup> <mi>P</mi> <mn>1</mn> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> <mo>*</mo> <msubsup> <mi>P</mi> <mn>1</mn> <mi>T</mi> </msubsup> <mo>)</mo> </mrow> </mrow>
wherein,representing the transmit power of the cellular user and the D2D user, i isNumber of iterations, P1＝[Pc,pd]，Pc＝{pn,1,n＝1,2,…,N}，pn,1Denotes the transmit power, p, of the nth RAU to the UE1dRepresents the maximum transmit power of the sender UE2 in the D2D pair,a convex set of constraints representing the optimal transmit power for the cellular user and the D2D user at maximum SE,represents the concave function transformed from the optimal transmit power problem at maximum SE for cellular users and D2D users,to representAt the point ofThe gradient of (a) is measured,representing the transformed convex function of the optimal transmit power problem at maximum SE for cellular and D2D users,represents P1The transposing of (1).
3. The method for allocating power in a DAS according to claim 1, wherein the step S102 specifically includes:
s1021, obtaining a searching direction of optimal power distribution corresponding to the formula of the CCCP algorithm by using a quasi-Newton method, and obtaining an optimal step length of each step of searching through a linear feedback searching Armijo rule;
s1022, solving the formula of the CCCP algorithm by combining the search direction and the optimal step length and combining an interior point method to obtain the formula corresponding to the ith iteration
4. A power allocation apparatus in a DAS including D2D communication in a multiplexing mode, wherein the power allocation method is adapted to optimize power allocation when spectrum efficiency SE is maximized, the DAS includes n remote access units RAUs, n of the RAUs are distributed in a communication cell, wherein a RAU1 is located at the center of the communication cell, and the remaining n-1 RAUs are connected to the RAU1 and uniformly distributed in the communication cell, and the communication cell includes 1 UE1 and 1 pair of UEs 2 and 3 of D2D, and 1 pair of UEs 3 multiplexing channels of the D2D users for communication, and the power allocation apparatus includes:
an initialization module for initializing the iteration number i in CCCP algorithm to 0 and initializing the transmission power of cellular users and D2D users
Wherein, a convex set of constraints representing the optimal transmit power for the cellular user and the D2D user at maximum SE;
a calculating module for calculating the corresponding ith iteration according to the formula of the CCCP algorithm
An iteration module, configured to make i ═ i +1, and calculate, according to the formula of the CCCP algorithm, a value corresponding to the i +1 th iteration
An optimum power acquisition module for use inAndwhen the 2 norm of the difference between the two is less than ξ, the judgment is madeThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to the computing module;
where ξ represents a small positive error parameter.
5. The apparatus for allocating power in a DAS of claim 4, wherein the CCCP algorithm has the formula:
<mrow> <msubsup> <mi>P</mi> <mn>1</mn> <mrow> <mo>(</mo> <mi>i</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> </msubsup> <mo>=</mo> <munder> <mi>argmax</mi> <mrow> <msub> <mi>P</mi> <mn>1</mn> </msub> <mo>&Element;</mo> <msubsup> <mi>C</mi> <mi>R</mi> <mn>1</mn> </msubsup> </mrow> </munder> <mrow> <mo>(</mo> <msubsup> <mi>f</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>n</mi> <mi>c</mi> <mi>a</mi> <mi>v</mi> <mi>e</mi> </mrow> <mrow> <mi>d</mi> <mn>2</mn> <mi>d</mi> </mrow> </msubsup> <mo>(</mo> <msub> <mi>P</mi> <mn>1</mn> </msub> <mo>)</mo> <mo>+</mo> <mo>&dtri;</mo> <msubsup> <mi>f</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>n</mi> <mi>v</mi> <mi>e</mi> <mi>x</mi> </mrow> <mrow> <mi>d</mi> <mn>2</mn> <mi>d</mi> </mrow> </msubsup> <mo>(</mo> <msubsup> <mi>P</mi> <mn>1</mn> <mrow> <mo>(</mo> <mi>i</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> <mo>*</mo> <msubsup> <mi>P</mi> <mn>1</mn> <mi>T</mi> </msubsup> <mo>)</mo> </mrow> </mrow>
wherein,representing the transmit power of the cellular user and the D2D user, i being the number of iterations, P1＝[Pc,pd]，Pc＝{pn,1,n＝1,2,…,N}，pn,1Denotes the transmit power, p, of the nth RAU to the UE1dRepresents the maximum transmit power of the sender UE2 in the D2D pair,a convex set of constraints representing the optimal transmit power for the cellular user and the D2D user at maximum SE,represents the concave function transformed from the optimal transmit power problem at maximum SE for cellular users and D2D users,to representAt the point ofThe gradient of (a) is measured,representing the transformed convex function of the optimal transmit power problem at maximum SE for cellular and D2D users,represents P1The transposing of (1).
