KR102509406B1 - Hybrid User Pairing Method for Spectral Efficiency in Multiuser MISO-NOMA System With SWIPT - Google Patents

Abstract

The present invention relates to a method for constructing a hybrid user pair capable of increasing spectrum efficiency by efficiently allocating network resources in a multi-user MISO-NOMA network system using SWIPT.
A hybrid user pair configuration method according to the present invention comprises a BS (Base Station) having L antennas, K energy receivers and M message receivers located in the first zone (Zone-1) having a radius r based on the BS And, MISO-NOMA (Multiple User-Multiple-Input Single-MISO-NOMA) having N message receivers located in the second zone (Zone-2) with a radius R based on the BS outside the first zone (Zone-1) Output Non-orthogonal Multiple Access) A hybrid user pair configuration method that simultaneously performs resource allocation for spectrum efficiency and user pair in a network system. setting a value; (b) iteratively finding a parameter value that optimally allocates limited network resources of the MISO-NOMA network system and optimizes a user pair of a message receiver in Zone-1 and Zone-2; (c) calculating network performance according to the optimized user pair and outputting the calculated network performance and optimized parameter values;

Description

Hybrid User Pairing Method for Spectral Efficiency in Multiuser MISO-NOMA System With SWIPT}

The present invention relates to a method for constructing a hybrid user pair for spectral efficiency in a MISO-NOMA network, and in particular, in a multi-user MISO-NOMA network system using SWIPT, a hybrid user that efficiently allocates network resources to increase spectral efficiency. It's about how to make a pair.

MISO-NOMA (multiple-input single-output non-orthogonal multiple access) is a network technology for supporting multiple users at the same time. It divides/allocates the same frequency to multiple users with different powers to enable multiple users at the same time. It is a technology that provides services to In this MISO-NOMA network system, unlike the existing orthogonal multiple access, slots (frequency, time, etc.) are assigned different transmission power to multiple users and transmitted simultaneously by using non-orthogonal multiple access, which allows various users to transmit in one transmission. You can send data to them.

Simultaneously wireless information and power transfer (SWIPT) is a technology for simultaneously transmitting information and energy, using some of the received signals for energy storage and the rest for data transmission.

Meanwhile, since resources are limited in a multi-user MISO-NOMA network system using such a SWIPT, a method for finding an optimized user pair to effectively allocate limited network resources is required.

Republic of Korea Patent Registration No. 10-1662687 (registered on September 28, 2016)

The present invention has been proposed to increase resource efficiency in a conventional MISO-NOMA network, and an object of the present invention is to maximize spectral efficiency through limited user pair optimization in a multi-user MISO-NOMA network using SWIPT to increase spectral efficiency. It is to provide a hybrid user pair configuration method that allows.

A hybrid user pair configuration method according to the present invention for achieving the above object is a BS (Base Station) having L antennas, and K energies located in the first zone (Zone-1) having a radius r based on the BS MISO-NOMA (Multiple- Input Single-Output Non-orthogonal Multiple Access) A hybrid user pair configuration method that simultaneously performs resource allocation for spectrum efficiency and user pair configuration in a network system. Parameters for resource allocation and user pair configuration in the MISO-NOMA network system setting an initial value; Iteratively finding parameter values that optimally allocate limited network resources of the MISO-NOMA network system and optimize user pairs of message recipients in Zone-1 and Zone-2; and calculating network performance according to the optimized user pair and outputting the calculated network performance and optimized parameter values.

According to the present invention, in the MISO NOMA network system using SWIPT, limited network resources are saved by constructing an optimized user pair through an SCA-based iterative (Successive convex approximation-based low-complexity iterative: successive convex approximation-based low-complexity search) algorithm. This has the effect of optimally allocating and finding pairs of message recipients.

1 is a conceptual diagram of a multi-user MISO-NOMA network system using SWIPT applied to the present invention;
2 is an example of a change in frequency efficiency according to an increase in the number of optimal resource allocation searches in a MISO-NOMA network system;
3 is an example of a change in average frequency efficiency as the transmission power of a BS increases in a MISO-NOMA network system;
4 is an example of average frequency efficiency change as the minimum transmission condition (R) increases in the MISO-NOMA network system;
5 shows an example of a change in average frequency efficiency according to a change in the number of antennas of a BS in a MISO-NOMA network system.

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

1 shows a conceptual diagram of a multi-user MISO-NOMA network system using SWIPT applied to the present invention.

