KR20170006587A - Beamforming method and device for joint localization and data transmission in distributed antenna systems - Google Patents

Abstract

The present invention relates to a beamforming method and apparatus for adjusting a beamforming vector such that power consumption is minimized in a communication system in which there is an asynchronous error between a transmitter for transmitting a signal and a receiver for receiving the signal, Transmitting a first signal to the terminal using the second communication unit and transmitting the first signal to the terminal using the second communication unit, estimating a location of the terminal based on a Time Difference Of Arrival (TDOA) of the plurality of signals, Transmitting data to the terminal based on the beamforming vector, receiving information on a data rate at which the terminal received data from the terminal, and transmitting the estimated position of the terminal and the actual Is not within a predetermined range of positional accuracy, or if the received data rate is less than If more than the defined data rate small, and a step of adjusting the beam-forming vector is the power consumption for the transmission of the data is minimized.

Description

BACKGROUND OF THE INVENTION Field of the Invention [0001] The present invention relates to a beamforming method and apparatus in a distributed antenna system for simultaneously supporting a position estimation service and a data communication,

Field of the Invention relates to a technology for providing a beamforming vector, and more particularly, to a beamforming method and apparatus for adjusting a beamforming vector according to a communication environment of a base station and a terminal.

As the mobile communication system evolves into information society, it becomes a core technology as infrastructure for social, economic and cultural activities. A method of generating a transmission signal for a high information transmission rate and a low transmission error rate and a beamforming method using multiple antennas have been studied. 2. Description of the Related Art [0002] With the development of mobile communication systems, a mobile communication system can provide various services rather than simply providing data communication. Recently, a technology for estimating the position of a mobile terminal in a communication network has attracted attention. In other words, technologies for locating users in disasters and emergencies caused by large-scale accidents such as terrorism, gas leakage, and war, as well as natural disasters such as indoor and building shadows, typhoons and earthquakes, have.

The positioning technique may be a technique for measuring the position of a user or a mobile terminal. The positioning technique can be classified into a method based on a network using a base station received signal of a communication network and a method based on a terminal using a GPS receiver mounted on the mobile terminal. In addition, there may be a mixing method in which the above methods are mixed and used.

The network-based approach may have different location accuracies depending on the cell size and measurement method of the base station, and may typically have measurement errors of several hundred meters to several kilometers. On the other hand, the terminal-based method may require the terminal to additionally include a signal receiving device such as a GPS receiver. The terminal-based approach may be more accurate than the network-based approach. However, the terminal-based method may be difficult to estimate the location because it does not properly receive the GPS reception signal in the shadowed area of the GPS, such as a densely populated urban area, forest, or indoor area.

Such conventional positioning techniques have been proposed for the purpose of improving positional accuracy. However, there is no research on the apparatus and method for providing services other than the position estimation service together with the position estimation service. Accordingly, in providing the location estimation service, it is required to consider the data communication, which is a fundamental requirement of the existing communication network.

Korean Patent Publication No. 10-2014-0014355 (published on Feb. 27, 2015) discloses an apparatus and method for adjusting a beamforming vector. In particular, an apparatus and method for generating a beamforming vector using a method of estimating a position of a terminal based on a time of arrival (TOA) of a signal transmitted from a base station to a terminal are disclosed. The method of generating the beamforming vector based on the arrival time (TOA) can be used only on the assumption that synchronous communication is performed between the base station and the terminal. That is, if the base station and the terminal perform asynchronous communication, the disclosed apparatus and method can not generate a beamforming vector.

The present invention is directed to solving the above-mentioned problems and other problems.

Another object is to a beamforming method and apparatus for adjusting a beamforming vector such that power consumption is minimized when the base station and the terminal perform asynchronous communication.

According to an embodiment of the present invention for realizing the above-mentioned problem

A method of generating a beamforming vector of a base station for a terminal performed by an electronic device according to an embodiment of the present invention includes generating a beamforming Covariance matrix using a first beamforming vector, Calculating a lower limit of the Weiss Fischer information matrix; Calculating a Fisher information matrix by a block coordinate iterative method for method 2; A Schur complement condition for positive semidefinite is applied to Method 1 and Method 2 and the position of the terminal estimated using the beamforming Covariance matrix and the position of the terminal Generating a matrix of positional accuracy between actual positions; Linearizing a non-convex portion of a function related to a data rate at which the terminal receives data from the base station using the generated beamforming Covariance matrix; A first condition that the position accuracy is within a predetermined position accuracy range based on a matrix for the position accuracy and a function related to the linearized data rate and a second condition that the data rate is equal to or greater than a predetermined data rate. Generating a Forming Covariance matrix; Generating a second beamforming vector satisfying a third condition such that power consumption for transmission of the data is minimized based on the local beamforming Covariance matrix; And calculating a power consumption of Method 1 and Method 2 to select a beamforming vector that generates a minimum power among the calculated power consumption.

An electronic device according to an embodiment of the present invention includes a beamforming Covariance matrix generator for generating a beamforming Covariance matrix using a first beamforming vector, Calculating a block coordinate iterative method and applying a Schur complement condition for a positive semidefinite to the block coordinate iterative method, A position accuracy generator for generating a matrix about positional accuracy between a position of a terminal estimated using a Covariance matrix and an actual position of the terminal, a terminal using the generated beamforming Covariance matrix, A linearization unit for linearizing a non-convex part of a function related to a data rate at which data is received, And a local beamforming Correlation matrix satisfying a first condition that the positional accuracy is within a range of predetermined positional accuracy and a second condition that the data rate is equal to or greater than a predetermined data rate based on a function related to the linearized data rate, And generating a second beamforming vector that satisfies a third condition such that power consumption for transmission of the data is minimized based on the local beamforming Covariance matrix.

Effects of the terminal and the control method according to the present invention will be described as follows.

Since the asynchronous situation in which the clock offset between the base station and the terminal exists is considered, the beamforming vector can be adjusted so that power consumption for data transmission is minimized even in an asynchronous system.

