O. Edfors, M. Sandell, J.-J. van de Beek, S. K. Wilson, and P. O. B orjesson, "OFDM channel estimation by singular value decomposition, " IEEE Trans. Commun., vol. 46, no. 7, pp. 931--939, July 1998.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....0 p[n,0] H[n,0] h 0 [n] DFT Figure 2: Block diagram of the channel estimator. 3. WIENER FILTERS FOR CHANNEL ESTIMATION Fig. 2 shows the structure of the proposed MMSE channel estimator. We note that related discussions of finite length MMSE channel estimation were previously provided in [2, 3]. The estimator first multiplies the x[n,k] received at the pilot locations by the pilot values. Using (1) we have H[n,k] # x[n,k] p[n,k] H[n,k] z[n, k] n,k) P, 0 , elsewhere, with z[n, k] z[n, k]p[n,k] In what follows, we assume P L to avoid aliasing. A scaled IDFT of ....

O. Edfors, M. Sandell, J.-J. van de Beek, S. K. Wilson, and P. O. Brjesson, "OFDM channel estimation by singular value decomposition," IEEE Trans. Comm., vol. 46, pp. 931--939, July 1998.

....of the proposed techniques. 1. INTRODUCTION Orthogonal frequency division multiplexing (OFDM) is an attractive modulation technique for high data rate wireless communications [1] A crucial issue in achieving high quality of service in wireless communications is reliable channel estimation [2, 3]. Beyond that, it was recently recognized that channel prediction is useful for various tasks like delay free equalization, adaptive modulation, and power control [4 6] Here, we propose two adaptive, decision directed predictors for time varying channels within a coded OFDM system. The adaptive ....

O. Edfors, M. Sandell, J.-J. van de Beek, S. K. Wilson, and P. O. Brjesson, "OFDM channel estimation by singular value decomposition," IEEE Trans. Comm., vol. 46, pp. 931--939, July 1998.

....which the channel can be assumed to be invariant during one transmitted frame, is to use known OFDM pilot symbols prior to transmission. In this framework, Least Squares (LS) and Minimum Mean Square Error (MMSE) channel estimators for OFDM systems have been presented in the single antenna case in [1]. The LS method has then been extended to the multi antenna case (transmit diversity) by Li et al. [2] Pilot design for multiple transmit antenna systems is in itself an open issue, and the number and the form of the pilots have been discussed in several papers. Whereas [3] aims at reusing the ....

O. Edfors, M. Sandell, J. van de Beek, S. Wilson, and P. Borjesson. OFDM Channel Estimation by Singular Value Decomposition. IEEE Trans. on Communications, 46:931--939, July 1998.

....(9) we are neglecting the correlation of noise and interference, as well as their correlation with the zero derivative parameters. We observe that in this case the ML channel estimator is limited to the static part of the channel and reduced complexity estimators are available in literature [8, 9], this allows a trade off between complexity and performance. In particular by substituting the product diag s # diag s with its averaged value, the matrix inversion can be computed off line. After has been estimated, its contribution is deleted from the received signal, i.e. assuming ....

O. Edfors, M. Sandell, J.-J. van den Beek, S. K. Wilson, P. O. Borjesson, "OFDM channel estimation by singular value decomposition," IEEE Trans. on Commun., vol. 46, no. 7, pp. 931--939, July 1998.

.... The estimation of the channel for this block type pilot arrangement can be based on Least Square (LS) or Minimum Mean Square (MMSE) The MMSE estimate has been shown to give 10 15 dB gain in signal to noise ratio (SNR) for the same mean square error of channel estimation over LS estimate [2] In [3], a low rank approximation is applied to linear MMSE by using the frequency correlation of the channel to eliminate the major drawback of MMSE, which is complexity. The later, the comb type pilot channel estimation, has been introduced to satisfy the need for equalizing when the channel changes ....

....channel estimation symbols are transmitted periodically, in which all sub carriers are used as pilots. If the channel is constant during the block, there will be no channel estimation error since the pilots are sent at all carriers. The estimation can be performed by using either LS or MMSE [2] [3]. If inter symbol interference is eliminated by the guard interval, we write equation 7 in matrix notation 3 Frequency Carriers Frequency Carriers Time Time BLOCK TYPE PILOT ARRANGEMENT COMB TYPE PILOT ARRANGEMENT Fig. 2. Pilot Arrangement Y = XFh W (9) X = diag X(0) X(1) ....

[Article contains additional citation context not shown here]

O. Edfors, M. Sandell, J.-J. van de Beek, S.K. Wilson, and P.O. Brjesson. OFDM channel estimation by singular value decomposition. IEEE Transactions on Communications, vol. 46, no. 7, pp. 931-939, July 1998.

