KR102280903B1 - Joint Resource Allocation Apparatus and method for Multi-User OFDMA SWIPT Systems - Google Patents

Abstract

The present technology discloses an apparatus and method for an integrated resource allocation of an OFDMA SWIPT system. According to a specific example of the present invention, by deriving the optimal Lagrangian variable of the base station and the optimal Lagrangian variable of the user terminal with the integrated optimization algorithm for channel allocation, power allocation of the base station and user, and the power split ratio, the channel capacity of the system is It can be maximized and thus the system performance can be improved.

Description

Joint Resource Allocation Apparatus and method for Multi-User OFDMA SWIPT Systems

The present invention relates to an apparatus and method for allocating integrated resources of a SWIPT system, and more particularly, to an integrated optimization algorithm for channel allocation, power allocation of a base station and a user, and an optimal Lagrangian variable of a base station and an optimum of a user terminal The present invention relates to a technique capable of maximizing a channel capacity of a system by deriving a Lagrangian variable and thereby improving system performance.

In wireless communication, a relay is considered a promising solution to expand the communication area of a cellular network and improve performance.

As a relay node, sometimes inactive customer terminals can be used. In this case, the customer terminal selected to operate as a relay node consumes its own power for communication between one base station and a plurality of users. Therefore, we want to provide a stable and continuous power supply.

Accordingly, in a wireless powered communication network (WPCN), it may be charged by wireless powered transfer (WPT). Excluding periodic battery replacement or recharging at the wireless communication node, WPCN can improve device lifespan, reduce network energy consumption, and consequently achieve higher performance than conventional wireless communication networks.

In WPCN, a technology in which a wireless communication node simultaneously transmits power and information is called simultaneous wireless information and power transfer (SWIPT). Research and development are underway to implement WPCN, WPT and SWIPT systems and to exploit the potential benefits of these systems.

Y. Jing and H. Jafarkhani, “Network beamforming using relays with perfect channel information,” IEEE Transactions on Infromation Theory, vol. 55, pp. In 2499-2517, June 2009., beamforming in a multi-relay system other than the SWIPT system was started. By adjusting the transmission power at each relay node based on channel state information (CSI) and noise power, the signal-to-noise ratio (SNR) at the destination node is maximized.

In Korean Patent Registration No. 10-1710012, "Energy harvesting method in a receiver and a receiver using the method, and a method and apparatus for detecting a blind modulation method therefor", energy harvesting (EH) in a receiver of a SWIPT system ) method was disclosed.

However, additional research is needed to decode information and harvest energy into one RF signal in a SWIPT (Simultaneous wireless information and power transfer) system of an orthogonal frequency division multiple access (OFDMA) method with increased bandwidth efficiency. .

Accordingly, in one embodiment, the channel capacity of the system can be maximized by deriving the optimal Lagrangian variable of the base station and the optimal Lagrangian variable of the user terminal with an integrated optimization algorithm for channel allocation, power allocation of the base station and user, and the power split ratio. An object of the present invention is to provide an apparatus and method for allocating integrated resources of an OFDMA SWIPT system capable of improving system performance.

According to an aspect of an embodiment, the method for allocating integrated resources of the OFDMA SWIPT system of an embodiment is

In the integrated resource allocation method of the OFDMA SWIPT system for receiving the RF signal of the base station from a plurality of user terminals and then beamforming information and power at the same time,

It is provided to include an integrated optimization step of deriving an optimal Lagrangian variable of a base station and an optimal Lagrangian variable of a user terminal with an integrated optimization algorithm for channel allocation to the base station, power allocation of the base station and user, and power split ratio do.

Preferably, the integrated optimization step is

및

, 기지국에서의 라그랑지안 변수

, 유저 단말에서의 라그랑지안 변수

, 및 전력분할비율

은 모두 초기화되고, 전력분할비율

는 0과 1 사이의 랜덤하게 설정한 다음 라그랑지안 곱수를 사용하여 설정된 채널 할당 문제의 해로 채널 할당 변수

를 도출하는 단계;(a) Downlink and Uplink Power Allocation

and

, the Lagrangian variable at the base station

, Lagrangian variables in the user terminal

, and power split ratio

are all initialized, and the power split ratio

is set randomly between 0 and 1, then the channel assignment variable as a solution to the set channel assignment problem using a Lagrangian multiplier.

deriving;

,

, 하베스트 에너지 총량

및 서브그래디언드 d 를 연산하는 단계;(b) Downlink and Uplink Power Allocation

,

, the total amount of harvested energy

and calculating a subgradient d;