The effects obtained by the present invention are not limited to the above-mentioned effects, and other effects not mentioned can be clearly understood by those skilled in the art from the following description will be.

FIG. 1 is a conceptual diagram for explaining a method of estimating a position of a terminal according to an example;
2 is a block diagram of a wireless communication system according to an embodiment of the present invention.
3 is a conceptual diagram for explaining a control method of an electronic device according to an embodiment of the present invention.
4 is a flowchart of a method of adjusting a beamforming vector based on a beamforming Covariance matrix according to an example.
5 is a conceptual diagram illustrating a beamforming vector adjustment system according to a distance difference between two terminals according to an example;
6 is a graph showing average power consumption of base stations according to a distance difference between two terminals according to an example;
FIG. 7 is a graph showing the results of selectively using the two different beam-forming design techniques described above with reference to FIG.
FIG. 8 is a block diagram of an exemplary embodiment of the present invention,
9 and 10 are block diagrams illustrating an electronic device according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like reference numerals are used to designate identical or similar elements, and redundant description thereof will be omitted. The suffix "module" and " part "for the components used in the following description are given or mixed in consideration of ease of specification, and do not have their own meaning or role. In the following description of the embodiments of the present invention, a detailed description of related arts will be omitted when it is determined that the gist of the embodiments disclosed herein may be blurred. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are intended to provide further explanation of the invention as claimed. , ≪ / RTI > equivalents, and alternatives.

Terms including ordinals, such as first, second, etc., may be used to describe various elements, but the elements are not limited to these terms. The terms are used only for the purpose of distinguishing one component from another.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between.

The singular expressions include plural expressions unless the context clearly dictates otherwise.

In the present application, the terms "comprises", "having", and the like are used to specify that a feature, a number, a step, an operation, an element, a component, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

FIG. 1 illustrates a method of estimating a position of a terminal according to an example.

The terminal described in this specification may be a mobile phone, a smart phone, a laptop computer, a digital broadcasting terminal, a personal digital assistant (PDA), a portable multimedia player (PMP), a navigation device, a slate PC, A tablet PC, an ultrabook, a wearable device (e.g., a smartwatch, a smart glass, a head mounted display (HMD), etc.) .

The mobile terminal includes a mobile communication module, and the mobile communication module includes a mobile communication module, a mobile communication module, and a mobile communication module. The mobile communication module includes at least one of technical standards or a communication method (e.g., Global System for Mobile communication, CDMA, WCDMA, (E.g., CDMA), HSDPA (High Speed Downlink Packet Access), LTE (Long Term Evolution), etc.)

In addition, the terminal may include a location information module. The location information module is for acquiring the location of the terminal, and representative examples thereof may include a Global Position System (GPS) module and a WiFi (Wireless Fidelity) module. The GPS module calculates distance information and accurate time information from three or more satellites, and then applies trigonometry to the calculated information, thereby accurately calculating three-dimensional current location information according to latitude, longitude, and altitude . At present, a method of calculating position and time information using three satellites and correcting an error of the calculated position and time information using another satellite is widely used. In addition, the GPS module can calculate speed information by continuously calculating the current position in real time. However, it is difficult to accurately measure the position of a terminal using a GPS module in a shadow area of a satellite signal, such as in a room. Accordingly, a WPS (WiFi Positioning System) can be utilized to compensate the positioning of the GPS system.

A WiFi Positioning System (WPS) is a technology for tracking a position of a terminal using a WiFi module provided in the terminal and a wireless AP (Wireless Access Point) transmitting or receiving a wireless signal with the WiFi module, Means a wireless local area network (WLAN) based positioning technology using WiFi.

The WiFi location tracking system may include a Wi-Fi location server, a terminal, a wireless AP connected to the terminal, and a database in which certain wireless AP information is stored.

The terminal connected to the wireless AP can transmit the location information request message to the Wi-Fi location server.

The Wi-Fi position location server extracts information of the wireless AP connected to the terminal based on the location information request message (or signal) of the terminal. The information of the wireless AP connected to the terminal may be transmitted to the Wi-Fi position location server through the terminal or may be transmitted from the wireless AP to the Wi-Fi location server.

The information of the wireless AP to be extracted based on the location information request message of the terminal includes at least one of MAC Address, SSID, RSSI, channel information, Privacy, Network Type, Signal Strength and Noise Strength .

As described above, the Wi-Fi position location server can receive the information of the wireless AP connected to the terminal and extract the wireless AP information corresponding to the wireless AP to which the terminal is connected from the pre-established database. In this case, the information of any wireless APs stored in the database includes at least one of MAC address, SSID, channel information, privacy, network type, radius coordinates of the wireless AP, building name, Available), the address of the AP owner, telephone number, and the like. At this time, in order to remove the wireless AP provided using the mobile AP or the illegal MAC address in the positioning process, the Wi-Fi location server may extract only a predetermined number of wireless AP information in order of RSSI.

Then, the Wi-Fi location server can extract (or analyze) location information of the terminal using at least one wireless AP information extracted from the database. And compares the received information with the received wireless AP information to extract (or analyze) the location information of the terminal.

A Cell-ID method, a fingerprint method, a triangulation method, a landmark method, and the like can be utilized as a method for extracting (or analyzing) position information of a terminal.

The Cell-ID method is a method for determining the location of the wireless AP having the strongest signal strength among the neighboring wireless AP information collected by the terminal as the location of the terminal. Although the implementation is simple, it does not cost extra and it can acquire location information quickly, but there is a disadvantage that positioning accuracy is lowered when the installation density of the wireless AP is low.

The fingerprint method collects signal strength information by selecting a reference position in a service area, and estimates the position based on the signal strength information transmitted from the terminal based on the collected information. In order to use the fingerprint method, it is necessary to previously convert the propagation characteristics into a database.

The triangulation method is a method of calculating the position of the terminal based on the coordinates of at least three wireless APs and the distance between the terminals. In order to measure the distance between the terminal and the wireless AP, the signal strength may be converted into distance information or the time of arrival (ToA) of the wireless signal may be used.

