Low-complexity Channel Estimation Research Articles

Low complexity channel estimation method for TDS-OFDM based Chinese DTTB system

The Chinese digital television terrestrial broadcasting (DTTB) standard uses pseudo-noise (PN) sequence as guard interval (GI) and the training sequence. This PN sequence is used to do channel estimation and synchronization in the system. The existing channel estimation methods often have to adopt iterative scheme when the length of channel impulse response (CIR) is long, which will increase the receiver complexity dramatically. In this paper, a channel estimation scheme for time domain synchronous OFDM (TDS-OFDM) systems is proposed. Interference free CIR information can be obtained by constructing special correlation windows, rather than removing interference from the time domain sequences through iteration. Moreover, the estimation can be achieved by using correlation process. Comparing to conventional schemes, the proposed algorithm greatly reduces the computational complexity. Simulation results show that the proposed method can meet the requirement of the Chinese DTTB systems. And the scheme is also suitable for other communication OFDM systems with time domain sequence headers.

Channel Estimation Scheme with Low-Complexity Discrete Cosine Transform in MIMO-OFDM System

Channel estimation is a key baseband processing task in wireless systems. Filtering or smoothing algorithms can improve the accuracy of channel estimates and the Discrete Cosine Transform (DCT) can be used for this purpose. By using the DCT, performance will be improved compared to the straight-forward approach of per subcarrier estimation (PSE). However, the complexity of the DCT is not negligible. This paper proposes a low-complexity channel estimation scheme using the DCT. Simulation results show that the performance is improved by more than 1dB compared with PSE in MIMO-OFDM system.

Synchronization, Channel Estimation, and Equalization in MB-OFDM Systems

This paper addresses preamble-based low complexity synchronization, channel estimation and equalization for Zero-padded (ZP) MB-OFDM based UWB systems. The proposed synchronization method consists of sync detection, coarse timing estimation, fine timing estimation, and oscillator frequency offset estimation. The distinctive features of MB-OFDM systems and the interplay between the timing and carrier frequency hopping at the receiver are judiciously incorporated in the proposed synchronization method. In order to apply the low complexity one-tap frequency-domain equalizer, the required circular convolution property of the received signal is obtained by means of an overlap-add method after the frequency offset compensation. The proposed low complexity channel estimator for each band is developed by first averaging the over-lapadded received preamble symbols within the same band and then applying time-domain least-squares method followed by the discrete Fourier transform. We develop an MMSE equalizer and its approximate version with low complexity. We also derive the probability density functions of the UWB channel path delays, and using them we present several optimization criteria for our proposed synchronization, channel estimation, and equalization. The effectiveness of our proposed methods and optimization criteria are confirmed by computer simulation results.

A Low-Complexity LMMSE Channel Estimation Method for OFDM-Based Cooperative Diversity Systems with Multiple Amplify-and-Forward Relays

Orthogonal frequency division multiplexing- (OFDM-) based amplify-and-forward (AF) cooperative communication is an effective way for single-antenna systems to exploit the spatial diversity gains in frequency-selective fading channels, but the receiver usually requires the knowledge of the channel state information to recover the transmitted signals. In this paper, a training-sequences-aided linear minimum mean square error (LMMSE) channel estimation method is proposed for OFDM-based cooperative diversity systems with multiple AF relays over frequency-selective fading channels. The mean square error (MSE) bound on the proposed method is derived and the optimal training scheme with respect to this bound is also given. By exploiting the optimal training scheme, an optimal low-rank LMMSE channel estimator is introduced to reduce the computational complexity of the proposed method via singular value decomposition. Furthermore, the Chu sequence is employed as the training sequence to implement the optimal training scheme with easy realization at the source terminal and reduced computational complexity at the relay terminals. The performance of the proposed low-complexity channel estimation method and the superiority of the derived optimal training scheme are verified through simulation results.

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.

Preamble Design for Multiple-Antenna OFDM

In this paper, we pursue the preamble design for multiple-antenna orthogonal frequency division multiplexing (OFDM) communications over frequency-selective channels. To reduce the overhead and minimize the peak-to-average power ratio, we propose a preamble consisting of a single constant- modulus training sequence per transmit-antenna. This proposed design is shown capable of not only achieving reliable frequency and time synchronization but also facilitating low-complexity channel estimation. Furthermore, when synchronization is perfect, it is optimal in the sense of minimizing the mean squared error of least-squares channel estimation. The performance of the proposed design is investigated via simulations and compared with a competing alternative.

Efficient MIMO channel estimation using complementary sequences

Low complexity channel estimation for single-carrier block transmission systems over multiple-input multiple-output time varying frequency-selective channels is investigated. A time slot structure that uses Golay complementary sequences with perfect periodic autocorrelations as two-sided pilot blocks is presented. Employing this strucutre, optimal least square estimate in the minimum mean square error (MMSE) sense is achieved. Furthermore, a computationally efficient algorithm which is named as fast periodic Golay correlation is proposed based on the specific generator and the properties related to circulant matrices. Finally, the simulation results show the MMSE performance of the proposed scheme and algorithm.

