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Adaptive Complex Interpolator for Channel Estimation in Pilot-Aided OFDM System
Abstract
In an orthogonal frequency division multiplexing system, conventional interpolation techniques cannot correctly balance performance and overhead when estimating dynamic long-delay channels in single frequency networks (SFNs). In this study, classical filter analysis and design methods are employed to derive a complex interpolator for maximizing the resistible echo delay in a channel estimator on the basis of the correlation between frequency domain interpolating and time domain windowing. The coefficient computation of the complex interpolator requires a key parameter, i.e., channel length, which is obtained in the frequency domain with a tentative estimation scheme having low implementation complexity. The proposed complex adaptive interpolator is verified in a simulated digital video broadcasting for terrestrial/handheld receiver. The simulation results indicate that the designed channel estimator can not only handle SFN echoes with more than 200 μs delay but also achieve a bit-error rate performance close to the optimum minimum mean square error method, which significantly outperforms conventional channel estimation methods, while preserving a low implementation cost in a short-delay channel.
... The adaptivity of the LPS-based CE can be provided by a real-time estimation of f d and τ max , which requires excessive signal processing. A tentative time-delay estimation method was proposed in [22] to choose an appropriate interpolator for the CE only in the frequency dimension. Different from the parametric LPS-CE, block processing algorithms in [23] were applied to the RLSand the NLMS-based adaptive interpolators, updating the coefficients only once every OFDM symbol by utilizing the time correlation of channel. ...
... By balancing A s and N f , the real coefficient can be calculated from (17). As analyzed in Section IV-A, the resistible echo delay can be expanded by the phase shift of the real coefficient [22], i.e., ...
... The iteration ofŵ[n] is realized by utilizing the BLMS algorithm, which is described as Fig. 2. In one OFDM symbol, the iteration comes to an end when all N t training pilots are utilized. Subsequently, the CE for data tone (l, k) is implemented as the 2D interpolation in (22), where the elements of are given as ...
In OFDM system, channel estimator with fixed-coefficient interpolation gives rise to significant estimation errors when the estimator mismatches the experienced time-varying channel. This paper presents a pilot-aided channel estimator adopting a double one-dimensional (1-D) polyphase subfilter structure, in which a few interpolating coefficients are applicable to all subcarriers of an OFDM symbol. By analyzing the channel interpolation for OFDM receiver, we propose a two-dimensional (2-D) adaptation scheme of the interpolating coefficient, based on a block least-mean-square algorithm, which requires none of knowledge on channel statistics. The 2-D adaptation scheme is simplified as two types of 1-D schemes respectively for the time and frequency dimensions, based on the known frequency- and time-direction interpolating coefficients. By simultaneously exploiting channel correlation in the time and frequency dimensions, the adaptive interpolators are trained to match channel properties. Furthermore, the proposed schemes of adaptive interpolation demand lower implementation cost, compared with the existing methods. Simulation results show that the adaptive interpolators converge at a high rate, and that the simplified schemes outperform the conventional methods in the high-speed mobile channel and the single-frequency-networks channel with long-delay echoes, while preserving a low implementation complexity.
... In DVB-T2 System, for bandwidth utilization pilot-data ration is improved in case of worst wireless channelling where number of spectral sub-channels is used using independent localized number of antenna configuration. In 2D-OFDM, many researchers has proved that pilot aided channel estimation can be improved by changing pilot allocation in given pilot-data ration framing without increasing payload of pilot [4][5]. To inline this, in our research we have proposed the 5 different proposed block and comb pilot patterns model and tested with different antenna configuration using Rayleigh fading channel. ...
... Then collected signal handover to adder with frame selection & allocation to get required signal. Based on literature [4], a typical antenna configuration is used to verify the capacity of proposed pilot aided frame structure which is modelled through 3D-OFDM. The transmitter side, different Nth antenna structure with same characteristics is used. ...