The landmark method is a method of measuring the position of a terminal using a landmark transmitter that knows the location.

The location information of the extracted terminal is transmitted to the terminal through the Wi-Fi location server, so that the terminal can acquire the location information.

The terminal may be connected to at least one wireless AP to obtain location information. At this time, the number of wireless APs required to acquire the location information of the terminal may be variously changed according to the wireless communication environment in which the terminal is located.

Meanwhile, a network as shown in FIG. 1 may be considered as a method of estimating the position of a terminal. The network of FIG. 1 includes a plurality of base stations A to C and a plurality of terminals.

Here, the terminal assumes that the location information of the base stations is known accurately. For example, the base station can transmit the signal including the unique position information to the signal transmitted to the terminal. As another example, the terminal may acquire location information of a base station stored in a memory or a server.

In addition, it is assumed that there is an asynchronous error between the transmitter that transmits the signal and the receiver that receives the signal. For example, it is assumed that there is an asynchronization error between the transmitting terminal and the receiving terminal, or between the terminal and the base station.

Under the above-mentioned premise, the base station can transmit a signal to the terminal. Due to the asynchronous assumption of the transmission / reception period, the terminal obtains the distance information by the difference of the reception times of two base stations, not one base station. Then, the terminal can generate a virtual hyperbola focusing on the two base stations from which the signal is generated, and estimate the intersection of the generated hyperbolas as the position of the terminal.

A method of estimating the position of the UE based on the difference in transmission arrival time of such a signal is referred to as a time of difference arrival (TDOA) method.

The TDOA method assumes asynchronization between a transmitter and a receiver of a signal.

As another example, a terminal may transmit signals to a plurality of base stations. Due to the asynchronous assumption of the transmission / reception period, the base stations acquire the distance information by the difference in the reception time of the signal received from the terminal. The plurality of base stations can estimate the location of the terminal using a time difference of arrival (TDOA) of a signal received from the terminal.

The method includes transmitting a signal to a terminal based on a beamforming vector performed by an electronic device, estimating a position of the terminal based on the transmitted signal, transmitting data to the terminal based on the beamforming vector, Receiving information on a data rate at which the terminal received data from the terminal, and determining whether the position accuracy between the estimated position of the terminal and the actual position of the terminal is not within a predetermined range of positional accuracy Adjusting the beamforming vector such that power consumption for transmission of the data is minimized when the received data rate is smaller than a predetermined data rate.

The transmitting of the signal may transmit the signal during the pilot interval of the pilot interval and the data transmission interval.

A plurality of signals may be transmitted to the terminal.

The plurality of signals may be transmitted through a plurality of antennas of the electronic device, respectively.

The step of estimating the location of the terminal may estimate the location of the terminal based on a Time Difference Of Arrival (TDOA) of the plurality of signals.

The beamforming vector adjustment method may further include determining whether the position accuracy is within the predetermined position accuracy range.

The beamforming vector adjustment method may further include determining whether a data rate at which the terminal received the data is greater than the predetermined data rate.

The signal may be generated using at least one of the beamforming vector and the pilot information including a pilot code shared by the electronic device and the terminal.

The data rate at which the terminal received the data may be calculated based on the effective channel gain of the terminal and the signal transmitted by the electronic device for the other terminal.

The positional accuracy can be calculated based on a Fisher information matrix associated with the beamforming vector.

The step of adjusting the beamforming vector may comprise generating a beamforming Covariance matrix of the beamforming vector.

The step of adjusting the beamforming vector may further comprise generating a local beamforming Covariance matrix by linearizing a function on the received data rate using the generated beamforming Covariance matrix.

The step of adjusting the beamforming vector may further comprise adjusting the beamforming vector based on the local beamforming coercivity matrix.

Wherein generating the local beamforming Covariance matrix comprises linearizing the non-convex portion of the function related to the received data rate using a majorization-minimization algorithm, A beamforming Covariance matrix can be generated.

Generating the local beamforming Covariance matrix may further comprise selecting two beamforming Covariance matrix generation methods according to the degree of the amount of information possessed for the asynchronization error.

The step of generating the local beamforming Covariance matrix may further comprise the step of changing the positioning requirement into a semi-definite programming (SDP) form in accordance with a Schur complement condition. have.

Generating the local beamforming Covariance matrix may further comprise generating a lower limit of the Fischer information matrix associated with the beamforming Covariance matrix.

Wherein generating the local beamforming Covariance matrix comprises applying a block coordinate iterative method to convex the non-convex nature of the Fischer information matrix associated with the beamforming Covariance matrix The method may further include the step of considering only the beamforming Covariance matrix of the base station to be used with the remaining beams, and fixing the remaining beamforming Covariance matrix.

A communication system comprising: a communication unit for transmitting a signal to a terminal based on a beamforming vector; and a processor for estimating a position of the terminal based on the transmitted signal, the communication unit comprising: Wherein the processor receives information on a data rate at which the terminal received data from the terminal, and the processor determines whether the positional accuracy between the estimated terminal position and the terminal's actual position is within a predetermined range of positional accuracy And adjusting the beamforming vector such that power consumption for transmission of the data is minimized when the data rate is not, or when the data rate is smaller than a predetermined data rate.

A method of generating a beamforming vector of a base station for a terminal performed by an electronic device, the method comprising: generating a beamforming coercivity matrix using a first beamforming vector; The first method comprises generating a lower limit of the Fisher information matrix of TDOA based position estimates, using a second method, a block coordinate iterative method, a positive semi-limited method for both the first method and the second method a Schur complement condition for a positive semidefinite is applied to generate a matrix of positional accuracy between the position of the estimated terminal using the beamforming Covariance matrix and the actual position of the terminal , A function of the terminal using the generated beamforming Covariance matrix with respect to a data rate at which data is received from the base station, Linearizing a portion that is not convex, a first condition that the positional accuracy is within a predetermined position accuracy range based on a function of the matrix about the positional accuracy and the linearized data rate, Generating a local beamforming Covariance matrix that satisfies a second condition that is equal to or greater than a data rate of the local beamforming Covariance matrix and a third condition that minimizes power consumption for transmission of the data based on the local beamforming Covariance matrix And generating a second beamforming vector to be used for generating the second beamforming vector.

