Channel Estimation For OFDM Systems Research Articles

Ml joint CFO and channel estimation in OFDM systems with timing ambiguity

This letter addresses the problem of joint estimation of carrier frequency offset (CFO) and channel for OFDM systems in the presence of timing ambiguity. Based on two signal models for quasi-synchronized OFDM systems, two joint CFO and channel estimators are derived from the Maximum Likelihood (ML) criterion. The first estimator obtained is a joint estimator for all unknown parameters, which needs a multi-dimensional search. The second estimator has a reduced complexity, but its performance slightly degrades compared with the first one. Through MSE analyses, we find that when the number of subcarriers is large, the two estimators are equivalent.

A New DFT-Based Channel Estimation Approach for OFDM with Virtual Subcarriers by Leakage Estimation

Equidistance in pilot spacing is an essential condition for discrete Fourier transform (DFT)-based channel estimation in OFDM systems. However, virtual subcarriers break this condition, degrade the estimation performance, and cause the interference (called ''leakage') because the orthogonality of Fourier matrix is broken. To solve this problem, we first analyze the leakage using the DFT-inverse DFT process. The pilot subcarriers inside virtual subcarriers area are estimated by the inverse of the estimated leakage. Thus, the equidistance condition is satisfied. The proposed estimator operates well in realistic environment such as IEEE 802.16, and it is robust to an increase of virtual subcarriers.

Channel estimation for OFDM systems using radial basis function networks

Channel estimation for OFDM systems using radial basis function networks

EM-based low complexity channel estimation for OFDM system

The EM algorithm is a general method for ML channel estimation that arise in statistical estimation problems. However, this algorithm has two drawbacks which are slow convergence and large complexity. In order to reduce the complexity of the EM algorithm, we adapt quasi-Newton methods to the EM algorithm for channel estimation in frequency selective environments. The proposed methods and conventional EM algorithm are compared with each other in terms of complexity and the BER performance. The performance evaluations are based on the European digital television system DVB-H. Also, the outstanding performance of this proposed methods is shown and compared with other existing methods in DVB-H.

A novel simplified channel tracking method for MIMO–OFDM systems with null sub-carriers

This paper proposes an efficient scheme to track the time variant channel induced by multi-path Rayleigh fading in mobile wireless multiple input multiple output–orthogonal frequency division multiplexing (MIMO–OFDM) systems with null sub-carriers. In the proposed method, a blind channel response predictor is designed to cope with the time variant channel. The proposed channel tracking scheme consists of a frequency domain estimation approach that is coupled with a minimum mean square error (MMSE) time domain estimation method, and does not require any matrix inverse calculation during each OFDM symbol. The main attributes of the proposed scheme are its reduced computational complexity and good tracking performance of channel variations. The simulation results show that the proposed method exhibits superior performance than the conventional channel tracking method [Y.G. Li, N. Seshadri, S. Ariyavisitakul, Channel estimation for OFDM systems with transmitter diversity in mobile wireless channels, IEEE J. Sel. Areas Commun. 17 (March 1999) 461–471] in time varying channel environments. At a Doppler frequency of 100 Hz and bit error rates (BER) of 10 - 4 , signal-to-noise power ratio ( E b / N 0 ) gains of about 2.5 dB are achieved relative to the conventional channel tracking method [Y.G. Li, N. Seshadri, S. Ariyavisitakul, Channel estimation for OFDM systems with transmitter diversity in mobile wireless channels, IEEE J. Sel. Areas Commun. 17 (March 1999) 461–471]. At a Doppler frequency of 200 Hz, the performance difference between the proposed method and conventional one becomes much larger.

An Efficient Design of Doubly Selective Channel Estimation for OFDM Systems

We find that placing each pilot tone in an equally spaced manner according to the conventional placement scheme is not suitable for doubly selective channel estimation. In this paper, we propose an efficient pilot tone placement scheme enabling accurate channel estimation in OFDM systems regardless of time variations of a channel. Since the number of channel impulse response taps to be estimated is typically much greater than the number of pilot tones, linear minimum mean square error (LMMSE) estimation schemes for time-invariant channels cannot be straightforwardly extended to doubly selective channel estimation. To overcome this problem, we propose an accurate LMMSE channel estimator that exploits a small number of pilot tones located according to the derived pilot placement. To achieve performance close to the LMMSE estimator but with lower complexity, an approximate LMMSE (ALMMSE) channel estimator is also proposed. Finally, we propose a novel iterative ALMMSE channel estimator that achieves better performance than the LMMSE and ALMMSE estimators, while having complexity in between the two.