MIMO ISI Channel Estimation Using Uncorrelated Golay Complementary Sets of Polyphase Sequences

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this paper, optimal training sequence design for multiple-input multiple-output (MIMO) intersymbol interference channels is addressed, and several novel low-complexity channel estimators are proposed, using uncorrelated Golay complementary sets of polyphase sequences.<footnoteref refid="fnote1"/><footnote id="fnote1"> <footnotepara>A polyphase sequence is a sequence of complex numbers, each of unit magnitude.</footnotepara> </footnote> The theoretical analysis and simulation show that, when the additive noise is Gaussian, the proposed best linear unbiased estimator achieves the minimum possible classical CramÉr–Rao lower bound (CRLB) if the channel coefficients are regarded as unknown deterministics. On the other hand, the proposed linear minimum mean-square error estimator attains the minimum possible Bayesian CRLB when the underlying channel coefficients are Gaussian and independent of the additive Gaussian noise. The proposed channel estimators not only achieve the best estimation performance but can also be implemented with low complexity via DSP or application-specified integrated circuit/field programmable gate array. This has been possible due to the special structures intrinsic to uncorrelated Golay complementary sets of polyphase sequences, which make the proposed channel estimators ready to use in the practical MIMO systems. </para>

Complexity-Reduced Channel Estimation in Spatially Correlated MIMO-OFDM Systems

The performance of a MIMO-OFDM system significantly depends upon the accuracy of the channel impulse response (CIR) estimates. In the presence of correlation between the CIRs of the transmit or receive antennas, it is desirable to exploit this correlation to improve the performance of CIR estimation. In this letter, we propose a low-complexity channel estimation filter composed of four concatenated one-dimensional Wiener filters which are optimized to the channel characteristics in the time and frequency domains, and the transmit and receiver antenna front ends, respectively. Finally, the performance of the proposed scheme is verified.

Low-complexity iterative channel estimation for serially concatenated systems over frequency-nonselective Rayleigh fading channels

A low-complexity iterative maximum a posteriori (MAP) channel estimator is proposed whose complexity increases linearly with the symbol alphabet size 'M. Prediction-based MAP channel estimation is not appropriate with a high-order prediction filter or a large modulation alphabet size, since the computational complexity increases with ML , where L is the predictor order. In contrast, the proposed channel estimator has a constant number of trellis states regardless of the prediction filter order, and is shown to provide comparable error performance to the prediction-based MAP estimator

Low-Complexity Optimal Estimation of MIMO ISI Channels With Binary Training Sequences

In this letter, a novel low-complexity optimal channel estimator using uncorrelated periodic complementary sets of binary sequences is proposed for multiple-input multiple-output (MIMO) intersymbol interference (ISI) channels. The estimator is optimal since it attains the minimum possible Crameacuter-Rao lower bound (CRLB). Moreover, it can be implemented with very low complexity via ASIC/FPGA, which makes it suitable and ready for practical MIMO systems

A Novel Low Complexity Channel Estimator with Frequency Offset Resistance for CDMA

A new channel estimator that does not require a separate frequency offset estimator is proposed. The new algorithm has low complexity and low latency compared to the well-known weighted multi-slot averaging algorithm. The simulation results demonstrate the improved resistance to high Doppler frequency and high frequency offset.

Time-variant channel estimation using discrete prolate spheroidal sequences

We propose and analyze a low-complexity channel estimator for a multiuser multicarrier code division multiple access (MC-CDMA) downlink in a time-variant frequency-selective channel. MC-CDMA is based on orthogonal frequency division multiplexing (OFDM). The time-variant channel is estimated individually for every flat-fading subcarrier, assuming small intercarrier interference. The temporal variation of every subcarrier over the duration of a data block is upper bounded by the Doppler bandwidth determined by the maximum velocity of the users. Slepian showed that time-limited snapshots of bandlimited sequences span a low-dimensional subspace. This subspace is also spanned by discrete prolate spheroidal (DPS) sequences. We expand the time-variant subcarrier coefficients in terms of orthogonal DPS sequences we call Slepian basis expansion. This enables a time-variant channel description that avoids the frequency leakage effect of the Fourier basis expansion. The square bias of the Slepian basis expansion per subcarrier is three magnitudes smaller than the square bias of the Fourier basis expansion. We show simulation results for a fully loaded MC-CDMA downlink with classic linear minimum mean square error multiuser detection. The users are moving with 19.4 m/s. Using the Slepian basis expansion channel estimator and a pilot ratio of only 2%, we achieve a bit error rate performance as with perfect channel knowledge.

Channel estimation using complementary sequence pairs for UWB/OFDM systems

It is well known that time domain channel estimation can achieve better performance than frequency domain channel estimation with a time-multiplexed preamble in common OFDM systems. When it is applied to UWB/OFDM systems, however, its high complexity becomes the main obstacle because of the large number of resolvable paths. To solve this problem, a low-complexity channel estimation scheme is presented by exploiting a special construction of complementary sequence pairs.

Low complexity channel estimation for space~time coded wideband ofdm systems

In this article, channel estimation for space-time coded orthogonal-frequency division multiplexing (OFDM) systems is considered. By assuming that the channel frequency response is quasi-static over two consecutive OFDM symbols, we develop channel parameter estimators based on the use of space-time block coded (STBC) training blocks. Using an STBC training pattern, a low-rank Wiener filter-based channel estimator with a significant complexity reduction is proposed. A simplified approach for the optimal low-rank estimator is also proposed to further reduce the estimator complexity while retaining an accurate frequency domain channel estimation. Numerical results are provided to demonstrate the performance of the proposed low complexity channel estimators for space-time trellis coded OFDM systems.

Analysis of DFT-Based Channel Estimators for OFDM

In this paper we analyze the performance of three low-complexity channel estimators, based on the discrete Fourier transform (DFT), for orthogonal frequency-division multiplexing (OFDM) systems. Es...