KR20120045670A - Apparatus and method for determining channel state indicator in mobile communication system - Google Patents

Abstract

PURPOSE: An apparatus and a method for determining a channel state indicator in a mobile communication system are provided to perform efficient AMC(Adaptive Modulation And Coding) scheduling which is matched with a channel condition through a simple additional operation process by using a mean square channel matrix method. CONSTITUTION: A terminal receives signals(701). The terminal estimates a channel matrix by using a reference signal from the received signals(703). The terminal outputs a predetermined value(705). The terminal calculates a mean value by leveling a value outputted from the former step(707). The terminal determines a predetermined target value by applying an equation based on the calculated value(709, 711).

Description

Method and device for determining channel status indicator in mobile communication system {APPARATUS AND METHOD FOR DETERMINING CHANNEL STATE INDICATOR IN MOBILE COMMUNICATION SYSTEM}

The present invention relates to a mobile communication system, and more particularly, to a method and apparatus for determining a channel state indicator in a multiple input multiple output (MIMO) -orthogonal frequency division multiplexing (OFDM) system.

The Long Term Evolution (LTE) standard is a next-generation broadband mobile communication standard that supports high-speed multimedia data services. As the rapidly growing wireless mobile communication market demands various multimedia services in a wireless environment, the LTE standard has developed and adopted various transmission and reception technologies to satisfy the high requirements of the next generation mobile communication market. Multiple Input Multiple Output (MIMO), orthogonal frequency division multiple access (OFDMA), etc. are typical technologies adopted in the LTE standard, which enable efficient transmission of a large amount of data and high speed data transmission while efficiently using a limited frequency. In the mobile communication system, the MIMO technology has a merit that a diversity gain and a code gain can be simultaneously obtained by forming a plurality of independent fading channels by using a plurality of antennas in a transmitter and a receiver. In addition, MIMO technology improves the data rate by using spatial multiplexing, which transmits different data to each transmit antenna, or improves the decoding success rate by using spatial diversity (eg, Alamouti). You can.

On the other hand, OFDM technology is a modulation scheme that multiplexes a high-speed transmission signal into a plurality of orthogonal narrowband subcarriers, and has robust characteristics in a multipath fading channel, and has an advantage of efficiently utilizing a frequency band. OFDM technology has been adopted in modern wireless communication standards such as LTE, LTE advanced, and IEEE 802.11e.

The LTE standard proposes open-loop and closed-loop MIMO systems.

The closed loop method selects and adjusts a transmission mode, a data rate, and a weight vector for a transmission signal based on channel state information. On the other hand, the open loop method adjusts the transmission mode and data rate based on partial information on the channel state. The closed loop scheme can achieve higher data rates than the open loop scheme.

When determining a channel state indicator (eg, channel representative value, channel quality indicator, etc., hereinafter, the channel representative value will be described as an example) in a MIMO-OFDM system in a multipath fading channel environment. Using the average channel matrix, the channel representative value can be determined with a small amount of computation, but there is a problem in that it does not properly reflect the actual channel state.

Instead of using the average channel matrix, a method of averaging post-detection SNR after detecting a received signal with an MMSE receiver can solve the problem of not properly reflecting actual channel conditions. However, the actual number of reference symbols used in the MIMO-OFDM system can be more than 48, and the process of calculating and averaging the SNR after detecting the MMSE corresponding to each reference symbol requires a large amount of computation. Therefore, there is a need for a method capable of accurately reflecting the actual channel state and reducing the amount of computation.

The present invention provides a method and apparatus for determining a channel state indicator that can accurately reflect a multipath fading channel state in a mobile communication system.

The present invention also provides a method and apparatus for calculating a channel state indicator through a simple operation in a mobile communication system.

In addition, the present invention provides a method and apparatus for determining a channel state indicator that can reflect the state of various channel matrices that change in both frequency and time domains due to the characteristics of multipath fading channels and OFDM modulation in a mobile communication system.

According to an aspect of the present invention, there is provided a method of determining a channel indicator in a mobile communication system, the method comprising: performing a hermithian operation on a channel estimated channel matrix; Calculating a mean square matrix by averaging the channel value of the Hermithian operation; Calculating an SNR based on the channel matrix averaging value; And determining a channel indicator based on the SNR.