As shown in FIG. 1, the multiuser MU-MISO NOMA (Multiuser Multiple-Input Single-Output Non-orthogonal Multiple Access) system using SWIPT is divided into two zones based on the BS (Base Station) having L antennas in the middle is lost

In the first zone (hereinafter referred to as 'Zone-1'), there are K energy receivers (EH _k ∼ EH _K ) and M message receivers (ID ⁽¹⁾ _m ∼ ID ⁽¹⁾ _M ). The radius of Zone-1 is r. And in the second zone (hereinafter referred to as 'Zone-2'), there are N message receivers (ID ⁽²⁾ _n ∼ ID ⁽²⁾ _N ), and the radius of this Zone-2 is R, and Zone-1 located on the outskirts of

At this time, the present invention proposes an SCA-based iterative (Successive convex approximation-based low-complexity iterative: low-complexity search based on contiguous convex approximation) algorithm, which is a resource allocation algorithm for effectively using limited network system resources, and limited network resources A value that optimally allocates and a pair of message recipients in Zone-1 and Zone-2 are found. That is, the SCA-based iterative algorithm proposed in the present invention provides a hybrid pair construction method for simultaneously performing resource allocation and user pairing to maximize spectral efficiency in a MISO-NOMA network system.

In FIG. 1, the BS can simultaneously transmit signals to message receivers and energy receivers of Zone-1 and message receivers of Zone-2 using NOMA. Therefore, the transmitted message is as shown in Equation 1 below.

는 Zone-1의 m번째 메시지 수신자와 L개의 안테나를 가진 BS 사이의 빔포밍 패턴의 벡터로 L×1로 이루어져 있고,

는 Zone-2의 n번째 메시지 수신자와 L개의 안테나를 가진 BS 사이의 빔포밍 패턴의 벡터로 L×1로 이루어져 있다. 그리고,

는 Zone-1에 K개의 에너지 수신자와 L개의 안테나를 가진 BS의 사이의 빔포밍 벡터로 L×K의 크기를 갖는다. 또한,

과

은 메시지 신호로 크기는

,

이다. here,

is the vector of the beamforming pattern between the m-th message receiver of Zone-1 and the BS with L antennas, and consists of L × 1,

is a vector of beamforming patterns between the nth message receiver of Zone-2 and a BS having L antennas, and is composed of L×1. and,

is a beamforming vector between K energy receivers in Zone-1 and a BS having L antennas and has a size of L×K. also,

class

is a message signal, the size of which is

,

am.

Therefore, the signals received from the BS by the m-th message receiver among the M message receivers, the n-th message receiver among the N-th message receivers, and the K energy receivers are as follows: Equations 2, 3, and 4.

는 BS와 m번째 메시지 사용자(Zone-1) 사이의 채널 효율,

는 BS와 n번째 메시지 수신자(Zone-2) 사이의 채널효율,

는 BS와 k번째 에너지 수신자(Zone-1) 사이의 채널 효율이다. here,

is the channel efficiency between the BS and the m-th message user (Zone-1),

is the channel efficiency between the BS and the nth message receiver (Zone-2),

is the channel efficiency between the BS and the kth energy receiver (Zone-1).

Therefore, the received energy of the k-th energy receiver is expressed in Equation 5 below.

는 Zone-1과 Zone-2에 위치한 메시지 수신자들과 L개의 안테나를 가진 BS 사이의 빔포밍 패턴들의 벡터(2×L)로,

이다. here,

Is a vector (2 × L) of beamforming patterns between message receivers located in Zone-1 and Zone-2 and a BS with L antennas,

am.

At this time, since the energy stored from the received energy is nonlinear, the energy stored and used by the k-th user is as shown in Equation 6 below.

이고,

는 최대로 에너지 수신자가 저장할 수 있는 에너지를 의미한다. 그리고

이다. here,

ego,

is the maximum energy that can be stored by the energy receiver. and

am.

Meanwhile, in the case of the receiver of the mth message, the signal-to-interference-plus-noise ratio (SINR) is expressed in Equation 7 below.

이다. here,

am.

In the case of the nth message user, the SINR is as shown in Equation 8 below.

,

이다. here,

,

am.

는 선택된 m번째 사용자와 n번째 사용자를 나타내는 행렬로 다음 수학식 9와 같다.

Is a matrix representing the selected m-th user and n-th user, as shown in Equation 9 below.

는 무한대가 된다. Additionally, if message receivers in Zone-1 and Zone-2 are not paired,

becomes infinite.

과

)은 다음 수학식 10 및 수학식 11과 같다. As a result, the channel capacity of the m-th message receiver in Zone-1 and the n-th receiver in Zone-2 (

class

) is as shown in Equations 10 and 11 below.

