KR20190115817A - Beamforming Device and Method for Non-orthogonal Multiple Acecess - Google Patents

Abstract

The present invention relates to a beamforming apparatus for non-orthogonal multi-access and a method thereof, which are capable of minimizing power consumption of a base station. The method of the present invention comprises the steps of: obtaining an optimal power allocation ratio; and obtaining an optimal beam steering vector.

Description

Beamforming Device and Method for Non-Orthogonal Multiple Access

The present invention relates to a beamforming apparatus and method, and more particularly, to a beamforming apparatus and method for non-orthogonal multiple access (NOMA) in a cellular downlink supporting multiple antennas.

4G (4th generation) to meet the traffic demand in the radio data communication system increases since the commercialization trend, efforts to develop improved 5G (5 ^th generation) communication system, or pre-5G communication system have been made. For this reason, a 5G communication system or a pre-5G communication system is called a Beyond 4G Network communication system or a Long Term Evolution (LTE) system (Post LTE) system.

However, a wireless communication system based on an orthogonal frequency division multiple access scheme cannot support the high data rate and large connectivity required by the 5G mobile communication system. In addition, when transmitting information in the downlink system, in order to guarantee the minimum transmission rate of each user, the power consumption of the base station should be increased or the bandwidth should be increased. As the guaranteed minimum transmission rate increases, the required power consumption increases exponentially. There is a limit to increasing power consumption, and there is a limit to increasing bandwidth because frequency resources are limited. Therefore, it is necessary to introduce a non-orthogonal multiple access method (NOMA) and to apply a multiple antenna technology.

Referring to Patent Document 1, in the NOMA-based downlink system, a method for reducing interference due to sharing of spatial resources by using cluster generation and beamforming vector is provided, but a channel of a user relatively close to a base station is relatively generated within the generated cluster. A beamforming vector is generated based on a reference, and there is a problem that power consumption of the base station is not considered. Referring to Patent Document 2, in the NOMA-based downlink system, the beamforming vector for each type is decremented based on the type information for a plurality of terminals. Although orthogonally generated and a method for allocating resources for the same are provided, there is a problem in that the beamforming vector is generated by dividing the types of the UEs to increase the complexity of the system and not consider power consumption of the base station.

Meanwhile, in order to solve the problems of Patent Documents 1 and 2, Non-Patent Document 1 used an independent beamforming vector for each user to support two users, and an iterative optimization method was considered to obtain an optimal beamforming vector. However, there is a problem in that the complexity is very high and the possibility of implementation is low.

Republic of Korea Patent Publication No. 10-2014-0125643 Republic of Korea Patent Publication No. 10-2016-0146501

 Z. Chen, Z. Ding, X. Dai, and G. K. Karagiannidis, “On the application of quasi-degradation to MISO-NOMA downlink,” IEEE Trans. Sig. Process., Vol. 64, no. 23, pp. 6174-6189, Dec. 2016.

An object of the present invention is to provide a beamforming apparatus and method that can ensure the minimum transmission rate of each user and minimize the power consumption of the base station for two paired users in the NOMA scheme for downlink.

In a beamforming method for minimizing power consumption of a base station according to an embodiment of the present invention, a user pair (i, j) in a cell area of the base station is provided through a first objective function for minimizing power consumption of the base station. Optimizing the power allocation ratio to obtain the optimal power allocation ratio and using the optimal power allocation ratio to optimize the beam steering vector for the user pair through a second objective function for minimizing the power consumption of the base station. And obtaining an optimal beam steering vector, wherein the first objective function is Can be defined by

here, Is the power allocation ratio ego, Is the beam steering vector, ego, ego, Is the user pair effective channel vector, ( )ego, Is the noise variance of the receiver.

Here, the optimal power allocation ratio Can be.

Here, the second objective function is Can be defined by here, .

Here, the obtaining of the optimal beam steering vector may include calculating the second objective function. By applying The method further includes the step of transforming the beam beam vector into It can be defined as here, , ego, .

The method may further include generating a beamforming vector using the optimal beam steering vector.

Herein, allocating power to a symbol to be transmitted to a terminal using the optimal power allocation ratio, encoding a symbol to be transmitted to the user pair, and generating an overlapping code signal by overlapping the encoded symbols And performing beamforming on the generated superimposed code signal by using the beamforming vector.

Here, the beamforming vector is the user pair effective channel vector when there is only the user pair within the cell radius of the base station. ) Is the actual channel vector ( Is equal to the optimal beam steering vector when set to < RTI ID = 0.0 >), and < / RTI > The beamforming vector when Can be defined by here, Is a matrix of basis vectors forming a null space of a downlink channel excluding users i and j, Where M is the number of antennas in the base station and K is the number of users.

