KR102388683B1 - Method and apparatus for transmission and power allocation for multi-user downlink system compensating nonlinear distortion of power amplifier - Google Patents

Abstract

A method and apparatus for transmitting and allocating power in a multi-user downlink system for compensating for distortion of a nonlinear power amplifier are provided. According to an embodiment, a transmitting apparatus of a multi-user downlink system to which a nonlinear power amplifier is applied includes: a power allocating apparatus for allocating power by adjusting transmit power; and a beamforming optimization apparatus for optimizing a precoding vector to optimize beamforming based on the allocated power, and may compensate for distortion of the nonlinear power amplifier by optimizing the precoding vector.

Description

Transmission and power allocation method and apparatus of a multi-user downlink system compensating for distortion of a nonlinear power amplifier

The following embodiments relate to a transmission method of a multi-antenna communication system, and more particularly, to a method and apparatus for transmitting and allocating power in a multi-user downlink system for compensating for distortion of a nonlinear power amplifier.

Among devices constituting an RF chain (Radio Frequency chain) of a communication system, a power amplifier serves to amplify an output signal so that a transmission signal is transmitted to a receiver. The input-output relationship of a power amplifier generally has a non-linear relationship, and in general, a power amplifier having a large amplification gain and high power efficiency tends to have a more severe non-linear characteristic.

The nonlinearity of the power amplifier applied to the multi-antenna system distorts the size of the signal output from each antenna to have a different gain, thereby distorting the beamforming result, reducing the size of the received signal, and increasing the generated distortion signal.

In a multi-user system, interference between streams transmitted to each user occurs, and controlling such interference is an important issue. In addition, in a nonlinear multi-antenna system, additional distortion due to nonlinearity occurs, and inter-stream interference and distortion must be simultaneously controlled.

Therefore, it is necessary to develop a transmission technique and a power allocation technique that reflect the nonlinearity of the power amplifier.

US Patent Publication No. US20160142922 relates to such a Transceiver Architecture for Multiple Antenna Systems (transceiver design for a multiple antenna system), and describes a technique for separately designing a transmission/reception beamformer using feedback information in an OFDM channel environment.

US Patent Publication No. US20160142922

The embodiments describe a method and apparatus for transmitting and allocating power in a multi-user downlink system for compensating for distortion of a nonlinear power amplifier. More specifically, the precoding optimization process consists of repeating the precoding optimization process and the power allocation process. The process updates the precoding matrix in anticipation of the distortion signal value, and the power allocation process provides a technique for updating the power allocation result in the direction of maximizing the total transmission rate of the nonlinear downlink system.

The embodiments solve the problem of interference and distortion in multi-user systems caused by nonlinearity by repeatedly updating the two values through precoding and power allocation methods, and maximize network transmission speed by allocating power appropriately. An object of the present invention is to provide a method and apparatus for transmitting and allocating power in a multi-user downlink system for compensating for distortion of a nonlinear power amplifier.

According to an embodiment, a transmitting apparatus of a multi-user downlink system to which a nonlinear power amplifier is applied includes: a power allocating apparatus for allocating power by adjusting transmit power; and a beamforming optimization apparatus for optimizing a precoding vector to optimize beamforming based on the allocated power, and may compensate for distortion of the nonlinear power amplifier by optimizing the precoding vector.

The power allocation result and the precoding vector may be updated by alternately and repeatedly using the power allocation apparatus and the beamforming optimization apparatus.

The power allocator may repeatedly update power in a direction to maximize the transmission rate.

The power allocator derives a power update equation from a stationarity condition, updates a power allocation result through the power update equation, and updates a Lagrangian multiplier can be repeated.

The power allocation apparatus may include: a power allocation vector update unit configured to update a power allocation vector for each user from a given Lagrange multiplier; a total power calculation unit for calculating a sum of power allocation results based on the power allocation vector; and updating the Lagrange multiplier through the minimum and maximum values of the Lagrange multipliers, and when the sum of the power allocation results exceeds a power constraint condition, substituting the Lagrange multipliers into the minimum value, and the sum of the power allocation results is the power constraint When the condition is not exceeded, a Lagrange multiplier update unit for substituting the Lagrange multiplier into a maximum value may be included.