CLAIMS What is claimed is: 1. An electronic device comprising: a beamforming Covariance matrix generator for generating a beamforming Covariance matrix using a first beamforming vector; generating a lower limit of a Fisher information matrix; A Fisher information matrix transformer for transforming a Fisher information matrix using a beamforming Covariance matrix and applying a Schur complement condition for the positive semidefinite, A position accuracy generator for generating a matrix of positional accuracy between a position of a terminal and an actual position of the terminal, A linearization unit for linearizing the non-convex part of the function, a matrix for the positional accuracy, Generating a local beamforming coercivity matrix that satisfies a first condition that the positional accuracy is within a predetermined range of positional accuracy and a second condition that the data rate is equal to or greater than a predetermined data rate based on a function related to the data rate, And a controller for generating a second beamforming vector that satisfies a third condition such that power consumption for transmission of the data is minimized based on the local beamforming Covariance matrix.

The method comprising: transmitting a signal to a terminal based on a beamforming vector, the base station performing a processing by a system including a base station and a central unit connected to the base station, the base station estimating a position of the terminal based on the transmitted signal The base station transmitting data to the terminal based on the beamforming vector, receiving information on a data rate at which the base station receives data from the terminal, and transmitting, by the central unit, When the position accuracy between the estimated position of the terminal and the actual position of the terminal is not within the range of the predetermined position accuracy or when the received data rate is smaller than the predetermined data rate, Adjusting the beamforming vector such that consumption is minimized, A beamforming vector adjustment system is provided.

A network as shown in FIG. 1 can be considered as a method of estimating the position of the terminal. The network of FIG. 1 may be a network between a plurality of base stations and terminals. Assuming that the terminal fully knows the location information of the base station, it is assumed that there is an asynchronous error between the transceivers. The base station can transmit a signal to the terminal. Due to the asynchronous assumption of the transmission / reception period, the terminal obtains the distance information by the difference of the reception times of the two base stations, not the one base station. More specifically, it is possible to generate a virtual hyperbola focusing on the two base stations from which the signal is generated. The intersection of the generated hyperbolas can be estimated as the position of the terminal. A method of estimating the position of the UE based on the difference in transmission arrival time of such a signal can be referred to as a Time Of Difference Arrival (TDOA) method. The TDOA method presupposes the asynchronization between the transmitter and the receiver of the signal.

A service for providing data communication between the base station and the terminal, and a service for estimating the position of the terminal can be individually provided. In addition, a service for providing data communication and a service for estimating the location of the terminal can be provided at the same time.

A large power consumption of the base station may be required to simultaneously provide the above services. As a method for reducing the power consumption, a method of considering both the amount of data to be provided to the terminal and the accuracy of the position estimation of the terminal can be used.

2 is a block diagram of a wireless communication system according to an embodiment of the present invention. 2 is a diagram illustrating a multi-user distributed antenna system model supporting simultaneous data communication and position estimation services.

A service for providing data communication between the base station and the terminal, and a service for estimating the position of the terminal can be individually provided. In addition, a service for providing data communication and a service for estimating the location of the terminal can be provided at the same time.

A large power consumption of the base station may be required to simultaneously provide the above services. As a method for reducing the power consumption, a method of considering both the amount of data to be provided to the terminal and the accuracy of the position estimation of the terminal can be used. If the position of the terminal is accurately estimated, the base station can increase the data rate that can be provided to the terminal while consuming minimum power by using the beamforming technique.

The system 200 for adjusting the beamforming vector may be a system of one or more devices.

According to one example, the system 200 may include a central unit 205 and a base station 210. For example, the system 200 may include a plurality of base stations 210-240.

Each base station can communicate with the central unit 205. The communication may be wired communication or wireless communication.

The base station 210 may include multiple antennas.

The system 200 includes N _B base stations with multiple antennas in the δxδ-size region and N _M terminals with a single antenna. Here,? Represents an arbitrary length. For example, referring to FIG. 2, N _B base stations may be base stations 210 to 240, and N _M terminals may be terminals 252 to 256. Each terminal in the system 200 can receive data from all base stations. Also, each terminal can estimate the location of the terminal using the arrival time difference (TDOA) method based on the signal received from the base stations.

In the present invention, the location of the terminal is based on two-dimensional location information, and the location information of the base station j and the terminal i is defined by Equation 1 and Equation 2, respectively. Base station j means any base station in the system 200 and terminal i can be any terminal in the system 200. [ i and j may be an integer of 1 or more.

In Equation (1), P _{B , j} is position information of the base station j, x _{B , j} is position information of the x axis of the base station j, and y _{B , j} is position information of the y axis of the base station j.

In Equation (2), P _{M , i} is position information of terminal i, x _{M , i} is position information of x axis of terminal i, and y _{M , i} is position information of y axis of terminal i.

2, the distances and angles between the base station j and the mobile terminal i are defined by [Equation 3] and [Equation 4].

In Equation (3), d _ji is the distance between the base station j and the terminal i, and? _Ji is the angle between the base station j and the terminal i.

The base stations 210 to 240 can perform communication using a time division multiple access (TDMA) scheme or a frequency division multiple access (FDMA) scheme. The communication channel between the base station 210 and the terminal 252 may be a non-selective frequency channel. The communication channel may be constant during the data transmission interval.

Meanwhile, the terminal is in asynchronous with the base stations 210 to 240, and the terminal is in asynchronous with the base stations 210 to 240, so that the position of the terminal can be estimated by the arrival time difference (TDOA) method.

Hereinafter, the asynchronous error between the base station and the terminal _i is defined as bi.