.... The estimation of the channel for this block type pilot arrangement can be based on Least Square (LS) or Minimum Mean Square (MMSE) The MMSE estimate has been shown to give 10 15 dB gain in signal to noise ratio (SNR) for the same mean square error of channel estimation over LS estimate [2] In [3], a lowrank approximation is applied to linear MMSE by using the frequency correlation of the channel to eliminate the major drawback of MMSE, which is complexity. The second, the combtype pilot channel estimation, has been introduced to satisfy the Sinem Coleri and Mustafa Ergen are Ph.D. ....

.... block. III. CHANNEL ESTIMATION BASED ON BLOCK TYPE PILOT ARRANGEMENT In block type pilot based channel estimation, OFDM channel estimation symbols are transmitted periodically, in which all sub carriers are used as pilots. The estimation can be performed by using either LS or MMSE [2] [3]. If the time domain channel vector h is Gaussian and uncorrelated with the channel noise W , the frequency domain MMSE estimate of h is given by [3] HMMSE = FRhY R 1 Y Y Y (2) where R hY and R Y Y are the cross covariance matrix between h and Y and the auto covariance matrix of Y ....

[Article contains additional citation context not shown here]

O. Edfors, M. Sandell, J.-J. van de Beek, S.K. Wilson, and P.O. Brjesson, OFDM channel estimation by singular value decomposition, IEEE Transactions on Communications, vol. 46, no. 7, pp. 931-939, July 1998.

....best performance, they require an accurate estimate of the channel frequency response. With this regard, it is known that good results are obtained by using an estimation algorithm based on the singular value decomposition (SVD) of the autocorrelation matrix of the channel frequency response, [1]. Based on this method a robust estimator was derived [2] However, as the number of tones of the MC system increases and the channel is more dispersive, both methods can become computationally expensive. We present two reduced complexity channel estimation methods for MC systems. The first one ....

....corresponding OFDM demodulated sample is y k [m] Here we consider estimation techniques which use only one OFDM symbol. To simplify the notation, the time index k is omitted. We assume that g is time invariant, at least for the duration of one OFDM symbol. Its M size FFT is G = G[0]# G[1]#: # G[M ; 1] 1) The input output relation turns out to be Y [m] G[m]a[m] W [m] m =0# 1#: #M; 1, where W [m] is additive white Gaussian noise (AWGN) with an average signal to noise ratio (SNR) From the received signal, Y , the LS estimate of the channel frequency response can ....

[Article contains additional citation context not shown here]

O. Edfors, M. Sandell, J. van de Beek, S. K. Wilson and P.O. Borjesson, "OFDM channel estimation by singular value decomposition, " IEEE Trans. on Commun., vol. 46, no. 7, pp. 931--939, July 1998.

.... The autocorrelation function is given by the DFT of the power delay profile ( denotes expectation with respect to , denotes the random variable corresponding to ) 1 (2) Given a particular communication environment, the values of , and can be quantified and introduced in (2) see, e.g. [22] and [23] Here, we focus on the discussion of coded modulation applied to noncoherent OFDM transmission in general. Consequently, the relation of the transmission parameters is specified rather than their actual quantities. In particular, we assume the channel length to be significantly shorter ....

O. Edfors, M. Sandell, J.-J. van de Beek, S. J. Wilson, and P. O. Brjesson, "OFDM channel estimation by singular value decomposition," IEEE Trans. Commun., vol. 46, pp. 931--939, July 1998.

.... with respect to , G[k f ] denotes the random variable corresponding to g[k f ] 1 EG fG[k f k f ]G [k f ]g = p X =0 2 h[ e j 2 D k f : 2) Given a particular communication environment, the values of p, D, and 2 h[ can be quanti ed and introduced in (2) cf. e.g. [22, 23]. Here, we focus on the discussion of coded modulation applied to noncoherent OFDM transmission in general. Consequently, the relation of the transmission parameters is speci ed rather than their actual quantities. In particular, we assume the channel length p to be signi cantly shorter than the ....

O. Edfors, M. Sandell, J.-J. van de Beek, S.J. Wilson, and P.O. Borjesson. OFDM Channel Estimation by Singular Value Decomposition. IEEE Trans. on Communications, 46(7):931{ 939, July 1998.

....improved properties regarding intersymbol interference (ISI) and interchannel interference (ICI) 5, 6] Here, we propose an OFDM BFDM receiver for random time varying channels that employs decision directed linear channel prediction. Regular transmission of pilot symbols for channel estimation [7, 8] is not required. This paper is organized as follows. Section 2 reviews coded OFDM BFDM communication over time varying channels. The structure of the novel receiver is described in Section 3. The design of the channel predictor is discussed in Sections 4 and 5. Finally, simulation results are ....

