KR100941107B1 - A method of channel estimation for orthogonal frequency division mutiplexing system and apparatus thereof - Google Patents

Abstract

The present invention relates to a channel estimation method in an orthogonal frequency division multiplexing OFDM system.

In the Orthogonal Frequency Division Multiplexing OFDM system according to the present invention, a channel estimation method includes estimating channel state information based on a received pilot signal, and receiving channel state information based on estimated channel state information. Estimating a Symbol Error Probability (SER) for the data signal in the received carrier frequency signal, estimating a reference data signal having a symbol decoding probability that is doubled with respect to the estimated symbol error probability among the data signals; Estimating a channel based on the pilot signal and the reference data signal.

According to the channel estimation method in the orthogonal frequency division multiplexing system of the present invention, the channel estimation performance of the orthogonal frequency division multiplexing system using the least mean square error estimation method can be improved.

Orthogonal Frequency Division Multiplexing OFDM, Channel Estimation, Estimation Error, Symbol Error Probability (SER), Signal to Noise Ratio (SNR)

Description

Channel Estimation Method and Channel Estimation System in Orthogonal Frequency Division Multiplexing System {A METHOD OF CHANNEL ESTIMATION FOR ORTHOGONAL FREQUENCY DIVISION MUTIPLEXING SYSTEM AND APPARATUS THEREOF}

The present invention relates to a channel estimation method in an orthogonal frequency division multiplexing (OFDM) system. More specifically, the present invention relates to a channel estimation method in an orthogonal frequency division multiplexing system using a minimum mean square error (MMSE) estimation method.

The orthogonal frequency division multiplexing system converts a data sequence input in serial form into parallel data of a predetermined block unit, and then multiplexes the parallelized symbols to different carrier frequencies orthogonal to each other, thereby converting broadband transmission into multiple narrowband parallel transmissions. It is a communication system to transmit. The orthogonal frequency division multiplexing system is resistant to multipath fading in a wireless communication environment and has a high data rate.

An orthogonal frequency division multiplexing system requires a channel estimating and channel compensating apparatus or a method of estimating and compensating a single tap equalizer in the form of a single tap equalizer. Accordingly, many methods have been proposed as channel estimation techniques of an orthogonal frequency division multiplexing system. Generally, channel estimation methods can be broadly classified into pilot-symbol-aided channel estimation and decision-oriented channel estimation. The channel estimation method based on the pilot signal is a method of estimating a channel by periodically sending signals promised to each other from a transmitting and receiving side called a pilot signal in the middle of data to estimate channel state information. This method can more accurately estimate the channel state information by using a larger number of pilot signals (or symbols). However, as the number of pilot signals increases, the amount of data transmitted decreases, thereby degrading band efficiency. The decision-oriented channel estimation method is a method of estimating a channel using not only a pilot signal but also a data signal. In this method, when a data signal having a low reliability is selected and used for channel estimation with a pilot signal, the channel performance is deteriorated.

SUMMARY OF THE INVENTION The present invention has been made in an effort to provide an efficient and improved channel estimation method and apparatus for estimating an orthogonal frequency division multiplexing system.

In the Orthogonal Frequency Division Multiplexing OFDM system according to the present invention, a channel estimation method includes estimating channel state information based on a received pilot signal, and receiving channel state information based on estimated channel state information. Estimating a Symbol Error Probability (SER) for the data signal in the received carrier frequency signal, estimating a reference data signal having a symbol decoding probability that is doubled with respect to the estimated symbol error probability among the data signals; Estimating a channel based on the pilot signal and the reference data signal.

The state information of the channel preferably includes the channel frequency response.

The estimation step of the symbol error probability is

Estimating a Signal to Noise Ratio (SNR) of the carrier frequency signal using the estimated channel state information and estimating a symbol error probability for the data signal using the estimated effective signal to noise ratio (SNR). It is preferable to include.

The estimating step of the reference data signal is

Preferably, the method includes estimating the number of data signals having a symbol decoding probability and selecting the reference data signal by the number of estimated data signals starting from the highest symbol decoding probability.