를 도출하고 도출된 기지국에서의 라그랑지안 변수

로 이전 기지국에서의 라그랑지안 변수

를 업데이트하고, 라그랑지안 변수

로 이전 기지국에서의 라그랑지안 변수

의 차가 기 정해진 임계치에 수렴할 때까지 반복 수행하여 기지국에서의 최적 라그랑지안 변수

를 도출하는 단계; 및(c) Lagrangian variables in the base station by performing binary optimization using the derived subgradient d

and Lagrangian variables in the derived base station

Lagrangian variables in the previous base station as

update the Lagrangian variable

Lagrangian variables in the previous base station as

The optimal Lagrangian variable in the base station is repeated until the difference of

deriving; and

를 도출하고, 도출된

를 전력분할비율

로 업데이트하고,

이 기 정해진 임계치 accuracy로 수렴할 때까지 반복 수행하여 최적 전력분할비율

을 도출하는 단계 중 적어도 하나를 포함하는 것을 일 특징으로 한다.(d) Power split ratio using the gradient descent method

derived and derived

power split ratio

update to

The optimal power split ratio is repeated until convergence to this predetermined threshold accuracy.

It is characterized in that it includes at least one of the steps of deriving .

According to another aspect of an embodiment, the apparatus for allocating integrated resources of the OFDMA SWIPT system of an embodiment,

In the integrated resource allocation apparatus of the OFDMA SWIPT system for receiving the RF signal of the base station from a plurality of user terminals and then beamforming information and power at the same time,

A control unit for deriving an optimal Lagrangian variable of a base station and an optimal Lagrangian variable of a user terminal with an integrated optimization algorithm for channel allocation to the base station, power allocation of the base station and user, and power split ratio,

및

, 기지국에서의 라그랑지안 변수

, 유저 단말에서의 라그랑지안 변수

, 및 전력분할비율

은 모두 초기화되고, 전력분할비율

는 0과 1 사이의 랜덤하게 설정한 다음 라그랑지안 곱수를 사용하여 설정된 채널 할당 문제의 해로 채널 할당 변수

를 도출하고,Preferably, the control unit allocates downlink and uplink power

and

, the Lagrangian variable at the base station

, Lagrangian variables in the user terminal

, and power split ratio

are all initialized, and the power split ratio

is set randomly between 0 and 1, then the channel assignment variable as a solution to the set channel assignment problem using a Lagrangian multiplier.

to derive,

,

, 하베스트 에너지 총량

및 서브그래디언드 d 를 연산하며,Downlink and Uplink Power Allocation

,

, the total amount of harvested energy

and a subgradient d ,

를 도출하고 도출된 기지국에서의 라그랑지안 변수

로 이전 기지국에서의 라그랑지안 변수

를 업데이트하고, 라그랑지안 변수

로 이전 기지국에서의 라그랑지안 변수

의 차가 기 정해진 임계치에 수렴할 때까지 반복 수행하여 기지국에서의 최적 라그랑지안 변수

를 도출하고,Lagrangian variables in the base station by performing binary optimization using the computed subgradient d

and Lagrangian variables in the derived base station

Lagrangian variables in the previous base station as

update the Lagrangian variable

Lagrangian variables in the previous base station as

The optimal Lagrangian variable in the base station is repeated until the difference of

to derive,

를 도출하고, 도출된

를 전력분할비율

로 업데이트하고,

이 기 정해진 임계치 accuracy로 수렴할 때까지 반복 수행하여 최적 전력분할비율

을 도출하도록 구비되는 것을 일 특징으로 한다.Power split ratio using gradient descent method

derived and derived

power split ratio

update to

The optimal power split ratio is repeated until convergence to this predetermined threshold accuracy.

It is characterized in that it is provided to derive .

According to the present invention, the channel capacity of the system can be maximized by deriving the optimal Lagrangian variable of the base station and the optimal Lagrangian variable of the user terminal with an integrated optimization algorithm for channel allocation, power allocation of the base station and user, and the power split ratio. This can improve system performance.

The following drawings attached to this specification illustrate preferred embodiments of the present invention, and serve to further understand the technical spirit of the present invention together with the detailed description of the present invention to be described later, so the present invention is a matter described in such drawings should not be construed as being limited only to
1 is a signal flow diagram of a first phase of an OFDMA SWIPT system in one embodiment;
2 is a signal flow diagram of a second phase of an OFDMA SWIPT system of an embodiment;
3 is a detailed configuration diagram of a user terminal according to an embodiment.
4 is a flowchart illustrating an integrated resource allocation process of a system according to an embodiment.
5 is a comparison graph of the thumb rate of the number of user terminals versus the SNR of one embodiment.
6 is a comparison graph of thumb rates according to the number of user terminals according to an embodiment.

Hereinafter, embodiments of the present invention will be described in more detail with reference to the drawings.