This paper aims, a 3D-Pilot Aided Multi-Input Multi-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) Channel Estimation (CE) for Digital Video Broadcasting -T2 (DVB-T2) for the 5 different proposed block and comb pilot patterns model and performed on different antenna configuration. The effects of multi-transceiver antenna on channel estimation are addressed with different pilot position in frequency, time and the vertical direction of spatial domain framing. This paper first focus on designing of 5-different proposed spatial correlated pilot pattern model with optimization of pilot overhead. Then it demonstrates the performance comparison of Least Square (LS) & Linear Minimum Mean Square Error (LMMSE), two linear channel estimators for 3D-Pilot Aided patterns on different antenna configurations in terms of Bit Error Rate. The simulation results are shown for Rayleigh fading noise channel environments. Also, 3×4 MIMO configuration is recommended as the most suitable configuration in this noise channel environments. © 2017 Institute of Advanced Engineering and Science. All rights reserved.
... Mar. 14,2017. Sheet 12 of 12 US 9,596,119 B2 i 1. ...
There is provided a computer-implemented method of estimating transmitted signals in a communication system, the signals being transmitted by a transmitter to a receiver over
a communication channel having a channel response, the method comprising estimating the transmitted signals based on generated trial sequences minimizing the channel
response between adjacent received signals. There is also provided a receiver, a signal detector device and a communication system adapted to estimated transmitted signals in
a communication system by generating trial sequences and determining the generated trial sequences minimizing the channel response between adjacent received signals. The
present invention is particularly adapted for OFDM communication systems.
... Deep learning has attained remarkable progress in recent years and has been widely applied to computer vision [1], natural language processing [2], autonomous driving [3], and other fields, with impressive results. Although communication is still developing at a high speed [4][5] [6], deep learning technology has been adopted and it is expected to achieve new breakthroughs. Data are the fuel for deep learning. ...
The use of deep neural network for decoding error control code will encounter two problems, namely, the high-precision requirements of the error control code and the complexity of the neural network due to the long code. In this paper, a deep neural network decoder is proposed to solve the decoding problem of long code by using the nature of convolutional code window decoding. A deep neural network decoder is utilized as a weak classifier, and an integrated decoder is proposed to improve the decoding performance greatly. The Viterbi decoder is improved by approximately 2 db at a bit error rate of level 5. Both decoder methods proposed in this paper can be decoded in parallel and are suitable for high-bit-rate applications. This study reveals that the accuracy of neural networks can reach level 8 more.
This paper presents a novel efficient receiver design for wireless communication systems that incorporate orthogonal frequency division multiplexing (OFDM) transmission. The proposed receiver does not require channel estimation or equalization to perform coherent data detection. Instead, channel estimation, equalization, and data detection are combined into a single operation, and hence, the detector performs a direct data detector
($D^{3}$)
. The
$D^{3}$
is applied to key practical wireless systems such as the Long Term Evolution (LTE) and the New Radio (NR) of the fifth-generation (5G) system. The performance of the proposed
$D^{3}$
is thoroughly analyzed theoretically in terms of bit error rate (BER), where closed-form accurate approximations are derived for several cases of interest, and validated by Monte Carlo simulations. Moreover, extensive complexity analysis are performed to evaluate the system suitability for implementation. The obtained theoretical and simulation results demonstrate that the BER of the proposed
$D^{3}$
is only 3 dB away from coherent detectors with perfect knowledge of the channel state information (CSI) in flat and frequency-selective fading channels for a wide range of signal-to-noise ratios (SNRs). If CSI is not known perfectly, then
$D^{3}$
outperforms the coherent detector substantially, particularly at high SNRs with linear interpolation. The computational complexity of
$D^{3}$
depends on the length of the sequence to be detected, nevertheless, a significant complexity reduction can be achieved using the Viterbi algorithm.
This correspondence presents the channel estimation and long-range prediction technique for adaptive-orthogonal-frequency-division-multiplexing (AOFDM) system. The efficient channel loading is accomplished by feeding the accurately predicted channel-state-information (CSI) back to transmitter. The frequency-selective wireless fading channel is modelled as a tapped-delay-line-filter governed by a first-order autoregressive (AR1) process; and an adaptive channel estimator based on the generalised-variable-step-size least-mean-square (GVSS-LMS) algorithm tracks AR1 correlation coefficient. To compensate for the signal fading due to channel state variations, a modified-Kalman-filter (MKF)-based channel estimator is utilised. In addition, channel tracking is also performed for predicting future CSI at receiver, based on the numeric-variable-forgetting-factor recursive-least-squares (NVFF-RLS) algorithm. Subsequently, adaptive bit allocation for AOFDM system is employed by using predicted CSI at transmitter. Here, the proposed combination of GVSS-LMS and MKF algorithms for robust channel estimation and the NVFF-RLS algorithm for efficient channel prediction is incorporated. The performance validation of presented method is carried out by using different channel realisations through simulation, and also by comparing it with fixed step-size LMS, MKF and fixed forgetting-factor RLS algorithm based conventional techniques. Eventually, the reliable performance of underlying AOFDM system can be achieved in terms of the lower mean squared estimation/prediction errors and alleviated symbol error rate.
