KR20060072096A - Apparatus and method for calculation of llr in a orthogonal frequency division multiplexing communication system using linear equalizer - Google Patents

Abstract

The present invention relates to an apparatus and method for calculating an LLR value required for decoding an FEC code in an orthogonal frequency division multiplexing communication system. The present invention relates to calculating a log likelihood ratio (LLR) in an orthogonal frequency division multiplexing communication system. A method comprising: generating a channel response and a received noise variance value, generating a final equalized signal for a received signal, and performing a symbol-bit conversion by inputting the generated final equalized signal to output an equalized signal for each bit And calculating a noise density vector value by inputting the channel response and the received noise variance value, and calculating an LLR value that is actually applied using the equalized output signal for each bit and the noise density vector value. It is characterized by.

Linear equalizer, Log Likelihood Ratio (LLR), OFDM, Frequency Hopping (FH).

Description

TECHNICAL FIELD AND ELECTRICAL CALCULATION OF LLR IN A ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING COMMUNICATION SYSTEM USING LINEAR EQUALIZER}

1 is a view schematically showing a transmission and reception apparatus of a general OFDM communication system,

2 is a diagram schematically illustrating a configuration of a demodulator device for LLR calculation in a general OFDM communication system;

3 is a diagram schematically illustrating a transmission and reception apparatus of an OFDM communication system employing a fast frequency hopping scheme according to the present invention;

4 is a diagram illustrating a configuration of an LLR block device in an OFDM communication system employing a fast frequency hopping scheme according to the present invention.

The present invention relates to an apparatus and a method for calculating an accurate LLR value in an orthogonal frequency division multiplexing communication system, and more particularly, to an apparatus and a method for calculating an LLR value considering both subchannel channel response and noise component.

In general, the 4th Generation (hereinafter, referred to as '4G') communication system, which is a next-generation communication system, has a variety of quality of service (QoS) with a high transmission speed. Active research is being conducted to provide users with the music. In particular, in 4G communication systems, broadband wireless such as a wireless local area network (hereinafter, referred to as a 'LAN') system and a wireless metropolitan area network (hereinafter, referred to as a 'MAN') system are used. Researches are being actively conducted to support high-speed services in a form of guaranteed mobility and QoS in a broadband wireless access (BWA) communication system.

Accordingly, the 4G communication system is actively studying an orthogonal frequency division multiplexing (OFDM) scheme as a method useful for high-speed data transmission in wired and wireless channels. The OFDM method is a method of transmitting data using a multi-carrier. A plurality of sub-carriers having mutually orthogonality are converted by converting symbol strings input in parallel in parallel. Multicarrier Modulation (MCM) is a type of multicarrier modulation that is modulated and transmitted.

Broadband spectrum resources are required for the 4G communication system to provide high speed, high quality wireless multimedia services. However, when the broadband spectrum resource is used, fading effects on the radio transmission path due to multipath propagation become serious and frequency selective fading also occurs within the transmission band. Therefore, the OFDM scheme, which is robust against frequency selective fading, has greater gain than the code division multiple access (CDMA) scheme for high-speed wireless multimedia services. There is a trend of being actively used in communication systems.

On the other hand, the Orthogonal Frequency Division Multiple Access (OFDMA) scheme is a multiple access scheme based on the OFDM scheme so that a plurality of terminals can use all sub-carriers. That's the way it is. The OFDMA method does not require a spreading sequence for spreading, but since the subchannel allocated to a specific terminal is kept fixed, the allocated subchannel is continuously fading. In this case, the transmission efficiency is reduced. Here, the subchannel refers to a channel composed of a plurality of subcarriers.

Accordingly, a frequency diversity gain may be obtained by dynamically changing a set of subcarriers allocated to a specific terminal, that is, a subchannel according to a fading characteristic of a wireless transmission path, and obtaining the obtained frequency diversity gain. This can increase the transmission efficiency. In this way, a method of dynamically changing a subchannel allocated to a specific terminal is called a 'dynamic resource allocation' method, and a representative method of the dynamic resource allocation method is called frequency hopping (FH). It will be called) method.

The FH scheme is a scheme in which a frequency band in which a signal is transmitted is hopped according to a preset frequency hopping pattern, thereby obtaining an averaged gain of inter-cell interference (ICI). A combination of the FH scheme and the OFDMA scheme is a frequency hopping-orthogonal frequency division multiple access (FH-OFDMA) scheme.

As a result, the FH-OFDMA scheme is a multiple access scheme having robustness to frequency selective fading through the characteristics of the OFDMA scheme and the FH scheme. In the FH-OFDMA scheme, a subchannel frequency allocated to each terminal is leaped using a preset FH code to simultaneously acquire effects due to the FH scheme as well as the OFDMA scheme. In this case, a Latin square code or the like is used as the FH code. The Latin square code has an advantage of reducing cell division as well as inter-cell interference (ICI) in a multi-cell environment.

Meanwhile, in a typical communication system, various forward error correcting (FEC) codes are used to improve performance. Representative FEC codes currently widely used include Turbo code, Convolutional code and Low Density Parity Check (hereinafter referred to as "LDPC") codes. They perform a decoding process by inputting a Log Likelihood Ratio (LLR) value at the receiver. Here, the channel decoder receives an LLR value as an input and performs a recognition and decoding process like a received signal in a white noise environment using BPSK modulation. In this case, when an incorrect LLR value is input to the channel decoder, the reception signal is distorted or the power of the noise signal is increased, thereby greatly deteriorating system performance. Therefore, there is a need for a method and apparatus for accurately calculating the LLR value, and studies on this are being actively conducted. In the following description, it is assumed that a turbo code is used among the various FEC codes for convenience of description.

The LLR value used in the FEC code technique may be defined as in Equation 1 below.

와

는 y가 수 신되었을 때 실제 전송된 신호 d가 +1 또는 -1일 때의 각각의 확률 값을 의미한다. In Equation 1, y represents a received signal or an equalizer output signal value, and d represents a transmit signal transmitted from a transmitter.

Wow

Is the probability value of each when y is received and the actual transmitted signal d is +1 or -1.

은 수신신호 y에 대해 송신신호 d가 각각 +1 또는 -1일 때의 확률비의 자연 로그(ln) 값을 의미한다. 조건부 확률의 성질에 따라 상기 수학식 1의 첫 번째 줄은 송신신호 d가 +1일 때 y가 수신될 확률인

와 송신신호 d가 -1일 때 y가 수신될 확률인

, 또한 송신신호 d가 각각 +1/-1일 두 확률

,

로 전개 가능하다. Therefore, the LLR value defined in Equation 1 above

Denotes a natural log (ln) value of the probability ratio when the transmission signal d is +1 or -1 with respect to the reception signal y, respectively. According to the conditional probability property, the first line of Equation 1 is the probability that y is received when the transmission signal d is +1.

And the probability that y is received when the transmission signal d is -1

Also, two probabilities that the transmission signal d is + 1 / -1, respectively

,

Can be deployed as.

,

이 동일하다고 가정한다. 따라서, 이하에서는 결국 상기 수학식 1의 LLR 값은 최종적으로 세 번째 줄과 같이 정의 및 설명을 전개하도록 한다.In the description of the present specification described below, the above two probabilities are provided for convenience of explanation.

,

Assume this is the same. Therefore, in the following, the LLR value of Equation 1 will eventually be defined and explained as shown in the third line.

Next, a structure of the OFDM communication system will be described with reference to FIG. 1.

1 is a diagram schematically illustrating a transmission and reception apparatus of a general OFDM communication system.

Referring to FIG. 1, a continuous input data sequence is first input to a turbo code encoder 110. Then, the encoder 110 encodes the input data sequence in the FEC mode, and outputs the encoded bit sequence to a first symbol to bit mapper 170. The first symbol mapper 170 converts the output bit sequence into data symbols and outputs the data symbols. In this case, the first symbol mapper 170 includes all arbitrary M-order modulation.

Next, the output data symbol sequence from the first symbol mapper 170 is converted into a symbol signal in parallel form through a serial to parallel converter 121, and then an inverse fast Fourier transform (Inverse Fast). Fourier Transform, hereinafter referred to as "IFFT"). Then, the IFFT unit 123 converts the input data signal, which is a signal in the frequency domain, into a time domain signal through a multicarrier modulation process. Subsequently, the time-domain signal output from the IFFT unit 123 is converted into a symbol signal of a serial form through a parallel to serial converter 125 so that a cyclic prefix (CP) is used. It is input to the inserter (127). The CP inserter 127 removes inter-symbol interference in a multi-transmission channel to the symbol signal converted into the serial form, and is called Inter Carrier Interference (ICI) in each sub-channel signal at the receiver. Add a CP to eliminate

Next, the output signal to which the CP of a form in which the last part of the data signal is repeated in the CP inserter 127 is added is converted into an analog signal in the digital to analog converter 129 and RF ( Radio Frequency) is transmitted to the channel via the processor 130.

Here, the entire block including the serial / parallel converter 121, the IFFT unit 123, the parallel / serial converter 125, the CP inserter 127, and the digital / analog converter 129 is a modulator of the OFDM system ( modulator) 120 is shown.