Advantages and features of the present invention, and a method for achieving them will become apparent with reference to the embodiments described below in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but can be implemented in various different forms, and only one embodiment makes the disclosure of the present invention complete, and common knowledge in the technical field to which the present invention pertains It is provided to fully inform the possessor of the scope of the invention, and the present invention is only defined by the scope of the claims.

Terms used in this specification will be briefly described, and the present invention will be described in detail.

The terms used in the present invention have been selected as currently widely used general terms as possible while considering the functions in the present invention, but these may vary depending on the intention or precedent of a person skilled in the art, the emergence of new technology, and the like. In addition, in a specific case, there is a term arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the corresponding invention. Therefore, the term used in the present invention should be defined based on the meaning of the term and the overall content of the present invention, rather than the name of a simple term.

When a part "includes" a certain element throughout the specification, this means that other elements may be further included, rather than excluding other elements, unless otherwise stated. Also, as used herein, the term “unit” refers to a hardware component such as software, FPGA, or ASIC, and “unit” performs certain roles. However, "part" is not meant to be limited to software or hardware. A “unit” may be configured to reside on an addressable storage medium and may be configured to refresh one or more processors.

Thus, by way of example, “part” includes components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables. The functionality provided within components and “parts” may be combined into a smaller number of components and “parts” or further divided into additional components and “parts”.

Hereinafter, with reference to the accompanying drawings, embodiments of the present invention will be described in detail so that those of ordinary skill in the art can easily carry out the embodiments of the present invention. And in order to clearly explain the present invention in the drawings, parts not related to the description are omitted.

An embodiment has a configuration for maximizing the thumb rate of the system by integrating and optimizing channel allocation, power allocation of a base station and user, and a power split ratio.

1 and 2 are conceptual diagrams illustrating a wireless power communication system of OFDMA according to an embodiment. Referring to FIG. 1 , it consists of one base station BS (Base station) and a plurality of user terminals Users. A single antenna is installed for the base station BS and the user terminal User.

As shown in FIG. 1 , in the first phase, the base station BS simultaneously beamforms information and power to each user terminal user 1 to user 4 , and as shown in FIG. 2 , in the second phase, user terminal user 1 to user 4 is The information is transmitted to the base station BS.

The OFDMA wireless power communication system (hereinafter abbreviated as system) including the base station BS and the user terminals user1 to use4 uses the thumb rate and harvested energy of the system in which the time division inversion is duplexed uplink and downlink. Derives the thumb rate of the link.

In addition, a plurality of user terminals User optimizes the system thumb rate by changing the power split ratio collected to transmit information to the base station BS, decodes the information, and then harvests energy from the RF signal received through the assigned sub-channel. At this time, the user terminal User derives the optimal power split ratio by integrating and optimizing the optimal channel allocation, the power allocation of the base station and the user, and the power split ratio, and then transmits the derived optimal power split ratio to the base station BS to set the system thumb rate. can be maximized.

3 is a detailed configuration diagram of the user terminal User shown in FIG. 1 . Referring to FIG. 3 , the user terminal User may include a receiver 110 , a controller 120 , and a transmitter 130 . The base station BS transmits an RF signal to each user terminal User using the assigned subchannel. Accordingly, the received RF signal is divided into information decoding and energy harvesting according to the power division ratio received by the control unit 120 from the received RF signal based on the receiving unit 110 of the user terminal User. In addition, the transmitting unit 130 of the user terminal User transmits the remaining information signal to the base station BS by using the previously collected energy.

과

로 표현되며, 여기서,

및

이다. k 번째 유저 단말 User 가 수신한 RF 신호를 2로 분할하기 위한 전력분할비율

은

로 정의된다.Here, the nth uplink and downlink subchannels between the base station (BS) and the kth user terminal User are respectively

class

is expressed as, where

and

am. Power division ratio for dividing the RF signal received by the k-th user terminal User by 2

silver

is defined as

The downlink signal received from the k- th user terminal through the n- th sub-channel is given by the following Equation (1).

[Equation 1]

는 n 번째 다운 링크 서브채널로 할당된 전력이고,

는 기지국 BS로부터 n 번째 서브채널 SC를 경유하여 k 번째 유저 단말 User 으로 전송된 정보 신호로 정의된다. here,

is the power allocated to the nth downlink subchannel,

is defined as an information signal transmitted from the base station BS to the k- th user terminal User via the n- th subchannel SC.

는 k번째 유저 단말 User 의 노이즈이다. 여기서,

은

라고 가정하고, 모든 유저 단말 User 와 서브채널 SCs 가 독립적이라고 가정하면, k 번째 유저 단말 User 로부터 n 번째 다른 링크 서브채널 SC를 통해 기지국 BS의 수신된 신호는 다음 수학식 2로 나타낸다.Also

is the noise of the k-th user terminal User. here,

silver

, and assuming that all user terminal Users and subchannel SCs are independent, the received signal of the base station BS from the kth user terminal User through the nth other link subchannel SC is expressed by Equation 2 below.