According to the wideband channel with the sparse characteristics of time frequency doubly selective fading, and the sparse energy mainly concentrating on a few clusters, this paper presents the compressed sensing algorithm, that is cluster-regularized adaptive matching pursuit(CRAMP) based on cluster characteristics. Through analyzing the time frequency doubly selective channel in orthogonal frequency division multiplexing(OFDM) system, and using the time domain and frequency domain correlation in channel, the algorithm uses the 2D-DFT as the observation matrix in compressed sensing channel. And then utilizing clustering characteristics, it estimates for each cluster rather than estimates for each element in channel. The simulation results show that the CRAMP algorithm in channel reconstruction accuracy and bit error ratio(BER) respects are superior to conventional compressed sensing ones.
Modern communication systems are based on orthogonal frequency division multiplexing (OFDM). They are designed for dealing with frequency selective channels considering invariance within the time-span of an OFDM symbol. However, this assumption is no longer valid when the transceivers operate in higher mobility scenarios or higher carrier frequencies. This condition provokes inter-carrier interference (ICI) that greatly degrades system performance. State-of-the-art approaches that satisfactorily mitigate this problem have a complexity of O(N3), which makes them infeasible with current technology. In this paper, a novel channel estimation algorithm to cope with this problem is presented. It is based on a subspace approach using two-dimensional Prolate functions, achieving a complexity of only O(N2). It depends only on the maximum delay spread and maximum Doppler spread while being robust in the sense that it is independent of the particular channel scattering function. Performance analysis of the proposed algorithm is presented. Simulation results under the WiMAX standard show that this algorithm improves previous results, achieving a bit error rate (BER) close to the one obtained with perfect channel state information (CSI) in very-fast transceiver mobility, as high as 874 Km/h over a 2.4 Ghz carrier frequency.
A family of iterative receivers is evaluated in terms of complexity and performance for the case of an uplink multi-user (MU) multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system. The transmission over block fading channels is considered. The analyzed class of receivers is performing channel estimation inside the iterative detection loop, which has been shown to improve estimation performance. As part of our results we illustrate the ability of this type of receiver to reduce the required amount of pilot symbols. A remaining question to ask is which combinations of estimation and detection algorithms that provide the best trade-off between performance and complexity. We address this issue by considering MU detectors and channel estimators, with varying algorithm complexity. For MU detection, two algorithms based on parallel interference cancellation (PIC) are considered and compared with the optimal symbol-wise maximum a-posteriori probability (MAP) detector. For channel estimation, an algorithm performing joint minimum-mean-square-error (MMSE) estimation is considered along with a low complexity replica making use of a Krylov subspace method. An estimator based on the space alternating generalized expectation-maximization (SAGE) algorithm is also considered. Our results show that low-complexity algorithms provide the best tradeoff, even though more receiver iterations are needed to reach a desired performance.
In this paper, we propose a low-complexity iterative joint channel estimation, detection and decoding technique for doubly selective channels. The key to the proposed technique is a segment-by-segment processing strategy under the assumption that the channel is approximately static within a short segment of a data block. Through a virtual zero-padding technique, the proposed segment-by-segment equalization approach inherits the low-complexity advantage of the conventional frequency domain equalization (FDE), but does not need the assistance of guard interval (for cyclic-prefixing or zero-padding), thereby avoiding the spectral and power overheads. Furthermore, we develop a low-complexity bidirectional channel estimator, where the Gaussian message passing (GMP) technique is used to exploit the channel correlation information, and the intermediate channel estimation results in the iterative process are employed to perform inter-tap interference cancellation. Simulation results demonstrate the effectiveness of the proposed detection and channel estimation algorithms.
