KR101977623B1 - Interpolation and prediction method for fast link adaptation, and apparatus thereof - Google Patents

Abstract

The present invention relates to a channel interpolation and prediction method, and more particularly, to a channel interpolation and prediction method in which a normal orthogonal basis is calculated using a channel estimated at a pilot symbol position, a correlation matrix is constructed using the calculated normal orthogonal basis, A channel interpolation and prediction method for fast link adaptation capable of performing channel interpolation and prediction using the same, and an apparatus therefor.
The channel interpolation and prediction method for high speed link adaptation according to an embodiment of the present invention includes receiving a demodulation reference signal from a user equipment (UE) and estimating a channel vector estimated at a pilot symbol position of the received demodulation reference signal And performing channel interpolation and prediction using the received signal.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a channel interpolation and prediction method for fast link adaptation,

The present invention relates to a channel interpolation and prediction method, and more particularly, to a channel interpolation and prediction method in which a normal orthogonal basis is calculated using a channel estimated at a pilot symbol position, a correlation matrix is constructed using the calculated normal orthogonal basis, A channel interpolation and prediction method for fast link adaptation capable of performing channel interpolation and prediction using the same, and an apparatus therefor.

Communication between people vs. objects and objects vs. objects, rather than communication between humans, has been presented as a variety of applications and scenarios for several years, some of which are being promoted by commercialization and standardization to some extent. Particularly, attention has recently been focused on V2X (Vehicle-to-Everything). V2X is a communication technology that provides information through wired and wireless networks around a vehicle, and can support various services related to vehicle communication such as traffic efficiency and autonomous driving. For example, if inter-vehicle communication is possible, information on dangerous road conditions, bad weather, and traffic congestion can be transmitted from one vehicle to another.

In such V2X communication, Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) are important communication technologies. MIMO can increase the channel capacity by providing spatial degrees of freedom without adding bandwidth. In the case of OFDM, CP (Cyclic Prefix) is used to eliminate interference between neighboring symbols and reduce the effect of delay spread by multipath And can be robust against a frequency selective fading channel. Most OFDM systems use a synchronous detection method and estimate CSI (Channel State Information) at the receiving end. CSI is needed for link adaptation such as space-time decoding, adaptive modulation and coding, power control, and transmit antenna diversity techniques.

On the other hand, V2X communication can be divided into Vehicle-to-Vehicle (V2V), Vehicle-to-Pedestrian (V2P), and Vehicle-to-Infrastructure (V2I) communication . Among them, V2I communication means performing communication between a vehicle and an infrastructure installed near a road, for example, a roadside base station, in order to provide ITS (Intelligent Transportation Systems) and telematics services. The vehicle receives data through the base station, collects road conditions and traffic information, and transmits the collected information to the base station. In order to provide such V2I communication service, a link adaptation technique capable of achieving high transmission rate is required. To this end, the receiving terminal estimates channel state information (CSI), transmits the estimated channel state information to the base station, which is the transmitting terminal, and performs baseband adaptation using the channel state information of the vehicle. However, in the case of a vehicle, even if the state information is estimated, it is difficult to adapt the high-speed link considering the fast change of the channel and the processing delay time between layers because it moves at a high speed.

Therefore, channel interpolation and prediction techniques are needed to perform link adaptation at high speed in V2I communication system.

Korean Registered Patent No. 10-1143242 Registered April 27, 2012 (Name: Channel Estimation for Wireless Communication)

SUMMARY OF THE INVENTION The present invention has been proposed in order to solve the above-described problems, and it is an object of the present invention to provide a high-speed link adaptation Channel interpolation and prediction method for the same, and a device for the same.

To this end, the present invention forms a normal orthogonal basis using a channel estimated at a pilot symbol position with respect to a channel that changes very rapidly over time, constructs a correlation matrix using the base, and then performs channel interpolation and prediction Channel adaptation and prediction method for high-speed link adaptation, and an apparatus therefor.

It is another object of the present invention to provide a channel interpolation and prediction method for fast link adaptation which can more accurately perform channel interpolation and prediction by performing smoothing for noise cancellation in the frequency domain, and an apparatus therefor have.

According to an aspect of the present invention, there is provided a channel interpolation and prediction method for fast link adaptation, comprising: receiving a demodulation reference signal from a user equipment; And performing channel interpolation and prediction using the estimated channel vector at the pilot symbol position of the received demodulation reference signal.