The channel state information and the channel estimation are preferably estimated using a minimum mean square error (MMSE) estimation method.

A channel estimating apparatus in an orthogonal frequency division multiplexing OFDM system according to the present invention is based on a first channel estimator for estimating channel state information based on a received pilot signal, and estimated channel state information. A symbol error probability estimator for estimating a symbol error probability (SER) for a data signal in a received carrier frequency signal and having a symbol decoding probability that is doubled with respect to an estimated symbol error probability among the data signals And a second channel estimator for estimating a channel based on the data signal estimator for estimating the reference data signal and the pilot signal and the reference data signal.

The state information of the channel preferably includes the channel frequency response.

The symbol error probability estimation unit estimates the effective signal-to-noise ratio (SNR) of the carrier frequency signal using the estimated channel state information, and uses the estimated effective signal-to-noise ratio to determine the symbol error of the data signal. It is desirable to estimate the probability.

The data signal estimator,

A data estimating unit for estimating the number of data signals having a symbol decoding probability and a data signal selecting unit for selecting the reference data signal as many as the estimated number of data signals starting from the highest symbol decoding probability are included.

The channel state information and the channel estimation are preferably estimated using a minimum mean square error (MMSE) estimation method.

According to the channel estimation method in the orthogonal frequency division multiplexing system of the present invention, the channel estimation performance of the orthogonal frequency division multiplexing system using the least mean square error estimation method is improved.

1 is a diagram illustrating a channel estimation method in an orthogonal frequency division multiplexing system according to an embodiment of the present invention.

According to an embodiment of the present invention, a quadrature phase shift keying (QPSK) scheme is applied and a baseband discrete time orthogonal frequency division multiplexing system using a total of N carrier frequency signals. do.

Referring to FIG. 1, a channel estimation method in an orthogonal frequency division multiplexing (OFDM) system according to an embodiment of the present invention may include estimating and estimating channel state information based on a received pilot signal. Estimating a symbol error probability (SER) for the data signal in the received carrier frequency signal based on the state information of the received channel, and symbol decoding probability that is betrayed to the estimated symbol error probability in the data signal. Estimating a reference data signal having a signal and estimating a channel based on the pilot signal and the reference data signal.

First, a step 100 of estimating state information of a channel using a pilot signal included in a received carrier frequency signal will be described. Assuming that the channel does not change during one orthogonal frequency division multiplexing symbol interval, the channel impulse response in the time domain with L multipaths may be expressed as follows.

는 전치 행렬 연산을 나타내고,

는 h가 평균이 0이고, 분산이

인 가우시안 확률 벡터(Gaussian random vector)임을 의미한다. 수학식 1과 같이 시간영역에서의 채널 임펄스 응답을 주파수 영역으로 변환하면 다음 수식과 같이 나타낼 수 있다.In Equation 1

Represents a transpose matrix operation,

H is 0 and the variance

It means that is a Gaussian random vector. As shown in Equation 1, when the channel impulse response in the time domain is converted into the frequency domain, it can be expressed as the following equation.

)은 m=0,1,2,...,N-1 및 n=0,1,2,...,L-1에 대하여 행렬 G의 (m,n)째 원소

과 같은 관계를 갖는다. 수학식 2에서 나타낸 채널의 주파수 응답을 이용하여 송수신단 간의 신호관계를 다음 수식과 같이 나타낼 수 있다.In Equation 2, the channel frequency response (

) Is the (m, n) th element of the matrix G for m = 0,1,2, ..., N-1 and n = 0,1,2, ..., L-1

Has the same relationship as By using the frequency response of the channel shown in Equation 2, the signal relationship between the transmitter and the receiver can be expressed as the following equation.

수신 반송 주파수 신호 벡터,

는 채널의 주파수 응답(

)의 원소로 이루어진 대각 행렬(Diagonal matrix)을 의미한다.