In accordance with another aspect of the present invention, an apparatus for determining a channel indicator in a mobile communication system is provided. A channel matrix averaging processor configured to calculate an average square matrix by averaging the channel output value of the hermithian calculator; An SNR calculator configured to calculate an SNR based on an output value of the channel matrix averaging processor; And a channel indicator determiner that determines a channel state indicator based on the SNR.

The present invention can determine a channel state indicator that can accurately reflect the multipath fading channel state in a mobile communication system.

In addition, the present invention can calculate the channel state indicator through a simple operation in the mobile communication system.

In addition, the present invention may reflect the state of various channel matrices that change in both frequency and time domains due to the characteristics of multipath fading channel and OFDM modulation in a mobile communication system.

In addition, the present invention can generate CQI information to enable efficient AMC scheduling according to the channel state through a simple additional calculation process using the mean square channel matrix method.

1 is a block diagram of a typical 2 x 2 MIMO-OFDM system;
2 is a diagram illustrating a resource grid corresponding to one subframe in a 2 × 2 MIMO-OFDM system having a channel bandwidth of 1.4 MHz;
3 is a flowchart illustrating an operation of determining a channel representative value using an average channel matrix;
4 is a flowchart illustrating an operation of determining a channel representative value using SNR after average detection of a linear receiver;
5 and 6 are graphs illustrating a change pattern in a frequency domain of a channel coefficient magnitude corresponding to the first OFDM symbol in an arbitrary subframe;
7 is a flowchart illustrating an operation of determining a channel representative value according to an embodiment of the present invention;
8 is a block diagram of an apparatus for determining channel representative values according to an embodiment of the present invention;
9 and 10 are performance diagrams of a MIMO-OFDM (MMSE) system according to a channel representative value determination method in a multipath fading channel (Pedestrian A) having a Doppler frequency of 20 Hz,
11 and 12 are performance diagrams of a MIMO-OFDM (MMSE) system according to a channel representative value determination method in a multipath fading channel (Vehicular A) having a Doppler frequency of 60 Hz,
13 and 14 are performance diagrams of a MIMO-OFDM (MMSE) system according to a channel representative value determination method in a multipath fading channel (Vehicular A) having a Doppler frequency of 110 Hz,
15 is a diagram of throughput performance of a MIMO-OFDM (MMSE) -HARQ system according to a channel representative value determination method in a multipath fading channel (Vehicular A) having a Doppler frequency of 110 Hz.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be noted that the same components in the figures represent the same numerals wherever possible.

In addition, specific details are set forth in the following description, which is provided to help a more general understanding of the present invention, and it is obvious to those skilled in the art that the present invention may be practiced without these specific details. Will do. In the following description of the present invention, detailed descriptions of related well-known functions or configurations will be omitted when it is determined that the detailed descriptions may unnecessarily obscure the subject matter of the present invention.

The present invention implements a closed loop MIMO-OFDM system based on the LTE downlink standard.

In describing the embodiments of the present invention in detail, the standard for 3GPP EUTRA (Evolved UMTS Terrestrial Radio Access) (or Long Term Evolution (LTE)) or Advanced E-UTRA (or LTE-A) is mainly used. Will be targeted. However, the main subject matter of the present invention is applicable to other communication systems having a similar technical background, channel type, network structure, or protocol in some variations without departing from the scope of the present invention. This will be possible in the judgment of a person skilled in the art of the present invention. The channel status indicator to be described below may be, for example, a channel representative value, a channel quality indicator (Channel Quality Indicator), a RI (Rank Indicator), a Precoding Matrix Indicator (PMI), or the like. It may further include a parameter.

In the MIMO system, a complex OFDM signal in a time domain is transmitted from each transmit antenna through a MIMO channel including NT transmit antennas and NR receive antennas. After FFT (fast Fourier transform) demodulation at the receiver, the received signal at the k-th subcarrier is represented by a vector equation as shown in Equation 1 below.