The performing the channel interpolation and the prediction may include calculating a correlation matrix using a basis function value of the channel vector estimated at the pilot symbol position, Constructing a parameter for performing channel interpolation and prediction using the calculated correlation matrix; And performing channel interpolation and prediction according to the configured parameters to calculate a channel estimation response.

At this time, the step of constructing the parameter may constitute a parameter using the calculated correlation matrix, the channel vector estimated from the received demodulation reference signal and the pilot symbol position.

In addition, the step of calculating the channel estimation response may calculate a channel estimation response according to channel interpolation and prediction using the parameter to the normal orthogonal basis.

In this case, the normal orthogonal basis may mean an eigenvector of the base matrix, which is constructed by applying a base matrix predefined to the estimated channel vector.

At this time, the base matrix can be calculated using the normalized Doppler frequency.

In addition, the step of performing channel interpolation and prediction may further include removing noise by applying smoothing in the frequency domain in the calculated channel estimation response.

In addition, performing the channel interpolation and prediction may perform channel estimation at a pilot symbol position of the received demodulation reference signal, and may perform channel estimation after interpolation at a position where there is no pilot symbol to calculate a channel estimation response .

According to an aspect of the present invention, there is provided a base station including a receiver for receiving a demodulation reference signal from a user equipment; And calculating a correlation matrix using a basis function value of a channel vector estimated at a pilot symbol position of the received demodulation reference signal and constructing a parameter for performing channel interpolation and prediction using the calculated correlation matrix, And a signal processing unit for performing channel interpolation and prediction according to the configured parameters to calculate a channel estimation response.

At this time, the signal processor may perform smoothing in the frequency domain in the calculated channel estimation response to remove noise, and then transmit the channel estimation response with noise removed to the user equipment.

 5G and B5G systems, and vehicle communications, the proposed channel interpolation and prediction scheme can provide higher performance gain compared to channel interpolation and prediction techniques used in existing mobile communication systems .

This improves the performance of Signal-to-Noise Ratio (SNR), which shows improvement of QoS of users. Finally, it can improve the performance of Prediction Mean Square Error, BER (Bit Error Rate), BLER (BLock Error Rate) have.

Also, if the present invention is successfully applied to 5G and B5G systems, it can be a preemptive technology in a vehicle environment, reliable data detection can be performed through accurate channel interpolation and prediction, and a safety effect can be obtained in vehicle communication.

As described above, the main core technologies of the present invention can bring about academic ripple effects and securing prior arts for national research and development.

1 is an exemplary diagram illustrating a link adaptation process in a V2I communication system according to an embodiment of the present invention.
2 is an exemplary diagram for explaining the position of a DMRS in a subframe.
3 is an exemplary diagram illustrating channel interpolation and prediction.
4 is an exemplary diagram illustrating throughput results for downlink delay times.
FIG. 5 shows a prediction error for a prediction horizon p.
6 is a block diagram illustrating a main configuration of a base station according to an embodiment of the present invention.
7 is an exemplary diagram for explaining a channel interpolation and prediction method for fast link adaptation in a base station according to an embodiment of the present invention.
8 is a diagram showing a performance evaluation index applied to the embodiment of the present invention.
9 through 12 are diagrams illustrating throughputs according to downlink delay in a highway environment.
13 to 16 are diagrams showing throughputs according to downlink delay in an urban environment.

BRIEF DESCRIPTION OF THE DRAWINGS For a more complete understanding of the nature and advantages of the present invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings, in which:

In the following description and the accompanying drawings, detailed description of well-known functions or constructions that may obscure the subject matter of the present invention will be omitted. It should be noted that the same constituent elements are denoted by the same reference numerals as possible throughout the drawings.

The terms and words used in the following description and drawings are not to be construed in an ordinary sense or a dictionary, and the inventor can properly define his or her invention as a concept of a term to be described in the best way It should be construed as meaning and concept consistent with the technical idea of the present invention. Therefore, the embodiments described in the present specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention, and not all of the technical ideas of the present invention are described. Therefore, It is to be understood that equivalents and modifications are possible.

