KR101581727B1 - A method for estimating a transmited signal in a wireless communications system - Google Patents

Abstract

A method for estimating a transmission signal in a wireless communication system includes receiving a plurality of received signal sequences having a plurality of subcarriers transmitted over a transmission channel and filtering the interference between the plurality of subcarriers from the received signal sequence Wherein the transmission channel is a product of an average channel matrix and a transformation matrix, and the output of the reception filter is a product of an approximate average channel matrix and a received signal sequence, It is possible to effectively reduce the ICI even when the number of subcarriers is large and the moving speed of the mobile station is high, by filtering the plurality of received signal sequences transmitted through the mobile station to have the time invariant channel characteristics.

Description

[0001] The present invention relates to a method for estimating a transmission signal in a wireless communication system,

The present invention relates to a method and apparatus for estimating a transmission signal in a wireless communication system. More particularly, the present invention relates to a method and apparatus for efficiently estimating a transmission signal by eliminating Inter Carrier Interference (ICI) in a wireless communication system using Orthogonal Frequency Division Multiplexing (OFDM) .

In a wireless communication or digital broadcasting system based on an OFDM scheme, inter-symbol interference (ISI) due to multipath of a wireless fading channel is canceled by orthogonality between a plurality of sub-carriers. However, the time-variant characteristic of the radio channels causes a loss of subcarrier orthogonality, which causes Inter Carrier Interference (ICI) and deteriorates data detection performance. There are ZF (zero forcing) and MMSE (Minimum Mean Square Error) in the time domain because of the computational complexity of O (N ² ), but the number of subcarriers is It is limited to 128.

The frequency domain algorithm can reduce the computational complexity to O (N) by ignoring relatively small ICI coefficients, but it is effective when the normalized Doppler frequency (NDF) is sufficiently small. However, when NDF is larger than 0.1, performance degradation occurs due to the computational complexity of O (N ² ). The iterative method for solving this problem has a computational complexity of O (N) for large NDFs, but only for systems with a small number of subcarriers. When the number of subcarriers is 500 or more, the iterative method can not effectively reduce the ICI.

In this regard, Korean Patent No. 10-0809017, entitled " Method for canceling interference between subcarriers and receiving apparatus using the same, " discloses a technique in which when a time-varying spurious matrix component is removed in a time domain, And the interference vector between the subcarriers is removed after performing the parallel interference cancellation process using the estimated vector.

Korean Patent No. 10-0809017, "Method for canceling interference between subcarriers and receiving apparatus using the method"

It is an object of the present invention to effectively reduce the ICI even when the number of subcarriers is large and the moving speed of the terminal is high.

It is another object of the present invention to effectively reduce the ICI for a terminal moving at a high speed in a communication system such as OFDM with a large number of subcarriers and to effectively estimate a transmission signal from a reception signal.

According to an aspect of the present invention, there is provided a method of estimating a transmission signal in a wireless communication system, the method including: receiving a plurality of received signal sequences having a plurality of subcarriers transmitted through a transmission channel; And filtering the interference between the plurality of subcarriers from the received signal sequence through a receive filter. Here, the transmission channel is formed by a product of an average channel matrix and a transform matrix, and an output of the receive filter is formed by a product of an approximate average channel matrix and the received signal sequence.

Wherein the filtering comprises updating the filter coefficients in a time period of k / N times the input period of the number of N transmit signal sequences.

The approximate average channel matrix is transformed into the average channel matrix by the updated filter coefficient.

The average channel matrix is a time-invariant channel matrix, and the transformation matrix converts the time-invariant channel into a time-varying channel.

The method of estimating the transmission signal further includes Fourier transforming the filtered reception signal sequence and estimating a channel equalized transmission signal from the Fourier-transformed reception signal sequence.

The transmission signal estimating step primarily combines the reception signal at the current time and the reception signal at the time immediately before the current time.