는

송신 반송 주파수 신호 벡터, n은

인 잡음성분을 의미하는 벡터이다. 수학식 3과 같이 나타낸 송,수신단 간의 신호관계로부터 수신되는 파일롯 신호에 대하여 정리하면 다음 수식과 같이 나타낼 수 있다.In equation 3 y is

Receive carrier frequency signal vector,

Is the frequency response of the channel (

Means a diagonal matrix of elements.

Is

Transmit carrier frequency signal vector, n is

A vector representing the noise component. The pilot signal received from the signal relationship between the transmitter and receiver represented by Equation 3 can be summarized as follows.

,

및

는 각각 파일롯 신호를 포함하는 채널 주파수 응답(

), 송신 반송 주파수 신호(

) 및 잡음성분(

)을 나타낸다. 여기서, 수학식 2에 근거하여, 수신된 반송 주파수 신호를 정리하면 다음 수식과 같이 나타낼 수 있다.In equation (4)

,

And

Is a channel frequency response (each containing a pilot signal)

), The transmit carrier frequency signal (

) And noise component (

). Here, based on Equation 2, the received carrier frequency signal can be summarized as shown in the following equation.

는 파일롯 신호에 해당하는

행렬을 의미한다. 따라서, 수신된 파일롯 신호에 기초하여, 베이시안(Bayesian) 최소 평균 자승 오차 추정법을 이용하면 시간영역에서 얻어진 채널은 다음 수식과 같이 나타낼 수 있다.In equation (5)

Corresponds to the pilot signal

It means a matrix. Therefore, based on the received pilot signal, when the Bayesian least mean square error estimation method is used, a channel obtained in the time domain may be represented by the following equation.

는 시간영역에서 추정된 채널 응답,

는 시간영역에서의 채널응답을 의미한다. 또한,

는 시간영역에서 채널응답 및 추정된 채널 응답 간의 오차 (즉, 시간영역에서의 채널추정오차)를 의미한다. 추정된 채널응답을 주파수 영역으로 변환하면 다음 수식과 같이 나타낼 수 있다.In equation (6)

Is the channel response estimated in the time domain,

Denotes the channel response in the time domain. Also,

Denotes an error (ie, channel estimation error in the time domain) between the channel response and the estimated channel response in the time domain. When the estimated channel response is converted into the frequency domain, it can be expressed as the following equation.

)은 주파수 영역에서 추정된 채널의 상태 정보를 의미한다. 또한,

의

째 원소

는 평균이 0이고 분산이

의 대각 합으로 (trace) 표현되는 가우시안 확률 변수이다.Channel response in the frequency domain represented by equation (7)

) Denotes state information of the channel estimated in the frequency domain. Also,

of

Element

Is 0 and the variance is

Gaussian random variable that is expressed as the diagonal sum of.

)에 이용하여 수신된 반송 주파수 신호로부터 유효 신호대잡음비(Signal to Noise Ratio; SNR)를 추정(110)한다. 먼저, 채널 정보 상태(

)를 이용하여, 송신된 k(k=0,1,2,...,N-1)번째 반송 주파수 신호의 채널영향을 보상하면, 다음 수식과 같이 나타낼 수 있다.Estimated channel state information (

Equation 110 to estimate the effective signal to noise ratio (SNR) from the received carrier frequency signal. First, the channel information status (

If the channel influence of the transmitted k (k = 0, 1, 2, ..., N-1) th carrier frequency signal is compensated for, it can be expressed as the following equation.

는 송신 반송 주파수 신호 벡터,

는

벡터의 k번째 원소를 의미한다. 또한,

는 수신단에서의 유효잡음을 의미한다. 추정된 채널 정보 상 태(

)를 바탕으로 유효잡음(

)의 분산을 연산하면 다음 수식과 같이 나타낼 수 있다.In equation (8)

The transmit carrier frequency signal vector,

Is

The k th element of the vector. Also,

Means effective noise at the receiving end. Estimated Channel Information Status (

Based on)

The variance of) can be expressed as

)값으로부터 수신단에서 겪는 유효 신호대잡음비를 추정(110)한다. 여기서, 유효 신호대잡음비는 채널 추정 오차(

)까지 고려한 신호대잡음비를 의미한다. 추정된 유효 신호대잡음비는 다음 수식과 같이 나타낼 수 있다.The variance value of the effective noise obtained from Equation 9

Value 110 to estimate the effective signal-to-noise ratio experienced at the receiver. Here, the effective signal to noise ratio is a channel estimation error (

Means signal to noise ratio. The estimated effective signal to noise ratio can be expressed by the following equation.