The method may further include selecting the user pair.

The selecting of the user pair may include obtaining an optimal power consumption using the optimal power allocation ratio and the optimal beam steering vector, and a third objective function for minimizing the total power consumption of the base station. Obtaining an optimal user pair index by optimizing the user pair index with respect to the third objective function. Can be defined by here, Is the user pair indicator, Is the optimal power consumption.

Here, the optimum power consumption is Can be defined by

In a beamforming method for minimizing power consumption of a base station according to an embodiment of the present invention, a user pair (i, j) in a cell area of the base station is provided through a first objective function for minimizing power consumption of the base station. Obtaining an optimal power allocation ratio by optimizing the power allocation ratio, and optimizing the beam steering vector for the pair of users through a second objective function for minimizing power consumption of the base station using the optimal power allocation ratio Obtaining an optimal beam steering vector, and selecting the user pair, wherein selecting the user pair comprises: a user pair effective channel vector ( ) The correlation coefficient of Calculating, selecting the user pairs in order of highest correlation coefficient for all user sets in the cell area of the base station, and removing the selected user pairs from all user sets. Including, the first objective function is Is defined by the second objective function Can be defined by here, Is the power allocation ratio ego, Is the beam steering vector, ego, ego, Is the user pair effective channel vector, ( )ego, Is the noise variance of the receiver, .

Here, the obtaining of the optimal beam steering vector may include calculating the second objective function. By applying The method further includes the step of transforming the beam beam vector into It can be defined as here, , ego, .

Here, the selecting of the user pair may be repeated until the users in all the user sets form the pair.

In a beamforming apparatus for minimizing power consumption of a base station according to an embodiment of the present invention, an optimal power allocation ratio and an optimal beam steering vector for a user pair (i, j) in a cell area of the base station are generated and A beamforming vector is generated using the optimal beam steering vector, a controller for selecting the user pair, encoding a symbol to be transmitted to the user pair, and generating an overlapping code signal by superimposing the encoded symbols. And an overlapping encoder and a beamformer configured to perform beamforming on the overlapped code signal generated by the overlapping encoder by using the beamforming vector generated by the beamforming vector generator.

Here, the controller obtains the optimal power allocation ratio by optimizing the power allocation ratio for the user pair through a first objective function, and optimizes the beam steering vector for the user pair through a second objective function. A beamforming vector generator for obtaining an optimal beam steering vector and generating the beamforming vector, a selector for selecting the user pair, and an optimal power allocation ratio to be transmitted to the user pair (i, j). And a power allocator for allocating power to each symbol, wherein the first objective function Is defined by the second objective function Can be defined by here, Is the power allocation ratio ego, Is the beam steering vector, ego, ego, Is the user pair effective channel vector, ( )ego, Is the noise variance of the receiver, .

Here, the beamforming vector generator generates the second objective function. By applying And the optimal beam steering vector is It can be defined as here, , ego, .

Here, the selecting unit is the user pair effective channel vector ( ) The correlation coefficient of The user pairs may be selected in order of the highest calculated correlation coefficient for all user sets in the cell area of the base station.

Here, the selector may remove the selected user pair from all the user sets.

According to an embodiment of the present invention, in the NOMA scheme for downlink, the minimum transmission rate of each user may be guaranteed for two paired users and the power consumption of the base station may be minimized.

In addition, the complexity of the beamforming method and user pair configuration can be reduced.

1 illustrates a non-orthogonal multiple access based downlink system according to an embodiment of the present invention.
2 is a block diagram of a beamforming apparatus according to an embodiment of the present invention.
3 is a flowchart of a beamforming method according to an embodiment of the present invention.
4 is a flowchart illustrating a user pair selection method according to an embodiment of the present invention.
5 is a flowchart illustrating a user pair selection method according to another embodiment of the present invention.
FIG. 6A shows a graph of power consumption of beamforming techniques according to the minimum data rate.
6B shows a graph of power consumption of beamforming techniques according to the number of users.

Specific structural or functional descriptions of the embodiments according to the inventive concept disclosed herein are merely illustrated for the purpose of describing the embodiments according to the inventive concept, and the embodiments according to the inventive concept. These may be embodied in various forms and are not limited to the embodiments described herein.

Embodiments according to the inventive concept may be variously modified and have various forms, so embodiments are illustrated in the drawings and described in detail herein. However, this is not intended to limit the embodiments in accordance with the concept of the present invention to specific embodiments, and includes modifications, equivalents, or substitutes included in the spirit and scope of the present invention.