According to an aspect of the present invention, there is provided an apparatus for estimating a transmission signal in a wireless communication system, the apparatus including: a receiver for receiving a plurality of received signal sequences having a plurality of subcarriers transmitted through a transmission channel; And filtering the interference between the plurality of subcarriers from the received signal sequence received from the receiver. Here, the transmission channel is formed by a product of an average channel matrix and a transform matrix, and an output of the receive filter is formed by a product of an approximate average channel matrix and the received signal sequence.

According to an aspect of the present invention, there is provided an apparatus for estimating a transmission signal in a wireless communication system, the apparatus comprising: receiving means for receiving a plurality of received signal sequences having a plurality of subcarriers transmitted through a transmission channel; And filtering the interference between the plurality of subcarriers from the received signal sequence received from the receiving means. Here, the transmission channel is formed by a product of an average channel matrix and a transform matrix, and an output of the receive filter is formed by a product of an approximate average channel matrix and the received signal sequence.

According to another aspect of the present invention, there is provided a method of estimating a transmission signal in a wireless communication system, the method comprising: receiving a plurality of received signal sequences transmitted through a transmission channel having a time- Filtering through a receive filter; And estimating a transmitted signal sequence using the filtered received signal sequence.

According to another aspect of the present invention, there is provided an apparatus for estimating a transmission signal in a wireless communication system, the apparatus comprising: a receiver for receiving a plurality of subcarrier interference signals from a plurality of received signal sequences transmitted through a transmission channel having a time- A receiving filter for filtering; And a transmission signal estimator estimating a transmission signal sequence using the filtered reception signal sequence from the reception filter.

According to another aspect of the present invention, there is provided an apparatus for estimating a transmission signal in a wireless communication system, the apparatus comprising: a receiver for receiving a plurality of subcarrier interference signals from a plurality of received signal sequences transmitted through a transmission channel having a time- Receiving filtering means for filtering; And transmission signal estimation means for estimating a transmission signal sequence using the filtered reception signal sequence from the reception filtering means.

According to the present invention, by filtering a plurality of received signal sequences transmitted through a transmission channel having time-varying channel characteristics to have time-invariant channel characteristics, ICI can be effectively reduced even when the number of sub- .

According to the present invention, by filtering a plurality of received signal sequences transmitted through a transmission channel having a time-varying channel characteristic to have time-invariant channel characteristics, a terminal moving at high speed in a communication system such as OFDM having a large number of sub- The transmission signal can be effectively estimated from the reception signal.

1 shows a communication system model according to the present invention for estimating a transmission signal from a received signal.
2 is a flowchart of a method for estimating a transmission signal from a received signal using the communication system model of FIG.
FIG. 3 shows the bit error rate (BER) according to the update rate for various NDFs.
FIG. 4 shows a bit error rate (BER) according to bandwidth W for various NDFs.
FIG. 5 shows the normalized Frobenius matrix size < RTI ID = 0.0 > E < / RTI & _F / N.
Figures 6 and 7 show the BER performance corresponding to the signal-to-noise ratio (SNR) for QPSK and 16-QAM, respectively, when NDF = 0.05
Figures 8 and 9 show the BER performance corresponding to the signal-to-noise ratio (SNR) for QPSK and 16-QAM, respectively, when NDF = 0.2.
Figure 10 shows BER performance when channel estimation is incomplete.
11 shows BER performance according to the number of subcarriers when SNR = 30 dB.

Hereinafter, a method and apparatus for estimating a transmission signal in a wireless communication system will be described in detail with reference to the accompanying drawings.

1 shows a communication system model according to the present invention for estimating a transmission signal from a received signal. The communication system model 100 includes a transmission channel 110 and a reception apparatus 120. [ The receiver 120 includes a receive filter 130 and a Fourier transformer 140 and a channel equalizer 150.