의 분산을 가지는 N_R×1 크기의 부가 백색정규 잡음(additive white Gaussian noise: AWGN) 벡터를 나타낸다. 여기서 I_k는 K×K 크기의 단위행렬이고, (.)^H는 Hermitian 연산자이다. 그리고 H_(k)는 j번째 행과 i번째 열의 성분 h _ji 가 i 번째 송신 안테나에서 j번째 수신 안테나 간의 채널 응답 특성을 나타내는 k번째 부반송파의 N _R ×N _T 채널 행렬에 해당한다. 이하 본 명세서에서는 기호 표기의 편의상 부반송파 인덱스 k를 생략하기로 한다. 본 발명에서는 2개의 송신(기지국) 안테나와 2개의 수신(사용자 단말) 안테나로 구성된 MIMO-OFDM 시스템을 고려한다. 또한 본 발명에서는 공간다중화 MIMO 시스템의 수신기 구조로는 ML(Maximum Likelihood) 수신기와 ZF(Zero Forcing), MMSE(Minimum Mean Square Error) 등의 선형 수신기를 고려한다. 상기 ML 수신기는 하기 <수학식 2>와 같이 최소 유클리디안(Euclidean) 거리 값을 찾기 위해 모든 송신 심볼의 조합을 비교하면서 각 송신 안테나의 심볼을 복조한다. In Equation 1, y _(k) and x _(k) are N _R × 1 sized reception symbol vectors and N _T × 1 sized transmission symbol vectors. Vector n _(k) has a mean of 0,

It represents an additive white Gaussian noise (AWGN) vector of size N _R × 1 having a variance of. Where I _k is a unit matrix of size K × K and (.) ^H is a Hermitian operator. H _(k) corresponds to the N _R × N _T channel matrix of the k th subcarrier whose component h _ji in the j th row and the i th column represents a channel response characteristic between the i th transmit antenna and the j th receive antenna. In the following specification, the subcarrier index k will be omitted for convenience of symbolic notation. The present invention considers a MIMO-OFDM system consisting of two transmit (base station) antennas and two receive (user terminal) antennas. In addition, in the present invention, as a receiver structure of a spatial multiplexed MIMO system, a linear receiver such as a maximum likelihood (ML) receiver, zero forcing (ZF), minimum mean square error (MMSE), and the like are considered. The ML receiver demodulates the symbols of each transmit antenna while comparing the combinations of all transmit symbols to find the minimum Euclidean distance value as shown in Equation 2 below.

는 벡터의 놈(norm) 연산을 나타내고, S 는 성상도 집합을 의미한다. 하지만, 변조차수(modulation order)와 송신 안테나의 수의 증가에 따라 지수적으로 증가하는 높은 연산 복잡도의 문제점을 갖는다. 반면, ZF, MMSE 등의 선형 수신기는 ML 수신기보다 검출 성능은 떨어지지만 간단한 형태로 설계 가능하다. 선형 수신기는 수신 신호에 검출 행렬(G)을 곱하여 송신 신호를 검출한다.(참고문헌 : “박경원, 조용수, “MIMO-OFDM 기술”, 대한전자공학회, 제18권, 제2호, pp. 16-27, 2002.”)here

Denotes a norm operation of a vector, and S denotes a constellation set. However, there is a problem of high computational complexity that increases exponentially with the increase of the modulation order and the number of transmit antennas. On the other hand, linear receivers such as ZF and MMSE have lower detection performance than ML receivers but can be designed in a simple form. The linear receiver detects the transmission signal by multiplying the received signal by the detection matrix (G). (Reference: “Kyung-Won Park, Yong-Soo Cho,“ MIMO-OFDM Technology ”, The Korean Institute of Electronics Engineers, Vol. 18, No. 2, pp. 16 -27, 2002.)

The detection matrices of the ZF receiver and the MMSE receiver are shown in Equations 4 and 5, respectively.

Where A ^-1 represents the inverse of the matrix A.

In order to apply an error correcting code such as a turbo code and a low density parity check (LDPC) code, the MIMO receiver must generate and pass a log-likelihood ratio (LLR) value to the decoder. The LLR value for the i th codeword bit of the m th transport layer of the ML receiver is expressed by Equation 6 below.

은 m번째 전송 레이어의 i번째 부호어 비트가 0(1)인 QAM (Quadrature Amplitude Modulation) 심볼 집합을 나타낸다. 이와 유사하게 MIMO 선형 수신기에서 m번째 전송 레이어의 i번째 부호어 비트를 위한 LLR 값은 하기 <수학식 7>과 같다.here

Denotes a Quadrature Amplitude Modulation (QAM) symbol set in which the i th codeword bit of the m th transport layer is 0 (1). Similarly, the LLR value for the i th codeword bit of the m th transport layer in the MIMO linear receiver is expressed by Equation 7 below.

은 i번째 부호어 비트가 0(1)인 QAM 심볼 집합을 나타낸다.