Also, terms including ordinal numbers such as first, second, etc. are used to describe various elements, and are used only for the purpose of distinguishing one element from another, Not used. For example, without departing from the scope of the present invention, the second component may be referred to as a first component, and similarly, the first component may also be referred to as a second component.

In addition, when referring to an element as being "connected" or "connected" to another element, it means that it can be connected or connected logically or physically. In other words, it is to be understood that although an element may be directly connected or connected to another element, there may be other elements in between, or indirectly connected or connected.

Also, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. It is also to be understood that the terms such as " comprising " or " having ", as used herein, are intended to specify the presence of stated features, integers, It should be understood that the foregoing does not preclude the presence or addition of other features, numbers, steps, operations, elements, parts, or combinations thereof.

In addition, embodiments within the scope of the present invention include computer-readable media having computer-executable instructions or data structures stored on computer-readable media. Such computer-readable media can be any available media that is accessible by a general purpose or special purpose computer system. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or in the form of computer- But is not limited to, a physical storage medium such as any other medium that can be used to store or communicate certain program code means of the general purpose or special purpose computer system, .

In the following description and claims, the term " network " is defined as one or more data links that enable electronic data to be transmitted between computer systems and / or modules. When the information is transmitted or provided to a computer system via a network or other (wired, wireless, or a combination of wired or wireless) communication connection, the connection may be understood as a computer-readable medium. Computer readable instructions include, for example, instructions and data that cause a general purpose computer system or special purpose computer system to perform a particular function or group of functions. The computer executable instructions may be binary, intermediate format instructions, such as, for example, assembly language, or even source code.

In addition, the invention may be practiced with other computer systems, including personal computers, laptop computers, handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, a pager, and the like. < RTI ID = 0.0 > [0040] < / RTI > The invention may also be practiced in distributed systems environments where both local and remote computer systems linked by a combination of wired data links, wireless data links, or wired and wireless data links over a network perform tasks. In a distributed system environment, program modules may be located in local and remote memory storage devices.

Now, a channel interpolation and prediction method for fast link adaptation according to an embodiment of the present invention and an apparatus therefor will be described in detail with reference to the drawings. Here, the same reference numerals are used for similar functions and functions throughout the drawings, and a duplicate description thereof will be omitted.

Hereinafter, a V2I communication system model according to an embodiment of the present invention will be described.

First, the link adaptation process in the V2I communication system will be described.

1 is an exemplary diagram illustrating a link adaptation process in a V2I communication system according to an embodiment of the present invention.

Referring to FIG. 1, the user device 100 of the present invention may include a navigation system installed in a vehicle or a device such as a terminal of a user boarding a vehicle. The user equipment 100 transmits a demodulation reference signal (DMRS) and a sounding reference signal (SRS) generated as indicated by (1) in the uplink transmission step to the base station 200 . At this time, the parameters required for transmitting the demodulation reference signal and the sounding reference signal are the same as the upper layer signaling such as RRC (Radio Resource Control) signaling transmitted semi-static or the DCI transmitted dynamically And may be received from the base station 200 via control information.

The base station 200 can perform channel estimation, prediction, data detection, and the like using the demodulation reference signal and the sounding reference signal received from the user equipment 100.

The base station 200 may transmit a new Precision Matrix Indicator (PMI) and a Modulation and Coding Scheme (MCS) level for the predicted channel to the UE 100 as instructed by the UE # 2, ) Performs performance enhancement through Adaptive Modulation Coding (AMC), which is one of the link adaptation schemes, using the received information as indicated by (3), and transmits it to the base station 200.

At this time, the 3rd Generation Partnership Project (3GPP) discloses a physical layer processing delay time of at least 5 ms. In order to reduce the influence on the delay time, more efficient channel interpolation and prediction techniques than the base station 200 are required.

In addition, in an environment in which the user equipment 100 moves at high speed, the base station 200 performs channel estimation and the like using the demodulation reference signal and the sounding reference signal received in the direction (1) To the user equipment 100. However, if the user equipment 100 moves to another location at a high speed, unnecessary information is transmitted, so that channel estimation must be performed more quickly.

In order to solve this problem, the present invention has been studied in an LTE based uplink system based on 3GPP standardization. The LTE uplink system is based on SC-FDMA (Single-Carrier Frequency Division Multiple Access), and this modulation scheme uses OFDM's DFT-spreading. In this system, channel estimation is performed based on pilot symbols, and DMRS (Demodulation Reference Signal) is used. God

Hereinafter, the demodulation reference signal DMRS in the V2I communication system model of the present invention will be described.