A plurality of transmission signal sequences 101 are transmitted to the reception apparatus 120 through the transmission channel 110. That is, the reception apparatus 120 receives a plurality of reception signal sequences 111 having a plurality of subcarriers through the transmission channel 110. The transmission channel 110 is modeled with a time-variant or time-invariant channel characteristic according to a radio propagation environment. The receive filter 130 filters the interference between the plurality of subcarriers from the received signal sequence 111. More specifically, the reception filter 130 filters the plurality of reception sequences 111 transmitted through the transmission channel 110 having time-varying channel characteristics to have time-invariant channel characteristics. Here, the channel matrix H _tv of the transmission channel is a product of an average channel matrix H _ave and a transformation matrix F, and the output 131 of the reception filter includes an approximate average channel matrix G, And a product of the received signal sequence 111.

The Fourier transformer 140 performs Fourier transform on the filtered received signal sequence 131 to obtain a frequency domain signal 141 from the time domain signal 131. The channel equalizer 150 estimates a channel equalized transmission signal 151 from the Fourier-transformed reception signal sequences 141. [ That is, the radio propagation channel requires channel equalization in order to recover these signals when the sum of the signals transmitted at different times by the multipath is reached. The channel equalizer 150 is t = t _n the current reception signal, and t = t _n-1, of at ..., t = t _nk by first binding the previous k of received signal at the current transmission signal . The equalizer 150 may use a 1-tap channel equalizer that primarily combines the received signal at the current time and the received signal at the time immediately before the current time.

2 is a flowchart of a method for estimating a transmission signal from a received signal using the communication system model 100 of FIG. The transmission signal estimation method includes a receiving sequence receiving step S210, a receiving sequence filtering step S220, a Fourier transforming step S230, and a channel equalizing step S240. In the receiving sequence receiving step S210, the receiving apparatus 120 receives the plurality of received signal sequences 111 having a plurality of subcarriers transmitted through the transmission channel 110 having a time-varying channel characteristic. In the reception sequence filtering step (S220), the interference between the plurality of subcarriers is filtered through the reception filter (130) from the plurality of reception signal sequences (111). By the filtering, the transmission channel 110 having a time-varying channel characteristic is filtered to have a time invariant channel characteristic. Wherein the transmission channel G is composed of a product of an average channel matrix H _ave and a transformation matrix F and the output 131 of the reception filter comprises an approximate average channel matrix G and a received signal sequence 111 ).

In the reception sequence filtering step (S220), the filter coefficient is updated in a time period of k / N times the input period of the N transmission signal sequences (101). The approximate average channel matrix G is transformed into the average channel matrix by the updated filter coefficient. Here, the average channel matrix is a time-invariant channel matrix, and the transformation matrix converts the time-invariant channel into a time-varying channel. This will be described in detail later using an OFDM system model.

In the Fourier transform step S230, the filtered received signal sequence 131 is Fourier transformed to obtain a frequency domain signal 141 from the time domain signal 131. [ In the channel equalization step S240, a channel equalized transmission signal 151 is estimated from the Fourier-transformed reception signal sequences 141. [

Meanwhile, according to an embodiment of the present invention, the communication system model 100 may be an OFDM system model using an N-point inverse discrete Fourier transform (IDFT) and a cyclic prefix (CP) . After removing the CP part, the reception sequence 111 is calculated by using the transmission signal sequence 101 and the transmission channel 110 according to the following equation (1) using the transmission signal sequence 101 and the transmission channel 110, assuming that the channel length L is shorter than the CP length: ). ≪ / RTI >

(1)

(One)

Where x, y, and n are column vectors for a transmitted signal sequence, a received signal sequence, and a noise sequence of length N, respectively, as shown in equations (2) (M), y (m), and n (m) with respect to N-1.

(2)

(2)

(3)

(3)

(4)

(4)

Here, the time-varying channel matrix impulse response is expressed by the following equation (5), where the channel impulse response is m = 0, 1, ..., N-1 and n = 0, 1, 1, h (m, n). Where N and L are the length of the data sequence and the length of the channel spread, respectively.