Terms such as first or second may be used to describe various components, but the components should not be limited by the terms. The terms are only for the purpose of distinguishing one component from another component, for example, without departing from the scope of the rights according to the inventive concept, the first component may be called a second component, Similarly, the second component may also be referred to as the first component.

When a component is referred to as being "connected" or "connected" to another component, it may be directly connected to or connected to that other component, but it may be understood that other components may be present in between. Should be. On the other hand, when a component is said to be "directly connected" or "directly connected" to another component, it should be understood that there is no other component in between. Expressions describing relationships between components, such as "between" and "immediately between" or "directly neighboring", should be interpreted as well.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. As used herein, the terms "comprise" or "have" are intended to designate that the stated feature, number, step, operation, component, part, or combination thereof is present, but one or more other features or numbers, It is to be understood that it does not exclude in advance the possibility of the presence or addition of steps, actions, components, parts or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art. Terms such as those defined in the commonly used dictionaries should be construed as having meanings consistent with the meanings in the context of the related art, and are not construed in ideal or excessively formal meanings unless expressly defined herein. Do not.

On the other hand, in describing the equations related to the invention on the present specification, if a symbol included in the equation to be described is already included in the previously described equation, the description of the meaning of the symbol is described previously Replace with the formula. Hereinafter, exemplary embodiments will be described in detail with reference to the accompanying drawings.

First, a technique for signal transmission in a non-orthogonal multiple access (NOMA) based system to which a beamforming apparatus and method according to an embodiment of the present invention can be applied will be briefly described.

Non-orthogonal multiple access (NOMA) technology includes a transmitter using superposition coding (SC) technology and a receiver using sequential interference cancellation (SIC) technology. It supports high data rates and large connectivity, and achieves excellent spectral efficiency.

Here, the superposition coding technique of the transmitter is for simultaneously transmitting information of each user in a system including multiple users. For this purpose, the transmitter may include an encoder suitable for the number of users to encode information of each user.

Here, the sequential interference cancellation technique of the receiver is for processing multiple received signals simultaneously, and first decodes and removes a signal having a stronger signal strength, and then removes a signal having a weak signal strength from the remaining signals.

1 illustrates a non-orthogonal multiple access based downlink system according to an embodiment of the present invention.

Referring to FIG. 1, the non-orthogonal multiple access based downlink system 1 may include two user terminals 20a and 20b paired with one base station 10.

Here, the base station 10 includes an advanced base station (ABS), a high reliability base station (HR-BS), a small base station, a node B (node B), an advanced node B (evolved node B, eNodeB), access point (AP), radio access station (RAS), base transceiver station (BTS), mobile multihop relay (MMR) -BS, relay serving as a base station station, RS), a high reliability relay (HR-RS) serving as a base station, etc., and may also be referred to as BS, ABS, HR-BS, small base station, NodeB, eNodeB, AP, RAS, It may also include all or part of the functions of BTS, MMR-BS, RS, HR-RS and the like.

Here, the terminals 20a and 20b may be mobile terminals (MT), mobile stations (MS), advanced mobile stations (AMS), high reliability mobile stations (HR-MS). May also refer to a subscriber station (SS), a portable subscriber station (PSS), an access terminal (AT), a user equipment (UE), or the like. It may also include all or part of the functions of AMS, HR-MS, SS, PSS, AT, UE and the like.

The base station 10 may generate and transmit a signal to the terminals 20a and 20b by using at least one beam to one pair of terminals 20a and 20b. Here, M may be a natural number). At this time, the transmission signal transmitted from the base station 10 to the user i for the user pair (i, j) is expressed by Equation 1 below.

here, Is a transmission signal generated from the base station 10, Is a symbol ( Power consumption of the base station 10 for user i, j required to transmit Is Beamforming vector subject to To eliminate sequential interference It means a power allocation ratio having a value. On the other hand, the beamforming vector ( ) Will be described later in the beamforming apparatus and method.

As described above, the base station 10 may overlap and transmit data symbols to at least one or more terminals 20a and 20b located in the cell area, wherein the terminal located closer to the location of the terminals 20a and 20b. Relatively less power can be allocated to 20a, and more power can be allocated to the terminal 20b located farther.

The terminals 20a and 20b are located in the cell area of the base station 10 and receive signals from the base station 10. In order to receive a signal from the base station 10, the terminals 20a and 20b may include one antenna or a plurality of antennas, but in the present embodiment, the terminals 20a and 20b include one antenna. It is assumed and explained. In this case, the signal received by the terminals 20a and 20b from the base station 10 is expressed by Equation 2 below.

here, Is the actual channel vector from base station 10 to terminals 20a and 20b, Is the user pair indicator, Is an additive Gaussian noise vector for user k. At this time, H denotes the Hermitian transpose operation.