Meanwhile, the final output signal of the transmitter through the RF processor 130 is received by the receiver after experiencing the channel 180 and is input to the analog to digital converter 151 through the RF processor 140. . The analog-to-digital converter 151 converts the input analog signal into a digital signal and outputs it to the CP remover 153. The CP remover 153 removes and outputs a CP included in the output digital received signal. Here, the CP added by the CP inserter 127 of the transmitter and removed by the CP remover 153 of the receiver serves to remove intersymbol interference in a multipath channel. The output signal of the CP remover 153 is converted into a parallel signal by the serial / parallel converter 155 and input to a fast Fourier transform (FFT) 157. The FFT unit 157 converts the input signal, which is a time domain signal, into a signal in the frequency domain and outputs the signal. A single tap equalizer 159 then performs channel compensation on the signal in the transformed frequency domain.

Here, in the OFDM system, when the length of the CP is greater than the length of the multipath, the output signal of the FFT unit 157 may be expressed in a form in which an independent channel response is multiplied for each subcarrier because there is no ICI. Channel compensation is also possible using the single tap equalizer 159, such as a 1-tap equalizer. The signal compensated for by the channel in the single tap equalizer 159 is converted into a serial data estimation symbol sequence through the parallel / serial converter 161 and input to the second symbol mapper 180. The second symbol mapper 180 converts the output data symbol into a data bit sequence and outputs the result to the turbo code decoder 160. The turbo code decoder 160 restores a final input data sequence after performing a channel decoding process on the data bit sequence.

As described above, in general, the receiver performs a decoding process by inputting a Log Likelihood Ratio (LLR) value, and the accuracy of the LLR value input to the decoder has a significant effect on the system performance. . Accordingly, there is a need for a method and apparatus for accurately calculating the LLR value.

Accordingly, an object of the present invention is to provide a method and apparatus for obtaining an LLR value required for decoding an FEC code in an OFDM communication system.

Another object of the present invention is to provide an apparatus and method for calculating an accurate LLR value considering both channel response and noise component for each subchannel in an orthogonal frequency division multiplexing communication system.

It is another object of the present invention to provide an accurate LLR calculation algorithm considering both an OFDM system using a linear equalizer in a receiver as well as a basic OFDM communication system and considering both channel response and noise components for each subchannel.

Another object of the present invention is to provide a method and apparatus for calculating a LLR (Log Likelihood Ration) value used as an input signal of a turbo code decoder in an OFDM communication system using a linear equalizer.

An apparatus according to the present invention for achieving the above object, in the orthogonal frequency division multiplexing communication system for calculating a Log Likelihood Ratio (LLR), the symbol in the parallel form by modulating the coded bit sequence to a data symbol Transmitting means for converting a signal, performing inverse fast Fourier transform on the parallel-converted symbol, shifting a phase of the inverse fast Fourier transformed signal, and outputting a transmission signal vector; And receiving means for receiving the received signal vector of the time domain from the time domain, and performing a frequency and time domain transformation on the received signal vector to estimate the transmission data symbol vector.

The transmitting means may further include a phase shifter configured to shift the phase of the inverse fast Fourier transformed signal through a diagonal matrix operation to generate a transmission signal vector. The receiving means may include a channel response and A demodulator for generating and outputting a received noise variance value, a symbol mapper for inputting the output signal of the demodulator and outputting a symbol-bit converted bit-wise equalized signal, a channel response and a received noise variance value estimated by the modulator, And an LLR calculator for calculating an LLR value by using the bit-wise equalized output signal of the symbol mapper.

The demodulator may further include a first fast Fourier transformer for performing an FFT on a parallel signal from which a cyclic prefix has been removed from a signal received from the transmitter, and a signal of the fast Fourier transformed frequency domain. A frequency domain linear equalizer for performing channel compensation, an inverse fast Fourier transformer for performing inverse fast Fourier transform on the signal in the channel compensated frequency domain, and performing channel compensation for the signal in the inverse fast Fourier transform time domain And a time domain linear equalizer functioning as a conjugate of the phase potentiometer of the transmitting means, a second fast Fourier transformer for performing fast Fourier transform on the signal in the channel compensated time domain, and the fast Fourier transformer. Parallel / Serial Inputs the Converted Output Signals to a Serial Estimated Data Symbol Sequence Characterized in that it comprises a ventilation, and a channel response estimator for estimating a channel response for the received signal received from the transmitting means, receiving a noise variance estimator for estimating the dispersion value of the received noise signal of said receiving means.

The LLR calculator may include a noise density vector calculator for calculating a noise density vector value by inputting a channel response and a received noise variance value of the demodulator, a bit-wise equalized output signal of the symbol mapper, and the noise density vector calculator. It includes an LLR calculator for calculating the actual LLR value using the noise density vector value.

A method according to the present invention for achieving the above object, in a method for calculating a Log Likelihood Ratio (LLR) in an orthogonal frequency division multiplexing communication system, a symbol of the parallel form by modulating the coded bit sequence into a data symbol Converting to a signal, performing fast Fourier transform on the parallel-converted symbol, shifting a phase of the fast Fourier transformed signal, and generating and outputting a transmission signal vector; The method includes receiving a received signal vector of a region and estimating a transmission data symbol vector by performing frequency and time domain transformation on the received signal vector.

In addition, the transmission data symbol vector estimating process may include generating a channel response and a received noise variance value, generating a final equalized signal for the received signal, and inputting the generated final equalized signal to perform symbol-bit conversion to perform bit Outputting a star equalization signal, and calculating an LLR value using the estimated channel response and received noise variance value and the bit-wise equalized output signal.

The final equalization signal generation may include performing a first fast Fourier transform on a parallel signal from which the cyclic prefix is removed from the received signal and compensating a channel for the signal in the fast Fourier transformed frequency domain. And performing an inverse fast Fourier transform on the signal in the channel compensated frequency domain, and then compensating a channel for the signal in the inverse fast Fourier transform time domain, and performing a signal in the channel compensated time domain. And performing a second fast Fourier transform on the input signal and converting the fast Fourier transformed output signal into a serial estimated data symbol sequence.

The LLR calculation may include calculating a noise density vector value by inputting the channel response and the received noise variance value, and calculating an LLR value that is actually applied using the equalized output signal for each bit and the noise density vector value. It is characterized by including the process of calculating.

Hereinafter, exemplary embodiments of the present invention will be described with reference to the accompanying drawings. In the following description of the present invention, if it is determined that a detailed description of a related known function or configuration may unnecessarily obscure the subject matter of the present invention, the detailed description thereof will be omitted.

Prior to the detailed description of the present invention, a method and apparatus for calculating a Log Likelihood Ratio (LLR) value used as an input signal of a turbo code decoder according to one embodiment of an OFDM system using a linear equalizer are provided. The LLR value obtained by the method proposed by the present invention can be applied to the decoder stages of various FEC codes in addition to the turbo code. In addition, the linear equalizer considered in the present invention also includes a single tap zero-forcing (ZF), minimum mean square error (MMSE), matched filter equalizer, etc. used in a general OFDM system. Therefore, in the present invention described below, first, a method and apparatus for calculating an LLR value when a single tap equalizer is used in a general OFDM system will be described, and it will be extended to the case where a linear equalizer is used based on this. do.

Also, in general, in order to calculate the LLR value, it is necessary to know a variance value, which is a statistical characteristic of a noise signal. That is, the receiver of the general system estimates the variance value of the received signal noise and uses the value. In the case of the OFDM system, the statistical characteristics of the noise signal change according to the channel response of each subchannel during the equalization process. In order to calculate the accurate noise signal variance and the LLR value from the output signal, a method considering the channel response for each subchannel is needed. In addition, in an OFDM system using advanced technology, a method for calculating an accurate noise signal dispersion value and an LLR value even in the presence of thermal noise and inter symbol interference (hereinafter, referred to as 'ISI') noise in a receiver is described. I would like to suggest.

LLR Calculation in General OFDM Systems

First, a method of calculating an LLR value in a receiver of a general OFDM system will be described with reference to FIGS. 1 and 2 below.

FIG. 2 is a diagram schematically illustrating a configuration of a demodulator device for calculating an LLR value in FIG. 1.

First, the received signal is mathematically modeled with reference to FIG. 1. That is, the received signal in the frequency domain which is the output signal of the FFT unit 157 of FIG. 1 may be defined as Equation 2 below.

In Equation 2, r _k represents a received signal of a k-th subcarrier, h _k represents a channel response of a k-th subcarrier, d _k represents a transmission signal transmitted to a k-th subcarrier, and n _k Denotes a noise signal of a k-th subcarrier. In this case, it is assumed that the total number of subcarriers is N and that the BPSK modulation scheme is used, and the second symbol mapper 180 for symbol-bit modulation of FIG. 1 is omitted in FIG. 2.

Next, a receiver operation of a general OFDM system and an LLR calculation method proposed by the present invention will be described with reference to FIG. 2.