[Equation 2]

는 k 번째 유저 단말 User 에게 할당된 n 번째 업 링크 서브채널에 할당된 전력이고,

는 k 번째 사용자가 n 번째 서브채널 SC를 통해 기지국 BS로 보내는 정보 신호이며,

는 기지국 BS에서의 노이즈로 나타낸다.here,

is the power allocated to the n-th uplink subchannel allocated to the k-th user terminal User,

is an information signal sent by the k-th user to the base station BS through the n-th sub-channel SC,

is represented by noise in the base station BS.

는

이고, 기지국 노이즈

가 분산

을 가지는 제로 평균이면, n번째 서브채널을 할당받은 유저 단말 User 는

로 나타낸다. k 번째 유저 단말 User 의 하베스트된 에너지는 다음 수학식 3으로 표현된다.Also

Is

and base station noise

is dispersed

If it is a zero average with , the user terminal User assigned to the nth subchannel is

is represented by The harvested energy of the k-th user terminal User is expressed by Equation 3 below.

[Equation 3]

는 k 번째 유저 단말 User 의 에너지 하베스트 효율을 나타내고,

는 k 번째 유저 단말 User 에게 할당된 서브채널의 집합이고,

이며, 에너지를 하베스트한다. 모든 서브채널 SC에 대해, 기지국 BS와 유저 단말 User 는 제로 평균이고, 노이즈 분산

인 가우시안 분포 잡음

로 가정하면,

및

는 다음 조건 4를 만족하여야 한다.here,

represents the energy harvesting efficiency of the k-th user terminal User,

is a set of subchannels allocated to the k-th user terminal User,

and harvests energy. For all sub-channel SC, base station BS and user terminal User are zero mean, and noise variance

In Gaussian Distribution Noise

Assuming that,

and

must satisfy the following condition 4.

[Condition 4]

From this condition, the channel capacity of the k- th user terminal User for the downlink and uplink satisfies Equations 5 and 6, respectively.

[Equation 5]

[Equation 6]

및

는 다운 링크 및 업 링크 각각의 가중치를 나타낸다. 이에 업 링크 및 다운 링크 레이트에 각각의 가중치를 부여하여 시스템의 채널 용량을의 합을 얻은 다음 모든 k 번째 유저 단말 User 에 대해 다음 수학식 7을 얻을 수 있다. here,

and

denotes the weights of the downlink and uplink, respectively. Accordingly, the sum of the channel capacity of the system is obtained by giving each weight to the uplink and downlink rates, and then the following Equation 7 can be obtained for every k-th user terminal User.

[Equation 7]

Equation 7 may be converted into Equation 8 as a sum of index functions of subchannels.

[Equation 8]

에 대해 채널 할당 변수

, 전력분할비율

, 다운 링크 및 업 링크 전력 할당

및

변수들을 최적화하고, 이들 변수들의 통합 문제는 다음 수학식 8로 정의된다.Accordingly, in order to maximize the total channel capacity of such a system, the controller 120 controls an arbitrary n- th user terminal and an arbitrary k- th sub-channel.

for channel assignment variable

, power split ratio

, downlink and uplink power allocation

and

The variables are optimized, and the problem of integrating these variables is defined by the following Equation (8).

[Equation 8]

Here, the integrated optimization problem is non-convex for all variables. Therefore, the integration problem is divided into three subproblems, and the solution of the three subproblems is derived, and then an iterative optimization algorithm is used to maximize the system channel capacity to derive a local optimum for the overall system channel capacity.

First, the optimal power allocation sets the channel allocation and power split ratio to constants and applies the Lagrangian multiplication approach to derive the solution of the power allocation sub-problem. Here, the Lagrangian function is given by the following Equation (10).

[Equation 10]

및

는 각 기지국 BS와 유저 단말 User 의 전력 조건의 라그랑지안 곱수이다. 이러한 라그랑지안 듀얼 문제는 다음 수학식 11과 같이 주어진다.Here, the variable

and

is the Lagrangian multiplier of the power conditions of each base station BS and the user terminal User. This Lagrangian dual problem is given by Equation 11 below.

[Equation 11]

및 유저 단말에서의 라그랑지안 변수

에 대해 볼록하다. 반대로 라그랑지안 듀얼 문제의 최소화

에 의해 시스템 채널 용량의 최대화가 가능하다. 따라서 라그랑지안 듀얼 문제의 해를 반복적으로 도출하여 최적 시스템 썸레이트를 도출한다. The Lagrangian dual problem is the Lagrangian variable in the base station.

and Lagrangian variables in the user terminal.

convex about Conversely, minimization of the Lagrangian dual problem

It is possible to maximize the system channel capacity by Therefore, the optimal system thumb rate is derived by iteratively deriving the solution of the Lagrangian dual problem.