....(Although this is LMMSE optimum, we suppress the superscript opt for convenience. This matrix is time invariant ; it can again be precomputed using the multi channel Levinson algorithm. Note that, formally, 16) is (11) with A 1 n RzA H n replaced by E A 1 n RzA H n = I (cf. [8]) A simpli cation can be obtained by constraining the coe cient matrices Wm to have band structure, i.e. only correlations of neighboring subcarriers are exploited for prediction. DFT based predictor. For large dimension K, the Toeplitz matrices RH [m] involved in (16) are approximately ....

O. Edfors, M. Sandell, J.-J. van de Beek, S. Wilson, and P. Borjesson, \OFDM channel estimation by singular value decomposition," IEEE Trans. Comm., vol. 46, pp. 931-939, July 1998.

.... (50) where e l (i) e xl (i) je yl (i) is a complex Gaussian random variable with mean E[e l ] 0 and variance # 2 e l = 1 2 E[e l e # l ] The error term e l (i) is assumed to be independent of h l (i) This simple model is actually valid for most practical channel estimation schemes [33,34]. In the analysis of the average bit error probability that follows in this paper, we assume that # 2 e l is known for the model in equation (50) Starting from the condition that a Maximum Likelihood decoder will select the erroneous codeword C j over the correct codeword C 0 (equation (38) ....

O. Edfors, M. Sandell, J.-J. Beek, S. Wilson, and P. O. Borjesson, "OFDM channel estimation by singular value decomposition," in Proceedings of VTC'96, vol. 2, pp. 923--927, 1996.

....phase reference. In general, known pilot symbols need to be inserted periodically in the data stream to enable channel estimation needed for a coherent detector on a fading p 4 p 4 DECISION DIRECTED COHERENT DETECTION IN MULTICARRIER SYSTEMS SYSTEM AND CHANNEL MODELS 12 channel [8] [18], 71] These symbols increase both the bandwidth and the required signal to noise ratio for a given bit error probability. Here we propose to use previously made decisions instead of pilot symbols for DQPSK. Thus we derive a decision directed coherent detector that can be used in both ....

O. Edfors, M. Sandell, J.-J. van de Beek, S. K. Wilson, and P. O. Börjesson, "OFDM channel estimation by singular value decomposition," in Proceedings IEEE Vehicular Technology Conference, Atlanta, USA, April 28-May 1, 1996, pp. 923-927. 71

....complexity, separation of the use of time and frequency correlation has been proposed in [3] This combined scheme uses two separate FIR Wiener filters, one in the frequency direction and the other in the time direction. In this paper we present and analyse a class of charmel estimators for OFDM [4], where only the frequency correlation of the channel is used in the estimation. Whatever their level of performance, they may be improved with the addition of a second filter using the time correlation [3, 5] Though a linear minimum mean squared error (LMMSE) estimator using only frequency ....

....for OFDM systems before [6, 7, 8] The work presented in this paper was inspired by the observations in [8] where it is shown that DFT based low rank channel estimators have limited performance for non sample spaced channels and high SNRs. A more complete description of this work can be found in [4]. After presenting the OFDM system model and our scenario in Section 2, we introduce the estimators and their mean squared error (MSE) performance in Section 3. We show that the main limitation on the achieved complexity reduction is an irreducible MSE floor inherent in low rank approximations of ....

[Article contains additional citation context not shown here]

Ove Edfors, Magnus Sandell, Jan-Jaap v.d. Beek, Sarah Kate Wilson, and Per-Ola B6rjesson. OFDM channel estimation by singular value decomposition. In Proceedings of IEEE VTC'96, Atlanta, GA, April 1996. To appear.

....channel, but also corrects for a part of the time offset. The performance of the proposed synchronization scheme is thus evaluated in a system with channel estimation and equalization. We use a generically designed pilot based Mimimum Mean Square Error (MMSE) channel estimator addressed in [13]. D. Control Channel Since all users must arrive at the base station with a cer tain synchrony in order to maintain orthogonality between the subcarriers, all users adapt to the base station receiver clock and oscillator. For this reason the base station enter rains a control channel on the ....

O. Edfors, M. Sandell, J.-J. van de Beek, S. K. Wilson, and P.-O. B6:iesson, "OFDM channel estimation by singular value decomposition," IEEE Trans. Commun., 1997. Accepted for publication.

....complexity, separation of the use of time and frequency correlation has been proposed in [3] This combined scheme uses two separate FIR Wiener filters, one in the frequency direction and the other in the time direction. In this paper we present and analyse a class of charmel estimators for OFDM [4], where only the frequency correlation of the channel is used in the estimation. Whatever their level of performance, they may be improved with the addition of a second filter using the time correlation [3, 5] Though a linear minimum mean squared error (LMMSE) estimator using only frequency ....