(5)

(5)

If the channel is time invariant, the channel matrix Htv has the form of a circular and band, but not in a time-varying channel situation. Linear equalization or linear filtering algorithms based on existing zero forcing (ZF) and MMSE schemes are very complex when implementing an OFDM system with a large number N of subcarriers. When the number N of subcarriers is large, the time-varying channel impulse response h (m, n) is represented by superposition of time-varying and time-invariant elements as shown in Equation (6) below.

(6)

(6)

Here, the time invariant element h _ave (n) can be obtained by averaging all channel impulse responses during a sequence frame, and is expressed as Equation (7) below.

(7)

(7)

The matrix representation of the time-varying channel model of Eq. (6) is expressed as Eq. (8) below.

(8)

(8)

The average channel matrix H _ave is a circular banded matrix, and the time-varying element H _var is _banded as H _ave . That is, each row or column of length N has L non-zero components. Using this channel model, the reception sequence 111 can be separated into a time invariant part and an ICI part as shown in equation (9) below.

(9)

(9)

Previous algorithms based on the time-domain signal model reduce the ICI by subtracting the time-varying elements of Eq. (9) from the received sequence using feedback information. The iterative algorithm estimates the input sequence x (n) using the average of the channel impulse responses in Eq. (7). The ICI sequence (H _var x) of equation (9) is then calculated and subtracted from the received sequence to obtain a sequence without ICI. This two step procedure is repeated. This method operates with complexity of O (N) per repetition when the number of subcarriers and the moving speed are small. However, since the large error of the feedback sequence can not be effectively restored by many iterations, performance degradation becomes more severe as the number of subcarriers increases.

The time-varying channel matrix proposed by the present invention is defined by the linear transformation of the time-invariant channel matrix as shown in equation (10).

(10)

(10)

If the channel is time invariant, the transform matrix F becomes a unit matrix of size N, and Htv = H _ave . From equation (10), it can be seen that the i-th row vector of Htv is the circular convolution of the i-th row vector of F and the temporal invariant channel impulse response when the mean channel matrix H _ave is a Toeplitz circle matrix, 11). ≪ / RTI >

(11)

(11)

For all i = 0, 1, ..., N-1, * denotes a circular convolution. Where h _tv and f ⁽ⁱ⁾ are the (i + 1) th row vectors of H _tv and F, h _ave is the first row vector of H _ave , and h _ave is expressed by the following equation (12) .

(12)

(12)

From Eq. (11), the components of matrix F are obtained by Eq. (13).

(13)

(13)

Here, H _{tv (i)} (k) and H _ave (k) denote h _tv (i) and H _ave DFT for k = 0, 1, ..., N-1.

When the equation (10) is substituted into the equation (1), the receiving sequence 111 is expressed by the following equation (14).

(14)

(14)

The ICI can be reduced by multiplying the inverse G by G · F = I _N , where I _N is the identity matrix of size N. The sequence without ICI obtained by the linear transformation of the reception sequence with matrix G is expressed by the following equation (15).

(15)

(15)

After removing the ICI components, the time invariant channel component can be removed in the frequency domain.

Since the calculation of the inverse matrix G using ZF and MMSE has no advantage over the inversion of H _tv , an approximated method is proposed for an actual implementation of an OFDM system with a large number of subcarriers. G · F = I _N and F · G = I _N , it can be expressed as the following equation (16).

(16)

(16)

F ⁽ⁱ⁾ is the (i + 1) -th column vector of the matrix F and g ⁽ⁱ⁾ is the (i + 1) th column vector of the matrix G, for all i, j = 0,1,2, ..., N- ) Th column vector. In the case of time invariant, each row of H _ave is a circular transposed version of each other. However, in the time-varying situation, equation (16) is expressed as equation (17) below using equation (6).

(17)

(17)

The row vector of H _tv is the sum of the time varying elements w _{i, j} (n) = h _var (j, n) -h _var (i, n) of the circularly shifted version of the other row and the relatively small value. Substituting equation (17) into equation (11), it can be expressed as the following equation (18).

(18)

(18)

Here, (n) N is the remainder (residue) of N modulo, f ⁽ⁱ⁾ (n) is the (n + 1) of f ⁽ⁱ⁾ th _element, d _{i, j (n)} is f ^(j) (n) is a time-varying element.