In the MISO-NOMA network system proposed in the present invention, the system performance is the sum of the performance of the m-th user and the n-th user.

은 다음 수학식 12와 같다. Therefore, network performance

Is equal to the following Equation 12.

Network resource limitations in the MISO-NOMA network system proposed in the present invention are limited. Therefore, the condition of these limited resources is shown in Equation 13 below.

과

는 m번째 메시지 수신자와 n번째 메시지 수신자의 서비스 요구사항이다. 그리고

는 k번째 에너지 사용자의 최소 에너지 충전 요구사항이다.

은 BS의 최대 전송파워이다. 따라서, 네트워크 성능(

)을 최대화하기 위해서는 수학식 13을 만족해야 한다. here,

class

is the service requirement of the m-th message receiver and the n-th message receiver. and

is the minimum energy charging requirement of the k-th energy user.

is the maximum transmit power of the BS. Therefore, network performance (

), Equation 13 must be satisfied.

This is expressed as an objective function (SEM) and a constraint (subject to: s. t.) as shown in Equation 14 below.

는 이원성을 가지 변수로, 이를 연속 변수로 바꾸면

와 같다. 따라서, 목적함수 및 제한조건은 다음 수학식 15와 같다.here,

is a variable with duality, and converting it into a continuous variable

Same as Therefore, the objective function and constraints are as shown in Equation 15 below.

Using the mathematical principle of Equation 16 below, the constraints of Equation 15 can be converted as shown in Equation 17.

와

는 m번째 메시지 수신자와 n번째 메시지 수신자의 소프트 데이터 속도(soft data rate)이고,

와

는 m번째 메시지 수신자와 n번째 메시지 수신자의 SINR이다. here,

and

is the soft data rate of the m-th message receiver and the n-th message receiver,

and

is the SINR of the m-th message receiver and the n-th message receiver.

는 선형(linear)이면서 볼록함수(convex function)이지만, 조건들in the above expression

is a linear and convex function, but the conditions

is a non-convex function. Therefore, when the conditions are approximated with a convex function using mathematical principles, the following Equation 18 is obtained.

는

이다. here,

Is

am.

는

이고,

는

을 만족하는 요소(

)들의 집합이다. also,

Is

ego,

Is

factor that satisfies (

) is a set of

는

이고,

은 실수부를 의미한다.

Is

ego,

means the real part.

는

이다.

Is

am.

는

이다.

Is

am.

는

이고,

는

의 대각합이다.

Is

ego,

Is

is the diagonal of

는

이다.

Is

am.

Since all variables in the above equation are convex functions, an optimal value can be found using an algorithm. To this end, the initial value is defined as in Equation 19 below.

And, the SCA-based iterative algorithm proposed in the present invention is shown in Table 1 below.

은 탐색횟수(k)의 초기값을 설정한 것이고,

는 시스템 성능을 최적화되는 출력 파라미터(

)의 초기값을 설정한 것이다. 또한,

는 입력 파라미터 초기값을 나타내고,

는 시스템 성능(

)을 최적화하는 입력 파라미터를 나타낸다. here,

is the initial value of the number of searches (k),

is the output parameter (

) to set the initial value. also,

represents the input parameter initial value,

is the system performance (

) represents the input parameters to optimize.

As shown in Table 1, the SCA-based iterative algorithm according to the present invention sets the resource allocation of the MISO-NOMA network system and the initial value of the parameter for configuring the user pair through Equation 19, and the MISO-NOMA network system The parameter value that optimally allocates the limited network resources of and optimizes the user pair of message receivers in Zone-1 and Zone-2 is repeatedly found through Equation 18, and the network performance according to the optimized user pair is calculated and calculated. The network performance and optimized parameter values are output.

Through the SCA-based iterative algorithm that performs the above process, it is possible to construct an optimized user pair in the MISO-NOMA network.

2 shows an example of a change in frequency efficiency according to an increase in the number of optimal resource allocation searches in a MISO-NOMA network system. Hybrid User Pairing (HUP) is a resource allocation technique to which the SCA-based iterative algorithm proposed in the present invention is applied, RUP (Random User Pairing) and MUB (Multiuser Beamforming) are among conventional resource allocation techniques.

As shown in FIG. 2, it can be seen that the frequency efficiency increases and then becomes constant as the number of searches increases in both the hybrid user pairing (HUP) technique according to the present invention, the conventional random user pairing (RUP) technique, and the multiuser beamforming (MUB) technique. , it can be seen that the HUP technique proposed in the present invention maximizes the frequency efficiency through resource allocation than other techniques according to the increase in the number of searches.