2 is an exemplary diagram for explaining the position of a DMRS in a subframe.

In general, the basic unit of data transmission is a subframe unit of a radio frame. A radio frame is composed of 10 subframes, and one subframe is composed of two slots (solots). At this time, the number of OFDM symbols included in one slot may vary according to a cyclic prefix (CP). Here, CP is a signal inserted in a guard interval in order to remove inter-symbol interference due to multipath in an OFDM transmission scheme. The CP is an extended CP and a normal CP, . ≪ / RTI > For example, when an OFDM symbol is configured by a general CP, the number of OFDM symbols included in one slot is 7, and one subframe is composed of 2 symbols. Therefore, a total of 14 OFDM symbols ≪ / RTI >

The demodulation reference signal DMRS may be multiplexed at the fourth and eleventh positions of the OFDM symbols of the time-frequency resource grid.

At this time, the signal received from the symbol time n and the subcarrier k is expressed by Equation (1) below.

는 전송된 심볼,

는 채널 계수,

는 가우시안 잡음을 나타낸다. 파일럿 심볼 위치에서 채널 추정은 LS(Least Square) 또는 MMSE(Minimum Mean Square Error) 방식을 이용하여 할 수 있다. 파일럿 심볼이 없는 위치의 채널 추정을 위해 보간 기법이 사용되며, 본 발명은 시간 영역 1차원 보간 기법을 적용하게 된다. 그리고 기지국(200)에서 링크 적응 파라미터 계산을 위한 처리 지연 시간의 보상을 위해 예측 기법이 사용된다. In Equation (1)

Lt; RTI ID = 0.0 > symbol,

Is the channel coefficient,

Represents a Gaussian noise. The channel estimation at the pilot symbol position can be performed using LS (Least Square) or MMSE (Minimum Mean Square Error) method. An interpolation scheme is used for channel estimation at locations without pilot symbols, and the present invention applies a time domain one-dimensional interpolation scheme. A prediction scheme is used to compensate the processing delay time for link adaptation parameter calculation in the base station 200.

See FIG. 3 for this.

는 최대 도플러 천이를 나타내며 v는 차량의 속도, c는 빛의 속도

, 그리고

는 캐리어 주파수를 나타낸다. 자기 상관 함수가 0.5 미만으로 떨어질 때 코히런스 시간은 하기의 <수학식 2>와 같이 나타낼 수 있다. FIG. 3 is an exemplary diagram for explaining channel interpolation and prediction. Referring to FIG. 3, interpolation is performed at an nth time, and a channel of an arbitrary n + p time is predicted from time n + ). Here, p is a prediction horizon, and it is a parameter to predict p time in advance. In the present invention, the channel model uses an Extended Rosa Zheng model. In the Jakes Doppler spectrum, the autocorrelation function is given as a zero - order one kind of Bessel function.

Represents the maximum Doppler shift, v is the speed of the vehicle, c is the speed of light

, And

Represents the carrier frequency. When the autocorrelation function falls below 0.5, the coherence time can be expressed as Equation (2) below.

를 5ms라고 가정하며 캐리어 주파수

를 2GHz라고 할 때 최대 견딜 수 있는 속도는 20.2km/h이다. For example, coherence time

Is assumed to be 5 ms, and the carrier frequency

Is 2GHz, the maximum speed that can withstand is 20.2km / h.

4 is an exemplary diagram illustrating throughput results for downlink delay time. As can be seen from FIG. 4, the greatest performance degradation occurs between delay 0 and delay 1. As the downlink delay time approaches the coherence time, the correlation weakens and the link adaptation performance improves.

Hereinafter, channel interpolation and prediction techniques according to an embodiment of the present invention will be described.

Existing channel interpolation and prediction techniques are exemplified by NLMS (Norm Least Mean Square), RLS (Recursive Least Square), and SM-APA (Set Membership Affine Projection Algorithm).