The base station 210 may have channel information through uplink training based on a time division duplex (TDD) system. The channel information of the base station 210 may be transmitted to the central unit 205, which may adjust or generate the beamforming vector of the base station 210.

Hereinafter, the following assumptions are made for the present invention. Each base station communicates through orthogonal frequency resources through a time division multiple access (TDMA) scheme or a frequency division multiple access (FDMA) scheme.

At this time, it is assumed that the communication channel between the base station and the mobile station is a non-selective frequency channel, and is constant during each information transmission period.

Further, it is assumed that each mobile station is asynchronized with all the base stations, and the asynchronous error between the base station and the mobile station i is defined as bi. The asynchronous error bi is generally unknown to the transceiver.

In the present invention, a TDOA-based positioning system is considered by considering the asynchronous error and the amount of priori information. It is assumed that the base station owns channel information through uplink training based on a time division duplex (TDD) system. It is assumed that the channel information of the base station is transmitted to a central unit 205 that is responsible for generating beamforming of the base station optimized for the system purpose.

A method for adjusting the beamforming vector will be described in detail with reference to Figs. 3 to 9 below.

3 shows a flow chart of a beamforming vector adjustment method according to an embodiment.

First, the base station j may transmit a signal to the terminal i based on the beamforming vector (S310).

The transmission information transmitted from the base station j to the terminal i is divided into a pilot interval for position estimation and channel information estimation and a section for transmitting data information. The total interval of each signal frame is defined as T, the pilot interval is allocated as Tp, and the data transmission interval is allocated as the remainder. That is, the period T in which the base station j transmits information to the terminal i can be divided into a pilot period Tp and a data transmission period Td. The pilot interval is an interval for estimating the position of the UE and an interval for estimating channel information, and a data transmission interval is a interval for transmitting data. Assuming that a total interval of each signal profile is defined as T, the total interval T includes a pilot interval Tp and a data transmission interval Td corresponding to the remaining interval.

At this time, the signal transmitted by the base station j during the pilot interval Tp is defined by Equation (5).

In Equation (5), x _j ^(p) (t) is the signal transmitted by the base station j at the time t within the pilot interval (or the transmission signal of the base station j). w _ji is the beamforming vector of the base station j for the terminal i, and s _ji ^(p) (t) is the pilot information at time t in the pilot section.

The pilot information is defined by Equation (6) below.

In Equation (6), m _ji ^(p) (1) is the pilot code shared by the base station j and the terminal i. g (t-1T _s ) denotes a pulse signal of a single energy, T _s denotes a symbol interval, and n _p denotes a number of bits transmitted in a pilot interval.

The single energy pulse signal may be a pulse having a symbol interval satisfying Nyquist theorem so that aliasing does not occur. The pilot information is used for channel estimation and position estimation of terminal i.

The signal transmitted by the base station j means a signal generated by at least one of pilot information and a beamforming vector including a pilot code shared by the base station j and the terminal i.

The signal received by the terminal i from the base station j is defined by Equation (7) below.

In Equation (7), y _ji ^(p) (t) denotes a signal received by the terminal i from the base station j at time t within the pilot period. ξ _ji denotes a path loss, and the path loss is a parameter that models a large-scale fading of a channel. For example, PASSROS may consider a shadowing effect that affects communication environments such as high-rise buildings or obstacles. The pass loss can be defined by the following equation (8).

In Equation (8), DELTA is a reference distance by which a path loss can be adjusted according to a distance between a base station j and a terminal i according to a channel environment. eta is the pass-through exponent, and the pass-through exponent is determined experimentally.

In Equation (7), h _ji denotes a complex channel vector between the base station j and the terminal i. h _ji is a channel modeling small-scale fading, and h _ji ^* is an adjoint matrix of h _ji .

In Equation (7),? _Ji denotes a signal transmission delay time, and the transmission delay time is defined by Equation (9).

In Equation (9), c denotes a signal speed and bi denotes an asynchronous error between the transceivers.

In Equation 7, z _ji ^(p) (t) may be a complex white Gaussian noise with an average of zero and a two-aided power spectral density N ₀ .

According to one embodiment, the first terminal 252 may receive a signal transmitted by the base station 210 for the second terminal 253. The effective channel gain of the signal for the terminal k transmitted by the base station j received at the terminal i is defined by Equation (10) below. The terminal k may be any terminal within the system 200 other than the terminal i.

Next, the position of the terminal is estimated (S320). The base station 210 or the central unit 205 may estimate the position of the terminal 252 based on the transmitted signal.

The location information of the base stations 210-240 in the system 200 may be known to the terminal 252. [ The terminal 252 may estimate its position based on the signal received during the pilot period in step S310. For example, terminal 252 may estimate the location of terminal 252 based on signals received from a plurality of base stations.

The location of the terminal 252 may be estimated based on the arrival time difference (TDOA) of a plurality of signals.

Next, a step S330 of transmitting data to the UE based on the beamforming vector may be performed.

The base station 210 may transmit data to the terminal 252 based on the beamforming vector (S330) during the data transmission period.

Terminal 252 may receive data transmitted by base station 210. Terminal 252 may calculate the data rate at which terminal 252 received the data.

For example, the data rate for data received by the terminal i from the base station j may be defined by the following equation (19). It is possible to numerically express the amount of information that the terminal can acquire and the accuracy of the position estimation based on the received signal of the data transmission period.

First, the amount of information that terminal i can obtain from base station j is defined by Equation (11) below.

In Equation (11), W _j may be a beamforming vector of base station j for all terminals.

In Equation (11), r _ji (W _j ) may be the data rate for data received by the terminal i from the base station j. The unit of r _ji (W _j ) may be bits / s / Hz

SINR _ji (W _j ) is the interference signal and noise ratio of the signal between the base station j and the terminal i, and can be defined by Equation (12).

