KR101537891B1 - Energy-efficient transmission power management scheme for multicast service over wireless access network - Google Patents

Abstract

Disclosed are an energy-efficient multicast method through a transmission power control and a communication system thereof. Provided is the multicast transmission method, comprising the steps of: calculating an electric power which maximizes multicast energy efficiency according to the number of user terminals of a multicast group; and setting the calculated electric power as a multicast transmission power and multicasting data into the multicast group.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to an energy efficient multicast method and communication system using transmission power control,

Embodiments of the present invention are directed to energy efficient multicast transmission schemes.

Multicast refers to a method in which one user among a plurality of users connected to a LAN or the Internet transmits information to a specific user, It refers to a service that spreads to a large number of users in the form of a relay (Bucket Relay).

The multicast service includes a single-cast service (Unicast) for providing information only to a specific individual and a group-call for providing information to an unspecified majority, that is, a broadcast Broadcast).

Korean Patent Registration No. 10-0323770 (filed Jan. 25, 2002) discloses a technique of using a periodic multicast control channel and an aperiodic multicast channel as transmission channels for flexible radio resource management.

As shown in FIG. 1, the existing multicast uses a constant fixed power regardless of the number of users in the multicast group. However, if multicast is supported using fixed power regardless of the number of users in a multicast group, power consumption of the system increases, which is disadvantageous in terms of energy efficiency.

In addition, as shown in FIG. 2, the existing multicast has a multicast coverage for the entire coverage of the base station (BS) to ensure the fairness of all group users existing within the same coverage. That is, the path loss experienced by the entire user to support a service with the same quality of service (QoS) for a user with a poor channel state becomes severe, which may result in a decrease in throughput .

A multicast transmission method and a communication system capable of maximizing energy efficiency by appropriately adjusting power according to the number of users of a multicast group are provided.

A multicast transmission method and a communication system capable of minimizing a path loss and improving an overall throughput in consideration of the number of users of a multicast group and a channel state of a user are provided.

A computer-implemented multicast transmission method comprising: calculating a power maximizing multicast energy efficiency according to the number of user terminals in a multicast group; And multicasting data into the multicast group by setting the calculated power as a multicast transmission power.

According to an aspect of the present invention, the step of calculating a power maximizing the multicast energy efficiency may obtain a CML (Continuous Modulation Level) power through a Lagrangian algorithm in order to maximize the multicast energy efficiency.

According to another aspect, calculating power to maximize the multicast energy efficiency may include calculating a power of a discrete modulation level (DML) through a heuristic search algorithm to maximize the multicast energy efficiency .

A computer-implemented multicast transmission method, comprising: calculating an expected distance between a user terminal and a user terminal having a channel state of a level lower than a predetermined level; And multicasting the data to the multicast group by setting the expected distance to the multicast coverage.

According to an aspect of the present invention, the step of calculating the expected distance from the user terminal may further include: dividing a cumulative distribution function of the user terminal into a probability density function (Probability Density Function) And the expected distance can be obtained using the probability density function.

A computer-implemented multicast transmission method comprising: calculating a power maximizing multicast energy efficiency according to the number of user terminals in a multicast group; Calculating an expected distance between the user terminal and the user terminal in the multicast group, the channel state of which is lower than a predetermined level; And setting the calculated power to a multicast transmission power and setting the expected distance to a multicast coverage.

At least one program loaded memory; And at least one processor, wherein the at least one processor calculates power to maximize multicast energy efficiency according to the number of user terminals of the multicast group under the control of the program; And multicasting data to the multicast group by setting the calculated power as a multicast transmission power.

At least one program loaded memory; And at least one processor, wherein the at least one processor calculates power to maximize multicast energy efficiency according to the number of user terminals of the multicast group under the control of the program; Calculating an expected distance between the user terminal and the user terminal in the multicast group; And setting the calculated power as a multicast transmission power and setting the estimated distance as a multicast coverage.

According to the embodiment of the present invention, the energy efficiency can be improved by adjusting the power to maximize the energy efficiency according to the number of users of the multicast group and changing the multicast coverage according to the number of users.

According to the embodiment of the present invention, by calculating an expected distance for a user having a bad channel state and using it as multicast coverage, the influence of the path loss can be reduced more than when covering the entire cell, You can help.