FIG. 5 shows a prediction error for a prediction horizon p. As shown in FIG. 5, the error increases as the p value increases. Where M is the number of samples used for prediction, mu, lambda and gamma are the parameters of each filter. Each filter has a disadvantage in that the convergence speed is determined according to a specific parameter, and there is a dependency depending on the channel environment. There is also a 2D MMSE (Two Dimensional Mimimum Mean Square Error) prediction technique. In this technique, the autocorrelation function of the channel and the signal to noise ratio (SNR) value are required. This assumption can not be applied to real channels.

These existing channel interpolation and prediction techniques can be classified into linear interpolation, prediction method, spline interpolation and prediction method.

First, we explain the linear interpolation and prediction technique. Linear interpolation and prediction techniques are the easiest to implement. The interpolation of the channel frequency response obtained from the channel estimation can be performed as Equation (3).

는 보간된 채널 주파수 응답,

와

는 4번째 그리고 11번째 파일럿 심볼에서의 추정된 채널을 나타낸다. 인접 두 점을 이용해 직선의 방정식으로 extrapolation과 예측을 하여 전체 채널 주파수 응답

를 구할 수 있다. Where m = 0, 1, ..., 6,

Lt; / RTI &gt; is the interpolated channel frequency response,

Wow

Represents the estimated channel in the 4 &lt; th &gt; and 11 &lt; th &gt; pilot symbols. By using extrapolation and prediction using a straight line equation using two adjacent points, the total channel frequency response

Can be obtained.

On the other hand, the spline interpolation and prediction technique refers to a technique of interpolating and predicting the approximation between the two pilot symbols and the edge by a third order polynomial. The third order polynomial can be expressed as Equation (4).

는 스플라인 S(x)의 계수 값이다. 계수 값을 결정하기 위해서는 4개의 조건이 필요하다. 이때, 하기 <수학식 5>와 같이 각 점에서 원래의 데이터 값을 곡선이 지나는 조건과 각 점에서 두 곡선의 함수 값이 같아야 하는 조건이 있다. here,

Is the coefficient value of the spline S (x). Four conditions are required to determine the coefficient value. At this time, there is a condition that the condition that the curve passes through the original data value at each point and the function value of the two curves at each point should be equal to each other as shown in Equation (5) below.

Also, the smoothness of the two curves at each point must be the same, which means that the derivative of the two curves should be the same. In order to smoothly meet each other, the second derivative values of the two curves may be equal to each other as shown in Equation (6) below.

By using such a condition, coefficients of the third order polynomial can be calculated, and interpolation and prediction can be performed.

Hereinafter, a proposal channel estimation technique according to an embodiment of the present invention will be described.

The present invention proposes an ADPSS channel interpolation and prediction technique. The proposed method creates a regular orthogonal basis and performs channel interpolation and prediction using a correlation matrix. It also removes noise through smoothing in the frequency domain.

는 기저 행렬 C의 고유 벡터로, 하기의 <수학식 7>을 만족한다. The following is a detailed process of the ADPSS technique. The normal orthogonal basis DPS sequence

Is an eigenvector of the base matrix C and satisfies the following Equation (7).

는 고유 값이며, 기저 행렬 C는 하기의 <수학식 8>과 같이 정의될 수 있다. here,

Is an eigenvalue, and the base matrix C can be defined as Equation (8) below.

는 정규화된 도플러 주파수 이며,

이다. 그리고 f는 파일럿 위치에서 채널 벡터를 기저 함수 값으로 <수학식 9>와 같이 나타낼 수 있다. here,

Is the normalized Doppler frequency,

to be. And f can represent the channel vector as a basis function value at the pilot position as shown in Equation (9).

The correlation matrix G can be defined as Equation (10).

을 나타낼 수 있다.Then, using the correlation matrix G

Lt; / RTI &gt;

는 수신된 신호,

는 송신한 파일럿 심볼을 나타낸다. 그 다음

를 DPS sequence

로 확장시키며 <수학식 8> - <수학식 11>의 과정의 파라미터를 사용하여 채널 보간과 예측을 할 수 있게 된다. here,

Lt; RTI ID = 0.0 &gt;

Represents the transmitted pilot symbol. next

DPS sequence

And channel interpolation and prediction can be performed using the parameters of Equation (8) - (Equation (11)).

The result is shown in Equation (12).

는 스무딩을 통하여 주파수 도메인에서 잡음을 제거할 수 있다. after,

Can remove noise in the frequency domain through smoothing.

Here, q is a smoothing parameter.

