Cell-free massive MIMO-based wireless information and power transmission communication system and method using linear programming method

Abstract

Disclosed are a CF mMIMO-based SWIPT communication system and method using a linear programming method. A specific embodiment of this technology may involve: generating an optimization problem P0 by optimizing, on the basis of a linear programming method, a problem P0 that minimizes total transmission power energy; generating, from the generated optimization problem P0, optimization problems P1, P2 that respectively minimize downlink transmission power and uplink transmission power including a nonlinear SINR; deriving uplink optimal transmission power and an optimal power division coefficient as a solution of the generated optimization problem P1; and deriving downlink optimal transmission power as a solution of the generated optimization problem P2. Accordingly, the energy efficiency of a user terminal may be maximized while a QoS constraint condition is satisfied, and stable communication can be performed at lower power.

Description

Cell-free Massive MIMO-based Wireless Information and Power Transmission Communication System and Method Using Linear Programming

[0001] The present invention relates to a wireless information and power transfer (SWIPT) communication system and method based on Cell-Free Massive Multiple-Input Multiple-Output (CF mMIMO) using linear programming, and more specifically, to a technology that can satisfy Quality of Service (QoS) limiting conditions and minimize total transmission power in a Simultaneous Wireless Information and Power Transfer (SWIPT) system based on Cell-Free Massive Multiple-Input Multiple-Output (CF mMIMO).

[0002] Due to the rapid advancement of communication and computing technologies, the Internet of Things (IoT) is currently being applied to real life.

[0003] However, the development of the Internet of Things (IoT) is facing serious problems such as the limited battery life of wireless devices, which is further highlighting the importance of efficient energy management.

[0004] Accordingly, research on energy harvesting (EH) technology capable of supplying power and information to wireless devices through Simultaneous Wireless Information and Power Transfer (SWIPT) technology has recently been actively conducted.

[0005] SWIPT technology is useful for efficiently managing communication and energy in wireless environments, and for maintaining stable power in IoT systems by simultaneously collecting energy and decoding information from the same RF signal. However, as propagation distance increases, the energy harvested from IoT devices is significantly degraded, leading to a decrease in Spectrum-to-Energy Efficiency (SE / EE).

[0006] Meanwhile, in a CF mMIMO-based SWIPT system, access points (APs) are deployed over a wide geographical area without cell boundaries and are interconnected to a central processing unit (CPU) via a backhaul link, preventing frequent handovers, and high SE / EE can jointly provide various services to multiple user terminals (UEs) with high macrodiversity gains.

[0007] Accordingly, the applicant intends to propose a method that maximizes energy efficiency by efficiently distributing information and energy with low computational complexity of the user terminal (UE) using a CF mMIMO-based SWIPT system, thereby enabling stable communication with low power consumption.

[0008] Accordingly, the present invention aims to provide a CF mMIMO-based SWIPT communication system and method using linear programming that can maximize energy efficiency by efficiently distributing information and energy of a user terminal using a CF mMIMO-based SWIPT system, and thereby perform stable communication with low power.

[0009] The objectives of the present invention are not limited to those mentioned above, and other objectives and advantages of the present invention not mentioned may be understood from the following description and will become more clearly known from the embodiments of the present invention. Furthermore, it will be readily apparent that the objectives and advantages of the present invention can be realized by the means and combinations thereof set forth in the claims.

[0010] A CF mMIMO-based SWIPT communication system using linear programming according to one embodiment of the present invention is,

[0011] At least one base station;

[0012] At least two user terminals performing a downlink for receiving a transmission signal from a base station and an uplink for transmitting a generated pilot signal to a base station; and

[0013] It includes a central processing unit connected to the above base station, and

[0014] The above central processing unit is,

[0015] The system is configured to derive the uplink optimal transmission power, the optimal power division factor, and the downlink optimal transmission power as a solution to the problem of minimizing the total transmission power energy, and to provide the derived uplink optimal transmission power, the optimal power division factor, and the downlink optimal transmission power to the base station.

[0016] One feature is that the base station controls a transmission signal with the uplink optimal transmission power, optimal power division factor, and downlink optimal transmission power of the received central processing unit, and is configured to provide the uplink optimal transmission power and the optimal power division factor to the at least two user terminals.

[0017] Preferably, the central processing unit is,

[0018] An optimization problem generation unit that generates a problem P0 that minimizes the total transmission power energy of a user terminal, then optimizes the generated problem P0 using linear programming to generate an optimization problem P0, and generates an uplink optimization problem P1 and a downlink optimization problem P2 from the generated optimization problem P0;

[0019] An uplink optimal transmission power calculation unit that derives an uplink optimal transmission power satisfying predefined constraints for the above optimization problem P1;

[0020] An optimal power division coefficient calculation unit that derives an optimal power division coefficient satisfying predefined constraints from the total transmission power energy derived from the sum of the energy of the derived uplink optimal transmission power and the energy of the pilot transmission power; and

[0021] One feature is that it includes a downlink optimal transmission power calculation unit that calculates the downlink optimal transmission power using the solution of the optimization problem P2 derived using an iterative technique.