및

변수는 다음 수학식 14 및 15에 나타낸 바와 같이 다운 링크와 업 링크 전력 할당 간의 차와 변동에 대한 라그랑지안 문제로부터 도출된다. Downlink and Uplink Power Allocation

and

The variable is derived from the Lagrangian problem for the difference and variation between downlink and uplink power allocation as shown in Equations 14 and 15 below.

는 수학식 12의 라그랑지안 듀얼 문제의 해로 도출될 수 있다.And, the Lagrangian variable in the user terminal

can be derived as a solution to the Lagrangian dual problem of Equation 12.

[Equation 12]

는 k 번째 유저 단말 User 에 할당된 서브 채널의 수이다. 따라서,

는 다운 링크 위상 동안 하베스트된 에너지 총 량으로부터 결정된다.

로부터 라그랑지안 듀얼 함수는 기지국에서의 라그랑지안 변수

에 대한 함수로 다음 수학식 13으로 표현된다.from the water fill algorithm

is the number of subchannels allocated to the k-th user terminal User. therefore,

is determined from the total amount of energy harvested during the downlink phase.

From the Lagrangian dual function is the Lagrangian variable at the base station.

It is expressed by the following Equation 13 as a function for .

[Equation 13]

[Equation 14]

[Equation 15]

가 도출되고, 이진법을 구현하기 위해 사용된 서브그래디언트는 다음 수학식 16로 주어진다.Lagrangian variables at base stations using binary

is derived, and the subgradient used to implement the binary system is given by the following Equation (16).

[Equation 16]

및

, 기지국에서의 라그랑지안 변수

, 및 유저 단말에서의 라그랑지안 변수

로부터 도출할 수 있다. 이러한 채널 할당 하위 문제는 폐쇄형 솔루션을 도출하기 어렵고 볼록 문제가 아니다.Next, the solution to the channel allocation subproblem is downlink and uplink power allocation

and

, the Lagrangian variable at the base station

, and Lagrangian variables in the user terminal

can be derived from This channel allocation subproblem is difficult to derive a closed solution and is not a convex problem.

Accordingly, the optimal channel allocation of the controller 120 is derived using a comprehensive search method. That is, the new Lagrangian from Equation 10 can be defined as Equation 17 below.

[Equation 17]

은 모든 서브 채널과 유저 단말 User 에 공통이므로, 채널 할당 하위 문제에 영향을 미치지 아니한다. 이에 채널 할당 방정식은 다음 수학식 18로 정의된다.Now

Since is common to all sub-channels and user terminals User, it does not affect the sub-problem of channel allocation. Accordingly, the channel allocation equation is defined by Equation 18 below.

[Equation 18]

및

에 대입하면 하기 수학식 19의 듀얼 문제의 해를 도출할 수 있다.Downlink and uplink power allocation of Equations 14 and 15 in Equation 17

and

By substituting into , a solution to the dual problem of Equation 19 below can be derived.

[Equation 19]

은 모든 n 개의 서브 채널에서 공통된 값이므로 채널 할당 문제를 해결함에 있어 영향을 미치지 아니한다. 따라서 공동 항을 제거함에 따라 최종 채널 할당 문제의 해는 하기 수학식 20 및 수학식 21으로 도출될 수 있다.here,

Since is a value common to all n subchannels, it does not affect the resolution of the channel allocation problem. Accordingly, as the joint term is removed, a solution to the final channel allocation problem can be derived from Equations 20 and 21 below.

[Equation 20]

Here, the following formula 21 is satisfied.

[Equation 21]

는 사용자 k에 대해 할당된 사용 채널의 수이다.On the other hand, the power division ratio sub-problem can initialize the following Equation 23, where

is the number of used channels allocated for user k.

[Equation 23]

에 대해 볼록하지만 폐쇄형이므로 구하기 어렵다. Here, the solution of the equation for deriving the solution of the power split ratio sub-problem is the power split ratio

It is convex to , but difficult to obtain because it is closed.

Therefore, the gradient descent method, which is one of the convex optimal algorithms, is used to derive the optimal power split ratio. The sub-gradient of Equation 23 used in the gradient descent method is derived from Equation 24 below.

[Equation 24]

Meanwhile, an algorithm for deriving a local optimization sum rate is as follows.