A linear channel estimator for multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) systems, based on a two-dimensional Slepian expansion, is presented. The estimator is meant to be part of an iterative receiver. We consider both estimation based on pilots only and on pilots and data, the latter considered as a reference for the case when feedback from decoders is exploited. Performances are analyzed via computer simulations comparing the relative minimum square error (RMMSE) of an analogous one-dimensional estimator and the proposed extension.
In this paper, we presents a novel synchronizer dealing with carrier frequency offset (CFO), sampling frequency offset (SFO), as well as frame timing offset (FTO) in TDS-OFDM receiver. The proposed schemes are based on tracking the output waveform of a composite PN-correlator (CPC), which provides sufficient correlative gains to detect its peaks even in the presence of large CFOs. From the correlation peaks, we can extract useful information for estimating the synchronization offsets. CFO is recovered by a multi-stage CPC scheme, of which the parameters are adjustable for meeting the system's demands on the tracking range and accuracy. According to the inter-frame variations of correlation waveform, we estimate SFO for a large scale and correct SFO through an interpolator. Meanwhile, frame timing is investigated in this paper, and the analysis indicates a very fast and robust timing scheme is possible for TDS-OFDM receiver. The developed synchronizer is quite robust against a large CFO even in very adverse fading channels, and it is shown by computer simulation that the residual synchronization error has little effect on the performance of TDS-OFDM receiver.
Compressed sensing (CS) has recently been applied for pilot-aided sparse channel estimation. However, the design of the pilot placement has not been considered. In this letter, we pro- pose a scheme using the modified discrete stochastic approxima- tiontooptimizethepilotplacementinOFDMsystems.Thechannel data is employed to offline search the near-optimal pilot placement before the transmission. Meanwhile wea lso get ac riterion to select CS algorithms based on the mean squared error (MSE) minimiza- tion. Simulations using a sparse wireless channel model have val- idated the effectiveness of the proposed scheme, which is demon- strated to be much faster convergent and more efficient than the exhaustive search. It has been shown that substantial performance improvement can be achieved for OMP and YALL1 based channel estimation, where YALL1 is preferred.
In orthogonal frequency division multiplexing (OFDM) systems, two-dimensional (both time and frequency) minimum mean square error (2D-MMSE) channel estimation is optimum. However, accurate channel statistics are required to realize it, which are often unavailable in practice. In contrast, two-dimensional adaptive channel estimation based on a two-dimensional least mean square (2D-LMS) algorithm does not require any channel statistics, and at the same time can make full use of the time and frequency-domain correlations of the frequency response of time-varying dispersive fading channels. In this paper, we further study two-dimensional adaptive channel estimation in OFDM systems. We derive two-dimensional normalized least mean square (2D-NLMS) algorithm and find that the 2D-LMS algorithm with the optimum step-size parameter is just its special case. Furthermore, a parallel 2D-(N)LMS channel estimation scheme is proposed to solve the realtime realization problem due to high computational complexity encountered by two-dimensional adaptive channel estimation. Finally, we apply two-dimensional adaptive channel estimation to multiple-input multiple-output (MIMO) OFDM systems.
Accurate channel estimation is necessary for coherent detection of the orthogonal frequency division multiplexing (OFDM) signals. This paper studies pilot-assisted adaptive interpolation channel estimation for different pilot arrangements: time-multiplexed pilot, frequency-multiplexed pilot and scattered pilot. Interpolation filter tap weights are adaptively updated according to changes of the propagation channels by using the normalized least mean square (NLMS) algorithm. The average bit error rate (BER) performance in a doubly (frequency and time)-selective Rayleigh fading channel is evaluated by computer simulation. It is confirmed that the scattered pilot with two-dimensional adaptive interpolation channel estimation provides overall a good BER performance, compared to the time (or frequency)-multiplexed pilot case with one-dimensional adaptive interpolation channel estimation.