The apparatus for optimizing beamforming includes: an antenna allocation power calculator configured to calculate power allocated to all antennas; a linear coefficient calculator for calculating a linearity coefficient for each antenna from the calculated power; a nonlinear function approximation unit for approximating a distortion phenomenon due to the nonlinearity based on the linear coefficients to a nonlinear function with respect to the precoding vector of each user; and a precoding vector updater configured to update the precoding vector by using a parameter calculated through approximation of the nonlinear function.

Here, before approximating the nonlinear function, and after arbitrarily transforming the precoding vector, the method further comprises a precoding transformation value and an expected distortion signal value calculator for calculating an expected distortion signal value, and calculating the distortion signal value Thus, the nonlinear function can be approximated.

In addition, the apparatus for optimizing beamforming includes: an antenna allocation power calculator configured to calculate power allocated to all antennas; a linear coefficient calculator for calculating a linearity coefficient for each antenna from the calculated power; a precoding transformation value and predicted distortion signal value calculator for calculating a distortion value of the precoding vector of a k-th user and calculating an expected distortion signal value from the calculated transformation value of the precoding vector; a nonlinear function approximator for calculating a least squares solution from the distortion value of the precoding vector and the distortion signal value and approximating it to a polynomial function; and a precoding vector update unit that aligns a polynomial parameter calculated through approximation of the nonlinear function into a matrix and updates the precoding vector from the matrix of polynomial parameters.

According to another embodiment, a transmission method of a multi-user downlink system to which a nonlinear power amplifier implemented by a computer device is applied includes: allocating power by adjusting transmission power; and optimizing a precoding vector to optimize beamforming based on the allocated power, wherein the precoding vector may be optimized to compensate for distortion of the nonlinear power amplifier.

By alternately performing the allocating power and optimizing the precoding vector, the power allocation result and the precoding vector may be updated.

The allocating power may include deriving a power update equation from a stationarity condition, updating a power allocation result through the power update equation, and updating a Lagrangian multiplier. the process can be repeated.

The allocating power may include: initializing a minimum value and a maximum value of a Lagrangian multiplier; updating the Lagrange multiplier through the minimum and maximum values of the Lagrange multiplier; updating a power allocation vector for each user from the given Lagrange multiplier; calculating a sum of power allocation results based on the power allocation vector; and when the sum of the power allocation results exceeds a power constraint, the Lagrange multiplier is substituted into a minimum value, and when the sum of the power allocation results does not exceed the power constraint, the Lagrange multiplier is substituted into a maximum value. may include steps.

The optimizing the precoding vector may include calculating power allocated to all antennas; calculating a linearity coefficient for each antenna from the calculated power; approximating the distortion phenomenon due to the nonlinearity based on the linear coefficients with a nonlinear function for the precoding vector of each user; and updating the precoding vector using a parameter calculated through approximation of the nonlinear function.

Here, before approximating to the nonlinear function, the method may further include calculating an expected distortion signal value after arbitrarily transforming the precoding vector, and calculating the distortion signal value to approximate the nonlinear function .

In addition, optimizing the precoding vector may include calculating power allocated to all antennas; calculating a linearity coefficient for each antenna from the calculated power; calculating a transformation value of the precoding vector of a k-th user; calculating an expected distortion signal value from the calculated transformation value of the precoding vector; calculating a least square solution from the distortion value of the precoding vector and the distortion signal value and approximating it to a polynomial function; arranging a polynomial parameter calculated through approximation of the nonlinear function into a matrix; and updating the precoding vector from the matrix of polynomial parameters.

According to embodiments, by repeatedly updating two values through precoding and power allocation method, interference and distortion problems in a multi-user system caused by nonlinearity are solved, and power is appropriately allocated to maximize network transmission speed It is possible to provide a method and apparatus for transmitting and allocating power in a multi-user downlink system for compensating for distortion of a nonlinear power amplifier.