은 행렬 G의 m번째 행 벡터이고, h _j 는 행렬 H의 j번째 열 벡터이다. 그리고

은 선형행렬의 검출과정 후의 잡음 벡터의 분산을 의미하며, ZF 수신기와 MMSE 수신기의 검출 후 잡음벡터는 하기 <수학식 8>, <수학식 9>와 같다.In Equation 7 above

Denotes a QAM symbol set in which the i th codeword bit is 0 (1).

Is the m-th row vector of the matrix G, and h _j is the j-th column vector of the matrix H. And

Denotes the variance of the noise vector after the linear matrix detection process, and the noise vectors after the detection of the ZF receiver and the MMSE receiver are represented by Equations 8 and 9 below.

Using Equations 8 and 9, an effective signal-to-noise ratio (SNR) obtained after the detection process can be obtained. After detection of the m th transport layer of each of the ZF receiver and the MMSE receiver, the SNR values are represented by Equations 10 and 11, respectively.

In Equations 10 and 11, E _s is the average energy of the transmitting symbol. In the present invention, the SNR values detected through Equations 10 and 11 are metrics for generating channel quality indicator (CQI) information. In the case of the ZF receiver, Equation 10 is used, and in the case of the MMSE receiver, Equation 11 is used to generate CQI information. In the case of the ML receiver, the MIMO channel cannot be distinguished independently, so the effective SNR value cannot be calculated as easily as the linear receiver. Therefore, the ML receiver generates CQI information using the SNR value after detecting the MMSE of Equation (11).

Here, the CQI information is feedback information for controlling modulation order and code rate of a transmission signal according to channel conditions in order to improve transmission efficiency of a closed loop MIMO-OFDM system. That is, it is necessary information to perform AMC scheduling that transmits data of high modulation order and code rate in good channel and transmits data of low modulation order and code rate in poor channel. In the LTE standard, CQI information consists of index values of a predefined CQI table for a combination of various code rates and orders of modulation schemes. The CQI table consists of a total of 15 indexes using modulation schemes such as QPSK, 16QAM, and 64QAM. In the present invention, the SNR range of the CQI table is set by analyzing the frame error rate (FER) performance of the turbo code defined in the LTE standard by applying a modulation method and a code rate corresponding to each CQI index. <Table 1> is an example of the CQI table used in the present invention, the SNR range of each index is 10 FER at the first transmission (not HARQ retransmission) of the SISO (Single-Input Single-Output) -OFDM system turbo-coded in the AWGN channel <"References J. Lee and J-K. Han, and J. Zhang," MIMO technologies in 3GPP LTE and LTE-advanced ", EURASIP Journal on Wireless Commun. and Network., vol. 2009, no. 302092, pp. 1-10, May 2009. ”

, 여기서 N_c는 부호어 개수)을 계산한 후, CQI 표의 각 인덱스에 해당하는 SNR 범위와 비교하여 검출후 SNR 값이 속하는 범위의 인덱스를 CQI 정보로 피드백한다. 즉, CQI 정보는 m 번째 선형 수신기의 MMSE 검출 후 SNR이 m 번째 전송 레이어에 매핑되어 전송되는 부호어가 겪는 채널상태를 나타내는 메트릭이 된다.In the MIMO-OFDM system, CQI information may be generated using the SNR values detected by the linear receiver using Equations 10 and 11 above. For example, SNR (=

, Where N _c is the number of codewords), and compares the SNR range corresponding to each index of the CQI table and feeds back the index of the range to which the SNR value belongs after detection with CQI information. That is, the CQI information is a metric indicating a channel state experienced by a codeword transmitted after SNR is mapped to the mth transport layer after detecting the MMSE of the mth linear receiver.

1 illustrates a MIMO-OFDM system with a feedback channel of CQI information and two transceiver antennas.

Referring to FIG. 1, reference numeral 100 denotes a transmitter and reference numeral 120 denotes a receiver.

The transmitter 100 receives a channel state indicator through a feedback channel from the receiver 120. The channel encoder 101 of the transmitter 100 determines and codes a channel code rate of a transmission codeword according to the fed back channel state indicator, and the QAM mappers 103a and 103b determine a modulation scheme according to the fed back channel state indicator. A sequence of modulation symbols is generated based on the determined modulation scheme. In the LTE standard, up to two independent codewords can be generated and transmitted in a spatial multiplexed MIMO-OFDM system. Accordingly, in the present invention, two codewords are independently generated, and CQI information for each of them is generated to perform AMC scheduling.