In this paper, we investigate several efficient interpolation techniques for pilot symbol assisted channel estimation in OFDM. The interpolation methods studied include two dimensional (2-D) separable lowpass sine interpolator with Kaiser window, 2-D separable Deslauriers-Dubuc (DD) interpolation and 2-D discrete Fourier transform (DFT) based lowpass interpolation. The performances of these interpolators are compared with those of the well known minimum mean-square error (MMSE) 2-D separable Wiener filter and the perfect channel state information. It is shown that the Kaiser window based interpolator and DD interpolation are simple, robust, and outperform the 2-D DFT based lowpass interpolation as well as several existing interpolation methods proposed in the literature. These two schemes are suitable candidates for use in 1-D and 2-D channel estimation
As an alternative to the traditional cyclic prefixed OFDM (CP-OFDM) technology, time-domain synchronous OFDM (TDS-OFDM) provides higher spectrum efficiency due to no pilot in the transmitted signal. However, the pilot-Aided channel estimation techniques in CP-OFDM cannot be applied to TDS-OFDM. In this paper, channel impulse responses are estimated in time domain based on the linear correlation between the received samples and the locally generated PN sequence. The iterative threshold detection (ITD), as well as the combination with decision feedback equalization (DFE), is proposed to improve the precision of channel estimation. It is shown by simulation that the proposed algorithm, ITD combined with DFE (ITD-DFE), performs very well even in multipath environments with long- delay and large-amplitude echoes.
Orthogonal frequency-division multiplexing (OFDM) modulation is a
promising technique for achieving the high bit rates required for a
wireless multimedia service. Without channel estimation and tracking,
OFDM systems have to use differential phase-shift keying (DPSK), which
has a 3-dB signal-to-noise ratio (SNR) loss compared with coherent
phase-shift keying (PSK). To improve the performance of OFDM systems by
using coherent PSK, we investigate robust channel estimation for OFDM
systems. We derive a minimum mean-square-error (MMSE) channel estimator,
which makes full use of the time- and frequency-domain correlations of
the frequency response of time-varying dispersive fading channels. Since
the channel statistics are usually unknown, we also analyze the mismatch
of the estimator-to-channel statistics and propose a robust channel
estimator that is insensitive to the channel statistics. The robust
channel estimator can significantly improve the performance of OFDM
systems in a rapid dispersive fading channel
We present and analyze low-rank channel estimators for orthogonal
frequency-division multiplexing (OFDM) systems using the frequency
correlation of the channel. Low-rank approximations based on the
discrete Fourier transform (DFT) have been proposed, but these suffer
from poor performance when the channel is not sample spaced. We apply
the theory of optimal rank-reduction to linear minimum mean-squared
error (LMMSE) estimators and show that these estimators, when using a
fixed design, are robust to changes in channel correlation and
signal-to-noise ratio (SNR). The performance is presented in terms of
uncoded symbol-error rate (SER) for a system using 16-quadrature
amplitude modulation (QAM)
Channel estimation techniques for OFDM systems based on a pilot arrangement are investigated. Channel estimation based on a comb type pilot arrangement is studied through different algorithms for both estimating the channel at pilot frequencies and interpolating the channel. Channel estimation at pilot frequencies is based on LS and LMS methods while channel interpolation is done using linear interpolation, second order interpolation, low-pass interpolation, spline cubic interpolation, and time domain interpolation. Time-domain interpolation is obtained by passing to the time domain by means of IDFT (inverse discrete Fourier transform), zero padding and going back to the frequency domain by DFT (discrete Fourier transform). In addition, channel estimation based on a block type pilot arrangement is performed by sending pilots in every sub-channel and using this estimation for a specific number of following symbols. We have also implemented a decision feedback equalizer for all sub-channels followed by periodic block-type pilots. We have compared the performances of all schemes by measuring bit error rates with 16QAM, QPSK, DQPSK and BPSK as modulation schemes, and multipath Rayleigh fading and AR based fading channels as channel models.