Hereinafter, a base station configuration and an operation method according to an embodiment of the present invention will be described.

FIG. 6 is a block diagram illustrating a main configuration of a base station according to an embodiment of the present invention. FIG. 7 is an exemplary diagram for explaining a channel interpolation and prediction method for fast link adaptation in a base station according to an embodiment of the present invention. to be.

6, a base station 200 according to an exemplary embodiment of the present invention may include a transmitter 210, a receiver 220, and a signal processor 230. Referring to FIG.

The transmitting unit 210 plays a role of transmitting a signal to the user device 100.

The receiving unit 220 may be operable to receive a signal transmitted by the user apparatus 100.

The signal processing unit 230 performs main control in the base station 200 according to an embodiment of the present invention. When the demodulation reference signal transmitted from the user equipment 100 is received through the receiving unit 220, And performs channel interpolation and prediction using the channel vector estimated at the pilot symbol position of the transmission signal transmitted to the user apparatus 100 through the channel estimation unit 210.

Referring to FIG. 7, the signal processing unit 230 transmits a signal to the user device 100 through the transmission unit 210, When the demodulation reference signal generated by the apparatus 100 is received through the receiving unit 220 in step S101, the channel vector is estimated at the pilot symbol position of the demodulation reference signal that is always received (S103) (S105). &Lt; / RTI > In this case, the signal processing unit 230 of the present invention calculates the basis function value of the channel vector at the pilot position according to Equation (9), and calculates the correlation matrix according to Equation (10).

을 의미하며, 신호 처리부(230)는 <수학식 12>와 같이 상기 파라미터를 정규 직교 기저 DPS sequence

에 적용하여 채널 보간 및 예측을 수행할 수 있게 된다(S111). Thereafter, the signal processing unit 230 of the present invention constructs parameters using the calculated correlation matrix (S109). The parameters at this time are calculated according to Equation (11)

, And the signal processing unit 230 outputs the parameter as a normal orthogonal basis DPS sequence

To perform channel interpolation and prediction (S111).

At this time, the definition of the normal orthogonal basis can be defined according to Equation (7) and Equation (8).

Thereafter, the signal processor 230 of the present invention removes noise through smoothing according to Equation (13) in the calculated channel estimation response (S113), and transmits the channel estimation response with the noise removed to the user equipment 100 (S115), and can support high-speed link adaptation.

The channel interpolation and prediction method for fast link adaptation according to the embodiment of the present invention has been described above.

Hereinafter, the performance applied to the embodiment of the present invention as described above will be described.

8 is a diagram showing a performance evaluation index applied to the embodiment of the present invention.

As shown in FIG. 8, there are four errors related to channel estimation and data detection of the present invention.

Here, CP denotes channel prediction, CE denotes channel estimation, and DD denotes data detection.

The simulation results and performance analysis of the present invention will be described.

가 2GHz의 경우 속도와 도플러 주파수의 관계는 다음과 같다. The simulation is based on the LTE uplink system,

Is 2 GHz, the relationship between the speed and the Doppler frequency is as follows.

Freeway Urban Vehicle velocity 140 km / h 15 km / h Doppler frequency 260Hz 28Hz

The LTE uplink system parameters are shown in Table 2 below.

Parameter Value Carrier frequency 2 GHz Bandwidth 1.4 Mhz Sample frequency 1.92 MHz Subframe duration 1ms Subcarrier spacing 15kHz FFT size 128 Occupied subcarriers 72 No. of subcarriers / PRB 12 Cyclic Prefix (CP) Normal CP No. of OFDM symblos / subframe 14 (Normal CP) Modulation scheme 4 QAM Noise AWGN Velocity Freeway: 140 km / h
Urban: 15 km / h Channel Model Freeway: Uma NLos
Urban UMi LoS MIMO Configuration 2 x 2 Channel Estimation MMSE Channel Interpolation and Prediction Linear, Spline, ADPSS Downlink delay 5 ms Advanced Receiver MMSE

For highways, the car runs at 140 km / h and the channel is Uma NLoS (Urban

Macro Non Line of Sight). In urban areas, the vehicle runs at 15 km / h and the channel assumes UMi LoS (Urban Micro Line of Sight).

The simulation result and performance are analyzed.