Iterative Equalization Technique for Double-Selective Channel Estimation in OFDM Systems

In OFDM based mobile communication systems, channel variation during one symbol period introduces intercarrier interference (ICI). Conventional pilot-aided equalization mitigates the ICI at the price of band inefficiency. On the other hand, the blind or semi-blind equalization method, which utilizes the known statistic properties of the transmitted data, will raise system complexity. In this letter, without bandwidth-consuming pilots, a novel channel estimation and tracking method based on an iterative equalization technique (IET) is proposed. The proposed approach successfully achieves a good compromise between bandwidth efficiency and system complexity, and its validity is demonstrated by numerical simulations, especially for fast fading channel.

Efficient DFT-based channel estimation for OFDM systems on multipath channels

An improved discrete Fourier transform (DFT)-based channel estimation for orthogonal frequency division multiplexing systems is proposed. Conventional DFT-based channel estimations improve the performance by suppressing time domain noise. However, they potentially require information on channel impulse responses and may also result in mean-square error (MSE) floor due to incorrect channel information such as channel delay spread. In contrast, our purposed channel estimation can improve the performance by deciding significant channel taps adaptively without requiring any channel statistical information. Significant channel taps are detected on the basis of a predetermined threshold. The optimal threshold to reduce the MSE of the estimation is also derived, and it is confirmed by computer simulation. Simulation results demonstrate that the proposed algorithm can improve the MSE performance ~6.5 dB compared with the conventional DFT-based estimation, and the MSE floor is not observed in any channels.

Blind adaptive channel estimation in ofdm systems

We consider the problem of blind channel estimation in zero padding OFDM systems, and propose blind adaptive algorithms in order to identify the impulse response of the multipath channel. In particular, we develop RLS and LMS schemes that exhibit rapid convergence combined with low computational complexity and numerical stability. Both versions are obtained by properly modifying the orthogonal iteration method used in numerical analysis for the computation of singular vectors. With a number of simulation experiments we demonstrate the satisfactory performance of our adaptive schemes under diverse signaling conditions

Comb Type Pilot Aided Channel Estimation in OFDM Systems With Transmit Diversity

Transmit diversity can be applied to OFDM systems by adopting space time code. Since the received signal is the overlapped signals transmitted from different transmit antennas, channel estimation is a rather challenging task for space time coded OFDM (ST-OFDM) systems. Pilot structure can help the receiver to effectively separate the overlapped signals and perform accurate channel estimation. In this paper, we propose three different channel estimation algorithms based on specially designed comb type pilots inserted in frequency domain. One of our proposed algorithms is performed in frequency domain and the other two are performed in time domain. Such comb type pilot based algorithms can provide higher bandwidth efficiency than common significant-tap-catching algorithm using training block pilots. Numerical analyzes and computational simulation show that our proposed estimation schemes have the same good performance while the time domain methods have relatively simple structure.

An efficient training sequences strategy for channel estimation in OFDM systems with transmit diversity

An efficient training sequences strategy for channel estimation in OFDM systems with transmit diversity

ICI Cancellation Based Channel Estimation for OFDM Systems

This paper proposes a novel frequency-domain channel estimator which mitigates the effects of ICI by jointly finding the frequency offset and channel frequency response (CFR). A binary search algorithm is used to find the present frequency offset and CFR jointly. The variance of the jointly estimated frequency offset is found to be very close to the Cramer-Rao lower bound.

A Low-Complexity KL Expansion-Based Channel Estimator for OFDM Systems

This paper first proposes a computationally efficient, pilot-aided linear minimum mean square error (MMSE) batch channel estimation algorithm for OFDM systems in unknown wireless fading channels. The proposed approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and finds MMSE estimates of the uncorrelated KL series expansion coefficients. Based on such an expansion, no matrix inversion is required in the proposed MMSE estimator. Moreover, optimal rank reduction is achieved by exploiting the optimal truncation property of the KL expansion resulting in a smaller computational load on the estimation algorithm. The performance of the proposed approach is studied through analytical and experimental results. We then consider the stochastic Cramér-Rao bound and derive the closed-form expression for the random KL coefficients and consequently exploit the performance of the MMSE channel estimator based on the evaluation of minimum Bayesian MSE. We also analyze the effect of a modelling mismatch on the estimator performance. To further reduce the complexity, we extend the batch linear MMSE to the sequential linear MMSE estimator. With the fast convergence property and the simple structure, the sequential linear MMSE estimator provides an attractive alternative to the implementation of channel estimator.

Performance analysis of channel estimation in OFDM systems

We investigate an analysis of channel estimation using an interpolation technique in orthogonal frequency division multiplexing systems. Then a criterion for the adaptive interval of pilot subcarriers is derived. The mean-square error (mse) of comb-type estimators is dominated by the length of channel delay and the interval of pilot subcarriers. Analysis shows that the mse performance of comb-type estimators with the adequate interval of pilot subcarriers is better than that of block-type estimator for indoor channels.