FIG. 2 illustrates the receiver devices in FIG. 1 in detail, and includes devices for equalizing received signals, such as analog / digital converter 251, CP canceller 253, serial / parallel converter 255, FFT device. In addition to the single tap equalizer 259 and the parallel / serial converter 261, a channel response estimator 263 and a variance estimator 265 of the received noise signal are included in the OFDM demodulator 250. Also added is an LLR calculator 260. Assuming that ICI does not exist in the above configuration, the received signals r _k , k = 1, ..., N in the frequency domain defined in Equation 2 are equal to the single tap equalizer of FIG. 259) to compensate for the distortion caused by the channel. On the other hand, the case where the single tap equalizer 259 is applied to the single tap ZF equalizer will be described.

That is, when the single tap ZF equalizer is used, since the channel value is divided from the received signal for each subcarrier, the output signals (y _k , k = 1, ..., N) of the single tap equalizer 259 are represented by the following equation. It can be represented as 3.

는 단일 탭 등화기(259)의 k번째 부반송파의 등화기 출력 신호에서 잡음신호를 나타낸다. 상기 수학식 3에 나타낸 바와 같이, 상기 단일 탭 ZF 등화를 수행하는 단일 탭 등화기(259)의 등화 과정을 거치면서 데이터 신호 뿐 아니라 상기 수학식 2의 수신 신호에 포함된 부반송파별잡음 신호 n_k 또한 채널 응답 값으로 나누어지면서 상기 잡음 신호 n_k는 하기 수학식 4와 같이

로 바뀌게 된다.In Equation 3, y _{k, ZF} represents the equalizer output signal of the k-th subcarrier and d _k represents the transmission signal transmitted to the k-th subcarrier,

Denotes a noise signal in the equalizer output signal of the k th subcarrier of single tap equalizer 259. As shown in Equation 3, the subcarrier-specific noise signal n _k included in the received signal of Equation 2 as well as the data signal through the equalization process of the single tap equalizer 259 performing the single tap ZF equalization. In addition, the noise signal n _k is divided by a channel response value as shown in Equation 4 below.

Will change to

In addition, using the definition of the LLR value shown in Equation 1, the logarithm of the probability ratio in which the single-tap ZF equalizer output signal is y _{k, ZF} and the transmission signal d _k is + 1 / -1 in the k th subcarrier, respectively The LLR value represented by the value may be defined as shown in Equation 5 below. At this time, in the present invention, for convenience of description, it is assumed that the two probabilities P (d = -1) and P (d = + 1) are the same, so that the LLR value of Equation 5 is finally Develop definitions and explanations together.

는 확률 값을 의미하는 기호를 나타내며,

는 자연 로그를 나타낸다.In Equation 5, d _k represents a transmission signal of the k-th subcarrier, and y _{k, ZF} represents an equalizer output signal of the k-th subcarrier when the ZF single tap equalizer is used. Also

Represents a symbol representing a probability value,

Indicates a natural logarithm.

와, 송신신호 d_k가 -1일 때 ZF 단일 탭 등화기의 k번째 부반송파 출력 신호가 y_k,ZF일 확률 값인

는 각각 하기 수학식 6과 같이 나타낼 수 있다.In Equation 5, the +1 or -1 probability of occurrence of the transmission signal d _k is equal to 1/2, and passes through a channel to which additional white Gaussian noise (hereinafter, referred to as 'AWGN') is added. In this case, when the transmission signal d _k is +1 in the molecular denominator of Equation 5, the k-th subcarrier output signal of the ZF single tap equalizer is a probability value of y _{k, ZF.}

And when the transmission signal d _k is -1, the probability value of the k th subcarrier output signal of the ZF single tap equalizer is y _{k, ZF}

Can be represented by Equation 6 below.

는 상기 수학식 4에서 정의한 k번째 부반송파에서 상기 잡음신호

의 분산 값을 나타내며, 상기 y_k,ZF는 ZF 단일 탭 등화기를 사용했을 때 k번째 부반송파의 등화기 출력 신호를 나타낸다.In Equation 6, E _tb means the transmission signal energy of one data bit,

Is the noise signal in the kth subcarrier defined in Equation (4)

Where y _{k and ZF} represent the equalizer output signal of the k th subcarrier when using a ZF single tap equalizer.

Accordingly, the LLR calculator 260 of FIG. 2 may obtain a value corresponding to Equation 5, which is an LLR value for each subchannel, by using the probability value obtained in Equation 6, and the output result is represented by Equation 5 below. It can be simply expressed as shown in Equation 7.

가 k번째 부반송파에 전송된 데이터 d_k의 LLR 값을 의미하며, 상기 E_tb는 하나의 데이터 비트의 전송 신호 에너지를 나타내며, 상기

는 상기 수학식 4에서 정의한 k번째 부반송파에서 상기 잡음신호

의 분산 값을 나타내며, 상기 y_k,ZF는 ZF 단일 탭 등화기를 사용했을 때 k번째 부반송파의 등화기 출력 신호를 나타낸다.Probability ratio in Equation 7

Is the LLR value of the data d _k transmitted on the k-th subcarrier, E _tb represents the transmission signal energy of one data bit,

Is the noise signal in the kth subcarrier defined in Equation (4)

Where y _{k and ZF} represent the equalizer output signal of the k th subcarrier when using a ZF single tap equalizer.

The output signal of the LLR calculator 260 is input to the turbo code decoder 170 of FIG. 1 and used to obtain input data bits.

을 구하기 위해서는 잡음 신호 분산 값

만 있으면 된다. Meanwhile, in Equation 7, {y _{k, ZF} } (k, 1, ..., N) denotes an equalizer output signal when a single tap ZF equalizer is used, and E _tb denotes a transmission signal of one data bit. Represents energy. In this case, E _tb may be regarded as transmission signal energy in case of M-order modulation and transmission signal energy in case of BPSK. Therefore, as defined in Equation 7

To obtain the noise signal variance

All you need is

의 분산 값

를 구하기 위하여 먼저 상기 수학식 2의 수신 잡음 신호 n_k의 통계적 특성을 살펴보기로 한다. Meanwhile, hereinafter, the noise signal of the k-th subcarrier output signal used in Equation 7

Variance of

First, the statistical characteristics of the received noise signal n _k of Equation 2 will be described.

로 동일하며, 상기

은 시간 영역의 수신 신호를 바탕으로 상기 도 2의 채널응답 추정기(265)에서 그 추정이 가능한 값이다. 하지만 OFDM 통신 시스템에서 신호의 등화 과정을 거침에 따라 각 부채널별로 채널 응답이 다르게 된다. 그러므로 잡음 신호 분산 값의 변화 또한 각 부채널별로 다르게 된다. 여기서, 상기 각 부채널의 채널 응답을 h_k라고 하고, 단일 탭 ZF 등화기를 사용했을 때 등화기 출력에서의 잡음신호

는 상기의 수학식 4의 정의를 참고하면, 상기 k번째 부반송파의 등화기 출력에서의 잡음 신호(

)의 분산 값(

)은 하기 수학식 8과 같이 정의할 수 있다. 이때, 하기 수학식 9에서

은 상기에서 언급한 바와 같이 수신 잡음 신호(n_k)의 분산 값을 나타낸다.Since the received noise signal n _k is AWGN, the variance value of n _k is for all subcarriers irrespective of k.

Same as above

Is a value that can be estimated by the channel response estimator 265 of FIG. 2 based on the received signal in the time domain. However, as the signal is equalized in an OFDM communication system, the channel response is different for each subchannel. Therefore, the change in the noise signal variance value is also different for each subchannel. Here, the channel response of each subchannel is h _k , and a noise signal at the equalizer output when a single tap ZF equalizer is used.

Referring to the definition of Equation 4, the noise signal at the equalizer output of the k-th subcarrier (

Variance value of

) Can be defined as in Equation 8 below. At this time, in the following equation (9)

_Denotes the variance of the received noise signal n _k as mentioned above.

In addition, when the LLR value derived from Equation 7 is obtained using the noise variance value for each subchannel of Equation 9, Equation 10 may be expressed as follows.

As a result, the LLR calculator 260 of FIG. 2 is a device for calculating Equation 10, and the subchannel estimated by the reception noise variance estimator 263 is input to the LLR calculator 260. The channel response estimation value, the equalizer output signal of the single tap equalizer 259, and the reception noise variance value estimated by the channel response estimator 265 of FIG. 2 are input.

Hereinafter, using the same method as described above, using a single tap PS (Phase Shift) equalizer for compensating for the phase distortion of the channel as another embodiment, and calculating the LLR value for the case of using the BPSK modulation scheme Explain.

의 분산 값은 각각 하기 수학식 11 및 수학식 12와 같이 나타낼 수 있다. 따라서, 이에 따른 상기 LLR 값 산출 식은 하기 수학식 13과 같이 정의된다.Output signal y _{k, PS} of the single tap PS equalizer of the kth subcarrier and noise signal of the single tap PS equalizer output signal

The variance values of may be represented by Equations 11 and 12, respectively. Accordingly, the LLR value calculation equation is defined as in Equation 13 below.

)가 k번째 부반송파에 전송된 데이터 d_k의 LLR 값을 의미하며, 상기 E_tb는 하나의 데이터 비트의 전송 신호 에너지를 의미하며, 상기

는 상기 수학식 12에서 정의한 k번째 부반송파에서 상기 잡음 신호

의 분산 값을 의미하며, 상기 y_k,PS는 단일 탭 PS 등화기를 사용했을 때 k번째 부반송파의 등화기 출력 신호를 나타낸다.In Equation 13, the probability ratio (

) Denotes an LLR value of data d _k transmitted on a k-th subcarrier, and E _tb denotes a transmission signal energy of one data bit.