1 is a diagram for explaining the concept of a multi-antenna system to which a nonlinear power amplifier according to an embodiment is applied.
2 is a block diagram illustrating a configuration of a multi-antenna system to which a nonlinear power amplifier is applied according to an embodiment.
3 is a flowchart illustrating a transmission method of a multi-user downlink system to which a nonlinear power amplifier is applied according to an embodiment.
4 is a flowchart illustrating a method of allocating power according to an embodiment.
5 is a flowchart illustrating a method of optimizing a precoding vector according to an embodiment.
6 illustrates a result of measuring the overall total transmission speed performance of a network through a transmission method according to an embodiment.

Hereinafter, embodiments will be described with reference to the accompanying drawings. However, the described embodiments may be modified in various other forms, and the scope of the present invention is not limited by the embodiments described below. In addition, various embodiments are provided in order to more completely explain the present invention to those of ordinary skill in the art. The shapes and sizes of elements in the drawings may be exaggerated for clearer description.

The following embodiments consider a multi-user multiple input multiple output (MU-MIMO) communication system in which a nonlinear power amplifier is applied to a transmitter.

The nonlinearity of the power amplifier generates different amplification gains in the output signals of each antenna of the multiple antennas and distorts the beamforming result, thereby attenuating the magnitude of the signal received at the receiver and increasing the magnitude of the distortion signal.

In order to design a power-efficient multi-antenna system, a power amplifier having a strong nonlinearity instead of a strong amplification gain should be introduced, and a signal processing and power allocation technique capable of compensating for signal distortion caused by this is required.

1 is a diagram for explaining the concept of a multi-antenna system to which a nonlinear power amplifier is applied according to an embodiment.

1, to explain the concept of a multi-user multi-antenna system to which the nonlinear power amplifier 101 is applied, the transmission device 100 of the multi-antenna system is a power allocation device for adjusting transmission power; 110) and a beamforming optimizer 120 that optimizes beamforming based on the adjusted power.

In this embodiment, a method of maximizing the ratio of the correlation signal to the distortion signal and noise by dividing the received signal into a correlation signal and a distortion signal correlated with the transmission signal may be used.

In order to simultaneously alleviate the interference problem between users occurring in a downlink system in which multiple users 102 exist and a distortion phenomenon caused by the nonlinearity of the power amplifier 101, the signal contrast of each user 102 A precoding vector can be designed to maximize interference and distortion and a signal-to-interference-plus-distortion-plus-noise ratio.

Since the distortion due to non-linearity is expressed as a function of the precoding vectors of all users 102 , the distortion component is inputted to each user 102 precoding vector as an input to eliminate mutual coupling that occurs. A method of approximation with a quadratic function can be used.

Power allocation may use an iterative water-filling method. An update equation is derived from the stationarity condition of the system in which the nonlinear power amplifier 101 is introduced, and the power allocation result is a power update equation for a given Lagrangian multiplier. can induce Lagrangian can be updated iteratively through bisection.

The proposed transmission and power allocation method (hereinafter, simply referred to as a transmission method) can iteratively update two values through the precoding and power allocation methods described above.

2 is a block diagram illustrating a configuration of a multi-antenna system to which a nonlinear power amplifier is applied according to an embodiment.

Referring to FIG. 2 , a detailed configuration of each device constituting a multi-antenna system to which a nonlinear power amplifier is applied is shown. That is, each detailed configuration of the beamforming optimization apparatus 220 and the power allocation apparatus 210 is shown. The power allocation apparatus 210 and the beamforming optimization apparatus 220 may update the power allocation result and the precoding vector through respective algorithms. The proposed system can update the precoding vector and the power allocation result by alternately and repeatedly using the power allocation device 210 and the beamforming optimization device 220 .