In the above Equation 2, when the users i, j are paired (that is, when the value of the user pair index is 1), the signals received by the terminals 20a and 20b of the paired users are represented by Equation 3 below. .

here, As Denotes a user pair effective channel vector. That is, when there is only one pair of user pairs within the cell radius of the base station as shown in Equations 2 and 3, the user pair effective channel vector ( ) Is the actual channel vector ( ), And if there is more than one pair of users within the cell radius of the base station, the user pair effective channel vector Same as

here, Is a matrix of basis vectors forming a null space of a downlink channel excluding users i and j, Where M is the number of antennas of the base station and K is the number of terminals (ie, users).

According to an embodiment, when continuous interference cancellation is performed in the terminals 20a and 20b of the user i among the paired users i, j, the transmission rate for the user i ( ) And the rate for user j ( ) Are each represented by Equation 4 below.

here, to be. At this time, the user pair about If so, the terminal performing the continuous interference cancellation is the terminal of user k. On the other hand, each transmission rate for the user i, j is the lowest transmission rate through the beamforming apparatus and method to be described later ( ) Can be satisfied.

In addition, the terminals 20a and 20b may be clustered with at least one terminal 20a and 20b. Preferably, as shown in FIG. 1, two terminals 20a and 20b may be clustered in pairs to minimize transmission power at lower complexity.

Meanwhile, as described above, the terminals 20a and 20b may first decode and remove an interference signal having a relatively strong signal strength according to sequential interference cancellation, and then decode a signal related to itself.

2 is a block diagram of a beamforming apparatus according to an embodiment of the present invention.

The beamforming apparatus 11 according to an embodiment of the present invention may be applied to the non-orthogonal multiple access based downlink system 1 of FIG. 1, and includes a controller 100, an overlapping encoder 200, and a beamforming unit. 300.

The beamforming apparatus 11 according to an embodiment of the present invention selects a pair of terminals whose power consumption of the base station 10 is minimum, allocates power of each terminal, or scales a signal according to a transmission rate and a desired direction. Form a beam to be transmitted to.

Here, the beamforming apparatus 11 forms a beam according to the above-described beamforming vector ( ) To generate a signal using the generated beamforming vector. The beamforming vector may be a beam that is common to both pairs of terminals i and j that receive signals from the base station.

According to an embodiment, the beamforming vector is expressed by Equation 5 below when not removing interference by another beam.

here, Is the beam steering vector that directs the signal towards users i and j. Since the power consumption for signal transmission in the base station varies according to the direction setting and scaling of the beam steering vector, it is an important factor in determining the performance of the entire system. The beam steering vector will be described in detail later.

According to an embodiment, when considering the cancellation of interference by other beams, the beamforming vector ( ) Is shown in Equation 6 below.

here, Is a matrix of base vectors forming a null space of a downlink channel excluding users i and j as described above.

That is, when considering the removal of interference by other beams, unlike in Equation 5, a block diagonalization based on zero-forcing is performed to remove interference existing between pairs of users in the beam steering vector. do. Where the matrix of basis vectors ( Channels of all users except users i and j ( Singular value decomposition can be performed by Equation 7 below.

That is, the matrix of the basis vector is obtained from the right unitary matrix obtained through the singular value decomposition of the channels of the remaining users except the users i and j according to Equation (7). ) Can be obtained.

In both the case of considering and eliminating interference by other beams as described above, the beamforming apparatus 11 performs optimization according to Equation 8 below to minimize power consumption of the base station for user i, j. Can be done.

here, Is the power consumption of the base station for user i, j.

On the other hand, the beamforming apparatus 11 performs optimization according to Equation 8 under the following first constraint.

That is, the beamforming apparatus 11 performs optimization in order to minimize power consumption of the base station. ), Power allocation ratio ( ) And beam steering vector ( ) Can be created.

The control unit 100 included in the beamforming apparatus 11 selects a pair of users to transmit a signal, allocates power to a signal to be transmitted to each user, and generates a beamforming vector. 110, a selector 130, and a power allocator 150.

The beamforming vector generator 110 Optimizing power allocation ratio by performing optimization by ) And the optimal beam steering vector ( ) Can be created. This may be equivalently represented by Equation 9 below.

here, ( )ego, Is the noise variance of the receiver, to be.

Meanwhile, the beamforming vector generator 110 performs optimization according to Equation 9 under a second constraint in which the following constraint is added to the first constraint.