The codeword is modulated into a complex QAM symbol according to the channel state indicator, and then the QAM symbol is generated as an OFDM symbol using a plurality of subcarriers after passing through the IFFTs 105a and 105b and the CP adders 107a and 107b. That is, the QAM symbol is mapped to the resource grid as shown in FIG. 2 and then modulated into an OFDM symbol through an inverse fast Fourier transform (IFFT) process.

Since the receiver 120 performs the reverse process of the transmitter 100, detailed description thereof will be omitted. However, the present invention operates in the feedback information generator 128 of the receiver 120, and the feedback information generator 128 generates efficient feedback information for the wideband MIMO-OFDM channel having various channel state indicators.

FIG. 2 shows a resource grid corresponding to one subframe defined in the LTE standard, assuming a channel bandwidth of 1.4 MHz.

Seven OFDM symbols constitute one time slot and two time slots constitute one subframe. Each OFDM symbol consists of 72 subcarriers and has an IFFT size of 2048. The first three OFDM symbols (l = 0, 1, 2) in each time slot are a physical downlink control channel (PDCCH), and the remaining OFDM symbols are a physical downlink shared channel (PDSCH). In the resource grid, the resource grid of the l-th OFDM symbol and the k-th subcarrier is represented as a resource component (l, k). R _p represents a reference signal corresponding to the p th transmit antenna. In the p th antenna port, only a corresponding reference symbol is mapped and used, and the resource grid corresponding to the other antenna is left blank. That is, the grid corresponding to the 0 reference symbol in the antenna 1 is not used. The receiver estimates the channel coefficient using the reference signal and detects the data.

Assuming a single path fading channel in units of blocks (or codewords) in an OFDM system, QAM symbols mapped to a resource grid as shown in FIG. 2 all experience the same fading channel. In other words, all resource components l, k have the same channel gain. Therefore, in such a MIMO-OFDM system, one channel matrix may be estimated every time one subframe is transmitted in each transport layer, and the CNR information may be generated by calculating an SNR value after detecting the MMSE. However, in an actual wireless communication environment, OFDM symbols undergo a multipath fading channel. In a multipath fading channel, OFDM symbols may experience different channel gains in the frequency and time domains. The QAM symbol in the resource grid corresponding to one subframe may have various channel coefficients.

In the MIMO-OFDM system of a multipath fading channel environment, since codewords mapped to one subframe undergo various channel matrices, it is unclear which channel matrices should be calculated after MMSE detection among several channel matrices. Accordingly, there is a need for a method of determining a channel state indicator (or channel representative value) required to generate one CQI information corresponding to one codeword. Since the receiver estimates the channel using the reference signal, the channel representative value M _Ch is determined by estimating the channel matrix corresponding to each reference symbol grid.

Basically, in a MIMO-OFDM system in a multipath fading channel environment, a channel representative value may be determined using an average channel matrix as shown in Equation 12.

는 k번째 기준심볼에 해당하는 채널행렬의 i번째 행과 j번째 행렬성분을 나타낸다. <수학식 13>과 같이 여러 기준심볼의 채널행렬을 평균화하여 하나의 평균 채널을 생성하고, 이에 기반하여 채널 대표값을 결정한다.Here, Nref represents the number of reference symbols per subframe of each antenna. In FIG. 2, 48 reference symbols are transmitted per subframe of each antenna.

Denotes the i th row and the j th matrix component of the channel matrix corresponding to the k th reference symbol. As shown in Equation 13, one average channel is generated by averaging channel matrices of several reference symbols, and the channel representative value is determined based on this.

The receiver generates CQI information using the representative value of the multipath fading channel as shown in Equation (13).

3 is a flowchart illustrating a method of using an average channel matrix.

Referring to FIG. 3, the terminal receives signals in step 301 and estimates a channel matrix H _ref (k) using a reference signal among the signals received in step 303. Thereafter, the terminal proceeds to step 305 to calculate the H _avg value (Equation 12) by averaging the channel matrix estimated in step 303. When the H _avg value is determined, SNR _MMSE (H _avg ) is calculated by substituting this in Equation 11 in step 307. Thereafter, the terminal proceeds to step 309 and determines the channel representative value by applying Equation 13 to the SNR _MMSE (H _avg ) calculated in step 307.