1 is an exemplary diagram for explaining a general multicast power management method.
2 is an exemplary diagram for explaining a general multicast coverage setting method.
3 is an exemplary diagram illustrating the definition of energy efficiency of a wireless network.
4 is a flow diagram illustrating an energy efficient multicast method in one embodiment of the present invention.
FIGS. 5 and 6 show the results of multicast energy efficiency according to transmission power.
7 is a block diagram illustrating an internal configuration of a communication system for transmitting data in a multicast transmission method according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

The present embodiment relates to a multicast transmission method and a communication system via wireless access networks and can be applied to a communication system for transmitting data to a plurality of nodes through a multicast transmission scheme .

In this specification, 'communication system' may mean a network and a network, or a communication relay system connecting a network and a terminal, or a terminal and a terminal, or an upper system controlling a communication relay system. Here, the communication system may refer to all stations having cell coverage such as an access point (AP), a base station (BS), a radio access station (RAS), and the like. (wibro access point), repeater, and so on. Hereinafter, the BS will be described as a typical example of the communication system.

The 'user' may include a subscriber station (SS) such as a mobile terminal that receives data from a communication system as a terminal of a service user. In this case, the node may refer to all wireless terminals having a certain radius boundary such as cell coverage.

3 is a diagram for explaining energy efficiency of a wireless network.

The energy efficiency can be defined as the sum of the throughputs of all users in the cell coverage and the ratio of the total power used by the base station (BS) (Equation 1).

The above-mentioned concept of energy efficiency is defined in the International Telecommunication Union-Telecommunication Standardization Sector (ITU-T) standard, which is an international telecommunication standard, and in the GreenTouch, which is leading the recent green network research.

In this embodiment, an energy efficient power management (EEPM) technology is proposed in terms of energy.

4 is a flow diagram illustrating an energy efficient multicast method in one embodiment of the present invention. The energy efficient multicast method according to one embodiment may be performed by the communication system described below.

)를 구할 수 있다(수학식 3).In step S401, the communication system may calculate an expected distance through a probability of a distance from a base station of a worst channel user to a multicast coverage. At this time, the communication system can distinguish a user terminal whose channel status is below a certain level as a user with a bad channel state by using the SNR between the base station and the terminal, and the known algorithms can be applied to check the channel status. This is because users who are far away from each other within the cell coverage based on the base station are regarded as users with poor channel status because only the path loss is considered on the system model and the reception SNR decreases as the distance from the base station increases. For example, the communication system obtains a PDF (Probability Density Function) by differentiating a CDF (Cumulative Distribution Function) of a user with a poor channel state (Equation 2) (expected multicast coverage)

) (Equation 3).

는 셀 내의 유저들이 모두 기지국과의 반경 x 안에 있을 확률을 의미하고 D_w=max{d₁,d₂,..,d_L}를 의미하며 이로부터 L명의 유저 각각의 기지국과의 거리 중 가장 멀리 떨어진 유저의 거리를 찾을 수 있다. 또한, d_c는 기지국의 셀 커버리지를 의미한다. 따라서, 셀 내의 모든 유저들이 커버리지의 반경 x 안에 있을 확률을 정의하면 수학식 2와 같다.here,

Denotes the probability that all the users in the cell are within the radius x of the base station and D _w = max {d ₁ , d ₂ , .., d _L } You can find the distance of the user who is far away. Also, d _c means cell coverage of the base station. Thus, defining the probability that all users in a cell are within the radius x of coverage is given by Equation 2.

Through the CDF obtained from Equation (2), a differential PDF can be obtained and the average coverage to be covered by multicast can be obtained as an integral.

In step S402, the communication system can manage the energy efficiency by adjusting the power to maximize the energy efficiency according to the number of users of the multicast group. (1) CML (Continuous Modulation Level) of theoretical upper bound using Shannon's law and (2) Signal-to-Noise Ratio (SNR) in power management to maximize energy efficiency. (DML) of a realistic approach that communicates according to the actual LTE-A frame structure by selecting the modulation suitable for the mobile terminal.

At this time, the communication system can formulate an optimization problem maximizing MEE (Multicast Energy Efficiency) when performing power management with CML as Equation (4).

Equation (1) in Equation (4) is an optimization problem for finding P _t that maximizes the MEE with an MEE equation for obtaining energy efficiency according to P _t through various processes. (2) is the condition that P _t should be smaller than the maximum value of transmit power available in the base station, (3) is the condition that the reception SNR according to P _t is Which is greater than the threshold.

In order to solve the optimization problem, a Lagrangian form (L) can be set as shown in Equation (5).