)는 k번째 반송 주파수 신호에서의 데이터 신호에 대한 심볼오류의 확률을 추정(120)하기 위해 이용된다. 추정된 심볼오류확률(Symbol Error Probability; SER)은 Q-function을 이용하여 다음 수식과 같이 나타낼 수 있다.Estimated effective signal to noise ratio (

) Is used to estimate 120 the probability of a symbol error for a data signal in a k th carrier frequency signal. The estimated symbol error probability (SER) can be expressed by the following equation using a Q-function.

는 반송 주파수 신호에서의 데이터 신호에 대한 심볼오류확률을 의미한다. In equation (11)

Denotes a symbol error probability for a data signal in a carrier frequency signal.

)을 이용하여, 기준데이터 신호를 선택(140)한다. 기준 데이터 신호를 추정하기 위해서는 파일롯 신호로서 사용될 수 있는 데이터 신호를 추정해야 한다. 또한, 이러한 데이터 신호를 추정하기 위해서는 파일롯 신호로서 사용될 수 있는 데이터 신호의 개수(130)를 추정해야 한다. k번째 반송 주파수 신호에서의 데이터 신호에 오류가 발생할 확률은 앞서 추정된 심볼오류확률(

)이며, 데이터 신호에 오류가 발생하지 않을 확률(즉, 수신 측에서 데이터 신호가 올바르게 검파될 확률)은 심볼오류확률(

)에 대하여 배반인 확률관계를 갖는 심볼복호확률(

)로 나타낼 수 있다. 따라서, 수신된 반송 주파수 신호 중 모든 데이터 신호에 대하여 심볼복호확률(

)을 갖는 데이터 신호의 개수를 추정한다. 따라서 심볼복호확률(

)을 이용하여 추정된 데이터 신호의 개수는 다음 수식에 따라 추정될 수 있다.Then, the estimated symbol error probability (

), A reference data signal is selected (140). In order to estimate the reference data signal, a data signal that can be used as a pilot signal must be estimated. In addition, in order to estimate such a data signal, it is necessary to estimate the number of data signals 130 that can be used as pilot signals. The probability that an error occurs in the data signal at the k th carrier frequency signal is based on the symbol error probability

), And the probability that an error does not occur in the data signal (that is, the probability that the data signal is correctly detected at the receiving end) is the symbol error probability (

Symbol Decoding Probability with Probability

) Therefore, the symbol decoding probability (for all data signals among the received carrier frequency signals)

Estimate the number of data signals with Therefore, symbol decoding probability (

The number of estimated data signals can be estimated according to the following equation.

는 데이터 반송파의 인덱스(index)로 이루어진 집합을 의미한다. 추정된 데이터 신호의 개수는 정수 값을 가져야 하기 때문에, 추정된 값에 가장 가까운 정수를 판별하여 선택한다. 이에 따라, 파일롯 신호와 함께 채널 추정에 사용될 데이터 신호의 개수를 추정(140)한 후, 추정된 심볼오류확률(

)이 낮은 순서부터 추정된 데이터 신호의 개수만큼 데이터 신호를 기준데이터 신호로서 선택(140)한다.In equation (12)

Means a set of indices of data carriers. Since the number of estimated data signals must have an integer value, the integer closest to the estimated value is determined and selected. Accordingly, after estimating 140 the number of data signals to be used for channel estimation together with the pilot signal, the estimated symbol error probability (

The data signal is selected as the reference data signal 140 by the number of estimated data signals starting from the lower order.

Thereafter, the channel is estimated 140 using the pilot signal and the selected reference data signal. Here, the channel may be estimated by using a minimum mean square error (MMSE) estimation method.