That is, the second constraint is different from the first constraint. It can include all of the conditions.

Since the objective function of Equation 9 is a monotonic decreasing function or monotonic increasing function, respectively, according to the change of the power allocation ratio, the power allocation ratio when the two functions are the same is the optimal power allocation ratio. At this time, the optimal power allocation ratio ( ) Is shown in Equation 10 below.

From the optimal power allocation ratio according to Equation 10, power consumption of the base station for user i, j as shown in Equation 11 below can be derived.

here, ego, to be.

As can be seen from Equation 11, in order to obtain a beam steering vector for minimizing power consumption of the base station, it can be seen that a value corresponding to the rightmost term of Equation 11 should be minimized. This optimization problem may be expressed as in Equation 12 below.

Meanwhile, in Equation 12 By applying the inequality, it can also be represented as an optimization problem by the following equation (13).

The optimal beam steering vector ( ) Can be obtained. Hereinafter, a process of solving an optimization problem by Equation 13 will be described.

The optimization problem of Equation 13 may be expressed as Equation 14 below with respect to the variable t.

Here, Equation 14 must satisfy the following third constraint.

In this case, the user pair effective channel vector may be represented as a linear combination of normal orthogonal vectors as shown in Equation 15 below through a Gram-Schmidt orthogonalization process.

Where orthogonal vectors , ego, to be.

Using the orthogonal vector, beam steering vector Can be expressed as: Accordingly, the equation (13) May be expressed as in Equation 16 below.

According to Equation 16, the phase vector ( ) Is only Only affects, and the objective function according to Equation 14 It can be seen that as increases with increases. therefore, Optimal phase vector to maximize ) Is any phase ( ) Is expressed by Equation 17 below.

According to the optimal phase vector, May be newly expressed as in Equation 18 below.

here, to be.

Accordingly, the objective function of Equation 14 according to the optimal phase vector is In this case, it may be expressed as Equation 19 below.

Here, Equation 19 must satisfy the following fourth constraint.

On the other hand, the solution of equation (19) is only Is present only when Wow By removing, the objective function of Equation 19 can be represented by Equation 20 below.

Here, Equation 20 must satisfy the following fifth constraint.

At this time, ego, ego, ego, to be. Meanwhile, To Represented by a linear function such as To When expressed as a convex function, Wow In the relationship, three cases can be considered.

[Case 1]

if If, among the fifth constraint Can only be considered. These cases 1 Wow in ego, Holds only when therefore, (Hereinafter, the first condition), Is 1.

[Case 2]

Wow The intersection of If only exists, all of the fifth constraints may be considered. In this case, the intersection is (Hereafter, the second condition). Thus, under the second condition to be.

[Case 3]

if in If, among the fifth constraint Can only be considered. These cases 3 ego Holds only when Where the optimal solution is Ramen Is the maximum point of Can be obtained from Ramen Can be obtained from Accordingly, (Hereinafter, third condition), the optimal solution is ego, (Hereinafter, fourth condition), the optimal solution is to be.

Through the above-described process, the optimal beam steering vector according to Equation 13 can be obtained as Equation 21 below.

here, ego to be.

The optimal beam steering vector of Equation 21 is And arbitrary phase ( ) Can also be represented by Equation 22 below.

here, Is any phase value,

Is the first condition ( ) Is 1,

Second condition ( )in ego,

Third condition ( )in ego,

Fourth condition ( )in to be.

Further, under the first to fourth conditions ego,

ego,

ego,

to be.

That is, the beamforming vector generator 110 performs optimization as described above with respect to the power allocation ratio and the beam steering vector in order to generate a beamforming vector that minimizes power consumption of the base station. Allocation fee ( ) And the optimal beam steering vector ( ) At this time, the optimal beam steering vector has different optimal values according to the first to fourth conditions as described above. The beamforming vector generator 110 finally generates a beamforming vector using the generated optimal beam steering vector. )

The selector 130 selects a user pair (i, j) to transmit a signal among users who have a terminal in the cell area of the base station. According to an embodiment of the present disclosure, the selecting unit 130 performs optimization according to Equation 23 below to select a pair of users whose total power consumption of the base station for transmitting signals to users in the cell area of the base station is minimized. .

here, Is a user pair indicator that has a value of 0 or 1 depending on whether the user is paired. Is the optimal power consumption of the base station for user i, j. In this case, the optimal power consumption may be calculated by Equation 24 below.

here, Is calculated by Equation 11 according to the optimal beam steering vector generated by the controller 100. At this time, Is the first condition in accordance with the first to fourth conditions ego,

Under the second condition ego,

Under the third condition ego,

Under the fourth condition to be.

here, to be.