의 값이 나오게 된다. 즉,

<P_t<

와 같이 정리가 되고, 이를 통해 라그랑지안 승수(multiplier)(λ₁,λ₂)를 통해 라그랑지안 폼으로 변형시켜 최적화 문제를 풀 수 있다.If the conditional expressions (2) and (3) in the expression (4) are summarized,

The value of < / RTI &gt; In other words,

<P _t <

(Λ ₁ , λ ₂ ) to solve the optimization problem by transforming into the Lagrangian form through the Lagrangian multiplier (λ ₁ , λ ₂ ).

Therefore, the transmission power of the base station (BS) maximizing the MEE can be found through the Lagrangian algorithm (Equation 6).

)를 통해 P_t와 λ값을 업데이트 하면서 수학식 4의 최적화 문제를 해결할 수 있다.The Lagrangian form and step size defined above (

) To solve the optimization problem of Equation (4) while updating P _t and lambda values.

On the other hand, in the DML for power management, since the modulation level is discrete, an optimization approach such as the CML case can not be used. Therefore, the communication system should find the optimal power by presenting the heuristic search algorithm when performing power management with DML. Table 1 shows the multicast energy-efficient power management algorithms.

<P_t<

)에 맞으면 MEE를 계산하여 조건에 만족하는 변조 레벨 중 MEE가 가장 큰 것을 선택하여 그에 해당하는 전력을 리턴 하는 방식이다.The algorithm of Table 1 calculates the received SNR according to each modulation when circuit power (P _c ), the number of users in the multicast group (L), the number of modulation levels (N) If the transmission power exceeds the condition of the if statement (

<P _t <

), The MEE is calculated to select the modulation level having the largest MEE among the modulation levels satisfying the condition, and the corresponding power is returned.

FIGS. 5 and 6 are the results of comparing MEE with using the optimal power determined according to the number of users in the multicast group and using the maximum power and the minimum power available in the base station (BS). FIG. 5 shows MEE comparison results for CML, and FIG. 6 shows MEE comparison results for DML.

According to the above-mentioned comparison result, it is found that both the CML-based power management and the DML-based power management have the highest MEE of supporting the multicast resource using the optimal power determined according to the number of users of the multicast group .

7 is a block diagram illustrating an internal configuration of a communication system for transmitting data in a multicast transmission method according to an embodiment of the present invention.

7, the communication system according to an embodiment may include a processor 700 and a memory 701 including a setting unit 710 and a transmitting unit 720. [

The memory 701 may store a program including a command for selecting a multicast transmission scheme and transmitting data. The processes of the multicast transmission method described with reference to Figs. 3 to 6 can be executed by a program stored in the memory 701. [ For example, the memory 701 may be a hard disk, an SSD, an SD card, and other storage media.

The setting unit 710 sets the coverage and transmission power for the multicast transmission in consideration of the number of users in the multicast group and the channel state of the user. At this time, the setting unit 710 may calculate a predicted distance based on a probability of a distance from a base station of a user having a bad channel state, and set the calculated distance as a coverage for multicast transmission. In addition, the setting unit 710 may determine the power that maximizes the energy efficiency according to the number of users of the multicast group, and then set the power to the multicast transmission power. For example, the setting unit 710 can obtain a CML-based transmission power maximizing the MEE using a Lagrangian algorithm. As another example, the setting unit 710 may use the heuristic search algorithm to obtain the DML-based transmit power maximizing the MEE.

The transmitter 720 can transmit data to users in a multicast manner in an optimal environment by applying multicast coverage and transmission power determined by the setting unit 710. In other words, the transmitter 720 can service multicast transmissions with optimal coverage and transmit power with maximum energy efficiency for power consumption and throughput.

The above-described multicast transmission method may include more shortened operations or additional operations based on the details described with reference to Figs. In addition, more than one operation may be combined, and the order or location of the operations may be changed.

The methods according to embodiments of the present invention may be implemented in the form of a program instruction that can be executed through various computer systems and recorded in a computer-readable medium.

As described above, according to the embodiment of the present invention, the energy efficiency can be improved by adjusting the power to maximize the energy efficiency according to the number of users of the multicast group and changing the multicast coverage according to the number of users. In addition, according to the embodiment of the present invention, by calculating a predicted distance to a user with a poor channel state and using it as multicast coverage, the influence of path loss can be reduced more than when covering the entire cell, You can give.