2 is a diagram illustrating a channel estimating apparatus in an orthogonal frequency division multiplexing system according to an exemplary embodiment of the present invention.

Referring to FIG. 2, the channel estimation apparatus 200 in an orthogonal frequency division multiplexing OFDM system according to an embodiment of the present invention estimates channel state information based on a received pilot signal. The first channel estimator 210 estimates a symbol error probability (SER) for the data signal in the received carrier frequency signal based on the estimated channel state information. ), A data signal estimator 230 for estimating a reference data signal having a symbol decoding probability that is double the estimated symbol error probability among the data signals, and a second channel for estimating a channel based on a pilot signal and a reference data signal. An estimator 240 is included.

First, the first channel estimator 210 for estimating the state information of the channel using the pilot signal 203 included in the received carrier frequency signal 201 will be described. Assuming that the channel does not change during one orthogonal frequency division multiplexing symbol interval, the channel impulse response in the time domain with L multipaths may be expressed as follows.

는 전치 행렬 연산을 나타내고,

는 h가 평균이 0이고, 분산이

인 가우시안 확률 벡터(Gaussian random vector)임을 의미한다. 수학식 13과 같이 시간영역에서의 채널 임펄스 응답을 주파수 영역으로 변환하면 다음 수식과 같이 나타낼 수 있다.In equation (13)

Represents a transpose matrix operation,

H is 0 and the variance

It means that is a Gaussian random vector. As shown in Equation 13, when the channel impulse response in the time domain is converted into the frequency domain, it can be expressed as the following equation.

)은 m=0,1,2,...,N-1 및 n=0,1,2,...,L-1에 대하여 행렬 G의 (m,n)째 원소

과 같은 관계를 갖는다. 수학식 13에서 나타낸 채널의 주파수 응답을 이용하여 송수신단 간의 신호관계를 다음 수식과 같이 나타낼 수 있다.In Equation 14, the channel frequency response (

) Is the (m, n) th element of the matrix G for m = 0,1,2, ..., N-1 and n = 0,1,2, ..., L-1

Has the same relationship as By using the frequency response of the channel shown in Equation 13, the signal relationship between the transmitter and the receiver can be expressed as follows.

수신 반송 주파수 신호 벡터,

는 채널의 주파수 응답(

)의 원소로 이루어진 대각 행렬(Diagonal matrix)을 의미한다.

는

송신 반송 주파수 신호 벡터, n은

인 잡음성분을 의미하는 벡터이다. 수학식 15과 같이 나타낸 송수신단 간의 신호관계로부터 수신되는 파일롯 신호에 대하여 정리하면 다음 수식과 같이 나타낼 수 있다.In equation (15) y is

Receive carrier frequency signal vector,

Is the frequency response of the channel (

Means a diagonal matrix of elements.

Is

Transmit carrier frequency signal vector, n is

A vector representing the noise component. The pilot signal received from the signal relationship between the transmitter and the receiver represented by Equation 15 may be summarized as follows.

,

및

는 각각 파일롯 신호를 포함하는 채널 주파수 응답(

), 송신 반송 주파수 신호(

) 및 잡음성분(

)을 나타낸다. 여기서, 수학식 14에 근거하여, 수신된 반송 주파수 신호를 정리하면 다음 수식과 같이 나타낼 수 있다.In equation (16)

,

And

Is a channel frequency response (each containing a pilot signal)

), The transmit carrier frequency signal (

) And noise component (

). Here, based on Equation 14, the received carrier frequency signal can be summarized as shown in the following equation.

는 파일롯 신호에 해당하는

행렬을 의미한다. 따라서, 수신된 파일롯 신호에 기초하여, 베이시안(Bayesian) 최소 평균 자승 오차 추정법을 이용하면 시간영역에서 얻어진 채널은 다음 수식과 같이 나타낼 수 있다.In equation (17)

Corresponds to the pilot signal

It means a matrix. Therefore, based on the received pilot signal, when the Bayesian least mean square error estimation method is used, a channel obtained in the time domain may be represented by the following equation.