On the other hand, the selector 130 performs optimization according to Equation 23 under the sixth constraint described below.

At this time, the user pair indicator ( ) Is 1 if user i and j are paired, regardless of the user performing sequential interference cancellation for all users (1, ..., K), otherwise 0.

On the other hand, in the case of performing the optimization according to Equation 23, the complexity is related to the number of users K in the system. As the number of users increases, it increases significantly. Therefore, instead of selecting the user pair by performing the optimization according to Equation 23, the selecting unit 130 according to an embodiment of the present invention uses a user pair effective channel vector ( You can also select a user pair using the correlation coefficient of). In this case, the correlation coefficient of the user pair effective channel vector is Can be expressed as: That is, the selector 130 may calculate the correlation coefficients for all the pairs of users k and select the user pairs in the order of the calculated correlation coefficients being high.

According to the above-described embodiments, the selector 130 may determine a user pair index that minimizes the total power consumption of the base station for transmitting signals to users in the cell area of the base station. ) Can be selected.

The power allocator 150 generates an optimal power allocation ratio (generated by the control unit) Power is allocated to each symbol to be transmitted to the selected user pair (i, j). In this case, as described above, relatively less power can be allocated to the terminal 20a located closer, and relatively more power can be allocated to the terminal 20b located farther.

The superposition encoder 200 encodes a symbol to be transmitted to the user pair (i, j), and generates a superposition code signal by superimposing the encoded symbols.

The beamformer 300 may generate a beamforming vector generated by the beamforming vector generator 110 with respect to the superimposed code signal generated by the superposition encoder 200. Beamforming is performed using

3 is a flowchart of a beamforming method according to an embodiment of the present invention. Hereinafter, a description of a portion overlapping with the above-described portion will be omitted.

In step S310, in order to form a beam for minimizing power consumption of the base station, Optimization based on Equation 9 is performed for a power allocation ratio having a value within a range. According to the result of the optimization, the optimal power allocation ratio is expressed by Equation 10 above.

In step S320, the beam steering vector is optimized by Equation 9 using the optimal power allocation ratio obtained through step S310. According to the optimization result, the optimal beam steering vector is expressed by Equation 21.

In step S330, a beamforming vector is generated using the optimal beam steering vector generated in step S320. According to one embodiment, if there is only a pair of users (ie, two users) within the cell radius of the base station, the beamforming vector is a user pair effective channel vector ( ) Is the actual channel vector ( Equal to the optimal beam steering vector when

According to another embodiment, when there are one or more pairs of users within the cell radius of the base station, the user pair effective channel vector The beamforming vector at is generated by Equation 6 above. That is, in this case, block diagonalization based on interference cancellation may be performed to remove interference by a pair of users other than the transmission target user pair for K users within a cell radius. Meanwhile, in order to obtain a matrix of basis vectors forming a null space for interference cancellation, step S330 may further perform singular value decomposition.

In step S340, a symbol to be transmitted to the terminal using the optimal power allocation ratio generated in steps S310 and S320 is used. Allocate power to). According to an embodiment, for user i, j The power consumption of the base station may be allocated in a ratio.

Step S350 finally generates a signal to be transmitted to the terminal according to Equation (1). More specifically, step S350 encodes a symbol to be transmitted to a user pair (i, j), generates an overlapped code signal by superimposing the encoded symbols, and then generates a beamforming vector ( Beamforming is performed using

4 is a flowchart illustrating a user pair selection method according to an embodiment of the present invention.

Referring to FIG. 4, step S410 is performed to obtain an optimum power consumption of the base station by performing optimization according to Equation 24. At this time, the optimal power consumption of the base station may have a different value according to the first to fourth conditions.

In operation S420, the optimization is performed according to Equation 23, and a user pair is selected when the total power consumption of the base station is minimized.

5 is a flowchart illustrating a user pair selection method according to another embodiment of the present invention.

Referring to Figure 5, step S510 is a user pair effective channel vector ( ) The correlation coefficient of Calculate by In step S530, the user pairs are selected in order of the highest correlation coefficient for all user sets in the cell area of the base station. Step S550 removes the selected user pair from all the user sets. Steps S530 to S550 may be repeatedly performed until users in all user sets form a pair.

As described above, not only the user selection method according to the embodiment of FIG. 4 but also the user selection method according to the embodiment of FIG. 5 may reduce the complexity according to the user pair selection.

FIG. 6A shows a graph of power consumption of beamforming techniques according to the minimum data rate.