....for OFDM systems before [6, 7, 8] The work presented in this paper was inspired by the observations in [8] where it is shown that DFT based low rank channel estimators have limited performance for non sample spaced channels and high SNRs. A more complete description of this work can be found in [4]. After presenting the OFDM system model and our scenario in Section 2, we introduce the estimators and their mean squared error (MSE) performance in Section 3. We show that the main limitation on the achieved complexity reduction is an irreducible MSE floor inherent in low rank approximations of ....

[Article contains additional citation context not shown here]

Ove Edfors, Magnus Sandell, Jan-Jaap v.d. Beek, Sarah Kate Wilson, and Per-Ola B6rjesson. OFDM channel estimation by singular value decomposition. In Proceedings of IEEE VTC'96, Atlanta, GA, April 1996. To appear.

....phase shift keying (QPSK) system modulates the data symbols differentially across the subcarriers. Therefore, 21 information symbols are transmitted in each OFDM symbol in a transmission block. Secondly, a coherent QPSK system is simulated, in which the base station uses a channel estimator [23], 24] and a channel equalizer to correct for the multiplicative channel distortion of the data symbols. The pilot positions for channel estimation are shown in Fig. 2. Each OFDM symbol in a transmission block contains 22 QPSK symbols, four of which are known pilot symbols. This modulation system ....

....pilot data. Since we do not know these channel correlations, we design generic matrices based on the following correlation properties: the assumed channel delay spread is exponentially decaying with an RMS value of ten samples. The channel correlation matrices for this channel are given in [23]. The correlation matrix is designed for an assumed SNR of 20 dB (see [23] B. Channel Model We have evaluated the synchronization scheme in one of the channel environments defined by ETSI for the evaluation of UMTS radio interface proposals. The time varying channel impulse response for these ....

[Article contains additional citation context not shown here]

O. Edfors, M. Sandell, J. J. van de Beek, S. K. Wilson, and P. O. B orjesson, "OFDM channel estimation by singular value decomposition, " IEEE Trans. Commun., vol. 46, pp. 931--939, July 1998.

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O. Edfors, M. Sandell, J.-J. van de Beek, S. K. Wilson, and P. O. B orjesson, "OFDM channel estimation by singular value decomposition, " IEEE Trans. Commun., vol. 46, no. 7, pp. 931--939, July 1998.

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O. Edfors, M. Sandell, J.-J. van de Beek, S. K. Wilson, and P. O. Borjesson, "OFDM channel estimation by singular value decomposition, " IEEE Trans. Commun., vol. 46, no. 7, pp. 931--939, July 1998.

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O. Edfors, M. Sandell, J.-J. van de Beek, S. K. Wilson, and P. O. Brjesson, "OFDM channel estimation by singular value decomposition," in Proc. IEEE Veh. Technol. Conf. (VTC), vol. 2, 1996, pp. 923--927.

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O. Edfors, M. Sandell, J.-J. van de Beek, S. K. Wilson, and P. O. B orjesson, "OFDM channel estimation by singular value decompostion, " IEEE Trans. on Comm., vol. 46, pp. 931-940, July 1998.

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O. Edfors, M. Sandell, J.-J.van de Beek, S. K. Wilson, and P. O. Bojesson, "OFDM channel estimation by singular value decomposition, " IEEE Trans. Commun., vol.46, pp.931-939, Jul. 1998.

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O.Edfors, M.Sandell, J.J. van de Beek, S.K.Wilson, and P.O.Borjesson, "OFDM channel estimation by singular value decomposition," IEEE Trans. Commun., vol.46, No 6, pp.931-939, July 1998. 125

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O. Edfors, M. Sandell, J.-J.van de Beek, S. K. Wilson, and P. O. Bojesson, "OFDM channel estimation by singular value decomposition, " IEEE Trans. Commun., vol.46, pp.931-939, Jul. 1998.

No context found.

O. Edfors, M. Sandell, J.-J.van de Beek, S. K. Wilson, and P. O. Bojesson, "OFDM channel estimation by singular value decomposition," IEEE Trans. Commun., vol.46, pp.931-939, Jul. 1998.

No context found.

O. Edfors, M. Sandell, J. J. van de Beek, S. K. Wilson, and P. O. Borjesson, "OFDM channel estimation by singular value decomposition," IEEE Trans. Commun., vol. 46, pp. 931--939, July 1998.

No context found.

O. Edfors, M. Sandell, J. J. van de Beek, S. K. Wilson, and P. O. Borjesson, "OFDM channel estimation by singular value decomposition," Proc. VTC 1996, pp. 923-927.

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