As shown in Equation (12), the signal-to-interference-noise ratio and the noise ratio are defined as the effective channel defined above. It is assumed that all the signals transmitted by the base station j for the terminals other than the terminal i are regarded as interference signals do. That is, the data rate may be computed based on the effective channel gain of terminal i and the signal transmitted by base station j for another terminal.

Next, a step S340 of receiving information on the data rate at which the terminal receives data from the terminal is performed. That is, in step S340, the base station 210 may receive information on the data rate at which the terminal 252 received the data from the terminal 252. [

Next, the central unit 205 may determine whether the position accuracy between the estimated position of the terminal 252 and the actual position of the terminal 252 is within a predetermined position accuracy range (S350).

For example, with respect to the terminal i, when the following expression (13) is satisfied, the central unit 205 can determine that the position accuracy is within the predetermined position accuracy range. The positional accuracy can be calculated based on the Fisher information matrix associated with the beamforming vector.

In Equation (13), Qi may be a predetermined positional accuracy.

Next, the central unit 205 may determine whether the data rate at which the terminal 252 received the data is greater than a predetermined data rate (S360).

For example, when the following Equation 13 is satisfied for the terminal i, the central unit 205 can determine that the data rate at which the terminal i received the data is larger than the predetermined data rate .

In Equation (14), Ri may be a predetermined data rate for terminal i.

According to one embodiment, terminal i may receive data from one or more base stations, respectively. When terminal i receives data from one or more base stations, the total sum of the data rates at which terminal station i receives data from each of the one or more base stations is the data rate at which terminal i received data from system 200 have.

Next, the central unit 205 determines whether the positional accuracy between the estimated position of the terminal 252 and the actual position of the terminal 252 is not within a predetermined range of positional accuracy, or if the received data rate is at a predetermined data rate The beamforming vector may be adjusted to minimize the power consumption for the transmission of the data (S380).

For example, for terminal i, if at least one of [Equation 13] and [Equation 14] in step 350 are not satisfied, the central unit 205 may adjust the beamforming vector.

The beamforming vector may be adjusted to minimize power consumption for the data via: < EMI ID = 15.0 >

Meanwhile, the criterion of the position accuracy in the present invention starts from SPE (Squared position error). The position accuracy of the terminal 252 may be calculated using a Squared Position Error (SPE). SPE is defined by the following equation (16).

는 추정된 단말 i의 위치일 수 있다. ρi(W)는 SPE일 수 있다.In Equation (16), p _{M , i} may be the position of the actual terminal i,

May be the estimated position of the terminal i. pi (W) can be SPE.

The present invention uses the CRB as a criterion of position accuracy based on the fact that the SPE presented in Equation (16) is bound to a Cramer-Rao bound (CRB) boundary. The relationship between the SPE and the CRB may have a relationship as shown in the following Equation (17).

The right side of Equation (17) is defined as the trace value of the inverse matrix of the Fischer information matrix as a CRB, and the definition of the Fisher information matrix is defined by Equation (15) below.

In Equation (18), K _bi is defined by Equation (18).

In Equation (18), W _j is a beamforming vector of the base station j for all terminals. The beamforming vector of the base station j for all terminals is defined by the following equation (20).

In Equation (16) and (17), W may mean a beamforming vector of all base stations. The beamforming vector of all the base stations can be defined by the following equation (21).

In Equation (18), SNRji (Wj) may be a signal-to-noise ratio between the base station j and the terminal i. The signal-to-noise ratio between the base station j and the terminal i is defined by the following equation (22).

In Equation (18),? May be an effective bandwidth. The effective bandwidth can be defined by the following equation (23).

In Equation (23), g (f) may be a signal obtained by Fourier transforming the pulse signal of the single energy of Equation (6).

In Equation (18), J _bi means the amount of priori information for the asynchronous error, and is defined by the following Equation (24).

는 두 기지국과 단말기의 방향 행렬을 의미하며, 하기의 [수학식 25]로 정의된다.In Equation 18,

Denotes a direction matrix of two base stations and a terminal, and is defined by the following equation (25).

It should be noted that all of the signals for terminals other than the terminal i are regarded as interference signals when data is transmitted to the terminal i, but are not regarded as interference signals when the position is estimated. Therefore, for data communication, it is necessary to reduce the interference signal, but it is necessary to increase the strength of all the signals of the base station j in order to obtain high positional accuracy. (18) is a relational expression of the Fisher information matrix of the TOA-based positioning system, which is a positioning technique when bi = 0, and can be expressed as follows.

로 정의되고, Here, the direction vector is

Lt; / RTI >

 The Fisher information matrix of the TOA based positioning system is

Lt; / RTI >

The direction matrix of the base station and the terminal is

와 같이 나타난다.

.

A method of adjusting the beamforming vector will be described in detail below with reference to FIG.

According to one embodiment, the method of adjusting the beamforming vector may be based on the performance of the terminal 252 and the estimated location of the terminal 252. [ That is, if the performance evaluation criterion is not satisfied, the beamforming vector can be adjusted.

The adjusted beamforming vector may be adjusted to minimize power consumption for data transmission. Therefore, the beamforming vector may have to satisfy all of the above-mentioned conditions (13), (14) and (15).

That is, in order to meet the required service condition and minimize the power consumption of the base station by using the data transmission amount and the CRB as the criterion for the level of the data communication and the position estimation service, the following equations (13), (14) All should be satisfied.

In the following, two beamforming design techniques are proposed.

First, we explain how to use bi when the amount of priori information is large. 4 shows a flow diagram of a method of adjusting a beamforming vector based on a beamforming Covariance matrix according to an example.

The above-described step S370 may include the following steps S410 to S430.

In step S410, the central unit 205 may generate a beamforming covariance matrix of beamforming vectors using a beamforming vector. The beamforming Covariance matrix can be defined by Equation (26) below.

The relationship between the TOA-based Fischer information matrix and the TDOA-based Fischer information matrix is used to calculate the lower limit of the TOA-based Fischer information matrix using Equation (28).

(13) is transformed into the following expression (29) using the expression (27).