The transformation matrix is expressed by the sum of a circular matrix and a relatively small error matrix as shown in the following equation (19).

(19)

(19)

Where F _C ⁽ⁱ⁾ is defined by a circular matrix whose first row vector is f ⁽ⁱ⁾ , and the elements of the error matrix E ⁽ⁱ⁾ are e _{j, n} (n). Since ^{F · g (i) = F} c (i) · g (i) + E (i) · g (i) and ^{_{F c (i) · g (}} i) it exhibits a circular convolution, f ⁽ⁱ⁾ Can be expressed as an approximation of g ⁽ⁱ⁾ as shown in the following equation (20).

(20)

(20)

Here, F ⁽ⁱ⁾ (k) is discrete Fourier transform of f ⁽ⁱ⁾ with respect to k = 0,1,2, ..., N-1, It will be a diagonally dominant matrix rather than a unit matrix. When approximate inverse transform is applied to Eq. (15), it is expressed as Eq. (22).

(21)

(21)

(22)

(22)

(I + E) H _ave · x, and (I + E) H _ave is the approximate average channel matrix, where E = G · F -I _N , and adding the first and second term in Eq. . The proposed method can not completely eliminate ICI because E is small but is not a zero matrix, and the residual ICI component limits the performance of the proposed method. The method proposed in the present invention effectively suppresses the inter-carrier interference (ICI) by making the components of the matrix E have a small value in a short time by appropriately adjusting the filter coefficient update period in an environment in which the mobile station has a high moving speed with many sub- can do.

Here, complexity reduction schemes that can be effectively implemented without performance degradation are proposed. For OFDM systems with N = 2048 complexity reduction is performed based on computer simulation results. A tapered delay line (TDL) channel model with five multipaths is applied to the radio propagation channel, which is generated by the Jake channel model. The delays of each tap are, and the relative power of each is. The symbol length is, and the modulation method is Quadrature Phase Shift Keying (QPSK) and 16-QAM (Quadrature Amplitude Modulation) modulation. Assuming that the channel is known, the least squares method applies to 1-tap equalization.

The filter coefficients g ⁽ⁱ⁾ (n) must be estimated for all i = 0,1,2, ..., N-1, which is complex to implement. Thus, filter coefficients are calculated every D time interval, then linear interpolation is applied to obtain the residual filter coefficients. The update rate, defined as K = N / D, should be minimized to reduce computational complexity.

FIG. 3 shows the bit error rate (BER) according to the update rate for various NDFs. Even in the case of NDF 0.2 corresponding to the traveling speed of 260 km / h, it can be seen that if K = 8, the BER has a value of 10 ^-3 or less, so that the update time interval N / 8 is sufficient.

To reduce the computational complexity, the number of non-zero elements in G must be minimized. The matrix G is a diagonal dominant matrix and a banded matrix with a relatively small bandwidth. FIG. 4 shows a bit error rate (BER) according to bandwidth W for various NDFs. When N is smaller than 0.2, it can be seen that W = 128 or more in order to have a BER of 10 -3 or less.

Using the complexity reduction scheme described above, the proposed method operates with a complexity O (N). The iterative method requires two iterations, and each process includes two N-point fast Fourier transforms (FFTs) with complexity (N log2 (N)). The number of complex operations according to various N is shown in Table 1. The complexity of the proposed method is about twice the complexity of the iterative method.

N 128 256 512 1024 2048 Iterative method
(Iterative) 11,776 24,576 51,200 106,496 221,184 Suggested method
(Proposed) 26,624 53,248 106,496 212,992 425,984 Rate 2.3 2.2 2.1 2.0 1,9

Table 2 shows the system parameters for the data detection performance simulation of the proposed method.