는 시간영역에서 추정된 채널 응답,

는 시간영역에서의 채널응답을 의미한다. 또한,

는 시간영역에서 채널응답 및 추정된 채널 응답 간의 오차(즉, 시간영역에서의 채널추정오차)를 의미한다. 추정된 채널응답을 주파수 영역으로 변환하면 다음 수식과 같이 나타낼 수 있다.In equation (18)

Is the channel response estimated in the time domain,

Denotes the channel response in the time domain. Also,

Denotes an error (ie, channel estimation error in the time domain) between the channel response and the estimated channel response in the time domain. When the estimated channel response is converted into the frequency domain, it can be expressed as the following equation.

)은 주파수 영역에서 추정된 채널의 상태 정보를 의미한다. 또한,

의

째 원소

는 평균이 0이고 분산이

의 대각 합으로 (trace) 표현되는 가우시안 확률 변수이다. 따라서, 제1 채널추정부(210)는 수신되는 반송 주파수 신호(201)에서의 파일롯 신호(203)만을 이용하여, 채널 주파수 응답을 포함하는 채널 상태 정보(

)(213)를 추정한다.The channel response in the frequency domain represented by equation (19)

) Denotes state information of the channel estimated in the frequency domain. Also,

of

Element

Is 0 and the variance is

Gaussian random variable that is expressed as the diagonal sum of. Accordingly, the first channel estimator 210 uses only the pilot signal 203 in the received carrier frequency signal 201 to transmit the channel state information including the channel frequency response.

213 is estimated.

The symbol error probability estimation unit 220 estimates a symbol error probability of the data signal 205 from the received carrier frequency signal 201.

)(213)를 이용하여 수신된 반송 주파수 신호(201)로부터 유효 신호대잡음비(Signal to Noise Ratio; SNR)를 추정한다. 먼저, 채널 정보 상태(

)를 이용하여, 송신 측에서부터 송신된 k(k=0,1,2,...,N-1)번째 반송 주파수 신호의 채널영향을 보상하면, 다음 수식과 같이 나타낼 수 있다.First, the channel state information estimated from the first channel estimation unit 210 (

213 is used to estimate an effective signal to noise ratio (SNR) from the received carrier frequency signal 201. First, the channel information status (

If the channel influence of the k (k = 0,1,2, ..., N-1) th carrier frequency signal transmitted from the transmitting side is compensated for by using the following equation, it can be expressed as the following equation.

는 송신 반송 주파수 신호 벡터,

는

벡터의 k번째 원소를 의미한다. 또한,

는 수신단에서의 유효잡음을 의미한다. 추정된 채널 정보 상태(

)를 바탕으로 유효잡음(

)의 분산을 연산하면 다음 수식과 같이 나타낼 수 있다.In Equation 20

The transmit carrier frequency signal vector,

Is

The k th element of the vector. Also,

Means effective noise at the receiving end. Estimated Channel Information Status (

Based on)

The variance of) can be expressed as

)값으로부터 수신단에서 겪는 유효 신호대잡음비를 추정한다. 여기서, 유효 신호대잡음비는 채널 추정 오차(

)까지 고려한 신호대잡음비를 의미한다. 추정된 유효 신호대잡음비는 다음 수식과 같이 나타낼 수 있다.Variance of effective noise (

Estimate the effective signal-to-noise ratio experienced by the receiver. Here, the effective signal to noise ratio is a channel estimation error (

Means signal to noise ratio. The estimated effective signal to noise ratio can be expressed by the following equation.

)는 k번째 반송 주파수 신호(201)에서의 데이터 신호(205)에 대한 심볼오류의 확률을 추정하기 위해 이용된다. 추정된 심볼오류확률(Symbol Error Probability; SER)(223)은 Q-function을 이용하여 다음 수식과 같이 나타낼 수 있다.Estimated effective signal to noise ratio (

) Is used to estimate the probability of symbol error for the data signal 205 in the k th carrier frequency signal 201. The estimated Symbol Error Probability (SER) 223 can be represented by the following equation using a Q-function.