6. A power allocation method in DAS with D2D communication in multiplexing mode, wherein the power allocation method is adapted to optimize power allocation when energy efficiency EE is maximized, the DAS includes n remote access units RAUs, and n RAUs are distributed in a communication cell, wherein RAU1 is located at the center of the communication cell, and the remaining n-1 RAUs are connected to RAU1 and uniformly distributed in the communication cell, and the communication cell includes 1 cellular user UE1 and 1 pair of D2D user UE2 and UE3, the power allocation method includes:
step S201, initializing parametersAnd the number of iterations t in the CCCP algorithm is 0, and the transmit powers of the cellular user and the D2D user are initialized
Wherein, a convex set of constraints representing the optimal transmit power for cellular and D2D users at maximum EE;
step S202, calculating the second step according to the formula of the CCCP algorithmCorresponding to t iterations
Step S203, let t be t +1, and calculate the corresponding iteration of the t +1 th iteration according to the formula of the CCCP algorithm
Step S204, calculating the calculatedEnergy efficiency EE for systems after bringing in add-on D2D communicationd2dMiddle calculation
Step S205, the transformed optimization function if the maximum EE is satisfiedIs less than ξ, thenThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to step S202;
where ξ represents a small positive error parameter.
7. The method for allocating power in a DAS of claim 6, wherein the CCCP algorithm has the formula:
<mrow> <msubsup> <mi>P</mi> <mn>2</mn> <mrow> <mo>(</mo> <mi>t</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> </msubsup> <mo>=</mo> <munder> <mi>argmax</mi> <mrow> <msub> <mi>P</mi> <mn>2</mn> </msub> <mo>&Element;</mo> <msubsup> <mi>C</mi> <mi>R</mi> <mn>2</mn> </msubsup> </mrow> </munder> <mrow> <mo>(</mo> <msubsup> <mi>f</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>n</mi> <mi>c</mi> <mi>a</mi> <mi>v</mi> <mi>e</mi> </mrow> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msubsup> <mo>(</mo> <msub> <mi>P</mi> <mn>2</mn> </msub> <mo>)</mo> <mo>+</mo> <mo>&dtri;</mo> <msubsup> <mi>f</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>n</mi> <mi>v</mi> <mi>e</mi> <mi>x</mi> </mrow> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msubsup> <mo>(</mo> <msubsup> <mi>P</mi> <mn>2</mn> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> <mo>*</mo> <msubsup> <mi>P</mi> <mn>2</mn> <mi>T</mi> </msubsup> <mo>)</mo> </mrow> </mrow>
wherein,representing the transmit power of the cellular user and the D2D user, t being the number of iterations, P2＝[Pc,pd]Representing an optimization variable, Pc＝{pn,1,n＝1,2,…,N}，pn,1Denotes the transmit power, p, of the nth RAU to the UE1dRepresents the maximum transmit power of the sender UE2 in the D2D pair,a convex set of constraints representing the optimum transmit power for maximizing EE for both cellular and D2D users,represents the concave function transformed from the optimum transmit power problem for cellular users and D2D users at maximum EE,to representAt the point ofThe gradient of (a) is measured,represents the transformed convex function of the optimal transmit power problem for cellular users and D2D users at maximum EE,represents P2The transposing of (1).