[0022] Preferably, the downlink optimal transmission power calculation unit is,

[0023] After initializing the average value with the upper and lower bounds of the total transmitted power energy, derive the solution to optimization problem P2 that minimizes the total transmitted power energy using the Convex Optimization (CVX) technique, and

[0024] If the constraints for the derived optimization problem P2 are satisfied, the upper limit of the total transmitted power energy is set to the average value, and

[0025] Deriving an optimal power splitting coefficient that satisfies predefined constraints from the total transmitted power energy of the above average value,

[0026] Based on the above optimal power division coefficient, the average value of the total transmitted power energy is updated, and

[0027] If the difference between the upper and lower limits of the total transmission power energy does not exceed a predetermined threshold, it may be configured to update the downlink optimal transmission power derived as the solution to optimization problem P2 that minimizes the average value of the total transmission power energy.

[0028] Preferably, the downlink optimal transmission power calculation unit is,

[0029] If the difference between the upper and lower limits of the total transmission power energy exceeds a predetermined threshold, the method may be configured to repeat the process until the difference between the upper and lower limits of the downlink transmission power energy derived by the convex optimization technique converges to a predetermined threshold.

[0030] A CF mMIMO-based SWIPT communication method using linear programming according to one embodiment, based on another embodiment of the present invention,

[0031] An optimization problem generation step of generating a problem P0 that minimizes total transmission power energy, then optimizing the generated problem P0 based on linear programming, and then deriving uplink optimization problem P1 and downlink optimization problem P2 from the optimized problem P0;

[0032] An uplink optimal transmission power calculation step for deriving an uplink optimal transmission power that satisfies the above optimization problem P1 and predefined constraints;

[0033] An optimal power division coefficient calculation step for deriving an optimal power division coefficient satisfying predefined constraints from the total transmission power energy derived from the sum of the energy of the derived uplink optimal transmission power and the energy of the pilot transmission power; and

[0034] One feature is that it includes a downlink optimal transmission power calculation step for deriving the downlink optimal transmission power as a solution to the above optimization problem P2.

[0035] Preferably, the downlink optimal transmission power calculation step is

[0036] A step of deriving the upper limit, lower limit, and average value of the total transmitted power energy, respectively, and then deriving the solution to optimization problem P2 that minimizes the total transmitted power energy using a block optimization (CVX: Convex Optimization) technique;

[0037] A step of setting the upper limit of the total transmitted power energy to the average value when the constraints for the derived optimization problem P2 are satisfied,

[0038] A step of deriving an optimal power splitting coefficient that satisfies the average value of the total transmitted power energy and predefined constraints,

[0039] A step of updating the average value of the total transmitted power energy based on the above optimal power division coefficient,

[0040] If the difference between the upper and lower limits of the total transmission power energy does not exceed a predetermined threshold, the method may be configured to include a step of updating the downlink optimal transmission power derived as the solution to optimization problem P2 that minimizes the average value of the total transmission power energy.

[0041] Preferably, the downlink optimal transmission power calculation step is,

[0042] If the difference between the upper and lower limits of the total transmission power energy exceeds a predetermined threshold, the method may further include a step of repeating the process until the difference between the upper and lower limits of the downlink transmission power energy derived by the convex optimization technique converges to a predetermined threshold.

[0043] According to one embodiment, a problem P0 that minimizes total transmission power energy is optimized based on linear programming to generate an optimization problem P0, and optimization problems P1 and P2 that minimize downlink transmission power and uplink transmission power, respectively, including nonlinear SINR, are generated from the generated optimization problem P0, and the uplink optimal transmission power and optimal power splitting coefficient are derived from the solution of the generated optimization problem P1, and the downlink optimal transmission power is derived from the solution of the generated optimization problem P2, thereby maximizing the energy efficiency of the user terminal while satisfying QoS constraints and enabling stable communication with low power.

[0044] The following drawings attached to this specification illustrate preferred embodiments of the present invention and serve to further enhance understanding of the technical concept of the present invention together with the detailed description of the invention provided below; therefore, the present invention should not be interpreted as being limited only to the matters described in such drawings.

[0045] Figure 1 is a configuration diagram of a CF mMIMO-based SWIPT communication system using linear programming to which one embodiment is applied.

[0046] Figure 2 is an example diagram showing the communication protocol of Figure 1.

[0047] Figure 3 is a detailed configuration diagram of the user terminal of Figure 1.

[0048] Figure 4 is a detailed configuration diagram of the central processing unit of Figure 3.

[0049] Figure 5 is an overall flowchart showing a CF mMIMO-based SWIPT communication process using linear programming of another embodiment of the present invention.

[0050] Figure 6 is a figure showing the operation process of the downlink optimal power transmission operation unit of Figure 5.

[0051] Specific structural or functional descriptions of the embodiments are disclosed for illustrative purposes only and may be modified and implemented in various forms. Accordingly, the embodiments are not limited to the specific disclosed forms, and the scope of this specification includes modifications, equivalents, or substitutions that fall within the technical concept.