9 to 12 are diagrams illustrating throughputs according to downlink delay in a highway environment, and show prediction MSE, BER, BLER, and throughput for a downlink delay time of 5 ms. Linear and spline schemes can not perform channel estimation with a delay time of 5ms and lead to poor link adaptation performance. The proposed ADPSS scheme has superior performance in terms of prediction error, which enables reliable data detection with more accurate link adaptation.

Meanwhile, FIGS. 13 to 16 show throughputs according to the downlink delay in the urban environment, and show Prediction MSE, BER, BLER, and Throughput with respect to time 5 ms. The urban environment has better performance in many respects because the vehicle speed is slower than the highway environment. As with the highway environment, the linear and spline schemes can hardly predict the channel with a delay time of 5ms, resulting in poor link adaptation performance. Also, the ADPSS technique shows excellent performance in urban areas with low vehicle speeds.

The channel interpolation and prediction method for fast link adaptation according to the embodiment of the present invention has been described above.

The channel interpolation and prediction method for high speed link adaptation according to an embodiment of the present invention as described above may be provided in the form of a computer readable medium suitable for storing computer program instructions and data.

At this time, the program recorded on the recording medium can be read and installed in the computer and executed, thereby executing the above-described functions.

In order to allow a computer to read a program recorded on a recording medium and to execute functions implemented by the program, the above-mentioned program may be stored in a computer-readable medium such as C, C ++, JAVA, machine language, and the like.

The code may include a function code related to a function or the like that defines the functions described above and may include an execution procedure related control code necessary for the processor of the computer to execute the functions described above according to a predetermined procedure. In addition, such code may further include memory reference related code as to what additional information or media needed to cause the processor of the computer to execute the aforementioned functions should be referenced at any location (address) of the internal or external memory of the computer . In addition, when a processor of a computer needs to communicate with any other computer or server that is remote to execute the above-described functions, the code may be stored in a memory of the computer using a communication module of the computer, It may further include a communication-related code such as how to communicate with another computer or a server, and what information or media should be transmitted or received during communication.

Such computer-readable media suitable for storing computer program instructions and data include, for example, magnetic media such as hard disks, floppy disks and magnetic tape, compact disk read only memory (CD-ROM) Optical media such as a DVD (Digital Video Disk), a magneto-optical medium such as a floppy disk, and a ROM (Read Only Memory), a RAM , Random Access Memory), flash memory, EPROM (Erasable Programmable ROM), and EEPROM (Electrically Erasable Programmable ROM). The processor and memory may be supplemented by, or incorporated in, special purpose logic circuits.

The computer readable recording medium may also be distributed over a networked computer system so that computer readable code can be stored and executed in a distributed manner. The functional program for implementing the present invention and the related code and code segment may be implemented by programmers in the technical field of the present invention in consideration of the system environment of the computer that reads the recording medium and executes the program, Or may be easily modified or modified by the user.

Each step according to the embodiments of the present invention can be implemented by a computer system and implemented by computer-executable instructions. As used herein, a " computing system " is defined as one or more software modules, one or more hardware modules, or a combination thereof that operate in conjunction with performing an operation on electronic data. For example, the definition of a computer system includes a software module such as a personal computer's operating system and a hardware component of a personal computer. The physical layout of the module is not important. The computer system may include one or more computers connected through a network.

Likewise, a computing system may be implemented in a single physical device in which an internal module, such as a memory and a processor, operates in conjunction with performing an operation on the electronic data.

Also, as described above, the present specification includes details of a number of specific implementations, but they should not be construed as being limitations on the scope of any invention or claim, but rather on the particular embodiment of a particular invention But should be understood as an explanation of certain features. Certain features described herein in the context of separate embodiments may be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented in multiple embodiments, either individually or in any suitable subcombination. Further, although the features may operate in a particular combination and may be initially described as so claimed, one or more features from the claimed combination may in some cases be excluded from the combination, Or a variant of a subcombination.

Likewise, although the operations are depicted in the drawings in a particular order, it should be understood that such operations must be performed in that particular order or sequential order shown to achieve the desired result, or that all illustrated operations should be performed. In certain cases, multitasking and parallel processing may be advantageous. Also, the separation of the various system components of the above-described embodiments should not be understood as requiring such separation in all embodiments, and the described program components and systems will generally be integrated together into a single software product or packaged into multiple software products It should be understood.

