2,432 research outputs found
Timing and Frequency Synchronization and Channel Estimation in OFDM-based Systems
Orthogonal frequency division multiplexing (OFDM) due to its appealing features, such as robustness against frequency selective fading and simple channel equalization, is
adopted in communications systems such as WLAN, WiMAX and DVB. However, OFDM systems are sensitive to synchronization errors caused by timing and frequency offsets. Besides, the OFDM receiver has to perform channel estimation for coherent detection. The goal of this thesis is to investigate new methods for timing and frequency synchronization and channel estimation in OFDM-based systems.
First, we investigate new methods for preamble-aided coarse timing estimation in OFDM systems. Two novel timing metrics using high order statistics-based correlation and differential normalization functions are proposed. The performance of the new timing metrics is evaluated using different criteria including class-separability, robustness to the carrier frequency offset, and computational complexity. It is shown that the new timing metrics can considerably increase the class-separability due to their more distinct values at correct and wrong timing instants, and thus give a significantly better detection performance than the existing timing metrics do. Furthermore, a new method for coarse estimation of the start of the frame is proposed, which remarkably reduces the probability of inter-symbol interference (ISI). The improved performances of the new schemes in multipath fading channels are shown by the probabilities of false alarm, missed-detection and ISI obtained through computer simulations. Second, a novel pilot-aided algorithm
is proposed for the detection of integer frequency offset (IFO) in OFDM systems. By transforming the IFO into two new integer parameters, the proposed method can largely reduce the number of trial values for the true IFO. The two new integer parameters are detected using two different pilot sequences, a periodic pilot sequence and an aperiodic
pilot sequence. It is shown that the new scheme can significantly reduce the computational complexity while achieving almost the same performance as the previous methods do.
Third, we propose a method for joint timing and frequency synchronization and channel estimation for OFDM systems that operate in doubly selective channels. Basis expansion
modeling (BEM) that captures the time variations of the channel is used to reduce the number of unknown channel parameters. The BEM coefficients along with the timing
and frequency offsets are estimated by using a maximum likelihood (ML) approach. An efficient algorithm is then proposed for reducing the computational complexity of the
joint estimation. The complexity of the new method is assessed in terms of the number of multiplications. The mean square estimation error of the proposed method is evaluated in comparison with previous methods, indicating a remarkable performance improvement by the new method.
Fourth, we present a new scheme for joint estimation of CFO and doubly selective channel in orthogonal frequency division multiplexing systems. In the proposed preamble-aided method, the time-varying channel is represented using BEM. CFO and BEM coefficients
are estimated using the principles of particle and Kalman filtering. The performance of the new method in multipath time-varying channels is investigated in comparison with
previous schemes. The simulation results indicate a remarkable performance improvement in terms of the mean square errors of CFO and channel estimates.
Fifth, a novel algorithm is proposed for timing and frequency synchronization and channel estimation in the uplink of orthogonal frequency division multiple access (OFDMA)
systems by considering high-mobility situations and the generalized subcarrier assignment.
By using BEM to represent a doubly selective channel, a maximum likelihood (ML) approach is proposed to jointly estimate the timing and frequency offsets of different users
as well as the BEM coefficients of the time-varying channels. A space-alternating generalized expectation-maximization algorithm is then employed to transform the maximization
problem for all users into several simpler maximization problems for each user. The computational complexity of the new timing and frequency offset estimator is analyzed and its performance in comparison with that of existing methods using the mean square error is evaluated .
Finally, two novel approaches for joint CFO and doubly selective channel estimation in the uplink of multiple-input multiple-output orthogonal frequency division multiple
access (MIMO-OFDMA) systems are presented. Considering high-mobility situations, where channels change within an OFDMA symbol interval, and the time varying nature
of CFOs, BEM is employed to represent the time variations of the channel. Two new approaches are then proposed based on Schmidt Kalman filtering (SKF). The first approach
utilizes Schmidt extended Kalman filtering for each user to estimate the CFO and BEM coefficients. The second approach uses Gaussian particle filter along with SKF to
estimate the CFO and BEM coefficients of each user. The Bayesian Cramer Rao bound is derived, and performance of the new schemes are evaluated using mean square error.