 In this case, the effective channel gain of the signal for the terminal k of the base station j received in the terminal i defined above is again defined as a beamforming Covariance matrix as follows.

If the Schur complement condition is applied using [30] and any positive semidefinite matrix, Equation (13) can be replaced by Equation (31) below.

Next, in step S420, the central unit 205 can generate a local beamforming Coberian matrix by linearizing a function on the received data rate using the generated beamforming Covariance matrix. have.

We relax the rank = 1 property of the beamforming Covariance matrix. The MM (Majorization minimization) algorithm is applied to linearize the non-convex part of the function in Equation (14) to create the convex programming. The final beamforming vector is designed by eigenvector approximation and scaling from the local beamforming Covariance matrix values obtained through this process.

In step S430, the central unit 205 may adjust the beamforming vector based on the local beamforming Covariance matrix. The central unit 205 may generate a beamforming vector using an eigenvalue approximation. The beamforming vector can be generated by the following equation (32).

는 빔포밍 코베리언스 행렬의 가장 큰 고유 값(eigen value)이고,

는 가장 큰 고유 값에 상응하는 고유 벡터(eigenvector)를 의미한다.In Equation 32,

Is the largest eigenvalue of the beamforming Covariance matrix,

Means an eigenvector corresponding to the largest eigenvalue.

The central unit 205 may determine the generated beamforming vector as a final beamforming vector in the case where the beamforming vector generated through Equation (32) is executable.

The central unit 205 may scale the beamforming vector if the generated beamforming vector is a non-executable vector. The method of scaling the beamforming vector can be defined as < EMI ID = 33.0 >

The left beamforming vector of Equation (35) may be a scaled beamforming vector. lt; / RTI > may be a positive scaling factor. The central unit 205 may adjust the beamforming vector by replacing the generated beamforming vector with an existing beamforming vector.

According to one embodiment, the beamforming adjustment method can always ensure feasibility for the conditions described above. Therefore, in the distributed antenna system, the beamforming adjustment method can simultaneously enable a service for providing data communication and a service for estimating the position of a terminal. In addition, the beamforming adjustment method can minimize the power consumption of the base station transmitting data.

On the other hand, the second beamforming design technique is a method in which a block coordinate iterative method is applied based on [Equation 17].

Although the first beamforming design scheme has a limitation in that the amount of priori information on the asynchronous error is large, the second method has the advantage of being free to use because there is no such limitation. In short, it optimizes the covariance matrix of one base station j for each iteration and fixes the covariance matrix of the remaining base stations. Then, the final beamforming vector is determined by the MM algorithm, rank relaxation, eigen approximation, and scaling as in the first method.

First, the central unit 205 generates a beamforming covariance matrix of beamforming vectors using a beamforming vector. The beamforming Covariance matrix can be generated by the above-described equation (26).

Next, Equation (13) is replaced by Equation (34) below.

이고,

로 정의한다. 또한, n번째 iteration에서의 단말기 i를 위한 기지국 j에서의 convariance matrix는

로 정의한다.here,

ego,

. Also, the convariance matrix at the base station j for terminal i in the n th iteration is

.

Next, in the first method, steps 4), 5) and 6) described above are performed.

As a result, the beamforming vector is adjusted.

According to the present invention, an apparatus and method are provided for adjusting a beamforming vector such that power consumption for transmission of data is minimized.

There is provided a beamforming vector adjusting apparatus and method for simultaneously providing a service for providing data communication and a service for estimating a position of a terminal on the premise of the asynchronization of a transceiver.

FIG. 5 illustrates a beamforming vector adjustment system according to a distance difference between two terminals according to an example.

According to one embodiment, as shown in FIG. 5, the base stations 210 to 240 and the terminals 252 and 253 may be disposed. The base stations 210-240 may be located at each vertex of a square cell. The terminal 252 may be located at the center of the cell, and the terminal 253 may move parallel to the x axis. For example, the base station may include five antennas.

Changes in the average power consumed by the base station as the terminal 253 moves will be described below with reference to Fig.

6 shows an average power consumption of BSs according to a distance difference between two terminals according to an example.

Referring to FIG. 6, it can be seen that when only data communication is supported, the average power consumption decreases as the distance between the two terminals increases. This is explained by the effect of the interference signal on each other as the distance difference increases. On the other hand, when only the location estimation service is supported, the average power consumption increases. As described above, since the position estimation service uses not only the signal for itself but also signals for other terminals, it is explained that the signal-to-noise ratio decreases as the distance difference increases. In addition, when supporting both data communication and location estimation services simultaneously, it can be seen that always greater power is required than the maximum power consumed in supporting each service alone. Also, when compared with the TOA-based positioning, it can be confirmed that more power is consumed as a whole. This is explained as more power is needed to support the same location service quality due to the asynchronization between the transceivers. In addition, when supporting the data communication and the position estimation at the same time, it can be seen that when the distance between the mobile terminals becomes long, convergence does not converge when only the position estimation service is supported. It is explained that the influence of interference on data communication is increased due to the intensity of the signal required due to the TDOA based positioning.

FIG. 7 is a diagram illustrating results of selectively using the two different beamforming design techniques described above with reference to FIG.

It can be seen that the amount of power consumption decreases as the amount of priori information for the asynchronous error becomes larger. Also, it can be seen that the first method is more suitable when possessing a low priori information amount, and the second method requires less power in terms of power use amount.

8 shows deployed base stations and terminals according to an example.

According to one embodiment, the base stations 210 to 240 and the terminals 252 to 256 may be arranged as shown in FIG. The base stations 210-240 may be located at each vertex of a square cell. The terminals 252 through 256 may be arbitrarily located within the cell.

9 illustrates an electronic device according to one embodiment.

The system 200 described above may be implemented in one electronic device 900.

The electronic device 900 may include a communication unit 910, a processing unit 920, and a storage unit 930.

The electronic device 100 may correspond to the beamforming adjustment system 200 described above. The communication unit 910 may correspond to the base station 210 described above. The processing unit 920 may correspond to the central unit 205 described above. A plurality of base stations of the system 200 may correspond to a plurality of antennas of the electronic device 900.