Referring to FIG. 6A, M (number of antennas of the base station) = K (number of users) = 8, the single cell radius of the base station is 500 [m], the noise power is -104 [dBm], and the path at the distance d. Loss The performance of the beamforming method and other beamforming methods according to an embodiment of the present invention is compared with the power consumption of the base station under the condition that the propagation model of the macro cell is a 3GPP TR 36.931 model having a bandwidth of 10 [MHz]. . In this case, the beamforming techniques showing the illustrated performance are proposed techniques (PBD) and conventional techniques (ZF, HBD, LBD, Hybrid), where ZF is an interference cancellation based beamforming technique, and HBD (LBD) is high. (low) It is a beamforming technique for users with SNR, and Hybrid is a beamforming technique according to Non Patent Literature 1.

As shown in FIG. 6A, the proposed beamforming scheme (PBD) shows that the base station can transmit a signal at a lower power at all minimum transmission rates than other conventional beamforming techniques (ZF, HBD, LBD, Hybrid). Can be.

6B shows a graph of power consumption of beamforming techniques according to the number of users.

Referring to FIG. 6B, under the conditions of FIG. 6A, performances of the beamforming method and other beamforming techniques according to the exemplary embodiment of the present invention are compared through power consumption of the base station. In this case, in the user pair selection technique applied to the beamforming techniques showing the performance shown, MPAA is a technique based on a message transfer algorithm, ECPA is a technique using a correlation coefficient of a user pair effective channel vector, and SUPA is expressed by Equation 15 above. This is the technique used.

As shown in FIG. 6B, when the proposed user pair selection techniques MPPA and ECPA are applied to the proposed beamforming technique PBD, the base station can transmit a signal even with lower power. In particular, when the ECPA technique is applied to the PBD, as the number of users increases, the performance is similar to that of applying the MPPA to the PBD.

As described above, according to the beamforming apparatus 11 and the method according to an embodiment of the present invention, it is possible to ensure the minimum transmission rate for each user and to minimize the power consumption of the base station. As shown in FIGS. 6A to 6B, it is possible to exhibit better performance in terms of power consumption than conventional beamforming techniques.

In addition, the beamforming apparatus 11 and the method according to an embodiment of the present invention may maximize the performance of the above-described power consumption by applying a user pair selection technique, and may reduce the complexity.

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 devices and components described in the embodiments may include, for example, processors, controllers, arithmetic logic units (ALUs), digital signal processors, microcomputers, field programmable arrays (FPAs), 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. The processing device may also access, store, manipulate, process, and generate data in response to the execution of the software. For the convenience of understanding, a processing device may be described as one being used, but a person skilled in the art will appreciate that the processing device includes a plurality of processing elements and / or a plurality of types of processing elements. It can be seen that it may include. For example, the processing device may include a plurality of processors or one processor and one controller. In addition, other processing configurations are possible, such as parallel processors.

The software may include a computer program, code, instructions, or a combination of one or more of the above, and configure the processing device to operate as desired, or process independently or collectively. You can command the device. Software and / or data may be any type of machine, component, physical device, virtual equipment, computer storage medium or device in order to be interpreted by or to provide instructions or data to the processing device. Or may be permanently or temporarily embodied in a signal wave to be transmitted. The software may be distributed over networked computer systems so that they may be stored or executed in a distributed manner. Software and data may be stored on one or more computer readable recording media.

The method according to the embodiment may be embodied in the form of program instructions that can be executed by 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 media may be those specially designed and constructed for the purposes of the embodiments, or they may be of the kind well-known and available to those having skill in the computer software arts. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tape, optical media such as CD-ROMs, DVDs, and magnetic disks, 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 not only machine code generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like. The hardware device described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

Although the embodiments have been described with reference to the accompanying drawings as described above, various modifications and variations are possible to those skilled in the art from the above description. For example, the described techniques may be performed in a different order than the described method, and / or components of the described systems, structures, devices, circuits, etc. may be combined or combined in a different form than the described method, or other components. Or even if replaced or substituted by equivalents, an appropriate result can be achieved.

Therefore, other implementations, other embodiments, and equivalents to the claims are within the scope of the claims that follow.