It is demonstrated that the new schemes can significantly improve the mean square error performance in comparison with that of the existing methods
Visualization on colour based flow vector of thermal image for movement detection during interactive session
Recently thermal imaging is exploited in applications such as motion and face detection. It has drawn attention many researchers to build such technology to improve lifestyle. This work proposed a technique to detect and identify a motion in sequence images for the application in security monitoring system or outdoor surveillance. Conventional system might cause false information with the present of shadow. Thus, methods employed in this work are Canny edge detector method, Lucas Kanade and Horn Shunck algorithms, to overcome the major problem when using thresholding method, which is only intensity or pixel magnitude is considered instead of relationships between the pixels. The results obtained could be observed in flow vector parameter and the segmentation colour based image for the time frame from 1 to 10 seconds. The visualization of both the parameters clarified the movement and changes of pixel intensity between two frames by the supportive colour segmentation, either in smooth or rough motion. Thus, this technique may contribute to others application such as biometrics, military system, and surveillance machine
A Novel Data-Aided Channel Estimation with Reduced Complexity for TDS-OFDM Systems
In contrast to the classical cyclic prefix (CP)-OFDM, the time domain
synchronous (TDS)-OFDM employs a known pseudo noise (PN) sequence as guard
interval (GI). Conventional channel estimation methods for TDS-OFDM are based
on the exploitation of the PN sequence and consequently suffer from intersymbol
interference (ISI). This paper proposes a novel dataaided channel estimation
method which combines the channel estimates obtained from the PN sequence and,
most importantly, additional channel estimates extracted from OFDM data
symbols. Data-aided channel estimation is carried out using the rebuilt OFDM
data symbols as virtual training sequences. In contrast to the classical turbo
channel estimation, interleaving and decoding functions are not included in the
feedback loop when rebuilding OFDM data symbols thereby reducing the
complexity. Several improved techniques are proposed to refine the data-aided
channel estimates, namely one-dimensional (1-D)/two-dimensional (2-D) moving
average and Wiener filtering. Finally, the MMSE criteria is used to obtain the
best combination results and an iterative process is proposed to progressively
refine the estimation. Both MSE and BER simulations using specifications of the
DTMB system are carried out to prove the effectiveness of the proposed
algorithm even in very harsh channel conditions such as in the single frequency
network (SFN) case
CRLBs for Pilot-Aided Channel Estimation in OFDM System under Gaussian and Non-Gaussian Mixed Noise
The determination of Cramer-Rao lower bound (CRLB) as an optimality criterion for the problem of channel estimation in wireless communication is a very important issue. Several CRLBs on channel estimation have been derived for Gaussian noise. However, a practical channel is affected by not only Gaussian background noise but also non-Gaussian noise such as impulsive interference. This paper derives the deterministic and stochastic CRLBs for Gaussian and non-Gaussian mixed noise. Due to the use of the non-parametric kernel method to build the PDF of non-Gaussian noise, the proposed CRLBs are suitable for practical channel environments with various noise distributions
Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers for WIFI, WIMAX, and Next-Generation Cellular Systems
Burts-by-burst (BbB) adaptive high-speed downlink packet access (HSDPA) style multicarrier systems are reviewed, identifying their most critical design aspects. These systems exhibit numerous attractive features, rendering them eminently eligible for employment in next-generation wireless systems. It is argued that BbB-adaptive or symbol-by-symbol adaptive orthogonal frequency division multiplex (OFDM) modems counteract the near instantaneous channel quality variations and hence attain an increased throughput or robustness in comparison to their fixed-mode counterparts. Although they act quite differently, various diversity techniques, such as Rake receivers and space-time block coding (STBC) are also capable of mitigating the channel quality variations in their effort to reduce the bit error ratio (BER), provided that the individual antenna elements experience independent fading. By contrast, in the presence of correlated fading imposed by shadowing or time-variant multiuser interference, the benefits of space-time coding erode and it is unrealistic to expect that a fixed-mode space-time coded system remains capable of maintaining a near-constant BER