More specifically, the transmission apparatus of the multi-user downlink system to which the nonlinear power amplifier according to an embodiment is applied optimizes beamforming based on the power allocator 210 for allocating power by adjusting the transmission power and the allocated power. In order to do this, the beamforming optimization device 220 for optimizing the precoding vector may be included, and distortion of the nonlinear power amplifier may be compensated for by optimizing the precoding vector.

The power allocation device 210 may include a power allocation vector update unit 211 , a total power calculation unit 212 , and a Lagrange multiplier update unit 213 , and repeatedly updates power in a direction to maximize the transmission speed. can do.

The power allocation vector update unit 211 may update the power allocation vector for each user from the given Lagrange multiplier.

The total power calculator may calculate a sum of power allocation results based on the power allocation vector.

The Lagrange multiplier update unit 213 updates the Lagrange multiplier through the minimum and maximum values of the Lagrange multiplier, and when the sum of the power allocation results exceeds the power constraint condition, substitutes the Lagrange multiplier into the minimum value, and the sum of the power allocation results If this power constraint is not exceeded, the Lagrange multiplier may be substituted for the maximum value.

The beamforming optimization apparatus 220 includes an antenna allocation power calculation unit 221 , a linear coefficient calculation unit 222 , a precoding strain value and an expected distortion signal value calculation unit 223 , a nonlinear function approximation unit 224 , and a precoding unit. A vector update unit 225 may be included. The beamforming optimization apparatus 220 may compensate for distortion of the nonlinear power amplifier by optimizing the precoding vector.

The antenna allocation power calculation unit 221 may calculate power allocated to all antennas.

The linear coefficient calculator 222 may calculate a linearity coefficient for each antenna from the calculated power.

The precoding deformation value and expected distortion signal value calculator 223 may calculate an expected distortion signal value after arbitrarily transforming the recording vector. Thereafter, the nonlinear function may be approximated by calculating the distortion signal value. More specifically, the precoding deformation value and expected distortion signal value calculation unit 223 may calculate a deformation value of the k-th user's precoding vector, and calculate an expected distortion signal value from the calculated deformation value of the precoding vector. there is.

The nonlinear function approximation unit 224 may approximate a distortion phenomenon due to nonlinearity based on linear coefficients as a nonlinear function for each user's precoding vector. More specifically, the nonlinear function approximation unit 224 may calculate a least squares solution from the deformation value of the precoding vector and the distortion signal value and approximate it as a polynomial function.

The precoding vector updater 225 may update the precoding vector by using a parameter calculated through approximation of the nonlinear function. More specifically, the precoding vector updater 225 may align a polynomial parameter calculated through approximation of a nonlinear function into a matrix, and update the precoding vector from the matrix of polynomial parameters.

Here, the power allocation result and the precoding vector may be updated by repeatedly using the power allocation apparatus 210 and the beamforming optimization apparatus 220 alternately.

Hereinafter, a transmission apparatus of a multi-user downlink system to which a nonlinear power amplifier according to an embodiment is applied will be described in more detail.

The transmission method of the multi-user downlink system to which the nonlinear power amplifier is applied according to an embodiment may be described in more detail with the example of the transmitting apparatus described with reference to FIG. 2 .

3 is a flowchart illustrating a transmission method of a multi-user downlink system to which a nonlinear power amplifier is applied according to an embodiment.

Referring to FIG. 3 , in the transmission method of a multi-user downlink system to which a nonlinear power amplifier implemented by a computer device according to an embodiment is applied, the step of allocating power by adjusting the transmission power (S110), and the allocated power and optimizing the precoding vector in order to optimize beamforming based on it ( S120 ), and by optimizing the precoding vector, the distortion of the nonlinear power amplifier may be compensated.

In step S110 , the power allocator 210 may allocate power by adjusting the transmission power.

In operation S120 , the beamforming optimization apparatus 220 may optimize a precoding vector to optimize beamforming based on the allocated power.

Here, the power allocation result and the precoding vector may be updated by alternately performing the allocating power of the power allocating apparatus 210 and optimizing the precoding vector of the beamforming optimizing apparatus 220 repeatedly. .

4 is a flowchart illustrating a method of allocating power according to an embodiment.