3 shows an example of a change in average frequency efficiency as the transmission power of a BS increases in a MISO-NOMA network system.

As shown in FIG. 3, as transmission power increases, average frequency efficiency increases in all of the HUP, RUP, and MUB techniques, which is due to more power. At this time, it can be confirmed that the HUP technique proposed in the present invention is superior to other techniques under the same conditions, and through this, it can be seen that the HUP technique according to the present invention brings about performance improvement. Additionally, the closest to optimal efficiency can be identified through BFS (random search method), which is a method that considers all cases.

4 shows an example of average frequency efficiency change as the minimum transmission condition (R) increases in the MISO-NOMA network system.

As can be seen in FIG. 4, it can be confirmed that the average frequency efficiency of the HUB technique also decreases as the minimum transmission condition increases.

5 shows an example of a change in average frequency efficiency according to a change in the number of antennas of a BS in a MISO-NOMA network system.

As shown in FIG. 5, as the number of antennas increases, the average frequency efficiency also increases. At this time, it can be seen that the average frequency efficiency of the HUP technique according to the present invention is the highest compared to other existing techniques. Through this, the method proposed by the present invention You can see that this resource is used effectively.

As such, in the present invention, by constructing an optimized user pair in the MISO NOMA network, it is possible to increase the spectral efficiency of the MISO NOMA network.

The present invention is not limited to the above-described embodiments, and various modifications and variations within the scope of equivalents of the technical spirit of the present invention and the claims to be described below by those skilled in the art to which the present invention pertains. Of course, this can be done.

Claims (5)

A BS (Base Station) having L antennas, K energy receivers and M message receivers located in the first zone (Zone-1) having a radius r based on the BS, and the first zone (Zone-1 ), the spectral efficiency in a MISO-NOMA (Multiple-Input Single-Output Non-orthogonal Multiple Access) network system having N message receivers located in the second zone (Zone-2) with a radius R based on BS outside of As a hybrid user pair configuration method for simultaneously performing resource allocation and user pair configuration for
(a) setting initial values of parameters for configuring resource allocation and user pairs of the MISO-NOMA network system; (b) iteratively finding a parameter value that optimally allocates limited network resources of the MISO-NOMA network system and optimizes a user pair of a message receiver in Zone-1 and Zone-2; (c) calculating network performance according to the optimized user pair and outputting the calculated network performance and optimized parameter values;
Step (a) of setting the initial value of the parameter
search times

and initial values of output parameters that optimize system performance.

, and the initial value of the input parameter through the following equation

Hybrid user pair configuration method characterized in that for setting.

(Where K is the number of energy receivers in Zone-1,

Is a vector of beamforming patterns between a message receiver located in Zone-1 and a BS having L antennas (L × 1),

Is a vector of beamforming patterns between a message receiver located in Zone-2 and a BS having L antennas (L × 1),

Is a vector (2 × L) of beamforming patterns between message receivers located in Zone-1 and Zone-2 and a BS with L antennas.

,
V is the beamforming vector (L×K) between K energy receivers in Zone-1 and BSs with L antennas,

Is a matrix representing the selected m-th user and n-th user,

is the channel efficiency between the BS and the m-th message user (Zone-1),

class

Is the service requirement of the m-th message receiver and the n-th message receiver,

is the minimum energy charge requirement of the kth energy user,

is the maximum transmission power of BS,

class

is the soft data rate of the m-th message receiver and the n-th message receiver,

class

is the signal-to-interference-plus-noise ratio (SINR) of the m-th message receiver and the n-th message receiver,

Is

factor that satisfies (

),

,

,

Is

go,

is the real part,

Is

represents)
delete According to claim 1,
In the step (b) of iteratively finding a parameter value that optimizes the user pair,
The system performance (

) as an input parameter to optimize

Hybrid user pair configuration method characterized in that for finding.

(here,

Is (SINR: Signal-to-interference-plus-noise ratio, signal-to-interference-noise ratio) of the m-th message receiver,

ego,

is the SINR of the nth message user,

,

is,

represents)
According to claim 3,
The system performance (

), the equation for optimizing
non-convex function

is approximated by a convex function,
A hybrid user pair configuration method characterized in that it is converted and expressed by the following equation.

(here,

Is

ego,

Is

is,

Is

represents)
According to claim 3 or 4,
Step (c) of outputting the network performance and optimized parameter values,
system performance (

) as an input parameter to optimize

If you find
Optimized output parameters

System performance when (

) is calculated,
Calculated system performance (

) and output parameters

Hybrid user pair configuration method characterized in that for outputting.

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