[0052] Terms such as "first" or "second" may be used to describe various components, but these terms should be interpreted solely for the purpose of distinguishing one component from another. For example, the first component may be named the second component, and similarly, the second component may be named the first component.

[0053] When it is stated that a component is "connected" to another component, it should be understood that it may be directly connected to or joined to that other component, or that there may be other components in between.

[0054] The singular expression includes the plural expression unless the context clearly indicates otherwise. In this specification, terms such as "comprising" or "having" are intended to specify the existence of the described features, numbers, steps, actions, components, parts, or combinations thereof, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0055] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this specification.

[0056] Hereinafter, the present invention will be described in detail by explaining preferred embodiments of the present invention with reference to the attached drawings.

[0057] FIG. 1 is a configuration diagram of a CF mMIMO-based SWIPT communication system using linear programming to which an embodiment is applied, FIG. 2 is an example diagram showing the communication protocol of FIG. 1, FIG. 3 is a detailed configuration diagram of the user terminal (UE: User Equipment, 21~2K) of FIG. 1, FIG. 4 is a detailed configuration diagram of the central processing unit (CPU 3) of FIG. 1, and FIG. 5 is a flowchart showing the operation process of the downlink optimal transmission power calculation unit of FIG. 4.

[0058] Referring to FIG. 1, a CF mMIMO-based SWIPT communication system using linear programming to which one embodiment is applied comprises L base stations (AP 1~AP L, 11~1L), K user terminals (UE 1~UE K, 21~2K), and a central processing unit (CPU, 3), wherein the base stations (11~1L) are connected to the central processing unit (3) via a wired backhaul link and can provide various services to the user terminals (UE 1~UE K, 21~2K).

[0059] Here, L base stations (11~1L) and a central processing unit (3) exchange information including Channel State Information (CSI), precoding / decoding, power allocation coefficients, scheduling, and control signals through a wired backhaul link, and the central processing unit (3) calculates the optimal transmission power of the downlink, the optimal transmission power of the uplink, and the optimal power division coefficient of the user terminal (21~2K) using the received information and provides them to the base stations (11~1L).

[0060] Referring to FIG. 2, the communication protocol between the base station (11~1L) and the central processing unit (3) is a coherence time (τ). c Assuming that it is performed using a Time Division Duplex (TDD) protocol for ), the user terminal (21~2K) has a predetermined time (τ p The pilot signal of ) is transmitted to the base station (11~1L) (uplink), and the base station (11~1L) transmits the pilot signal to the base station (11~1L) at a set time (τ dl During the slot, the transmission signal is transmitted (downlink) to the user terminal (21~2K). Here, each base station (11~1L) derives Channel State Information (CSI) based on the uplinked pilot signal from the user terminal (21~2K) and performs precoding using the derived Channel State Information.

[0061] Meanwhile, the user terminal (21~2K), with reference to FIG. 3, includes a downlink section (100) including a power divider (110), an energy harvester (120: Energy Harevest), and an information decoder, and an uplink section (200) including an energy storage unit (210) and an information transmitter (220).

[0062] At this time, assuming that the user terminal (21~2K) is equipped with a single antenna and the base station (11~1L) is connected to the central processing unit (3) through L infinite capacity and error-free wired backhaul links, any k-th user terminal (2k) and The th base station (AP) Channel between the nth antennas of ) It can be expressed by the following Equation 1.

[0063] [Equation 1]

[0064]

[0065] Here, is a large fading value, and is a small fading value.

[0066] And, the k-th user terminal (2k) to obtain channel state information (CSI) 1st base station (1 The pilot sequence is transmitted to the base station. At this time, the pilot sequence assigned to the k-th user terminal (2k) is Defined as, and here, and It is defined as, and accordingly, the pilot signal It can be expressed by the following Equation 2.

[0067] [Equation 2]

[0068]

[0069]

[0070] Here, Is 1st base station (1 It is a channel between the nth antenna of ) and the user terminal (21~2K), and each The th base station (AP) It is the noise and pilot power of the nth antenna of ). That is, the power consumption of the user terminal (21~2K) while estimating the channel state information (CSI) is is. Here, 1st base station (1 ) estimates Channel State Information (CSI) using the Linear Less Mean Squared Error (LMMSE) technique, and the estimated Channel State Information It can be expressed by the following Equation 3.

[0071] [Equation 3]

[0072]

[0073]

[0074] Here, in Equation 3 is a diagonal matrix of large-scale fading values, and is the pilot signal matrix, and is the conjugate transpose of the pilot signal matrix, and is the transmission power of the pilot signal, and σ 2 I is the noise covariance matrix.

[0075] This channel status information Effective channel gain from is derived, and the derived effective channel gain It can be expressed by the following Equation 4.

[0076] [Equation 4]

[0077]

[0078] Here, and, estimated channel error is derived using the LMMSE (Linear Minimum Mean Square Error) technique, and the derived estimated channel error It can be expressed by the following Equation 5.

[0079] [Equation 5]

[0080]

[0081] Here, the estimated error Is 1st base station (1 The actual channel between ) and the k-th user terminal (2k) and the calculated channel of Equation 3 Derived from the difference, and the computed channel is the estimated channel error They are mutually independent regarding.