는 반송 주파수 신호에서의 데이터 신호(205)에 대한 심볼오류확률(223)을 의미한다.In equation (23)

Denotes a symbol error probability 223 for the data signal 205 in the carrier frequency signal.

The data signal estimator 230 receives the symbol error probability 223 from the symbol error probability estimator 220 and selects a reference data signal 239 that can be used for channel estimation as a pilot signal among the data signals 205. do.

)(223)이며, 데이터 신호(205)에 오류가 발생하지 않을 확률(즉, 수신 측에서 데이터 신호(205)가 올바르게 검파될 확률)은 심볼오류확률(

)(223)에 대하여 배반인 확률관계를 갖는 심볼복호확률(

)로 나타낼 수 있다. 따라서, 수신된 반송 주파수 신호(201) 중 모든 데이터 신호(205)에 대하여 심볼복호확률(

)을 이용하여, 파일롯 신호로서 사용될 수 있는 데이터 신호(205)의 개수(235)를 추정한다. 데이터 신호(235)의 개수는 다음 수식에 따라 추정될 수 있다.First, the data estimator 233 estimates the number of data signals that can be used as pilot signals. The probability that an error occurs in the data signal 205 in the k-th carrier frequency signal is estimated by the symbol error probability

223 and the probability that an error does not occur in the data signal 205 (that is, the probability that the data signal 205 is correctly detected at the receiving end) is a symbol error probability (

Symbol decoding probability with a probability relationship

) Therefore, the symbol decoding probability for all the data signals 205 among the received carrier frequency signals 201 (

) Is used to estimate the number 235 of data signals 205 that can be used as pilot signals. The number of data signals 235 may be estimated according to the following equation.

는 추정된 기준 데이터 신호(203)의 개수를 의미한다. 수학식 24에서

는 데이터 반송파의 인덱스(index)로 이루어진 집합을 의미한다. 추정된 데이터 신호의 개수(235)는 정수 값을 가져야 하기 때문에, 추정된 값에 가장 가까운 정수를 판별하여 선택한다. 이에 따라, 파일롯 신호(203)와 함께 채널 추정에 사용될 데이터 신호의 개수를 추정한 후, 데이터 신호의 개수에 대한 신호가 데이터 신호 선택부(237)로 입력된다.In equation (24)

Denotes the estimated number of reference data signals 203. In equation (24)

Means a set of indices of data carriers. Since the estimated number of data signals 235 should have an integer value, an integer closest to the estimated value is determined and selected. Accordingly, after estimating the number of data signals to be used for channel estimation together with the pilot signal 203, a signal for the number of data signals is input to the data signal selector 237.

)이 높은 순서(또는 심볼오류확률(

)이 낮은 순서)부터 추정된 개수(235)만큼 데이터 신호를 기준데이터 신호(239)로서 선택한다.The data signal selection unit 237 has a symbol decoding probability (

) In high order (or symbol error probability (

Data signals are selected as the reference data signal 239 by the estimated number 235.

The second channel estimator 240 estimates a channel based on the pilot signal 203 and the reference data signal 239 selected from the data signal estimator 230. Here, the second channel estimator 240 may perform channel estimation using a minimum mean square error (MMSE) estimation method.

3 is a graph illustrating reference data signals and pilot signals used for channel estimation in an orthogonal frequency division multiplexing system according to an embodiment of the present invention according to a signal-to-noise ratio.

Referring to FIG. 3, the vertical axis of the graph represents the number of signals used for channel estimation, and the horizontal axis represents the signal-to-noise ratio. As shown in FIG. 3, the number of pilot signals and reference data signals 300 used for channel estimation in an orthogonal frequency division multiplexing system according to an embodiment of the present invention is correctly detected at the pilot signal and the actual receiver. It can be seen that the number nearly coincides with the number 310 of data signals. In Fig. 3, it can be seen that the signal-to-noise ratio (symbol error probability per bit) increases more and more.

4 is a graph showing channel estimation performance in an orthogonal frequency division multiplexing system according to an embodiment of the present invention.