Parameter Value FFT point (N) 2,048 Carrier Frequency (GHz) 1 GHz 심볼 길이 0.2μs Bandwidth of G (W) 128 Update rate (K) 8 Modulation method QPSK, 16-QAM NDF 0.05, 0.2

The sum of the non-diagonal components of the matrix GF determines the performance of the proposed method. FIG. 5 shows the normalized Frobenius matrix size < RTI ID = 0.0 > E < / RTI & _F / N. From FIG. 4, it can be seen that the proposed method is suitable when N is larger than 250, when the normalized size is less than -30 dB. Since the size of E is relatively large when N is small, the proposed method may not operate efficiently for an OFDM system with a small N. [

Figures 6 and 7 show the BER performance corresponding to the signal-to-noise ratio (SNR) for QPSK and 16-QAM, respectively, when NDF = 0.05. Where the channel impulse response is assumed to be known. From FIG. 6, it can be seen that when the NDF = 0.05 and QPSK is used, the BER is 0.08% when the ISI reduction is not used for the SNR = 35 dB, and that the proposed method reduces the BER to 0.03% . It can be seen from Fig. 7 that the BER of 0.22% of the iterative method is reduced to 0.15% by the proposed method when using 16-QAM. Figures 8 and 9 show the BER performance corresponding to the signal-to-noise ratio (SNR) for QPSK and 16-QAM, respectively, when NDF = 0.2. In this case, it can be seen that there is a performance improvement from 1.3% to 0.8% and 3.2% to 0.4% for QPSK and 16-QAM, respectively. Table 3 shows the bit error rate results for the iterative method and the proposed method.

Figure 10 shows BER performance when channel estimation is incomplete. The simulation parameters are the same as in Fig. 8, and the overall detection performance deteriorates as the mean squared error (MSE) of the channel estimation increases. It can be seen that the method proposed from FIG. 10 has better BER performance than the iterative method.

11 shows BER performance according to the number of subcarriers when SNR = 30 dB. It can be seen from FIG. 11 that the iterative method works effectively when the number of subcarriers is smaller than 300, but the performance deteriorates as the number of subcarriers increases. In the case of the repetition method, when the number of subcarriers is greater than about 500 It is more effective.

Further, embodiments of the present invention include a computer readable medium having program instructions for performing various computer implemented operations. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The media may be program instructions that are specially designed and constructed for the present invention or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like.

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments. Therefore, the scope of the present invention should not be limited to the described embodiments, but should be determined by the equivalents of the claims and the claims.

100: Communication system model
110: Transmission channel
120: Receiver
130: Receive filter
140: Fourier transformer
150: Channel equalizer

Claims (28)