Referring to FIG. 4 , the step of allocating power (S110) includes initializing the minimum and maximum values of the Lagrange multiplier (S111), updating the Lagrange multiplier through the minimum and maximum values of the Lagrange multiplier (S112); Updating the power allocation vector for each user from the given Lagrange multiplier (S113), calculating the sum of the power allocation vector-based power allocation results (S114), and the sum of the power allocation results exceeding the power constraint case, substituting the Lagrange multiplier into the minimum value, and substituting the Lagrange multiplier into the maximum value when the sum of the power allocation results does not exceed the power constraint condition (S115).

The method of allocating power according to an embodiment may be performed through the power allocating device 210, and as described above, the power allocating device 210 includes the power allocation vector updater 211 and the total power calculator ( 212) and a Lagrange multiplier update unit 213 may be included.

The power allocation process consists of a process of deriving a power update equation from a stationarity condition, updating the power allocation result through this, and repeating the process of updating the Lagrangian multiplier. can

The power allocation process may repeat the following process.

은 0, 최대값은

로 초기화할 수 있다.In step S111, first, the Lagrange multiplier update unit 213 sets the minimum value of the Lagrangian multiplier.

is 0, the maximum value is

can be initialized with

를 라그랑주 승수의 최소값 및 최대값을 통해 다음과 같이 업데이트할 수 있다.In step S112 , the Lagrange multiplier update unit 213 performs the Lagrange multiplier

can be updated as follows through the minimum and maximum values of the Lagrange multipliers.

[Equation 1]

로부터 각 사용자에 대해, 전력 할당 벡터를 업데이트할 수 있다. 전력 업데이트 공식(power update equation)

는 정상성 조건(stationarity condition)을 각 사용자의 전력에 대해 편미분하여 얻을 수 있으며, 다음 식과 같이 나타낼 수 있다.In step S113, the power allocation vector update unit 211 is

For each user, we can update the power allocation vector. power update equation

can be obtained by partial differentiation of the stationarity condition with respect to the power of each user, and can be expressed as the following equation.

[Equation 2]

는 업데이트(update)의 속도를 조절하는 파라미터(parameter)이다.here,

is a parameter that controls the speed of update.

를 증가시키며 전력(power)이 수렴할 때까지 반복할 수 있다.the above process

can be repeated until the power converges.

In step S114 , the total power calculator 212 may calculate the sum of the power allocation results based on the power allocation vector.

를 초과하였으면, 현재의

를

에 대입하며, 초과하지 않을 경우 현재의

를

에 대입할 수 있다.Thereafter, in step S115 , the Lagrange multiplier updater 213 determines that the sum of the power allocation results is a power constraint condition.

If it exceeds, the current

cast

, and if it does not exceed the current

cast

can be substituted into

이하로 만족될 때 알고리즘을 종료하며, 이는 다음 식과 같이 나타낼 수 있다.Complementary Slackness Condition is a certain threshold for the above process.

The algorithm is terminated when the following are satisfied, which can be expressed as the following equation.

[Equation 3]

5 is a flowchart illustrating a method of optimizing a precoding vector according to an embodiment.

Referring to FIG. 5 , the optimizing the precoding vector ( S120 ) includes calculating power allocated to all antennas ( S121 ), and calculating a linearity coefficient for each antenna from the calculated power ( S122 ). ), calculating the distortion value of the k-th user's precoding vector (S123), calculating an expected distortion signal value from the calculated transformation value of the precoding vector (S124), the distortion value and distortion of the precoding vector calculating a least squares solution from the signal value and approximating it to a polynomial function (S125), arranging the polynomial parameter calculated through approximation of the nonlinear function into a matrix (S126), and from the matrix of polynomial parameters It may include updating the precoding vector (S127).