은 하베스트된 에너지의 총량으로부터 도출되고 기 알고리즘의 반복 탐색 마다 각 유저 단말 User 에 대해 업데이트되어야 한다. 이에 로컬 최적 썸레이트를 도출하기 위해 알고리즘의 반복 수행마다 변경되는 유저 단말에서의 라그랑지안 변수

로는 모든 유저 단말과 동일한 조건과 비교할 수 없다.Here, from Equation 12, it is a Lagrangian variable that is a Lagrangian multiplier in the user terminal.

is derived from the total amount of harvested energy and should be updated for each user terminal User at every iterative search of the algorithm. Accordingly, in order to derive the local optimal thumb rate, the Lagrangian variable in the user terminal is changed for each iteration of the algorithm.

It cannot be compared with the same conditions as all user terminals.

가 제공되는 첫번째 채널 할당 이후의 정확한 채널 할당 문제가 해결되지 아니한다. 이에 첫번째 채널 할당 시 채널할당문제는 라그랑지안 곱수( Lagrange multipliers )로 구현된다. Therefore, the Lagrangian variable in the user terminal is equal to all users.

The problem of correct channel assignment after the first channel assignment is not solved. Therefore, when the first channel is allocated, the channel allocation problem is implemented as Lagrange multipliers.

4 is an algorithm showing a process of performing integrated optimization of power allocation, channel allocation, and power split ratio of the control unit 120. Referring to FIG. 4, a channel allocation derivation step 121, an operation step 123, And it may include at least one of the power division ratio deriving step (125).

및

, 기지국에서의 라그랑지안 변수

, 유저 단말에서의 라그랑지안 변수

, 및 전력분할비율

은 모두 초기화되고, 전력분할비율

는 0과 1 사이의 랜덤하게 설정된다. 그리고 기지국에서의 라그랑지안 변수

와 유저 단말의 그랑지안 변수

은 라그랑지안 곱수로 정의되며, 0보다 큰 값으로 설정된다. 이분법(bisection method)를 이용하기 위해, 기지국에서의 라그랑지안 변수

를 정의하고 최적 기지국에서의 라그랑지안 변수

를 포함한다. 또한 초기화된 라그랑지안 곱수를 사용하여 수학식 20의 채널 할당 문제의 해를 도출하면 채널 할당 변수

는 도출될 수 있다.First, in the channel allocation deriving step 121, the controller 120 according to an embodiment allocates downlink and uplink power.

and

, the Lagrangian variable at the base station

, Lagrangian variables in the user terminal

, and power split ratio

are all initialized, and the power split ratio

is set randomly between 0 and 1. And the Lagrangian variable at the base station

and the Grangian variables of the user terminal.

is defined as a Lagrangian multiplier, and is set to a value greater than zero. To use the bisection method, the Lagrangian variable at the base station

and define the Lagrangian variable at the optimal base station.

includes In addition, when the solution of the channel allocation problem of Equation 20 is derived using the initialized Lagrangian multiplier, the channel allocation variable

can be derived.

, 하베스트 에너지 총량

, 및 서브그래디언드 d 를 이용하여 유저 단말의 라그랑지앙 변수

을 도출한다. And, if the channel allocation problem is solved using the Lagrangian multiplier, the controller 120 according to an embodiment allocates the downlink power in the operation step 123 .

, the total amount of harvested energy

, and the Lagrangian variable of the user terminal using the subgradient d

to derive

를 도출하고 도출된 기지국에서의 라그랑지안 변수

로 이전 기지국에서의 라그랑지안 변수

를 업데이트한다. 이러한 기지국에서의 라그랑지안 변수

의 업데이트는

이 기 정해진 임계치 accuracy 이하에 도달할 때 까지 반복된다. Then, in the operation step 123, the control unit 120 of an embodiment performs binary optimization using the derived subgradient d to perform Lagrangian variables in the base station.

and Lagrangian variables in the derived base station

Lagrangian variables in the previous base station as

update Lagrangian variables in these base stations

the update of

This is repeated until it reaches below a predetermined threshold accuracy.

를 제외한 모든 변수가 accuracy에 수렴하면, 전력분할비율 도출단계(124)에서 제어부(120)는 수학식 24에 의거 전력분할비율

를 도출하고, 그래디언드 디센트 방법을 통해 도출된 이전 전력분할비율

를 도출된

로 업데이트한다. 이러한 전력분할비율

최적화는

이 기 정해진 임계치 accuracy 이하에 도달할 때 까지 반복된다. 이에 모든 변수들은 로컬 최적 썸레이트에 수렴한다.At this time, the power division ratio in the first loop

When all variables except for converge to the accuracy, in the power split ratio derivation step 124 , the controller 120 controls the power split ratio based on Equation 24

, and the previous power split ratio derived through the gradient descent method.

derived from

update to This power split ratio

optimization is

This is repeated until it reaches below a predetermined threshold accuracy. Accordingly, all variables converge to the local optimal thumb rate.