A time-domain based channel estimation for OFDM system with
pilot-data multiplexed scheme is investigated. As an approximation to
linear minimum mean square estimator (LMMSE), a time-domain based
channel estimation is proposed where intra-symbol time-averaging and
most significant channel taps selection are applied. The relation and
differences of the proposed method to DFT-based LMMSE methods are
discussed. The performances of the proposed method, DFT-based LMMSE
method and the methods of Chini, Wu, El-Tanany and Mahmoud (see IEEE
Trans. on Broadcasting, vol.44, no.1, p.2-11, 1998) and of Yeh and Lin
(see IEEE Trans. on Broadcasting, vol.45, no.4, p.400-409, 1999) are
evaluated in multipath fading channels. The simulation results show that
proposed method achieves almost the same performance as DFT-based LMMSE
method and better BER performance than the other methods while keeping
less complexity
As an alternative to the traditional pilot-aided orthogonal frequency division multiplexing (OFDM), the time-domain pseudonoise (PN)-padded OFDM provides a higher spectral efficiency. However, the carrier frequency offset (CFO) attenuates peaks of the conventional PN correlation output, which limits the CFO estimation range of the OFDM synchronizer. An improved correlation is proposed in this letter to remove the CFO-induced amplitude attenuation of correlation peaks. For a synchronizer adopting the designed correlator, a larger range of CFO acquisition is obtained through using wider correlation windows with a smaller interval between them. The proposed method of CFO acquisition is verified in a digital terrestrial multimedia broadcast receiver, in which the synchronizer is able to acquire CFOs up to kHz in the DVB-T F1 channel. Furthermore, the acquisition range can be expanded in more favorable channels.
This paper addresses training-sequence-based joint timing synchronization and channel estimation for orthogonal frequency division multiplexing (OFDM) systems. The proposed approach consists of three stages. First, a coarse timing offset estimate is obtained. Then an advanced timing, relative timing indices, and channel impulse response estimates are obtained by maximum-likelihood estimation based on a sliding observation vector. Finally, the fine time adjustment based on the minimum mean squared error criterion is performed. The simulation results show that the proposed approach has excellent performance of timing synchronization in several channel models at low signal-to-noise ratio (SNR) which is smaller than 1dB. Moreover, for a low-density parity-check coded 1x2 single-input multiple-output OFDM system with maximum ratio combining, zero bit-error-rate is achievable using our proposed approach when SNR exceeds 1dB.
This paper presents a low-complexity interpolation-based channel estimator suited for scattered-pilot OFDM systems in fast-fading channel. The proposed estimator consists of two interpolators: one RLS interpolator for estimating scattered subcarriers along the time direction and another raised-cosine (RC) interpolator for estimating data subcarriers along the frequency direction. A low-complexity architecture tailored for DVB-T/H is demonstrated as an exemplar. Simulation results show that the proposed channel estimator has comparable accuracy with almost order-of-magnitude lower complexity than conventional adaptive channel estimators.
Channel estimation and equalization techniques are crucial for the ubiquitous broadcasting systems. Conventional receivers for most broadcasting or wireless standards preset the channel length to the maximal expected duration of the channel impulse response for the adopted channel estimation and equalization algorithms. The excessive channel length often significantly increases the implementational complexity of the wireless receivers and leads to the redundant information which would induce the additional estimation errors. Moreover, such a scheme does not allow the dynamic memory allocation for variable channel lengths. This could further increase the power consumption and reduce the battery life of a mobile device. The knowledge of the actual channel length would, in principle, help the system designers decrease the complexity of the channel estimators using maximum likelihood (ML) and minimum-mean-square-error (MMSE) algorithms. In this paper, we address this important channel length estimation problem and propose a novel autocorrelation-based algorithm to estimate the channel length without the need of pilots or training sequence. The associated threshold for the channel length estimation depends on the sample size, the signal-to-noise ratio and the leading/last channel coefficients. In addition, we provide the mean-square analysis on the effectiveness of the proposed non-pilot-aided channel length estimator through Monte Carlo simulations.
During digital television (TV) transition, analog signal disturbs digital terrestrial television (DTT) transmission in an area where a simulcast service is available. In the TDS-OFDM- based DTTB system, the receiver is extremely sensitive to the co-channel interference (CCI) introduced by analog TV service. The CCI not only generates strong narrow-band interference in the frequency domain, but also greatly degrades the estimation of time-domain demodulating parameters in TDS-OFDM receiver. In this paper, a method of the time-domain autocorrelation of the received DTT signal is developed to detect the CCI, and it utilizes the line synchronization mechanism of analog TV signals. Also an IIR filter, setting one notch at each carrier of analog TV signal, is designed to reject the CCI in the time domain. From the filtered signal, synchronization errors and channel responses can be estimated by means of conventional algorithms for TDS-OFDM receiver. A DTMB receiver is designed to verify the proposed solutions and its robustness against the CCI is enforced about 20 dB in terms of signal interference ratio (SIR).