Is the noise signal in the k-th subcarrier defined in Equation 12

Where y _{k, PS} denotes the equalizer output signal of the k-th subcarrier when a single tap PS equalizer is used.

As described above, in the case of using the single tap PS equalizer, the dispersion value of the noise signal is not changed, but as the energy value of the equalizer output signal value is changed, the LLR value as shown in Equation 13 for each subchannel. Will be different.

Meanwhile, in the above description, only two embodiments of the ZF equalizer and the PS equalizer have been described, but the present invention is not limited thereto. For example, according to the present invention, even when an MMSE equalizer, a matched filter equalizer, etc. are used, an accurate LLR value is obtained in the same manner according to the dispersion value of the noise signal and the energy level of the equalizer output signal according to the channel response for each subchannel. Of course it can be induced.

On the other hand, if there is no ICI between each sub-channel, using a single tap equalizer as described in the equation (10) or equation (13), only considering the noise variance change value according to the channel response of the sub-channel independent We have seen an example of calculating the LLR value. This corresponds to a method of calculating an LLR value in a receiver of a basic OFDM communication system. On the other hand, in order to improve system performance, when a variety of advanced technologies such as frequency hopping (FFH) are introduced in an OFDM communication system, the receiver performs channel compensation for each subchannel. A linear equalizer is also used for the entire receive vector, not the equalizer.

Therefore, hereinafter, a method and apparatus for obtaining an LLR value in an OFDM communication system using a linear equalizer by extending the LLR calculation method in the basic OFDM communication system proposed above will be described. In addition, although the LLR calculation method proposed in the present invention is applicable to all OFDM communication systems using a linear equalizer, in the following description, for convenience of explanation, the OFDM (Fast Frequency Hopping-Orthogonal Frequency) using the proposed FFH technique is described. Division Multiplexing, hereinafter referred to as 'FFH-OFDM'. In addition, since the single tap equalizer used in the basic OFDM communication system is also included as one of the linear equalizers, the method of using the basic single tap equalizer described above and the method to be described later can be applied.

LLR Calculation in OFDM System Using Linear Equalizer

1. Mathematical Models of Signals

The present invention provides accurate LLR values in an OFDM system using a linear equalizer at the receiving end, such as a communication system using a fast frequency hopping method and an orthogonal frequency division multiplexing method (hereinafter, referred to as a 'high frequency hopping-OFDM communication system'). We propose an apparatus and method for calculating. In the following description, for the convenience of description, the fast frequency hopping scheme is performed by setting the period for performing frequency hopping to an OFDM sample period or an integer multiple of the OFDM samples instead of an OFDM symbol period. As a method of performing frequency hopping, when the fast frequency hopping method is used, one OFDM symbol is spread and transmitted to a plurality of sub-carriers in a frequency domain.

First, the structure and apparatus of a transceiver of the FFH-OFDM communication system will be described with reference to FIG. 3.

3 is a diagram schematically illustrating a transmission and reception apparatus of an OFDM communication system employing a fast frequency hopping scheme according to the present invention.

As shown in FIG. 3, the FFH-OFDM communication system according to the present invention is largely composed of a transmitter and a receiver.

The transmitter includes a turbo code encoder 310, a first symbol mapper 320, a serial / parallel converter 331, an IFFT unit 333, a phase shifter 335, and a parallel / serial converter 337. ), A CP inserter 339, a digital-to-analog converter 341, and a radio frequency (hereinafter, referred to as RF) processor 340.

On the transmitter, consecutive input data sequences are first input to the turbocode encoder 310. The encoder 310 then turbo-codes the input data sequence in a corresponding coding scheme, for example, an FEC mode, and outputs the encoded bit sequence to the first symbol mapper 320. In this case, the coding scheme is encoded by a turbo coding scheme or a convolutional coding scheme having the predetermined coding rate as described above. The first symbol mapper 320 generates a modulation symbol by modulating the output bit sequence into a data symbol through a corresponding modulation scheme, and then outputs the modulation symbol to the serial / parallel converter 331. In this case, the first symbol mapper 320 includes all of the M-order modulations. Here, as the modulation scheme, for example, Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK), Quadrature Amplitude Modulation (16QAM), or 64QAM may be used.

The serial / parallel converter 331 inputs the serial modulation symbols output from the first symbol mapper 320 and converts them in parallel and then outputs them to the IFFT unit 333. The IFFT unit 333 inputs the signal output from the serial / parallel converter 331 to perform an N-point IFFT and then outputs it to the phase potentiometer 335.

The phase potential 335 shifts the phase of the IFFT signal and outputs a transmission signal vector to the parallel / serial converter 337. The parallel / serial converter 337 inputs the signal output from the phase potentiometer 335 to perform serial conversion and outputs the signal to the CP inserter 339. The CP inserter 339 inputs a signal output from the parallel / serial converter 337, inserts a CP, and outputs the CP to the digital / analog converter 341. Herein, the CP insertion is inserted to remove interference between the OFDM symbol transmitted at the previous OFDM symbol time and the current OFDM symbol to be transmitted at the current OFDM symbol time when the OFDM symbol is transmitted in the OFDM communication system. In addition, when the receiver incorrectly estimates the start point of an OFDM symbol, an effective OFDM symbol is copied by copying the last predetermined bits of the OFDM symbol in the time domain in order to compensate for the disadvantage that interference between subcarriers occurs and the probability of misjudging a received OFDM symbol increases. It is used as a 'Cyclic Prefix' method of inserting a symbol into a 'Cyclic Prefix' method or a 'Cyclic Postfix' method of copying first predetermined bits of an OFDM symbol in a time domain and inserting it into a valid OFDM symbol.

The digital-to-analog converter 341 receives the signal output from the CP inserter 339, converts the signal, and outputs the analog signal to the RF processor 340. Here, the RF processor 340 includes components such as a filter and a front end unit, and performs RF processing to transmit a signal output from the digital / analog converter 341 on an actual channel. Then transmit on the channel.

The transmitter has been described above and the receiver will be described next. The receiver has a reverse structure of the transmitter.

The receiver includes an RF processor 350, an analog / digital converter 361, a CP canceller 363, a serial / parallel converter 365, a first FFT unit 367, a channel response estimator 379, and a frequency domain. Linear Equalizer in frequency domain 369, IFFT 371, Linear Equalizer in time domain 373, second FFT 375, parallel / serial converter 379), a reception noise variance estimator 381, an LLR calculator 380, and a turbo code decoder 390.

On the receiver, the signal first transmitted at the transmitter is received through the receiver's Rx antenna in a multipath channel 300 and added noise. The signal received through the receive antenna is input to the RF processor 350, and the RF processor 350 down converts the signal received through the receive antenna to an intermediate frequency (IF) band. And then outputs to the analog-to-digital converter 361. The analog-to-digital converter 361 digitally converts an analog signal output from the RF processor 360 and outputs the digital signal to the CP remover 363.

The CP remover 363 inputs the signal output from the analog / digital converter 361 to remove the CP inserted by the transmitter and outputs the CP to the serial / parallel converter 365. The serial / parallel converter 365 inputs a serial signal output from the CP remover 365 to perform parallel conversion and outputs the serial signal to the first FFT unit 367. The first FFT unit 367 performs an N-point FFT on the signal output from the serial / parallel converter 365 and then outputs the signal to the frequency domain linear equalizer 369. The frequency-domain linear equalizer 369 inputs the signal output from the FFT unit 367, and channel-equalizes the channel information estimated by the channel response estimator 379 and then an IFFT unit 371. )

The IFFT unit 371 receives a channel equalized signal output from the frequency domain linear equalizer 369, performs an N-point IFFT, and outputs the result to the time domain linear equalizer 373. The time domain linear equalizer 373 inputs the signal output from the IFFT unit 371, performs channel equalization on the time domain signal, and outputs a channel compensated signal to the second FFT unit 375. The second FFT unit 375 inputs a signal output from the time-domain linear equalizer 373 to perform an N-point FFT and outputs the same to the parallel / serial converter 377. The parallel / serial converter 377 inputs the signal output from the second FFT unit 375, converts the signal in series, and outputs the converted signal.

The signal output from the RF processor 350 is input to the channel response estimator 379 and the reception noise variance estimator 381. The channel response estimator 379 detects pilot symbol or preamble signals from the input signal and performs channel estimation using the detected pilot symbol or preamble signals. In this case, the channel estimation result is output to the frequency domain linear equalizer 369 and the LLR calculator 380. The reception noise variance estimator 381 estimates the reception noise signal variance value of the AWGN such as thermal noise with respect to the reception signal of the receiver and outputs the received noise signal variance value of the AWGN.

The LLR calculator 380 calculates an LLR value by inputting the signal output from the demodulator 360 and the channel response and reception noise variance values output from the channel response estimator 379 and the reception noise variance estimator 381. After that, it is output to the turbo code decoder 390. The turbo code decoder 390 decodes the signal output from the LLR calculator 380 by a corresponding decoding method and then outputs the finally decoded bit sequence. Here, the demodulation method and the decoding method are demodulation methods and decoding methods corresponding to the modulation method and encoding method applied by the transmitter.