Certain embodiments of the subject matter described herein have been described. Other embodiments are within the scope of the following claims. For example, the operations recited in the claims may be performed in a different order and still achieve desirable results. By way of example, the process illustrated in the accompanying drawings does not necessarily require that particular illustrated or sequential order to obtain the desired results. In certain implementations, multitasking and parallel processing may be advantageous.

The description sets forth the best mode of the invention, and is provided to illustrate the invention and to enable those skilled in the art to make and use the invention. The written description is not intended to limit the invention to the specific terminology presented. Thus, while the present invention has been described in detail with reference to the above examples, those skilled in the art will be able to make adaptations, modifications, and variations on these examples without departing from the scope of the present invention.

Therefore, the scope of the present invention should not be limited by the described embodiments but should be defined by the claims.

The next generation mobile communication core technology obtained through the present invention is expected to contribute not only to enhancement of mobile communication performance but also to export of terminal parts and network construction. In addition, reliable data detection can have a significant impact on the vehicle communications market. Specifically, it will contribute to securing superiority in standardization competition and leading the next generation mobile communication market. It will also improve technology self-reliance and price competitiveness of domestic mobile communication industry through transfer of intellectual property rights such as patents related to next generation mobile communication, In addition to reducing the cost of mobile communication industry due to cross-licensing, it is anticipated to reduce royalty payment and import substitution effect by securing core technology of next generation mobile communication.

In addition, since the present invention is not only possible to be marketed or operated, but also can be practically and practically carried out, it is industrially applicable.

100: User device
200: base station
210:
220:
230: Signal processor

Claims (10)

The base station,
Receiving a demodulation reference signal from a user equipment; And
Performing channel interpolation and prediction using an estimated channel vector at a pilot symbol position of the received demodulation reference signal; And
And smoothing the channel estimation response calculated through the channel interpolation and prediction to remove noise in the frequency domain,
Wherein performing the channel interpolation and prediction comprises:
Performs channel estimation at a pilot symbol position of the received demodulation reference signal, performs channel estimation at a position where there is no pilot symbol, performs channel estimation to calculate a channel estimation response,
The step of removing the noise includes:
Wherein the smoothing is performed using the following equation: &lt; EMI ID = 17.0 &gt;
[Mathematical Expression]

(here,

Denotes a channel estimation response, and q denotes a smoothing parameter) The method according to claim 1,
Wherein performing the channel interpolation and prediction comprises:
Calculating a correlation matrix using a basis function value of the channel vector estimated at the pilot symbol position;
Constructing a parameter for performing channel interpolation and prediction using the calculated correlation matrix; And
Performing channel interpolation and prediction according to the configured parameters to calculate a channel estimation response;
Wherein the channel estimation and prediction method for fast link adaptation comprises: 3. The method of claim 2,
The step of constructing the parameter
Wherein the parameters are configured using the calculated correlation matrix, the channel vector estimated at the received demodulation reference signal and the pilot symbol position. 3. The method of claim 2,
The step of calculating the channel estimation response
Wherein a channel estimation response is calculated according to a channel interpolation and a prediction in which the parameter is applied to a normal orthogonal basis. 5. The method of claim 4,
The normal orthogonal basis
And an eigenvector of the base matrix formed by applying a base matrix predefined to the estimated channel vector. 6. The method of claim 5,
The base matrix
Wherein the channel estimation is performed using the normalized Doppler frequency. delete delete A receiver for receiving a demodulation reference signal from a user equipment; And
Calculating a correlation matrix using a basis function value of a channel vector estimated at a pilot symbol position of the received demodulation reference signal and constructing a parameter for performing channel interpolation and prediction using the calculated correlation matrix, Calculates a channel estimation response by performing channel interpolation and prediction according to the configured parameters, smoothing the calculated channel estimation response to remove noise in the frequency domain, and then transmits the channel estimation response with the noise removed to the user device And a signal processing unit for controlling the signal processing unit,
The signal processing unit
Performs channel estimation at a pilot symbol position of the received demodulation reference signal, performs channel estimation at a position where the pilot symbol does not exist, and performs channel estimation to calculate a channel estimation response,
Wherein the smoothing is performed using the following equation.
[Mathematical Expression]

(here,

Denotes a channel estimation response, and q denotes a smoothing parameter) delete

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