Meanwhile, according to another embodiment, the step of optimizing the precoding vector (S120) includes calculating power allocated to all antennas (S121), calculating a linearity coefficient for each antenna from the calculated power ( S122), approximating the distortion phenomenon due to nonlinearity based on linear coefficients to a nonlinear function for each user's precoding vector (S125), and precoding using a parameter (S126) calculated through approximation of the nonlinear function It may include updating the vector (S127). Here, before approximating to a non-linear function, after arbitrarily transforming the precoding vector (S123), the method further includes a step (S124) of calculating an expected distortion signal value, and calculating the distortion signal value to approximate the non-linear function. can

Hereinafter, a method of optimizing a precoding vector according to an embodiment will be described in more detail with an example. Meanwhile, the beamforming optimization apparatus 220 includes an antenna allocation power calculation unit 221 , a linear coefficient calculation unit 222 , a precoding strain value and an expected distortion signal value calculation unit 223 , a nonlinear function approximation unit 224 and It may include a precoding vector updater 225 .

The beamforming optimization apparatus 220 may optimize the precoding vector with respect to the currently given power allocation result. The beamforming optimization process is shown below. The following process can be repeated for all users.

을 계산할 수 있으며, 다음 식과 같이 나타낼 수 있다.In step S121 , the antenna allocation power calculation unit 221 calculates the power allocated to all antennas.

can be calculated, and can be expressed as

[Equation 4]

를 계산할 수 있으며, 다음 식과 같이 나타낼 수 있다.In step S122, the linear coefficient calculator 222 calculates a linearity coefficient for each antenna from the calculated power.

can be calculated, and can be expressed as

[Equation 2]

,

,

을 계산할 수 있다. 이는 여러 방법으로 가능하며, 임의의 scaling으로 할 수 있다. k 번째 사용자의 프리코딩 벡터의 변형 값을 다음 식과 같이 나타낼 수 있다.And, in step S123, three variant values of the k-th user's precoding vector

can be calculated. This can be done in several ways, with arbitrary scaling. The transformation value of the k-th user's precoding vector can be expressed as the following equation.

[Equation 5]

을 계산할 수 있다.In step S124, the precoding deformation value and expected distortion signal value calculator 223 calculates a distortion signal value expected from the calculated deformation value of the precoding vector.

can be calculated.

In step S125, the nonlinear function approximation unit 224 may calculate a least squares solution from the calculated precoding vector and the distortion signal value and approximate it with a polynomial function, which may be expressed as the following equation.

[Equation 6]

을 행렬로 정렬하여

를 계산할 수 있으며, 다음 식과 같이 나타낼 수 있다.In step S126, the precoding vector update unit 225 obtains the polynomial parameter

by sorting in a matrix

can be calculated, and can be expressed as

[Equation 7]

In step S127, the precoding vector update unit 225 may update the precoding vector from the obtained parameter matrix as follows.

[Equation 8]

는 정규화 상수이다.here,

is a regularization constant.

를 증가시키며 수렴할 때까지 반복할 수 있다.the above process

can be repeated until convergence is increased.

By repeating the above-described beamforming optimization process and power allocation process, the entire process may be terminated when the maximum number of iterations is exceeded or the precoding and power allocation results converge.

Through the above process, it is possible to solve the problem of interference and distortion in multi-user systems caused by nonlinearity, and to maximize network transmission speed by properly allocating power. Through the present embodiments, it is possible to configure a multi-user network with high power efficiency by introducing a nonlinear power amplifier to a base station and a repeater.

6 illustrates a result of measuring the overall total transmission speed performance of a network through a transmission method according to an embodiment.

As shown in FIG. 6 , the embodiments may maximize the transmission speed through optimization and power allocation of a multi-user downlink beamforming system to which a nonlinear power amplifier is applied. In addition, according to embodiments, it is possible to simultaneously solve an interference problem occurring in a multi-antenna system and a distortion problem occurring in a nonlinear system.

By greatly improving the performance of the nonlinear communication system through the embodiments and allowing a nonlinear power amplifier with high power efficiency to be applied to the communication system, it is possible to greatly reduce the production cost of the future communication system and significantly improve the power efficiency. From this, it is possible to contribute to the development of the industry by reducing the production cost of the base station and repeater, and by improving power consumption, thereby contributing to the realization of a high-density network.