[0082] Meanwhile, each base station (11~3L) performs procoding based on channel state information (CSI) estimated using the Maximum Ratio Transmission (MRT) technique.

[0083] The th base station (AP) The transmission signal of ) and, here, , Is 1st base station (1 It is a power and information signal transmitted from ) to the j-th user terminal (2j). 1st base station (1 ) is the received signal of the k-th user terminal (2k) receiving the transmission signal of It can be expressed by the following Equation 6.

[0084] [Equation 6]

[0085]

[0086] Here, is the noise of the k-th user terminal (2k).

[0087] And the received signal of the k-th user terminal (2k) It is provided to an energy harvester (120) and an information decoder (130) via a power splitter (110) of the downlink section (100) and is divided into an energy signal and an information signal, wherein the energy signal of the energy harvester (120) and information signals Each can be expressed by the following Equation 7.

[0088] [Equation 7]

[0089]

[0090] Here, power division coefficient And, is noise included in the energy signal. is noise included in the information signal.

[0091] For example, the k-th user terminal (2k) is In this case, information signals are collected, and as another example, In this case, energy signals are collected, and the total transmission power of the downlink section (100) It is represented by the following Equation 8.

[0092] [Equation 8]

[0093]

[0094] Here, silver 3rd base station (3 It is the transmission power of ), and is the maximum power available when transmitting from each base station to the user terminal, and the energy harvested from the k-th user terminal (2k). It can be expressed by the following Equation 9.

[0095] [Equation 9]

[0096]

[0097] Here, P TH is the energy harvesting efficiency and power threshold of the non-linear energy harvester (120), and is the energy harvesting efficiency.

[0098] Also, energy harvested from the k-th user terminal (2k) The lower bound of is represented by the following Equation 10.

[0099] [Equation 10]

[0100]

[0101] Here, am.

[0102] Meanwhile, the information signal of the information decoder (130). It is represented by the following Equation 11.

[0103] [Equation 11]

[0104]

[0105] In Equation 11, the first term includes the desired signal DS, the beamforming uncertainty gain BUG, ​​the multi-user interference MUI, and the effective noise noise, and the desired signal DS is independent of the effective noise noise.

[0106] Achievable downlink speed at the k-th user terminal (2k) It can be expressed by the following Equation 12.

[0107] [Equation 12]

[0108]

[0109] Here, is the interference-plus-noise ratio (SINR) of the downlink section (100), defined by the following Equation 13.

[0110] [Equation 13]

[0111]

[0112] Here,

[0113] ,

[0114] ,

[0115] , and

[0116] am.

[0117] Signal-to-interference and noise ratio (DL SINR) of the downlink section (100) of Equation 13 To derive the solution, if the DL SINR of the downlink section (100) of Equation 13 is rearranged into a closed form, it can be expressed as Equation 14 below.

[0118] [Equation 14]

[0119]

[0120] Here,

[0121] ,

[0122] , and

[0123] And, The second and third terms of are the Pilot Contamination Power, for example, when the pilot sequences are mutually orthogonal, the Pilot Contamination Power is 0. Here, the Pilot Contamination Power represents the magnitude of mutual interference between user terminals in a multi-user terminal environment.

[0124] Meanwhile, the information transmitter (220) of the uplink section (200) receives the information signal of the k-th user terminal (2k). cast 1st base station (1 Send to ) and at this time 1st base station (1 Received signal of ) It can be expressed by the following Equation 15.

[0125] [Equation 15]

[0126]

[0127] Here, silver 1st base station (1 It is noise of ), and is an information signal of the j-th user terminal (2j), and is the transmission power of the j-th user terminal (2j), and is the maximum available power.

[0128] Meanwhile, available energy stored in the energy storage unit (210) of the uplink section (200) of the k-th user terminal (2k) It can be expressed by the following Equation 16.

[0129] [Equation 16]

[0130]

[0131] Here, is from the k-th user terminal (2k) at the set time (τ ul Information signal during the ) slot 1st base station (1 It is the transmission power of the uplink section (200) that is transmitted to ).

[0132] one side, 1st base station (1 Received signal of ) Since it includes average gain and uncorrelated Gaussian noise, 1st base station (1 Received signal of ) It is transmitted to the central processing unit (3) after receiving and filtering the MRC, and the received signal of the central processing unit (3) is It can be expressed as Equation 17 below.

[0133] [Equation 17]

[0134]

[0135] Received signal of the central processing unit (3) It includes the desired signal DS and effective noise such as beamforming uncertainty gain BUG, ​​multi-user interference MUI, and noise.

[0136] And, the transmission signal of the uplink section (200) of the k-th user terminal (2k) achievable speed It can be expressed by the following Equation 18.

[0137] [Equation 18]

[0138]

[0139] Signal interference and noise ratio (UL SINR) of the uplink section (200) in Equation 18 It can be expressed by the following Equation 19.

[0140] [Equation 19]

[0141]

[0142] Here,

[0143] ,

[0144] ,

[0145] , and

[0146]

[0147] And, the signal interference and noise ratio (UL SINR) of the uplink section (200) To derive the solution, if we rearrange it into a closed form, it can be expressed as Equation 20 below.