This paper proposes to implement an improved orthogonal frequency division multiplexing (OFDM) receiver by utilizing a channel impulse response (CIR)-based synchronization and sparse equalization for DVB-T2 system operating in both the single-input single-output (SISO) and multi-input single-output (MISO) transmission modes. First, the proposed OFDM receiver performs a pilot-aided CIR estimation after a coarse symbol timing recovery (STR). Then, the proposed CIR-based fine STR compensates for a false symbol timing offset (STO). In particular, the fine STR resolves an ambiguity effect of CIR, which is the main problem caused by a false coarse STO in exploiting the CIR. Upon the completion of the fine synchronization, the proposed CIR-based sparse equalization is performed in order to minimize the noise and interference effects by shifting or selecting a basic frequency interpolation (FI) filter according to an echo delay (phase) or maximum delay spread, respectively. Performance evaluations are accomplished in large delay spread channels in which the maximum delay spread is less or longer than a guard interval (GI). It is shown that the proposed receiver is not only capable of estimating the fine STO but also minimizing effectively the noise effects. In particular, the performance gain in a single pre-echo channel being longer than GI is remarkable as compared with a conventional receiver.
In an OFDM system using pilots for channel estimation, time interpolation among pilots of different OFDM symbols is commonly used to improve the estimate. The estimated channel impulse response may be also windowed to further reduce noise and disturbances. However, for a transmission over a time-varying channel, suboptimal time interpolation, implemented with a filter having only a few taps not matched to the maximum Doppler frequency, degrades channel estimation. In this paper we provide an analysis of the effects of pilot time interpolation over time-varying channels. We show in particular that suboptimal time interpolation yields aliases in the estimated channel impulse response and we derive a closed-form expression of the aliases¿ variance. As aliases can lead to an erroneous estimate of channel length and consequent errors in windowing, we propose a technique to detect aliases and correct the channel length estimate. Parameters of the detection techniques are optimized by an analysis that provides closed-form expressions of the false alarm and miss detection probabilities. Numerical results show the merits of the proposed techniques in a mobile transmission of the terrestrial digital video broadcasting standard (DVB-T).
For pilot-aided channel estimation in orthogonal frequency-division multiplexing (OFDM) systems, adaptive algorithms enable tracking of a time-varying channel. Using several subcarriers for the update step in the adaptive algorithm, i.e., performing block processing, improves the robustness and convergence speed of the adaptation. To decrease the complexity of these algorithms, simplified versions are deduced as well as versions with real-valued filters. In the latter case the number of required arithmetic operations can be reduced significantly not only in the adaptive algorithm but also in the filtering process itself, which represents a dominating part regarding the complexity due to the huge amount of subcarriers of practical OFDM transmission schemes. Simulation results show that gains w.r.t. the convergence behavior can be achieved by real-valued filters compared to complex-valued filters - even in scenarios where real-valued filters are theoretically suboptimum.
This paper proposes two low-complexity two-dimensional channel estimators for MIMO-OFDM systems derived from a joint time–frequency channel estimator. The estimators exploit both time and frequency correlations of the wireless channel via use of Slepian-basis expansions. The computational saving comes from replacing a two-dimensional Slepian-basis expansion with two serially concatenated one-dimensional Slepian-basis expansions. Performance in terms of normalized mean square error (NMSE) vs. signal-to-noise ratio (SNR) is analyzed via numerical simulations and compared with the original estimator. The analysis of the performance takes into account the impact of both system and channel parameters. The estimators are finally tested when used within the loop of an iterative receiver for MIMO-OFDM systems.
