Download or read book Exploration of Blind Channel Estimation Using Subspace based Algorithms for Block Transmission Systems written by 方士豪 and published by . This book was released on 2012 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Generalized Subspace based Blind Channel Estimation Algorithm in MIMO Zero padded Block Transmission Systems written by 易宗陽 and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Novel Subspace based Blind Channel Estimation Algorithm in Space time Block Coded Zero padded Systems with Few Received Blocks written by 周柏夆 and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Generalized Algorithms for Subspace based Blind Channel Estimation in Space time Block Coded ZP Systems written by 游尚益 and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Subspace Based Semi Blind Channel Estimation in Uplink OFDMA Systems written by 潘俊憲 and published by . This book was released on 2008 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Blind Channel Estimation and Single user Detection for Multi carrier and Spread spectrum Systems with Transmit Diversity written by Shahrokh Nayeb Nazar and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "The application of transmit diversity techniques such as Space-Time Block Coding (STBC) to the downlink of multiuser wireless communications systems has received considerable attention. The main advantage of such an approach is its ability to provide diversity gains through the use of multiple antennas only at the transmitting side without significantly increasing the complexity at the receiving end. Among the many multiple access techniques proposed, Multi-Carrier (MC) and Direct Sequence (DS) Code Division Multiple Access (CDMA) techniques are known as the most promising candidates for future broadband mobile communication networks. In MC and DS-CDMA systems or combination thereof, employing transmit diversity, the spatial diversity gains can only be realized if the underlying channels are accurately acquired at the receiver. Furthermore, such systems suffer from high computational complexity which should be properly addressed for practical implementations. Motivated by these observations, in the first part of this dissertation, we introduce the chip-level ST block coding scheme for DS-CDMA systems. For this scheme, we address the problems of single-user detection as well as blind channel estimation, and we show that chip-level coding does not suffer from antenna order ambiguity. Moreover, we demonstrate that chip-level schemes exhibit low decoding delay and allow for the design of adaptive single-user detectors with improved short data-record performance characteristics compared to their symbol-level counterparts. In the second part of this dissertation, we present a novel transmission scheme for the downlink of MC-CDMA systems with transmit diversity that is based on chip-level Space-Frequency (SF) block coding. For this scheme, we investigate the problem of blind channel estimation when the received signal processing is done (i) pre-Fast Fourier Transform (FFT); and (ii) post-FFT. We propose two blind channel estimation algorithms based on subspace and Minimum Variance Distortionless Response (MVDR) principles. Moreover, we present an analytical performance analysis of the proposed algorithms by investigating the bias as well as the finite data record mean-square error of the channel estimates. Our analysis shows that SFBC MC-CDMA systems do not suffer from antenna order ambiguity. In addition, to benchmark the accuracy of our estimation algorithms, we derive the corresponding Cramer-Rao bounds (CRB) based on a novel approach that assumes the knowledge of only the spreading code of the desired user. Our approach has the advantage of providing lower bounds which are tighter than the CRBs with known signatures. We also study the problem of single user detection for downlink transmissions to address the issue of multiuser interference. In the case of the post-FFT approach, we take advantage of the SFBC-induced signal structure to derive linear single-user detectors with improved performance in short data-record situations. Finally, in order to address the issue of computational complexity, we exploit the structure of the covariance matrix of the received signal to simplify the computations involved in estimating the channel, and forming the detector."--
Download or read book Subspace based Blind Channel Estimation written by Wei Kang and published by . This book was released on 2003 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Blind and Semi blind Channel Estimation Under Space time Coded Transmissions written by Nejib Ammar and published by . This book was released on 2005 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Semi Blind Channel Estimation Using Second Order Statistics and Its Application to Time Reversal Space Time Block Codes written by Hemanth Mullar Srikantaiah and published by . This book was released on 2006 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adaptive Semiblind Channel Estimation for OFDM OQAM Systems written by Tianze Su and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "In this thesis, we propose and investigate novel adaptive semi-blind channel estimation algorithms for OFDM/OQAM systems. OFDM/OQAM is regarded as a promising alternative to conventional CP-OFDM for multi-carrier modulation since it can provide better spectrum efficiency, albeit at the price of increased complexity. We first formulate a general system model of an OFDM/OQAM transceiver. Based on this model, we review a recently proposed block based semi-blind channel estimation method for OFDM/OQAM systems, known as the sign covariance matrix (SCM) method. This method mainly exploits the higher-order statistical properties of the data at the receiver side but is not well-suited for applications to time-varying channels. Subsequently, to overcome the drawbacks of this block-based technique, we propose adaptive semi-blind channel estimation algorithms for application to OFDM/OQAM. The proposed algorithms consist of an adaptive SCM technique obtained through exponential recursive averaging, as well as several constant modulus algorithms (CMA) for recursive estimation. Although all the adaptive algorithms are designed to deal with time-varying channels, they can also be used for rapid channel acquisition in the case of static or slowly-varying channels. Furthermore, we explore the coherence bandwidth of the channel and make use of this concept to improve the estimation accuracy via a frequency averaging technique that can be combined with the adaptive SCM. Simulation results validate the efficacy of the proposed adaptive estimation algorithms over both time-invariant and varying channels, showing their robustness in terms of convergence speed, tracking capability and residual estimation error in steady-state. In particular, the CMA with recursive least squares (CMA-RLS) updating proves to be the most preferable due to its excellent trade-off between convergence rate and residual error level. The CMA-RLS also offers the best performance in tracking a time-varying channel. In addition, simulation experiments demonstrate the effectiveness of combining the frequency averaging technique with the proposed adaptive SCM algorithm." --