[0148] [Equation 20]

[0149]

[0150] Here,

[0151] ,

[0152] ,

[0153] , and

[0154] am.

[0155] Harvested energy of Equation 10 and the closed signal interference and noise ratio (DL SINR) of the downlink section (100) of Equation 14 and the closed signal interference and noise ratio (DL SINR) of the uplink section (200) of Equation 20 The desired power DS increases with the number of antennas N and base stations L, pilot contamination increases, and the remaining noise increases linearly.

[0156] Here, pilot contamination is the limited length (τ) of the pilot signal. p It is reused among users by means of ), and thus interference occurs between users using the same pilot signal, and therefore, as the number of antennas N, the number of base stations L, and the number of user terminals K increase, pilot contamination increases.

[0157] Accordingly, the desired signal DS for evaluating the performance of the system increases in proportion to the transmission power, the beamforming uncertainty gain BUG and multi-user interference MUI increase, and the noise power is maintained constant. Therefore, when the transmission power increases, the SINR of the downlink section (100) and the SINR of the uplink section (200) are improved.

[0158] And, when the transmission power reaches a threshold value small enough to ignore noise, the achievable speed converges to 0, and the SINR of the downlink section (100) of Equation 14 at It can be ignored as a small value.

[0159] one side, The th base station (AP) Effective channel gain of Equation 4 between ) and the k-th user terminal (2k) As the desired signal DS and interference signal MUI increase, and the beamforming uncertainty gain BUG increases linearly, the communication and energy efficiency of the CF mMIMO-based SWIPT system are improved.

[0160] And, pilot signal power If increases, the accuracy of channel estimation increases, so the effective channel gain This increases and accordingly, the effective channel gain large fading coefficient It converges to. Accordingly, the pilot signal power by Effective channel gain As this increases, the desired power DS and SINR are improved, and the communication and energy efficiency of the CF mMIMO-based SWIPT system are enhanced.

[0161] Accordingly, the central processing unit (3) receives the transmission power and power division coefficient of the downlink unit (100) of the user terminal (21~2K) and the transmission power of the uplink unit (200), calculates the optimal transmission power of the downlink unit (100), the optimal power division coefficient, and the optimal transmission power of the uplink unit (200) as the solution to the optimization problem generated, and provides them to the base station.

[0162] The base station determines the transmission power by reflecting the optimal transmission power of the downlink section (100), the optimal power division coefficient, and the optimal transmission power of the uplink section (200), and provides the transmission signal of the determined transmission power, the optimal power division coefficient, and the optimal transmission power of the uplink section (200) to the user terminal, thereby maximizing the energy efficiency of the user terminal and enabling stable communication with low power.

[0163] That is, the central processing unit (3) generates a problem P0 that minimizes the total transmission power energy, then optimizes the generated problem P0 using linear programming (LP) to generate an optimization problem P0, and generates optimization problems P1 and P2 respectively that minimize the transmission power of the downlink unit (100) and the transmission power of the uplink unit (200) each including a non-linear SINR from the generated optimization problem P0, and derives the optimal transmission power of the uplink unit (200) that minimizes the sum of the energy of the transmission power of the uplink unit (200) of each user terminal (21~2K), the optimal power division coefficient of the downlink unit (100), and the optimal transmission power of the downlink unit (100) that minimizes the total transmission power energy using the solutions of the generated optimization problems P1 and P2. Referring to FIG. 4, the system is configured to derive an optimization problem generation unit (310), an uplink optimal transmission power calculation unit (320), an optimal power division coefficient calculation unit (330), and a downlink optimal transmission power It may include an operation unit (340).

[0164] First, the optimization problem generation unit (310) of the central processing unit (3) has a threshold value of QoS of the downlink unit (100). and the threshold value of QoS of the uplink section (200) Each is defined by the following Equation 21.

[0165] [Equation 21]

[0166]

[0167] Here, and This is the SINR threshold of the k-th user terminal (2k). Accordingly, the optimization problem generation unit (310) of the central processing unit (3) [is the total transmission power of the downlink unit (100). The problem P0 and constraints (22a~22f) for minimizing can be expressed by the following Equation 22.

[0168] [Equation 22]

[0169] P0:

[0170] Here,

[0171] (22a)

[0172] (22b)

[0173] (22c)

[0174] (22d)

[0175] (22e)

[0176] (22f)

[0177] That is, according to constraint 22a, the transmission power of the downlink section (100) of the base station (AP) is the maximum transmission power The transmission power of the uplink section (200) of each user terminal cannot exceed, and in accordance with constraint 22b This maximum available power It cannot exceed, and the power splitting factor according to constraint 22c and, energy harvested according to constraint 22d is the power consumption of the k-th user terminal (2k). It must be larger, and constraints 22e and 22f are QoS conditions for the downlink section (100) and the uplink section (200).

[0178] Here, harvested energy is the power consumption of the k-th user terminal (2k). Based on the constraint 22d that it must be greater than, the problem PO is non-convex.