Scattered Pilots and Virtual Carriers Based Frequency Offset Tracking for OFDM Systems: Algorithms, Identifiability, and Performance Analysis
In this paper, we propose a novel carrier frequency offset (CFO) tracking algorithm for orthogonal frequency division multiplexing (OFDM) systems by exploiting scattered pilot carriers and virtual carriers embedded in the existing OFDM standards. Assuming that the channel remains constant during two consecutive OFDM blocks and perfect timing, a CFO tracking algorithm is proposed using the limited number of pilot carriers in each OFDM block. Identifiability of this pilot based algorithm is fully discussed under the noise free environment, and a constellation rotation strategy is proposed to eliminate the c-ambiguity for arbitrary constellations. A weighted algorithm is then proposed by considering both scattered pilots and virtual carriers. We find that, the pilots increase the performance accuracy of the algorithm, while the virtual carriers reduce the chance of CFO outlier. Therefore, the proposed tracking algorithm is able to achieve full range CFO estimation, can be used before channel estimation, and could provide improved performance compared to existing algorithms. The asymptotic mean square error (MSE) of the proposed algorithm is derived and simulation results agree with the theoretical analysis
Nonlinear Channel Estimation for OFDM System by Complex LS-SVM under High Mobility Conditions
A nonlinear channel estimator using complex Least Square Support Vector
Machines (LS-SVM) is proposed for pilot-aided OFDM system and applied to Long
Term Evolution (LTE) downlink under high mobility conditions. The estimation
algorithm makes use of the reference signals to estimate the total frequency
response of the highly selective multipath channel in the presence of
non-Gaussian impulse noise interfering with pilot signals. Thus, the algorithm
maps trained data into a high dimensional feature space and uses the structural
risk minimization (SRM) principle to carry out the regression estimation for
the frequency response function of the highly selective channel. The
simulations show the effectiveness of the proposed method which has good
performance and high precision to track the variations of the fading channels
compared to the conventional LS method and it is robust at high speed mobility.Comment: 11 page
Decision Directed Channel Estimation Aided OFDM Employing Sample-Spaced and Fractionally-Spaced CIR Estimators
Abstract—In this letter we characterize the substantial difference between two channel estimation approaches, namely the sample-spaced (SS) and the fractionally-spaced (FS) channel impulse response (CIR) estimators. The achievable performance of decision-directed channel estimation (DDCE) methods employing both the SS- and the FS-CIR estimators is analyzed in the context of an OFDM system. The performance of the two estimation methods is compared and it is shown that the DDCE scheme employing the Projection Approximation Subspace Tracking (PAST)-aided FS-CIR estimator outperforms its SS-CIR estimator-based counterpart. Index Terms—Multiuser OFDM, decision directed channel estimation, impulse response estimation SDMA
Semiblind Channel Estimation and Data Detection for OFDM Systems With Optimal Pilot Design
This paper considers semiblind channel estimation and data detection for orthogonal frequency-division multiplexing (OFDM) over frequency-selective fading channels. We show that the samples of an OFDM symbol are jointly complex Gaussian distributed, where the mean and covariance are determined by the locations and values of fixed pilot symbols. We exploit this distribution to derive a novel maximum-likelihood (ML) semiblind gradient-descent channel estimator. By exploiting the channel impulse response (CIR) statistics, we also derive a semiblind data detector for both Rayleigh and Ricean fading channels. Furthermore, we develop an enhanced data detector, which uses the estimator error statistics to mitigate the effect of channel estimation errors. Efficient implementation of both the semiblind and the improved data detectors is provided via sphere decoding and nulling-canceling detection. We also derive the Cramér-Rao bound (CRB) and design optimal pilots by minimizing the CRB. Our proposed channel estimator and data detector exhibit high bandwidth efficiency (requiring only a few pilot symbols), achieve the CRB, and also nearly reach the performance of an ideal reference receiver
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