The embodiments may be applied to a multi-antenna communication field using a low-power, low-cost device, and thus may be applied to reduction in production cost and power consumption of a communication system. In addition, the embodiments may be applied to reduce the production cost and power consumption of a huge array antenna system, which is noted as a promising technology of an IoT system or a distributed system or a future communication system in which power consumption reduction is essential.

The device described above may be implemented as a hardware component, a software component, and/or a combination of the hardware component and the software component. For example, devices and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), It may be implemented using one or more general purpose or special purpose computers, such as a programmable logic unit (PLU), 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. A processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For convenience of understanding, although one processing device is sometimes described as being used, one of ordinary skill in the art will recognize that the processing device includes a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that can include For example, the processing device may include a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as parallel processors.

Software may comprise a computer program, code, instructions, or a combination of one or more thereof, which configures a processing device to operate as desired or is independently or collectively processed You can command the device. The software and/or data may be any kind of machine, component, physical device, virtual equipment, computer storage medium or apparatus, to be interpreted by or to provide instructions or data to the processing device. may be embodied in The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored in one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions 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, etc. alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiment, or may be known and available to those skilled in the art of computer software. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floppy disks. - includes magneto-optical media, and hardware devices specially configured to store and execute program instructions, such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like.

As described above, although the embodiments have been described with reference to the limited embodiments and drawings, various modifications and variations are possible from the above description by those skilled in the art. For example, the described techniques are performed in an order different from the described method, and/or the described components of the system, structure, apparatus, circuit, etc. are combined or combined in a different form than the described method, or other components Or substituted or substituted by equivalents may achieve an appropriate result.

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

Claims (15)