Using the average channel matrix is a simple way to determine the representative channel value with a small amount of computation.However, in the process of averaging the channel matrix, the actual channel matrix components are not 0, but the average value is 0. There is a problem generating. Therefore, instead of averaging the channel matrix, the method of calculating the SNR first after detecting the MMSE of the channel matrix corresponding to each reference symbol and averaging these values is considered. This method will be described with reference to FIG. 4. 4 is a flowchart illustrating a method of determining a channel representative value using SNR after average detection of a linear receiver.

First, the terminal receives signals in step 401 and estimates a channel matrix using a reference signal among the signals received in step 403. Thereafter, in step 405, the terminal calculates an SNR _MMSE (H _ref (k)) by substituting the estimated value in step 403 into Equation 11, and proceeds to step 407 to calculate the SNR _MMSE (H calculated in step 405). _ref (k)) is applied to Equation 14 to calculate SNR _avg .

Equation 14 represents a process of averaging SNR values after detecting N _ref MMSEs. After detecting the average MMSE obtained as described above, the UE determines the channel representative value such that the SNR value is used as the channel representative value in Equation 15 in step 409.

As described above, two methods for determining channel representative values in a MIMO-OFDM system in a multipath fading channel environment are briefly described.

First, as shown in FIG. 3, the method using the average channel matrix has a problem in that the average value becomes 0 according to the change pattern of the channel coefficient. 5 and 6 illustrate a change of channel coefficient magnitudes corresponding to the first OFDM symbol in an arbitrary subframe. In particular, FIG. 5 shows the change of the channel coefficient h ₀₁ in the frequency domain, and FIG. 6 shows the change of the channel coefficient h ₁₀ in the frequency domain.

5 and 6 divide the channel coefficient into real and imaginary parts and analyze the change in the magnitude on the frequency axis. Looking at the channel coefficient of the real part, it can be seen that it has a mean value close to zero while changing to a form similar to a sine wave. Although this phenomenon does not occur in all OFDM symbols, when this phenomenon occurs, the average channel matrix usage method generates CQI information that does not properly reflect the actual channel state.

As shown in FIG. 4, the above-described problem can be prevented by applying the method using the SNR after detecting the average MMSE of each reference symbol as the channel representative value. However, the actual number of reference symbols used in the MIMO-OFDM system may be larger than 48 considered in the present invention, and the process of calculating and averaging the SNR after detecting the MMSE corresponding to each reference symbol requires a large amount of computation. do. Therefore, the method of using SNR after detecting the average MMSE of each reference symbol as the channel representative value has a problem of high computational complexity.

The present invention proposes a method and apparatus for determining a channel representative value that can reflect a multipath fading channel state while solving the above problems of the prior art. In particular, the present invention proposes a channel representative value that is calculated through a simple operation and improves the throughput performance of the MIMO-OFDM system.

In particular, the present invention proposes a method and apparatus for generating CQI information that can reflect the state of various channel matrices that change in both frequency and time domains due to the characteristics of multipath fading channels and OFDM modulation. In particular, the present invention proposes an excellent method and apparatus in terms of throughput performance and computational complexity of a MIMO-OFDM system.

In general, a channel representative value is determined by averaging the channel matrix corresponding to the reference signal or averaging the SNR value after detecting the MMSE. 9 to 15 show the frame error rate (FER) and the throughput performance of the two methods in the simulation environment as shown in Table 2. When the target error rate was set to 1% FER and the CQI table was adjusted accordingly, it was confirmed that the average SNR utilization method showed excellent throughput performance in various channel environments, especially vehicular channels. However, the average SNR usage method requires a large amount of computation in the averaging process.

The present invention can reduce the amount of computation and exhibit almost the same throughput performance as the average SNR usage. In the present invention, the channel matrix is averaged. However, the channel matrix is averaged after performing a Hermitian operation without using each channel matrix as it is. Equation 16 shows a process of averaging the channel matrix after the Hermitian operation.

Where (.) ^H is a Hermitian operator, H _ref (k) represents the channel matrix corresponding to the k th reference symbol, and N _ref represents the number of reference symbols. When the result matrix calculated as in Equation 16 is an average squared matrix, the channel representative value using this value is represented by Equation 17 below.

In Equation 17, M _ch represents a channel representative value, and H ^* _avg represents an average square matrix.