Download or read book High order Statistical Methods for Blind Channel Identification and Source Detection with Applications to Wireless Communications written by Carlos Estêvão Rolim Fernandes and published by . This book was released on 2008 with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern telecommunication systems offer services demanding very high transmission rates. Channel identification appears as a major concern in this context. Looking forward better trade-offs between the quality of information recovery and suitable bit-rates, the use of blind techniques is of great interest. Making use of the special properties of the 4th-order output cumulants, this thesis introduces new statistical signal processing tools with applications in radio-mobile communication systems. Exploiting the highly symmetrical structure of the output cumulants, we address the blind channel identification problem by introducing a multilinear model for the 4th-order output cumulant tensor, based on the Parallel Factor (Parafac) analysis. The components of the new tensor model have a Hankel structure, in the SISO case. For (memoryless) MIMO channels, redundant tensor factors are exploited in the estimation of the channel coefficients. In this context, we develop blind identification algorithms based on a single-step least squares (SSLS) minimization problem. The proposed methods fully exploit the multilinear structure of the cumulant tensor as well as its symmetries and redundancies, thus enabling us to avoid any kind of pre-processing. Indeed, the SS-LS approach induces a solution based on a sole optimisation procedure, without intermediate stages, contrary to the vast majority of methods found in the literature. Using only the 4th-order cumulants, and exploiting the Virtual Array concept, we treat the source localization problem in multiuser sensor array processing. Exploiting a particular arrangement of the cumulant tensor, an original contribution consists in providing additional virtual sensors by improving the array resolution by means of an enhanced array structure that commonly arises when using 6th-order statistics. We also consider the problem of estimating the physical parameters of a multipath MIMO communication channel. Using a fully blind approach, we first treat the multipath channel as a convolutive MIMO model and propose a new technique to estimate its coefficients. This non-parametric technique generalizes the methods formerly proposed for the SISO and (memoryless) MIMO cases. Using a tensor formalism to represent the multipath MIMO channel, we estimate the physical multipath parameters by means of a combined ALS-MUSIC technique based on subspace algorithms. Finally, we turn our attention to the problem of determining the order of FIR channels in the context of MISO systems. We introduce a complete combined procedure for the detection and estimation of frequency-selective MISO communication channels. The new algorithm successively detects the signal sources, determines the order of their individual transmission channels and estimates the associated channel coefficients using a deflationary approach.
Download or read book Batch Algorithms for Blind Channel Equalization and Blind Channel Shortening Using Convex Optimization written by Dung Huy Han and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we present novel batch algorithms to tackle the multi-path fading effect of the wireless channels using convex optimization tools. We consider two major problems: channel equalization and channel shortening. Blind channel equalization has been widely investigated in the past decade. Blind algorithms are preferred because of their ability to equalize the channel without spending extra bandwidth. Existing works have proposed various blind channel equalization costs and characterized their convergence. Most of the blind signal recovery algorithms are implemented as stochastic gradient descent based adaptive schemes making them attractive to applications where the channel is slow varying. However, existing solutions for blind channel equalization often suffer from slow convergence and require long data samples. On the other hand, packet based data transmission in many practical digital communication systems makes it attractive to develop steepest descent implementation in order to speed up convergence. We focus on developing steepest decent implementation of several well-known blind signal recovery algorithms for multi-channel equalization and source separation. Our steepest descent formulation is more amenable to additional parametric and signal subspace constraints for faster convergence and superior performance. Most of the well-known blind channel equalization algorithms are based on higher-order statistics making the corresponding cost non-linear non-convex functions of the equalizer parameters. Therefore, the steepest descent implementations often converge to local optima. We develop batch algorithms that use modern optimization tools so that the global optima can be found in polynomial time. We convert our blind costs of interest into fourth-order functions and apply a semi-definite formulation to convert them into convex optimization problems so that they can be solved globally. Our algorithms work well not only for removing multipath fading effect in channel equalization problem but also for mitigating inter-channel interference in source separation problem. Nevertheless, in practical communication systems, pilot symbols are inserted to the packet for various purposes including channel estimation and equalization. Hence, the use of the pilot in conjunction with blind algorithms is more preferred. We investigate simple and practical means for performance enhancement for equalizing wireless packet transmission bursts that rely on short sequence as equalization pilots. Utilizing both the pilot symbols and additional statistical and constellation information about user data symbols, we develop efficient means for improving the performance of linear channel equalizers. We present two convex optimization algorithms that are both effective in performance enhancement and can be solved efficiently. We also propose a fourth-order training based cost so that it can be combined with other fourth-order blind costs and be solved efficiently using semi-definite programming. The simulation results show that with the help of very few pilots, the equalization can be done under very short packet length. Many modern communication systems adopt multicarrier modulation for optimum utilization of multi-path fading channel. Under this scenario, a cyclic prefix which is not shorter than the channel length is added to enable equalization. We study the problem of channel shortening in multicarrier modulation systems when this assumption is not met. We reformulate two existing second-order statistic based methods into semidefinite programming to overcome their shortcoming of local convergence. Our batch processor is superior to the conventional stochastic gradient algorithms in terms of achievable bit rate and signal to interference and noise ratio (SINR). Addressing the shortcoming of second-order statistic based costs, we propose a new criterion for blind channel shortening based on high order statistical information. The optimization criterion can be achieved through either a gradient descent algorithm or a batch algorithm using the aforementioned convex optimization for global convergence.