Next, the apparatus and the signal of the FFH-OFDM system are defined with reference to FIG. 3.

라고 가정한다. 상기 병렬 신호 벡터

는 하기 수학식 14와 같이 나타낼 수 있다.Referring to FIG. 3, as described above, the continuous input data sequence is first input to the turbo code encoder 310. Then, the encoder 310 performs turbo code encoding on the input data sequence in the FEC mode, and outputs the encoded bit sequence to the first symbol mapper 320. The first symbol mapper 320 modulates the output bit sequence into data symbols and outputs the modulated data symbols. In this case, the first symbol mapper 320 includes all of the M-order modulations. Next, the output data symbol sequence from the first symbol mapper 320 is converted into a symbol signal in parallel form through the serial / parallel converter 331 and then input to the IFFT unit 333. At this time, the IFFT unit 333 inputs an input data symbol vector having N elements input from the serial / parallel converter 331.

Assume that The parallel signal vector

Can be expressed as Equation 14 below.

는 복소 신호 벡터이며 N 크기를 가지는 상기 IFFT기(333)(행렬

로 모델링 가능)와 위상 전위기(Phase Shifter)(335)를 거쳐서 N개의 송신 데이터 신호 벡터

로 출력된다. In Equation 14, T represents a transpose operation, and N represents the total number of subcarriers used in the fast frequency hopping OFDM communication system. remind

Is the complex signal vector and has size N, the IFFT unit 333 (matrix

N transmit data signal vectors via the PSI and Phase Shifter 335

Is output.

를 N-포인트(N-point) IFFT를 수행한 후 상기 위상 전위기(335)로 출력한다. 상기 위상 전위기(335)는 상기 IFFT기(333)에서 출력한 신호를 입력하여 선형 처리한 후 상기 병렬/직렬 변환기(337)로 출력한다.The IFFT unit 333 outputs the signal output from the serial / parallel converter 331.

Is output to the phase potentiometer 335 after performing an N-point IFFT. The phase potentiator 335 inputs the signal output from the IFFT unit 333 and performs a linear process, and then outputs the signal to the parallel / serial converter 337.

를 정의하면 하기 수학식 15와 같이 나타낼 수 있다.Hereinafter, the operation of the IFFT unit 333 and the phase potentiometer 335, which is an apparatus added to perform a modulation / demodulation process by applying a fast frequency hopping technique, will be described in detail. First, a matrix representing an IFFT device 333 that is an inverse fast Fourier device

If it is defined as can be expressed as shown in Equation 15 below.

의 허미시안(Hermitian)

으로 표현 가능하다. 일반적인 OFDM 시스템에서는 상기의 역고속 푸리에 변환 장치 및 고속 푸리에 변환 장치를 이용하여 주파수 변복조 과정을 수행한다.In Equation 15, N denotes the total number of subcarriers used in the OFDM communication system, n denotes a sample index, and m denotes a sub-channel index. Here, the subchannel means a channel composed of a plurality of subcarriers, that is, at least one subcarrier. In addition, an operation of a fast Fourier transform (hereinafter, referred to as an 'FFT') using the FFT scheme corresponding to the IFFT device may be performed by an inverse fast Fourier transform matrix shown in Equation 15 above.

Hermitian of

Can be expressed as In a typical OFDM system, a frequency modulation and demodulation process is performed using the inverse fast Fourier transform device and the fast Fourier transform device.

와는 상이한, 하기 수학식 16과 같은 새로운 행렬, 즉 고속 주파수 도약 기법을 적용하여 주파수 변조를 수행하는, 즉 고속 주파수 도약 행렬

를 정의한다.However, in order to perform a fast frequency hopping for subcarriers transmitting data every OFDM sample time or a time corresponding to a multiple of the OFDM sample time of the present invention, the matrix implemented by the IFFT device

A new matrix such as Equation 16, i.e., performs a frequency modulation by applying a fast frequency hopping technique, i.e., a fast frequency hopping matrix

Define.

은 n번째 샘플에서 m번째 서브 채널의 데이터가 송신되는 서브 캐리어를 나타내며, 따라서,

이 상기 고속 주파수 도약 수행시 고속 주파수 도약 패턴을 결정한다.In Equation 16, n represents a sample index, and m represents a sub-channel index. Also, the

Denotes a subcarrier on which data of the m th subchannel is transmitted in the n th sample, and thus,

When performing the fast frequency hopping, a fast frequency hopping pattern is determined.

로 모델링 가능하며, 그 대각 원소 값은 하기 수학식 17에 나타낸 바와 같다. 본 발명에서는 설명의 편의상 상기 고속 주파수 도약 패턴을 순환 고속 주파수 도약 패턴을 일예로 하여 설명하며, 따라서 상기 행렬

역시 대 각 행렬로 정의되는 것이며, 상기 고속 주파수 도약 패턴의 형태는 변형 가능함은 물론이다.As described above, according to the present invention, it can be seen that the phase potentiometer 335 is newly added to the transmitter of the FFH-OFDM communication system as compared with the transmitter of the basic OFDM communication system of FIG. The phase potentiometer 335 has a diagonal matrix when a cyclic frequency hopping pattern is used.

It can be modeled as, the diagonal element value is as shown in the following equation (17). In the present invention, for convenience of description, the fast frequency hopping pattern will be described using a cyclic fast frequency hopping pattern as an example.

Again, it is defined as a diagonal matrix, and the shape of the fast frequency hopping pattern can be modified.

Meanwhile, in the following description, operations of the other blocks of FIG. 3 are the same as those of the conventional OFDM communication system described above with reference to FIGS. 1 and 2, and thus description thereof will be omitted or simplified. Note that it is excluded from the signal model.

로 정의하여 신호 벡터로 모델링하면, 상기 송신신호 벡터는

로 모델링되는 참조부호 300의 채널을 통과하여 수신된다.In addition, hereinafter, the output signal of the phase potentiometer 335 of FIG. 3 is called a transmission signal vector of an FFH-OFDM communication system, and the transmission signal vector

When modeled as a signal vector, the transmission signal vector is

It is received through the channel of reference numeral 300 which is modeled as.

가 N개의 시간 영역의 수신신호 벡터이며 AWGN인 수신 잡음 신호

는 하기 수학식 18과 같은 공분산 행렬(covariance matrix)을 가진다.Input signal from the FFT unit 367 through the RF processor 350, analog-to-digital converter 361 at the receiver and the CP removed from the CP remover 363

Is a received vector of N time-domain received signals and AWGN

Has a covariance matrix as shown in Equation 18 below.

의 통계적 특성을 나타내는 공분산 행렬

를 정의하였다. 하기 수학식 18의 수신 잡음 신호

의 분산 값인

는 상기 도 3의 수신 잡음 분산 추정기(381)에서 추정한 값을 사용한다. 상기 수신 잡음 분산 추정기(381)는 수신기의 열잡음 등을 AWGN 잡음 으로 모델링하여 송신신호가 없을 때의 신호 분산 값을 측정하는 방법 등을 통해 그 값을 추정하는 장치이다. 또한, 하기 수학식 18에서의 I_N은 대각 행렬의 값이 모두 1인 N by N 행렬을 나타낸다.In Equation 18, the received noise signal vector

Covariance matrix representing the statistical properties of

Defined. Receive Noise Signal of Equation 18

Is the variance of

Uses the value estimated by the reception noise variance estimator 381 of FIG. The reception noise variance estimator 381 is an apparatus for estimating the value of the signal variance value when there is no transmission signal by modeling the thermal noise of the receiver as AWGN noise. In addition, I _N in following formula (18) represents the N by N matrix whose value of diagonal matrix is all 1.

를 이용해서 전송 데이터 심볼 벡터

를 추정하기 위한 선형 등화기를

로 모델링할 수 있다. FFH-OFDM 통신 시스템에서의 상기

는 하기 수학식 19의 행렬식으로 모델링할 수 있으며, 여기에는 신호의 주파수, 시간 영역 변환을 위한 IFFT기(371) 및 FFT기들(367)(375)과, 주파수 영역 선형 등화기(Linear Equalizer in frequency domain)(369), 시간 영역 선형 등화기(Linear Equalizer in time domain)(373)를 모두 포함하고 있다. 즉, 상기 도 3을 참조하면 수신기의 아날로그/디지털 컨버터(361), CP 제거기(363), 직렬/병렬 변환기(365), FFT기(367), 선형 등화기(주파수 영역)(369), IFFT기(371), 선형 등화기(시간 영역)(373), FFT기(375), 병렬/직렬 변환기(377)를 포함하는 FFH-OFDM 디모듈레이터(360)가 상기 선 형 등화기

를 구현하기 위한 장치에 해당된다. Next, the receiver receives the time-domain received signal vector defined by Equation 17 above.