8. The method for allocating power in a DAS according to claim 6, wherein the step S202 specifically includes:
s2021, obtaining a search direction of optimal power distribution corresponding to a formula of the CCCP algorithm by using a quasi-Newton method, and obtaining an optimal step length of each step of search by linear feedback search Armijo rules;
s2022, solving the formula of the CCCP algorithm by combining the search direction and the optimal step length and combining an inner point method to obtain a formula corresponding to the t-th iteration
9. A power distribution apparatus in DAS with D2D communication in multiplexing mode, wherein the power distribution method is adapted to maximize optimal power distribution when energy efficiency EE is maximized, the DAS includes n remote access units RAUs, and n RAUs are distributed in a communication cell, wherein RAU1 is located at the center of the communication cell, and the remaining n-1 RAUs are connected to RAU1 and uniformly distributed in the communication cell, and the communication cell includes 1 cellular user UE1 and 1 pair of D2D user UE2 and UE3, and the power distribution method includes:
an initialization module for initializing parametersAnd the number of iterations t in the CCCP algorithm is 0, and the transmit powers of the cellular user and the D2D user are initialized
Wherein, a convex set of constraints representing the optimal transmit power for cellular and D2D users at maximum EE;
a first calculating module, configured to calculate a value corresponding to the t-th iteration according to a formula of the CCCP algorithm
An iteration module, configured to make t equal to t +1, and calculate a value corresponding to the t +1 th iteration according to the formula of the CCCP algorithm
A second calculation module for calculating the calculatedEnergy efficiency EE for systems after bringing in add-on D2D communicationd2dMiddle calculation
An optimum power acquisition module for post-conversion optimization when maximizing EE is satisfiedIs less than ξ, it is determined thatThe optimal power is obtained, and the iteration operation is ended; otherwise, returning to the first computing module;
where ξ represents a small positive error parameter.
10. The device for allocating power in a DAS of claim 8, wherein the CCCP algorithm has the formula:
<mrow> <msubsup> <mi>P</mi> <mn>2</mn> <mrow> <mo>(</mo> <mi>t</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> </msubsup> <mo>=</mo> <munder> <mi>argmax</mi> <mrow> <msub> <mi>P</mi> <mn>2</mn> </msub> <mo>&Element;</mo> <msubsup> <mi>C</mi> <mi>R</mi> <mn>2</mn> </msubsup> </mrow> </munder> <mrow> <mo>(</mo> <msubsup> <mi>f</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>n</mi> <mi>c</mi> <mi>a</mi> <mi>v</mi> <mi>e</mi> </mrow> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msubsup> <mo>(</mo> <msub> <mi>P</mi> <mn>2</mn> </msub> <mo>)</mo> <mo>+</mo> <mo>&dtri;</mo> <msubsup> <mi>f</mi> <mrow> <mi>c</mi> <mi>o</mi> <mi>n</mi> <mi>v</mi> <mi>e</mi> <mi>x</mi> </mrow> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msubsup> <mo>(</mo> <msubsup> <mi>P</mi> <mn>2</mn> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </msubsup> <mo>)</mo> <mo>*</mo> <msubsup> <mi>P</mi> <mn>2</mn> <mi>T</mi> </msubsup> <mo>)</mo> </mrow> </mrow>
wherein,representing the transmit power of the cellular user and the D2D user, t being the number of iterations, P2＝[Pc,pd]Representing an optimization variable, Pc＝{pn,1,n＝1,2,…,N}，pn,1Denotes the transmit power, p, of the nth RAU to the UE1dRepresents the maximum transmit power of the sender UE2 in the D2D pair,a convex set of constraints representing the optimum transmit power for maximizing EE for both cellular and D2D users,represents the concave function transformed from the optimum transmit power problem for cellular users and D2D users at maximum EE,to representAt the point ofThe gradient of (a) is measured,represents the transformed convex function of the optimal transmit power problem for cellular users and D2D users at maximum EE,represents P2The transposing of (1).
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