[0179] Accordingly, the optimization problem generation unit (310) optimizes the problem P0 of the total transmission power based on linear programming (LP) to generate the optimization problem P0.

[0180] That is, since the total energy decreases when the harvested energy decreases, the transmission power of the downlink section (100) is It is set to, and accordingly, the energy harvested from the k-th user terminal (2k) It can be summarized as Equation 23 below.

[0181] [Equation 23]

[0182] =

[0183] Here, the harvested energy when e1 and e2 are at their maximum is maximum, and the upper and lower bounds for e1 and e2 are calculated by the Cauchy-Schwarz inequality, and the upper and lower bounds for e1 and e2 can be expressed by Equation 24 below.

[0184] [Equation 24]

[0185]

[0186] Transmission power of the downlink section (100) in Equation 23 is the effective channel gain It is maximized when varying linearly with respect to . Transmission power of the downlink section (100) It can be summarized by the following equation 25.

[0187] [Equation 25]

[0188]

[0189] Here, am.

[0190] In other words, effective channel gain Regarding the transmission power of the downlink section (100) ...varies linearly, and the total transmitted power is derived from Equation 26 below, and the derived total power is expressed by Equation 26 and constraint 26a below.

[0191] [Equation 26]

[0192] Optimization Problem P0:

[0193] The above constraints are

[0194] (26a) and,

[0195] Here,

[0196] ,

[0197] ,

[0198]

[0199]

[0200]

[0201] The optimization problem generation unit (310) generates the transmission power optimization problem P1 of the uplink unit (200) and the transmission power optimization problem P2 of the downlink unit (100) from the optimization problem P0 of Equation 26 generated based on linear programming (LP).

[0202] At this time, the problem of optimizing the transmission power of the uplink section (200) P1 can be summarized by the following Equation 27 and constraint 27a, and the problem of optimizing the transmission power of the downlink section (100) P2 can be summarized by Equation 28 and constraints 28a to 28d.

[0203] [Equation 27]

[0204] P1:

[0205] The constraint here is (27a) is.

[0206] [Equation 28]

[0207] P2:

[0208] The constraint here is

[0209] (28a) is.

[0210] Meanwhile, the uplink optimal transmission power calculation unit (320) calculates the optimal transmission power of the uplink unit (200) as the solution to problem P1 of Equation 27. Derived. That is, the energy for the transmission of the pilot signal in Equation 23 Since is a constant, problem P1 can be expressed by the following equation 29 and constraint 29a.

[0211] [Equation 29]

[0212] =

[0213] Here, (29a)

[0214] Optimal transmission power of the uplink section (100) in Equation 29 It can be defined by the following Equation 30.

[0215] [Equation 30]

[0216]

[0217] Here, And,

[0218] It is defined as.

[0219] Optimal transmission power of the uplink section (100) of the k-th user terminal (2k) When this is determined, the total transmission power energy of the k-th user terminal (2k) is the sum of the transmission power energy of the information signal and the transmission power energy of the pilot signal. It is determined as, where, the energy of the optimal transmission power of the information signal is am.

[0220] Accordingly, the optimal power division coefficient calculation unit (330) of the central processing unit (3) calculates the optimal power division coefficient for harvesting only the necessary energy of the downlink unit (100). It is derived from the following Equation 31.

[0221] [Equation 31]

[0222]

[0223] Here, harvested energy and, accordingly, constraints Optimal power splitting factor satisfying This is derived.

[0224] And, the downlink optimal transmission power calculation unit (340) of the central processing unit (3) calculates the optimal transmission power of the downlink unit (200). The optimization problem P2 for deriving can be expressed by the following Equation 32 and constraints 32a to 32c.

[0225] [Equation 32]

[0226] =

[0227] Here, the constraint is

[0228] (32a) is.

[0229] Accordingly, the optimal transmission power calculation unit (340) can derive the downlink optimal transmission power as the solution to the optimization problem P2 of Equation 32 that satisfies the constraint of Equation 32a.

[0230] And, one embodiment is the optimal transmission power of the uplink section (200). is derived from Equation 29, and the optimal power splitting coefficient is based on Equation 31, and the optimal transmission power of the downlink section (100) It is derived based on Equation 32.

[0231] FIG. 5 is a diagram showing the operation process of the central processing unit of FIG. 4. With reference to FIG. 5, a CF mMIMO-based SWIPT communication process using linear programming according to another embodiment of the present invention is explained.

[0232] That is, it may further include a computer-readable recording medium characterized by having a program recorded thereon for executing a CF mMIMO-based SWIPT communication method using linear programming on a computer, and may further include a computer program stored on the computer-readable recording medium to be combined with a computer to execute a CF mMIMO-based SWIPT communication method using linear programming on a computer. Referring to FIG. 5, the CF mMIMO-based SWIPT communication method using linear programming of the computer program may include an optimization problem generation step (S100), an uplink optimal transmission power calculation step (S200), an optimal power division coefficient calculation step (S300), and a downlink optimal transmission power calculation step (S400).