A method for estimating a transmission signal in a wireless communication system,
Comprising: receiving a plurality of received signal sequences having a plurality of subcarriers transmitted on a transmission channel; And
And filtering the interference between the plurality of subcarriers from the received signal sequence through a receive filter,
Wherein the transmit channel is comprised of a product of an average channel matrix and a transform matrix and the output of the receive filter is a product of an approximate average channel matrix and the received signal sequence. The method according to claim 1,
Wherein the filtering comprises updating the filter coefficient with a time period of k / N times the input period of the number of N transmit signal sequences. 3. The method of claim 2,
Wherein the approximate average channel matrix is transformed to the mean channel matrix by the updated filter coefficient. The method according to claim 1,
Wherein the average channel matrix is a time-invariant channel matrix and the transform matrix transforms the time invariant channel into a time-varying channel. The method according to claim 1,
Performing a Fourier transform on the filtered received signal sequence; And
Further comprising estimating a channel equalized transmission signal from the Fourier transformed received signal sequence. The method according to claim 1,
Wherein the transmission signal estimation step primarily combines the reception signal at the current time and the reception signal at the time immediately before the current time. An apparatus for estimating a transmission signal in a wireless communication system,
A receiver for receiving a plurality of received signal sequences having a plurality of subcarriers transmitted through a transmission channel; And
And a reception filter for filtering the interference between the plurality of subcarriers from the received signal sequence received from the receiver,
Wherein the transmit channel is comprised of a product of an average channel matrix and a transform matrix and the output of the receive filter is a product of an approximate average channel matrix and the received signal sequence. 8. The method of claim 7,
Wherein the receive filter updates the filter coefficient with a time period of k / N times the input period of the number of N transmit signal sequences. 9. The method of claim 8,
Wherein the approximate average channel matrix is transformed into an average channel matrix by the updated filter coefficient. 8. The method of claim 7,
Wherein the mean channel matrix is a time invariant channel matrix and the transform matrix transforms the time invariant channel into a time varying channel. 8. The method of claim 7,
A Fourier transformer for Fourier transforming the filtered received signal sequence; And
And a channel equalizer for estimating a channel equalized transmission signal from the Fourier transformed received signal sequence. 12. The method of claim 11,
Wherein the channel equalizer is a 1-tap channel equalizer that primarily combines a reception signal at a current time and a reception signal at a time immediately before the current time, and estimates a transmission signal in the wireless communication system. A method for estimating a transmission signal in a wireless communication system,
Filtering interference between a plurality of subcarriers from a plurality of received signal sequences transmitted through a transmission channel having a time-varying channel characteristic through a reception filter; And
Estimating a transmitted signal sequence using the filtered received signal sequence,
Wherein the transmit channel is comprised of a product of an average channel matrix and a transform matrix and the output of the receive filter is a product of an approximate average channel matrix and the received signal sequence. delete 14. The method of claim 13,
Wherein the filtering comprises updating a filter coefficient with a time period of k / N times the input period of the number of N transmit signal sequences. 16. The method of claim 15,
Wherein the approximate average channel matrix is transformed to the mean channel matrix by the updated filter coefficient. 14. The method of claim 13,
Wherein the mean channel matrix is a time invariant channel matrix and the transform matrix transforms the time invariant channel into the time varying channel. 14. The method of claim 13,
Wherein the step of estimating the transmission signal comprises:
Fourier transforming the filtered received signal sequence;
And removing inter-symbol interference (ISI) between the Fourier-transformed received signal sequences. 19. The method of claim 18,
Wherein removing the intersymbol interference comprises combining the received signal at the current time and the received signal at a time just before the current time, in a wireless communication system. An apparatus for estimating a transmission signal in a wireless communication system,
A reception filter for filtering interference between a plurality of subcarriers from a plurality of received signal sequences transmitted through a transmission channel having a time-varying channel characteristic; And
And a transmission signal estimator estimating a transmission signal sequence using the filtered reception signal sequence from the reception filter,
Wherein the transmit channel is comprised of a product of an average channel matrix and a transform matrix and the output of the receive filter is a product of an approximate average channel matrix and the received signal sequence. delete 21. The method of claim 20,
Wherein the receive filter updates a filter coefficient in a time period of k / N times the input period of the number of N transmit signal sequences. 23. The method of claim 22,
Wherein the approximate average channel matrix is transformed into the mean channel matrix by the updated filter coefficient. 21. The method of claim 20,
Wherein the average channel matrix is a time-invariant channel matrix and the transform matrix transforms the time invariant channel into the time-varying channel. 21. The method of claim 20,
Wherein the transmission signal estimator comprises: a Fourier transformer for Fourier transforming the filtered received signal sequence; And
And a channel equalizer that removes inter symbol interference (ISI) between the Fourier transformed received signal sequences from the Fourier transformer. 26. The method of claim 25,
Wherein the channel equalizer is a 1-tap channel equalizer that primarily combines a reception signal at a current time and a reception signal at a time immediately before the current time, and estimates a transmission signal in the wireless communication system. An apparatus for estimating a transmission signal in a wireless communication system,
Receiving means for receiving a plurality of received signal sequences having a plurality of subcarriers transmitted through a transmission channel; And
And reception filtering means for filtering the interference between the plurality of subcarriers from the received signal sequence received by the reception means,
Wherein the transmit channel is comprised of a product of an average channel matrix and a transform matrix and the output of the receive filter is a product of an approximate average channel matrix and the received signal sequence. delete

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