Data symbol vector using

Linear equalizer for estimating

Can be modeled as: Above in FFH-OFDM Communication System

Can be modeled by the determinant of Equation 19, which includes an IFFT unit 371 and FFT units 367 and 375 for frequency and time domain transformation of a signal, and a linear domain equalizer in frequency. domain 369 and Linear Equalizer in time domain 373. That is, referring to FIG. 3, the analog / digital converter 361 of the receiver, the CP canceller 363, the serial / parallel converter 365, the FFT unit 367, the linear equalizer (frequency domain) 369, and the IFFT. FFH-OFDM demodulator 360, which includes a 376, a linear equalizer (time domain) 373, an FFT 375, and a parallel / serial converter 377, is used for the linear equalizer.

Corresponds to the apparatus for implementing the.

는 상기 수학식 15에서 정의한 역고속 푸리에 변환기를 나타내며, 상기 행렬

의 켤레(conjugate) 행렬에 해당되는

는 고속 푸리에 변환기를 나타내며, 행렬

는 도 3의 시간 영역의 선형 등화기(373)를 나타내며, 행렬

는 상기 도 3의 주파수 영역의 선형 등화기(369)를 나타낸다.In Equation 19

Denotes an inverse fast Fourier transformer defined in Equation 15, and the matrix

Corresponds to the conjugate matrix of

Denotes a fast Fourier transformer, the matrix

Denotes a linear equalizer 373 in the time domain of FIG.

Denotes a linear equalizer 369 in the frequency domain of FIG.

행렬로 모델링되는 상기 주파수 영역의 선형 등화기(369)는 상기에서 설명한 기본적인 OFDM 통신 시스템의 단일 탭 등화기와 같은 기능을 수행하고, 그 일예로 Zero forcing 등화기, MMSE 등화기 등을 사용 가능하다. 상기

로 표현된 상기 시간 영역의 선형 등화기(373)는 상기 수학식 17에서

로 정의한 송신기의 상기 위상 전위기(335)의 켤레(conjugate)에 해당되는 장치로 역시 대각행렬인

로 모델링이 가능하다.In Equation 18,

The linear equalizer 369 of the frequency domain modeled as a matrix performs the same function as the single tap equalizer of the basic OFDM communication system described above, and examples thereof include a zero forcing equalizer, an MMSE equalizer, and the like. remind

The linear equalizer 373 of the time domain represented by

A device corresponding to the conjugate of the phase potentiometer 335 of the transmitter defined by

Modeling is possible.

를 이용했을 때 최종 등화기 출력 신호 벡터

는 하기 수학식 20과 같이 나타낼 수 있다.Linear equalizer as in Equation 19

Equalizer Output Signal Vector When Using

Can be expressed as in Equation 20 below.

는 시간 영역의 채널(300)을 나타내며, 행렬

는 상기 수학식 15에서 정의한 역고속 푸리에 변환기를 나타내며, 행렬

는 상기 수학식 17에서 정의한 송신기의 위상 전위기(335)를 나타낸다.Matrix in Equation 20

Represents channel 300 in the time domain,

Denotes an inverse fast Fourier transformer defined in Equation 15,

Denotes a phase potentiometer 335 of the transmitter defined in Equation 17 above.

는 병렬/직렬 변환기(377)를 통하여 직렬 추정 데이터 심볼 시퀀스로 LLR 산출기(380)로 입력되어 각 데이터 비트에 대한 LLR 값을 계산한다. 마지막으로, 상기 LLR 산출기(380)에서 계산된 비트별 LLR 값들이 터보코드 디코더(390)에서 복호화(decoding) 과정을 거쳐 최종 입력 비트 시퀀스를 추정하게 된다.Next, the output signal of the FFT unit 375

Is input to the LLR generator 380 as a sequence of serial estimated data symbols via a parallel / serial converter 377 to calculate the LLR value for each data bit. Finally, the LLR values for each bit calculated by the LLR calculator 380 are decoded by the turbo code decoder 390 to estimate the final input bit sequence.

On the other hand, in the FFH-OFDM communication system using the linear equalizer as described above, the LLR equation can be derived from Equation (1). That is, as in the general OFDM communication system, the equation for obtaining the LLR value includes the linear equalizer output signal, the variance of the noise component for each subchannel, and the channel response value in Equation 20 above. Among these, the variance of the noise components for each subchannel may be modeled as a noise density vector and obtained as follows.

)과 ISI 잡음(

), 열잡음(thermal noise)(

) 성분을 하기 수학식 21과 같이 각각 분리할 수 있다.That is, the equalizer output signal of Equation (20) is an actual data signal component (

) And ISI noise (

), Thermal noise (

) Components can be separated as shown in Equation 21 below.

에 따라 상기 수학식 20에서의

는 AWGN에 의한 열잡음과 함께 ISI에 의한 잡음도 함께 포함할 수 있다. 따라서 두 잡음 성분을 합한 것을 전체 잡음이라고 두고 이에 대한 분산 값을 구한다. 상기 수학식 21에서 상기 수학식 20에서 정의된 등화기 출력 신호 벡터

를 실제 데이터 신호 벡터와 ISI 잡음 성분 벡터, 열잡음 성분 벡터로 분리하여 각각

,

,

로 정의하고, 특히 ISI 잡음 성분 벡터와 열잡음 성분 벡터의 합을

로 나타내었다.Looking at Equation 21 is as follows. That is, a linear equalizer matrix for data demodulation

In Equation 20 according to

In addition to the thermal noise by AWGN may include noise by the ISI. Therefore, the sum of the two noise components is called total noise, and the variance value is calculated. Equalizer output signal vector defined in Equation 20 in Equation 21

Are separated into real data signal vectors, ISI noise component vectors, and thermal noise component vectors, respectively.

,

,

In particular, the sum of the ISI noise component vector and the thermal noise component vector

Represented by.

를 각각 다음과 같이 정의한다. 즉, 상기

는 각각 데이터 신호 성분, ISI 잡음 성분, 열잡음 성분을 표현하기 위하여 정의된 행렬을 나타낸다.Hereinafter, in order to facilitate the expansion of the equation for Equation 21, Equation 21 is expressed through a special matrix operation.

Are defined as follows. That is

Denotes a matrix defined to represent data signal components, ISI noise components, and thermal noise components, respectively.

)이 가우시안 분포를 따른다고 가정하면, 전체 잡음 신호 벡터(

)의 잡음 밀도 벡터(

)는 하기 수학식 22와 같이 정의된다. In Equation 21, the data signal and the noise signal are independent, and the length of the data signal vector is sufficiently long so that the ISI noise (

) Assumes a Gaussian distribution,

Noise density vector of

) Is defined as in Equation 22 below.

는 각각 열잡음 및 ISI 잡음에 대한 잡음 밀도 벡터를 나타내며, 상기

는 각각 전체 잡음, 열잡음, ISI잡음의 공분산 행렬(covariance matrix)로 하기 수학식 23으로 나타낼 수 있다. In Equation 22,

Represents noise density vectors for thermal noise and ISI noise, respectively,

The covariance matrix of total noise, thermal noise, and ISI noise may be represented by Equation 23 below.

는 확률 변수의 평균을 나타내는 기호이며, 상기 E_d는 데이터 심볼

의 평균 전송 에너지를 나타낸다. 상기

는 상기 수학식 21에서 정의된 등화기 출력 신호

에서 ISI 잡음 신호 성분

을 분리하기 위한 ISI 잡음 성분 행렬을 나타내며, 상기

는 상기 수학식 21에서 정의된 등화기 출력 신호

에서 열잡음 신호 성분

을 분리하기 위한 ISI 잡음 성분 행렬을 나타내며, 상기

는 상기 수학식 20에서 정의된 것과 같이 수신신호에 포함된 잡음 성분을 나타내며, 상기

는 상기 수신 잡음 신호(

)의 분산 값을 나타낸다.In Equation 23,

Is a symbol representing an average of random variables, and E _d is a data symbol

Represents the average transmission energy. remind

Equalizer output signal defined in Equation 21

ISI noise signal component in

Represents an ISI noise component matrix for

Equalizer output signal defined in Equation 21

Thermal noise signal component

Represents an ISI noise component matrix for

Denotes a noise component included in the received signal as defined in Equation 20,

Is the received noise signal (

Variance value.

Hereinafter, the configuration of the LLR calculator 380 among the receivers according to FIG. 3 will be described in more detail with reference to FIG. 4.

4 is a diagram illustrating a detailed configuration of an LLR calculator in an OFDM communication system employing a fast frequency hopping scheme according to the present invention.

Referring to FIG. 4, the LLR calculator 380 according to the present invention outputs a noise density vector calculator 410 for calculating a noise density vector value and a noise density vector calculator 410. LLR computation block 430 for calculating the actual LLR value using the noise density vector value. Hereinafter, the operation of the LLR calculator 380 having the above configuration will be described.

The LLR calculator 380 inputs an equalizer output signal, which is symbol-bit converted in the second symbol mapper 370, and a channel response and a received noise variance value estimated by the demodulator 360 as input. Output In this case, the noise density vector calculator 410 calculates a noise density vector value by inputting a channel response and a received noise variance value of the demodulator 360. The LLR calculator 430 calculates an actual LLR value using the bit-wise equalizer output signal of the second symbol mapper 370 and the noise density vector value of the noise density vector calculator 410.

Next, an algorithm of a process performed by the noise density vector calculator 410 and the LLR calculator 430 will be described.