4, the vertical axis of the graph shows the mean square error, and the horizontal axis shows the signal-to-noise ratio. Here, the mean squared error means an average of error squares of the signals used in the channel estimation, and the lower the numerical value, the higher the performance of the channel estimation. As shown in FIG. 4, in the channel estimation, only the pilot signal is used (410), the reference data signal and the pilot signal are used (420), and the actual correctly detected data signal and the pilot signal are used (430). In comparison, the mean square error values of the data signal and the pilot signal detected correctly as the signal-to-noise ratio is increased (430) and the method (420) by the method according to an embodiment of the present invention are substantially the same. It can be seen.

Therefore, according to the channel estimation method and apparatus in the orthogonal frequency division multiplexing system according to an embodiment of the present invention, since a larger amount of information can be used for channel estimation than the conventional channel estimation method using only pilot signals. The mean square error performance is improved. Accordingly, the channel estimation performance of an orthogonal frequency division multiplexing system using the least mean square error estimation method can be improved.

As described above, those skilled in the art will appreciate that the present invention can be implemented in other specific forms without changing the technical spirit or essential features. Therefore, the above-described embodiments are to be understood in all respects as illustrative and not restrictive, and the scope of the present invention is indicated by the appended claims rather than the foregoing description, and the meaning and scope of the claims and All changes or modifications derived from the equivalent concept should be interpreted as being included in the scope of the present invention.

1 is a diagram illustrating a channel estimation method in an orthogonal frequency division multiplexing system according to an embodiment of the present invention.

2 is a diagram illustrating a channel estimating apparatus in an orthogonal frequency division multiplexing system according to an exemplary embodiment of the present invention.

3 is a graph showing a pilot signal and a reference data signal according to an embodiment of the present invention.

4 is a graph showing channel estimation performance according to an embodiment of the present invention.

******** Explanation of symbols for the main parts of the drawing ********

220: symbol error probability estimation unit

233: data estimator

235: reference data signal estimator

Claims (10)

Estimating state information of the channel based on the received pilot signal; Estimating a symbol decoding probability for each symbol of the data signal in the received carrier frequency signal based on the estimated channel state information; Selecting an integer closest to the sum of the symbol decoding probabilities as a reference data number; Selecting as many symbols as the number of reference data in order of the highest symbol decoding probability among each symbol of the data signal; And Re-estimating the channel using the pilot signal and the number of symbols of the selected reference data; A channel estimation method for an orthogonal frequency division multiplexing OFDM system comprising a. The method of claim 1, And the state information of the channel includes a channel frequency response. The method of claim 1, Estimating the symbol decoding probability, Estimating an effective signal to noise ratio (SNR) of the carrier frequency signal using the estimated channel state information; And Estimating a symbol decoding probability for each symbol of the data signal using the estimated effective signal to noise ratio; Channel estimation method for an orthogonal frequency division multiplexing system comprising a. delete The method of claim 1, And the channel state information and the channel estimate are estimated using a minimum mean square error (MMSE) estimation method. A first channel estimator estimating state information of the channel based on the received pilot signal; A symbol error probability estimator estimating a symbol decoding probability for each symbol of the data signal in the received carrier frequency signal based on the estimated channel state information; A data estimator for selecting an integer closest to the sum of the symbol decoding probabilities as a reference data number; A data signal selection unit for selecting as many symbols as the number of reference data in order of the highest symbol decoding probability among the symbols of the data signal; And A second channel estimator for re-estimating the channel using the pilot signal and the number of symbols of the selected reference data; Channel estimation apparatus for an orthogonal frequency division multiplexing OFDM system comprising a. The method of claim 6, And the state information of the channel includes a channel frequency response. The method of claim 6, The symbol error probability estimation unit Estimating a Signal to Noise Ratio (SNR) of the carrier frequency signal using the estimated state information of the channel, and using the estimated effective signal to noise ratio, for each symbol of the data signal A channel estimator for orthogonal frequency division multiplexing system for estimating symbol decoding probability. delete The method of claim 6, The channel state information and the channel estimation are estimated using a minimum mean square error (MMSE) estimation method, the channel estimation apparatus for an orthogonal frequency division multiplexing system.

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