In the transmitting apparatus of a multi-user downlink system to which a nonlinear power amplifier is applied,
a power allocator for allocating power by adjusting transmission power; and
A beamforming optimization apparatus for optimizing a precoding vector to optimize beamforming based on the allocated power
including,
The power allocating device,
a power allocation vector update unit for updating a power allocation vector for each user from a given Lagrange multiplier;
a total power calculation unit for calculating a sum of power allocation results based on the power allocation vector; and
The Lagrange multiplier is updated through the minimum and maximum values of the Lagrange multiplier, and when the sum of the power allocation results exceeds the power constraint condition, the Lagrange multiplier is substituted for the minimum value, and the sum of the power allocation results is the power constraint condition. If it does not exceed, the Lagrange multiplier update unit for substituting the Lagrange multiplier into the maximum value.
including,
Compensating for distortion of the nonlinear power amplifier by optimizing the precoding vector. According to claim 1,
Updating a power allocation result and a precoding vector by repeatedly using the power allocation device and the beamforming optimization device alternately
characterized in that, the transmitting device. According to claim 1,
The power allocating device,
Updating the power repeatedly in the direction that maximizes the transfer rate
characterized in that, the transmitting device. According to claim 1,
The power allocating device,
Deriving a power update equation from a stationarity condition, updating the power allocation result through the power update equation, and repeating the process of updating the Lagrangian multiplier
characterized in that, the transmitting device. delete In the transmitting apparatus of a multi-user downlink system to which a nonlinear power amplifier is applied,
a power allocator for allocating power by adjusting transmission power; and
A beamforming optimization apparatus for optimizing a precoding vector to optimize beamforming based on the allocated power
including,
The beamforming optimization device,
an antenna allocation power calculation unit for calculating power allocated to all antennas;
a linear coefficient calculator for calculating a linearity coefficient for each antenna from the calculated power;
a nonlinear function approximation unit for approximating a distortion phenomenon due to the nonlinearity based on the linear coefficients to a nonlinear function with respect to the precoding vector of each user; and
A precoding vector update unit that updates the precoding vector by using a parameter calculated through approximation of the nonlinear function
Including, a transmitting device. 7. The method of claim 6,
Before approximating the nonlinear function, after arbitrarily transforming the precoding vector, the precoding transformation value and expected distortion signal value calculator 223 calculates an expected distortion signal value
further comprising,
approximating the non-linear function by calculating the value of the distortion signal.
characterized in that, the transmitting device. In the transmitting apparatus of a multi-user downlink system to which a nonlinear power amplifier is applied,
a power allocator for allocating power by adjusting transmission power; and
A beamforming optimization apparatus for optimizing a precoding vector to optimize beamforming based on the allocated power
including,
The beamforming optimization device,
an antenna allocation power calculation unit for calculating power allocated to all antennas;
a linear coefficient calculator for calculating a linearity coefficient for each antenna from the calculated power;
a precoding deformation value and predicted distortion signal value calculator for calculating a deformation value of the precoding vector of the k-th user and calculating an expected distortion signal value from the calculated deformation value of the precoding vector;
a nonlinear function approximator for calculating a least squares solution from the distortion value of the precoding vector and the distortion signal value and approximating it to a polynomial function; and
A precoding vector update unit that aligns a polynomial parameter calculated through approximation of a nonlinear function into a matrix, and updates the precoding vector from the matrix of polynomial parameters
Including, a transmitting device. In the transmission method of a multi-user downlink system to which a nonlinear power amplifier implemented by a computer device is applied,
allocating power by adjusting transmit power; and
optimizing a precoding vector to optimize beamforming based on the allocated power;
including,
Allocating the power comprises:
initializing a minimum value and a maximum value of a Lagrangian multiplier;
updating the Lagrange multiplier through the minimum and maximum values of the Lagrange multiplier;
updating a power allocation vector for each user from the given Lagrange multiplier;
calculating a sum of power allocation results based on the power allocation vector; and
When the sum of the power allocation results exceeds a power constraint condition, substituting the Lagrange multiplier into a minimum value, and when the sum of the power allocation results does not exceed a power constraint condition, substituting the Lagrange multiplier into a maximum value
including,
Compensating for distortion of a nonlinear power amplifier by optimizing the precoding vector. 10. The method of claim 9,
updating the power allocation result and the precoding vector by repeatedly performing the allocating power and optimizing the precoding vector alternately
characterized in that, the transmission method. 10. The method of claim 9,
Allocating the power comprises:
Deriving a power update equation from a stationarity condition, updating the power allocation result through the power update equation, and repeating the process of updating the Lagrangian multiplier
characterized in that, the transmission method. delete In the transmission method of a multi-user downlink system to which a nonlinear power amplifier implemented by a computer device is applied,
allocating power by adjusting transmit power; and
optimizing a precoding vector to optimize beamforming based on the allocated power;
including,
Optimizing the precoding vector comprises:
calculating power allocated to all antennas;
calculating a linearity coefficient for each antenna from the calculated power;
approximating the distortion phenomenon due to the nonlinearity based on the linear coefficients with a nonlinear function for the precoding vector of each user; and
updating the precoding vector by using a parameter calculated through approximation of the nonlinear function.
Including, a transmission method. 14. The method of claim 13,
Before approximating to the non-linear function, arbitrarily transforming the precoding vector, and then calculating an expected distortion signal value.
further comprising,
approximating the non-linear function by calculating the value of the distortion signal.
characterized in that, the transmission method. In the transmission method of a multi-user downlink system to which a nonlinear power amplifier implemented by a computer device is applied,
allocating power by adjusting transmit power; and
optimizing a precoding vector to optimize beamforming based on the allocated power;
including,
Optimizing the precoding vector comprises:
calculating power allocated to all antennas;
calculating a linearity coefficient for each antenna from the calculated power;
calculating a transformation value of the precoding vector of a k-th user;
calculating an expected distortion signal value from the calculated transformation value of the precoding vector;
calculating a least square solution from the distortion value of the precoding vector and the distortion signal value and approximating it to a polynomial function;
arranging a polynomial parameter calculated through approximation of a nonlinear function into a matrix; and
updating the precoding vector from the matrix of polynomial parameters.
Including, a transmission method.

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