Equations 17 and 18 are performed by a feedback information generator in the block diagram of FIG. 1. The feedback information generator generates an average square matrix as shown in Equation 16 using the channel matrix estimated from the channel estimator as an input value, and generates a channel representative value of Equation 17 using the channel matrix estimated as an input value. Here, referring to Equations 10 and 11, the SNR calculation process after the detection of the linear receiver uses the H ^H H value. Therefore, in the process of calculating the SNR value after detection of the linear receiver, the present invention passes the mean square matrix H ^* _avg directly to the input.

The present invention does not average the channel matrix as it is, but similar to MRC (Maximum Ratio Combining) combining the channel coefficients in the state (phase) in the phase (average) is a method of averaging the power of the channel coefficients. Therefore, the problem of the method using the average channel matrix can be solved, and the computational complexity is low because the Hermitian operation is performed but the SNR value is not calculated after detection of all reference signals.

7 is a flowchart illustrating a method of using an average squared channel matrix according to an embodiment of the present invention.

The terminal receives the signals in step 701 and estimates the channel matrix H _ref ^(k) using the reference signal among the signals received in step 703. Thereafter, the terminal ^multiplies (H _ref ^(k) ) ^H and (H _ref ^(k) ) as shown in Equation 16 in step 705. Thereafter, the terminal proceeds to step 707 to calculate H ^* _avg by averaging the value output in step 705. Thereafter, the UE calculates the SNR _MMSE (H ^* _avg ) by substituting H ^* _avg into Equation 11 in step 709, and proceeds to step 711 to calculate the SNR _MMSE (H ^* _avg ) calculated in step 709. Determine M _ch by applying Eq. 17>.

8 is a block diagram of a feedback information generator of a receiver according to an exemplary embodiment of the present invention. The receiver includes a hermitian calculator 128a, a channel matrix averaging processor 128b, an SNR calculator 128c, and a channel representative value determiner. It consists of 128d.

The Hermitian operation section (128b) is a when the channel estimated channel matrix (H _ref (k)) is received from the channel estimator 126 of FIG. 1, as shown in the <Equation 16>, Hermitian operation that is, (H _ref ^{( k)} ) ^H is multiplied by (H _ref ^(k) ) and output to the channel matrix averaging processor 128c. The channel matrix averaging processor 128c averages the value output from the hermithian calculator 128b, calculates H ^* _avg, and outputs the calculated H ^* _avg to the SNR calculator 128c.

The SNR calculator 128c calculates an SNR _MMSE (H ^* _avg ) by substituting the H ^* _avg into Equation 11 and outputs the SNR _MMSE (H ^* _avg ) to the channel representative value determiner 128d.

The channel representative value determiner (or channel indicator determiner) 128d determines M _ch by applying the following Equation 17 to the SNR _MMSE (H ^* _avg ).

The mean square channel matrix may be used to generate feedback information such as rank indicators (RIs) and precoding matrix indicators (PMIs) as defined in the LTE standard, as well as CQI information. As the Hermitian operation is performed, the averaged result matrix H ^* _avg has the average of the values produced by the square or product of the original channel matrix components. Assuming that the components of the result matrix are values of the power region, it is necessary to convert them to values of the amplitude region to generate RI information and PMI information. Therefore, using Equation 18, H ^* _avg is decomposed into a matrix expressed as a value in the size domain.

의 계수(rank)를 계산하여, 계수 값이 1인 경우에는 송신 다이버시티 모드로 (2 이상인 경우에는 공간다중화 모드로) MIMO 시스템이 동작하도록 피드백 RI정보의 생성이 가능하다. 또한, 행렬

에 기반하여 채널 용량 최대화, 최소 SNR 최대화 등의 다양한 프리코딩 행렬 선택기준<참조문헌 D. J. Love, and R. W. Heath, Jr., “Limited Feedback Unitary Precoding for Spatial Multiplexing Systems,” IEEE Trans. Inform Theo., vol. 51, no. 8. pp. 2967-2976, Aug. 2005.>을 적용하여 프리코딩 행렬을 선택할 수 있다. LTE 표준에서는 송수신기에 미리 정의된 코드북(codebook)에서 현재 채널상태에 적합한 프리코딩 행렬을 선택하고, 결정된 프리코딩 행렬의 코드북 인덱스 번호를 PMI 정보로 피드백한다.Equation 18 may be performed by decomposing H ^* _avg into an Eigen transform. The present invention can generate feedback information such as RI and PMI using a matrix expressed as in Equation 18. For example, the matrix