Local Optimal Thumb Rate to simulation results for

및

은 1로 설정된다. 그리고 유저 단말 User 의 수는 4이고 노이즈 전력 스펙트럼 밀도는 -155 dBm/Hz로 설정된다. Assume that the total system bandwidth is divided into 64 subcarriers at 20 MHz, and the channel path loss is -30dB. It is assumed that the distance between the base station BS and the user terminal User is 1 m, and the reference distance is 1 m. In addition, when the energy harvest efficiency is 0.7, that is, it is assumed that it is 70% of the total received power of the harvest, and it is assumed that the channel has multipath multi-Gaussian distribution noise having 5 delay steps, and all channels of the user terminal User are independent It is assumed that the downlink and uplink rate weights

and

is set to 1. And the number of user terminal users is 4 and the noise power spectral density is set to -155 dBm/Hz.

에 대해 50%의 시스템 썸레이트 게인을 얻을 수 있다. 또한 0.9 bps/Hz의 시스템 썸레이트를 달성하기 위해 3dB 전력 손실이 적용된다. 결국 낮은 SNR 영역에서 일 실시예는 이득을 확인할 수 있고, 최적 채널 할당 문제를 고려하지 아니한 경우 기존의 OFDMA 시스템 보다 시스템 썸레이트의 성능이 향상됨을 알 수 있다. 5 is a graph showing the system thumb rate performance for SNR derived by different methods. Referring to FIG. 5, it can be seen that the system thumb rate for all methods increases as the SNR increases, and in one embodiment It can be seen that the system thumb rate derived by That is, an SNR of 12dB and a fixed power split ratio

You can get a system thumb rate gain of 50% for . A 3dB power dissipation is also applied to achieve a system thumb rate of 0.9 bps/Hz. As a result, it can be seen that an embodiment can confirm a gain in a low SNR region, and the performance of the system thumb rate is improved compared to the existing OFDMA system when the optimal channel allocation problem is not considered.

6 is a diagram showing the system thumb rate performance with respect to the number of user terminals for a fixed SNR of 15 dB. Referring to FIG. 6, since the system thumb rate hardly changes when a fixed channel allocation is used, the number of users is changed. . However, in one embodiment, it can be seen that the total number of system thumb rates increases when the number of user terminal users is increased using the proposed channel allocation scheme. Also, when optimizing the channel allocation problem, it can be seen that when the number of user terminal users increases, the power allocation gain decreases, and the system thumb rate increases as the number of user terminal users increases.

However, in the case of a system with a limited bandwidth, the channel capacity per user terminal user is gradually reduced, so that a thumb rate is achieved at a high number of user terminal users.

In one embodiment, in performing the integrated optimization of power allocation, channel allocation, and power split ratio, the channel allocation problem is not a convex problem, but the power allocation and power split ratio are included, and the suboptimal having a fixed power split ratio and a fixed power This method is fixed for all variables, and thus, the performance of the OFDMA SWIPT system having one antenna for the base station BS and the user terminal User is excellent.

Although the present invention has been described in detail through representative embodiments above, those of ordinary skill in the art to which the present invention pertains can make various modifications to the above-described embodiments without departing from the scope of the present invention. will understand Therefore, the scope of the present invention should not be limited to the described embodiments, and should be defined by all changes or modifications derived from the claims and equivalent concepts as well as the claims to be described later.

Claims (12)

In the integrated resource allocation method of the OFDMA SWIPT system for receiving the RF signal of the base station from a plurality of user terminals and then beamforming information and power at the same time,
In the base station, an integrated optimization step of deriving an optimal Lagrangian variable of a base station and an optimal Lagrangian variable of a user terminal with an integrated optimization algorithm for channel allocation, power allocation of the base station and user, and power split ratio,
The integrated optimization step is
(a) Downlink and Uplink Power Allocation

and

, the Lagrangian variable at the base station

, Lagrangian variables in the user terminal

, and power split ratio

are all initialized, and the power split ratio

is set randomly between 0 and 1, then the channel assignment variable as a solution to the set channel assignment problem using a Lagrangian multiplier.

deriving;
(b) Downlink and Uplink Power Allocation

,

, the total amount of harvested energy

and calculating a subgradient d;
(c) Lagrangian variables in the base station by performing binary optimization using the derived subgradient d

and Lagrangian variables in the derived base station

Lagrangian variables in the previous base station as

update the Lagrangian variable

Lagrangian variables in the previous base station as

The optimal Lagrangian variable in the base station is repeated until the difference of

deriving; and
(d) Power split ratio using the gradient descent method

derived and derived

power split ratio

update to

The optimal power split ratio is repeated until convergence to this predetermined threshold accuracy.