In this paper, we first show equivalence of OFDM channel estimation using time-domain windowing and using frequency-domain interpolation. Based on this equivalence, a new frequency-domain channel interpolator featuring the advantage of time-domain channel impulse response windowing is proposed. Furthermore, the proposed raised-cosine channel interpolator can adaptively adjust its coefficients to accommodate various channel power delay profiles. Both theoretical and simulation results verify that the proposed interpolator achieves more accurate channel estimation performance than other existing solutions.
The potential of pilot-symbol-aided channel estimation in two
dimensions are explored. In order to procure this goal, the discrete
shift-variant 2-D Wiener filter is derived and analyzed given an
arbitrary sampling grid, an arbitrary (but possibly optimized) selection
of observations, and the possibility of model mismatch. Filtering in two
dimensions is revealed to outperform filtering in just one dimension
with respect to overhead and mean-square error performance. However, two
cascaded orthogonal 1-D filters are simpler to implement and shown to be
virtually as good as true 2-D filters
A new approach to low-complexity channel estimation in orthogonal-frequency division multiplexing (OFDM) systems is proposed. A low-rank approximation is applied to a linear minimum mean-squared error (LMMSE) estimator that uses the frequency correlation of the channel. By using the singular value decomposition (SVD) an optimal low-rank estimator is derived, where performance is essentially preserved-even for low computational complexities. A fixed estimator, with nominal values for channel correlation and signal-to-noise ratio (SNR), is analysed. Analytical mean-squared error (MSE) and symbol-error rates (SER) are presented for a 16-QAM OFDM system
Multiple-input-multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems have recently attracted substantial research interest. However, compared to single-input-single-output (SISO) systems, channel estimation in the MIMO scenario becomes more challenging, owing to the increased number of independent transmitter-receiver links to be estimated. In the context of the Bell layered space-time architecture (BLAST) or space division multiple access (SDMA) multi-user MIMO OFDM systems, none of the known channel estimation techniques allows the number of users to be higher than the number of receiver antennas, which is often referred to as a "rank-deficient" scenario, owing to the constraint imposed by the rank of the MIMO channel matrix. Against this background, in this paper we propose a new genetic algorithm (GA) assisted iterative joint channel estimation and multi-user detection (GA-JCEMUD) approach for multi-user MIMO SDMA-OFDM systems, which provides an effective solution to the multi-user MIMO channel estimation problem in the above-mentioned rank-deficient scenario. Furthermore, the GAs invoked in the data detection literature can only provide a hard-decision output for the forward error correction (FEC) or channel decoder, which inevitably limits the system's achievable performance. By contrast, our proposed GA is capable of providing "soft" outputs and hence it becomes capable of achieving an improved performance with the aid of FEC decoders. A range of simulation results are provided to demonstrate the superiority of the proposed scheme.
In this paper, we investigate pilot-symbol-aided parameter
estimation for orthogonal frequency division multiplexing (OFDM)
systems. We first derive a minimum mean-square error (MMSE)
pilot-symbol-aided parameter estimator. Then, we discuss a robust
implementation of the pilot-symbol-aided estimator that is insensitive
to channel statistics. From the simulation results, the required
signal-to-noise ratios (SNRs) for a 10% word error rate (WER) are 6.8 dB
and 7.3 dB for the typical urban (TU) channels with 40 Hz and 200 Hz
Doppler frequencies, respectively, and they are 8 dB and 8.3 dB for the
hilly-terrain (HT) channels with 40 Hz and 200 Hz Doppler frequencies,
respectively. Compared with the decision-directed parameter estimator,
the pilot-symbol-aided estimator is highly robust to Doppler frequency
for dispersive fading channels with noise impairment even though it has
some performance degradation for systems with lower Doppler frequencies
A comparative investigation on various channel estimation algorithms for OFDM system in the mobile communication environment is presented and analyzed in terms of computational complexity, mean square error, and bit error rate in this paper. As a result, Wiener filter estimation shows the best error performance. Concerning the computational complexity as well as the performance, however, the piecewise linear estimator is considered as a proper choice when the reference signal spacing is relatively narrow. And the cubic-spline estimator is a good alternative to the Wiener filter estimation if the reference signal spacing is wider than the coherent bandwidth of transmission channel.
An investigation into time-domain approach for OFDM channel estimation
- Y Zhao
- A Huang
Adaptive pilot symbol aided channel estimation for OFDM systems
- S Sand
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