Claims (18)

In the beamforming method for minimizing the power consumption of the base station,
Obtaining an optimal power allocation ratio by optimizing a power allocation ratio for a pair of users (i, j) in a cell area of the base station through a first objective function for minimizing power consumption of the base station; And
Obtaining a beam steering vector by optimizing the beam steering vector for the pair of users through a second objective function for minimizing power consumption of the base station using the optimal power allocation ratio;
The first objective function is The beamforming method defined by.
here, Is the power allocation ratio ego, Is the beam steering vector, ego, ego, Is the user pair effective channel vector, ( )ego, Is the noise variance of the receiver.
The method of claim 1,
The optimal power allocation ratio In-beam forming method.
The method of claim 2,
The second objective function is The beamforming method defined by.
here, .
The method of claim 3,
Obtaining the optimal beam steering vector
The second objective function By applying Further comprising the step of transforming,
The optimal beam steering vector is A beamforming method defined as
here, , ego, .
The method of claim 4, wherein
Generating a beamforming vector using the optimal beam steering vector.
The method of claim 5,
Allocating power to a symbol to be transmitted to a terminal using the optimal power allocation ratio;
Encoding a symbol to be transmitted to the user pair, and generating an overlapped code signal by superimposing the encoded symbols; And
And performing beamforming on the generated superimposed code signal by using the beamforming vector.
The method of claim 5,
The beamforming vector is the user pair effective channel vector when there is only the user pair within the cell radius of the base station. ) Is the actual channel vector ( Is equal to the optimal beam steering vector when set to < RTI ID = 0.0 >), and < / RTI > The beamforming vector when The beamforming method defined by.
here, Is a matrix of basis vectors forming a null space of a downlink channel excluding users i and j, Where M is the number of antennas in the base station and K is the number of users.
The method of claim 2,
And selecting the pair of users.
The method of claim 8,
Selecting the user pair is
Obtaining an optimal power consumption using the optimal power allocation ratio and the optimal beam steering vector; And
Obtaining an optimal user pair index by optimizing the user pair index with respect to a third objective function for minimizing the total power consumption of the base station,
The third objective function is The beamforming method defined by.
here, Is the user pair indicator, Is the optimal power consumption.
The method of claim 9,
The optimal power consumption The beamforming method defined by.
In the beamforming method for minimizing the power consumption of the base station,
Obtaining an optimal power allocation ratio by optimizing a power allocation ratio for a pair of users (i, j) in a cell area of the base station through a first objective function for minimizing power consumption of the base station;
Obtaining a beam steering vector by optimizing the beam steering vector for the user pair through a second objective function for minimizing power consumption of the base station using the optimal power allocation ratio; And
Selecting the pair of users,
Selecting the user pair is
User Pair Effective Channel Vector ( ) The correlation coefficient of Calculating by;
Selecting the pair of users in order of the highest correlation coefficient calculated for all sets of users in the cell area of the base station; And
Removing the selected user pair from all the user sets,
The first objective function is Is defined by the second objective function The beamforming method defined by.
here, Is the power allocation ratio ego, Is the beam steering vector, ego, ego, Is the user pair effective channel vector, ( )ego, Is the noise variance of the receiver, .
The method of claim 11,
Obtaining the optimal beam steering vector
The second objective function By applying Further comprising the step of transforming,
The optimal beam steering vector is A beamforming method defined as
here, , ego, .
The method of claim 11,
The selecting of the user pairs may be repeated until the users in all the user sets form the pairs.
In the beamforming device to minimize the power consumption of the base station,
Generate an optimal power allocation ratio and an optimal beam steering vector for the user pair (i, j) in the cell region of the base station, generate a beamforming vector using the optimal beam steering vector, and generate the user pair. A controller for selecting;
An overlapping encoder which encodes a symbol to be transmitted to the user pair and generates an overlapped code signal by superimposing the encoded symbols; And
And a beamforming unit configured to perform beamforming on the superimposed code signal generated by the overlapping encoder by using the beamforming vector generated by the beamforming vector generator.
The method of claim 14,
The control unit
The optimal power allocation ratio is obtained by optimizing the power allocation ratio for the user pair through a first objective function, and the optimal beam steering vector is obtained by optimizing the beam steering vector for the user pair through a second objective function. A beamforming vector generator for obtaining the beamforming vector;
A selection unit for selecting the pair of users; And
A power allocator for allocating power to symbols to be transmitted to the user pairs i and j using the optimal power allocation ratio;
The first objective function is Is defined by the second objective function Beamforming apparatus as defined by.
here, Is the power allocation ratio ego, Is the beam steering vector, ego, ego, Is the user pair effective channel vector, ( )ego, Is the noise variance of the receiver, .
The method of claim 15,
The beamforming vector generator
The second objective function By applying Transform to
The optimal beam steering vector is A beamforming method defined as
here, , ego, .
The method of claim 15,
The selection unit
The user pair effective channel vector ( ) The correlation coefficient of And selecting the user pairs in order of the highest correlation coefficient calculated for all user sets in the cell area of the base station.
The method of claim 17,
And the selecting unit removes the selected user pair from all user sets.