The storage unit 930 may store the information received by the communication unit 910 and the information generated by the processing unit 920.

Thus, in the embodiments described above, the system 200 may be replaced by an electronic device 900. In addition, the base station 210 may be replaced by a communication unit 910, and the central unit 205 may be replaced by a processing unit 920. [ Communication between the base station 210 and the central unit 205 may be replaced by communication between the communication unit 910 and the processing unit 920. The functions, operations, and configurations described with respect to the system 200, the base station 210, and the central unit 205 can be applied to the electronic device 900, the communication unit 910, and the processing unit 920, respectively.

For example, the communication unit 910 of the electronic device 900 may send a signal to the terminal 252 based on the beamforming vector and may transmit data to the terminal 252 based on the beamforming vector. The processing unit 920 can estimate the position of the terminal 252 based on the transmitted signal and estimate the positional accuracy between the estimated position of the terminal 252 and the actual position of the terminal 252 at a predetermined position The beamforming vector may be adjusted such that the power consumption for transmission of data is minimized when it is not within the accuracy range or when the received data rate is smaller than the predetermined data rate.

10 illustrates an electronic device according to one embodiment.

According to one embodiment, the electronic device 1000 may include a beamforming covariance generator 1010, a position accuracy generator 1020, a linearizer 1030, and a controller 1040. For example, the beamforming covariance generator 1010, the position accuracy generator 1020, the linearizer 1030, and the controller 1040 may be implemented by a processor included in the electronic device 1000, Lt; / RTI >

According to another embodiment, the electronic device 1000 may correspond to the processing unit 920 of the central unit 205 or the electronic device 900 described above. That is, each function performed by the beamforming cervixer generation unit 1010, the position accuracy generation unit 1020, the linearization unit 1030, and the control unit 1040 of the electronic device 1000 is performed by the central unit 205 or the electronic unit Can be understood as a function performed by the processing unit 920 of the apparatus 900. [

The electronic device 1000 may generate a second beamforming vector using the first beamforming vector. The second beamforming vector may be a beamforming vector satisfying the above-mentioned conditions (12) to (14).

The present invention is similar to the prior art (Korean Patent Laid-Open No. 10-2014-0014355) and the system objective to be achieved (beamforming design using minimum power considering both data service and location estimation service) The solution to design beamforming differs.

Considering the TDOA-based position estimation, it is necessary to consider an asynchronous state in which a clock offset between the base station and the terminal exists. Therefore, the beamforming covariance matrix generator and the position accuracy generator for designing the beamforming vector have differentiation . Since the CRB equation representing the positional accuracy in the asynchronous situation is different from the TOA-based positional estimation, the beamforming design technique is different for the beamforming design since it is changed as [Equation 16] and [Equation 17] .

If the proposed beamforming method in the TOA based position estimation is applied in the asynchronous situation, the beamforming vector satisfying the required position accuracy and data service condition will not be generated.

In the position accuracy generation part, the present invention proposes two methods according to the degree of information on the clock offset.

First, a method for designing a position accuracy generator using Equation (27) using Equation (27), using the algorithm proposed in TOA-based position estimation, i.e., the MM method, rank relaxation, eigen approximation and scaling Method.

However, since the first method is effective only when the amount of information on the clock offset is sufficient, a second method is proposed by a universal beamforming design method which is not limited in use.

The second method is a block coordinate iterative method, which optimizes the Covariance matrix of one base station for each iteration and fixes the Covariance matrix of the remaining base stations. Then, the final beamforming vector is obtained by using the MM method, rank relaxation, eigen approximation, and scaling proposed in the first method.

Claims (7)

The present invention relates to a beamforming vector adjustment method performed by an electronic device including a first communication unit and a second communication unit,
Transmitting a first signal to the terminal using the first communication unit and transmitting the first signal to the terminal using the second communication unit;
Estimating a position of the UE based on a Time Difference Of Arrival (TDOA) of the plurality of signals;
Transmitting data to the terminal based on the beamforming vector;
Receiving information on a data rate at which the terminal received data from the terminal; And
When the position accuracy between the estimated position of the terminal and the actual position of the terminal is not within a predetermined range of the position accuracy or when the received data rate is smaller than a predetermined data rate, And adjusting the beamforming vector such that consumption is minimized. The method according to claim 1,
Wherein adjusting the beamforming vector comprises:
Generating a beamforming Covariance matrix of the beamforming vector;
Generating a local beamforming Covariance matrix by linearizing a function on the received data rate using the generated beamforming Covariance matrix; And
And adjusting the beamforming vector based on the local beamforming Covariance matrix. 3. The method of claim 2,
Wherein generating the local beamforming coercivity matrix comprises:
Wherein a beamforming Covariance matrix is generated in a different manner according to the degree of ownership information on the asynchronization error generated by the first and second communication units. 3. The method of claim 2,
Wherein generating the local beamforming coercivity matrix comprises:
Further comprising changing the positioning requirement to a semi-definite programming (SDP) form according to a Schur complement condition. 3. The method of claim 2,
Wherein generating the local beamforming coercivity matrix comprises:
Wherein generating the local beamforming Covariance matrix further comprises generating a lower limit of a Fischer information matrix associated with the beamforming Covariance matrix. 3. The method of claim 2,
Wherein generating the local beamforming coercivity matrix comprises:
The method of claim 1, wherein the beamforming is performed using a block coordinate iterative method so that the non-convex property of the Fourier information matrix associated with the beam-forming Covariance matrix is convex, Wherein only the Covariance matrix is considered, and the remaining beam-forming Covariance matrix is fixed. 3. The method of claim 2,
Wherein generating the local beamforming coercivity matrix comprises:
Characterized in that the local beamforming coercivity matrix is generated by linearizing a non-convex portion of a function related to the received data rate using a majorizationminimization algorithm, Vector adjustment method.

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