When the coefficient value is 1, the feedback RI information may be generated to operate the MIMO system in the transmit diversity mode (or the spatial multiplexing mode in the case of 2 or more). Also, the matrix

Based on various criteria of precoding matrix selection, such as maximizing channel capacity and maximizing minimum SNR, see DJ Love, and RW Heath, Jr., “Limited Feedback Unitary Precoding for Spatial Multiplexing Systems,” IEEE Trans. Inform Theo., Vol. 51, no. 8. pp. 2967-2976, Aug. 2005.> can be applied to select a precoding matrix. In the LTE standard, a precoding matrix suitable for a current channel state is selected from a predefined codebook in a transceiver, and the codebook index number of the determined precoding matrix is fed back as PMI information.

In the following Table 3, the fading profile consists of pedestrian A (PA) and vehicular A (VA). The fading profile has a relative power value corresponding to the tap delay time for each of the pedestrian A (PA) and the vehicular A (VA).

9 to 14 show the performance of the MIMO-OFDM MMSE system according to the channel representative value determination method when the Doppler frequencies are 20 Hz, 60 Hz, and 110 Hz in the multipath fading channel.

In FIG. 9, the fading profile is pedestrian A (PA), and in FIGS. 10 and 11 is vehicular A (VA). In the PA channel of FIG. 9, since almost no change in the channel matrix occurs in the subframe, the throughput performance of the three determination methods is the same. However, in the VA channels of FIGS. 10 and 11, since the channel change is large in the subframe, the throughput performance varies according to the channel representative value determination method. The method using the average channel matrix shows the throughput performance deteriorated by the same phenomenon as those of FIGS. 5 and 6. The method using the average SNR and the method using the mean square channel matrix exhibit almost the same throughput performance. However, since the method proposed in the present invention requires less calculation amount than the average SNR method, it can be easily applied to the actual MIMO-OFDM system.

FIG. 15 shows the performance of a closed loop MIMO-OFDM MMSE system to which a hybrid automatic repeat request (HARQ) protocol is applied when the Doppler frequency is 110 Hz in a multipath fading channel (VA). Referring to FIG. 15, it can be seen that even in a system to which HARQ technology is applied, transmission performance of the average square channel matrix method and the average SNR method is superior to the average channel matrix method.

Claims (8)

In the channel indicator determination method in a mobile communication system,
Performing a hermisian operation on the channel estimated channel matrix;
Calculating a mean square matrix by averaging the channel value of the Hermithian operation;
Calculating an SNR based on the channel matrix averaging value; And
And determining a channel indicator based on the SNR.
The method of claim 1,
The mean square matrix is calculated as in the following equation.
&Lt; Equation &

Where (.) ^H is a Hermitian operator, H _ref ^(k) represents the channel matrix corresponding to the kth reference symbol, and N _ref represents the number of reference symbols.
The method of claim 1,
The SNR is calculated as in the following equation.
&Lt; Equation &

E _s is the average energy of the transmitting symbol.
The method of claim 1,
Wherein the channel indicator is calculated as in the following equation.
&Lt; Equation &

Where M _ch represents the channel indicator and H ^* _avg represents the mean square matrix.
In the channel indicator determination apparatus in a mobile communication system,
A hermithian operation unit for performing a hermithian operation on the channel estimate channel matrix and outputting the hermian operation;
A channel matrix averaging processor configured to calculate an average square matrix by averaging the channel output value of the hermithian calculator;
An SNR calculator configured to calculate an SNR based on an output value of the channel matrix averaging processor; And
And a channel indicator determiner for determining a channel state indicator based on the SNR.
The method of claim 5,
And the average square matrix is calculated as in the following equation.
&Lt; Equation &

Where (.) ^H is a Hermitian operator, H _ref ^(k) represents the channel matrix corresponding to the kth reference symbol, and N _ref represents the number of reference symbols.
The method of claim 5,
And the SNR is calculated as in the following equation.
&Lt; Equation &

E _s is the average energy of the transmitting symbol.
The method of claim 5,
And the channel indicator is calculated as in the following equation.
&Lt; Equation &

Where M _ch represents the channel indicator and H ^* _avg represents the mean square matrix.

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