An integrated resource allocation method of an OFDMA SWIPT system comprising at least one of deriving delete 2. The method of claim 1, wherein the downlink and uplink power allocation

,

each
It is provided to set the channel allocation and power split ratio as constants and derive it using a Lagrangian multiplication approach and a subgradient d , and uplink and downlink power allocation

,

and each of the subgradients d is provided to satisfy the following Relations 1 to 3, An integrated resource allocation method of an OFDMA SWIPT system.
[Relational Expression 1]

[Relational Expression 2]

[Relational Expression 3]

here,

is the Lagrangian variable at the base station,

is the channel assignment variable,

is a Lagrangian variable in the user terminal,

is the sub channel

is the channel information of

is the downlink weight,

is the uplink weight,

is the power split ratio,

is the total power. 4. The variable of claim 3, wherein the channel assignment variable

silver,
Downlink and Uplink Power Allocation

and

, the Lagrangian variable at the base station

, and Lagrangian variables in the user terminal

, uplink and downlink weights

,

An integrated resource allocation method of an OFDMA SWIPT system, characterized in that it is derived from Relations 4 and 5 determined from
[Relational Expression 4]

[Relational Expression 5]

5. The Lagrangian parameter of the base station according to claim 4,

Is
subgradient

An integrated resource allocation method of an OFDMA SWIPT system, characterized in that it is derived using a binary method for . According to claim 5, Lagrangian variable of the user terminal

Is
Total amount of energy harvested during downlink

is determined by
The Lagrangian dual problem that satisfies the following relation (6)

An integrated resource allocation method of the OFDMA SWIPT system, characterized in that it is derived from the solution of
[Relational Expression 6]

here,

,

is the channel information,

is the number of server channels allocated to the user terminal. In the integrated resource allocation apparatus of the OFDMA SWIPT system for receiving the RF signal of the base station from a plurality of user terminals and then beamforming information and power at the same time,
A control unit for deriving an optimal Lagrangian variable of a base station and an optimal Lagrangian variable of a user terminal with an integrated optimization algorithm for channel allocation to the base station, power allocation of the base station and user, and power split ratio,
The control unit is
Downlink and Uplink Power Allocation

and

, the Lagrangian variable at the base station

, Lagrangian variables in the user terminal

, and power split ratio

are all initialized, and the power split ratio

is set randomly between 0 and 1, then the channel assignment variable as a solution to the set channel assignment problem using a Lagrangian multiplier.

to derive,
Downlink and Uplink Power Allocation

,

, the total amount of harvested energy

and a subgradient d ,
Lagrangian variables in the base station by performing binary optimization using the computed subgradient d

and Lagrangian variables in the derived base station

Lagrangian variables in the previous base station as

update the Lagrangian variable

Lagrangian variables in the previous base station as

The optimal Lagrangian variable in the base station is repeated until the difference of

to derive,
Power split ratio using gradient descent method

derived and derived

power split ratio

update to

The optimal power split ratio is repeated until convergence to this predetermined threshold accuracy.

Integrated resource allocation apparatus of the OFDMA SWIPT system, characterized in that it is provided to derive. delete 8. The allocation of downlink and uplink power according to claim 7

,

each
It is provided to set the channel allocation and power split ratio as constants and derive it using a Lagrangian multiplication approach and a subgradient d , and uplink and downlink power allocation

,

and each of the subgradients d is provided to satisfy the following Relations 11 to 13. The apparatus for allocating integrated resources in an OFDMA SWIPT system.
[Relational Expression 11]

[Relational Expression 12]

[Relationship 13]

here,

is the Lagrangian variable at the base station,

is the channel assignment variable,

is a Lagrangian variable in the user terminal,

is the sub channel

is the channel information of

is the downlink weight,

is the uplink weight,

is the power split ratio,

is the total power. 10. The method of claim 9, wherein the channel assignment variable

silver,
Downlink and Uplink Power Allocation

and

, the Lagrangian variable at the base station

, and Lagrangian variables in the user terminal

, uplink and downlink weights

,

An apparatus for allocating integrated resources of an OFDMA SWIPT system, characterized in that it is derived from Relations 14 and 15 determined from
[Relational Expression 14]

[Relational Expression 15]

11. The method of claim 10, Lagrangian parameter of the base station.

Is
subgradient

An apparatus for allocating integrated resources of an OFDMA SWIPT system, characterized in that it is derived using a binary method for . 12. The method of claim 11, wherein the Lagrangian variable of the user terminal.

Is
Total amount of energy harvested during downlink

is determined by
Lagrangian dual problem that satisfies the following relation 16

Integrated resource allocation apparatus of the OFDMA SWIPT system, characterized in that derived from the solution.
[Relation 16]

here,

,

is the channel information,

is the number of server channels allocated to the user terminal.

Images