[0233] Here, the optimization problem generation step (S100) generates a problem P0 that minimizes total transmission power energy (S110), optimizes the generated problem P0 based on linear programming (S120), and derives uplink optimization problem P1 and downlink optimization problem P2 from the optimized problem P0 (S130).

[0234] And the uplink optimal transmission power calculation step (S200) derives the uplink optimal transmission power that satisfies the optimization problem P1 and the predefined constraints.

[0235] Meanwhile, the optimal power division coefficient calculation step (S300) derives an optimal power division coefficient that satisfies predefined constraints from the total transmission power energy derived from the sum of the energy of the derived uplink optimal transmission power and the energy of the pilot transmission power.

[0236] And, the downlink optimal transmission power calculation step (S400) derives the downlink optimal transmission power as the solution to the optimization problem P2.

[0237] FIG. 6 is a diagram showing the operation process of the downlink optimal transmission power calculation step (S400) of FIG. 5, and the process of deriving the downlink optimal transmission power is explained in detail with reference to FIG. 6.

[0238] First, the downlink optimal transmission power calculation step (S400) is a power division coefficient a value between 0 and 1, that is, Initialize to (Step 1), and the uplink optimal transmission power of the uplink optimal transmission power calculation step (S200) Calculate (Step 2).

[0239] The downlink optimal transmission power calculation step (S400) derives the total power transmission energy using the uplink optimal transmission power, power division coefficient, and downlink power transmission.

[0240] Accordingly, the downlink optimal transmission power calculation step (S400) is the upper limit of the total power transmission energy , lower limit of total power transmission energy , and the average value of the energy of downlink power transmission Initialize the upper limit, lower limit, and average value of the total power transmission energy (Step 3).

[0241] Meanwhile, the downlink optimal transmission power calculation unit (340) calculates the optimization problem P2 using the convex optimization (CVX) technique (step 5), and if the solution to the optimization problem P2 satisfies the constraints previously defined for the optimization problem P2, the upper limit of the total transmission power energy is set as the average value, and If the constraints of , 32a are not satisfied, the lower limit of the total transmitted power energy is set to the average value. (Step 6).

[0242] Accordingly, the upper and lower limits of the total transmitted power energy are gradually reduced to the average value to search for a total transmitted power energy that satisfies the constraints of the above optimization problem P2.

[0243] And, the downlink optimal transmission power calculation unit (340) provides the total transmission power of step 6 to the optimal power division coefficient calculation step (S300), and the optimal power division coefficient calculation step (S300) provides the optimal power division coefficient Derive (Step 7).

[0244] Afterwards, the downlink optimal transmission power calculation unit (340) updates the average value of the total transmission power energy (step 8) and then repeats the process until the difference between the upper and lower limits of the total transmission power energy does not exceed a predetermined threshold value (step 8). That is, Accordingly, the downlink optimal transmission power calculation unit (340) repeats the process until the difference between the upper limit and lower limit of the total transmission power energy converges to a predetermined threshold value.

[0245] And, the downlink optimal transmission power calculation unit (340) calculates the downlink optimal transmission power as the solution to the optimization problem P2 of Equation 34 if the difference between the upper limit value and the lower limit value of the average value does not exceed a predetermined threshold value. Update (Step 9).

[0246] The derived uplink optimal transmission power, optimal power division factor, and downlink optimal transmission power are transmitted to the base station, and the base station adjusts the transmission power based on the received uplink optimal transmission power, optimal power division factor, and downlink optimal transmission power, and provides the transmission signal, uplink optimal transmission power, and optimal power division factor to the user terminal.

[0247] Accordingly, one embodiment can maximize the energy efficiency of the user terminal and perform stable communication with low power.

[0248] The embodiments described above may be implemented as hardware components, software components, and / or combinations of hardware and software components. For example, the devices, methods, and components described in the embodiments may be implemented using one or more general-purpose or special-purpose computers, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and one or more software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are also possible.

[0249] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or command the processing unit independently or collectively. Software and / or data may be permanently or temporarily embodied in any type of machine, component, physical device, virtual equipment, computer storage medium or device, or transmitted signal wave so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

[0250] 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 on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., either alone or in combination. The program instructions recorded on the computer-readable medium may be those specifically designed and configured for the embodiment, or they may be those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The above-mentioned hardware devices may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

[0251] Although the embodiments have been described above with reference to the limited drawings, those skilled in the art can apply various technical modifications and variations based on the above. For example, suitable results may be achieved even if the described techniques are performed in a different order than described, and / or if the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0252] [Explanation of the symbol]

[0253] 11~1L: Base Station

[0254] 21~2K: User terminal

[0255] 3: Central Processing Unit

[0256] 100: Downlink section

[0257] 200: Uplink section

[0258] 310: Optimization Problem Generation Section

[0259] 320: Uplink Optimal Transmission Power Calculation Unit

[0260] 330: Optimal Power Division Factor Calculation Unit

[0261] 340: Downlink Optimal Transmission Power Calculation Unit

Claims

1. At least one base station; At least two user terminals performing a downlink for receiving a transmission signal from a base station and an uplink for transmitting a generated pilot signal to a base station; and It includes a central processing unit connected to the above base station, and The above central processing unit is, The system is configured to derive the uplink optimal transmission power, the optimal power division factor, and the downlink optimal transmission power as a solution to the problem of minimizing the total transmission power energy, and to provide the derived uplink optimal transmission power, the optimal power division factor, and the downlink optimal transmission power to the base station. A CF mMIMO-based SWIPT communication system using linear programming, characterized in that the base station controls a transmission signal with the uplink optimal transmission power, optimal power division factor, and downlink optimal transmission power of the received central processing unit, and is configured to provide the uplink optimal transmission power and the optimal power division factor to at least two user terminals.