Improving channel estimation in OFDM systems for sparse multipath channels

We describe an algorithm for sparse channel estimation applicable to orthogonal frequency division multiplexing systems. The proposed algorithm uses a least squares (LS) technique for channel estimation and a generalized Akaike information criterion to estimate the channel length and tap positions. This effectively reduces the signal space of the LS estimator, and hence improves the estimation performance as demonstrated using computer simulations. For example, the proposed modified LS with sparse channel-estimation algorithm has a 5-dB lower mean square error in channel estimation when compared to the conventional approach , which translates to approximately 0.5 dB improvement in signal-to-noise ratio at the receiver.

A Proof of the Identifiability of a Subspace-Based Blind Channel Estimation for OFDM Systems

Muquet et al. (2002) have proposed a subspace-based blind method for estimating the channel responses of cyclic-prefixed OFDM systems. Their proof for the channel identifiability uses the roots of channel transfer function and therefore depends on the channel order. When only an upper bound is known for the channel order, the proof fails. In this letter, a new proof for the identifiability is given which does not require knowledge of the precise channel order and can handle various choices of length of the OFDM block.

Channel estimation for OFDM with fast fading channels by modified Kalman filter

In OFDM systems, time-varying channels destroy the orthogonality between subchannels and cause interchannel interference (ICI) in conventional frequency-domain channel estimation approaches. To compensate for this ICI, we propose a new channel estimator for OFDM systems in a fast and frequency-selective Rayleigh fading channel. The proposed method is based on a new modified Kalman filter (MKF). The time-varying channel is modeled as an autoregressive (AR) process and the proposed MKF is used to estimate this AR parameter. In addition, to track the time-varying channel, a channel predictor using regression analysis and the minimum mean-squared error (MMSE) time-domain equalizer are also proposed. The simulation results show that the proposed channel estimator can effectively compensate for ICI.

Iterative Receiver for Joint Detection and Channel Estimation in OFDM Systems Under Mobile Radio Channels

In this paper, an iterative receiver for a joint data-detection and channel-estimation scheme is presented for orthogonal frequency-division multiplexing systems, which incorporates iterative decoding in the receiver. In the proposed scheme, a maximum a posteriori-based decoder and a channel estimator provide more reliable information on the coded bits for each other in an iterative manner. We first consider a practical implementation issue for the optimal minimum mean squared error two-dimensional (2-D) channel estimator as an essential element in the iterative receiver. To reduce the complexity of the 2-D estimator as suited to the iterative receiver, we focus on rigorously investigating how a separable estimator must be designed so that its structure may become asymptotically equivalent to that of the optimal 2-D estimator. Furthermore, we derive an analytical expression of the iterative process to evaluate a convergence performance as a function of the number of iterations and discuss its convergence property. Our simulation results demonstrate that the proposed iterative receiver achieves a near-ideal performance with only a few iterations under time-variant multipath fading channels.

Effects of frequency offset compensation error on channel estimation for OFDM system under mobile radio channels

In this paper, we analyze the effects of frequency offset compensation on the pilot-assisted channel estimation for the orthogonal frequency division multiplexing system under a time-variant multipath fading channel. The analysis focuses on the pilot arrangement of a pilot-assisted channel estimation scheme, in which the minimum mean-square error channel estimation is employed to exploit both time- and frequency-domain correlation characteristics of the frequency response of time-variant multipath fading channels. We also investigate the effect of the length of the training signal used for frequency offset estimation on the channel estimation and subsequently, on the bit error rate performance, subject to varying signal-to-noise power ratio under mobile radio channel. Numerical results show that the maximum allowable pilot carrier spacing in time-domain is critically affected by the frequency offset error. In addition, a proper length of the training signal must be configured to suppress the noise influence while reducing a systematic error due to the time-variant behavior of the channel.

Maximuma posteriori semi-blind channel estimation for ofdm systems operating on highly frequency and time selective channels

We propose a semi-blind block-by-block channel estimation algorithm for ofdm systems operating in highly frequency and time selective channels. This algorithm, based on the Expectation-Maximization algorithm, performs an iterative maximum a posteriori estimation of the channel. It can incorporate the coded structure of each coded block in a turbo-processing fashion to enhance channel estimation quality. Moreover, it can use the maximum a posteriori training-based channel estimation algorithm for its optimum initialization. The performance of this channel estimation algorithm is evaluated through simulation results, with and without turbo-processing and optimum initialization. It is also compared to two benchmarks based on least-square error channel estimation. Our algorithm can be potentially applied for the efficient estimation of the propagation channel in drm, dvb-t, hiper-LAN/2 and IEEE 802.11a systems.