2. Noise density vector calculation algorithm

)는 상기 수학식 21에서 정의된 공분산 행렬들(

,

,

) 내지 수학식 23에서 정의된 ISI 잡음 성분 행렬(

), 열잡음 성분 행렬(

)을 사용하면 하기의 수학식 24와 같이 나타낼 수 있다.The noise density vector (

) Are the covariance matrices (

,

,

) To the ISI noise component matrix defined in (23)

), Thermal noise matrix (

) Can be expressed as in Equation 24 below.

는 상기 수학식 15에서 정의한 역고속 푸리에 변환기를 나타내며, 상기 행렬

의 켤레(conjugate) 행렬에 해당되는

는 고속 푸리에 변환기를 나타내며, 상기 N은 상기 OFDM 통신 시스템에서 사용한 부반송파의 개수를 나타내며, 상기

는 상기 수학식 19에서 정의된 수신 잡음 신호(

)의 분산 값을 나타내며, 상기 E_d는 상기 수학식 14에서 정의된 데이터 심볼 벡터(

)의 평균 전송 에너지를 나타낸다.Matrix in Equation 24

Denotes an inverse fast Fourier transformer defined in Equation 15, and the matrix

Corresponds to the conjugate matrix of

Denotes a fast Fourier transformer, and N denotes the number of subcarriers used in the OFDM communication system.

Is the received noise signal defined in Equation 19

), And E _d is a data symbol vector defined in Equation (14).

Is the average transmission energy.

과 순환 주파수 도 약 패턴을 사용했을 때 시간 영역 등화 행렬

이 모두 대각 행렬이므로 그 대각 성분만을 표현한 벡터들이 상기 수학식 24의

이다. 또한, 상기 수학식 21에서 등화기 출력의 데이터 신호 성분에 곱해진 행렬

역시 대각 행렬이므로 그 대각 성분만을 벡터로 표현하면

와 같으며, 상기 수학식 24에서 함께 정의되어 있다. 또한, 상기 수학식 24에서 사용된 연산기호

는 켤레(conjugate) 노테이션을 나타내며, 연산기호

는 컨쥬게이트(congugate) 노테이션을 나타내며, 연산기호

는 하다마드(Hadamad) 연산으로 벡터의 각 성분별 곱을 의미한다.Looking at Equation 24, the frequency domain equalization matrix

Time Domain Equalization Matrix Using and Cyclic Frequency Hopping Patterns

Since all of these are diagonal matrices, vectors representing only the diagonal components are

to be. Further, the matrix multiplied by the data signal component of the equalizer output in Equation 21

It's also a diagonal matrix, so if we only represent that diagonal component as a vector,

And are defined together in Equation (24). In addition, the operation symbol used in the equation (24)

Represents a conjugate notation, and the operator symbol

Represents a conjugate notation, and the operator symbol

Is the Hadamad operation and means the product of each component of the vector.

는 열잡음뿐만 아니라 ISI 잡음을 모두 포함하고 있는 경우에도 정확한 LLR 값을 계산할 수 있으며, 채널 디코더가 상기의 정확한 LLR 값을 사용하여 복호화(decoding)를 수행함으로써, FEC 코드의 성능을 향상시킬 수 있다. 또한 LLR 값을 구하는 과정에서 상기와 같은 적절한 특수 행렬 연산 예컨대, 하다마드(Hadamard) 연산 등을 도입함으로써 그 복잡도가 큰 행렬 연산을 각 벡터들의 성분의 곱으로 표현함으로써 시스템 복잡도를 크게 줄일 수 있다.Noise density vector calculated as in Equation 24

Can calculate an accurate LLR value even if it contains not only thermal noise but also ISI noise, and can improve the performance of the FEC code by decoding the channel decoder using the correct LLR value. In addition, in the process of obtaining the LLR value, by introducing the appropriate special matrix operation described above, for example, the Hadamard operation, the complexity of the matrix can be greatly reduced by expressing the matrix operation of the components of each vector, thereby greatly reducing the system complexity.

를 구하는 실시 예 중 하나로, M_U = u_all인 경우 상기 수학식 24는 다음 수학식 26과 같이 간단히 개선 가능하다. 상기 수학식 24를 하기 수학식 26으로 유도하기 위하여 수학식 27의 성질이 사용되었다. 수학식 26은 잡음 밀도 벡터

를 구하기 위하여 4개의 FFT/IFFT 동작과 9번의 element-wise 곱셈, 3 번의 element-wise 덧셈을 수행하므로 이는 수학식 24에 비하여 50% FFT/IFFT 동작, 64% element-wise 곱셈으로 복잡도를 감소, 개선한 것이다.Noise density vector

As one of the embodiments of obtaining the equation, when M _U = u _all , Equation 24 may be simply improved as in Equation 26 below. The property of Equation 27 was used to derive Equation 24 to Equation 26 below. Equation 26 is the noise density vector

Since 4 FFT / IFFT operations, 9 element-wise multiplications, and 3 element-wise additions are performed to obtain, the complexity is reduced by 50% FFT / IFFT operation and 64% element-wise multiplication compared to Eq. It is an improvement.

Since the frequency domain MMSE equalizer generally used in the FFH / OFDM system is the same as Equation 28, applying it to Equation 26 above, a simpler Equation 29 can be used to obtain a noise density vector. Equation 29 further improves the complexity of calculating the noise density vector using only 50% FFT / IFFT operation, 21% element-wise multiplication, and 0% element-wise addition calculation compared to using Equation 24. .

3. LLR value calculation algorithm

를 이용하여 실제 LLR 값을 계산하는 알고리즘에 대하여 살펴보기로 한다.Hereinafter, the noise density vector obtained from Equation 24

The algorithm for calculating the actual LLR value using is described.

개의 데이터 비트들에 의해 하나의 데이터 심볼이 결정되므로, 상기 도 3의 FFH-OFDM 송신기에서 터보 코드 인코더(310)를 거쳐 상기 제1 심볼 매퍼(320)에 입력되는 데이터 비트 벡터를

라 하고, 상기 제1 심볼 매퍼(320)까지 통과하여 출력되는 데이터 심볼 벡터를 상기 수학식 14에서 나타낸 것과 같이

라 할 수 있다. 그러면, 등화기 출력 신호 벡터가

일 때,

번째 송신된 데이터 비트

값이 +1 또는 -1 일 확률비의 로그 값을 나타내면 하기의 수학식 30과 같이 정의할 수 있다. First, when using the V-ary modulation technique

Since one data symbol is determined by the number of data bits, the data bit vector inputted to the first symbol mapper 320 through the turbo code encoder 310 in the FFH-OFDM transmitter of FIG.

The data symbol vector passed through the first symbol mapper 320 and outputted as shown in Equation (14)

It can be said. Then the equalizer output signal vector

when,

Data bits sent

If the value represents the logarithm of the probability ratio of +1 or -1, it can be defined as in Equation 30 below.

신호 성분이 포함된 데이터 심볼의 인덱스를 나타낸다. 따라서, 데이터 심볼 d_n은

개의 비트들,

에 의해 결정됨을 알 수 있다. 다음으로, 상기 수학식 30에서 정의된 LLR 값을 구하기 위하여 각 텀들을 자세히 설명하도록 한다. N in Equation (30) is the absence of ISI

Indicates an index of a data symbol including a signal component. Thus, data symbol d _n is

Bits,

It can be seen that it is determined by. Next, each term will be described in detail in order to obtain an LLR value defined in Equation 30 above.

는

개의 데이터 비트들이 +1 또는 -1의 값을 가질 때 가능한 모든 경우의 데이터 심볼들의 집합이다. 따라서 상기 수학식 30에서

값은

번째 데이터 비트

의 값이 1일 때 가능한 모든 데이터 심볼(

)들이 전송될 확률들을 더한 것과 같으므로 상기 수학식 30은 하기의 수학식 32로 간단히 정리할 수 있다.That is, the set defined in Equation 31

Is

Is the set of all possible data symbols when two data bits have a value of +1 or -1. Therefore, in Equation 30

The value is

Data bits

When possible, all possible data symbols (

) Is equal to the sum of the probabilities to be transmitted, so Equation 30 can be simply summarized as Equation 32 below.

를 이용하고 이를 실/허수 축으로 분리하면, 상기 수학식 32으로 표현되는 LLR 값은 하기의 수학식 33과 같이 구할 수 있다. 이때, 데이터 비트

가

의 실수 부분에 변조되면

, 허수부분에 변조되면

를 LLR 값 계산에 적용한다. Further, the equalizer output signal vector obtained from Equation 21

By using and separating this into the real / imaginary axis, the LLR value represented by Equation 32 can be obtained as Equation 33 below. Data bits

end

Is modulated in the real part of

When modulated in the imaginary part

Applies to the calculation of the LLR value.

On the other hand, the detailed description as described above has been described taking the case that the modulation scheme is BPSK. However, the present invention is not limited thereto, and of course, the present invention can be applied to all other methods including QPSK modulation. Next, a process of obtaining the LLR value of Equation 32 for the case of using the ZF equalizer in the QPSK modulation scheme as another embodiment of the present invention will be described.