Download or read book On the Performance of Subspace SIMO Blind Channel Identification Methods written by Kareem Y. Bonna and published by . This book was released on 2017 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: Channel Identification is an important part of wireless communication systems. Radio-Frequency (RF) signals are subject to reflection, refraction, and diffraction, attenuation, and other effects, that result in a distorted signal at a receiver, particularly over what are known as frequency-selective channels. Traditionally, such distortion is estimated using a ``training sequence" which is a known reference signal used to estimate, and then correct for, the distortion. However, use of training sequences is not always possible, for example in military applications where the source signal is not known, or in broadcast environments where there is a high cost of transmitting a signal. One potential solution is to estimate the channel blindly, that is, without knowledge of the transmitted signal. Blind Channel Identification (BCI) and Equalization has been a extensive topic of research since at least 1975. One strategy in Blind Channel Identification is to use the structure of the received signals in a Single Input Multiple Output (SIMO) system to estimate the channel. Research has occurred on a number of methods that exploit this in the past several decades. The subspace methods form the channel estimate in terms of a one-dimensional subspace constructed using the estimated second-order statistics of the received signals. Additionally, the use of sparsity in signal estimation has been a topic of interest as well, and has recently been used in certain cases to improve the robustness of the subspace methods in a number of works. In this thesis, the Cross-Relations and Noise-Subspace methods, both of which are SIMO BCI methods, as well as their sparse variant, are examined for a deterministic channel. The expected Normalized Projection Misalignment (NPM) is analytically approximated for all considered methods. In addition, it is compared to simulation results for a random source signal and several measured RF channels from earlier literature. Finally, the sensitivity of the sparse variant of the subspace methods as a function of the regularization parameter is studied using simulation for a set of measured RF channels from earlier literature.
Download or read book Blind Channel Estimation and Blind Block Synchronization in OFDM Systems by Repeated Use of Remodulated Received Blocks written by 黃璽軒 and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Blind Channel Estimation Using Redundant Precoding written by Borching Su and published by . This book was released on 2008 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Blind Channel Estimation for Orthogonal Space time Block Codes in MISO Systems microform written by Elzbieta Beres and published by National Library of Canada = Bibliothèque nationale du Canada. This book was released on 2004 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis presents a closed-form, blind channel estimation scheme for Alamouti's and other orthogonal STBC. Unlike other blind channel estimation algorithms used in such systems, the scheme is able to estimate the channels, to within a phase constant, in multiple-input single-output systems, i.e. systems that employ only one receive antenna. The channel matrix is estimated from the eigenvalue decomposition of the fourth order cumulant matrix of the output signal. The performance of the scheme depends partly upon the accuracy of the estimated cumulants, and thus a scheme to improve the cumulant matrix estimate is suggested. Using these improved cumulants, the algorithm performs very well in slowly changing channel conditions. A single pilot-tuple is required to correctly assign the estimated to the actual channels and to resolve the phase ambiguity common to all blind estimators. The main disadvantage of the scheme is its higher complexity related to the estimation of higher order cumulants; this complexity can be reduced by exploiting the symmetry inherent in the cumulant matrix. Furthermore, it is shown that to achieve good performance in terms of bit error rate, 1000 sample points are sufficient to estimate the cumulant matrix.
Download or read book Efficient Channel Estimation for Block Transmission Systems written by Changyong Shin and published by . This book was released on 2006 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, we present three approaches for efficient channel estimation in block transmission systems. First, to provide a bandwidth-efficient solution for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) channel estimation, we establish conditions for channel identifiability and propose a blind channel estimation method based on a subspace technique.