The apparatus described above may be implemented as a hardware component, a software component, and / or a combination of hardware components and software components. For example, the apparatus and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA) , A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing unit may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device , Or may be permanently or temporarily embodied in a transmitted signal wave. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions to be recorded on the medium may be those specially designed and configured for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI &gt; or equivalents, even if it is replaced or replaced.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

710:
720:

Claims (11)

delete A computer-implemented multicast transmission method comprising:
Calculating power that maximizes multicast energy efficiency according to the number of user terminals of the multicast group; And
Multicasting data into the multicast group by setting the calculated power as a multicast transmission power
Lt; / RTI &gt;
Wherein calculating the power maximizing the multicast energy efficiency comprises:
In order to maximize the multicast energy efficiency, the CML (Continuous Modulation Level) power is obtained through a Lagrangian algorithm
The multicast transmission method comprising: A computer-implemented multicast transmission method comprising:
Calculating power that maximizes multicast energy efficiency according to the number of user terminals of the multicast group; And
Multicasting data into the multicast group by setting the calculated power as a multicast transmission power
Lt; / RTI &gt;
Wherein calculating the power maximizing the multicast energy efficiency comprises:
In order to maximize the multicast energy efficiency, a power of DML (Discrete Modulation Level) is obtained through a heuristic search algorithm
The multicast transmission method comprising: delete A computer-implemented multicast transmission method comprising:
Calculating an expected distance with a user terminal whose channel status is below a certain level; And
Multicasting data into a multicast group by setting the expected distance to multicast coverage
Lt; / RTI &gt;
Wherein calculating the expected distance from the user terminal comprises:
Calculating a probability density function indicating a distance probability with the user terminal by differentiating a cumulative distribution function of the user terminal and obtaining the estimated distance using the probability density function;
The multicast transmission method comprising: delete A computer-implemented multicast transmission method comprising:
Calculating power that maximizes multicast energy efficiency according to the number of user terminals of the multicast group;
Calculating an expected distance between the user terminal and the user terminal in the multicast group, the channel state of which is lower than a predetermined level; And
Setting the calculated power to a multicast transmission power and setting the expected distance to a multicast coverage
Lt; / RTI &gt;
Wherein calculating the power maximizing the multicast energy efficiency comprises:
In order to maximize the multicast energy efficiency, the CML (Continuous Modulation Level) power is obtained through a Lagrangian algorithm
The multicast transmission method comprising: A computer-implemented multicast transmission method comprising:
Calculating power that maximizes multicast energy efficiency according to the number of user terminals of the multicast group;
Calculating an expected distance between the user terminal and the user terminal in the multicast group, the channel state of which is lower than a predetermined level; And
Setting the calculated power to a multicast transmission power and setting the expected distance to a multicast coverage
Lt; / RTI &gt;
Wherein calculating the power maximizing the multicast energy efficiency comprises:
In order to maximize the multicast energy efficiency, a power of DML (Discrete Modulation Level) is obtained through a heuristic search algorithm
The multicast transmission method comprising: 9. The method according to claim 7 or 8,
Wherein calculating the expected distance from the user terminal comprises:
Calculating a probability density function indicating a distance probability with the user terminal by differentiating a cumulative distribution function of the user terminal and obtaining the estimated distance using the probability density function;
The multicast transmission method comprising: At least one program loaded memory; And
At least one processor
Lt; / RTI &gt;
Wherein the at least one processor, under control of the program,
Calculating a power maximizing multicast energy efficiency according to the number of user terminals of the multicast group; And
Multicasting data to the multicast group by setting the calculated power as a multicast transmission power
Lt; / RTI &gt;
Calculating a power for maximizing the multicast energy efficiency,
In order to maximize the multicast energy efficiency, the CML (Continuous Modulation Level) power is obtained through a Lagrangian algorithm or the DML (Discrete Modulation Level) power is obtained through a heuristic search algorithm
. At least one program loaded memory; And
At least one processor
Lt; / RTI &gt;
Wherein the at least one processor, under control of the program,
Calculating a power maximizing multicast energy efficiency according to the number of user terminals of the multicast group;
Calculating an expected distance between the user terminal and the user terminal in the multicast group; And
Setting the calculated power as a multicast transmission power and setting the expected distance as a multicast coverage
Lt; / RTI &gt;
Calculating a power for maximizing the multicast energy efficiency,
In order to maximize the multicast energy efficiency, a CML (Continuous Modulation Level) power is obtained through a Lagrangian algorithm or a DML (Discrete Modulation Level) power is obtained through a heuristic search algorithm that
.

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