는 모두 1이 된다.That is, the LLR value when QPSK modulation is used in the embodiment of Equation 32 and the ZF equalizer is used as the frequency domain equalizer may be expressed as Equation 34 below. In this case, it is assumed that the probability that +1 or -1 is transmitted is the same, and when the ZF equalizer is used as the frequency domain equalizer,

Becomes all ones.

는 상기 수학식 22에서 정의한 전체 잡음 신호 성분 벡터(

)의 잡음 밀도 벡터 중 n번째 원소를 나타내며,

는 디코더에서 디코딩할

번째 비트를 나타내며,

은 등화기 최종 출력신호 벡터

의 n번째 원소를 나타낸다.In Equation 34

Is the total noise signal component vector (

) Represents the nth element of the noise density vector of

Decode at decoder

The second bit,

Silver Equalizer Final Output Signal Vector

Represents the nth element of.

는 상기 수학식 34에서는 채널 응답뿐 아니라 ICI까지 고려한 잡음 밀도 벡터

로 나타나고, 상기 수학식 10의 E_tb는 상기 수학식 31에서 평균 심볼 에너지

로 나타나고, 상기 수학식 10에서 y_k,ZF인 등화기 출력 값은 상기 수학식 34에서

또는

로 나타난다. Here, the LLR values of Equation 10 obtained in the basic OFDM communication system and Equation 34 in the FFH-OFDM communication system are compared as follows. That is, the variance value considering the channel response for each subchannel in Equation 10

Is a noise density vector considering not only the channel response but also the ICI.

E _tb of Equation 10 is the average symbol energy in Equation 31

In Equation 10, the equalizer output value y _{k, ZF} is expressed in Equation 34.

or

Appears.

를 출력한다. 이때, 평균 심볼 에너지

는 이미 알고 있는 상수 값이며 등화기 출력 신호로는 복소 신호의 실/허수 중 하나가 사용되며 이를 y라 하였다. 한편, 출력된 각 데이터 비트별 LLR 값들은 터보 코드 디코더로 입력되어, 이후 입력 데이터 신호 벡터를 복호화 하는데 사용된다.That is, as described above, the elements for determining the LLR value are basically the same, but it can be seen that there is a slight change depending on the received signal model or the selected modulation scheme. The apparatus for calculating Equation 34 corresponding to the LLR value when the QPSK modulation is used is the same as the LLR calculator 430 of FIG. 4 as described above. The LLR calculator receives an equalizer output signal and a noise density vector value already calculated by the noise density vector calculator 410 of FIG. 4 as an input, and then uses a multiplier and a divider to calculate an operation corresponding to Equation 31. Through

Outputs In this case, the average symbol energy

Is a known constant value, and one of the real and imaginary numbers of complex signals is used as the equalizer output signal. Meanwhile, the output LLR values for each data bit are input to the turbo code decoder, and then used to decode the input data signal vector.

As described above, the present invention proposes an LLR calculation algorithm and its apparatus using an OFDM communication system using a linear equalizer in a receiver by introducing a fast frequency hopping (FFH) technique. Of course, the application is also possible in all OFDM communication systems using the equalizer.

As described above, although the present invention has been described by way of limited embodiments and drawings, the present invention is not limited thereto and is intended by those skilled in the art to which the present invention pertains. Of course, various modifications and variations are possible within the scope of equivalents of the claims to be described.

As described above, according to the method and apparatus for calculating an LLR in an orthogonal frequency division multiplexing communication system using the linear equalizer of the present invention, an accurate LLR value can be calculated in a basic OFDM communication system. In addition, even when the advanced technology such as the fast frequency hopping technique (FFH) is introduced into the OFDM communication system and the linear equalizer is used, the accurate LLR value considering the subchannel channel response and ICI can be proposed. In addition, the decoding performance of the received data packet can be improved by inputting the correct LLR value to the turbo code decoder. In addition, the matrix operation can be implemented by a simple multiplier using a special matrix operation, and by converting the matrix operation into a component-by-component product, hardware and computational complexity can be reduced when implementing an actual system.

Claims (19)

An apparatus for calculating a Log Likelihood Ratio (LLR) in an orthogonal frequency division multiplexing communication system, The coded bit sequence is modulated into data symbols and converted into a parallel symbol signal, an inverse fast Fourier transform is performed on the parallel converted symbols, and a phase is shifted with respect to the inverse fast Fourier transformed signal. Transmitting means for outputting a transmission signal vector by And receiving means for receiving a received signal vector in a time domain from the transmitting means and estimating a transmission data symbol vector by performing frequency and time domain transform on the received signal vector. The method of claim 1, wherein the transmitting means, And a phase shifter for generating a transmission signal vector by shifting a phase through a diagonal matrix operation on the inverse fast Fourier transformed signal. The method of claim 1, wherein the receiving means, A demodulator for generating and outputting channel response and reception noise variance values; A symbol mapper for inputting an output signal of the demodulator and outputting a symbol-bit converted bit-wise equalization signal; And an LLR calculator for calculating an LLR value using the channel response and the received noise variance estimated by the modulator and the bit-wise equalized output signal of the symbol mapper. According to claim 3, The demodulator of the receiving means, A first fast Fourier transformer for performing fast Fourier transform on the parallel signal from which the cyclic prefix has been removed from the signal received from the transmitting means; A frequency domain linear equalizer for performing channel compensation on the fast Fourier transformed frequency domain signal; An inverse fast Fourier transformer for performing an inverse fast Fourier transform on the signal in the channel compensated frequency domain; A time domain linear equalizer which performs channel compensation on the inverse fast Fourier transformed time domain signal and functions as a conjugate of the phase potentiometer of the transmitting unit; A second fast Fourier transformer for performing fast Fourier transform on the signal in the channel compensated time domain; A parallel / serial converter for inputting the fast Fourier transformed output signal and converting the fast Fourier transformed output signal into a serial estimated data symbol sequence; A channel response estimator for estimating a channel response to the received signal received from the transmitting means; And a reception noise variance estimator for estimating a variance value of the reception noise signal of the reception means. The method of claim 4, wherein the first fast Fourier transformer, And a covariance matrix as shown in the following equation for the received noise signal included in the vector received signal.

remind

Denotes an estimated variance value of the received noise variance estimator. The method of claim 3, wherein the LLR calculator, A noise density vector calculator for calculating a noise density vector value by inputting a channel response and a reception noise variance value of the demodulator; And an LLR calculator for calculating an actual LLR value using the bit-wise equalized output signal of the symbol mapper and the noise density vector value of the noise density vector calculator. The method of claim 6, The noise density vector of the noise density vector calculator is defined by the following equation.

remind

Represents a noise density vector, and

Denotes the product of each component of the vector in a Hadamard operation. The method of claim 6, The noise density vector includes thermal noise and inter symbol interference noise. The method of claim 6, The LLR value calculated and output from the LLR calculator is characterized in that defined by the following equation.

The method of claim 9, The output LLR value of the LLR calculator may be calculated through any one of the following equations, and the data bits

end

Is modulated in the real part of

When modulated in the imaginary part

The apparatus of claim 1, wherein the method is applied to the LLR value calculation.

A method for calculating a Log Likelihood Ratio (LLR) in an orthogonal frequency division multiplexing communication system, The coded bit sequence is modulated into data symbols and converted into a parallel symbol signal, an inverse fast Fourier transform is performed on the parallel converted symbols, and a phase is shifted with respect to the inverse fast Fourier transformed signal. Generating and outputting a transmission signal vector; Receiving the outputted received signal vector of the time domain, and performing a frequency and time domain transform on the received signal vector to estimate the transmission data symbol vector. The method of claim 11, wherein the transmitting data symbol vector estimating process comprises: Generating a channel response and received noise variance value and generating a final equalized signal for the received signal; Outputting an equalized signal for each bit by performing symbol-bit conversion by inputting the generated final equalized signal; Calculating an LLR value by using the estimated channel response and the received noise variance value and the bit-wise equalized output signal. The method of claim 12, wherein the final equalization signal generation, Performing a first fast Fourier transform on the parallel signal from which the cyclic prefix is removed from the received signal, and compensating a channel for a signal in the fast Fourier transformed frequency domain; After performing an inverse fast Fourier transform on the signal in the channel-compensated frequency domain, compensating a channel for the signal in the inverse fast Fourier transform time domain; And performing a second fast Fourier transform on the signal in the channel compensated time domain and inputting the fast Fourier transformed output signal into a serial estimated data symbol sequence. The method of claim 13, wherein the first fast Fourier transform is performed: And a covariance matrix as shown in the following equation for the received noise signal included in the vector received signal.

remind

Denotes the received noise variance value. The method of claim 12, wherein the LLR calculation, Calculating a noise density vector value by inputting the channel response and the received noise variance value; And calculating an LLR value actually applied using the equalized output signal for each bit and the noise density vector value. The method of claim 15, The noise density vector is defined as in the following equation.

remind

Represents a noise density vector, and

Denotes the product of each component of the vector in a Hadamard operation. The method of claim 15, The noise density vector includes thermal noise and inter symbol interference noise. The method of claim 15, The LLR value may be defined as in the following equation.

The method of claim 18, The LLR value may be calculated through at least one of the following equations, and the data bit

end

Is modulated in the real part of

When modulated in the imaginary part

The method according to claim 1, characterized in that for applying the LLR value calculation.

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