2. In paragraph 1, the central processing unit is, An optimization problem generation unit that generates a problem P0 that minimizes the total transmission power energy of a user terminal, then optimizes the generated problem P0 using linear programming to generate an optimization problem P0, and generates an uplink optimization problem P1 and a downlink optimization problem P2 from the generated optimization problem P0; An uplink optimal transmission power calculation unit that derives an uplink optimal transmission power satisfying predefined constraints for the above optimization problem P1; An optimal power division coefficient calculation unit that derives an optimal power division coefficient satisfying predefined constraints from the total transmission power energy derived from the sum of the energy of the derived uplink optimal transmission power and the energy of the pilot transmission power; and A CF mMIMO-based SWIPT communication system using linear programming, characterized by including a downlink optimal transmission power calculation unit that calculates the downlink optimal transmission power as a solution to the optimization problem P2 derived using an iterative method.

3. In paragraph 2, the downlink optimal transmission power calculation unit is, After initializing the average value with the upper and lower bounds of the total transmitted power energy, derive the solution to optimization problem P2 that minimizes the total transmitted power energy using the block optimization (CVX: Convex Optimization) technique, and If the constraints for the derived optimization problem P2 are satisfied, the upper limit of the total transmitted power energy is set to the average value, and Deriving an optimal power splitting coefficient that satisfies predefined constraints from the total transmitted power energy of the above average value, Based on the above optimal power division coefficient, the average value of the total transmitted power energy is updated, and A CF mMIMO-based SWIPT communication system using linear programming configured to update the downlink optimal transmission power derived as the solution to the optimization problem P2 that minimizes the average value of the total transmission power energy when the difference between the upper and lower limits of the total transmission power energy does not exceed a predetermined threshold value.

4. In paragraph 3, the above-mentioned downlink optimal transmission power calculation unit A CF mMIMO-based SWIPT communication system using linear programming, characterized by being configured to repeat the process until the difference between the upper and lower limits of the total transmission power energy derived by the convex optimization technique converges to a predetermined threshold when the difference between the upper and lower limits of the total transmission power energy exceeds a predetermined threshold.

5. A CF mMIMO-based SWIPT communication method using linear programming performed according to a CF mMIMO-based SWIPT communication system using linear programming of Claim 1, wherein At least one processor included in a CF mMIMO-based SWIPT communication system using the above linear programming method is, An optimization problem generation step of generating a problem P0 that minimizes total transmission power energy, then optimizing the generated problem P0 based on linear programming, and then deriving uplink optimization problem P1 and downlink optimization problem P2 from the optimized problem P0; An uplink optimal transmission power calculation step for deriving an uplink optimal transmission power that satisfies the above optimization problem P1 and predefined constraints; An optimal power division coefficient calculation step for deriving an optimal power division coefficient satisfying predefined constraints from the total transmission power energy derived from the sum of the energy of the derived uplink optimal transmission power and the energy of the pilot transmission power; and A CF mMIMO-based SWIPT communication method using linear programming, characterized by including a downlink optimal transmission power calculation step that derives the downlink optimal transmission power as a solution to the above optimization problem P2.

6. In paragraph 5, the downlink optimal transmission power calculation step is A step of deriving the upper limit, lower limit, and average value of the total transmitted power energy, respectively, and then deriving the solution to optimization problem P2 that minimizes the total transmitted power energy using a block optimization (CVX: Convex Optimization) technique; A step of setting the upper limit of the total transmitted power energy to the average value when the constraints for the derived optimization problem P2 are satisfied, A step of deriving an optimal power splitting coefficient that satisfies the average value of the total transmitted power energy and predefined constraints, A step of updating the average value of the total transmitted power energy based on the above optimal power division coefficient, A CF mMIMO-based SWIPT communication method using linear programming, comprising a step of updating the downlink optimal transmission power derived as the solution to the optimization problem P2 that minimizes the average value of the total transmission power energy when the difference between the upper and lower limits of the total transmission power energy does not exceed a predetermined threshold value.

7. In paragraph 6, the downlink optimal transmission power calculation step is, A CF mMIMO-based SWIPT communication method using linear programming, characterized by further including a step of repeating the process until the difference between the upper and lower limits of the transmission power energy of the downlink derived by the convex optimization technique converges to a predetermined threshold when the difference between the upper and lower limits of the total transmission power energy exceeds a predetermined threshold.

8. A recording medium capable of being judged by a computer, on which a program for executing a CF mMIMO-based SWIPT communication method using linear programming according to any one of paragraphs 5 through 7 is recorded.

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